Articles | Volume 12, issue 11
https://doi.org/10.5194/gmd-12-4803-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-4803-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
21 Nov 2019
Model evaluation paper |
| 21 Nov 2019
| 21 Nov 2019
Impact of model improvements on 80 m wind speeds during the second Wind Forecast Improvement Project (WFIP2)
Cooperative Institute for Research in
Environmental Sciences, Boulder, CO, USA
National Oceanic and Atmospheric Administration/Earth Systems Research Laboratory, Boulder, CO, USA
Irina V. Djalalova
Cooperative Institute for Research in
Environmental Sciences, Boulder, CO, USA
National Oceanic and Atmospheric Administration/Earth Systems Research Laboratory, Boulder, CO, USA
James M. Wilczak
National Oceanic and Atmospheric Administration/Earth Systems Research Laboratory, Boulder, CO, USA
Joseph B. Olson
Cooperative Institute for Research in
Environmental Sciences, Boulder, CO, USA
National Oceanic and Atmospheric Administration/Earth Systems Research Laboratory, Boulder, CO, USA
Jaymes S. Kenyon
Cooperative Institute for Research in
Environmental Sciences, Boulder, CO, USA
National Oceanic and Atmospheric Administration/Earth Systems Research Laboratory, Boulder, CO, USA
Aditya Choukulkar
Cooperative Institute for Research in
Environmental Sciences, Boulder, CO, USA
National Oceanic and Atmospheric Administration/Earth Systems Research Laboratory, Boulder, CO, USA
Vibrant Clean Energy, Boulder, CO, USA
Larry K. Berg
Pacific Northwest National Laboratory, Richland, WA, USA
Harindra J. S. Fernando
Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN, USA
Eric P. Grimit
Vaisala Inc., Seattle, WA, USA
Raghavendra Krishnamurthy
Pacific Northwest National Laboratory, Richland, WA, USA
Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN, USA
Julie K. Lundquist
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USA
National Renewable Energy Laboratory, Golden, CO, USA
Paytsar Muradyan
Argonne National Laboratory, Lemont, IL, USA
Mikhail Pekour
Pacific Northwest National Laboratory, Richland, WA, USA
Yelena Pichugina
Cooperative Institute for Research in
Environmental Sciences, Boulder, CO, USA
National Oceanic and Atmospheric Administration/Earth Systems Research Laboratory, Boulder, CO, USA
Mark T. Stoelinga
Vaisala Inc., Seattle, WA, USA
David D. Turner
National Oceanic and Atmospheric Administration/Earth Systems Research Laboratory, Boulder, CO, USA
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Lindsay M. Sheridan, Raghu Krishnamurthy, Gabriel García Medina, Brian J. Gaudet, William I. Gustafson Jr., Alicia M. Mahon, William J. Shaw, Rob K. Newsom, Mikhail Pekour, and Zhaoqing Yang
Wind Energ. Sci., 7, 2059–2084, https://doi.org/10.5194/wes-7-2059-2022, https://doi.org/10.5194/wes-7-2059-2022, 2022
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Heather Guy, David D. Turner, Von P. Walden, Ian M. Brooks, and Ryan R. Neely
Atmos. Meas. Tech., 15, 5095–5115, https://doi.org/10.5194/amt-15-5095-2022, https://doi.org/10.5194/amt-15-5095-2022, 2022
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Atmos. Meas. Tech., 15, 4585–4622, https://doi.org/10.5194/amt-15-4585-2022, https://doi.org/10.5194/amt-15-4585-2022, 2022
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Earth Syst. Sci. Data, 14, 3423–3438, https://doi.org/10.5194/essd-14-3423-2022, https://doi.org/10.5194/essd-14-3423-2022, 2022
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This work focuses on an expanding number of data sets observed using ARM TBS (133 flights) and UAS (seven flights) platforms by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research, such as the aerosol–cloud interaction in the boundary layer.
James B. Duncan Jr., Laura Bianco, Bianca Adler, Tyler Bell, Irina V. Djalalova, Laura Riihimaki, Joseph Sedlar, Elizabeth N. Smith, David D. Turner, Timothy J. Wagner, and James M. Wilczak
Atmos. Meas. Tech., 15, 2479–2502, https://doi.org/10.5194/amt-15-2479-2022, https://doi.org/10.5194/amt-15-2479-2022, 2022
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In this study, several ground-based remote sensing instruments are used to estimate the height of the convective planetary boundary layer, and their performance is compared against independent boundary layer depth estimates obtained from radiosondes launched as part of the CHEESEHEAD19 field campaign. The impact of clouds (particularly boundary layer clouds) on the estimation of the boundary layer depth is also investigated.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Lindsay M. Sheridan, Caleb Phillips, Alice C. Orrell, Larry K. Berg, Heidi Tinnesand, Raj K. Rai, Sagi Zisman, Dmitry Duplyakin, and Julia E. Flaherty
Wind Energ. Sci., 7, 659–676, https://doi.org/10.5194/wes-7-659-2022, https://doi.org/10.5194/wes-7-659-2022, 2022
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The small wind community relies on simplified wind models and energy production simulation tools to obtain energy generation expectations. We gathered actual wind speed and turbine production data across the US to test the accuracy of models and tools for small wind turbines. This study provides small wind installers and owners with the error metrics and sources of error associated with using models and tools to make performance estimates, empowering them to adjust expectations accordingly.
Vincent Pronk, Nicola Bodini, Mike Optis, Julie K. Lundquist, Patrick Moriarty, Caroline Draxl, Avi Purkayastha, and Ethan Young
Wind Energ. Sci., 7, 487–504, https://doi.org/10.5194/wes-7-487-2022, https://doi.org/10.5194/wes-7-487-2022, 2022
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In this paper, we have assessed to which extent mesoscale numerical weather prediction models are more accurate than state-of-the-art reanalysis products in characterizing the wind resource at heights of interest for wind energy. The conclusions of our work will be of primary importance to the wind industry for recommending the best data sources for wind resource modeling.
Adam S. Wise, James M. T. Neher, Robert S. Arthur, Jeffrey D. Mirocha, Julie K. Lundquist, and Fotini K. Chow
Wind Energ. Sci., 7, 367–386, https://doi.org/10.5194/wes-7-367-2022, https://doi.org/10.5194/wes-7-367-2022, 2022
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Wind turbine wake behavior in hilly terrain depends on various atmospheric conditions. We modeled a wind turbine located on top of a ridge in Portugal during typical nighttime and daytime atmospheric conditions and validated these model results with observational data. During nighttime conditions, the wake deflected downwards following the terrain. During daytime conditions, the wake deflected upwards. These results can provide insight into wind turbine siting and operation in hilly regions.
Irina V. Djalalova, David D. Turner, Laura Bianco, James M. Wilczak, James Duncan, Bianca Adler, and Daniel Gottas
Atmos. Meas. Tech., 15, 521–537, https://doi.org/10.5194/amt-15-521-2022, https://doi.org/10.5194/amt-15-521-2022, 2022
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In this paper we investigate the synergy obtained by combining active (radio acoustic sounding system – RASS) and passive (microwave radiometer) remote sensing observations to obtain temperature vertical profiles through a radiative transfer model. Inclusion of the RASS observations leads to more accurate temperature profiles from the surface to 5 km above ground, well above the maximum height of the RASS observations themselves (2000 m), when compared to the microwave radiometer used alone.
Ye Liu, Yun Qian, and Larry K. Berg
Wind Energ. Sci., 7, 37–51, https://doi.org/10.5194/wes-7-37-2022, https://doi.org/10.5194/wes-7-37-2022, 2022
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Uncertainties in initial conditions (ICs) decrease the accuracy of wind speed forecasts. We find that IC uncertainties can alter wind speed by modulating the weather system. IC uncertainties in local thermal gradient and large-scale circulation jointly contribute to wind speed forecast uncertainties. Wind forecast accuracy in the Columbia River Basin is confined by initial uncertainties in a few specific regions, providing useful information for more intense measurement and modeling studies.
Fan Mei, Steven Spielman, Susanne Hering, Jian Wang, Mikhail S. Pekour, Gregory Lewis, Beat Schmid, Jason Tomlinson, and Maynard Havlicek
Atmos. Meas. Tech., 14, 7329–7340, https://doi.org/10.5194/amt-14-7329-2021, https://doi.org/10.5194/amt-14-7329-2021, 2021
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This study focuses on understanding a versatile water-based condensation particle counter (vWCPC 3789) performance under various ambient pressure conditions (500–1000 hPa). A vWCPC has the advantage of avoiding health and safety concerns. However, its performance characterization under low pressure is rare but crucial for ensuring successful airborne deployment. This paper provides advanced knowledge of operating a vWCPC 3789 to capture the spatial variations of atmospheric aerosols.
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
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We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Hannah Livingston, Nicola Bodini, and Julie K. Lundquist
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-68, https://doi.org/10.5194/wes-2021-68, 2021
Preprint withdrawn
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In this paper, we assess whether hub-height turbulence can easily be quantified from either other hub-height variables or ground-level measurements in complex terrain. We find a large variability across the three considered locations when trying to model hub-height turbulence intensity and turbulence kinetic energy. Our results highlight the nonlinear and complex nature of atmospheric turbulence, so that more powerful techniques should instead be recommended to model hub-height turbulence.
Miguel Sanchez Gomez, Julie K. Lundquist, Petra M. Klein, and Tyler M. Bell
Earth Syst. Sci. Data, 13, 3539–3549, https://doi.org/10.5194/essd-13-3539-2021, https://doi.org/10.5194/essd-13-3539-2021, 2021
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In July 2018, the International Society for Atmospheric Research using Remotely-piloted Aircraft (ISARRA) hosted a flight week to demonstrate unmanned aircraft systems' capabilities in sampling the atmospheric boundary layer. Three Doppler lidars were deployed during this week-long experiment. We use data from these lidars to estimate turbulence dissipation rate. We observe large temporal variability and significant differences in dissipation for lidars with different sampling techniques.
Miguel Sanchez Gomez, Julie K. Lundquist, Jeffrey D. Mirocha, Robert S. Arthur, and Domingo Muñoz-Esparza
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-57, https://doi.org/10.5194/wes-2021-57, 2021
Revised manuscript not accepted
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Winds decelerate upstream of a wind plant as turbines obstruct and extract energy from the flow. This effect is known as wind plant blockage. We assess how atmospheric stability modifies the upstream wind plant blockage. We find stronger stability amplifies this effect. We also explore different approaches to quantifying blockage from field-like observations. We find different methodologies may induce errors of the same order of magnitude as the blockage-induced velocity deficits.
Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, https://doi.org/10.5194/amt-14-4403-2021, 2021
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Planetary boundary layer (PBL) height is a critical parameter in atmospheric models. Continuous PBL height measurements from remote sensing measurements are important to understand various boundary layer mechanisms, especially during daytime and evening transition periods. Due to several limitations in existing methodologies to detect PBL height from a Doppler lidar, in this study, a machine learning (ML) approach is tested. The ML model is observed to improve the accuracy by over 50 %.
Maria A. Zawadowicz, Kaitlyn Suski, Jiumeng Liu, Mikhail Pekour, Jerome Fast, Fan Mei, Arthur J. Sedlacek, Stephen Springston, Yang Wang, Rahul A. Zaveri, Robert Wood, Jian Wang, and John E. Shilling
Atmos. Chem. Phys., 21, 7983–8002, https://doi.org/10.5194/acp-21-7983-2021, https://doi.org/10.5194/acp-21-7983-2021, 2021
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This paper describes the results of a recent field campaign in the eastern North Atlantic, where two mass spectrometers were deployed aboard a research aircraft to measure the chemistry of aerosols and trace gases. Very clean conditions were found, dominated by local sulfate-rich acidic aerosol and very aged organics. Evidence of
long-range transport of aerosols from the continents was also identified.
David D. Turner and Ulrich Löhnert
Atmos. Meas. Tech., 14, 3033–3048, https://doi.org/10.5194/amt-14-3033-2021, https://doi.org/10.5194/amt-14-3033-2021, 2021
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Temperature and humidity profiles in the lowest couple of kilometers near the surface are very important for many applications. Passive spectral radiometers are commercially available, and observations from these instruments have been used to get these profiles. However, new active lidar systems are able to measure partial profiles of water vapor. This paper investigates how the derived profiles of water vapor and temperature are improved when the active and passive observations are combined.
Alex Rybchuk, Mike Optis, Julie K. Lundquist, Michael Rossol, and Walt Musial
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-50, https://doi.org/10.5194/gmd-2021-50, 2021
Preprint withdrawn
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We characterize the wind resource off the coast of California by conducting simulations with the Weather Research and Forecasting (WRF) model between 2000 and 2019. We compare newly simulated winds to those from the WIND Toolkit. The newly simulated winds are substantially stronger, particularly in the late summer. We also conduct a refined analysis at three areas that are being considered for commercial development, finding that stronger winds translates to substantially more power here.
Tyler M. Bell, Petra M. Klein, Julie K. Lundquist, and Sean Waugh
Earth Syst. Sci. Data, 13, 1041–1051, https://doi.org/10.5194/essd-13-1041-2021, https://doi.org/10.5194/essd-13-1041-2021, 2021
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In July 2018, numerous weather sensing remotely piloted aircraft systems (RPASs) were flown in a flight week called Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). As part of LAPSE-RATE, ground-based remote and in situ systems were also deployed to supplement and enhance observations from the RPASs. These instruments include multiple Doppler lidars, thermodynamic profilers, and radiosondes. This paper describes data from these systems.
Daniel Vassallo, Raghavendra Krishnamurthy, and Harindra J. S. Fernando
Wind Energ. Sci., 6, 295–309, https://doi.org/10.5194/wes-6-295-2021, https://doi.org/10.5194/wes-6-295-2021, 2021
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Machine learning is quickly becoming a commonly used technique for wind speed and power forecasting and is especially useful when combined with other forecasting techniques. This study utilizes a popular machine learning algorithm, random forest, in an attempt to predict the forecasting error of a statistical forecasting model. Various atmospheric characteristics are used as random forest inputs in an effort to discern the most useful atmospheric information for this purpose.
Caroline Draxl, Rochelle P. Worsnop, Geng Xia, Yelena Pichugina, Duli Chand, Julie K. Lundquist, Justin Sharp, Garrett Wedam, James M. Wilczak, and Larry K. Berg
Wind Energ. Sci., 6, 45–60, https://doi.org/10.5194/wes-6-45-2021, https://doi.org/10.5194/wes-6-45-2021, 2021
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Mountain waves can create oscillations in low-level wind speeds and subsequently in the power output of wind plants. We document such oscillations by analyzing sodar and lidar observations, nacelle wind speeds, power observations, and Weather Research and Forecasting model simulations. This research describes how mountain waves form in the Columbia River basin and affect wind energy production and their impact on operational forecasting, wind plant layout, and integration of power into the grid.
Jessica M. Tomaszewski and Julie K. Lundquist
Wind Energ. Sci., 6, 1–13, https://doi.org/10.5194/wes-6-1-2021, https://doi.org/10.5194/wes-6-1-2021, 2021
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We use a mesoscale numerical weather prediction model to conduct a case study of a thunderstorm outflow passing over and interacting with a wind farm. These simulations and observations from a nearby radar and surface station confirm that interactions with the wind farm cause the outflow to reduce its speed by over 20 km h−1, with brief but significant impacts on the local meteorology, including temperature, moisture, and winds. Precipitation accumulation across the region was unaffected.
Gijs de Boer, Adam Houston, Jamey Jacob, Phillip B. Chilson, Suzanne W. Smith, Brian Argrow, Dale Lawrence, Jack Elston, David Brus, Osku Kemppinen, Petra Klein, Julie K. Lundquist, Sean Waugh, Sean C. C. Bailey, Amy Frazier, Michael P. Sama, Christopher Crick, David Schmale III, James Pinto, Elizabeth A. Pillar-Little, Victoria Natalie, and Anders Jensen
Earth Syst. Sci. Data, 12, 3357–3366, https://doi.org/10.5194/essd-12-3357-2020, https://doi.org/10.5194/essd-12-3357-2020, 2020
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This paper provides an overview of the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field campaign, held from 14 to 20 July 2018. This field campaign spanned a 1-week deployment to Colorado's San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. This overview paper provides insight into the campaign for a special issue focused on the datasets collected during LAPSE-RATE.
Antonia Englberger, Julie K. Lundquist, and Andreas Dörnbrack
Wind Energ. Sci., 5, 1623–1644, https://doi.org/10.5194/wes-5-1623-2020, https://doi.org/10.5194/wes-5-1623-2020, 2020
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Wind turbines rotate clockwise. The rotational direction of the rotor interacts with the nighttime veering wind, resulting in a rotational-direction impact on the wake. In the case of counterclockwise-rotating blades the streamwise velocity in the wake is larger in the Northern Hemisphere whereas it is smaller in the Southern Hemisphere.
Antonia Englberger, Andreas Dörnbrack, and Julie K. Lundquist
Wind Energ. Sci., 5, 1359–1374, https://doi.org/10.5194/wes-5-1359-2020, https://doi.org/10.5194/wes-5-1359-2020, 2020
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At night, the wind direction often changes with height, and this veer affects structures near the surface like wind turbines. Wind turbines usually rotate clockwise, but this rotational direction interacts with veer to impact the flow field behind a wind turbine. If another turbine is located downwind, the direction of the upwind turbine's rotation will affect the downwind turbine.
Nicola Bodini, Julie K. Lundquist, and Mike Optis
Geosci. Model Dev., 13, 4271–4285, https://doi.org/10.5194/gmd-13-4271-2020, https://doi.org/10.5194/gmd-13-4271-2020, 2020
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While turbulence dissipation rate (ε) is an essential parameter for the prediction of wind speed, its current representation in weather prediction models is inaccurate, especially in complex terrain. In this study, we leverage the potential of machine-learning techniques to provide a more accurate representation of turbulence dissipation rate. Our results show a 30 % reduction in the average error compared to the current model representation of ε and a total elimination of its average bias.
Patrick Murphy, Julie K. Lundquist, and Paul Fleming
Wind Energ. Sci., 5, 1169–1190, https://doi.org/10.5194/wes-5-1169-2020, https://doi.org/10.5194/wes-5-1169-2020, 2020
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We present and evaluate an improved method for predicting wind turbine power production based on measurements of the wind speed and direction profile across the rotor disk for a wind turbine in complex terrain. By comparing predictions to actual power production from a utility-scale wind turbine, we show this method is more accurate than methods based on hub-height wind speed or surface-based atmospheric characterization.
Daniel Vassallo, Raghavendra Krishnamurthy, and Harindra J. S. Fernando
Wind Energ. Sci., 5, 959–975, https://doi.org/10.5194/wes-5-959-2020, https://doi.org/10.5194/wes-5-959-2020, 2020
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Model error and uncertainty is a challenge in the wind energy industry, potentially leading to mischaracterization of millions of dollars' worth of wind resource. This paper combines meteorological knowledge with machine learning techniques, specifically artificial neural networks (ANNs), to better extrapolate wind speeds. It is found that ANNs can reduce power-law extrapolation error by up to 52 % while simultaneously reducing uncertainty. A test case is shown to help decipher the ANN results.
Paul Fleming, Jennifer King, Eric Simley, Jason Roadman, Andrew Scholbrock, Patrick Murphy, Julie K. Lundquist, Patrick Moriarty, Katherine Fleming, Jeroen van Dam, Christopher Bay, Rafael Mudafort, David Jager, Jason Skopek, Michael Scott, Brady Ryan, Charles Guernsey, and Dan Brake
Wind Energ. Sci., 5, 945–958, https://doi.org/10.5194/wes-5-945-2020, https://doi.org/10.5194/wes-5-945-2020, 2020
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This paper presents the results of a field campaign investigating the performance of wake steering applied at a section of a commercial wind farm. It is the second phase of the study for which the first phase was reported in a companion paper (https://wes.copernicus.org/articles/4/273/2019/). The authors implemented wake steering on two turbine pairs and compared results with the latest FLORIS model of wake steering, showing good agreement in overall energy increase.
Jessica M. Tomaszewski and Julie K. Lundquist
Geosci. Model Dev., 13, 2645–2662, https://doi.org/10.5194/gmd-13-2645-2020, https://doi.org/10.5194/gmd-13-2645-2020, 2020
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Wind farms can briefly impact the nearby environment by reducing wind speeds and mixing warmer air down to the surface. The wind farm parameterization (WFP) in the Weather Research and Forecasting (WRF) model is a tool that numerically simulates wind farms and these meteorological impacts. We highlight the importance of choice in model settings and find that sufficiently fine vertical and horizontal grids with turbine turbulence are needed to accurately simulate wind farm meteorological impacts.
Erin A. Riley, Jessica M. Kleiss, Laura D. Riihimaki, Charles N. Long, Larry K. Berg, and Evgueni Kassianov
Atmos. Meas. Tech., 13, 2099–2117, https://doi.org/10.5194/amt-13-2099-2020, https://doi.org/10.5194/amt-13-2099-2020, 2020
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Discrepancies in hourly shallow cumuli cover estimates can be substantial. Instrument detection differences contribute to long-term bias in shallow cumuli cover estimates, whereas narrow field-of-view configurations impact measurement uncertainty as averaging time decreases. A new tool is introduced to visually assess both impacts on sub-hourly cloud cover estimates. Accurate shallow cumuli cover estimation is needed for model–observation comparisons and studying cloud-surface interactions.
Philipp Gasch, Andreas Wieser, Julie K. Lundquist, and Norbert Kalthoff
Atmos. Meas. Tech., 13, 1609–1631, https://doi.org/10.5194/amt-13-1609-2020, https://doi.org/10.5194/amt-13-1609-2020, 2020
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We present an airborne Doppler lidar simulator (ADLS) based on high-resolution atmospheric wind fields (LES). The ADLS is used to evaluate the retrieval accuracy of airborne wind profiling under turbulent, inhomogeneous wind field conditions inside the boundary layer. With the ADLS, the error due to the violation of the wind field homogeneity assumption used for retrieval can be revealed. For the conditions considered, flow inhomogeneities exert a dominant influence on wind profiling error.
Fan Mei, Jian Wang, Jennifer M. Comstock, Ralf Weigel, Martina Krämer, Christoph Mahnke, John E. Shilling, Johannes Schneider, Christiane Schulz, Charles N. Long, Manfred Wendisch, Luiz A. T. Machado, Beat Schmid, Trismono Krisna, Mikhail Pekour, John Hubbe, Andreas Giez, Bernadett Weinzierl, Martin Zoeger, Mira L. Pöhlker, Hans Schlager, Micael A. Cecchini, Meinrat O. Andreae, Scot T. Martin, Suzane S. de Sá, Jiwen Fan, Jason Tomlinson, Stephen Springston, Ulrich Pöschl, Paulo Artaxo, Christopher Pöhlker, Thomas Klimach, Andreas Minikin, Armin Afchine, and Stephan Borrmann
Atmos. Meas. Tech., 13, 661–684, https://doi.org/10.5194/amt-13-661-2020, https://doi.org/10.5194/amt-13-661-2020, 2020
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In 2014, the US DOE G1 aircraft and the German HALO aircraft overflew the Amazon basin to study how aerosols influence cloud cycles under a clean condition and around a tropical megacity. This paper describes how to meaningfully compare similar measurements from two research aircraft and identify the potential measurement issue. We also discuss the uncertainty range for each measurement for further usage in model evaluation and satellite data validation.
Simon K. Siedersleben, Andreas Platis, Julie K. Lundquist, Bughsin Djath, Astrid Lampert, Konrad Bärfuss, Beatriz Cañadillas, Johannes Schulz-Stellenfleth, Jens Bange, Tom Neumann, and Stefan Emeis
Geosci. Model Dev., 13, 249–268, https://doi.org/10.5194/gmd-13-249-2020, https://doi.org/10.5194/gmd-13-249-2020, 2020
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Wind farms affect local weather and microclimates. These effects can be simulated in weather models, usually by removing momentum at the location of the wind farm. Some debate exists whether additional turbulence should be added to capture the enhanced mixing of wind farms. By comparing simulations to measurements from airborne campaigns near offshore wind farms, we show that additional turbulence is necessary. Without added turbulence, the mixing is underestimated during stable conditions.
Miguel Sanchez Gomez and Julie K. Lundquist
Wind Energ. Sci., 5, 125–139, https://doi.org/10.5194/wes-5-125-2020, https://doi.org/10.5194/wes-5-125-2020, 2020
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Wind turbine performance depends on various atmospheric conditions. We quantified the effect of the change in wind direction and speed with height (direction and speed wind shear) on turbine power at a wind farm in Iowa. Turbine performance was affected during large direction shear and small speed shear conditions and favored for the opposite scenarios. These effects make direction shear significant when analyzing the influence of different atmospheric variables on turbine operation.
Norman Wildmann, Nicola Bodini, Julie K. Lundquist, Ludovic Bariteau, and Johannes Wagner
Atmos. Meas. Tech., 12, 6401–6423, https://doi.org/10.5194/amt-12-6401-2019, https://doi.org/10.5194/amt-12-6401-2019, 2019
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Turbulence is the variation of wind velocity on short timescales. In this study we introduce a new method to measure turbulence in a two-dimensionial plane with lidar instruments. The method allows for the detection and quantification of subareas of distinct turbulence conditions in the observed plane. We compare the results to point and profile measurements with more established instruments. It is shown that turbulence below low-level jets and in wind turbine wakes can be investigated this way.
Paul Fleming, Jennifer King, Katherine Dykes, Eric Simley, Jason Roadman, Andrew Scholbrock, Patrick Murphy, Julie K. Lundquist, Patrick Moriarty, Katherine Fleming, Jeroen van Dam, Christopher Bay, Rafael Mudafort, Hector Lopez, Jason Skopek, Michael Scott, Brady Ryan, Charles Guernsey, and Dan Brake
Wind Energ. Sci., 4, 273–285, https://doi.org/10.5194/wes-4-273-2019, https://doi.org/10.5194/wes-4-273-2019, 2019
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Wake steering is a form of wind farm control in which turbines use yaw offsets to affect wakes in order to yield an increase in total energy production. In this first phase of a study of wake steering at a commercial wind farm, two turbines implement a schedule of offsets. For two closely spaced turbines, an approximate 14 % increase in energy was measured on the downstream turbine over a 10° sector, with a 4 % increase in energy production of the combined turbine pair.
Nicola Bodini, Julie K. Lundquist, Raghavendra Krishnamurthy, Mikhail Pekour, Larry K. Berg, and Aditya Choukulkar
Atmos. Chem. Phys., 19, 4367–4382, https://doi.org/10.5194/acp-19-4367-2019, https://doi.org/10.5194/acp-19-4367-2019, 2019
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To improve the parameterization of the turbulence dissipation rate (ε) in numerical weather prediction models, we have assessed its temporal and spatial variability at various scales in the Columbia River Gorge during the WFIP2 field experiment. The turbulence dissipation rate shows large spatial variability, even at the microscale, with larger values in sites located downwind of complex orographic structures or in wind farm wakes. Distinct diurnal and seasonal cycles in ε have also been found.
Robert Menke, Nikola Vasiljević, Jakob Mann, and Julie K. Lundquist
Atmos. Chem. Phys., 19, 2713–2723, https://doi.org/10.5194/acp-19-2713-2019, https://doi.org/10.5194/acp-19-2713-2019, 2019
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This research utilizes several months of lidar measurements from the Perdigão 2017 campaign to investigate flow recirculation zones that occur at the two parallel ridges at the measurement site in Portugal. We found that recirculation occurs in over 50 % of the time when the wind direction is perpendicular to the direction of the ridges. Moreover, we show three-dimensional changes of the zones along the ridges and the implications of recirculation on wind turbines that are operating downstream.
Joseph C. Y. Lee, M. Jason Fields, and Julie K. Lundquist
Wind Energ. Sci., 3, 845–868, https://doi.org/10.5194/wes-3-845-2018, https://doi.org/10.5194/wes-3-845-2018, 2018
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To find the ideal way to quantify long-term wind-speed variability, we compare 27 metrics using 37 years of wind and energy data. We conclude that the robust coefficient of variation can effectively assess and correlate wind-speed and energy-production variabilities. We derive adequate results via monthly mean data, whereas uncertainty arises in interannual variability calculations. We find that reliable estimates of wind-speed variability require 10 ± 3 years of monthly mean wind data.
Jessica M. Tomaszewski, Julie K. Lundquist, Matthew J. Churchfield, and Patrick J. Moriarty
Wind Energ. Sci., 3, 833–843, https://doi.org/10.5194/wes-3-833-2018, https://doi.org/10.5194/wes-3-833-2018, 2018
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Wind energy development has increased rapidly in rural locations of the United States, areas that also serve general aviation airports. The spinning rotor of a wind turbine creates an area of increased turbulence, and we question if this turbulent air could pose rolling hazards for light aircraft flying behind turbines. We analyze high-resolution simulations of wind flowing past a turbine to quantify the rolling risk and find that wind turbines pose no significant roll hazards to light aircraft.
Jeffrey D. Mirocha, Matthew J. Churchfield, Domingo Muñoz-Esparza, Raj K. Rai, Yan Feng, Branko Kosović, Sue Ellen Haupt, Barbara Brown, Brandon L. Ennis, Caroline Draxl, Javier Sanz Rodrigo, William J. Shaw, Larry K. Berg, Patrick J. Moriarty, Rodman R. Linn, Veerabhadra R. Kotamarthi, Ramesh Balakrishnan, Joel W. Cline, Michael C. Robinson, and Shreyas Ananthan
Wind Energ. Sci., 3, 589–613, https://doi.org/10.5194/wes-3-589-2018, https://doi.org/10.5194/wes-3-589-2018, 2018
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This paper validates the use of idealized large-eddy simulations with periodic lateral boundary conditions to provide boundary-layer flow quantities of interest for wind energy applications. Sensitivities to model formulation, forcing parameter values, and grid configurations were also examined, both to ascertain the robustness of the technique and to characterize inherent uncertainties, as required for the evaluation of more general wind plant flow simulation approaches under development.
John E. Shilling, Mikhail S. Pekour, Edward C. Fortner, Paulo Artaxo, Suzane de Sá, John M. Hubbe, Karla M. Longo, Luiz A. T. Machado, Scot T. Martin, Stephen R. Springston, Jason Tomlinson, and Jian Wang
Atmos. Chem. Phys., 18, 10773–10797, https://doi.org/10.5194/acp-18-10773-2018, https://doi.org/10.5194/acp-18-10773-2018, 2018
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We report aircraft observations of the evolution of organic aerosol in the Manaus urban plume as it ages. We observe dynamic changes in the organic aerosol. The mean carbon oxidation state of the OA increases from −0.6 to −0.45. Hydrocarbon-like organic aerosol (HOA) mass is lost and is balanced out by formation of oxygenated organic aerosol (OOA). Because HOA loss is balanced by OOA formation, we observe little change in the net Δorg / ΔCO values with aging.
Nicola Bodini, Julie K. Lundquist, and Rob K. Newsom
Atmos. Meas. Tech., 11, 4291–4308, https://doi.org/10.5194/amt-11-4291-2018, https://doi.org/10.5194/amt-11-4291-2018, 2018
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Turbulence within the atmospheric boundary layer is critically important to transfer heat, momentum, and moisture. Currently, improved turbulence parametrizations are crucially needed to refine the accuracy of model results at fine horizontal scales. In this study, we calculate turbulence dissipation rate from sonic anemometers and discuss a novel approach to derive turbulence dissipation from profiling lidar measurements.
Rochelle P. Worsnop, Michael Scheuerer, Thomas M. Hamill, and Julie K. Lundquist
Wind Energ. Sci., 3, 371–393, https://doi.org/10.5194/wes-3-371-2018, https://doi.org/10.5194/wes-3-371-2018, 2018
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This paper uses four statistical methods to generate probabilistic wind speed and power ramp forecasts from the High Resolution Rapid Refresh model. The results show that these methods can provide necessary uncertainty information of power ramp forecasts. These probabilistic forecasts can aid in decisions regarding power production and grid integration of wind power.
Luca Delle Monache, Stefano Alessandrini, Irina Djalalova, James Wilczak, and Jason C. Knievel
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-1214, https://doi.org/10.5194/acp-2017-1214, 2018
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The authors demonstrate how the analog ensemble (AnEn) can efficiently generate deterministic and probabilistic forecasts of air quality. The method avoids the complexity and real-time computational expense of dynamical (i.e., model-based) ensembles. AnEn deterministic predictions have lower errors and are better correlated with observations. Probabilistic forecasts from AnEn are statistically consistent, reliable, and sharp, and they quantify the uncertainty of the underlying prediction.
Dean B. Atkinson, Mikhail Pekour, Duli Chand, James G. Radney, Katheryn R. Kolesar, Qi Zhang, Ari Setyan, Norman T. O'Neill, and Christopher D. Cappa
Atmos. Chem. Phys., 18, 5499–5514, https://doi.org/10.5194/acp-18-5499-2018, https://doi.org/10.5194/acp-18-5499-2018, 2018
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We use in situ measurements of particle light extinction to assess the performance of a typical aerosol remote retrieval method. The retrieved fine-mode fraction of extinction, a property commonly used to characterize the anthropogenic influence on the aerosol optical depth, compares well with the in situ measurements as does the retrieved effective fine-mode radius, which characterizes the average size of the particles that contribute most to scattering.
Claire Pettersen, Ralf Bennartz, Aronne J. Merrelli, Matthew D. Shupe, David D. Turner, and Von P. Walden
Atmos. Chem. Phys., 18, 4715–4735, https://doi.org/10.5194/acp-18-4715-2018, https://doi.org/10.5194/acp-18-4715-2018, 2018
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A novel method for classifying Arctic precipitation using ground based remote sensors is presented. The classification reveals two distinct, primary regimes of precipitation over the central Greenland Ice Sheet: snowfall coupled to deep, fully glaciated ice clouds or to shallow, mixed-phase clouds. The ice clouds are associated with low-pressure storm systems from the southeast, while the mixed-phase clouds slowly propagate from the southwest along a quiescent flow.
Robert A. Stillwell, Ryan R. Neely III, Jeffrey P. Thayer, Matthew D. Shupe, and David D. Turner
Atmos. Meas. Tech., 11, 835–859, https://doi.org/10.5194/amt-11-835-2018, https://doi.org/10.5194/amt-11-835-2018, 2018
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This work focuses on making unambiguous measurements of Arctic cloud phase and assessing those measurements within the context of cloud radiative effects. It is found that effects related to lidar data recording systems can cause retrieval ambiguities that alter the interpretation of cloud phase in as much as 30 % of the available data. This misinterpretation of cloud-phase data can cause a misinterpretation of the effect of cloud phase on the surface radiation budget by as much as 10 to 30 %.
Joseph C. Y. Lee and Julie K. Lundquist
Geosci. Model Dev., 10, 4229–4244, https://doi.org/10.5194/gmd-10-4229-2017, https://doi.org/10.5194/gmd-10-4229-2017, 2017
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We evaluate the wind farm parameterization (WFP) in the Weather Research and Forecasting (WRF) model, a powerful tool to simulate wind farms and their meteorological impacts numerically. In our case study, the WFP simulations with fine vertical grid resolution are skilful in matching the observed winds and the actual power productions. Moreover, the WFP tends to underestimate power in windy conditions. We also illustrate that the modeled wind speed is a critical determinant to improve the WFP.
Louis Marelle, Jean-Christophe Raut, Kathy S. Law, Larry K. Berg, Jerome D. Fast, Richard C. Easter, Manish Shrivastava, and Jennie L. Thomas
Geosci. Model Dev., 10, 3661–3677, https://doi.org/10.5194/gmd-10-3661-2017, https://doi.org/10.5194/gmd-10-3661-2017, 2017
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We develop the WRF-Chem 3.5.1 model to improve simulations of aerosols and ozone in the Arctic. Both species are important air pollutants and climate forcers, but models often struggle to reproduce observations in the Arctic. Our developments concern pollutant emissions, mixing, chemistry, and removal, including processes related to snow and sea ice. The effect of these changes are quantitatively validated against observations, showing significant improvements compared to the original model.
Jean-Christophe Raut, Louis Marelle, Jerome D. Fast, Jennie L. Thomas, Bernadett Weinzierl, Katharine S. Law, Larry K. Berg, Anke Roiger, Richard C. Easter, Katharina Heimerl, Tatsuo Onishi, Julien Delanoë, and Hans Schlager
Atmos. Chem. Phys., 17, 10969–10995, https://doi.org/10.5194/acp-17-10969-2017, https://doi.org/10.5194/acp-17-10969-2017, 2017
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We study the cross-polar transport of plumes from Siberian fires to the Arctic in summer, both in terms of transport pathways and efficiency of deposition processes. Those plumes containing soot may originate from anthropogenic and biomass burning sources in mid-latitude regions and may impact the Arctic climate by depositing on snow and ice surfaces. We evaluate the role of the respective source contributions, investigate the transport of plumes and treat pathway-dependent removal of particles.
Timothy A. Bonin, Aditya Choukulkar, W. Alan Brewer, Scott P. Sandberg, Ann M. Weickmann, Yelena L. Pichugina, Robert M. Banta, Steven P. Oncley, and Daniel E. Wolfe
Atmos. Meas. Tech., 10, 3021–3039, https://doi.org/10.5194/amt-10-3021-2017, https://doi.org/10.5194/amt-10-3021-2017, 2017
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Three different techniques for measuring turbulent quantities from a single Doppler lidar are evaluated against in situ observations for verification. A six-beam method generally produced the most accurate measurements of the turbulence quantities evaluated. Generally, turbulence kinetic energy can be accurately measured across all scales from a Doppler lidar. Individual velocity variances are measured less accurately, and velocity covariances are shown to be difficult to measure.
Nicola Bodini, Dino Zardi, and Julie K. Lundquist
Atmos. Meas. Tech., 10, 2881–2896, https://doi.org/10.5194/amt-10-2881-2017, https://doi.org/10.5194/amt-10-2881-2017, 2017
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Wind turbine wakes have considerable impacts on downwind turbines in wind farms, given their slower wind speeds and increased turbulence. Based on lidar measurements, we apply a quantitative algorithm to assess wake parameters for wakes from a row of four turbines in CWEX-13 campaign. We describe how wake characteristics evolve, and for the first time we quantify the relation between wind veer and a stretching of the wake structures, and we highlight different results for inner and outer wakes.
Katherine McCaffrey, Laura Bianco, and James M. Wilczak
Atmos. Meas. Tech., 10, 2595–2611, https://doi.org/10.5194/amt-10-2595-2017, https://doi.org/10.5194/amt-10-2595-2017, 2017
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In this paper, we use two wind profiling radars, operating along side a highly instrumented 300 m meteorological tower, to observe turbulence dissipation rates in the planetary boundary layer from an optimized performance setup. Analysis of post-processing techniques, including spectral averaging and moments' calculation methods, shows the optimal parameters which result in good agreement, especially after bias corrections, with sonic anemometers on the tall tower.
Yann Blanchard, Alain Royer, Norman T. O'Neill, David D. Turner, and Edwin W. Eloranta
Atmos. Meas. Tech., 10, 2129–2147, https://doi.org/10.5194/amt-10-2129-2017, https://doi.org/10.5194/amt-10-2129-2017, 2017
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Multiband thermal measurements of zenith sky radiance were used in a retrieval algorithm, to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. The retrieval technique was validated using a synergy lidar and radar data. Inversions were performed across three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of thin ice clouds.
Clara M. St. Martin, Julie K. Lundquist, Andrew Clifton, Gregory S. Poulos, and Scott J. Schreck
Wind Energ. Sci., 2, 295–306, https://doi.org/10.5194/wes-2-295-2017, https://doi.org/10.5194/wes-2-295-2017, 2017
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We use upwind and nacelle-based measurements from a wind turbine and investigate the influence of atmospheric stability and turbulence regimes on nacelle transfer functions (NTFs) used to correct nacelle-mounted anemometer measurements. This work shows that correcting nacelle winds using NTFs results in similar energy production estimates to those obtained using upwind tower-based wind speeds. Further, stability and turbulence metrics have been found to have an effect on NTFs below rated speed.
Laura Bianco, Katja Friedrich, James M. Wilczak, Duane Hazen, Daniel Wolfe, Ruben Delgado, Steven P. Oncley, and Julie K. Lundquist
Atmos. Meas. Tech., 10, 1707–1721, https://doi.org/10.5194/amt-10-1707-2017, https://doi.org/10.5194/amt-10-1707-2017, 2017
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XPIA is a study held in 2015 at NOAA's Boulder Atmospheric Observatory facility, aimed at assessing remote-sensing capabilities for wind energy applications. We use well-defined reference systems to validate temperature retrieved by two microwave radiometers (MWRs) and virtual temperature measured by wind profiling radars with radio acoustic sounding systems (RASSs). Water vapor density and relative humidity by the MWRs were also compared with similar measurements from the reference systems.
Rob K. Newsom, W. Alan Brewer, James M. Wilczak, Daniel E. Wolfe, Steven P. Oncley, and Julie K. Lundquist
Atmos. Meas. Tech., 10, 1229–1240, https://doi.org/10.5194/amt-10-1229-2017, https://doi.org/10.5194/amt-10-1229-2017, 2017
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Doppler lidars are remote sensing instruments that use infrared light to measure wind velocity in the lowest 2 to 3 km of the atmosphere. Quantifying the uncertainty in these measurements is crucial for applications ranging from wind resource assessment to model data assimilation. In this study, we evaluate three methods for estimating the random uncertainty by comparing the lidar wind measurements with nearly collocated in situ wind measurements at multiple levels on a tall tower.
Mithu Debnath, Giacomo Valerio Iungo, W. Alan Brewer, Aditya Choukulkar, Ruben Delgado, Scott Gunter, Julie K. Lundquist, John L. Schroeder, James M. Wilczak, and Daniel Wolfe
Atmos. Meas. Tech., 10, 1215–1227, https://doi.org/10.5194/amt-10-1215-2017, https://doi.org/10.5194/amt-10-1215-2017, 2017
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The XPIA experiment was conducted in 2015 at the Boulder Atmospheric Observatory to estimate capabilities of various remote-sensing techniques for the characterization of complex atmospheric flows. Among different tests, XPIA provided the unique opportunity to perform simultaneous virtual towers with Ka-band radars and scanning Doppler wind lidars. Wind speed and wind direction were assessed against lidar profilers and sonic anemometer data, highlighting a good accuracy of the data retrieved.
Katherine McCaffrey, Laura Bianco, Paul Johnston, and James M. Wilczak
Atmos. Meas. Tech., 10, 999–1015, https://doi.org/10.5194/amt-10-999-2017, https://doi.org/10.5194/amt-10-999-2017, 2017
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Using an optimized turbulence mode of two wind profiling radars (449 MHz and 915 MHz) during the XPIA field campaign, we present improved measurements of vertical velocity variance at the resolved and unresolved scales, using first and second Doppler spectral moments, and the total variance over all scales. Comparisons with sonic anemometers gave strong results, particularly during the daytime convective period. Profiles up to 2 km are possible with the 449 MHz WPR and 1 km from the 915 MHz WPR.
Mithu Debnath, G. Valerio Iungo, Ryan Ashton, W. Alan Brewer, Aditya Choukulkar, Ruben Delgado, Julie K. Lundquist, William J. Shaw, James M. Wilczak, and Daniel Wolfe
Atmos. Meas. Tech., 10, 431–444, https://doi.org/10.5194/amt-10-431-2017, https://doi.org/10.5194/amt-10-431-2017, 2017
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Triple RHI scans were performed with three simultaneous scanning Doppler wind lidars and assessed with lidar profiler and sonic anemometer data. This test is part of the XPIA experiment. The scan strategy consists in two lidars performing co-planar RHI scans, while a third lidar measures the transversal velocity component. The results show that horizontal velocity and wind direction are measured with good accuracy, while the vertical velocity is typically measured with a significant error.
Katherine McCaffrey, Paul T. Quelet, Aditya Choukulkar, James M. Wilczak, Daniel E. Wolfe, Steven P. Oncley, W. Alan Brewer, Mithu Debnath, Ryan Ashton, G. Valerio Iungo, and Julie K. Lundquist
Atmos. Meas. Tech., 10, 393–407, https://doi.org/10.5194/amt-10-393-2017, https://doi.org/10.5194/amt-10-393-2017, 2017
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During the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) field campaign, the wake and flow distortion from a 300-meter meteorological tower was identified using pairs of sonic anemometers mounted on opposite sides of the tower, as well as profiling and scanning lidars. Wind speed deficits up to 50% and TKE increases of 2 orders of magnitude were observed at wind directions in the wake, along with wind direction differences (flow deflection) outside of the wake.
Aditya Choukulkar, W. Alan Brewer, Scott P. Sandberg, Ann Weickmann, Timothy A. Bonin, R. Michael Hardesty, Julie K. Lundquist, Ruben Delgado, G. Valerio Iungo, Ryan Ashton, Mithu Debnath, Laura Bianco, James M. Wilczak, Steven Oncley, and Daniel Wolfe
Atmos. Meas. Tech., 10, 247–264, https://doi.org/10.5194/amt-10-247-2017, https://doi.org/10.5194/amt-10-247-2017, 2017
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This paper discusses trade-offs among various wind measurement strategies using scanning Doppler lidars. It is found that the trade-off exists between being able to make highly precise point measurements versus covering large spatial extents. The highest measurement precision is achieved when multiple lidar systems make wind measurements at one point in space, while highest spatial coverage is achieved through using single lidar scanning measurements and using complex retrieval techniques.
Clara M. St. Martin, Julie K. Lundquist, Andrew Clifton, Gregory S. Poulos, and Scott J. Schreck
Wind Energ. Sci., 1, 221–236, https://doi.org/10.5194/wes-1-221-2016, https://doi.org/10.5194/wes-1-221-2016, 2016
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We use turbine nacelle-based measurements and measurements from an upwind tower to calculate wind turbine power curves and predict the production of energy. We explore how different atmospheric parameters impact these power curves and energy production estimates. Results show statistically significant differences between power curves and production estimates calculated with turbulence and stability filters, and we suggest implementing an additional step in analyzing power performance data.
Nicola Bodini, Julie K. Lundquist, Dino Zardi, and Mark Handschy
Wind Energ. Sci., 1, 115–128, https://doi.org/10.5194/wes-1-115-2016, https://doi.org/10.5194/wes-1-115-2016, 2016
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Year-to-year variability of wind speeds limits the certainty of wind-plant preconstruction energy estimates ("resource assessments"). Using 62-year records from 60 stations across Canada we show that resource highs and lows persist for decades, which makes estimates 2–3 times less certain than if annual levels were uncorrelated. Comparing chronological data records with randomly permuted versions of the same data reveals this in an unambiguous and easy-to-understand way.
Ivan Ortega, Sean Coburn, Larry K. Berg, Kathy Lantz, Joseph Michalsky, Richard A. Ferrare, Johnathan W. Hair, Chris A. Hostetler, and Rainer Volkamer
Atmos. Meas. Tech., 9, 3893–3910, https://doi.org/10.5194/amt-9-3893-2016, https://doi.org/10.5194/amt-9-3893-2016, 2016
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We present an inherently calibrated retrieval to measure aerosol optical depth (AOD) and the aerosol phase function parameter, g, based on measurements of azimuth distributions of the Raman scattering probability (RSP), the near-absolute rotational Raman scattering (RRS) intensity by the University of Colorado two-dimensional (2-D) MAX-DOAS. The retrievals are maximally sensitive at low AOD and do not require absolute radiance calibration. We compare results with data from independent sensors.
Christopher D. Cappa, Katheryn R. Kolesar, Xiaolu Zhang, Dean B. Atkinson, Mikhail S. Pekour, Rahul A. Zaveri, Alla Zelenyuk, and Qi Zhang
Atmos. Chem. Phys., 16, 6511–6535, https://doi.org/10.5194/acp-16-6511-2016, https://doi.org/10.5194/acp-16-6511-2016, 2016
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Measurements of size-dependent aerosol optical properties at visible wavelengths made during the 2010 CARES study are reported on, with a special focus on the characterization of supermicron particles. The relationships with and dependence upon particle composition, particle size, photochemical aging, water uptake and heating are discussed, along with broader implications of these in situ measurements for the interpretation of remote sensing products.
Chun Zhao, Maoyi Huang, Jerome D. Fast, Larry K. Berg, Yun Qian, Alex Guenther, Dasa Gu, Manish Shrivastava, Ying Liu, Stacy Walters, Gabriele Pfister, Jiming Jin, John E. Shilling, and Carsten Warneke
Geosci. Model Dev., 9, 1959–1976, https://doi.org/10.5194/gmd-9-1959-2016, https://doi.org/10.5194/gmd-9-1959-2016, 2016
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In this study, the latest version of MEGAN is coupled within CLM4 in WRF-Chem. In this implementation, MEGAN shares a consistent vegetation map with CLM4. This improved modeling framework is used to investigate the impact of two land surface schemes on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models.
Claire Pettersen, Ralf Bennartz, Mark S. Kulie, Aronne J. Merrelli, Matthew D. Shupe, and David D. Turner
Atmos. Chem. Phys., 16, 4743–4756, https://doi.org/10.5194/acp-16-4743-2016, https://doi.org/10.5194/acp-16-4743-2016, 2016
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We examined four summers of data from a ground-based atmospheric science instrument suite at Summit Station, Greenland, to isolate the signature of the ice precipitation. By using a combination of instruments with different specialities, we identified a passive microwave signature of the ice precipitation. This ice signature compares well to models using synthetic data characteristic of the site.
Andrew M. Dzambo, David D. Turner, and Eli J. Mlawer
Atmos. Meas. Tech., 9, 1613–1626, https://doi.org/10.5194/amt-9-1613-2016, https://doi.org/10.5194/amt-9-1613-2016, 2016
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Radiosondes are used to characterize the humidity in the middle and upper troposphere, but suffer from a solar radiation induced dry bias. This work investigates the accuracy of two published correction algorithms using comparisons with other instruments.
A. Lupascu, R. Easter, R. Zaveri, M. Shrivastava, M. Pekour, J. Tomlinson, Q. Yang, H. Matsui, A. Hodzic, Q. Zhang, and J. D. Fast
Atmos. Chem. Phys., 15, 12283–12313, https://doi.org/10.5194/acp-15-12283-2015, https://doi.org/10.5194/acp-15-12283-2015, 2015
D. B. Atkinson, J. G. Radney, J. Lum, K. R. Kolesar, D. J. Cziczo, M. S. Pekour, Q. Zhang, A. Setyan, A. Zelenyuk, and C. D. Cappa
Atmos. Chem. Phys., 15, 4045–4061, https://doi.org/10.5194/acp-15-4045-2015, https://doi.org/10.5194/acp-15-4045-2015, 2015
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This work describes an analysis of measurements of the influence of water uptake on the light-scattering properties of sub- and supermicron-sized particles as observed in the Sacramento, CA, USA region during the 2010 CARES field campaign. The observations are used to derive campaign-average effective hygroscopicity parameters for submicron oxygenated organic aerosol and for supermicron particles, and the influence of chloride displacement reactions on particle hygroscopicity is examined.
L. K. Berg, M. Shrivastava, R. C. Easter, J. D. Fast, E. G. Chapman, Y. Liu, and R. A. Ferrare
Geosci. Model Dev., 8, 409–429, https://doi.org/10.5194/gmd-8-409-2015, https://doi.org/10.5194/gmd-8-409-2015, 2015
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This work presents a new methodology for representing regional-scale impacts of cloud processing on both aerosol and trace gases in sub-grid-scale convective clouds. Using the new methodology, we can better simulate the aerosol lifecycle over large areas. The results presented in this work highlight the potential change in column-integrated amounts of black carbon, organic aerosol, and sulfate aerosol, which were found to range from -50% for black carbon to +40% for sulfate.
J. K. Lundquist, M. J. Churchfield, S. Lee, and A. Clifton
Atmos. Meas. Tech., 8, 907–920, https://doi.org/10.5194/amt-8-907-2015, https://doi.org/10.5194/amt-8-907-2015, 2015
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Wind-profiling lidars are now regularly used in boundary-layer meteorology and in applications like wind energy, but their use often relies on assuming homogeneity in the wind. Using numerical simulations of stable flow past a wind turbine, we quantify the error expected because of the inhomogeneity of the flow. Large errors (30%) in winds are found near the wind turbine, but by three rotor diameters downwind, errors in the horizontal components have decreased to 15% of the inflow.
R. Ahmadov, S. McKeen, M. Trainer, R. Banta, A. Brewer, S. Brown, P. M. Edwards, J. A. de Gouw, G. J. Frost, J. Gilman, D. Helmig, B. Johnson, A. Karion, A. Koss, A. Langford, B. Lerner, J. Olson, S. Oltmans, J. Peischl, G. Pétron, Y. Pichugina, J. M. Roberts, T. Ryerson, R. Schnell, C. Senff, C. Sweeney, C. Thompson, P. R. Veres, C. Warneke, R. Wild, E. J. Williams, B. Yuan, and R. Zamora
Atmos. Chem. Phys., 15, 411–429, https://doi.org/10.5194/acp-15-411-2015, https://doi.org/10.5194/acp-15-411-2015, 2015
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High 2013 wintertime O3 pollution events associated with oil/gas production within the Uinta Basin are studied using a 3D model. It's able quantitatively to reproduce these events using emission estimates of O3 precursors based on ambient measurements (top-down approach), but unable to reproduce them using a recent bottom-up emission inventory for the oil/gas industry. The role of various physical and meteorological processes, chemical species and pathways contributing to high O3 are quantified.
D. Müller, C. A. Hostetler, R. A. Ferrare, S. P. Burton, E. Chemyakin, A. Kolgotin, J. W. Hair, A. L. Cook, D. B. Harper, R. R. Rogers, R. W. Hare, C. S. Cleckner, M. D. Obland, J. Tomlinson, L. K. Berg, and B. Schmid
Atmos. Meas. Tech., 7, 3487–3496, https://doi.org/10.5194/amt-7-3487-2014, https://doi.org/10.5194/amt-7-3487-2014, 2014
E. Kassianov, J. Barnard, M. Pekour, L. K. Berg, J. Shilling, C. Flynn, F. Mei, and A. Jefferson
Atmos. Meas. Tech., 7, 3247–3261, https://doi.org/10.5194/amt-7-3247-2014, https://doi.org/10.5194/amt-7-3247-2014, 2014
J. D. Fast, J. Allan, R. Bahreini, J. Craven, L. Emmons, R. Ferrare, P. L. Hayes, A. Hodzic, J. Holloway, C. Hostetler, J. L. Jimenez, H. Jonsson, S. Liu, Y. Liu, A. Metcalf, A. Middlebrook, J. Nowak, M. Pekour, A. Perring, L. Russell, A. Sedlacek, J. Seinfeld, A. Setyan, J. Shilling, M. Shrivastava, S. Springston, C. Song, R. Subramanian, J. W. Taylor, V. Vinoj, Q. Yang, R. A. Zaveri, and Q. Zhang
Atmos. Chem. Phys., 14, 10013–10060, https://doi.org/10.5194/acp-14-10013-2014, https://doi.org/10.5194/acp-14-10013-2014, 2014
A. J. Scarino, M. D. Obland, J. D. Fast, S. P. Burton, R. A. Ferrare, C. A. Hostetler, L. K. Berg, B. Lefer, C. Haman, J. W. Hair, R. R. Rogers, C. Butler, A. L. Cook, and D. B. Harper
Atmos. Chem. Phys., 14, 5547–5560, https://doi.org/10.5194/acp-14-5547-2014, https://doi.org/10.5194/acp-14-5547-2014, 2014
K. Van Tricht, I. V. Gorodetskaya, S. Lhermitte, D. D. Turner, J. H. Schween, and N. P. M. Van Lipzig
Atmos. Meas. Tech., 7, 1153–1167, https://doi.org/10.5194/amt-7-1153-2014, https://doi.org/10.5194/amt-7-1153-2014, 2014
B. Friedman, A. Zelenyuk, J. Beranek, G. Kulkarni, M. Pekour, A. Gannet Hallar, I. B. McCubbin, J. A. Thornton, and D. J Cziczo
Atmos. Chem. Phys., 13, 11839–11851, https://doi.org/10.5194/acp-13-11839-2013, https://doi.org/10.5194/acp-13-11839-2013, 2013
G. Maschwitz, U. Löhnert, S. Crewell, T. Rose, and D. D. Turner
Atmos. Meas. Tech., 6, 2641–2658, https://doi.org/10.5194/amt-6-2641-2013, https://doi.org/10.5194/amt-6-2641-2013, 2013
M. P. Cadeddu, J. C. Liljegren, and D. D. Turner
Atmos. Meas. Tech., 6, 2359–2372, https://doi.org/10.5194/amt-6-2359-2013, https://doi.org/10.5194/amt-6-2359-2013, 2013
M. Gyawali, W. P. Arnott, R. A. Zaveri, C. Song, M. Pekour, B. Flowers, M. K. Dubey, A. Setyan, Q. Zhang, J. W. Harworth, J. G. Radney, D. B. Atkinson, S. China, C. Mazzoleni, K. Gorkowski, R. Subramanian, B. T. Jobson, and H. Moosmüller
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-7113-2013, https://doi.org/10.5194/acpd-13-7113-2013, 2013
Revised manuscript not accepted
Related subject area
Atmospheric sciences
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
Investigating Ground-Level Ozone Pollution in Semi-Arid and Arid Regions of Arizona Using WRF-Chem v4.4 Modeling
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
FUME 2.0 – Flexible Universal processor for Modeling Emissions
Application of regional meteorology and air quality models based on MIPS CPU Platform
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?
Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1
A global grid model for the estimation of zenith tropospheric delay considering the variations at different altitudes
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations
Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors
A mountain-induced moist baroclinic wave test case for the dynamical cores of atmospheric general circulation models
The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure facilitating further processing to allow emission processing from continental to street scale.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-202, https://doi.org/10.5194/gmd-2023-202, 2023
Revised manuscript accepted for GMD
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Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
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The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
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We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
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The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
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Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
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This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
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Short summary
During the second Wind Forecast Improvement Project, improvements to the parameterizations were applied to the High Resolution Rapid Refresh model and its nested version. The impacts of the new parameterizations on the forecast of 80 m wind speeds and power are assessed, using sodars and profiling lidars observations for comparison. Improvements are evaluated as a function of the model’s initialization time, forecast horizon, time of the day, season, site elevation, and meteorological phenomena.
During the second Wind Forecast Improvement Project, improvements to the parameterizations were...
