Articles | Volume 8, issue 10
https://doi.org/10.5194/gmd-8-3311-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-3311-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Mapping of satellite Earth observations using moving window block kriging
J. M. Tadić
CORRESPONDING AUTHOR
Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
X. Qiu
Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
V. Yadav
Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
A. M. Michalak
Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
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Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak
Biogeosciences, 21, 869–891, https://doi.org/10.5194/bg-21-869-2024, https://doi.org/10.5194/bg-21-869-2024, 2024
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Assessing agreement between bottom-up and top-down methods across spatial scales can provide insights into the relationship between ensemble spread (difference across models) and model accuracy (difference between model estimates and reality). We find that ensemble spread is unlikely to be a good indicator of actual uncertainty in the North American carbon balance. However, models that are consistent with atmospheric constraints show stronger agreement between top-down and bottom-up estimates.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 20, 323–331, https://doi.org/10.5194/acp-20-323-2020, https://doi.org/10.5194/acp-20-323-2020, 2020
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere. The satellite measures radiation, and these measurements are then converted to an estimate of atmospheric CO2. This conversion or retrieval algorithm has improved markedly since the satellite launch. We find that these improvements in the CO2 retrieval are having a potentially transformative effect on satellite-based estimates of the global biospheric carbon balance.
Peter J. Rayner, Anna M. Michalak, and Frédéric Chevallier
Atmos. Chem. Phys., 19, 13911–13932, https://doi.org/10.5194/acp-19-13911-2019, https://doi.org/10.5194/acp-19-13911-2019, 2019
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This paper describes the methods for combining models and data to understand how nutrients and pollutants move through natural systems. The methods are analogous to the process of weather forecasting in which previous information is combined with new observations and a model to improve our knowledge of the internal state of the physical system. The methods appear highly diverse but the paper shows that they are all examples of a single underlying formalism.
Ju-Mee Ryoo, Laura T. Iraci, Tomoaki Tanaka, Josette E. Marrero, Emma L. Yates, Inez Fung, Anna M. Michalak, Jovan Tadić, Warren Gore, T. Paul Bui, Jonathan M. Dean-Day, and Cecilia S. Chang
Atmos. Meas. Tech., 12, 2949–2966, https://doi.org/10.5194/amt-12-2949-2019, https://doi.org/10.5194/amt-12-2949-2019, 2019
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We designed cylindrical flights and computed the emission fluxes using a kriging method and Gauss's theorem over Sacramento, California. Differences in wind treatment and background affect the emission estimates by a factor of 1.5 to 7. The effects of the vertical layer average and the vertical mass transfer on the emission estimates are found to be small, esp. local scale. The result also suggests a closed-shape flight profile can better contain total emissions than a one-sided curtain flight.
Scot M. Miller, Anna M. Michalak, Vineet Yadav, and Jovan M. Tadić
Atmos. Chem. Phys., 18, 6785–6799, https://doi.org/10.5194/acp-18-6785-2018, https://doi.org/10.5194/acp-18-6785-2018, 2018
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere globally. We evaluate the extent to which current OCO-2 observations can inform scientific understanding of the biospheric carbon balance. We find that current observations are best-equipped to constrain the biospheric carbon balance across continental or hemispheric regions and provide limited information on smaller regions.
Anna M. Michalak, Nina A. Randazzo, and Frédéric Chevallier
Atmos. Chem. Phys., 17, 7405–7421, https://doi.org/10.5194/acp-17-7405-2017, https://doi.org/10.5194/acp-17-7405-2017, 2017
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The use of inverse modeling for quantifying emissions of greenhouse gases is increasing. Estimates are very difficult to evaluate objectively, however, due to limited atmospheric observations and the lack of direct emissions measurements at compatible scales. Diagnostic tools have been proposed to partially circumvent these limitations. This paper presents the first systematic review of the scope and applicability of these tools for atmospheric inversions of long-lived greenhouse gases.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 17, 3963–3985, https://doi.org/10.5194/acp-17-3963-2017, https://doi.org/10.5194/acp-17-3963-2017, 2017
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We reviewed recent efforts to estimate state- and national-scale carbon dioxide and methane emissions from individual anthropogenic source sectors in the United States. State and federal greenhouse gas regulations almost always target reductions from specific source sectors, and reliable emission estimates are important to support and evaluate these policies. We also describe a number of forward-looking opportunities that would improve sector-specific estimates.
Jovan M. Tadić, Xuemei Qiu, Scot Miller, and Anna M. Michalak
Geosci. Model Dev., 10, 709–720, https://doi.org/10.5194/gmd-10-709-2017, https://doi.org/10.5194/gmd-10-709-2017, 2017
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We developed a new method to create contiguous maps from sparse and/or noisy satellite observations. This approach could be used to produce retroactive or real-time estimates of environmental data observed by satellites which exhibit spatio-temporal autocorrelations. The method could be applied in a standalone mode or as part of a broader satellite data processing package. Maps produced in this way could then be incorporated into physical and biogeochemical models of the Earth system.
Sander Houweling, Peter Bergamaschi, Frederic Chevallier, Martin Heimann, Thomas Kaminski, Maarten Krol, Anna M. Michalak, and Prabir Patra
Atmos. Chem. Phys., 17, 235–256, https://doi.org/10.5194/acp-17-235-2017, https://doi.org/10.5194/acp-17-235-2017, 2017
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The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements. It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.
Vineet Yadav and Anna M. Michalak
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-204, https://doi.org/10.5194/gmd-2016-204, 2016
Revised manuscript has not been submitted
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Multiplication of two matrices that consists of few non-zero entries is a fundamental operation in problems that involve estimation of greenhouse gas fluxes from atmospheric measurements. To increase computational efficiency of estimating these quantities, modification of the standard matrix multiplication algorithm for multiplying these matrices is proposed in this research.
Bjorn-Gustaf J. Brooks, Ankur R. Desai, Britton B. Stephens, Anna M. Michalak, and Jakob Zscheischler
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-223, https://doi.org/10.5194/bg-2016-223, 2016
Manuscript not accepted for further review
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CO2 is the primary greenhouse gas, and its abundance in the atmosphere tends to increase during disturbances like drought. This paper demonstrates how CO2 measurements are combined with models to determine not only how strongly different locations influence CO2 measurement stations, but also the capacity of those measurement stations to detect drought effects. Understanding detection sensitivity will help assess what kinds of changes and turnings points can be monitored using atmospheric CO2.
Scot M. Miller, Roisin Commane, Joe R. Melton, Arlyn E. Andrews, Joshua Benmergui, Edward J. Dlugokencky, Greet Janssens-Maenhout, Anna M. Michalak, Colm Sweeney, and Doug E. J. Worthy
Biogeosciences, 13, 1329–1339, https://doi.org/10.5194/bg-13-1329-2016, https://doi.org/10.5194/bg-13-1329-2016, 2016
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We use atmospheric data from the US and Canada to examine seven wetland methane flux estimates. Relative to existing estimates, we find a methane source that is smaller in magnitude with a broader seasonal cycle. Furthermore, we estimate the largest fluxes over the Hudson Bay Lowlands, a spatial distribution that differs from commonly used remote sensing estimates of wetland location.
J. Ray, J. Lee, V. Yadav, S. Lefantzi, A. M. Michalak, and B. van Bloemen Waanders
Geosci. Model Dev., 8, 1259–1273, https://doi.org/10.5194/gmd-8-1259-2015, https://doi.org/10.5194/gmd-8-1259-2015, 2015
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The paper presents a statistical method (shrinkage) that can be used to estimate rough emission fields, e.g., fossil fuel CO2 emissions, from measurements of concentrations. This method is demonstrated in a test case where the emissions are modeled using wavelets. We find that the method can eliminate unnecessary complexity from the wavelet model, ensures non-negativity of the emissions, is computationally efficient and is, by construction, insensitive to prior guesses of the total emission.
Y. Fang, A. M. Michalak, Y. P. Shiga, and V. Yadav
Biogeosciences, 11, 6985–6997, https://doi.org/10.5194/bg-11-6985-2014, https://doi.org/10.5194/bg-11-6985-2014, 2014
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Terrestrial biospheric models (TBMs) are used to assess carbon--climate interactions. We present a new and complementary approach for evaluating the spatiotemporal patterns, rather than magnitudes, of biosphere--atmosphere carbon exchange predicted by TBMs, based on atmospheric observations. Experiments demonstrate that the performance of TBMs varies substantially across seasons and biomes, with best performance during the growing season and more limited skill during transition seasons.
Y. Wei, S. Liu, D. N. Huntzinger, A. M. Michalak, N. Viovy, W. M. Post, C. R. Schwalm, K. Schaefer, A. R. Jacobson, C. Lu, H. Tian, D. M. Ricciuto, R. B. Cook, J. Mao, and X. Shi
Geosci. Model Dev., 7, 2875–2893, https://doi.org/10.5194/gmd-7-2875-2014, https://doi.org/10.5194/gmd-7-2875-2014, 2014
J. Ray, V. Yadav, A. M. Michalak, B. van Bloemen Waanders, and S. A. McKenna
Geosci. Model Dev., 7, 1901–1918, https://doi.org/10.5194/gmd-7-1901-2014, https://doi.org/10.5194/gmd-7-1901-2014, 2014
S. M. Miller, A. M. Michalak, and P. J. Levi
Geosci. Model Dev., 7, 303–315, https://doi.org/10.5194/gmd-7-303-2014, https://doi.org/10.5194/gmd-7-303-2014, 2014
A. Chatterjee and A. M. Michalak
Atmos. Chem. Phys., 13, 11643–11660, https://doi.org/10.5194/acp-13-11643-2013, https://doi.org/10.5194/acp-13-11643-2013, 2013
V. Yadav and A. M. Michalak
Geosci. Model Dev., 6, 583–590, https://doi.org/10.5194/gmd-6-583-2013, https://doi.org/10.5194/gmd-6-583-2013, 2013
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Scalable Feature Extraction and Tracking (SCAFET): a general framework for feature extraction from large climate data sets
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Tom Keel, Chris Brierley, and Tamsin Edwards
Geosci. Model Dev., 17, 1229–1247, https://doi.org/10.5194/gmd-17-1229-2024, https://doi.org/10.5194/gmd-17-1229-2024, 2024
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Jet streams are an important control on surface weather as their speed and shape can modify the properties of weather systems. Establishing trends in the operation of jet streams may provide some indication of the future of weather in a warming world. Despite this, it has not been easy to establish trends, as many methods have been used to characterise them in data. We introduce a tool containing various implementations of jet stream statistics and algorithms that works in a standardised manner.
Amir Golparvar, Matthias Kästner, and Martin Thullner
Geosci. Model Dev., 17, 881–898, https://doi.org/10.5194/gmd-17-881-2024, https://doi.org/10.5194/gmd-17-881-2024, 2024
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Coupled reaction transport modelling is an established and beneficial method for studying natural and synthetic porous material, with applications ranging from industrial processes to natural decompositions in terrestrial environments. Up to now, a framework that explicitly considers the porous structure (e.g. from µ-CT images) for modelling the transport of reactive species is missing. We presented a model that overcomes this limitation and represents a novel numerical simulation toolbox.
Stefan Hergarten
Geosci. Model Dev., 17, 781–794, https://doi.org/10.5194/gmd-17-781-2024, https://doi.org/10.5194/gmd-17-781-2024, 2024
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The Voellmy rheology has been widely used for simulating snow and rock avalanches. Recently, a modified version of this rheology was proposed, which turned out to be able to predict the observed long runout of large rock avalanches theoretically. The software MinVoellmy presented here is the first numerical implementation of the modified rheology. It consists of MATLAB and Python classes, where simplicity and parsimony were the design goals.
Arjun Babu Nellikkattil, Danielle Lemmon, Travis Allen O'Brien, June-Yi Lee, and Jung-Eun Chu
Geosci. Model Dev., 17, 301–320, https://doi.org/10.5194/gmd-17-301-2024, https://doi.org/10.5194/gmd-17-301-2024, 2024
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This study introduces a new computational framework called Scalable Feature Extraction and Tracking (SCAFET), designed to extract and track features in climate data. SCAFET stands out by using innovative shape-based metrics to identify features without relying on preconceived assumptions about the climate model or mean state. This approach allows more accurate comparisons between different models and scenarios.
Mohammad Mortezazadeh, Jean-François Cossette, Ashu Dastoor, Jean de Grandpré, Irena Ivanova, and Abdessamad Qaddouri
Geosci. Model Dev., 17, 335–346, https://doi.org/10.5194/gmd-17-335-2024, https://doi.org/10.5194/gmd-17-335-2024, 2024
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The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach. In this paper we implement a new interpolation scheme into the semi-Lagrangian approach which has the same computational cost as a third-order polynomial scheme but with the accuracy of a fourth-order interpolation scheme. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps.
Boris Gailleton, Luca C. Malatesta, Guillaume Cordonnier, and Jean Braun
Geosci. Model Dev., 17, 71–90, https://doi.org/10.5194/gmd-17-71-2024, https://doi.org/10.5194/gmd-17-71-2024, 2024
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This contribution presents a new method to numerically explore the evolution of mountain ranges and surrounding areas. The method helps in monitoring with details on the timing and travel path of material eroded from the mountain ranges. It is particularly well suited to studies juxtaposing different domains – lakes or multiple rock types, for example – and enables the combination of different processes.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
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In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Carlos Spa, Otilio Rojas, and Josep de la Puente
Geosci. Model Dev., 16, 7237–7252, https://doi.org/10.5194/gmd-16-7237-2023, https://doi.org/10.5194/gmd-16-7237-2023, 2023
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This paper develops a calibration methodology of all absorbing techniques typically used by Fourier pseudo-spectral time-domain (PSTD) methods for geoacoustic wave simulations. The main contributions of the paper are (a) an implementation and quantitative comparison of all absorbing techniques available for PSTD methods through a simple and robust numerical experiment, and (b) a validation of these absorbing techniques in several 3-D seismic scenarios with gradual heterogeneity complexities.
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023, https://doi.org/10.5194/gmd-16-6987-2023, 2023
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Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.
Kees Nederhoff, Maarten van Ormondt, Jay Veeramony, Ap van Dongeren, Jose Antolínez, Tim Leijnse, and Dano Roelvink
EGUsphere, https://doi.org/10.5194/egusphere-2023-2341, https://doi.org/10.5194/egusphere-2023-2341, 2023
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Forecasting tropical cyclones and their flooding impact is challenging. Our research introduces the Tropical Cyclone Forecasting Framework (TC-FF), enhancing cyclone predictions despite uncertainties. TC-FF generates global wind and flood scenarios, valuable even in data-limited regions. Applied to cases like Cyclone Idai, it showcases potential in bettering disaster preparation, marking progress in handling cyclone threats.
Younghun Kang and Ethan J. Kubatko
EGUsphere, https://doi.org/10.5194/egusphere-2023-1434, https://doi.org/10.5194/egusphere-2023-1434, 2023
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Models used to simulate the flow of coastal and riverine waters, including flooding, require a geometric representation (or mesh) of geographic features that exhibit a range of disparate spatial scales—from large open waters to small, narrow channels. Representing these features in an accurate way without excessive computational overhead presents a challenge. Here, we develop an automatic mesh generation tool to help address this challenge. Our results demonstrate the efficacy of our approach.
Stefan J. Miller, Paul A. Makar, and Colin J. Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-159, https://doi.org/10.5194/gmd-2023-159, 2023
Revised manuscript accepted for GMD
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This work outlines a new solver written in Fortran 90 to calculate the partitioning of metastable aerosols at thermodynamic equilibrium based on the algorithms of ISORROPIA II. The new code includes numerical improvements that decrease the computational speed (compared to ISORROPIA II) while improving the accuracy of the partitioning solution.
Tor Nordam, Ruben Kristiansen, Raymond Nepstad, Erik van Sebille, and Andy M. Booth
Geosci. Model Dev., 16, 5339–5363, https://doi.org/10.5194/gmd-16-5339-2023, https://doi.org/10.5194/gmd-16-5339-2023, 2023
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We describe and compare two common methods, Eulerian and Lagrangian models, used to simulate the vertical transport of material in the ocean. They both solve the same transport problems but use different approaches for representing the underlying equations on the computer. The main focus of our study is on the numerical accuracy of the two approaches. Our results should be useful for other researchers creating or using these types of transport models.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 16, 5265–5279, https://doi.org/10.5194/gmd-16-5265-2023, https://doi.org/10.5194/gmd-16-5265-2023, 2023
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Multiple‐point geostatistics are widely used to simulate complex spatial structures based on a training image. The use of these methods relies on the possibility of finding optimal training images and parametrization of the simulation algorithms. Here, we propose finding an optimal set of parameters using only the training image as input. The main advantage of our approach is to remove the risk of overfitting an objective function.
Fernanda Alvarado-Neves, Laurent Ailleres, Lachlan Grose, Alexander R. Cruden, and Robin Armit
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-85, https://doi.org/10.5194/gmd-2023-85, 2023
Revised manuscript accepted for GMD
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Previous work have demonstrated how adding geological knowledge to modelling methods create more accurate and reliable models. Following this reasoning, we added constraints from magma emplacement mechanisms into existing modelling frameworks to improve the 3D characterisation of igneous intrusions. We test the method in synthetic and real-world case studies, and the results show that our method can reproduce intrusion morphologies with no manual processing and using realistic datasets.
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
EGUsphere, https://doi.org/10.48550/arXiv.2306.05377, https://doi.org/10.48550/arXiv.2306.05377, 2023
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Sophisticated numerical models of the Earth's atmosphere include representations of many physical and chemical processes. In numerical simulations, these processes need to be calculated in a certain sequence. This study reveals the weaknesses of the sequence of calculations used for aerosol processes in a global atmosphere model. A revision of the sequence is proposed, and its impacts on the simulated global aerosol climatology are evaluated.
Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
EGUsphere, https://doi.org/10.48550/arXiv.2306.04929, https://doi.org/10.48550/arXiv.2306.04929, 2023
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Generally speaking, accurate climate simulation requires an accurate evolution of the underlying mathematical equations on large computers. The equations are typically formulated and evolved in process groups. Process coupling refers to how the evolution of those groups of combined to evolve the full set of equations for the whole atmosphere. This work presents a mathematical framework to evaluate methods without the need to first implement the methods.
Siting Li, Ping Wang, Hong Wang, Yue Peng, Zhaodong Liu, Wenjie Zhang, Hongli Liu, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 16, 4171–4191, https://doi.org/10.5194/gmd-16-4171-2023, https://doi.org/10.5194/gmd-16-4171-2023, 2023
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Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
Thomas Richter, Véronique Dansereau, Christian Lessig, and Piotr Minakowski
Geosci. Model Dev., 16, 3907–3926, https://doi.org/10.5194/gmd-16-3907-2023, https://doi.org/10.5194/gmd-16-3907-2023, 2023
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Sea ice covers not only the pole regions but affects the weather and climate globally. For example, its white surface reflects more sunlight than land. The oceans around the poles are therefore kept cool, which affects the circulation in the oceans worldwide. Simulating the behavior and changes in sea ice on a computer is, however, very difficult. We propose a new computer simulation that better models how cracks in the ice change over time and show this by comparing to other simulations.
Emma J. MacKie, Michael Field, Lijing Wang, Zhen Yin, Nathan Schoedl, Matthew Hibbs, and Allan Zhang
Geosci. Model Dev., 16, 3765–3783, https://doi.org/10.5194/gmd-16-3765-2023, https://doi.org/10.5194/gmd-16-3765-2023, 2023
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Earth scientists often have to fill in spatial gaps in measurements. This gap-filling or interpolation can be accomplished with geostatistical methods, where the statistical relationships between measurements are used to inform how these gaps should be filled. Despite the broad utility of these methods, there are few freely available geostatistical software applications. We present GStatSim, a Python package for performing different geostatistical interpolation methods.
Ian Madden, Simone Marras, and Jenny Suckale
Geosci. Model Dev., 16, 3479–3500, https://doi.org/10.5194/gmd-16-3479-2023, https://doi.org/10.5194/gmd-16-3479-2023, 2023
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To aid risk managers who may wish to rapidly assess tsunami risk but may lack high-performance computing infrastructure, we provide an accessible software package able to rapidly model tsunami inundation over real topography by leveraging Google's Tensor Processing Unit, a high-performance hardware. Minimally trained users can take advantage of the rapid modeling abilities provided by this package via a web browser thanks to the ease of use of Google Cloud Platform.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev., 16, 3291–3311, https://doi.org/10.5194/gmd-16-3291-2023, https://doi.org/10.5194/gmd-16-3291-2023, 2023
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A novel subgrid channel (SGC) model is developed for river–floodplain modelling, allowing utilization of subgrid-scale bathymetric information while performing computations on relatively coarse grids. By including adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low-friction regions such as urban areas is addressed. Evaluation of the new SGC model through structured tests confirmed that the accuracy and stability have improved.
Xiaqiong Zhou and Hann-Ming Henry Juang
Geosci. Model Dev., 16, 3263–3274, https://doi.org/10.5194/gmd-16-3263-2023, https://doi.org/10.5194/gmd-16-3263-2023, 2023
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The National Centers for Environmental Prediction Global Forecast System version 16 experienced model instability failures in real-time runs resolved by increasing the minimum thickness depth parameter. Further investigation revealed that the issue was caused by the advection of geopotential heights at the model's layer interfaces. By replacing high-order boundary conditions with zero-gradient boundary conditions for interface-wind reconstruction, the instability was effectively addressed.
Grant T. Euen, Shangxin Liu, Rene Gassmöller, Timo Heister, and Scott D. King
Geosci. Model Dev., 16, 3221–3239, https://doi.org/10.5194/gmd-16-3221-2023, https://doi.org/10.5194/gmd-16-3221-2023, 2023
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Due to the increasing availability of high-performance computing over the past few decades, numerical models have become an important tool for research. Here we test two geodynamic codes that produce such models: ASPECT, a newer code, and CitcomS, an older one. We show that they produce solutions that are extremely close. As methods and codes become more complex over time, showing reproducibility allows us to seamlessly link previously known information to modern methodologies.
Mohammad Kazem Sharifian, Georges Kesserwani, Alovya Ahmed Chowdhury, Jeffrey Neal, and Paul Bates
Geosci. Model Dev., 16, 2391–2413, https://doi.org/10.5194/gmd-16-2391-2023, https://doi.org/10.5194/gmd-16-2391-2023, 2023
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This paper describes a new release of the LISFLOOD-FP model for fast and efficient flood simulations. It features a new non-uniform grid generator that uses multiwavelet analyses to sensibly coarsens the resolutions where the local topographic variations are smooth. Moreover, the model is parallelised on the graphical processing units (GPUs) to further boost computational efficiency. The performance of the model is assessed for five real-world case studies, noting its potential applications.
André R. Brodtkorb, Anna Benedictow, Heiko Klein, Arve Kylling, Agnes Nyiri, Alvaro Valdebenito, Espen Sollum, and Nina Kristiansen
EGUsphere, https://doi.org/10.5194/egusphere-2023-51, https://doi.org/10.5194/egusphere-2023-51, 2023
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It is vital to know the extent and concentration of volcanic ash in the atmosphere during a volcanic eruption. Whilst satellite imagery may give an estimate of the ash right now (assuming no cloud coverage), we also need to know where it will be in the coming hours. This paper presents a method for estimating parameters for a volcanic eruption based on satellite observations of ash in the atmosphere. The software package is open source and applicable to similar inversion scenarios.
Bruno K. Zürcher
Geosci. Model Dev., 16, 1697–1711, https://doi.org/10.5194/gmd-16-1697-2023, https://doi.org/10.5194/gmd-16-1697-2023, 2023
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We present a novel algorithm to efficiently compute Barnes interpolation, which is a method for transforming data values recorded at irregularly spaced points into a corresponding regular grid. In contrast to naive implementations with an algorithmic complexity that depends on the product of the number of sample points and the number of grid points, our approach reduces this dependency to their sum.
Daniel Giles, Matthew M. Graham, Mosè Giordano, Tuomas Koskela, Alexandros Beskos, and Serge Guillas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-38, https://doi.org/10.5194/gmd-2023-38, 2023
Revised manuscript accepted for GMD
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Digital twins of physical and human systems informed by real-time data are becoming ubiquitous across a wide range of settings. Progress for researchers is currently limited by a lack of tools to run these models effectively and efficiently. One of the current challenges is the optimal use of real-time observations. The work presented here focuses on a developed open source software platform which aims to improve this usage, with an emphasis placed on flexibility, efficiency and scalability.
David H. Marsico and Paul A. Ullrich
Geosci. Model Dev., 16, 1537–1551, https://doi.org/10.5194/gmd-16-1537-2023, https://doi.org/10.5194/gmd-16-1537-2023, 2023
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Climate models involve several different components, such as the atmosphere, ocean, and land models. Information needs to be exchanged, or remapped, between these models, and devising algorithms for performing this exchange is important for ensuring the accuracy of climate simulations. In this paper, we examine the efficacy of several traditional and novel approaches to remapping on the sphere and demonstrate where our approaches offer improvement.
Moritz Liebl, Jörg Robl, Stefan Hergarten, David Lundbek Egholm, and Kurt Stüwe
Geosci. Model Dev., 16, 1315–1343, https://doi.org/10.5194/gmd-16-1315-2023, https://doi.org/10.5194/gmd-16-1315-2023, 2023
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In this study, we benchmark a topography-based model for glacier erosion (OpenLEM) with a well-established process-based model (iSOSIA). Our experiments show that large-scale erosion patterns and particularly the transformation of valley length geometry from fluvial to glacial conditions are very similar in both models. This finding enables the application of OpenLEM to study the influence of climate and tectonics on glaciated mountains with reasonable computational effort on standard PCs.
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023, https://doi.org/10.5194/gmd-16-1265-2023, 2023
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This paper introduces the Met Office's new shallow water model. The shallow water model is a building block towards the Met Office's new atmospheric dynamical core. The shallow water model is tested on a number of standard spherical shallow water test cases, including flow over mountains and unstable jets. Results show that the model produces similar results to other shallow water models in the literature.
Anthony Gruber, Max Gunzburger, Lili Ju, Rihui Lan, and Zhu Wang
Geosci. Model Dev., 16, 1213–1229, https://doi.org/10.5194/gmd-16-1213-2023, https://doi.org/10.5194/gmd-16-1213-2023, 2023
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This work applies a novel technical tool, multifidelity Monte Carlo (MFMC) estimation, to three climate-related benchmark experiments involving oceanic, atmospheric, and glacial modeling. By considering useful quantities such as maximum sea height and total (kinetic) energy, we show that MFMC leads to predictions which are more accurate and less costly than those obtained by standard methods. This suggests MFMC as a potential drop-in replacement for estimation in realistic climate models.
Piyoosh Jaysaval, Glenn E. Hammond, and Timothy C. Johnson
Geosci. Model Dev., 16, 961–976, https://doi.org/10.5194/gmd-16-961-2023, https://doi.org/10.5194/gmd-16-961-2023, 2023
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We present a robust and highly scalable implementation of numerical forward modeling and inversion algorithms for geophysical electrical resistivity tomography data. The implementation is publicly available and developed within the framework of PFLOTRAN (http://www.pflotran.org), an open-source, state-of-the-art massively parallel subsurface flow and transport simulation code. The paper details all the theoretical and implementation aspects of the new capabilities along with test examples.
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023, https://doi.org/10.5194/gmd-16-833-2023, 2023
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We develop a multi-dimensional, parallelized domain decomposition strategy for mass-transfer particle tracking methods in two and three dimensions, investigate different procedures for decomposing the domain, and prescribe an optimal tiling based on physical problem parameters and the number of available CPU cores. For an optimally subdivided diffusion problem, the parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to thousands of cores.
John Mern and Jef Caers
Geosci. Model Dev., 16, 289–313, https://doi.org/10.5194/gmd-16-289-2023, https://doi.org/10.5194/gmd-16-289-2023, 2023
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In this work, we formulate the sequential geoscientific data acquisition problem as a problem that is similar to playing chess against nature, except the pieces are not fully observed. Solutions to these problems are given in AI and rarely used in geoscientific data planning. We illustrate our approach to a simple 2D problem of mineral exploration.
Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
EGUsphere, https://doi.org/10.5194/egusphere-2022-863, https://doi.org/10.5194/egusphere-2022-863, 2023
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This paper applies cutting-edge numerical methods to show how uncertain climate change and technological progress affect the future utilization of the scarce world's land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The more uncertain the future crop yields are, the more forest conversion will be necessary to sustain human welfare. Some of that conversion takes place even when crop yields are not actually affected.
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029, https://doi.org/10.5194/gmd-15-9015-2022, https://doi.org/10.5194/gmd-15-9015-2022, 2022
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While the national ambient air quality standard of ozone is based on the 3-year average of the fourth highest 8 h maximum (MDA8) ozone concentrations, these predicted extreme values using numerical methods are always biased low. We built four computational models (GAM, MARS, random forest and SVR) to predict the fourth highest MDA8 ozone in Southern California using precursor emissions, meteorology and climatological patterns. All models presented acceptable performance, with GAM being the best.
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784, https://doi.org/10.5194/gmd-15-8765-2022, https://doi.org/10.5194/gmd-15-8765-2022, 2022
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A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.
Till Sachau, Haibin Yang, Justin Lang, Paul D. Bons, and Louis Moresi
Geosci. Model Dev., 15, 8749–8764, https://doi.org/10.5194/gmd-15-8749-2022, https://doi.org/10.5194/gmd-15-8749-2022, 2022
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Knowledge of the internal structures of the major continental ice sheets is improving, thanks to new investigative techniques. These structures are an essential indication of the flow behavior and dynamics of ice transport, which in turn is important for understanding the actual impact of the vast amounts of water trapped in continental ice sheets on global sea-level rise. The software studied here is specifically designed to simulate such structures and their evolution.
Keith J. Roberts, Alexandre Olender, Lucas Franceschini, Robert C. Kirby, Rafael S. Gioria, and Bruno S. Carmo
Geosci. Model Dev., 15, 8639–8667, https://doi.org/10.5194/gmd-15-8639-2022, https://doi.org/10.5194/gmd-15-8639-2022, 2022
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Finite-element methods (FEMs) permit the use of more flexible unstructured meshes but are rarely used in full waveform inversions (FWIs), an iterative process that reconstructs velocity models of earth’s subsurface, due to computational and memory storage costs. To reduce those costs, novel software is presented allowing the use of high-order mass-lumped FEMs on triangular meshes, together with a material-property mesh-adaptation performance-enhancing strategy, enabling its use in FWIs.
Konstantinos Papadakis, Yann Pfau-Kempf, Urs Ganse, Markus Battarbee, Markku Alho, Maxime Grandin, Maxime Dubart, Lucile Turc, Hongyang Zhou, Konstantinos Horaites, Ivan Zaitsev, Giulia Cozzani, Maarja Bussov, Evgeny Gordeev, Fasil Tesema, Harriet George, Jonas Suni, Vertti Tarvus, and Minna Palmroth
Geosci. Model Dev., 15, 7903–7912, https://doi.org/10.5194/gmd-15-7903-2022, https://doi.org/10.5194/gmd-15-7903-2022, 2022
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Vlasiator is a plasma simulation code that simulates the entire near-Earth space at a global scale. As 6D simulations require enormous amounts of computational resources, Vlasiator uses adaptive mesh refinement (AMR) to lighten the computational burden. However, due to Vlasiator’s grid topology, AMR simulations suffer from grid aliasing artifacts that affect the global results. In this work, we present and evaluate the performance of a mechanism for alleviating those artifacts.
Artur Safin, Damien Bouffard, Firat Ozdemir, Cintia L. Ramón, James Runnalls, Fotis Georgatos, Camille Minaudo, and Jonas Šukys
Geosci. Model Dev., 15, 7715–7730, https://doi.org/10.5194/gmd-15-7715-2022, https://doi.org/10.5194/gmd-15-7715-2022, 2022
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Reconciling the differences between numerical model predictions and observational data is always a challenge. In this paper, we investigate the viability of a novel approach to the calibration of a three-dimensional hydrodynamic model of Lake Geneva, where the target parameters are inferred in terms of distributions. We employ a filtering technique that generates physically consistent model trajectories and implement a neural network to enable bulk-to-skin temperature conversion.
Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681, https://doi.org/10.5194/gmd-15-7641-2022, https://doi.org/10.5194/gmd-15-7641-2022, 2022
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Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Lixin Wu, Dexun Chen, Yang Gao, Zhiqiang Wei, Dongning Jia, and Xiaopei Lin
Geosci. Model Dev., 15, 6695–6708, https://doi.org/10.5194/gmd-15-6695-2022, https://doi.org/10.5194/gmd-15-6695-2022, 2022
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To understand the scientific consequence of perturbations caused by slave cores in heterogeneous computing environments, we examine the influence of perturbation amplitudes on the determination of the cloud bottom and cloud top and compute the probability density function (PDF) of generated clouds. A series of comparisons of the PDFs between homogeneous and heterogeneous systems show consistently acceptable error tolerances when using slave cores in heterogeneous computing environments.
Vijay S. Mahadevan, Jorge E. Guerra, Xiangmin Jiao, Paul Kuberry, Yipeng Li, Paul Ullrich, David Marsico, Robert Jacob, Pavel Bochev, and Philip Jones
Geosci. Model Dev., 15, 6601–6635, https://doi.org/10.5194/gmd-15-6601-2022, https://doi.org/10.5194/gmd-15-6601-2022, 2022
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Coupled Earth system models require transfer of field data between multiple components with varying spatial resolutions to determine the correct climate behavior. We present the Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol to evaluate the accuracy, conservation properties, monotonicity, and local feature preservation of four different remapper algorithms for various unstructured mesh problems of interest. Future extensions to more practical use cases are also discussed.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
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Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Andrew M. Bradley, Peter A. Bosler, and Oksana Guba
Geosci. Model Dev., 15, 6285–6310, https://doi.org/10.5194/gmd-15-6285-2022, https://doi.org/10.5194/gmd-15-6285-2022, 2022
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Tracer transport in atmosphere models can be computationally expensive. We describe a flexible and efficient interpolation semi-Lagrangian method, the Islet method. It permits using up to three grids that share an element grid: a dynamics grid for computing quantities such as the wind velocity; a physics parameterizations grid; and a tracer grid. The Islet method performs well on a number of verification problems and achieves high performance in the E3SM Atmosphere Model version 2.
Léo Pujol, Pierre-André Garambois, and Jérôme Monnier
Geosci. Model Dev., 15, 6085–6113, https://doi.org/10.5194/gmd-15-6085-2022, https://doi.org/10.5194/gmd-15-6085-2022, 2022
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This contribution presents a new numerical model for representing hydraulic–hydrological quantities at the basin scale. It allows modeling large areas at a low computational cost, with fine zooms where needed. It allows the integration of local and satellite measurements, via data assimilation methods, to improve the model's match to observations. Using this capability, good matches to in situ observations are obtained on a model of the complex Adour river network with fine zooms on floodplains.
Ludovic Räss, Ivan Utkin, Thibault Duretz, Samuel Omlin, and Yuri Y. Podladchikov
Geosci. Model Dev., 15, 5757–5786, https://doi.org/10.5194/gmd-15-5757-2022, https://doi.org/10.5194/gmd-15-5757-2022, 2022
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Continuum mechanics-based modelling of physical processes at large scale requires huge computational resources provided by massively parallel hardware such as graphical processing units. We present a suite of numerical algorithms, implemented using the Julia language, that efficiently leverages the parallelism. We demonstrate that our implementation is efficient, scalable and robust and showcase applications to various geophysical problems.
Meriem Krouma, Pascal Yiou, Céline Déandreis, and Soulivanh Thao
Geosci. Model Dev., 15, 4941–4958, https://doi.org/10.5194/gmd-15-4941-2022, https://doi.org/10.5194/gmd-15-4941-2022, 2022
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We evaluated the skill of a stochastic weather generator (SWG) to forecast precipitation at different time scales and in different areas of western Europe from analogs of Z500 hPa. The SWG has the skill to simulate precipitation for 5 and 10 d. We found that forecast weaknesses can be associated with specific weather patterns. The comparison with ECMWF forecasts confirms the skill of our model. This work is important because it provides information about weather forecasts over specific areas.
Cited articles
Alkhaled, A. A., Michalak, A. M., Olsen, S., Kawa, S. R., and Wang, J.-W.: A global evaluation of the regional spatial variability of column integrated CO2 distributions, J. Geophys. Res.-Atmos., 113, D20303, https://doi.org/10.1029/2007JD009693, 2008.
Atkinson, P. M. and Curran, P. J.: Defining an optimal size of support for remote sensing investigations, IEEE T. Geosci. Remote, 33, 768–776, 1995.
Basu, S., Guerlet, S., Butz, A., Houweling, S., Hasekamp, O., Aben, I., Krummel, P., Steele, P., Langenfelds, R., Torn, M., Biraud, S., Stephens, B., Andrews, A., and Worthy, D.: Global CO2 fluxes estimated from GOSAT retrievals of total column CO2, Atmos. Chem. Phys., 13, 8695–8717, https://doi.org/10.5194/acp-13-8695-2013, 2013.
Basu, S., Krol, M., Butz, A., Clerbaux, C., Sawa, Y., Machida, T., Matsueda, H., Frankenberg, C., HAsekamp, O. P., and Aben, I.: The seasonal variation of the CO2 flux over Tropical Asia estimated from GOSAT, CONTRAIL, and IASI, Geophys. Res. Lett., 41, 1809–1815, https://doi.org/10.1002/2013GL059105, 2014.
Braverman, A., Nguyen, H., Olsen, E., Miller, C., Cressie, N., Kratzfuss, M., Wang, R., and Michalak, A.: Geostatistical data fusion for remote sensing applications, NASA Annu. Rep., Apr. 2011, 2011 Report from the ESTO Advanced Information Systems Technology (AIST) Program, NASA, Greenbelt, MD, USA, 2011.
Chevallier, F., Palemer, P. I., Feng, L., Boesch, H., O'Dell, C. W., and Bousquet, P.: Toward robust and consistent regional CO2 flux estimates from in situ and spaceborne measurements of atmospheric CO2, Geophys. Res. Lett., 41, 1065–1070, https://doi.org/10.1002/2013GL058772, 2014.
Chiles, J.-P. and Delfiner, P.: Geostatistics, 2nd edn., Wiley, 2012.
CO2 DAAD: http://dge.stanford.edu/labs/michalaklab/CO2DAAD/XCO2maps.html (last access: 12 October 2015), 2014.
Collins, J. B. and Woodcock, C. E.: Geostatistical estimation of resolution-dependent variance in remotely sensed images, Photogramm. Eng. Rem. S., 65, 41–50, 1999.
Crevoisier, C., Chédin, A., Matsueda, H., Machida, T., Armante, R., and Scott, N. A.: First year of upper tropospheric integrated content of CO2 from IASI hyperspectral infrared observations, Atmos. Chem. Phys., 9, 4797–4810, https://doi.org/10.5194/acp-9-4797-2009, 2009.
Crisp, D., Fisher, B. M., O'Dell, C., Frankenberg, C., Basilio, R., Bösch, H., Brown, L. R., Castano, R., Connor, B., Deutscher, N. M., Eldering, A., Griffith, D., Gunson, M., Kuze, A., Mandrake, L., McDuffie, J., Messerschmidt, J., Miller, C. E., Morino, I., Natraj, V., Notholt, J., O'Brien, D. M., Oyafuso, F., Polonsky, I., Robinson, J., Salawitch, R., Sherlock, V., Smyth, M., Suto, H., Taylor, T. E., Thompson, D. R., Wennberg, P. O., Wunch, D., and Yung, Y. L.: The ACOS CO2 retrieval algorithm – Part II: Global XCO2 data characterization, Atmos. Meas. Tech., 5, 687–707, https://doi.org/10.5194/amt-5-687-2012, 2012.
Deng, F., Jones, D. B. A., Henze, D. K., Bousserez, N., Bowman, K. W., Fisher, J. B., Nassar, R., O'Dell, C., Wunch, D., Wennberg, P. O., Kort, E. A., Wofsy, S. C., Blumenstock, T., Deutscher, N. M., Griffith, D. W. T., Hase, F., Heikkinen, P., Sherlock, V., Strong, K., Sussmann, R., and Warneke, T.: Inferring regional sources and sinks of atmospheric CO2 from GOSAT XCO2 data, Atmos. Chem. Phys., 14, 3703–3727, https://doi.org/10.5194/acp-14-3703-2014, 2014.
Frankenberg, C., Fisher, J. B., Worden, J., Badgley, G., Saatchi, S. S., Lee, J.-E., Toon, G. C., Butz, A., Jung, M., Kuze, A., and Yokota, T.: New global observations of the terrestrial carbon cycle from GOSAT: patterns of plant fluorescence with gross primary productivity, Geophys. Res. Lett., 38, L17706, https://doi.org/10.1029/2011GL048738, 2011.
Frankenberg, C., O'Dell, C., Guanter, L., and McDuffie, J.: Remote sensing of near-infrared chlorophyll fluorescence from space in scattering atmospheres: implications for its retrieval and interferences with atmospheric CO2 retrievals, Atmos. Meas. Tech., 5, 2081–2094, https://doi.org/10.5194/amt-5-2081-2012, 2012.
Frankenberg, C., O'Dell, C., Berry, J., Guanter, L., Joiner, J., Köhler, P., Pollock, R., and Taylor, T. E.: Prospects for chlorophyll fluorescence remote sensing from the Orbiting Carbon Observatory-2, Remote Sens. Environ., 147, 1–12, https://doi.org/10.1016/j.rse.2014.02.007, 2014.
GOSAT Project: http://www.gosat.nies.go.jp/eng/gosat/page5.htm (last access: 12 October 2015), 2014.
Guanter, L., Frankenberg, C., Dudhia, A., Lewis, P. E., Gomez-Dans, J., Kuze, A., Suto, H., and Grainger, R. G.: Retrieval and global assessment of terrestrial chlorophyll fluorescence from GOSAT space measurements, Remote Sens. Environ., 121, 236–251, https://doi.org/10.1016/j.rse.2012.02.006, 2012.
Guerlet, S., Basu, S., Butz, A., Krol, M., Hahne, P., Houweling, S., Hasekamp, O. P., and Aben, I.: Reduced carbon uptake during the 2010 Northern Hemisphere summer from GOSAT, Geophys. Res. Lett., 40, 2378–2383, https://doi.org/10.1002/grl.50402, 2013.
Haas, T. C.: Lognormal and moving window methods of estimating acid deposition, J. Am. Stat. Assoc., 85, 950–963, 1990.
Hammerling, D. M., Michalak, A. M., and Kawa, S. R.: Mapping of CO2 at high spatiotemporal resolution using satellite observations: global distributions from OCO2, J. Geophys. Res., 117, D06306, https://doi.org/10.1029/2011JD017015, 2012a.
Hammerling, D. M., Michalak, A. M., O'Dell, C., and Kawa, S. R.: Global CO2 distributions over land from the Greenhouse Gases Observing Satellite (GOSAT), Geophys. Res. Lett., 39, L08804, https://doi.org/10.1029/2012GL051203, 2012b.
Harris, P., Charlton, M., and Fotheringham, A. S.: Moving window kriging with geographically weighted variograms, SERRA, 24, 1193–1209, 2010.
Huang, C., Zhang, H., and Robeson, S. M.: On the validity of commonly used covariance and variogram functions on the sphere, Math. Geosci., 43, MR2824128, 721–733, 2011.
Joiner, J., Yoshida, Y., Vasilkov, A. P., Yoshida, Y., Corp, L. A., and Middleton, E. M.: First observations of global and seasonal terrestrial chlorophyll fluorescence from space, Biogeosciences, 8, 637–651, https://doi.org/10.5194/bg-8-637-2011, 2011.
Joiner, J., Yoshida, Y., Vasilkov, A. P., Middleton, E. M., Campbell, P. K. E., Yoshida, Y., Kuze, A., and Corp, L. A.: Filling-in of near-infrared solar lines by terrestrial fluorescence and other geophysical effects: simulations and space-based observations from SCIAMACHY and GOSAT, Atmos. Meas. Tech., 5, 809–829, https://doi.org/10.5194/amt-5-809-2012, 2012.
Joiner, J., Guanter, L., Lindstrot, R., Voigt, M., Vasilkov, A. P., Middleton, E. M., Huemmrich, K. F., Yoshida, Y., and Frankenberg, C.: Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2, Atmos. Meas. Tech., 6, 2803–2823, https://doi.org/10.5194/amt-6-2803-2013, 2013.
Kulawik, S. S., Jones, D. B. A., Nassar, R., Irion, F. W., Worden, J. R., Bowman, K. W., Machida, T., Matsueda, H., Sawa, Y., Biraud, S. C., Fischer, M. L., and Jacobson, A. R.: Characterization of Tropospheric Emission Spectrometer (TES) CO2 for carbon cycle science, Atmos. Chem. Phys., 10, 5601–5623, https://doi.org/10.5194/acp-10-5601-2010, 2010.
Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T.: Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl. Optics, 48, 6716–6733, https://doi.org/10.1364/AO.48.006716, 2009.
Lee, J.-E., Frankenberg, C., van der Tol, C., Berry, J. A., Guanter, L., Boyce, C. K., Fisher, J. B., Morrow, E., Worden, J. R., Asefi, S., Badgley, G., and Saatchi, S.: Forest productivity and water stress in Amazonia: observations from GOSAT chlorophyll fluorescence, Proc. R. Soc. B, 280, 1762, https://doi.org/10.1098/rspb.2013.0171, 2013.
NASA Earth Science: http://science.nasa.gov/earth-science/earth-science-data/data-processing-levels-for-eosdis-data-products/ (last access: 12 October 2015), 2014.
O'Dell, C. W., Connor, B., Bösch, H., O'Brien, D., Frankenberg, C., Castano, R., Christi, M., Eldering, D., Fisher, B., Gunson, M., McDuffie, J., Miller, C. E., Natraj, V., Oyafuso, F., Polonsky, I., Smyth, M., Taylor, T., Toon, G. C., Wennberg, P. O., and Wunch, D.: The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations, Atmos. Meas. Tech., 5, 99–121, https://doi.org/10.5194/amt-5-99-2012, 2012.
Parazoo, N. C., Bowman, K., Frankenberg, C., Lee, J. E., Fisher, J. B., Worden, J., Jones, D. B. A., Berry, J., Collatz, G. J., Baker, I. T., Jung, M., Liu, J., and Osterman, G.: Interpreting seasonal changes in the carbon balance of southern Amazonia using measurements of XCO2 and chlorophyll fluorescence from GOSAT, Geophys. Res. Lett., 40, 2829–2833, https://doi.org/10.1002/grl.50452, 2013.
Takagi, H., Houweling, S., Andres, R. J., Belikov, D., Bril, A., Boesch, H., Butz, A., Guerlet, S., Hasekamp, O., Maksyutov, S., Morino, I., Oda, T., O'Dell, C. W., Oshchepkov, S., Parker, R., Saito, M., Uchino, O., Yokota, T., Yoshida, Y., and Valsala, V.: Influence of differences in current GOSAT XCO2 retrievals on surface flux estimation, Geophys. Res. Lett., 41, 2598–2605, https://doi.org/10.1002/2013GL059174, 2014.
Van Tooren, C. F. and Haas, T. C.: A site investigation strategy using moving window kriging and automated semivariogram modelling, in: Contaminated Soil '93, Kluwer Academic Press, Dordrecht, 609–622, 1993.
Walter, C., McBratney, A. B., Douaoui, A., and Minasny, B.: Spatial prediction of topsoil salinity in the Chelif Valley, Algeria, using local ordinary kriging with local variograms vs. whole-area variogram, Aust. J. Soil Res., 39, 259–272, 2001.
Webster, R.: Geostatistics for engineers and earth scientists, Eur. J. Soil Sci., 51, 541–549, https://doi.org/10.1046/j.1365-2389.2000.00334-9.x, 2000.