Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 9, 3919-3932, 2016
https://doi.org/10.5194/gmd-9-3919-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Development and technical paper
02 Nov 2016
A method for retrieving clouds with satellite infrared radiances using the particle filter
Dongmei Xu1,2, Thomas Auligné2, Gaël Descombes2, and Chris Snyder2 1Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China
2National Center for Atmospheric Research, Boulder, Colorado 80301, USA
Abstract. Ensemble-based techniques have been widely utilized in estimating uncertainties in various problems of interest in geophysical applications. A new cloud retrieval method is proposed based on the particle filter (PF) by using ensembles of cloud information in the framework of Gridpoint Statistical Interpolation (GSI) system. The PF cloud retrieval method is compared with the Multivariate Minimum Residual (MMR) method that was previously established and verified. Cloud retrieval experiments involving a variety of cloudy types are conducted with the PF and MMR methods with measurements of infrared radiances on multi-sensors onboard both geostationary and polar satellites, respectively. It is found that the retrieved cloud masks with both methods are consistent with other independent cloud products. MMR is prone to producing ambiguous small-fraction clouds, while PF detects clearer cloud signals, yielding closer heights of cloud top and cloud base to other references. More collections of small-fraction particles are able to effectively estimate the semi-transparent high clouds. It is found that radiances with high spectral resolutions contribute to quantitative cloud top and cloud base retrievals. In addition, a different way of resolving the filtering problem over each model grid is tested to better aggregate the weights with all available sensors considered, which is proven to be less constrained by the ordering of sensors. Compared to the MMR method, the PF method is overall more computationally efficient, and the cost of the model grid-based PF method scales more directly with the number of computing nodes.

Citation: Xu, D., Auligné, T., Descombes, G., and Snyder, C.: A method for retrieving clouds with satellite infrared radiances using the particle filter, Geosci. Model Dev., 9, 3919-3932, https://doi.org/10.5194/gmd-9-3919-2016, 2016.
Publications Copernicus
Download
Short summary
This study proposed a new cloud retrieval method based on the particle filter (PF). The PF cloud retrieval method is compared with the Multivariate and Minimum Residual (MMR) method that was previously established and verified. Cloud retrieval experiments involving a variety of cloudy types are conducted with the PF and MMR methods with measurements of Infrared radiances on multi-sensors onboard both GOES and MODIS, respectively.
This study proposed a new cloud retrieval method based on the particle filter (PF). The PF cloud...
Share