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cloud parameters Retrieved by the Bispectral Reflectance Algorithm and Associated Applications

Journal of Meteorological Research 2014年第5期28卷 965-982页

作者：傅云飞 School of Earth and Space Sciences University of Science and Technology of China State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences

Retrieval of cloud parameters is fundamental for descriptions of the cloud process in weather and cloud models, and is also the base for theoretical and applicational investigations on weather modification, aerosol- cloud-precipitation interaction, cloud-radiative climate effects, and so on. However, it is still difficult to ob- rain full information of cloud parameters over a wide area under the current level of science and technology. Luckily, parameters at the top of clouds can be retrieved with the satellite spectrum remote sensing, which is useful in obtaining global cloud properties. In this paper, cloud parameters retrieved by the bispectral reflectance （BSR） method and other methods developed on the basis of the BSR are briefly summarized. Recent advances in studies on the indirect effects of aerosol on cloud parameters are reviewed. The rela- tionships among cloud parameters and precipitation intensity, type, and structure are elaborated on, based upon the pixel-level merged datasets derived from daily measurements of precipitation radar and visible and infrared scanner, together with cloud parameters retrieved by the BSR. It is revealed that cloud particle effective radius and liquid water path near cloud tops are effective to identify the thickness and intensity of convective precipitating clouds. Furthermore, the differences in cloud parameters and precipitation intensity for precipitating and non-precipitating clouds over land and ocean are compared in this paper.

关键词： cloud parameters bispectral reflectance method aerosol precipitation

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Daytime precipitation identification scheme based on multiple cloud parameters retrieved from visible and infrared measurements

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Science China Earth Sciences 2014年第9期57卷 2112-2124页

作者： LIU XianTong LIU Qi FU YunFei LI Rui Key Laboratory of the Atmospheric Composition and Optical Radiation Chinese Academy Sciences School of Earth and Space SciencesUniversity of Science and Technology of China Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction China Meteorological Administration

Visible and infrared(VIR) measurements and the retrieved cloud parameters are commonly used in precipitation identification algorithms, since the VIR observations from satellites, especially geostationary satellites, have high spatial and temporal resolutions. Combined measurements from visible/infrared scanner(VIRS) and precipitation radar(PR) aboard the Tropical Rainfall Measuring Mission(TRMM) satellite are analyzed, and three cloud parameters, i.e., cloud optical thickness(COT), effective radius(Re), and brightness temperature of VIRS channel 4(BT4), are particularly considered to characterize the cloud status. By associating the information from VIRS-derived cloud parameters with those from precipitation detected by PR, we propose a new method for discriminating precipitation in daytime called Precipitation Identification Scheme from cloud parameters information(PISCP). It is essentially a lookup table(LUT) approach that is deduced from the optimal equitable threat score(ETS) statistics within 3-dimensional space of the chosen cloud parameters. South and East China is selected as a typical area representing land surface, and the East China Sea and Yellow Sea is selected as typical oceanic area to assess the performance of the new scheme. It is proved that PISCP performs well in discriminating precipitation over both land and oceanic areas. Especially, over ocean, precipitating clouds(PCs) and non-precipitating clouds(N-PCs) are well distinguished by PISCP, with the probability of detection(POD) near 0.80, the probability of false detection(POFD) about 0.07, and the ETS higher than 0.43. The overall spatial distribution of PCs fraction estimated by PISCP is consistent with that by PR, implying that the precipitation data produced by PISCP have great potentials in relevant applications where radar data are unavailable.

关键词： precipitation identification cloud parameters Tropical Rainfall Measuring Mission(TRMM)

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A cloud parameters Retrieval Algorithm in the Variational Assimilation System

A Cloud Parameters Retrieval Algorithm in the Variational As...

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2012年计算机应用与系统建模国际会议

作者： Huang Qunbo Zhang Weimin Yu Yi School of computer science National University of defense technology NO.94865 Troops Chinese People's Liberation Army

According to the past experience of retrieving cloud parameters, the assimilation of cloud-affected infrared radiances is a difficult problem in the numerical weather prediction. Based on our own four-dimensional variational assimilation (4D-Var) system’s characteristics, we have designed our own cloud-affected infrared satellite radiances variational assimilation system which includes a one-dimensional variational assimilation (1D-Var) retrieval algorithm of cloud parameters. In this system, cloud parameters are considered as the intermediary to constrain the radiative transfer calculation after they are passed to our 4D-Var system. Consequently, acquiring the accurate cloud parameters is the key step of the assimilation of cloud-affected infrared radiances. This article analyzes the 1D-Var algorithm which is used to retrieve cloud parameters in our variational data assimilation system and validates the good performance of this method.

关键词： cloud parameters 1D-Var 4D-Var

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MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER cloudY CONDITIONS: METHODS AND IDEAL TESTS

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Journal of Tropical Meteorology 2010年第4期16卷 313-324页

作者：丁伟钰万齐林张诚忠陈子通黄燕燕 Guangzhou Institute of Tropical and Marine Meteorology China Meteorological Administration

clouds have important effects on the infi＇ared radiances transmission in that the inclusion of cloud effects in data assimilation can not only improve the quality of the assimilated atmospheric parameters greatly, but also minimize the initial error of cloud parameters by adjusting part of the infrared radiances data. On the basis of the Grapes-3D-var （Global and Regional Assimilation and Prediction Enhanced System）, cloud liquid water, cloud ice water and cloud cover are added as the governing variables in the assimilation. Under the conditions of clear sky, partly cloudy cover and totally cloudy cover, the brightness temperature of 16 MODIS channels are assimilated respectively in ideal tests. Results show that when the simulated background brightness temperatures are lower than the observation, the analyzed field will increase the simulated brightness temperature by increasing its temperature and reducing its moisture, cloud liquid water, cloud ice water, and cloud cover. The simulated brightness temperature can be reduced if adjustment is made in the contrary direction. The adjustment of the temperature and specific humidity under the clear sky conditions conforms well to the design of MODIS channels, but it is weakened for levels under cloud layers. The ideal tests demonstrate that by simultaneously adding both cloud parameters and atmospheric parameters as governing variables during the assimilation of infrared radiances, both the cloud parameters and atmospheric parameters can be adjusted using the observed infrared radiances and conventional meteorological elements to make full use of the infrared observations.

关键词： cloud parameters MODIS brightness temperature data assimilation

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