Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2018.06.011 |
An examination of microwave rainfall retrieval biases and their characteristics over the Amazon | |
Costa, Izabelly C.1; Machado, Luiz A. T.1; Kummerow, Christian2 | |
2018-11-15 | |
发表期刊 | ATMOSPHERIC RESEARCH
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ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2018 |
卷号 | 213页码:323-330 |
文章类型 | Article |
语种 | 英语 |
国家 | Brazil; USA |
英文摘要 | Estimates of surface precipitation obtained from passive microwave sensors over land are closely related to the ice path present in the clouds. However, there are cloud types without any ice or with an ice layer not thick enough to justify the associated rainfall. For these cloud types, the precipitation is not estimated correctly, causing an underestimation of the precipitation. On the other hand, there are cases of deep clouds, in which the signal produced by ice scattering is not effectively associated with precipitation, producing, in turn, an overestimate of rainfall. This study analyzes cases that have large errors in the rainfall estimates obtained from passive microwave data to better understand and potentially mitigate these biases. This study uses data from the Tropical Rainfall Measuring Mission (TRMM) satellite, specifically the Precipitation Radar (PR), TRMM Microwave Imager (TMI) and Lightning Imaging Sensor (US). Ten years of TRMM data (2002 - 2011) are used in the analysis. The study area is approximately 1,110,000 km(2), centered on the city of Manaus in the Amazon region. The error distribution resembled a Gaussian distribution. The error population was then divided into three categories, one class denominated as consistent, in the center of the distribution (20 percentile to 80 percentile), and the others two, as under- and over-estimated populations, representing the tails of the distribution. For under- and over-estimated categories, the vertical structure of the clouds was evaluated. The underestimation error is correlated with almost all cloud properties (rain rate, cloud top, Liquid Water path (LWP), Ice Water Path (IWP), polarization and Polarization Corrected Temperature at 85 GHZ (PCT85)) while the overestimation error is only function of the IWP. The use of combinations of low and high frequency channels was able to identify some characteristics associated with under- and over-estimated cases. A high positive difference between the 10 GHz and 85 GHz as well as 19 GHz - 85 GHz is characteristic of very high scattering at 85 GHz (high amount of ice) and small liquid water amounts corresponding to cases that are often overestimated by the radiometer. On the other hand, underestimated cases have smaller ice particles that are not sensitive to the high frequency microwaves channels measured by TMI. These results open potential new avenues to improve the quality of passive microwave rainfall estimates. |
英文关键词 | Satellite rainfall estimation Passive microwave rainfall estimation Satellite rainfall estimation errors |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000442169800027 |
WOS关键词 | PROFILING ALGORITHM ; SOUNDING UNIT ; PRECIPITATION ; TRMM ; CLOUD ; SURFACE ; SCATTERING ; EVOLUTION ; SENSORS ; RADAR |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/38510 |
专题 | 地球科学 |
作者单位 | 1.Natl Inst Space Res INPE, Ctr Weather Forecast & Climate Studies CPTEC, Rodovia Presidente Dutra,Km 40, Sao Paulo, Brazil; 2.Colorado State Univ, Dept Atmospher Sci, Ft Collins, CO 80523 USA |
推荐引用方式 GB/T 7714 | Costa, Izabelly C.,Machado, Luiz A. T.,Kummerow, Christian. An examination of microwave rainfall retrieval biases and their characteristics over the Amazon[J]. ATMOSPHERIC RESEARCH,2018,213:323-330. |
APA | Costa, Izabelly C.,Machado, Luiz A. T.,&Kummerow, Christian.(2018).An examination of microwave rainfall retrieval biases and their characteristics over the Amazon.ATMOSPHERIC RESEARCH,213,323-330. |
MLA | Costa, Izabelly C.,et al."An examination of microwave rainfall retrieval biases and their characteristics over the Amazon".ATMOSPHERIC RESEARCH 213(2018):323-330. |
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