What does CloudSat reveal about global land precipitation detection by other spaceborne sensors?

被引:68
作者
Behrangi, Ali [1 ]
Tian, Yudong [2 ,3 ]
Lambrigtsen, Bjorn H. [1 ]
Stephens, Graeme L. [1 ]
机构
[1] CALTECH, Jet Prop Lab, Pasadena, CA 91125 USA
[2] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20742 USA
[3] NASA, Goddard Space Flight Ctr, Hydrol Sci Lab, Greenbelt, MD 20771 USA
关键词
PASSIVE MICROWAVE; UNITED-STATES; SATELLITE; RADAR; WATER; RAIN; INFORMATION; ALGORITHM; AMSU;
D O I
10.1002/2013WR014566
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Current orbital land precipitation products have serious shortcomings in detecting light rain and snowfall, the most frequent types of global precipitation. The missed precipitation is then propagated into the merged precipitation products that are widely used. Precipitation characteristics such as frequency and intensity and their regional distribution are expected to change in a warming climate. It is important to accurately capture those characteristics to understand and model the current state of the Earth's climate and predict future changes. In this work, the precipitation detection performance of a suite of precipitation sensors, commonly used in generating the merged precipitation products, are investigated. The high sensitivity of CloudSat Cloud Profiling Radar (CPR) to liquid and frozen hydrometeors enables superior estimates of light rainfall and snowfall within 80 degrees S-80 degrees N. Three years (2007-2009) of CloudSat precipitation data were collected to construct a climatology reference for guiding our analysis. In addition, auxiliary data such as infrared brightness temperature, surface air temperature, and cloud types were used for a more detailed assessment. The analysis shows that no more than 50% of the tropical (40 degrees S-40 degrees N) precipitation occurrence is captured by the current suite of precipitation measuring sensors. Poleward of 50 degrees latitude, a combination of various factors such as an abundance of light rainfall, snowfall, shallow precipitation-bearing clouds, and frozen surfaces reduces the space-based precipitation detection rate to less than 20%. This shows that for a better understanding of precipitation from space, especially at higher latitudes, there is a critical need to improve current precipitation retrieval techniques and sensors.
引用
收藏
页码:4893 / 4905
页数:13
相关论文
共 77 条
  • [1] Adler R., 2004, AMSR E AQUA L2B GLOB
  • [2] Adler RF, 2003, J HYDROMETEOROL, V4, P1147, DOI 10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO
  • [3] 2
  • [4] Evaluation of satellite-retrieved extreme precipitation rates across the central United States
    AghaKouchak, A.
    Behrangi, A.
    Sorooshian, S.
    Hsu, K.
    Amitai, E.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2011, 116
  • [5] [Anonymous], 2011, INT GEOPHYS, DOI DOI 10.1016/B978-0-12-385022-5.00008-7
  • [6] On the quantification of oceanic rainfall using spaceborne sensors
    Behrangi, Ali
    Lebsock, Matthew
    Wong, Sun
    Lambrigtsen, Bjorn
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2012, 117
  • [7] REFAME: Rain Estimation Using Forward-Adjusted Advection of Microwave Estimates
    Behrangi, Ali
    Imam, Bisher
    Hsu, Kuolin
    Sorooshian, Soroosh
    Bellerby, Timothy J.
    Huffman, George J.
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2010, 11 (06) : 1305 - 1321
  • [8] Hydrologic evaluation of satellite precipitation products over a mid-size basin
    Behrangi, Ali
    Khakbaz, Behnaz
    Jaw, Tsou Chun
    AghaKouchak, Amir
    Hsu, Kuolin
    Sorooshian, Soroosh
    [J]. JOURNAL OF HYDROLOGY, 2011, 397 (3-4) : 225 - 237
  • [9] Daytime Precipitation Estimation Using Bispectral Cloud Classification System
    Behrangi, Ali
    Hsu, Koulin
    Imam, Bisher
    Sorooshian, Soroosh
    [J]. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2010, 49 (05) : 1015 - 1031
  • [10] PERSIANN-MSA: A Precipitation Estimation Method from Satellite-Based Multispectral Analysis
    Behrangi, Ali
    Hsu, Kuo-Lin
    Imam, Bisher
    Sorooshian, Soroosh
    Huffman, George J.
    Kuligowski, Robert J.
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2009, 10 (06) : 1414 - 1429