Validation of GSMaP Products for a Heavy Rainfall Event over Complex Terrain in Mongolia Captured by the GPM Core Observatory

被引:1
|
作者
Komatsu, Kensuke K. [1 ,2 ]
Iijima, Yoshihiro [3 ]
Kaneko, Yuki [4 ]
Oyunbaatar, Dambaravjaa [5 ]
机构
[1] Univ Tokyo, Atmosphere & Ocean Res Inst, Kashiwa, Chiba, Japan
[2] Japan Meteorol Agcy, Meteorol Res Inst, Tsukuba, Ibaraki, Japan
[3] Mie Univ, Grad Sch Bioresources, 1577 Kurima Machiya Cho, Tsu, Mie 5148507, Japan
[4] Japan Aerosp Explorat Agcy, Earth Observat Res Ctr, Tsukuba, Ibaraki, Japan
[5] Informat & Res Inst Meteorol Hydrol & Environm, Ulaanbaatar, Mongolia
关键词
Global Satellite Mapping of Precipitation; precipitation dataset; orographic classification; gauge calibration; Ulaanbaatar; PASSIVE MICROWAVE; PRECIPITATION; ALGORITHM; IMPROVEMENT; RETRIEVALS; PROJECT; BASIN;
D O I
10.2151/jmsj.2021-048
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This paper focuses on the uncertainty of summer precipitation estimations produced by Global Satellite Mapping of Precipitation (GSMaP) over Mongolia, a region with complex terrain and sparse weather observation networks. We first compared the average summer precipitation over Mongolian territory as reported by several precipitation products. Although the interannual variability of the product was comparable, the amount of recorded precipitation differed among various products. The rain gauge-based analysis reported the lowest amount of precipitation, whereas the satellite-based GSMaP_MVK (Moving Vector algorithm with Kalman filter) reported the highest amount. Our results represent the first estimate of the characteristic differences among various precipitation-monitoring products, including Global Precipitation Measurement (GPM)-based products, as they relate to climatic and hydrometeorological assessments in Mongolia. We then performed a detailed comparison using a case study, in which a heavy rainfall event was captured by the GPM mission's core observatory near Ulaanbaatar in July 2016. In this case, gauged and ungauged GSMaP estimates of the precipitation over the mountain area significantly differed between algorithm versions 6 and 7. An intercomparison of atmospheric numerical modeling, the GPM core observatory, and rain gauge observation revealed that the rain gauge calibration of GSMaP effectively moderates the large error of the ungauged GSMaP data. The source of the significant ungauged GSMaP error is likely to be the rain rate estimates in algorithm version 7. However, the GSMaP gauge-calibrated estimates of the precipitation over mountainous areas may be affected by a potential underestimation of gauge analysis due to the missing localized precipitation occurring in the large gaps of the routine observation network. We expect that these findings will be helpful for developers aiming to further improve the GSMaP algorithm.
引用
收藏
页码:1003 / 1022
页数:20
相关论文
共 27 条
  • [1] Validation of high-resolution satellite rainfall products over complex terrain
    Dinku, T.
    Chidzambwa, S.
    Ceccato, P.
    Connor, S. J.
    Ropelewski, C. F.
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2008, 29 (14) : 4097 - 4110
  • [2] Assessment of GPM and SM2RAIN-ASCAT rainfall products over complex terrain in southern Italy
    Chiaravalloti, Francesco
    Brocca, Luca
    Procopio, Antonio
    Massari, Christian
    Gabriele, Salvatore
    [J]. ATMOSPHERIC RESEARCH, 2018, 206 : 64 - 74
  • [3] Validation of the GPM Version-5 Surface Rainfall Products over Great Britain and Ireland
    Watters, Daniel
    Battaglia, Alessandro
    Mroz, Kamil
    Tridon, Frederic
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2018, 19 (10) : 1617 - 1636
  • [4] Validation of GPM Dual-Frequency Precipitation Radar (DPR) Rainfall Products over Italy
    Petracca, M.
    D'Adderio, L. P.
    Porcu, F.
    Vulpiani, G.
    Sebastianelli, S.
    Puca, S.
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2018, 19 (05) : 907 - 925
  • [5] Validation of the Version 05 Level 2 precipitation products from the GPM Core Observatory and constellation satellite sensors
    Kidd, Christopher
    Tan, Jackson
    Kirstetter, Pierre-Emmanuel
    Petersen, Walter A.
    [J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2018, 144 : 313 - 328
  • [6] Ground Validation of GPM IMERG Rainfall Products over the Capital Circle in Northeast China on Rainstorm Monitoring
    Sun, Wei
    Sun, Yonghua
    Zhang, Youquan
    Qiu, Qi
    Wang, Tao
    Wang, Yanbing
    [J]. REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XX, 2018, 10783
  • [7] Evaluation of GPM-era Global Satellite Precipitation Products over Multiple Complex Terrain Regions
    Derin, Yagmur
    Anagnostou, Emmanouil
    Berne, Alexis
    Borga, Marco
    Boudevillain, Brice
    Buytaert, Wouter
    Chang, Che-Hao
    Chen, Haonan
    Delrieu, Guy
    Hsu, Yung Chia
    Lavado-Casimiro, Waldo
    Manz, Bastian
    Moges, Semu
    Nikolopoulos, Efthymios I.
    Sahlu, Dejene
    Salerno, Franco
    Rodriguez-Sanchez, Juan-Pablo
    Vergara, Humberto J.
    Yilmaz, Koray K.
    [J]. REMOTE SENSING, 2019, 11 (24)
  • [8] Polarimetric radar measurements and rainfall performance during an extreme rainfall event in complex terrain over Eastern China
    Gou, Yabin
    Wang, Zhangwei
    Hu, Yunli
    Chen, Haonan
    He, Jieying
    [J]. IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 5337 - 5340
  • [9] Validation of satellite rainfall products over East Africa's complex topography
    Dinku, T.
    Ceccato, P.
    Grover-Kopec, E.
    Lemma, M.
    Connor, S. J.
    Ropelewski, C. F.
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2007, 28 (7-8) : 1503 - 1526
  • [10] Spatio-attention-based network to improve heavy rainfall prediction over the complex terrain of Assam
    Dhananjay Trivedi
    Omveer Sharma
    Sandeep Pattnaik
    [J]. Neural Computing and Applications, 2024, 36 (19) : 11257 - 11273