Representation of Dropsonde-Observed Atmospheric River Conditions in Reanalyses

被引:22
作者
Cobb, A. [1 ]
Delle Monache, L. [1 ]
Cannon, F. [1 ]
Ralph, F. M. [1 ]
机构
[1] Univ Calif San Diego, Scripps Inst Oceanog, Ctr Western Weather & Water Extremes CW3E, La Jolla, CA 92093 USA
关键词
atmospheric river; dropsonde observations; ERA5; MERRA-2; JRA-55; reanalysis; US WEST-COAST; HIGH-RESOLUTION; INTENSITY; IMPACT; IMPLEMENTATION; ASSIMILATION; STRENGTH;
D O I
10.1029/2021GL093357
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Atmospheric rivers (ARs) are the primary mechanism for mid-latitude water vapor transport, and are identified by a key variable, integrated water vapor transport (IVT). The ability of atmospheric reanalyses in providing a ground-truth dataset for the IVT field is assessed by comparing ERA5, MERRA-2, and JRA-55 data against a large sample (>1,700) of dropsonde profiles deployed in and around ARs. Bias and error increase with IVT magnitude, although asymmetrically around the AR core. A partitioning of the source of error reveals that humidity contributes more to the difference in IVT above 800 hPa, while wind is the dominant source in the lowest levels (to 950 hPa). This quantification of reanalysis error and bias identifies ERA5 as the dataset with the lowest IVT errors and demonstrates remaining challenges in representing the observed state in ARs.
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页数:11
相关论文
共 63 条
[1]   Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT [J].
Belmonte Rivas, Maria ;
Stoffelen, Ad .
OCEAN SCIENCE, 2019, 15 (03) :831-852
[2]  
Bosilovich M. G., 2016, MERRA 2 FILE SPECIFI, V9
[3]   Twentieth-century atmospheric river activity along the west coasts of Europe and North America: algorithm formulation, reanalysis uncertainty and links to atmospheric circulation patterns [J].
Brands, S. ;
Gutierrez, J. M. ;
San-Martin, D. .
CLIMATE DYNAMICS, 2017, 48 (9-10) :2771-2795
[4]   Observations and Predictability of a High-Impact Narrow Cold-Frontal Rainband over Southern California on 2 February 2019 [J].
Cannon, Forest ;
Oakley, Nina S. ;
Hecht, Chad W. ;
Michaelis, Allison ;
Cordeira, Jason M. ;
Kawzenuk, Brian ;
Demirdjian, Reuben ;
Weihs, Rachel ;
Fish, Meredith A. ;
Wilson, Anna M. ;
Ralph, F. Martin .
WEATHER AND FORECASTING, 2020, 35 (05) :2083-2097
[5]   Predictability of Extreme Precipitation in Western US Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration [J].
Chen, Xiaodong ;
Leung, L. Ruby ;
Gao, Yang ;
Liu, Ying ;
Wigmosta, Mark ;
Richmond, Marshall .
GEOPHYSICAL RESEARCH LETTERS, 2018, 45 (21) :11693-11701
[6]  
Climate Prediction Division Global Environment and Marine Department Japan Meteorological Agency, 2013, JRA 55 PROD US HDB 1 JRA 55 PROD US HDB 1
[7]  
Cobb A., 2020, MON WEATHER REV, V1
[8]   Atmospheric rivers drive flood damages in the western United States [J].
Corringham, Thomas W. ;
Ralph, F. Martin ;
Gershunov, Alexander ;
Cayan, Daniel R. ;
Talbot, Cary A. .
SCIENCE ADVANCES, 2019, 5 (12)
[9]   The ERA-Interim reanalysis: configuration and performance of the data assimilation system [J].
Dee, D. P. ;
Uppala, S. M. ;
Simmons, A. J. ;
Berrisford, P. ;
Poli, P. ;
Kobayashi, S. ;
Andrae, U. ;
Balmaseda, M. A. ;
Balsamo, G. ;
Bauer, P. ;
Bechtold, P. ;
Beljaars, A. C. M. ;
van de Berg, L. ;
Bidlot, J. ;
Bormann, N. ;
Delsol, C. ;
Dragani, R. ;
Fuentes, M. ;
Geer, A. J. ;
Haimberger, L. ;
Healy, S. B. ;
Hersbach, H. ;
Holm, E. V. ;
Isaksen, L. ;
Kallberg, P. ;
Koehler, M. ;
Matricardi, M. ;
McNally, A. P. ;
Monge-Sanz, B. M. ;
Morcrette, J. -J. ;
Park, B. -K. ;
Peubey, C. ;
de Rosnay, P. ;
Tavolato, C. ;
Thepaut, J. -N. ;
Vitart, F. .
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2011, 137 (656) :553-597
[10]   Dropsonde Observations of the Ageostrophy within the Pre-Cold-Frontal Low-Level Jet Associated with Atmospheric Rivers [J].
Demirdjian, Reuben ;
Norris, Joel R. ;
Martin, Andrew ;
Ralph, F. Martin .
MONTHLY WEATHER REVIEW, 2020, 148 (04) :1389-1406