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Potential caveats in land surface model evaluations using the US drought monitor

Roles of base periods and drought indicators

Bibliographic Data

ID15545362
AuthorsHailan Wang (0000-0001-7320-247X, NOAA Climate Prediction Center, corresponding author), Li Xu (0000-0001-5665-4861, NOAA Climate Prediction Center), Mimi Hughes (0000-0002-4554-9289, NOAA Physical Sciences Laboratory), Muthuvel Chelliah (NOAA Climate Prediction Center), David G DeWitt (NOAA Climate Prediction Center), Brian Fuchs (0000-0001-7725-084X), Brian A Fuchs, Darren L Jackson (0000-0001-5211-7866, Cooperative Institute for Research in Environmental Sciences)
Year2021
Volume17
Issue1
Pages014011-014011
Publication date2021-12-07
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/ac3f63
OpenAlexW4200254004
LanguageEN
Citations received1
References cited29

The US drought monitor (USDM) has been widely used as an observational reference for evaluating land surface model (LSM) simulation of drought. This study investigates potential caveats in such evaluation when the USDM and LSMs use different base periods and drought indices to identify drought. The retrospective national water model (NWM) v2.0 simulation (1993–2018) was used to exemplify the evaluation, supplemented by North American land data assimilation system phase 2 (NLDAS-2). Over their common period (2000–2018), in distinct contrast with the USDM which shows high drought occurrence (>50%) in the western half of the continental US (CONUS) and the southeastern US with low occurrence (<30%) elsewhere, the NWM and NLDAS-2 based on soil moisture percentiles (SMPs) consistently show higher drought occurrence (30%–40%) in the central and southeastern US than the rest of the CONUS. Much of the differences between the LSMs and USDM, particularly the strong LSM underestimation of drought occurrence in the western and southeastern US, are not attributed to the LSM deficiencies, but rather the lack of long-term drought in the LSM simulations due to their relatively short lengths. Specifically, the USDM integrates drought indices with century-long periods of record, which enables it to capture both short-term (<6 months) drought and long-term (⩾6 months) drought, whereas the relatively short retrospective simulations of the LSMs allows them to adequately capture short-term drought but not long-term drought. In addition, the USDM integrates many drought indices whereas the NWM results are solely based on the SMP, further adding to the inconsistency. The high occurrence of long-term drought in the western and southeastern US in the USDM is further found to be driven collectively by the post-2000 long-term warm sea surface temperature (SST) trend, cold Pacific decadal oscillation and warm Atlantic multi-decadal oscillation, all of which are typical leading patterns of global SST variability that can induce drought conditions in the western, central, and southeastern US. Our findings highlight the effects of the above caveats and suggest that LSM evaluation should stay qualitative when the caveats are considerable

Climatology · Data assimilation · Geography · Meteorology · Percentile · Statistics · Term (time · Climate variability and models · Environmental Science · Hydrology and Drought Analysis · Hydrology and Watershed Management Studies · Mathematics · Geology

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Unique citing works1
Citations per year1
Citation span2025 - 2025 (1)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 1

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