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Anthony M. DeAngelis, Hailan Wang, Randal D. Koster, Siegfried D. Schubert, Yehui Chang, and Jelena Marshak

data.) The GEOS atmospheric model is similar to that used for the Modern-Era Retrospective Analysis for Research Applications, version 2 (MERRA-2) ( Molod et al. 2015 , 2020 ). The land surface model (LSM) in GEOS is the catchment-based LSM that is also used for MERRA-2 and is documented in Koster et al. (2000) . The ocean component is the Modular Ocean Model, version 5 (MOM5), that was developed at the Geophysical Fluid Dynamics Laboratory ( Griffies et al. 2005 ; Griffies 2012 ), and the sea

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Chul-Su Shin, Bohua Huang, Paul A. Dirmeyer, Subhadeep Halder, and Arun Kumar

reforecasts reproduce selected severe drought events that occurred during 1979–2010. We also examine the role of realistic representation of land initial states in improving drought prediction in the United States using a case study of the drought in the winter of 1999. Section 2 describes the coupled forecast system, the identical-twin experiments, and verification data. Predictive skill of precipitation indices and prediction of U.S. severe drought events for 32 years are evaluated in sections 3 and

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Keyhan Gavahi, Peyman Abbaszadeh, Hamid Moradkhani, Xiwu Zhan, and Christopher Hain

atmospheric data such as precipitation and relative humidity, or land surface data acquisition such as SM and ET. The latter can be indirectly assimilated into the land surface models to achieve more accurate and reliable predictions of hydrologic fluxes as well as for monitoring purposes ( Kumar et al. 2014 ; Pan and Wood 2006 ; Pipunic et al. 2008 ; Reichle et al. 2014 ; Sawada et al. 2015 ; Xu et al. 2020 ). SM prediction using land surface models driven by meteorological forcing carries

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Shanshui Yuan, Steven M. Quiring, and Chen Zhao

inhibition; enhancing the probability of convective precipitation over drier soils ( Ford et al. 2015a , 2018 ; Tuttle and Salvucci 2016 ). Hence, soil moisture is a critical variable for both characterizing drought conditions and for investigating land–atmosphere interactions. Drought indices have been used to characterize near-surface moisture conditions in some land–atmosphere interaction studies because of the lack of available soil moisture measurements. For example, Hirschi et al. (2010) used

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David M. Mocko, Sujay V. Kumar, Christa D. Peters-Lidard, and Shugong Wang

Abstract

This study presents an evaluation of the impact of vegetation conditions on a land-surface model (LSM) simulation of agricultural drought. The Noah-MP LSM is used to simulate water and energy fluxes and states, which are transformed into drought categories using percentiles over the continental U.S. from 1979 to 2017. Leaf Area Index (LAI) observations are assimilated into the dynamic vegetation scheme of Noah-MP. A weekly operational drought monitor (the U.S. Drought Monitor) is used for the evaluation. The results show that LAI assimilation into Noah-MP’s dynamic vegetation scheme improves the model's ability to represent drought, particularly over cropland areas. LAI assimilation improves the simulation of the drought category, detection of drought conditions, and reduces the instances of drought false alarms. The assimilation of LAI in these locations not only corrects model errors in the simulation of vegetation, but also can help to represent unmodeled physical processes such as irrigation towards improved simulation of agricultural drought.

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Wen-Ying Wu, Zong-Liang Yang, and Michael Barlage

Abstract

Texas is subject to severe droughts, including the record-breaking one in 2011. To investigate the critical hydrometeorological processes during drought, we use a land surface model, Noah-MP, to simulate water availability and investigate the causes of the record drought. We conduct a series of experiments with runoff schemes, vegetation phenology, and plant rooting depth. Observation-based terrestrial water storage, evapotranspiration, runoff, and leaf area index are used to compare with results from the model. Overall, the results suggest that using different parameterizations can influence the modeled water availability, especially during drought. The drought-induced vegetation responses not only interact with water availability but also affect the ground temperature. Our evaluation shows that Noah-MP with a groundwater scheme produces a better temporal relationship in terrestrial water storage compared with observations. Leaf area index from dynamic vegetation is better simulated in wet years than dry years. Reduction of positive biases in runoff and reduction of negative biases in evapotranspiration are found in simulations with groundwater, dynamic vegetation, and deeper rooting zone depth. Multi-parameterization experiments show the uncertainties of drought monitoring and provide a mechanistic understanding of disparities in dry anomalies.

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Lu Su, Qian Cao, Mu Xiao, David M. Mocko, Michael Barlage, Dongyue Li, Christa D. Peters-Lidard, and Dennis P. Lettenmaier

Abstract

We examine the drought variability over the Conterminous United States (CONUS) for 1915-2018 using the Noah-MP land-surface model. We examine different model options on drought reconstruction including optional representation of groundwater and dynamic vegetation phenology. Over our 104-year reconstruction period, we identify 12 great droughts that each covered at least 36% of CONUS and lasted for at least 5 months. The great droughts tend to have smaller areas when groundwater and/or dynamic vegetation are included in the model configuration. We detect a small decreasing trend in dry area coverage over CONUS in all configurations. We identify 45 major droughts in the baseline (with a dry area coverage greater than 23.6% of CONUS) that are, on average, somewhat less severe than great droughts. We find that representation of groundwater tends to increase drought duration for both great and major droughts, primarily by leading to earlier drought onset (some due to short-lived recovery from a previous drought) or later demise (groundwater anomalies lag precipitation anomalies). In contrast, representation of dynamic vegetation tends to shorten major droughts duration, primarily due to earlier drought demise ( closed stoma or dead vegetation reduces ET loss during droughts). On a regional basis, the U.S. Southwest (Southeast) has the longest (shortest) major drought durations. Consistent with earlier work, dry area coverage in all subregions except the Southwest has decreased. The effects of groundwater and dynamic vegetation vary regionally due to differences in groundwater depths (hence connectivity with the surface) and vegetation types.

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Chul-Su Shin, Paul A. Dirmeyer, Bohua Huang, Subhadeep Halder, and Arun Kumar

. 2015 ; Al-Yaari et al. 2017 ; Reichle et al. 2019 ). A number of recent studies have investigated weather and climate models’ ability to accurately represent various aspects of land–atmosphere coupled processes in nature using much improved datasets of land surface states in terms of their spatial and temporal coverage and quality (e.g., Trigo et al. 2015 ; Levine et al. 2016 ; Dirmeyer et al. 2016 , 2018a ). In this paper, we introduce “identical twin” sets of 32-yr (1979–2010) reforecasts

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Kingtse C. Mo and Dennis P Lettenmaier

P -deficit flash droughts following Mo and Lettenmaier (2015 , 2016) . 2. Flash drought forecasts As indicated by Pendergrass et al. (2020) , prediction of flash drought is a challenge because of their rapid onset, and the fact that most land–atmosphere coupled models do not predict land atmosphere interactions well. An alternative is to use statistical methods; for instance, Otkin et al. (2015) predicted flash drought intensification probabilities derived from their RCI. Here, we prefer to

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Yaling Liu, Dongdong Chen, Soukayna Mouatadid, Xiaoliang Lu, Min Chen, Yu Cheng, Zhenghui Xie, Binghao Jia, Huan Wu, and Pierre Gentine

Agency (ESA) Climate Change Initiative (CCI) soil moisture product provides harmonized global daily SM for the period of 1978–2017, by combining various single-sensor active and passive microwave soil moisture products ( Dorigo et al. 2017 ). Meanwhile, LSMs also simulate soil moisture at large scale. For instance, the Variable Infiltration Capacity (VIC) land surface model has been used to estimate global SM ( Nijssen et al. 2001 ). Nonetheless, satellite SM retrievals are usually jeopardized by

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