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Sensitivity of U.S. Drought Prediction Skill to Land Initial States

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  • 1 Department of Atmospheric, Oceanic and Earth Sciences, Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, Virginia
  • | 2 K. Banerjee Centre of Atmospheric and Ocean Studies, University of Allahabad, Allahabad, Uttar Pradesh, India
  • | 3 NOAA/National Centers for Environmental Prediction/Climate Prediction Center, College Park, Maryland
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Abstract

In addition to remote SST forcing, realistic representation of land forcing (i.e., soil moisture) over the United States is critical for a prediction of U.S. severe drought events approximately one season in advance. Using “identical twin” experiments with different land initial conditions (ICs) in the 32-yr (1979–2010) CFSv2 reforecasts (NASA GLDAS-2 reanalysis versus NCEP CFSR), sensitivity and skill of U.S. drought predictions to land ICs are evaluated. Although there is no outstanding performer between the two sets of forecasts with different land ICs, each set shows greater skill in some regions, but their locations vary with forecast lead time and season. The 1999 case study demonstrates that although a pattern of below-normal SSTs in the Pacific in the fall and winter is realistically reproduced in both reforecasts, GLDAS-2 land initial states display a stronger east–west gradient of soil moisture, particularly drier in the eastern United States and more consistent with observations, leading to warmer surface temperature anomalies over the United States. Anomalies lasting for one season are accompanied by more persistent barotropic (warm core) anomalous high pressure over CONUS, which results in better prediction skill of this drought case up to 4 months in advance in the reforecasts with GLDAS-2 land ICs. Therefore, it is essential to minimize the uncertainty of land initial states among the current land analyses for improving U.S. drought prediction on seasonal time scales.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JHM-D-20-0025.s1.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Chul-Su Shin, cshin3@gmu.edu

This article has a companion article which can be found at http://journals.ametsoc.org/doi/abs/10.1175/JHM-D-20-0024.1.

Abstract

In addition to remote SST forcing, realistic representation of land forcing (i.e., soil moisture) over the United States is critical for a prediction of U.S. severe drought events approximately one season in advance. Using “identical twin” experiments with different land initial conditions (ICs) in the 32-yr (1979–2010) CFSv2 reforecasts (NASA GLDAS-2 reanalysis versus NCEP CFSR), sensitivity and skill of U.S. drought predictions to land ICs are evaluated. Although there is no outstanding performer between the two sets of forecasts with different land ICs, each set shows greater skill in some regions, but their locations vary with forecast lead time and season. The 1999 case study demonstrates that although a pattern of below-normal SSTs in the Pacific in the fall and winter is realistically reproduced in both reforecasts, GLDAS-2 land initial states display a stronger east–west gradient of soil moisture, particularly drier in the eastern United States and more consistent with observations, leading to warmer surface temperature anomalies over the United States. Anomalies lasting for one season are accompanied by more persistent barotropic (warm core) anomalous high pressure over CONUS, which results in better prediction skill of this drought case up to 4 months in advance in the reforecasts with GLDAS-2 land ICs. Therefore, it is essential to minimize the uncertainty of land initial states among the current land analyses for improving U.S. drought prediction on seasonal time scales.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JHM-D-20-0025.s1.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Chul-Su Shin, cshin3@gmu.edu

This article has a companion article which can be found at http://journals.ametsoc.org/doi/abs/10.1175/JHM-D-20-0024.1.

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