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Christa D. Peters-Lidard
,
David M. Mocko
,
Lu Su
,
Dennis P. Lettenmaier
,
Pierre Gentine
, and
Michael Barlage

Abstract

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snowpack evolution now support a range of drought indicators that better reflect coupled water, energy, and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity, and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

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Cenlin He
,
Fei Chen
,
Michael Barlage
,
Zong-Liang Yang
,
Jerry W. Wegiel
,
Guo-Yue Niu
,
David Gochis
,
David M. Mocko
,
Ronnie Abolafia-Rosenzweig
,
Zhe Zhang
,
Tzu-Shun Lin
,
Prasanth Valayamkunnath
,
Michael Ek
, and
Dev Niyogi
Open access
Jordan G. Powers
,
Joseph B. Klemp
,
William C. Skamarock
,
Christopher A. Davis
,
Jimy Dudhia
,
David O. Gill
,
Janice L. Coen
,
David J. Gochis
,
Ravan Ahmadov
,
Steven E. Peckham
,
Georg A. Grell
,
John Michalakes
,
Samuel Trahan
,
Stanley G. Benjamin
,
Curtis R. Alexander
,
Geoffrey J. Dimego
,
Wei Wang
,
Craig S. Schwartz
,
Glen S. Romine
,
Zhiquan Liu
,
Chris Snyder
,
Fei Chen
,
Michael J. Barlage
,
Wei Yu
, and
Michael G. Duda

Abstract

Since its initial release in 2000, the Weather Research and Forecasting (WRF) Model has become one of the world’s most widely used numerical weather prediction models. Designed to serve both research and operational needs, it has grown to offer a spectrum of options and capabilities for a wide range of applications. In addition, it underlies a number of tailored systems that address Earth system modeling beyond weather. While the WRF Model has a centralized support effort, it has become a truly community model, driven by the developments and contributions of an active worldwide user base. The WRF Model sees significant use for operational forecasting, and its research implementations are pushing the boundaries of finescale atmospheric simulation. Future model directions include developments in physics, exploiting emerging compute technologies, and ever-innovative applications. From its contributions to research, forecasting, educational, and commercial efforts worldwide, the WRF Model has made a significant mark on numerical weather prediction and atmospheric science.

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