Open AccessRepresentation of Soil Moisture Feedbacks during Drought in NASA Unified WRF (NU-WRF)
Author(s) -
Benjamin F. Zaitchik,
Joseph A. Santanello,
Sujay V. Kumar,
Christa D. PetersLidard
Publication year - 2013
Publication title -
journal of hydrometeorology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.733
H-Index - 123
eISSN - 1525-755X
pISSN - 1525-7541
DOI - 10.1175/jhm-d-12-069.1
Subject(s) - weather research and forecasting model , precipitation , environmental science , albedo (alchemy) , water content , climatology , moisture , climate model , atmospheric sciences , climate change , meteorology , geography , geology , art , oceanography , geotechnical engineering , performance art , art history
Positive soil moisture–precipitation feedbacks can intensify heat and prolong drought under conditions of precipitation deficit. Adequate representation of these processes in regional climate models is, therefore, important for extended weather forecasts, seasonal drought analysis, and downscaled climate change projections. This paper presents the first application of the NASA Unified Weather Research and Forecasting Model (NU-WRF) to simulation of seasonal drought. Simulations of the 2006 southern Great Plains drought performed with and without soil moisture memory indicate that local soil moisture feedbacks had the potential to concentrate precipitation in wet areas relative to dry areas in summer drought months. Introduction of a simple dynamic surface albedo scheme that models albedo as a function of soil moisture intensified the simulated feedback pattern at local scale—dry, brighter areas received even less precipitation while wet, whereas darker areas received more—but did not significantly change the total amount of precipitation simulated across the drought-affected region. This soil-moisture-mediated albedo land–atmosphere coupling pathway is structurally excluded from standard versions of WRF.