Journal Article10.1029/2009GL037505
Land‐atmosphere coupling and diurnal temperature range over the contiguous United States
TL;DR: In this article, a soil moisture feedback parameter is computed based on lagged covariance ratios over the zone from California through the Midwest to the Southeast, where the soil moisture exhibits a negative feedback on DTR mainly through its damping effect on Tmax.
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Abstract: [1] Soil moisture influences on daily maximum (Tmax) and minimum (Tmin) temperatures, and thus the diurnal temperature range (DTR) in summer, are statistically quantified across the contiguous Unites States using soil moisture from the Global Land Data Assimilation System and observational temperatures A soil moisture feedback parameter is computed based on lagged covariance ratios Over the zone from California through the Midwest to the Southeast, the soil moisture exhibits a negative feedback on DTR mainly through its damping effect on Tmax In contrast, a positive feedback on DTR dominates Arizona and New Mexico as the soil moisture exerts a stronger negative forcing on Tmin relative to Tmax The feedback-induced variability accounts for typically 10–20% of the total DTR variance over regions where strong feedbacks are identified The results provide a useful benchmark for evaluating climate model simulations, although the employed data and method have limitations that should be recognized
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References
The Global Land Data Assimilation System
Mathew Rodell,Paul R. Houser,U. Jambor,Jon Gottschalck,Kenneth E. Mitchell,C. J. Meng,Kristi R. Arsenault,B. Cosgrove,J Radakovich,Michael G. Bosilovich,Jared Entin,Jeffrey P. Walker,Dag Lohmann,David Toll +13 more
TL;DR: The Global Land Data Assimilation System (GLDAS) as mentioned in this paper is an uncoupled land surface modeling system that drives multiple models, integrates a huge quantity of observation-based data, runs globally at high resolution (0.25°), and produces results in near-real time (typically within 48 h of the present).
5.2K
An improved method of constructing a database of monthly climate observations and associated high-resolution grids
Timothy D. Mitchell,Philip Jones +1 more
TL;DR: In this paper, a database of monthly climate observations from meteorological stations is constructed and checked for inhomogeneities in the station records using an automated method that refines previous methods by using incomplete and partially overlapping records and by detecting inhomalities with opposite signs in different seasons.
4.3K
North american regional reanalysis
Fedor Mesinger,Geoff DiMego,Eugenia Kalnay,Kenneth E. Mitchell,Perry Shafran,Wesley Ebisuzaki,Dusan Jovic,John S. Woollen,Eric Rogers,Ernesto Hugo Berbery,Michael Ek,Yun Fan,Robert Grumbine,Wayne Higgins,Hong Li,Ying Lin,Geoff Manikin,David F. Parrish,Wei Shi +18 more
TL;DR: The North American Regional Reanalysis (NARR) project as mentioned in this paper uses the NCEP Eta model and its Data Assimilation System (at 32-km-45-layer resolution with 3-hourly output) to capture regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.
Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model
Michael Ek,Kenneth E. Mitchell,Y. Lin,E. Rogers,P. Grunmann,Victor Koren,G. Gayno,J. D. Tarpley +7 more
TL;DR: In this article, the authors present the impact tests that preceded the most recent operational upgrades to the land surface model used in the National Centers for Environmental Prediction (NCEP) mesoscale Eta model, whose operational domain includes North America.
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Regions of Strong Coupling Between Soil Moisture and Precipitation
Randal D. Koster,Paul A. Dirmeyer,Zhichang Guo,Gordon B. Bonan,Edmond Chan,Peter M. Cox,C. T. Gordon,Shinjiro Kanae,Eva Kowalczyk,David M. Lawrence,Ping Liu,Cheng-Hsuan Lu,Sergey Malyshev,Bryant J. McAvaney,Kenneth E. Mitchell,David Mocko,Taikan Oki,Keith W. Oleson,Andrew J. Pitman,Yogesh C. Sud,Christopher M. Taylor,Diana Verseghy,R. Vasic,Yongkang Xue,Tomohito J. Yamada +24 more
TL;DR: A multimodel estimation of the regions on Earth where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer indicates potential benefits of this estimation may include improved seasonal rainfall forecasts.
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