Journal ArticleDOI
Real‐time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project
Brian Cosgrove,Brian Cosgrove,Dag Lohmann,Kenneth E. Mitchell,Paul R. Houser,Eric F. Wood,John Schaake,Alan Robock,Curtis H. Marshall,Justin Sheffield,Qingyun Duan,Lifeng Luo,Lifeng Luo,R. Wayne Higgins,Rachel T. Pinker,J. Dan Tarpley,Jesse Meng +16 more
TLDR
The real-time forcing data set is constantly evolving to make use of the latest advances in forcing-related data sets, and all of the realtime and retrospective data sets are available online at http://ldas.gsfc.nasa.gov for visualization and downloading in both full and subset forms as discussed by the authors.Abstract:
[1] The accuracy of forcing data greatly impacts the ability of land surface models (LSMs) to produce realistic simulations of land surface processes. With this in mind, the multi-institutional North American Land Data Assimilation System (NLDAS) project has produced retrospective (1996–2002) and real-time (1999–present) data sets to support its LSM modeling activities. Featuring 0.125° spatial resolution, hourly temporal resolution, nine primary forcing fields, and six secondary validation/model development fields, each data set is based on a backbone of Eta Data Assimilation System/Eta data and is supplemented with observation-based precipitation and radiation data. Hourly observation-based precipitation data are derived from a combination of daily National Center for Environmental Prediction Climate Prediction Center (CPC) gauge-based precipitation analyses and hourly National Weather Service Doppler radar-based (WSR-88D) precipitation analyses, wherein the hourly radar-based analyses are used to temporally disaggregate the daily CPC analyses. NLDAS observation-based shortwave values are derived from Geostationary Operational Environmental Satellite radiation data processed at the University of Maryland and at the National Environmental Satellite Data and Information Service. Extensive quality control and validation efforts have been conducted on the NLDAS forcing data sets, and favorable comparisons have taken place with Oklahoma Mesonet, Atmospheric Radiation Measurement Program/cloud and radiation test bed, and Surface Radiation observation data. The real-time forcing data set is constantly evolving to make use of the latest advances in forcing-related data sets, and all of the real-time and retrospective data are available online at http://ldas.gsfc.nasa.gov for visualization and downloading in both full and subset forms.read more
Citations
More filters
Journal ArticleDOI
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).
Journal ArticleDOI
Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling
TL;DR: In this article, the authors describe the creation of a global, 50-yr, 3-hourly, 1.0° dataset of meteorological forcings that can be used to drive models of land surface hydrology.
Journal ArticleDOI
The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system
Kenneth E. Mitchell,Dag Lohmann,Paul R. Houser,Eric F. Wood,John Schaake,Alan Robock,Brian Cosgrove,Justin Sheffield,Qingyun Duan,Lifeng Luo,Lifeng Luo,R. Wayne Higgins,Rachel T. Pinker,J. Dan Tarpley,Dennis P. Lettenmaier,Curtis H. Marshall,Curtis H. Marshall,Jared Entin,Ming Pan,Wei Shi,Victor Koren,Jesse Meng,Jesse Meng,Bruce H. Ramsay,Andrew A. Bailey +24 more
TL;DR: A real-time and retrospective North American Land Data Assimilation System (NLDAS) is presented in this article, which consists of four land models executing in parallel in uncoupled mode, common hourly surface forcing, and common streamflow routing: all using a 1/8° grid over the continental United States.
Journal ArticleDOI
Development of gridded surface meteorological data for ecological applications and modelling
TL;DR: In this article, a spatially and temporally complete, high-resolution (4-km) gridded dataset of surface meteorological variables required in ecological modelling for the contiguous United States from 1979 to 2010 is presented.
Journal ArticleDOI
Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products
Youlong Xia,Kenneth E. Mitchell,Michael Ek,Justin Sheffield,Brian Cosgrove,Eric F. Wood,Lifeng Luo,Charles Alonge,Helin Wei,Jesse Meng,Ben Livneh,Dennis P. Lettenmaier,Victor Koren,Qingyun Duan,Kingtse C. Mo,Yun Fan,David Mocko +16 more
TL;DR: The second phase of the NLDAS-2 research partnership is presented in this article, where four land surface models (Noah, Variable Infiltration Capacity, Sacramento Soil Moisture Accounting, and Mosaic) are executed over the conterminous U.S. (CONUS) in real-time and retrospective modes.
References
More filters
Journal ArticleDOI
A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain
TL;DR: In this article, the authors present an analytical model that distributes point measurements of monthly and annual precipitation to regularly spaced grid cells in midlatitude regions, using a combination of climatological and statistical concepts to analyze orographic precipitation.
Journal ArticleDOI
The WSR-88D Rainfall Algorithm
TL;DR: In this paper, a detailed description of the operational WSR-88D rainfall estimation algorithm is presented, and the processing steps to quality control and compute the rainfall estimates are described, and current deficiencies and future plans for improvement are discussed.
Journal ArticleDOI
Surface soil moisture parameterization of the VIC-2L model: Evaluation and modification
TL;DR: In this article, a modified version of VIC-2L, which has a new feature that allows diffusion of moisture between soil layers, and a 0.1 m thin layer on top of the previous upper layer, is described.
Journal ArticleDOI
Assessment of the Land Surface and Boundary Layer Models in Two Operational Versions of the NCEP Eta Model Using FIFE Data
TL;DR: In this article, data from the 1987 summer FIFE experiment for four pairs of days are compared with corresponding 48-h forecasts from two different versions of the Eta Model, both initialized from the NCEP-NCAR (National Centers for Environmental Prediction-National Center for Atmospheric Research) global reanalysis.
Journal ArticleDOI
Changes to the Operational ''Early'' Eta Analysis / Forecast System at the National Centers for Environmental Prediction
Eric Rogers,Thomas L. Black,Dennis G. Deaven,Geoffrey J. DiMego,Qingyun Zhao,Michael E. Baldwin,Norman W. Junker,Ying Lin +7 more
TL;DR: In this paper, the National Centers for Environmental Prediction (NCEP) operational early eta model was improved by an increase in the horizontal grid spacing from 80 to 48 km, incorporation of a cloud prediction scheme, replacement of the original static analysis system with a 12-h intermittent data assimilation system using the ETa model, and use of satellite-sensed total column water data in the eta optimum interpolation analysis.
Related Papers (5)
The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system
Kenneth E. Mitchell,Dag Lohmann,Paul R. Houser,Eric F. Wood,John Schaake,Alan Robock,Brian Cosgrove,Justin Sheffield,Qingyun Duan,Lifeng Luo,Lifeng Luo,R. Wayne Higgins,Rachel T. Pinker,J. Dan Tarpley,Dennis P. Lettenmaier,Curtis H. Marshall,Curtis H. Marshall,Jared Entin,Ming Pan,Wei Shi,Victor Koren,Jesse Meng,Jesse Meng,Bruce H. Ramsay,Andrew A. Bailey +24 more