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Fanglin Yang
,
Kenneth Mitchell
,
Yu-Tai Hou
,
Yongjiu Dai
,
Xubin Zeng
,
Zhuo Wang
, and
Xin-Zhong Liang

Abstract

This study examines the dependence of surface albedo on solar zenith angle (SZA) over snow-free land surfaces using the intensive observations of surface shortwave fluxes made by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program and the National Oceanic and Atmospheric Administration Surface Radiation Budget Network (SURFRAD) in 1997–2005. Results are used to evaluate the National Centers for Environmental Prediction (NCEP) Global Forecast Systems (GFS) parameterization and several new parameterizations derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) products. The influence of clouds on surface albedo and the albedo difference between morning and afternoon observations are also investigated. A new approach is taken to partition the observed upward flux so that the direct-beam and diffuse albedos can be separately computed. The study focused first on the ARM Southern Great Plains Central Facility site. It is found that the diffuse albedo prescribed in the NCEP GFS matched closely with the observations. The direct-beam albedo parameterized in the GFS is largely underestimated at all SZAs. The parameterizations derived from the MODIS product underestimated the direct-beam albedo at large SZAs and slightly overestimated it at small SZAs. Similar results are obtained from the analyses of observations at other stations. It is also found that the morning and afternoon dependencies of direct-beam albedo on SZA differ among the stations. Attempts are made to improve numerical model algorithms that parameterize the direct-beam albedo as a product of the direct-beam albedo at SZA = 60° (or the diffuse albedo), which varies with surface type or geographical location and/or season, and a function that depends only on SZA. A method is presented for computing the direct-beam albedos over these snow-free land points without referring to a particular land-cover classification scheme, which often differs from model to model.

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Youlong Xia
,
David Mocko
,
Maoyi Huang
,
Bailing Li
,
Matthew Rodell
,
Kenneth E. Mitchell
,
Xitian Cai
, and
Michael B. Ek

Abstract

To prepare for the next-generation North American Land Data Assimilation System (NLDAS), three advanced land surface models [LSMs; i.e., Community Land Model, version 4.0 (CLM4.0); Noah LSM with multiphysics options (Noah-MP); and Catchment LSM-Fortuna 2.5 (CLSM-F2.5)] were run for the 1979–2014 period within the NLDAS-based framework. Unlike the LSMs currently executing in the operational NLDAS, these three advanced LSMs each include a groundwater component. In this study, the model simulations of monthly terrestrial water storage anomaly (TWSA) and its individual water storage components are evaluated against satellite-based and in situ observations, as well as against reference reanalysis products, at basinwide and statewide scales. The quality of these TWSA simulations will contribute to determining the suitability of these models for the next phase of the NLDAS. Overall, it is found that all three models are able to reasonably capture the monthly and interannual variability and magnitudes of TWSA. However, the relative contributions of the individual water storage components to TWSA are very dependent on the model and basin. A major contributor to the TWSA is the anomaly of total column soil moisture content for CLM4.0 and Noah-MP, while the groundwater storage anomaly is the major contributor for CLSM-F2.5. Other water storage components such as the anomaly of snow water equivalent also play a role in all three models. For each individual water storage component, the models are able to capture broad features such as monthly and interannual variability. However, there are large intermodel differences and quantitative uncertainties, which are motivating follow-on investigations in the NLDAS Science Testbed developed by the NASA and NCEP NLDAS teams.

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Geoffrey J. DiMego
,
Kenneth E. Mitchell
,
Ralph A. Petersen
,
James E. Hoke
,
Joseph P. Gerrity
,
James J. Tuccillo
,
Richard L. Wobus
, and
Hann-Ming H. Juang

Abstract

The recent implementation of changes to the National Meteorological Center's (NMC's) Regional Analysis and Forecast System (RAFS) is described. The changes include an expansion of the innermost grids of the nested-grid model (NGM) and the implementation of the Regional Data Assimilation System (RDAS). The new version of the forecast model and a 3-hourly RDAS analysis system were implemented on 7 August 1991. Some results from tests of the revised forecast model and the combined RDAS/NGM system are presented.

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Ralph A. Petersen
,
Geoffrey J. DiMego
,
James E. Hoke
,
Kenneth E. Mitchell
,
Joseph P. Gerrity
,
Richard L. Wobus
,
Hann-Ming H. Juang
, and
Michael J. Pecnick

Abstract

The final set of changes to NMC's Regional Analysis and Forecast System (RAFS) is described. The changes include modifications to both the forecast model and the analysis model, as well as development of a Regional Data Assimilation System (RDAS). The forecast model changes were developed to correct a number of known deficiencies in the Nested Grid Model (NGM), while the RDAS development will allow the RAFS to take advantage of the new asynoptic data sets soon to be available. Several of the changes were implemented on 7 November 1990. The remaining changes (including the RDAS) are planned for implementation before mid 1991. Results from tests of the revised forecast model and the combined RDAS/NGM system are presented and discussed.

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Jennifer M. Comstock
,
Robert d'Entremont
,
Daniel DeSlover
,
Gerald G. Mace
,
Sergey Y. Matrosov
,
Sally A . McFarlane
,
Patrick Minnis
,
David Mitchell
,
Kenneth Sassen
,
Matthew D. Shupe
,
David D. Turner
, and
Zhien Wang

The large horizontal extent, with its location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the Earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud-scale processes in largescale models and for accurately predicting the Earth's future climate. A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper-tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice water path in ice clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for their improvement.

Currently, there are significant discrepancies among the algorithms for ice clouds with very small optical depths (τ < 0.3) and those with 1 < τ < 5. The good news is that for thin clouds (0.3 < τ < 1), the algorithms tend to converge. In this first stage of the intercomparison, we present results from a representative case study, compare the retrieved cloud properties with aircraft and satellite measurements, and perform a radiative closure experiment to begin gauging the accuracy of these retrieval algorithms.

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RICHARD LAWFORD
,
MIKE BOSILOVICH
,
SUSANNA EDEN
,
SAM BENEDICT
,
CONSTANCE BROWN
,
ARNOLD GRUBER
,
PAUL HOUSER
,
KUOLIN HSU
,
JIN HUANG
,
WILLIAM LAU
,
TILDEN MEYERS
,
KENNETH MITCHELL
,
CHRISTA PETERS-LIDARD
,
JOHN ROADS
,
MATT RODELL
,
SOROOSH SOROOSHIAN
,
DAN TARPLEY
, and
STEVE WILLIAMS

The Coordinated Enhanced Observing Period (CEOP) is an international project that was first proposed by the Global Energy and Water Cycle Experiment (GEWEX) in 1997 and was formally launched in 2001. Since that time it has been adopted by the World Climate Research Programme (WCRP), which views it as an essential part of its strategy for developing global datasets to evaluate global climate models, and by the Integrated Global Observing Strategy Partnership (IGOS-P), which views it as the first element of its global water cycle theme. The United States has been an active partner in all phases of CEOP. In particular, the United States has taken the lead in contributing data from a number of reference sites, providing data processing, and archiving capabilities and related research activities through the GEWEX Americas Prediction Project (GAPP). Other U.S. programs and agencies are providing components including model and data assimilation output, satellite data, and other services. The U.S. science community has also been using the CEOP database in model evaluation and phenomenological studies. This article summarizes the U.S. contributions during the first phase of CEOP and outlines opportunities for readers to become involved in the data analysis phase of the project.

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Fedor Mesinger
,
Geoff DiMego
,
Eugenia Kalnay
,
Kenneth Mitchell
,
Perry C. Shafran
,
Wesley Ebisuzaki
,
Dušan Jović
,
Jack Woollen
,
Eric Rogers
,
Ernesto H. Berbery
,
Michael B. Ek
,
Yun Fan
,
Robert Grumbine
,
Wayne Higgins
,
Hong Li
,
Ying Lin
,
Geoff Manikin
,
David Parrish
, and
Wei Shi

In 1997, during the late stages of production of NCEP–NCAR Global Reanalysis (GR), exploration of a regional reanalysis project was suggested by the GR project's Advisory Committee, “particularly if the RDAS [Regional Data Assimilation System] is significantly better than the global reanalysis at capturing the regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.” Following a 6-yr development and production effort, NCEP's North American Regional Reanalysis (NARR) project was completed in 2004, and data are now available to the scientific community. Along with the use of the NCEP Eta model and its Data Assimilation System (at 32-km–45-layer resolution with 3-hourly output), the hallmarks of the NARR are the incorporation of hourly assimilation of precipitation, which leverages a comprehensive precipitation analysis effort, the use of a recent version of the Noah land surface model, and the use of numerous other datasets that are additional or improved compared to the GR. Following the practice applied to NCEP's GR, the 25-yr NARR retrospective production period (1979–2003) is augmented by the construction and daily execution of a system for near-real-time continuation of the NARR, known as the Regional Climate Data Assimilation System (R-CDAS). Highlights of the NARR results are presented: precipitation over the continental United States (CONUS), which is seen to be very near the ingested analyzed precipitation; fits of tropospheric temperatures and winds to rawinsonde observations; and fits of 2-m temperatures and 10-m winds to surface station observations. The aforementioned fits are compared to those of the NCEP–Department of Energy (DOE) Global Reanalysis (GR2). Not only have the expectations cited above been fully met, but very substantial improvements in the accuracy of temperatures and winds compared to that of GR2 are achieved throughout the troposphere. Finally, the numerous datasets produced are outlined and information is provided on the data archiving and present data availability.

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Lifeng Luo
,
Alan Robock
,
Konstantin Y. Vinnikov
,
C. Adam Schlosser
,
Andrew G. Slater
,
Aaron Boone
,
Pierre Etchevers
,
Florence Habets
,
Joel Noilhan
,
Harald Braden
,
Peter Cox
,
Patricia de Rosnay
,
Robert E. Dickinson
,
Yongjiu Dai
,
Qing-Cun Zeng
,
Qingyun Duan
,
John Schaake
,
Ann Henderson-Sellers
,
Nicola Gedney
,
Yevgeniy M. Gusev
,
Olga N. Nasonova
,
Jinwon Kim
,
Eva Kowalczyk
,
Kenneth Mitchell
,
Andrew J. Pitman
,
Andrey B. Shmakin
,
Tatiana G. Smirnova
,
Peter Wetzel
,
Yongkang Xue
, and
Zong-Liang Yang

Abstract

The Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated.

It was found that when soil-water freezing is explicitly included in a model, it improves the simulation of soil temperature and its variability at seasonal and interannual scales. Although change of thermal conductivity of the soil also affects soil temperature simulation, this effect is rather weak. The impact of frozen soil on soil moisture is inconclusive in this experiment due to the particular climate at Valdai, where the top 1 m of soil is very close to saturation during winter and the range for soil moisture changes at the time of snowmelt is very limited. The results also imply that inclusion of explicit snow processes in the models would contribute to substantially improved simulations. More sophisticated snow models based on snow physics tend to produce better snow simulations, especially of snow ablation. Hysteresis of snow-cover fraction as a function of snow depth is observed at the catchment but not in any of the models.

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