Editorial Type:
Article
Article Type:
Research Article

A Reanalysis System for the Generation of Mesoscale Climatographies

Andrea N. Hahmann National Center for Atmospheric Research, Boulder, Colorado**
Risø National Laboratory for Sustainable Energy, Technical University of Denmark, Roskilde, Denmark

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Dorita Rostkier-Edelstein National Center for Atmospheric Research, Boulder, Colorado**

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Thomas T. Warner National Center for Atmospheric Research, Boulder, Colorado**
Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado

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Francois Vandenberghe National Center for Atmospheric Research, Boulder, Colorado**

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Yubao Liu National Center for Atmospheric Research, Boulder, Colorado**

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Richard Babarsky National Ground Intelligence Center, Charlottesville, Virginia

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Scott P. Swerdlin National Center for Atmospheric Research, Boulder, Colorado**

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Print Publication:
01 May 2010
DOI:
https://doi.org/10.1175/2009JAMC2351.1
Page(s):
954–972
Restricted access

Abstract

The use of a mesoscale model–based four-dimensional data assimilation (FDDA) system for generating mesoscale climatographies is demonstrated. This dynamical downscaling method utilizes the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), wherein Newtonian relaxation terms in the prognostic equations continually nudge the model solution toward surface and upper-air observations. When applied to a mesoscale climatography, the system is called Climate-FDDA (CFDDA). Here, the CFDDA system is used for downscaling eastern Mediterranean climatographies for January and July. The downscaling method performance is verified by using independent observations of monthly rainfall, Quick Scatterometer (QuikSCAT) ocean-surface winds, gauge rainfall, and hourly winds from near-coastal towers. The focus is on the CFDDA system’s ability to represent the frequency distributions of atmospheric states in addition to time means. The verification of the monthly rainfall climatography shows that CFDDA captures most of the observed spatial and interannual variability, although the model tends to underestimate rainfall amounts over the sea. The frequency distributions of daily rainfall are also accurately diagnosed for various regions of the Levant, except that very light rainfall days and heavy precipitation amounts are overestimated over Lebanon. The verification of the CFDDA against QuikSCAT ocean winds illustrates an excellent general correspondence between observed and modeled winds, although the CFDDA speeds are slightly lower than those observed. Over land, CFDDA- and the ECMWF-derived wind climatographies when compared with mast observations show similar errors related to their inability to properly represent the local orography and coastline. However, the diurnal variability of the winds is better estimated by CFDDA because of its higher horizontal resolution.

# Permanent affiliation: Israel Institute of Biological Research, Ness-Ziona, Israel

Corresponding author address: Andrea N. Hahmann, Risø National Laboratory for Sustainable Energy, Technical University of Denmark, P.O. Box 49, 4000 Roskilde, Denmark. Email: ahah@risoe.dtu.dk

Abstract

The use of a mesoscale model–based four-dimensional data assimilation (FDDA) system for generating mesoscale climatographies is demonstrated. This dynamical downscaling method utilizes the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), wherein Newtonian relaxation terms in the prognostic equations continually nudge the model solution toward surface and upper-air observations. When applied to a mesoscale climatography, the system is called Climate-FDDA (CFDDA). Here, the CFDDA system is used for downscaling eastern Mediterranean climatographies for January and July. The downscaling method performance is verified by using independent observations of monthly rainfall, Quick Scatterometer (QuikSCAT) ocean-surface winds, gauge rainfall, and hourly winds from near-coastal towers. The focus is on the CFDDA system’s ability to represent the frequency distributions of atmospheric states in addition to time means. The verification of the monthly rainfall climatography shows that CFDDA captures most of the observed spatial and interannual variability, although the model tends to underestimate rainfall amounts over the sea. The frequency distributions of daily rainfall are also accurately diagnosed for various regions of the Levant, except that very light rainfall days and heavy precipitation amounts are overestimated over Lebanon. The verification of the CFDDA against QuikSCAT ocean winds illustrates an excellent general correspondence between observed and modeled winds, although the CFDDA speeds are slightly lower than those observed. Over land, CFDDA- and the ECMWF-derived wind climatographies when compared with mast observations show similar errors related to their inability to properly represent the local orography and coastline. However, the diurnal variability of the winds is better estimated by CFDDA because of its higher horizontal resolution.

# Permanent affiliation: Israel Institute of Biological Research, Ness-Ziona, Israel

Corresponding author address: Andrea N. Hahmann, Risø National Laboratory for Sustainable Energy, Technical University of Denmark, P.O. Box 49, 4000 Roskilde, Denmark. Email: ahah@risoe.dtu.dk

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Journal of Applied Meteorology and Climatology

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