TY - JOUR
T1 - A Reanalysis System for the Generation of Mesoscale Climatographies
AU - Hahmann, Andrea N.
AU - Rostkier-Edelstein, Dorita
AU - Warner, Thomas T.
AU - Vandenberghe, Francois
AU - Liu, Yubao
AU - Babarsky, Richard
AU - Swerdlin, Scott P.
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
KW - Wind energy
KW - Wind power meteorology
KW - Vindkraftmeteorologi
KW - Vindenergi
U2 - 10.1175/2009JAMC2351.1
DO - 10.1175/2009JAMC2351.1
M3 - Journal article
SN - 1558-8424
VL - 49
SP - 954
EP - 972
JO - Journal of Applied Meteorology and Climatology
JF - Journal of Applied Meteorology and Climatology
IS - 5
ER -