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) or to an evolving modeled climate system ( Fyfe and Saenko 2006 ). These previous investigations have focused, by necessity, on large-scale changes in the forcing, and have had difficulties separating various controls. These works have determined that the ACC transport is determined by thermodynamics, as well as dynamics, making a simple relationship impossible to find ( Cai and Baines 1996 ; Gnanadesikan and Hallberg 2000 ). The Southern Ocean winds are highly variable on all time scales. To
) or to an evolving modeled climate system ( Fyfe and Saenko 2006 ). These previous investigations have focused, by necessity, on large-scale changes in the forcing, and have had difficulties separating various controls. These works have determined that the ACC transport is determined by thermodynamics, as well as dynamics, making a simple relationship impossible to find ( Cai and Baines 1996 ; Gnanadesikan and Hallberg 2000 ). The Southern Ocean winds are highly variable on all time scales. To
flux accuracy through assimilation of oceanic observations in an ocean state estimate could be a very useful result. Our main results follow. First, the SOSE adjustments of NCEP1 forcing fields (which SOSE used as an initial guess) largely correct the NCEP1 biases reported by WGASF , and they are largely in agreement with the independent adjustments of LY09 . Since the methods and observations used by LY09 and SOSE to improve the NCEP1 atmospheric state estimate are very different, the good
flux accuracy through assimilation of oceanic observations in an ocean state estimate could be a very useful result. Our main results follow. First, the SOSE adjustments of NCEP1 forcing fields (which SOSE used as an initial guess) largely correct the NCEP1 biases reported by WGASF , and they are largely in agreement with the independent adjustments of LY09 . Since the methods and observations used by LY09 and SOSE to improve the NCEP1 atmospheric state estimate are very different, the good
conducted using reanalyses that have led to an improved understanding of high-latitude teleconnection patterns (e.g., Thompson and Wallace 1998 ; Hurrell et al. 2001 ; Genthon et al. 2003 ; Monaghan and Bromwich 2008 ) and the identification of prevailing atmospheric conditions during recent, dramatic reductions in Arctic perennial sea ice cover ( Ogi and Wallace 2007 ). Reanalyses are also used as first-order validation for climate models and provide necessary boundary forcing conditions for ocean
conducted using reanalyses that have led to an improved understanding of high-latitude teleconnection patterns (e.g., Thompson and Wallace 1998 ; Hurrell et al. 2001 ; Genthon et al. 2003 ; Monaghan and Bromwich 2008 ) and the identification of prevailing atmospheric conditions during recent, dramatic reductions in Arctic perennial sea ice cover ( Ogi and Wallace 2007 ). Reanalyses are also used as first-order validation for climate models and provide necessary boundary forcing conditions for ocean
Reanalysis Downscaling at 10 km (CARD10) produced for the California current region with some improvement in the boundary conditions and model physics ( Yoshimura and Kanamitsu 2009 ; Kanamitsu et al. 2010 ). Small-scale features are generated by forcing a high-resolution regional atmospheric model with large-scale NCEP–NCAR reanalysis fields on the domain boundaries. For the California downscaling CARD10, daily SSTs from ECMWF reanalysis (1° × 1°) were used ( Fiorino 2004 ; Kanamitsu and Kanamaru 2007
Reanalysis Downscaling at 10 km (CARD10) produced for the California current region with some improvement in the boundary conditions and model physics ( Yoshimura and Kanamitsu 2009 ; Kanamitsu et al. 2010 ). Small-scale features are generated by forcing a high-resolution regional atmospheric model with large-scale NCEP–NCAR reanalysis fields on the domain boundaries. For the California downscaling CARD10, daily SSTs from ECMWF reanalysis (1° × 1°) were used ( Fiorino 2004 ; Kanamitsu and Kanamaru 2007
the changes in ozone, cloudiness, and surface albedo were dealt with in Bernhard et al. (2007) . In a comprehensive investigation by Dong et al. (2010) using 10 yr of cloud and radiative flux observations collected by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program at the North Slope of Alaska (NSA), it is reported that the longwave cloud-radiative forcing (CRF) has a high positive correlations (0.8–0.9) with cloud fraction, liquid water path, and radiating
the changes in ozone, cloudiness, and surface albedo were dealt with in Bernhard et al. (2007) . In a comprehensive investigation by Dong et al. (2010) using 10 yr of cloud and radiative flux observations collected by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program at the North Slope of Alaska (NSA), it is reported that the longwave cloud-radiative forcing (CRF) has a high positive correlations (0.8–0.9) with cloud fraction, liquid water path, and radiating
weather prediction. For MERRA, the GEOS DAS was run at a horizontal resolution of ⅔° longitude by ½° latitude and 72 hybrid-sigma coordinate vertical levels to produce an observational analysis at 6-h intervals. Boundary conditions include climatological aerosol and solar forcing. Sea surface temperature and sea ice are linearly interpolated in time from weekly 1° resolution Reynolds fields ( Reynolds et al. 2002 ). The atmospheric model is coupled to a catchment-based hydrologic model on land
weather prediction. For MERRA, the GEOS DAS was run at a horizontal resolution of ⅔° longitude by ½° latitude and 72 hybrid-sigma coordinate vertical levels to produce an observational analysis at 6-h intervals. Boundary conditions include climatological aerosol and solar forcing. Sea surface temperature and sea ice are linearly interpolated in time from weekly 1° resolution Reynolds fields ( Reynolds et al. 2002 ). The atmospheric model is coupled to a catchment-based hydrologic model on land
surface heat flux and drive the change of near-surface temperatures and convective mixing. Cayan (1992a) discussed the connection of LHF and SHF to the atmospheric circulation modes in the North Pacific and North Atlantic, and showed that the LHF + SHF anomalies force the local SST anomalies. The importance of LHF plus SHF in causing deep convection in the northern North Atlantic was best demonstrated in a recent study by Våge et al. (2009) . An unusual deep convective overturning event in the
surface heat flux and drive the change of near-surface temperatures and convective mixing. Cayan (1992a) discussed the connection of LHF and SHF to the atmospheric circulation modes in the North Pacific and North Atlantic, and showed that the LHF + SHF anomalies force the local SST anomalies. The importance of LHF plus SHF in causing deep convection in the northern North Atlantic was best demonstrated in a recent study by Våge et al. (2009) . An unusual deep convective overturning event in the
) dataset ( Röske 2006 ), which was created as the forcing data for ocean general circulation models (OGCMs). In this dataset, ice concentrations were derived from the Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite and from the SSM/I on satellites of the Defense Meteorological Satellite Program (DMSP). In the sea ice zone, the OMIP heat flux is larger than that calculated by neglecting the ice concentration. Daily ice concentration has also been used in an air
) dataset ( Röske 2006 ), which was created as the forcing data for ocean general circulation models (OGCMs). In this dataset, ice concentrations were derived from the Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite and from the SSM/I on satellites of the Defense Meteorological Satellite Program (DMSP). In the sea ice zone, the OMIP heat flux is larger than that calculated by neglecting the ice concentration. Daily ice concentration has also been used in an air
