TY - JOUR
T1 - Spatial distribution of melt season cloud radiative effects over Greenland: Evaluating satellite observations, reanalyses, and model simulations against in situ measurements
AU - Wang, Wenshan
AU - Zender, Charles S.
AU - van As, Dirk
AU - Miller, Nathaniel B.
N1 - Funding Information:
We thanks Michael G. Bosilovich for explaining the details of MERRA-2 cloud retrieval processes and Dennis Shea and Mary Haley for clarifying spatial interpolation methods used by NCAR Command Language (NCL). The GC-Net data were obtained from the Steffen Research Group, the Cooperative Institute for Research in Environmental Sciences (http://cires1.colorado.edu/science/groups/ steffen/gcnet/order/admin/station.php). The PROMICE data were obtained from the PROMICE website, collected by the Geological Survey of Denmark and Greenland (GEUS) in collaboration with the (Technical University of Denmark) DTU Space and Asiaq, Greenland Survey (http://www.promice.org/ DataDownload.html). The CERES data were obtained from the NASA Langley Research Center Atmospheric Science Data Center (https://ceres-tool.larc.nasa.gov/ ord-tool/jsp/SYN1degSelection.jsp). The MERRA-2 data were obtained from the NASA EARTHDATA, provided by the Global Modeling and Assimilation Office (GMAO) from NASA Goddard Space Flight Center (https://disc.sci.gsfc.nasa.gov/ daac-bin/FTPSubset2.pl). The ERA-Interim data were obtained from the European Centre for Medium-Range Weather Forecasts (http://apps.ecmwf.int/datasets/data/ interim-full-daily/levtype=sfc/). The ASR data were obtained from the National Center for Atmospheric Research/University Corporation for Atmospheric Research (NCAR/UCAR) and Polar Meteorology Group, Byrd Polar Research Center, the Ohio State University (https://rda.ucar.edu/ datasets/ds631.0/;DOI:10.5065/D6K072B5). The LENS data were obtained from the Earth System Grid at NCAR (https://www.earthsystemgrid.org/dataset/ ucar.cgd.ccsm4.CESM_CAM5_BGC_LE. atm.proc.monthly_ave.html). The ICECAPS data (supported by NSF PLR1303879) were from ftp://ftp1.esrl.noaa.gov/psd3/arctic/summit/ radiosonde/processed/. Project supported by NASA ACCESS NNX14AH55A and by DOE ACME DE-SC0012998.
Funding Information:
We thanks Michael G. Bosilovich for explaining the details of MERRA-2 cloud retrieval processes and Dennis Shea and Mary Haley for clarifying spatial interpolation methods used by NCAR Command Language (NCL). The GC-Net data were obtained from the Steffen Research Group, the Cooperative Institute for Research in Environmental Sciences (http://cires1.colorado.edu/science/groups/steffen/gcnet/order/admin/station.php). The PROMICE data were obtained from the PROMICE website, collected by the Geological Survey of Denmark and Greenland (GEUS) in collaboration with the (Technical University of Denmark) DTU Space and Asiaq, Greenland Survey (http://www.promice.org/DataDownload.html). The CERES data were obtained from the NASA Langley Research Center Atmospheric Science Data Center (https://ceres-tool.larc.nasa.gov/ord-tool/jsp/SYN1degSelection.jsp). The MERRA-2 data were obtained from the NASA EARTHDATA, provided by the Global Modeling and Assimilation Office (GMAO) from NASA Goddard Space Flight Center (https://disc.sci.gsfc.nasa.gov/daac-bin/FTPSubset2.pl). The ERA-Interim data were obtained from the European Centre for Medium-Range Weather Forecasts (http://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/). The ASR data were obtained from the National Center for Atmospheric Research/University Corporation for Atmospheric Research (NCAR/UCAR) and Polar Meteorology Group, Byrd Polar Research Center, the Ohio State University (https://rda.ucar.edu/datasets/ds631.0/;DOI: 10.5065/D6K072B5). The LENS data were obtained from the Earth System Grid at NCAR (https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.CESM_CAM5_BGC_LE. atm.proc.monthly_ave.html). The ICECAPS data (supported by NSF PLR1303879) were from ftp://ftp1.esrl.noaa.gov/psd3/arctic/summit/radiosonde/processed/. Project supported by NASA ACCESS NNX14AH55A and by DOE ACME DE-SC0012998.
Publisher Copyright:
©2018. American Geophysical Union. All Rights Reserved.
PY - 2019/1/16
Y1 - 2019/1/16
N2 - Arctic clouds can profoundly influence surface radiation and thus surface melt. Over Greenland, these cloud radiative effects (CRE) vary greatly with the diverse topography. To investigate the ability of assorted platforms to reproduce heterogeneous CRE, we evaluate CRE spatial distributions from a satellite product, reanalyses, and a global climate model against estimates from 21 automatic weather stations (AWS). Net CRE estimated from AWS generally decreases with elevation, forming a “warm center” distribution. CRE areal averages from the five large-scale data sets we analyze are all around 10 W/m
2 . Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), ERA-Interim, and Clouds and the Earth's Radiant Energy System (CERES) CRE estimates agree with AWS and reproduce the warm center distribution. However, the National Center for Atmospheric Research Arctic System Reanalysis (ASR) and the Community Earth System Model Large ENSemble Community Project (LENS) show strong warming in the south and northwest, forming a warm L-shape distribution. Discrepancies are mainly caused by longwave CRE in the accumulation zone. MERRA-2, ERA-Interim, and CERES successfully reproduce cloud fraction and its dominant positive influence on longwave CRE in this region. On the other hand, longwave CRE from ASR and LENS correlates strongly with ice water path instead of with cloud fraction or liquid water path. Moreover, ASR overestimates cloud fraction and LENS underestimates liquid water path substantially, both with limited spatial variability. MERRA-2 best captures the observed interstation changes, captures most of the observed cloud-radiation physics, and largely reproduces both albedo and cloud properties. The warm center CRE spatial distribution indicates that clouds enhance surface melt in the higher accumulation zone and reduce surface melt in the lower ablation zone.
AB - Arctic clouds can profoundly influence surface radiation and thus surface melt. Over Greenland, these cloud radiative effects (CRE) vary greatly with the diverse topography. To investigate the ability of assorted platforms to reproduce heterogeneous CRE, we evaluate CRE spatial distributions from a satellite product, reanalyses, and a global climate model against estimates from 21 automatic weather stations (AWS). Net CRE estimated from AWS generally decreases with elevation, forming a “warm center” distribution. CRE areal averages from the five large-scale data sets we analyze are all around 10 W/m
2 . Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), ERA-Interim, and Clouds and the Earth's Radiant Energy System (CERES) CRE estimates agree with AWS and reproduce the warm center distribution. However, the National Center for Atmospheric Research Arctic System Reanalysis (ASR) and the Community Earth System Model Large ENSemble Community Project (LENS) show strong warming in the south and northwest, forming a warm L-shape distribution. Discrepancies are mainly caused by longwave CRE in the accumulation zone. MERRA-2, ERA-Interim, and CERES successfully reproduce cloud fraction and its dominant positive influence on longwave CRE in this region. On the other hand, longwave CRE from ASR and LENS correlates strongly with ice water path instead of with cloud fraction or liquid water path. Moreover, ASR overestimates cloud fraction and LENS underestimates liquid water path substantially, both with limited spatial variability. MERRA-2 best captures the observed interstation changes, captures most of the observed cloud-radiation physics, and largely reproduces both albedo and cloud properties. The warm center CRE spatial distribution indicates that clouds enhance surface melt in the higher accumulation zone and reduce surface melt in the lower ablation zone.
KW - automatic weather stations
KW - cloud
KW - Greenland
KW - radiation
UR - http://www.scopus.com/inward/record.url?scp=85059559485&partnerID=8YFLogxK
U2 - 10.1029/2018JD028919
DO - 10.1029/2018JD028919
M3 - Article
VL - 124
SP - 57
EP - 71
JO - Journal of Geophysical Research: Atmospheres
JF - Journal of Geophysical Research: Atmospheres
SN - 2169-8996
IS - 1
ER -