FN Archimer Export Format
PT J
TI Uncertainties in Ocean Latent Heat Flux Variations over Recent Decades in Satellite-Based Estimates and Reduced Observation Reanalyses
BT 
AF Robertson, Franklin R.
   Roberts, Jason B.
   Bosilovich, Michael G.
   Bentamy, Abderrahim
   Clayson, Carol Anne
   Fennig, Karsten
   Schröder, Marc
   Tomita, Hiroyuki
   Compo, Gilbert P.
   Gutenstein, Marloes
   Hersbach, Hans
   Kobayashi, Chiaki
   Ricciardulli, Lucrezia
   Sardeshmukh, Prashant
   Slivinski, Laura C.
AS 1:1;2:1;3:2;4:3;5:4;6:5;7:5;8:6;9:7,8;10:5;11:9;12:10;13:11;14:7,8;15:7,8;
FF 1:;2:;3:;4:PDG-ODE-LOPS-SIAM;5:;6:;7:;8:;9:;10:;11:;12:;13:;14:;15:;
C1 NASA Marshall Space Flight Center, Huntsville, Alabama
   NASA GSFC Global Modeling and Assimilation Office, Greenbelt, Maryland
   Laboratoire d’Océanographie Spatiale, Institut Français pour la Recheche et l’Exploitation de la Mer (IFREMER), Brest, France
   Woods Hole Oceanographic Institution, Woods Hole, Massachusetts
   Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Offenbach, Germany
   Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Japan
   Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado
   NOAA Physical Sciences Laboratory, Boulder, Colorado
   European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
   Meteorological Research Institute, Tsukuba, Japan
   Remote Sensing Systems, Santa Rosa, California
C2 NASA, USA
   NASA, USA
   IFREMER, FRANCE
   WHOI, USA
   CM SAF, GERMANY
   UNIV NAGOYA, JAPAN
   UNIV COLORADO BOULDER, USA
   NOAA, USA
   ECMWF, UK
   METEOROL RES INST, JAPAN
   REMOTE SENSING SYSTEMS, USA
SI BREST
SE PDG-ODE-LOPS-SIAM
UM LOPS
IN WOS Ifremer UMR
   copubli-europe
   copubli-int-hors-europe
IF 5.148
TC 15
UR https://archimer.ifremer.fr/doc/00654/76588/77737.pdf
LA English
DT Article
AB Four state-of-the-art satellite-based estimates of ocean surface latent heat fluxes (LHFs) extending over three decades are analyzed, focusing on the interannual variability and trends of near-global averages and regional patterns. Detailed intercomparisons are made with other datasets including 1) reduced observation reanalyses (RedObs) whose exclusion of satellite data renders them an important independent diagnostic tool; 2) a moisture budget residual LHF estimate using reanalysis moisture transport, atmospheric storage, and satellite precipitation; 3) the ECMWF Reanalysis 5 (ERA5); 4) Remote Sensing Systems (RSS) singlesensor passive microwave and scatterometer wind speed retrievals; and 5) several sea surface temperature (SST) datasets. Large disparities remain in near-global satellite LHF trends and their regional expression over the 1990–2010 period, during which time the interdecadal Pacific oscillation changed sign. The budget residual diagnostics support the smaller RedObs LHF trends. The satellites, ERA5, and RedObs are reasonably consistent in identifying contributions by the 10-m wind speed variations to the LHF trend patterns. However, contributions by the near-surface vertical humidity gradient from satellites and ERA5 trend upward in time with respect to the RedObs ensemble and show less agreement in trend patterns. Problems with wind speed retrievals from Special Sensor Microwave Imager/Sounder satellite sensors, excessive upward trends in trends in Optimal Interpolation Sea Surface Temperature (OISST AVHRR-Only) data used in most satellite LHF estimates, and uncertainties associated with poor satellite coverage before the mid-1990s are noted. Possibly erroneous trends are also identified in ERA5 LHF associated with the onset of scatterometer wind data assimilation in the early 1990s. 
PY 2020
PD OCT
SO Journal Of Climate
SN 0894-8755
PU American Meteorological Society
VL 33
IS 19
UT 000589983000014
BP 8415
EP 8437
DI 10.1175/JCLI-D-19-0954.1
ID 76588
ER

EF