Ocean Surface heat fluxesLisan Yu and Robert Wellerlyu@whoi.edurweller@whoi.edu

http://oaflux.whoi.edu

Ocean Surface heat fluxesA brief introduction of the OAFlux projectSurface latent and sensible heat fluxes the state of the latent and sensible heat fluxes in 2005 its relation to 2004 and to the analysis record that starts from 1981 the long-term trend in latent heat fluxSurface longwave and shortwave radiations (ISCCP) time series of the global averaged long- and short-wave radiations (1984-2004) Problems of the ISCCP datasetsComparisons mean pattern comparison with SOC, NCEP1, and ERA40 time series comparison with buoy measurements

Objectively Analyzed air-sea Fluxes (OAFlux) website: http://oaflux.whoi.edu/The project is supported by NOAA Office of Climate Observation (OCO) and Climate Change and Data Detection (CCDD). PIs: Yu and Weller, with technical support from X.Jin

It is to develop gridded air-sea heat fluxes analysis for the global ice-free oceans for the past 50 years The development is based on a weighted objective analysis that combines surface meteorology from satellite retrievals, COADS ship observations, and model outputs from atmosphere reanalyses.

Data currently available online: Global QLH and QSH on daily/monthly and 1-grid for the years 1981-2005. Global QLW and QSW (1983-2004) are from ISCCP (Bill Rossow).

OAFlux: estimating QLH and QSHInput Data Sources Atmospheric reanalyses (NCEP/DOE and ERA40) Air humidity and temperature at 2m, surface wind at 10m, SST, sea level pressure Satellite retrievals: SSMI wind speed and air humidity, AVHRR SST, TMI and AMSR-E SST, scatterometer windsWeighted Objective Analysis: produce optimal estimate for variable fields through combining data from various sourcesBest estimates of daily flux-related variable fieldsDaily latent and sensible heat fluxes COARE bulk flux algorithm 3.0 (Fairall et al. 2003)References regarding the methodology and validation:

Yu, L., R. A. Weller, and B. Sun, 2004a: Improving latent and sensible heat flux estimates for the Atlantic Ocean (1988-1999) by a synthesis approach. J. Climate, 17, 373-393.

Yu, L., R. A. Weller, and B. Sun, 2004b: Mean and variability of the WHOI daily latent and sensible heat fluxes at in situ flux measurement sites in the Atlantic Ocean. J. Climate, 17, 2096-2118. Yu, L., and R. A. Weller, 2006: Objectively Analyzed air-sea heat Fluxes (OAFlux) for the global ice-free oceans: Trend and variability during 1981-2005. Submitted to Bull. Amer. Meteor. Soc.QLH = Le ce U (qs qa)QSH = cp cp U (Ts Ta)Four independent variablesU, Ts, qa, and Ta.

State of ocean heat fluxes in 2005

Difference 2005 -2004

Changes in oceanic heat fluxes and SST since 1981

Linear trends 1981-2005

Variance contributions of q and U

ISCCP Surface longwave and shortwave radiationsyearly-mean averaged over the global oceans

Problems in the ISCCP datasets(1) spatial structure

Effect on the EOF analysisThe Atlantic Ocean

Problems in the ISCCP datasets(2) mean bias: QLW+QSW (1984-2002)Positive downward

TRITON heat fluxes at (1.5S, 90E) (H. Hase/IORGC)shortwavenetsensiblelongwavelatent(provided by Dr. Yoshifumi Kuroda)OAFluxISCCP

Locations of in situ measurements All components No QLW x No QLW and QSW

Stratus buoy (693 days, 10/08/00 to 08/31/02)Fluxes comparison statistic based on daily means---------------------------------------------------------------------- QNET QLH+QSH QSW+QLW----------------------------------------------------------------------Buoys 50 -110 160OAFlux&ISCCP 54 ( +4) -113 ( -3) 168 ( +8)NCEP1 -14 (-64) -144 (-34) 130 (-30)ERA40 47 ( -3) -124 (-14) 171 (+11)----------------------------------------------------------------------30-day running mean appliedStatistics based on daily means

Pacific Basin: TAO arrayThe meridionally averaged mean QSW (Sep.1991 Aug.2002) for TAO array, ISCCP, ERA40, NCEP1 and NCEP2 as a function of longitude

QSW QLW 09/91 08/02 04/00 08/02TAO ArrayBOUY 227 -42 ISCCP 238 (+10) -30 (+11) NCEP1 208 (-19) -50 (-8) NCEP2 196 (-31) -38 (+3) ERA40 206 ( -21) -40 (+2)

Atlantic Basin

QSW QLW QSW +QLWPIRATA Array

(09/97 08/02)BOUY 217 ISCCP 235 (+18) -39 196NCEP1 212 ( -5) -54 158NCEP2 193 (-23) -43 150ERA40 194 ( -22) -45 149NTAS

(03/01 08/02)BOUY 242 -53 189 ISCCP 254 (+12) -58 (-5) 196 (+7)NCEP1 217 (-25) -57(-4) 161 (-28)NCEP2 244 (+2) -56 (-3) 188 (-1)ERA40 227 (-15) -51 (+2) 176 (-13)Subduction

(06/91 06/93)BOUY 200 -63 137ISCCP 207 ( +7) -58 (+5) 149 (+12)NCEP1 188 (-12) -60 (+3) 128 ( -9)NCEP2 207 ( +7) -59 (+4) 148 (+11)ERA40 201 ( +1) -60 (+3) 141 (+4)CMO

(07/96 06/97)BOUY 132 -39 93ISCCP 138 ( +6) -54 (-15) 84 ( -9)NCEP1 147 (+15) -61 (-22) 86 ( -7)NCEP2 167 (+35) -68 (-29) 99 ( +6)ERA40 150 (+18) -60 (-21) 90 ( -3)

SummaryThe OAFlux product 1981-2005: a synthesis of satellite observations and NWP reanalyses outputs of surface meteorology.

Surface latent and sensible heat fluxes There is a long-term trend in latent heat flux. The mean has increased by about 10Wm-2 since 1981, which amounts to almost 12% change. The increasing trend in latent heat flux is in concert with the warming trend of global SST.

Surface longwave and shortwave radiations (ISCCP) time series of the global averaged long- and short-wave radiations (1984-2004) Problems of the ISCCP datasets: (1) spatial structure is affected by the mean drifts in different sensors (2) mean bias in the tropical oceans: Too much net downward QSW

Input data and procedure of the objective analysis. In situ observations are not used for the period from 1981 onward.(1) It is not clear whether the reduction in latent heat flux in 2005 is a temporary perturbation or a change of the trend(2) There is a long-term upward trend in latent heat loss, but not in sensible heat loss.(3) The latent heat flux has increased by about 10 Wm-2 between 1981 and 2005, which amounts to almost 12% increase of the mean value.(1) (Fig.b) q is the primary contributor and accounts for more than 50% of the total variance. (2) (Fig.c) U is the dominant term in the tropical oceans, particularly in the Indian and western Pacific.(3) (Fig.d) The covariance of yearly anomalies, U and q, is generally weak, accounting for less than 4% of the total variance, except for a small region in the central equatorial Pacific. Do the fluctuations represent the real change? Mean pattern looks smooth, but not the anomaly pattern.The mean drifts in different sensors affect the EOF analysis.ISCCP net downward radiation is positive biased in the equatorial region. Away form the equator, the sign of biases can be either positive or negative.This page is provided by Yoshifumi Kuroda at JAMSTEC.Mean differences in QLW and QSW between buoy and ISCCP estimates are large. QSW (ISCCP-Buoy) = 33.2 Wm-2QLW(ISCCP-Buoy) = 7.3Wm-2About the TableNumbers in white denote the mean values, those in colors denote the differences from buoys.