Advanced Remote Sensing Data Analysis and Application References: Chou, M.-D., W. Zhao, and S.-H. Chou, 1998: Radiation budgets and cloud radiative forcing in the Pacific warm pool during TOGA COARE. J. Geophys. Res., 103, Chou, M.-D., P.-K. Chan, and M. M.-H. Yan, 2001: A sea surface radiation dataset for climate applications in the tropical western Pacific and South China Sea. J. Geophys. Res., 106, Chou, S.-H., 1993 : A comparison of airborne eddy correlation and bulk aerodynamic methods for ocean-air turbulent fluxes during cold-air outbreaks. Bound.-Layer Meteor., 64, Chou, S.-H., R. M. Atlas, C.-L. Shie, and J. Ardizzone, 1995: Estimates of surface humidity and latent heat fluxes over oceans from SSM/I data. Mon. Wea. Rev., 123, Chou, S.-H., C.-L. Shie, R. M. Atlas, and J. Ardizzone, 1997: Air-sea fluxes retrieved from Special Sensor Microwave Imager data. J. Geophys. Res., 102, Chou, S.-H., W. Zhao, and M.-D. Chou, 2000: Surface heat budgets and sea surface temperature in the Pacific warm pool during TOGA COARE. J. Climate, 13, Chou, S.-H., E. Nelkin, J. Ardizzone, R. M. Atlas, and C.-L. Shie, 2003: Surface turbulent heat and momentum fluxes over global oceans based on the Goddard satellite retrievals, version 2 (GSSTF2). J. Climate, 16, Curry, J. A., A. Bentamy, M. A. Bourassa, D. Bourras, E. F. Bradley, M. Brunke, S. Castro, S.-H. Chou, C. A. Clayson, W. J. Emery, L. Eymard, C. W. Fairall, M. Kubota, B. Lin, W. Perrie, R. A. Reeder, I. A. Renfrew, W. B. Rossow, J. Schulz, S. R. Smith, P. J. Webster, G. A. Wick, and X. Zeng, 2004: SEAFLUX. Bull. Amer. Meteor. Soc.,85, Chou, S.-H., M.-D. Chou, P.-K. Chan, P.-H. Lin, and K.-H Wang, 2004a: Tropical warm pool surface heat budgets and temperature: Contrasts between 1997/98 El Nino and 1998/99 La Nina. J. Climate, 17, Chou, S.-H., E. Nelkin, J. Ardizzone, and R. M. Atlas, 2004b: A comparison of latent heat fluxes over global oceans for four flux products. J. Climate, in press. Chou, S.-H., E. Nelkin, J. Ardizzone, and R. M. Atlas, 2004c: A comparison of latent heat fluxes over global oceans for four flux products. 13th Conf. on Interaction of the Sea and Atmosphere, 9-13 August 2004, Portland, Maine. (color figures)

Graduate Course: Advanced Remote Sensing Data Analysis and Application VERSION 2 GODDARD SATELLITE-BASED SURFACE TURBULENT FLUXES (GSSTF2) Shu-Hsien Chou Dept. of Atmospheric Sciences National Taiwan University , ext 262

Outlines: GSSTF2 Data Set GSSTF2 Data Set GSSTF2 Bulk Flux Parameterization GSSTF2 Bulk Flux Parameterization GSSTF2 Input Parameters GSSTF2 Input Parameters Validation of Input Parameters and Turbulent Fluxes Validation of Input Parameters and Turbulent Fluxes Spatial Distributions of Annual Mean Turbulent Fluxes and Input Parameters over Global Oceans Spatial Distributions of Annual Mean Turbulent Fluxes and Input Parameters over Global Oceans Spatial Distributions of Seasonal Mean Turbulent Fluxes and Input Parameters over Global Oceans Spatial Distributions of Seasonal Mean Turbulent Fluxes and Input Parameters over Global Oceans

Any problem about reading GSSTF2 data set, please contact: Shuk-Mei Tse Dept. of Atmospheric Sciences National Taiwan University , ext 220

Version 2 Goddard Satellite-Based Surface Turbulent Fluxes (GSSTF2; Chou et al. 2003) (1)* Latent heat flux (9) Total column water vapor (1)* Latent heat flux (9) Total column water vapor (2)* Zonal wind stress (10) SST (2)* Zonal wind stress (10) SST (3)* Meridional wind stress (11) 2-m temperature (3)* Meridional wind stress (11) 2-m temperature (4)* Sensible heat flux (12) SLP (4)* Sensible heat flux (12) SLP (5)* 10-m specific humidity (5)* 10-m specific humidity (6)* 500-m bottom layer water vapor (6)* 500-m bottom layer water vapor (7)* 10-m wind speed (7)* 10-m wind speed (8)* Sea-air humidity difference (8)* Sea-air humidity difference Duration: July 1987–Dec 2000 Spatial resolution: 1 o x 1 o lat-lon Temporal resolutions: one day, and one month (Combine DMSP F8, F10, F11, F13, F14 satellites) Climatology: monthly- and annual-mean ( , combine all satellites) *Archive at NASA/GSFC DAAC: Chou, S.-H., E. Nelkin, J. Ardizzone, R. M. Atlas, and C.-L. Shie, 2003: Surface turbulent heat and momentum fluxes over global oceans based on the Goddard satellite retrievals, version 2 (GSSTF2). J. Climate, 16,

Table 1. Characteristics of SSM/I on board DMSP satellites Center of freq ( GHZ ) Center of channels (mm) Polarization V, H V V, H V, H 3 dB footprint (km x km) 69x43 50x40 37x29 15x13 Swath width (km) Spatial sampling (deg) SSM/I --- Special Sensor Microwave/Imager DMSP --- Defense Meteorological Satellite Program

Table 2. Approximate local times (LT) of equatorial crossing and data records for each SSM/I of the DMSP satellites used in the derivation of GSSTF2. –––––––––––––––––––––––––––––––––––––––––– SatellitesEquatorial Data records __________crossing (LT)__________________________ F081815/06159 Jul 1987 – 31 Dec 1991 F100945/21451 Jan 1991 – 14 Nov 1997 F110600/18001 Jan 1992 – 31 Dec 1996 F130600/18003 May 1995 – 31 Dec 2000 F140845/20458 May 1997 – 31 Dec 2000 ––––––––––––––––––––––––––––––––––––––––––– descend/ascend

24-hour coverage provided by : (a) The F8 SSM/I (b) The F10 and F11 SSM/Is in combination

Definition of parameters for bulk flux model: Z -- Reference height for wind, temperature, and humidity (can be different for different variables) Z -- Reference height for wind, temperature, and humidity (can be different for different variables) U -- Surface wind speed at Z U -- Surface wind speed at Z  s -- Sea surface temperature (SST)  s -- Sea surface temperature (SST) Qs – Sea surface saturation specific humidity (salinity, cool skin effect) Qs – Sea surface saturation specific humidity (salinity, cool skin effect) Q -- Surface air specific humidity at Z Q -- Surface air specific humidity at Z  -- Surface air potential temperature at Z  -- Surface air potential temperature at Z  -- Air density  -- Air density Cp -- Isobaric specific heat Cp -- Isobaric specific heat Lv -- Latent heat of vaporation Lv -- Latent heat of vaporation C D, C H, C E – Bulk transfer coefficients for momentum, sensible and latent heat fluxes C D, C H, C E – Bulk transfer coefficients for momentum, sensible and latent heat fluxes L -- Monin-Obukhov length { =  v u * 2 /( g k  v * ) } L -- Monin-Obukhov length { =  v u * 2 /( g k  v * ) } k -- von Karmen constant ( =0.4) k -- von Karmen constant ( =0.4)  --  kinematic viscosity of air  --  kinematic viscosity of air

GSSTF2 BULK FLUX MODEL: (Chou 1993; Chou et al. 2003) Wind stress  =  C D (U – Us) 2 Sensible heat flux F SH =  Cp C H (U – Us) (  s –  ) Latent heat flux F LH =  Lv C E (U – Us) (Qs – Q) Input parameters: U(Z),  s, , Qs, Q(Z) and Z * C D, C H, and C E depend on U, (  s –  ), and (Qs – Q) (Monin-Obukhov similarity theory or surface layer similarity theory) Us = 0.55 u *

GSSTF2 BULK FLUX MODEL: (Chou 1993; Chou et al. 2003) Wind Stress  =  u * 2 Sensible Heat Flux F SH = –  Cp u *  * Latent Heat Flux F LH = –  Lv u * q * Flux – Profile Relationship in Atmospheric Surface Layer: (U – Us)/u * = [ln(Z/Z o ) –  u (Z/L)]/k (  –  s )/  * = [ln(Z/Z oT ) –  T (Z/L)]/k (Q – Qs)/q * = [ln(Z/Z o q ) –  q (Z/L)]/k  =∫(1 –  ) d ln(Z/L), L =  v u * 2 /(g k  v* )  u = (1 – 16 Z/L)  0.25,  T =  q = (1 – 16 Z/L )  0.5 (unstable)  u =  T =  q = Z/L (stable), k = 0.40

GSSTF2 BULK FLUX MODEL: (Chou 1993; Chou et al. 2003) * C D, C H, and C E depend on U, (  S –  ), and (Q S – Q) (Monin-Obukhov similarity theory) C D = k 2 /[ln( Z / Z O ) –  u ( Z/L )] 2 C H = C D 1/2 k/[ln( Z / Z OT ) –  T ( Z/L )] C E = C D 1/2 k/[ln( Z / Z O q ) –  q ( Z/L )] Z o = u * 2 / g  /u * ( momentum roughness length) Z o T =  /u * [a 1 ( Z O u * /  ) b1 ] ( temperature roughness length) Z oq =  /u * [a 2 ( Z O u * /  ) b2 ] ( humidity roughness length) Z oq =  /u * [a 2 ( Z O u * /  ) b2 ] ( humidity roughness length)

RETRIEVAL OF GSSTF2 FLUXES: (Chou et al. 2003) Wind Stress  =  C D (U – U S ) 2 Sensible Heat Flux F SH =  Cp C H (U – U S ) (  S –  ) Latent Heat Flux F LH =  Lv C E (U – U S ) (Q S – Q) U -- daily SSM/I-v4 10-m wind (Wentz 1997) U -- daily SSM/I-v4 10-m wind (Wentz 1997)  S -- daily SST (NCEP reanalysis)  S -- daily SST (NCEP reanalysis) Q S x e S /p S (salinity, cool skin effect) Q S x e S /p S (salinity, cool skin effect) Q -- daily SSM/I-v4 10-m specific humidity (Chou et al. 1995, 1997) Q -- daily SSM/I-v4 10-m specific humidity (Chou et al. 1995, 1997)  -- daily 2-m potential temp (NCEP reanalysis)  -- daily 2-m potential temp (NCEP reanalysis) Stress direction -- SSM/I-v4 10-m wind direction (Atlas, et al. 1996) Stress direction -- SSM/I-v4 10-m wind direction (Atlas, et al. 1996) C D, C H, C E depend on U, (  S –  ) & (Q S – Q) (Monin-Obukhov similarity or surface layer similarity theory) C D, C H, C E depend on U, (  S –  ) & (Q S – Q) (Monin-Obukhov similarity or surface layer similarity theory) Chou, S.-H., E. Nelkin, J. Ardizzone, R. M. Atlas, and C.-L. Shie, 2003: Surface turbulent heat and momentum fluxes over global oceans based on the Goddard satellite retrievals, version 2 (GSSTF2). J. Climate, 16,

ASTEX: Atlantic Stratocumulus Transition Experiment COARE: Coupled Ocean-Atmosphere Response Experiment FASTEX: Fronts and Atlantic Storm Track Experiment JASMINE: Joint Air-Sea Monsoon Interaction Experiment KWAJEX: Kwajalein Experiment NAURU99: Nauru ’99 Experiment SCOPE: San Clemente Ocean Probing Experiment TIWE: Tropical Instability Wave Experiment PACSF99: Pan-American Climate Study in eastern Pacific during 1999 MOORINGS: Buoy service in the North Pacific

1913-hourly fluxes calculated from ship data using GSSTF2 bulk flux model vs observed (a) wind stresses determined by ID method, (b) latent and (c) sensible heat fluxes determined by covariance method of 10 field experiments. C: COARE F: FASTEX X: other experiments

GSSTF2 daily (a) wind speeds, (b) specific humidity, and (c) temperature of surface air vs those of nine field experiments. C: COARE F: FASTEX X: other experiments

GSSTF2 daily flux retrievals vs observed (a) ID wind stresses, (b) covariance latent heat fluxes, and (c) covariance sensible heat fluxes of nine field experiments. C: COARE F: FASTEX X: other experiments

Annual Average

Conclusion: GSSTF2 is a 13.5-yr (July 1987-Dec 2000) global dataset of daily ocean surface turbulent fluxes of momentum, latent and sensible heat, with 1 o resolution GSSTF2 is a 13.5-yr (July 1987-Dec 2000) global dataset of daily ocean surface turbulent fluxes of momentum, latent and sensible heat, with 1 o resolution GSSTF2 bulk flux model validated well by comparing computed hourly fluxes from research ship data with those of 10 field experiments conducted over tropical and northern midlatitude oceans during GSSTF2 bulk flux model validated well by comparing computed hourly fluxes from research ship data with those of 10 field experiments conducted over tropical and northern midlatitude oceans during GSSTF2 daily wind stress, LHF, wind speed, surface air humidity, and SST compare reasonably well with those of collocated nine field fields experiments during GSSTF2 daily wind stress, LHF, wind speed, surface air humidity, and SST compare reasonably well with those of collocated nine field fields experiments during Global distributions of GSSTF annual- and seasonal-mean turbulent fluxes show reasonable patterns related to atmospheric general circulation and seasonal variations Global distributions of GSSTF annual- and seasonal-mean turbulent fluxes show reasonable patterns related to atmospheric general circulation and seasonal variations GSSTF2 is useful for studying intra-seasonal to inter-annual variability, Asian monsoon, ENSO, water cycle, and surface heat budgets GSSTF2 is useful for studying intra-seasonal to inter-annual variability, Asian monsoon, ENSO, water cycle, and surface heat budgets

NASA QuikSCAT scatterometer 10-m vector wind averaged for November 1999 and the corresponding divergence field. Red and blue denote convergence and divergence respectively.

Three-day composite average maps of sea surface temperature for July 1998, during a time of year when the equatorial Pacific and Atlantic are typically cool. The maps are based on measurements from a satellite microwave radiometer (TMI). White areas represent land or rain contamination. The sharp northern edge of the cold tongue is distorted by westward-propagating tropical instability waves, which originate in the ocean but produce a distinct signature in the fields of cloudiness and wind speed.