README file for fluxWCURFSM*.cdf This readme file serves to describe the Cronin et al. 2006 flux files based upon TAO 95W and 110W moorings that were enhanced for the Eastern Pacific Investigation of Climate processes (EPIC) experiment from 1999-2004. The daily (*_dy.cdf) and monthly (* _mn.cdf) flux files created by Meghan Cronin on Jan 3, 2006, and Hourly (*_hr.cdf) flux files created Dec 30 2005, are provided online at: https://www.pmel.noaa.gov/tao/epic/taoepic_flux.html If you use these data, please cite Cronin et al. (2006): Cronin, M. F., Fairall, C. W., and McPhaden, M. J. (2006), An assessment of buoy-derived and numerical weather prediction surface heat fluxes in the tropical Pacific, J. Geophys. Res., 111, C06038, doi:10.1029/2005JC003324. Please also acknowledge the NOAA/PMEL TAO-EPIC project if you use these data in publications and send a preprint and/or reprint to -- Kenneth.Connell@noaa.gov for inclusion in the GTMBA Project bibliography, and to -- Nathan.Anderson@noaa.gov for inclusion in the OCS Project bibliography. Comments and questions regarding the mooring data should be directed to kenneth.connell@noaa.gov Comments and questions regarding the flux calculation should be directed to Meghan.F.Cronin@noaa.gov Comments and questions regarding the website should be directed to Nathan.Anderson@noaa.gov Details of the flux calculation can be found in Cronin et al. (2006). Briefly: * fluxWCURFSM*_hr.cdf << hourly fluxes with currents & FSM data fluxes are computed from hourly-averaged buoy data using the matlab version of the Fairall et al. v30a. Hourly averaged buoy data are computed from high resolution 10 minute buoy data, using a 13-point hanning filter and sub-sampling to once per hour. * FSM in filename indicates inclusion of fastmode data (after the mooring was anchored) inserted into the high res data to reduce gaps associated with mooring recovery deployment. This was important for ship/buoy intercomparisons. * Warm layer/cool skin correction was applied. For hourly flux calculation when highres shortwave radiation data was available, the corrrection is computed using the COARE algorithm model. The models also require longwave radiation input. If LWR is not available, but SWR is, the Bunker et al. (1976) algorithm was used to estimate LWR. When high resolution solar radiation is not available (data gap), or if the flux is being calculated from daily-averaged data, a default coolskin correction of 0.2C and no warm layer correction are applied. * winds are relative to 10 m sontek current meter data. When 10 m current meter is not available, OSCAR (satellite derived) surface currents were used. WCUR in the flux filename indicates that 10 m current meter data were available at that site. * Daily-averaged fluxes were created by smoothing hourly flux time series with a 24-hour boxcar and subsampling to once per day, with a timestamp at the center of the averaging period. * If "nort" is NOT included in the filename, then Gaps in daily-averaged fluxes are filled with flux time series computed from telemetered daily-averaged bulk data, with a latitude dependent mesoscale gustiness added to the vector-averaged daily winds. * "nort" in the filename indicates that only high-resolution delay-mode data were used in the calculation. This version has some months-long gaps when the mooring failed due to vandalism or other factors and the "ATLAS tube" could not be recovered. * When incoming LWR is not available, a bulk net longwave radiation is computed based upon the Bunker et al. (1976) algorithm. * For calculation of the monthly averaged fluxes, gaps of up to 9 days are linearly interpolated. Monthly averages are then computed using a 31-day boxcar. Monthly data are then subsampled to once per month in ferret by applying the grid defined as: define axis/t="15-nov-1999 12:00":"15-dec-2003 12:00"/npoints=50 tmonths Other notes: * An albedo value of 0.055 is assumed for the Net Shortwave Radiation: Qsw = (1-0.055)*SWR * The sensible heat flux of Rain, RF, is not included in the net surface heat flux estimate Q0. Variables included in the fluxWCURFSM95w_dy.cdf file: Q0:long_name = "Net Surface Heat Flux" ; [Wm-2] Qsw:long_name = "Net Shortwave Radiation" ; [Wm-2] Qlw:long_name = "Net Longwave Radiation" ; [Wm-2] QE:long_name = "Latent Heat Flux" ; [Wm-2] QH:long_name = "Sensible Heat Flux" ; [Wm-2] RF:long_name = "Sensible Heat Flux due to Rain" ; [Wm-2] LWR:long_name = "Incoming Longwave Radiation" ; [Wm-2] T0:long_name = "Skin Temperature best estimate" ; [C] TAU:long_name = "Wind Stress" ; [Nm-2] TAUX:long_name = "Zonal Wind Stress" ; [Nm-2] TAUY:long_name = "Meridional Wind Stress" ; [Nm-2] evap:long_name = "Evaporation" ; [mm/hr] EMP:long_name = "Evaporation - Precipitation" ; [m/s] dTsea:long_name = "Warm Layer Correction" ; [C] DTCOOL:long_name = "Cool Skin Correction" ; [C] WG:long_name = "Gustiness factor" ; [m/s] QAT_5021:long_name = "Air Temp Quality Index" ; QRH_5910:long_name = "RH Quality Index" ; * Sampling, Sensors, and Moorings: For detailed information about sampling, sensors, and moorings, see these web pages: http://www.pmel.noaa.gov/gtmba/sensor-specifications http://www.pmel.noaa.gov/gtmba/sampling http://www.pmel.noaa.gov/gtmba/moorings * Air Temperature and Relative Humidity Quality Codes: Using the quality codes you can tune your analysis to trade-off between quality and temporal/spatial coverage. Quality code definitions are listed below 0 = Datum Missing. 1 = Highest Quality. Pre/post-deployment calibrations agree to within sensor specifications. In most cases, only pre-deployment calibrations have been applied. 2 = Default Quality. Default value for sensors presently deployed and for sensors which were either not recovered, not calibratable when recovered, or for which pre-deployment calibrations have been determined to be invalid. In most cases, only pre-deployment calibrations have been applied. 3 = Adjusted Data. Pre/post calibrations differ, or original data do not agree with other data sources (e.g., other in situ data or climatology), or original data are noisy. Data have been adjusted in an attempt to reduce the error. 4 = Lower Quality. Pre/post calibrations differ, or data do not agree with other data sources (e.g., other in situ data or climatology), or data are noisy. Data could not be confidently adjusted to correct for error. 5 = Sensor or Tube Failed.