README file for: Daily Satellite Products Derived from SSM/I over the west Pacific and Indian Ocean. The name GAME stands for the GEWEX Asian Monsoon Experiment which these images and products were originally developed to support. Produced by Wesley Berg at the NOAA/CIRES Environmental Technology Laboratory ------------------------------------------------------------------------------- SSM/I product images (GAME*.gif): Daily product images computed from SSM/I from multiple satellites (including F10, F11, F13, and F14). The data has been gridded into a 0.25 by 0.25 degree rectangular lat/lon grid from 45S to 45N and 0 to 180E. References for the retrieval algorithms are included below. rn2 -> rainfall rate in mm/hour (Ferriday algorithm). To convert to mm/day multiply by 24 and divide by 100 (the data scale factor). wvp -> column integrated water vapor in g/cm^2 (Schluessel algorithm). Divide the integer*2 values by 1000 to get values in g/cm^2. clw -> column integrated cloud liquid water in g/m^2 (Weng algorithm). Divide the integer*2 values by 1000 to get values in g/m^2. SSM/I product data files (GAME*.dat.gz): The gridded data files from which the gif files were produced. These are stored as direct access files of 720 columns by 360 rows. To minimize storage space, the estimates are stored as 2-byte (short) integer values which have been multiplied by 100 for rn2 and by 1000 for clw and wvp. To get the actual estimates, therefore, it is necessary to divide the values by 100 for rn2 and 1000 for wvp and clw when reading the data. The files were written on a Sun computer so it may be necessary to perform byte swapping for PC's or certain other computer systems. The lat/lon coordinates specified below are for the center of the bins. All of the data files have been compressed using gzip. DATA TYPE: 2-byte integer SCALE: multiply by 0.01 (rn2) or 0.001 (wvp and clw) to get actual data values (there is no offset) LONGITUDE: 720 values from 0.125 E to 179.875 E incrementing by 0.25 deg LATITUDE: 360 values from 44.875 N to 44.875 S incrementing by 0.25 deg MISSING VALUE: -1 -------------------------------------------------------------------------- Files (shown for year 99, julian day 001 -> Jan 01, 1999): GAMEclw_99001.gif -> SSM/I cloud liquid water image GAMEwvp_99001.gif -> SSM/I integrated water vapor images GAMErn2_99001.gif -> SSM/I rainfall image GAMEclw_99001.dat -> SSM/I cloud liquid water data file GAMEwvp_99001.dat -> SSM/I integrated water vapor data file GAMErn2_99001.dat -> SSM/I rainfall data file -------------------------------------------------------------------------- Algorithm References: Ferriday global rainfall algorithm: This algorithm is based on a fairly simple combination of the SSM/I channels utilizing all four SSM/I frequences as well as dual polarization information. The algorithm was developed by James Ferriday and is discussed in detail in the following paper. Ferriday, J. G. and S. K. Avery, 1994: Passive microwave remote sensing of rainfall with SSM/I: Algorithm development and implementation, J. Appl. Meteor., Vol 33, pp. 1587-1596. * Note: Different algorithms are utilized over land and ocean with the ocean algorithm using both liquid water emission and ice scattering information while the land algorithm uses a simple ice scattering retrieval technique. The emission technique over the ocean is a more direct measure of cloud liquid water or rainfall. Since the land algorithm only detects scattering by ice particles, not only is low level warm rain is not detected, but the relationship between the ice scattering signal and precipitation is difficult to quantify. Looking at the daily images one will note that large systems which contain a significant ice layer will produce a relatively consistant rainfall estimate over land/ocean boundaries, however smaller systems often show significant discontinuities over the land/ocean boundary. Another problem over land is discriminating between cloud ice and snow cover. This is manifest as a persistant rainfall signal over both the Chilean Andes and the Rocky Mountains during northern hemisphere winter. Over oceans a sea ice detection algorithm has been used as well to eliminate a similar problem, although this should not be much of a problem below the 45 degree latitude cutoff. In addition, there are problems over coastal boundaries due to geolocation errors resulting in the use of the ocean algorithm for pixels with partial land coverage. Because of these limitations the user is cautioned when using the land cover rain estimates. They can certainly be useful in a qualitative sense, but quantitative accuracy is suspect. For additional information refer to the Ferriday and Avery 1994 paper or contact Wesley Berg at the address given below. Weng cloud liquid water algorithm: This is an updated version of the operational cloud liquid water path retrieval algorithm. Because of significant improvements in this algorithm from the original, cloud liquid water path estimates prior to 1995 made with that algorithm have been deleted. Weng, F. and N. C. Grody, 1994: Retrieval of cloud liquid water using the special sensor microwave imager, J. Geophys. Res., Vol 99, pp. 25,535. Weng, F., N. C. Grody, R. R. Ferraro, A. Basist, and D. Forsyth, 1996: Cloud liquid water climatology from the special sensor microwave imager, submitted to J. Climate. Schluesel total column integrated water vapor: Estimates of the total column integrated water vapor amount are estimated using information from the 22.235 GHz SSM/I channel, which is centered on a weak water vapor line. Integrated water vapor is the simplest and most accurate product to retrieve from the SSM/I and is therefore very useful for quantitative comparisons with model results or other data sets. Schluessel, P., and W. J. Emery, 1990: Atmospheric water vapour over oceans from SSM/I measurements, Int. J. of Remote Sensing, Vol 11, pp. 753. Schulz, J., P. Schluessel, and H. Grassl, 1993: Water vapour in the atmospheric boundary layer over oceans from SSM/I measurements, Int. J. Rem. Sens., Vol 14, pp. 2773. Bauer, P. and P. Schluessel, 1993: Rainfall, total water, ice water, and water vapor over sea from polarized microwave simulations and special sensor microwave/imager data, J. Geophys. Res., Vol 98, pp. 20,737. -------------------------------------------------------------------------- Disclaimer: The high resolution SSM/I derived daily products are limited by the available satellite sampling. For most days during this period there were between 3 and 4 satellites providing coverage, however, there are a a number of days with incomplete coverage. Due to the high variability of rainfall and cloud coverage, these fields are highly dependent on the number of satellite overpasses. As a result, sampling errors limit the quantitative accuracy for daily estimates. This is less of a problem with the column integrated water vapor estimates, however, it is stil a factor when comparing to in-situ radiosonde observations. In addition, as discussed above the rainfall estimates over land are primarily useful for qualitative analyses. If you have any problems or questions please contact Wesley Berg at the following address. -------------------------------------------------------------------------- Contact information: Dr. Wesley Berg (303) 497-6066 Cooperative Institute for Research (303) 497-3794 (fax) in Environmental Sciences (CIRES) email: Wesley.K.Berg@noaa.gov Campus Box 216 University of Colorado Boulder, CO 80309-0216 Satellite group web site: http://www1.etl.noaa.gov/climsat Personal web site: http://www1.etl.noaa.gov/~wkb/