GPCP_PRC.DOC


                             1.  TITLE

1.1  Data Set Identification.

     Precipitation.

     (Monthly ; GPCP/GPCC)

1.2  Data Base Table Name.

     Not Applicable.

1.3  CD-ROM File Name.

     \DATA\HYDR_SOL\GPCP_PRC\nnYyyMmm.sfx

     Note: capital letters indicate fixed values that appear on the CD-ROM 
     exactly as shown here, lower case indicates characters (values) that 
     change for each path and file.

     The format used for the filenames is: nnYyyMmm.sfx, where nn is the type 
     of precipitation data product (e.g. GR=Gridded surface observations, 
     BR=Browse product), yy is the last two digits of the year (e.g., 
     Y87=1987), and mm is the month of the year (e.g., M12=December).  The 
     filename extension (.sfx), identifies the data set content for the file 
     (see Section 8.2) and is equal to .PRC and .FYI (For Your Information) 
     for this data set. Files ending in .PRC contain precipitation data, while 
     files ending in .FYI contain information on the number of stations per 
     grid for GR files and information on data source (i.e., satellite, 
     model) for BR files.

1.4  Revision Date Of This Document.

     April 5, 1995

                         2.  INVESTIGATOR(S)

2.1  Investigator(s) Name And Title.

     Mr. Bruno Rudolf
     Global Precipitation Climatology Centre
     Deutscher Wetterdienst

2.2  Title Of Investigation.

     WCRP Global Precipitation Climatology Project (GPCP)

2.3  Contacts (For Data Production Information).

_________________________________________________________
              |      Contact 1     |    Contact 2        |
______________|____________________|_____________________|
2.3.1 Name    |Mr Bruno Rudolf     |Mr Udo Schneider     |
2.3.2 Address |GPCP/GPCC           |GPCP/GPCC            |
              |Deutscher Wetter-   |Deutscher Wetter-    |
              |dienst              |dienst               |
              |Zentralamt K7/WZN   |Zentralamt K7/WZN    |
              |Postfach 10 04 65   |Postfach 10 04 65    |
      City/St.|Offenbach/Germany   |Offenbach/Germany    |
      Zip Code|63004               |63004                |
2.3.3 Tel.    |+49-69-8062-2981    |+49-69-8062-2980     |
2.3.4 Email   |                    |                     |
______________|____________________|_____________________|

2.4  Requested Form of Acknowledgment.

     Thanks to B. Rudolf and U. Schneider of the WCRP Global Precipitation 
     Climatology Centre for Providing the GPCP/GPCC, 1994: Preliminary 1987/88 
     continental precipitation data sets for ISLSCP on a 1 degree grid based 
     on precipitation-gauge measurements.
 
                            3.  INTRODUCTION

3.1  Objective/Purpose.

     The Global Precipitation Climatology Project (GPCP) was initiated by the
     World Climate Research Program (WCRP). The Global Precipitation Clima-
     tology Center (GPCC), which is operated by the Deutscher Wetterdienst 
     (National Meteorological Service of Germany), is a central element of the
     GPCP. The main purpose of the GPCP (for details see WCRP, 1990) is to
     evaluate and provide global gridded data sets of monthly precipitation
     based on all suitable observation techniques as a basis for:

     -  verification of climate model simulations,
     -  investigations of the global hydrological cycle and
     -  climate change detection studies.
 
3.2  Summary of Parameters.

     Gridded monthly precipitation, as well as the number of stations per 
     grid.

     Global gridded data sets of monthly precipitation derived from 
     precipitation-gauge measurements including the number of stations per 
     grid used in the objective analysis. A browse precipitation product 
     created from ground, satellite and model precipitation data is also 
     supplied.

     A browse product of global precipitation created by merging ground, 
     satellite and model precipitation data sets is also supplied. Information 
     on the source of data (i.e., ground, satellite or model) is supplied with 
     the browse data.

3.3  Discussion.

     The main task of the GPCP/GPCC is the evaluation of global gridded data
     sets of monthly precipitation on the basis of all suitable observation
     techniques, such as conventional precipitation-gauge measurements 
     and estimates from satellite infrared and passive microwave data. The 
     satellite-based rainfall estimates provided to the GPCC are derived by 
     the satellite component operators of the GPCP, which are operated by the 
     Climate Analysis Center (CAC) of NOAA (IR-component), Washington D.C., 
     and by the NASA Goddard Space Flight Center (microwave component) in 
     Greenbelt, MD.

     The GPCC collects monthly precipitation totals received in climate 
     reports via the World Weather Watch GTS (Global Telecommunication System) 
     and calculates monthly totals from synoptic reports. The GPCC also 
     acquires monthly precipitation data from international/national 
     meteorological and hydrological services/institutions. On the basis of 
     these precipitation-gauge measurements, gridded analyses over land areas 
     are carried out using a spatial objective analysis method (see Rudolf, 
     1993). 

     In order to produce complete global data sets the GPCC is merging these
     precipitation-gauge analyses with satellite based rainfall estimates 
     over the tropical to mid-latitude oceans by using a simple blending 
     scheme. Gaps in polar regions are filled with model estimates accumulated 
     from daily forecasts of the weather prediction model of ECMWF (European 
     Centre for Medium-Range Weather Forecasts), Reading UK. In the future, 
     the merging will be performed using a quality-dependent weighting scheme. 

     The 1 x 1 degree precipitation data sets, produced for this CD-ROM, are 
     based only on the precipitation-gauge analysis.  The 2.5 degree 
     satellite-based estimates are not available at a 1 degree resolution.

                        4.  THEORY OF MEASUREMENTS

The main basis for the precipitation analyses over land are conventional 
precipitation-gauge measurements. Area-average monthly precipitation is 
calculated from the point measurements by using a spatial objective analysis 
method, which is based on an inverse distance and directional weighting. The 
point measurements at the stations are representative only for an area 
surrounding the rain-gauge, the size of which depends on orographic and 
climatic conditions.

The methodological error in obtaining area-average precipitation from point 
measurements depends on the analysis method used and on the spatial density 
and distribution of the point measurements. Inaccuracies of the point 
precipitation data consist of two parts, the systematic gauge-measuring error 
and a random error component. (For details, see section10.1).

                            5.  EQUIPMENT

5.1  Instrument Description.

     Below are descriptions of surface rain gauges.  The satellite 
     instruments, which produced the data used for the satellite precipitation 
     data has not been described, since this is only a browse product.

     5.1.1  Platform.

            The height of the gauge orifice varies between zero and more than 
            1 m above the ground. This is defined by countrie's national 
            standards (see section 5.1.4 for more detail).

     5.1.2  Mission Objectives.

            To measure precipitation.

     5.1.3  Key Variables.

            Precipitation.

     5.1.4  Principles of Operation.

            The operation and type of precipitation-gauges vary depending on 
            the country (See section 5.1.5 for details). Generally, national 
            daily standard-gauges measure precipitation at or near the ground, 
            and are observed at least once a day.

     5.1.5  Instrument Measurement Geometry.

            A large variety of instrument types for precipitation-gauge 
            measurements are in use world-wide (ca. 100). The geometry and 
            size of the different instrument types can vary considerably (see 
            Sevruk, 1982).

            National daily standard gauges are observed at least once a day 
            and thus must be big enough to collect more than the average one-
            day or maximum 1-2 hour precipitation which differs according to 
            various climatic conditions. The standard gauges are also commonly 
            used to measure both rain and snow, and the latter affects 
            fundamentally the form and dimensions of a particular national 
            gauge (snow gauges are bigger). Thus, in countries with negligible 
            snowfall but much rain or where different gauges are used for rain 
            and snow (e.g., Canada), it is advantageous if the gauge orifice 
            is small (Canada, 47 cm^2; Belgium, 100 cm^2, U.K. 125 cm^2 but 
            Australia 324 cm^2) or the collector is shallow with a steep 
            funnel (Australia, Belgium). In both cases, the wetting losses 
            tend to be relatively small. In areas with little snowfall, gauges 
            can be installed so that the rim is near to the ground (0.3 m in 
            Australia, Belgium, Canada (in summer) and U.K., 0.4 in Holland).  
            This reduces losses from wind and consequently the systematic 
            error. In contrast, in countries with heavy snowfall the gauges 
            are, in general, large (500 cm^2 in ex-Czechoslovakia and Finland; 
            325 cm^2 in U.S.A., but 200 cm^2 in most European countries) and 
            the collectors are deep. Thus the wetting losses for rain tend to 
            be relatively large. In addition, the precipitation gauges in 
            these countries are set high above ground-level (1 m in ex-
            Czechoslovakia, Federal Republic of Germany and the U.S.A.; 1.5 m 
            in Denmark, Finland and Switzerland; and 2 m in the ex-U.S.S.R) 
            and the systematic error for measurement of rain is relatively 
            greater. In some countries or regions which experience heavy 
            snowfall, the daily standard precipitation gauges are even 
            equipped with windshields (Finland, Norway, U.S.S.R.); or special 
            snow gauges may be used (Canada).

     5.1.6  Manufacturer of Instrument.

            Varies by country - documented in country's national metadata 
            archive.

5.2  Calibration.

     5.2.1  Specifications.

            Corrections for systematic gauge-measuring errors (generally an
            undercatch of the actual precipitation) are planned, but not
            available at this revision.

            5.2.1.1  Tolerance.

                     Not available at this revision.

     5.2.2  Frequency of Calibration.

            None.

     5.2.3  Other Calibration Information.

            None. 

                          6.  PROCEDURE

6.1  Data Acquisition Methods.

     The GPCC collects monthly precipitation totals received in climate 
     reports via the World Weather Watch GTS (Global Telecommunication System) 
     and calculates monthly totals from synoptic reports. The GPCC also 
     acquires monthly precipitation data from international/national 
     meteorological and hydrological services/institutions. These additional 
     monthly precipitation data are acquired in the framework of the WCRP 
     Global Precipitation Climatology Project with support of the World 
     Meteorological Organization (WMO) and on the basis of bilateral contacts 
     from international/regional institutions and from national 
     meteorological/hydrological services (see Rudolf, 1993).

6.2  Spatial Characteristics.

     The horizontal resolution of the data set prepared for ISLSCP is 1 X 1 
     degree lat/long. (Up to now the horizontal resolution of the GPCP 
     products have been 2.5 X 2.5 degrees lat/long, but in future the data 
     sets will also be prepared at a higher spatial resolution).

     6.2.1  Spatial Coverage.

            The coverage of both gridded surface observation and satellite 
            browse precipitation are global.  Data in each file are ordered 
            from North to South and from West to East beginning at 180 degrees 
            West and 90 degrees North.  Point (1,1) represents the grid cell 
            centered at 89.5 N and 179.5 W (see section 8.4).

     6.2.2  Spatial Resolution.

            The data derived from gauge measurements, are given in an equal-
            angle lat/long grid that has a spatial resolution of 1 X 1 degree 
            lat/long.

            The data derived from satellite measurements are given in an 
            equal-angle lat/long grid that has a spatial resolution of 2.5 X 
            2.5 degree lat/long.

6.3  Temporal Characteristics.

     6.3.1  Temporal Coverage.

            January 1987 through December 1988.

     6.3.2  Temporal Resolution.

            Monthly totals.

                           7.  OBSERVATIONS

7.1  Field Notes.

     None.

                         8.  DATA DESCRIPTION

8.1  Table Definition With Comments.

     Not available. 

8.2  Type of Data.

--------------------------------------------------------------------------------
|                 8.2.1                  |               |          |          |
|Parameter/Variable Name                 |               |          |          |
--------------------------------------------------------------------------------
|    |               8.2.2               |     8.2.3     |  8.2.4   |  8.2.5   |
|    |Parameter/Variable Description     |Range          |Units     |Source    |
--------------------------------------------------------------------------------
|PRECIP_GAUGE                            |               |          |          |
|    |Monthly precipitation as analyzed  |min = 0        |[MM]      |Rain-gauge|
|    |from precip-gauge measurements.    |max = 1800     |          |measure-  |
|    |                                   |               |          |ments     |
|    |                                   |               |          |          |
--------------------------------------------------------------------------------
|PRECIP_BROWSE (Satellite)               |               |          |          |
|    |Monthly precipitation browse data  |min =  0       |[MM]      |Satellite |
|    |produced from satellite data.      |max = 1000     |          |measure-  |
|    |                                   |               |          |ments     |
--------------------------------------------------------------------------------
|PRECIP_GAUGE_FYI                        |               |          |          |
|    |For your information files which   |min = 0        |[NA]      |Rain-gauge|
|    |contain the number of guages used  |max = 10       |          |measure-  |
|    |to derive precipitation for a grid |               |          |ments     |
|    |cell.                              |               |          |          |
--------------------------------------------------------------------------------
|PRECIP_BROWSE_FYI (Satellite)           |               |          |          |
|    |For your information files which   |min =  -42*    |[NA]      |Satellite |
|    |contain information on the # of    |max = 32*      |          |measure-  |
|    |gauges or satellite/model used to  |               |          |ments     |
|    |derive the browse precipitation    |               |          |          |
|    |data.                              |               |          |          |
--------------------------------------------------------------------------------
* The table below contains definitions for the numerical fields in the 
  PRECIP_BROWSE_FYI files
           Indication of the data source                         |
            >= 0   -->  number of stations per grid              |
                        included in the objective analysis.      |
            = -11  -->  derived from IR satellite data;          |   2.5 deg.
            = -21  -->  derived from SSM/I satellite data;       |   5   deg.
            = -22  -->  derived from SSM/I satellite data;       |   2.5 deg.
            = -31  -->  mixed satellite estimates; (IR+SSM/I)/2; |   2.5 deg.
            = -41  -->  ECMWF model results (0-24 H);            |   2.5 deg.
            = -42  -->  ECMWF model results (12-36 H);           |   2.5 deg.

8.3  Sample Data Base Data Record.

     Not applicable.

8.4  Data Format.

     The CD-ROM file format is ASCII, and consists of numerical fields of 
     varying length, which are space delimited and arranged in columns and 
     rows.  Each column contains 180 numerical values and each row contain 360 
     numerical values.  

          Grid arrangement

             ARRAY(I,J)
             I  = 1 IS CENTERED AT 179.5W
             I INCREASES EASTWARD BY 1 DEGREE
             J  = 1 IS CENTERED AT 89.5N
             J INCREASES SOUTHWARD BY 1 DEGREE

             90N - | - - - | - - - | - - - | - -
                   | (1,1) | (2,1) | (3,1) |
             89N - | - - - | - - - | - - - | - -
                   | (1,2) | (2,2) | (3,2) |
             88N - | - - - | - - - | - - - | - -
                   | (1,3) | (2,3) | (3,3) |
             87N - | - - - | - - - | - - - |
                  180W   179W    178W   177W

             ARRAY(360,180)

8.5  Related Data Sets.

     Not available.

                         9.  DATA MANIPULATIONS

9.1  Formulas.

     9.1.1  Derivation Techniques/Algorithms.

            The area-average precipitation is calculated from the 
            precipitation-gauge point measurements by using the spatial 
            objective analysis method known as the SPHEREMAP. This procedure 
            is based on the distance and angular weighting scheme on a plane 
            of Shepard (1968), which was transferred to spherical coordinates 
            by Willmott et al.  (1985). The method has been applied by Legates 
            (1987) to calculate his global precipitation climatology on a 0.5 
            degree grid.

9.2  Data Processing Sequence.

     9.2.1  Processing Steps and Data Sets.

            Gauge precipitation data:

            The philosophy behind the quality-control of the gauge-measured
            precipitation data at the GPCC is not to simply throw away "bad
            data", but to use as many of the data as possible, because they 
            might be important in data sparse areas and many data errors are 
            obvious and can be corrected (Schneider, 1993).

            First, the monthly precipitation amounts are checked for
            extreme values and against climatological normals. In a second 
            step, the point-measured precipitation data from different sources 
            are intercompared to check for discrepancies. As a last 
            step in the automatic quality-control procedure, the spatial 
            homogeneity of the point-measured monthly precipitation data is 
            checked.

            Subsequent to these automatic quality-control checks data flagged   
            as incorrect or questionable during this process are checked
            manually at a graphics workstation which can display all station-
            related information (e.g. geographical coordinates, elevation) and
            overlay topographic fields, such as orography, as background
            information.  

            Browse precipitation data:

            Below is a description of the Blending Scheme, used for Merging 
            the data from different observation techniques to get complete 
            global data sets

            -------------------------------------------|----------------------
                                    AREA               |       DATA USED
            -------------------------------------------|----------------------
            1. Over all land areas                     | Objective analysis of
               ( land-portion >= 50% )                 | gauge measurements
                                                       |
            2. Over ocean areas (landportion < 50%)    | (IR + SSMI)/2.
               within the "tropical" latitude belt     | (IR only if SSM/I 
               (definition see below)                  |  is missing )
                                                       |
            3. Over ocean areas (land-portion < 50%)   | SSM/I
               outside of the "tropical" latitude belt |
               up to 50 degree North, respectively to  |
               50 degree South                         |
                                                       |
            4. Over remaining areas not covered by any | ECMWF model results
               observed data                           |
            -------------------------------------------|----------------------

            Gauge measurements from world-wide about 6700 stations, 
            interpolated by the SPHEREMAP code (Shepard, 1968; Willmott et al. 
            1985);

            - interpolation  for  Antarctica  was  made  separately from the 
              interpolation run for the other continents to avoid any 
              influence of far distant stations.

            Since it is not clear, which estimates are most reliable, the IR 
            and SSM/I results are mixed 50%-weighted, as discussed with P.A. 
            Arkin.

            SSMI estimates on the 5 degree grid  from the separate results of 
            the AM-path and PM-path are used the following way: (AM+PM)*0.9, 
            which should provide the best possible estimates, as discussed 
            with its producer A.T.C. Chang.

            For all oceanic areas where no satellite based estimates are 
            available, the monthly accumulated daily numerical precipitation 
            forecasts are used (ECMWF model, the 12 to 36 hour forecasts or if 
            not available the 0 to 24 hour forecasts).

                Definition of the "tropical" latitude belt 
                -------------------------------------------
                           North    to   South        
                           -------------------       
                     Jan   |  20    |  40    |       
                     Feb   |  25    |  35    |       
                     Mar   |  30    |  30    |       
                     Apr   |  35    |  25    |       
                     May   |  40    |  20    |       
                     Jun   |  40    |  20    |       
                     Jul   |  40    |  20    |       
                     Aug   |  35    |  25    |       
                     Sep   |  30    |  30    |       
                     Oct   |  25    |  35    |       
                     Nov   |  20    |  40    |       
                     Dec   |  20    |  40    |       
                           -------------------       

     9.2.2  Processing Changes.

            Not available at this revision.

9.3  Calculations.

     9.3.1  Special Corrections/Adjustments.

            A correction for systematic gauge-measurement errors (see section 
            10.1) is planned, but not available at this revision. 

9.4  Graphs and Plots.

     The monthly precipitation data sets on a 2.5 degree grid for 1987 have
     been published in GPCC (1992) and for 1988 in GPCC (1993). 

                          10.  ERRORS

10.1  Sources of Error.

      Although analyses of conventional rain-gauge measurements are considered
      to provide the most reliable precipitation information over land areas,
      they can be affected by different sources of uncertainty, which can be
      classified into two major error types: 1) a methodological component
      in obtaining area-average precipitation from point measurements 
      depending on the analysis method used (Bussieres and Hogg, 1989), on the 
      spatial density and on the distribution of the point measurements (WMO, 
      1985; Schneider et al., 1993) and 2) inaccuracies of the point 
      precipitation measurements themselves.

      The second error type consists of two parts, the systematic gauge-
      measuring error and a random error component. The systematic error
      generally results in an under measurement of the true precipitation 
      mainly due to wind effects, especially on snowfall, and wetting as well 
      as evaporative losses (Sevruk, 1982; Legates and Willmott, 1990). For 
      rainfall the systematic error is about 5%, whereas for snowfall it can 
      reach 50% or even more. Random errors can be caused by the gauge (e.g., 
      leakage from or damage to the gauge), by the observer (e.g., 
      inaccuracies in reading the instrument) or can be introduced in the 
      course of data processing and transmission (see Groisman and Legates, 
      1994; Schneider et al., 1994).

      The systematic error in the measurement of precipitation is affected by 
      gauge characteristics, such as dimensions, form and material. 
      Differences in the characteristics of various types of gauges complicate 
      the comparison of both precipitation measurements and correction 
      formulae. There is, as yet, no generally accepted theory for the 
      physical nature of the problems associated with precipitation gauges.  
      Consequently, if a correction formula developed for one type of gauge is 
      to be used for another, special field and/or laboratory investigations 
      are required. In each case, a review is made of the results of 
      comparisons made elsewhere together with an examination of the gauges 
      involved.

10.2  Quality Assessment.

      10.2.1  Data Validation by Source.

              The rain-gauge analyses (on the 2.5 degree grid) have been 
              intercompared to different precipitation climatologies, to 
              satellite-based precipitation estimates derived from IR and 
              microwave images and to results accumulated from daily 
              forecasts of the operational weather prediction model of ECMWF 
              as global, continental and zonal averages, as difference fields 
              and in regression analyses.

      10.2.2  Confidence Level/Accuracy Judgment.

              Not available at this revision for 1 degree data set. For rain-
              gauge analyses on the 2.5 degree grid, the spatial sampling 
              error has been estimated for the dense rain-gauge networks of 
              Australia, Germany and the USA (Schneider et al., 1993a). The 
              spatial sampling error decreases with increasing station 
              density number of stations per grid. An assessment of the other 
              error components is in preparation (Schneider et al., 1994).

      10.2.3  Measurement Error for Parameters and Variables.

              These case studies indicated that at least 2 to 8 stations per
              2.5 degree grid (depending on orographic and climatological
              conditions in the grid) are required to estimate area-average
              precipitation with a relative error of less than 10% (Schneider 
              et al., 1993). An assessment of the other error components is in 
              preparation (Schneider et al., 1994).

      10.2.4  Additional Quality Assessment Applied.

              None.

                             11.  NOTES

11.1  Known Problems With The Data.

      The rain-gauge measurements have not been corrected for the systematic 
      gauge-measuring error (in general an underestimation of the true 
      precipitation by about 10% on global average).

11.2  Usage Guidance.

      In data void/sparse continental areas, the quality of the analysis 
      results will be poor.

11.3  Other Relevant Information.

      Not available.

                           12.  REFERENCES

12.1  Satellite/Instrument/Data Processing Documentation.

      WCRP, 1990. The Global Precipitation Climatology Project - 
         Implementation and Data Management Plan. WMO/TD-No. 367, Geneva, June 
         1990, 47 pp. and appendices.

12.2  Journal Articles and Study Reports.

      Bussieres, N., W.D. Hogg, 1989. The objective analysis of daily rainfall
         by distance weighting schemes on a meso-scale grid. Canadian 
         Meteorol. and Oceanographic Society, Atmosphere-Ocean, 27(3):521-541.
      GPCC, 1992. Monthly precipitation estimates based on gauge measurements
         on the continents for the year 1987 (preliminary results) and future
         requirements. Ed. by WCRP and Deutscher Wetterdienst, Rep.-No. 
         DWD/K7/WZN-1992/08-1, Offenbach, August 1992.
      GPCC, 1993. Global area-mean monthly precipitation totals for the year
         1988 (preliminary estimates, derived from rain-gauge measurements,
         satellite observations and numerical weather prediction results).
         Ed. by WCRP and Deutscher Wetterdienst, Rep.-No. DWD/K7/WZN-1993/07-
         1, Offenbach, July 1993.
      Groisman, P.Y., D.R. Legates 1994. The accuracy of United States
         precipitation data. Bull. Amer. Met. Soc., 75(2): 215-227.
      Legates, D.R., 1987. A climatology of global precipitation. Publ. in
         Climatology, 40 (1), Newark, Delaware, 85 pp.
      Legates, D.R., C.J. Willmott, 1990. Mean seasonal and spatial
         variability in gauge-corrected global precipitation. Internat. J.
         Climatol., 9:111-127.
      Rudolf, B., 1993. Management and analysis of precipitation data on a
         routine basis. Proc. Internat. WMO/IAHS/ETH Symp. on Precipitation 
         and Evaporation. Slovak Hydrometeorol. Inst., Bratislava, Sept. 1993,
         (Eds. M. Lapin, B. Sevruk), 1:69-76.
      Rudolf, B., H. Hauschild, M. Reiss, U. Schneider, 1992. Beitraege zum
         Weltzentrum fuer Niederschlagsklimatologie - Contributions to the
         Global Precipitation Climatology Centre. Meteorol. Zeitschrift N.F.,
         1(1):7-84 (In German, with Abstracts and Summary in English).
      Schneider, U., 1993. The GPCC quality-control system for gauge-measured
         precipitation data. In: Report of a GEWEX workshop "Analysis methods 
         of precipitation on a global scale", Koblenz, Germany, September 
         1992, WCRP-81, WMO/TD-No. 558, June 1993, A5-A7.
      Schneider, U., B. Rudolf, W. Rueth, 1993. The spatial sampling error of
         areal mean monthly precipitation totals analyzed from gauge-
         measurements. Proc. 4th Internat. Conf. on Precipitation 
         "Hydrological and meteorological aspects of rainfall measurement and 
         predictability", Iowa City, Iowa, April 1993, pg. 80-82.
      Schneider, U., W. Rueth, B. Rudolf, 1994. Estimating the error-range
         associated with area-average monthly precipitation analyzed from 
         rain-gauge measurements on a global scale. In preparation.
      Sevruk, B., 1982. Methods of correction for systematic error in point
         precipitation measurement for operational use. Operational Hydrology
         Rep.-No. 21, World Meteorological Organization, Geneva, WMO Rep.-No.
         589, 91 pp.
      Shepard, D., 1968. A two-dimensional interpolation function for
         irregularly spaced data. Proc. 23rd ACM Nat. Conf., Brandon/Systems
         Press, Princeton, NJ, 517-524.
      Willmott, C.J, C.M. Rowe, W.D. Philpot, 1985. Small-scale climate maps:
         A sensitivity analysis of some common assumptions associated with 
         grid-point interpolation and contouring. The Amer. Cartographer, 
         12(1):5-16.
      WMO, 1985. Review of requirements for area-averaged precipitation data,
         surface-based and space-based estimation techniques, space and time
         sampling, accuracy and error; data exchange. WCP-100, WMO/TD-No. 115,
         57 pp. and appendices.

12.3  Archive/DBMS Usage Documentation.

      Contact the EOS Distributed Active Archive Center (DAAC) at NASA Goddard 
      Space Flight Center (GSFC), Greenbelt Maryland (see Section 13 below).
      Documentation about using the archive or information about access to the 
      on-line information system is available through the GSFC DAAC User 
      Services Office.

                             13.  DATA ACCESS

13.1  Contacts for Archive/Data Access Information.

      GSFC DAAC User Services
      NASA/Goddard Space Flight Center
      Code 902.2
      Greenbelt, MD 20771

      Phone:     (301) 286-3209
      Fax:       (301) 286-1775
      Internet:  daacuso@eosdata.gsfc.nasa.gov

13.2  Archive Identification.

      Goddard Distributed Active Archive Center
      NASA Goddard Space Flight Center
      Code 902.2
      Greenbelt, MD 20771

      Telephone:  (301) 286-3209
      FAX:        (301) 286-1775
      Internet:   daacuso@eosdata.gsfc.nasa.gov

13.3  Procedures for Obtaining Data.

      Users may place requests by accessing the on-line system, by sending 
      letters, electronic mail, FAX, telephone, or personal visit.

      Accessing the GSFC DAAC Online System:

      The GSFC DAAC Information Management System (IMS) allows users to 
      ordering data sets stored on-line.  The system is open to the public.

      Access Instructions:

      Node name:  daac.gsfc.nasa.gov
      Node number: 192.107.190.139
      Login example: telnet daac.gsfc.nasa.gov
      Username:  daacims
      password:  gsfcdaac

      You will be asked to register your name and address during your first
      session.

      Ordering CD-ROMs:

      To order CD-ROMs (available through the Goddard DAAC) users should 
      contact the Goddard DAAC User Support Office (see section 13.2).

13.4  GSFC DAAC Status/Plans.

      The ISLSCP Initiative I CD-ROM is available from the Goddard DAAC.

                   14.  OUTPUT PRODUCTS AND AVAILABILITY

14.1  Tape Products.

      The gridded data sets (at a resolution of 2.5 degrees latitude by
      longitude), together with a visualization program, are available from
      GPCC on floppy diskettes (IBM-compatible). From World Data Center A for
      Meteorology the gridded data sets for 1987 and 1988 are available over
      Internet via Email.
 
14.2  Film Products.

      Not available at this revision.

14.3  Other Products.

      The results for 1987 and 1988 have been published in GPCC (1992, 1993).

                       15.  GLOSSARY OF ACRONYMS

CD-ROM      Compact Disk (optical), Read Only Memory
CAC         NOAA Climate Analysis Centre
DAAC        Distributed Active Archive Center
ECMWF       European Centre for Medium-Range Weather Forecasts
EOS         Earth Observing System
IDS         Inter disciplinary Science
ISLSCP      International Satellite Land Surface Climotology Project
GCM         General Circulation Model of the atmosphere
GPCC        Global Precipitation Climatology Centre
GPCP        Global Precipitation Climatology Project
GSFC        NASA Goddard Space Flight Center
GTS         WWW Global Telecommunication System
NASA        National Aeronautics and Space Administration
NOAA        National Oceanic and Atmospheric Administration
WCRP        World Climate Research Program
WMO         World Meteorological Organization
WWW         World Weather Watch of WMO World Climate Data and Monitoring
            Program