Mr. Bruno Rudolf Global Precipitation Climatology Centre Deutscher Wetterdienst
_________________________________________________________
| 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