National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service(NESDIS)
This directory contains the documentation on Legates and Willmott's Monthly Average Surface Air Temperature and Precipitation (re-gridded), published in the Global Ecosystems Database:
*LEGATES AND WILLMOTT CLIMATE_help
Global Ecosystems Database Disc A: Chapter 4
Legates and Willmott Average Monthly Surface Air Temperature and
Precipitation (re-gridded)
Gauge Corrected Precipitation (re-gridded)
Standard Error for Gauge Corrected Precipitation (re-gridded)
Measured Precipitation (re-gridded)
Surface Air Temperature (re-gridded)
DATA-SET DESCRIPTION
Data-Set Name: Legates and Willmott Average Monthly Surface Air
Temperature and Precipitation (re-gridded)
Principal Investigator: David R. Legates and Cort J. Willmott
Scientific Reference: (* reprint on CD-ROM)
+ Legates, David R. 1989. "A high-resolution climatology of
gage-corrected global precipitation." In:
Precipitation Measurement, B. Sevruk (ed.), Proceedings
of the WMO/IAHS/ETH International Workshop on
Precipitation Measurement, St. Moritz, Switzerland,
Dec. 3-7, 1989. Zurich: Swiss Federal Institute of
Technology, pp. 519-526.
+ Legates, David R. and Cort J. Willmott. 1990. "Mean
seasonal and spatial variability in gauge-corrected
global precipitation." International Journal of
Climatology, vol. 10. pp. 111-127.
+ Legates, David R. and Cort J. Willmott. 1990. "Mean
seasonal and spatial variability in global surface air
temperature." Theoretical and Applied Climatology,
vol. 41, pp. 11-21.
SOURCE
Source Data Citation:
Legates, D.R. and C.J. Willmott, 1989. Average Monthly
Surface Air Temperature and Precipitation. Digital
Raster Data on a .5-degree Geographic (lat/long)
361x721 grid (centroid-registered on .5 degree
meridians). Boulder CO: National Center for Atmospheric
Research. 4 files on 9-track tape. 83MB.
Contributor:
Dr. David R. Legates and Dr. Cort J. Willmott
Department of Geography Center for Climatic Research
College of Geosciences Department of Geography
University of Oklahoma University of Delaware
Norman, OK 73019 USA Newark, DE 19716 USA
(405) 325-6547 (302) 451-8998
Distributor:
NCAR
Vintage:
circa 1980's
Lineage:
(1) Principal Investigators: David R. Legates and Cort J.
Willmott
(2) Archived and Distributed by:
Roy Jenne
National Center for Atmospheric Research
Boulder, CO
ORIGINAL DESIGN
Variables:
VARIABLE UNITS
PRECISION
(1) Measured precipitation mm/month 1mm
(2) Gauge corrected precipitation mm/month 1mm
(3) Standard error of
corrected precipitation mm/month 1mm
(4) Surface Air temperature degrees Celsius 0.1 C
Origin:
24,941 independent surface air temperature and 26,858
independent precipitation stations, and oceanic grid point
estimates from a variety of sources (see Primary
Documentation).
Geographic Reference:
latitude/longitude
Centroid-registered grid cells on 30-minute lat/long
meridians. Original grid (361x721) extends from pole to
pole and originates at the International Date Line.
Geographic Coverage:
Global
Maximum Latitude: +90 degrees (N)
Minimum Latitude: -90 degrees (S)
Maximum Longitude: +180 degrees (E)
Minimum Longitude: -180 degrees (W)
Geographic Sampling:
Weighted (using a spherically-based interpolation algorithm)
30-minute cell averages of station data and oceanic
trackline samples, on a centroid-registered 30-minute grid.
Time Period:
Modern "average" climate, from records mostly between 1920 and
1980.
Temporal Sampling:
12 characteristic months and characteristic years for each variable,
representing long-term (approx. 60 year) monthly and annual means.
INTEGRATED DATA-SET
Data-Set Citation:
Legates, D.R. and C.J. Willmott. 1992. Monthly Average
Surface Air Temperature and Precipitation. Digital
Raster Data on a 30 minute Geographic (lat/long)
360x720 grid. In: Global Ecosystems Database Version
1.0: Disc A. Boulder, CO: NOAA National Geophysical
Data Center. 48 independent and 4 derived single-attribute
spatial layers on CD-ROM, 47.2MB.[first published in 1989]
Analyst:
John Kineman and Mark Ohrenschall
Projection:
Geographic (lat/long), GED window (see User's Guide).
Spatial Representation:
30-minute cell values interpolated from the 4 overlapping
quadrant values of the original grid, which contained values
interpolated from irregularly spaced point observations.
Temporal Representation:
12 characteristic months and characteristic years for each
variable, representing long-term (approx. 60 year) means.
Data Representation:
2-byte integers, representing:
VARIABLE UNITS PRECISION
1) Measured precipitation mm/month 1mm
2) Gauge corrected precipitation mm/month 1mm
3) Surface Air temperature C x 10 .1 C
4) Standard deviation
(expressed in the same units and precision as above) of
the interpolated cell values for each measurement
(precipitation, corrected precipitation, and
temperature) are provided as separate layers as an
estimate of uncertainty introduced by the re-gridding
process -- these three standard deviation ("SD") files
were not part of the original data-set.
5) RMS Std. error of
corrected precip. mm/month 1mm
Note that this variable was re-gridded by a different method
than the first three: The re-gridding method employed a
root-mean-square average to combine the 4 quadrant
values into the newly registered grid cell for the GED.
Layers and Attributes:
52 independent and 39 derived single-attribute spatial layers
Compressed Data Volume:
15,707,536 bytes
ADDITIONAL REFERENCES
Legates, David R. 1987. A Climatology of Global
Precipitation. Pub. Climatol., 40(1): 103 p.
Sevruk, B. 1989. "Reliability of precipitation
measurement." In: Precipitation Measurement, B. Sevruk
(ed.), Proceedings of the WMO/IAHS/ETH International
Workshop on Precipitation Measurement, St. Moritz,
Switzerland, Dec. 3-7, 1989. Zurich: Swiss Federal
Institute of Technology, pp. 519-526
Shepard, D. 1968. "A two-dimensional interpolation function
for irregularly-spaded data." In: Proceedings of 23rd
National Conference of the Association for Computing
Machinery. ACM Pub. P-68. Princeton, NJ:
Brandon/Systems Press, Inc.
Willmott, C.J., C.M. Rowe, and W.D. Philpot. 1985. "Small-
scale climate maps: a sensitivity analysis of some
common assumptions associated with grid-point
interpolation and contouring. The American
Cartographer, 12(1): 5-16.
TECHNICAL REPORT
John Kineman and Mark Ohrenschall
National Geophysical Data Center
Boulder, Colorado
OVERVIEW
The Legates and Willmott data are referenced to a
latitude/longitude grid with the data values located at
intersections of the .5-degree latitude and longitude meridians,
globally. This can be seen as a grid of half-degree cells with
the cell centers located at the .5 degree meridian intersections.
Note also that the "cell" boundaries of this type of grid extend
beyond the "edges" of the global lat/long grid extending between
+/- 180 degrees longitude and +/- 90 degrees latitude. This
differs from the convention adopted for the GED, of edge
alignment with a nested set of GED "conventional" latitude and
longitude meridians, one of which is .5-degrees (i.e., the GED
"nested" grids - see User's Guide). In the GED convention, the
cell boundaries are aligned with the edges of the global window
and with each "nested" meridian. The difference between these
two grid conventions is cell registration, but it poses a problem
for integration or intercomparison with other data in the
database since differently registered grid cells do not occupy
the same location, and thus must be either interpolated or
accepted with a spatial offset of 1/2 the diagonal of a cell
(e.g., systems that would automatically grid-sample to obtain the
edge-registered grid values from a centroid-registered grid).
In a raster GIS, each number in a digital image file is
referenced to a "cell," which covers some area on the surface of
the earth. Given data values spaced a half-degree apart on a
latitude/longitude grid, each value is considered to refer to a
half-degree "cell" on the surface of the earth (although with
true "point" data sets the value more properly refers to the
centroid of the cell). In practice, the spatial meaning of cell
values may vary considerably between data-sets, depending on
design criteria of the original investigators. The Legates and
Willmott data are carefully interpolated from irregularly spaced
point observations to values that have a spatial resolution
approximately equal to the cell size (i.e., .5-degree). It is
therefore not correct to assume a spatial uncertainty of .5-
degrees, as commonly used "nearest-neighbor" resampling would.
Unfortunately, owing to the complex nature of rainfall data and
the spatial interpolation techniques that were applied (see
references), any method of re-gridding introduces problems.
In resampling from the Legates and Willmott grid to the Global
Ecosystems Database grid two methods were tested: (2) combining
resampling and interpolation to represent the data on a GED-
compatible 10-minute grid, and (2) regridding (interpolation) to
the GED conventional half-degree grid using a simple 2x2 quadrant
average for each cell in the new grid. The first of these
products was distributed on the 1991 Prototype CD-ROM of the GED
Database (Version 0.1 - Beta Test). Partly based on the 1991
review, the decision was made to include the second product on
the current release of the GED database (Version 1.0). Both of
these solutions are considered inferior to re-producing the data
from source material, however this will require more time and
resources.
METHOD USED IN THE PROTOTYPE
The method used for the prototype was to expand (by pixel
replication) the Legates and Willmott grid by a factor of six in
both row and column dimensions, window on the inner 2160 rows and
4320 columns (excluding the outer-most three rows and columns),
and then contract (with cell averaging) by a factor of two. The
result was a 10-minute grid that can nest with other gridded
images in the Global Ecosystems Database. While the new 10-
minute grid was to some degree interpolated from the original
grid, the advantage of this method was that the original grid
values are preserved amongst interpolated values, and the
original data-set can be recovered from the new grid by sampling.
Its disadvantage was that it was unclear how to use this mixed
grid in normal processing, and the artificially fine grids (10-
minutes) require a lot of storage space and may mislead users
into assuming greater regional resolution than actually exists.
In other words, the expanded grid would have to be aggregated to
a coarser grid to have proper meaning anyway.
METHOD USED IN THE CURRENT VERSION
The method used for the current release was a simple grid
interpolation, averaging 4 cell values to obtain a 1/2 cell
offset data-set on a .5-degree grid that is compatible with the
GED convention. This, unfortunately, also smooths the original
data, thus reducing its variability and changing its spatial
meaning. Statistically, the new grid represents averages of four
1/2-degree "quadrant" cells covering a 1x1 degree region, taken
at 1/2-degree grid increments. The data should be interpreted
with this in mind, as it is a questionable procedure for many
uses to interpolate variables such as precipitation in this way
(although the original values are themselves interpolated and
spatially general). It may be more appropriate to use this
interpolated GED grid for coarser studies, at 1-degree or greater
resolution.
To assess the uncertainty in the re-gridding process, companion
data files are provided for each variable giving the standard
deviation (sample s.d., i.e., 1/n-1) for each cell's 4 source
values. This may serve as a reliability indicator for the
interpolated values.
According to the NCAR documentation, the gauge-error data (for
the gauge-corrected precipitation estimates) is expressed as a
standard error, however the literature references discuss gauge-
errors in percent. It was decided to interpolate the gauge-error
file as standard error estimates, using a simple root-mean-square
algorithm.
Further investigation of these methods is warranted.
Original source files are contained on the definitive Global
Ecosystems Database, available from NOAA/NGDC.
SOURCE FILE FORMATTING
The Legates and Willmott data came as four files on tape, one
file for each parameter, with an 80-character fixed-record format
containing latitude, longitude, and 13 data fields for the twelve
monthly averages and the annual average. Since each record did
have geo-referencing, a cell sequencing was unnecessary,
nonetheless the data files had cell sequencing north to south
within longitude columns, with column sequencing from west to
east, beginning at 90 degrees north and 180 degrees west. Each
data value was referenced by half-degree multiples, including 90
degrees north, 90 degrees south, 180 degrees west, and 180
degrees east.
DATA PROCESSING
In processing the data, the first task was running a custom-
written program to resequence the cells and extract the data
fields to produce an Idrisi image for each parameter for each
monthly and annual image. Next, a program was written to average
a moving window of 4 original cell values, writing the averages
and standard deviations of the 2x2 average to the new grid.
In the following figure, the double-line represents the original
grid before regridding. The single-line represents the half-
degree meridians and parallels, as well as the new, interpolated
grid. The new values are located at the intersection of 4
original 0.5 degree cells. An "X" indicates the location of data
points in the original Legates and Willmott grid.
L & W grid cell centered on half-degree meridians and parallels
: X
180 W 179.5 W
90 N XDWDXDWDXDWDX XDDDX half-degree edge-aligned cells
LMXMNMXMNMXMNM3 3 3 compatible with the GED
nested grid
89.5 N : XDWDXDWDXDWDX XDDDX structure
CONCLUSION
The representation of the Legates and Willmott data is a
compromise to achieve integration with multi-thematic data. As
with any data-set, the user must assess its value for the purpose
at hand. These "re-gridded" data will loose regional variability
information due to the smoothing effect of the interpolation.
The amount of loss may be estimated by the standard deviation
values provided with the re-gridded data, and by experimenting
with the sample source file provided with the database.
Nevertheless, an obvious future improvement would be to re-
calculate the data-set on the desired grid from station
observations, using the original (or improved) interpolation
methods.
*LEGATES AND WILLMOTT CLIMATE
ANCILLARY ENVIRONMENTAL DATA
Corrected Precip #*CORRECTED PRECIP
Standard Error for Corrected Precip #*STANDARD ERROR FOR CORRECTED PRECIP
Measured Precip #*MEASURED PRECIP
Temperature #*TEMPERATURE
Scanned Documentation #*LW SCANNED DOCUMENTATION
*LW SCANNED DOCUMENTATION_help
The scanned documentation noted here is contained in the \document
directory on the CD-ROM as .gif files. These files can be read by
any computer program that reads PC Paintbrush format files.
The GeoVu software provided on this CD-ROM contains such a utility.
To use the GeoVu utility, merely select the appropriate file from
this menu, using the "Open Data" option that you have been using to
this point.
If you are VERY NEW to GeoVu, you can open a file by
1. Selecting "File" from the options at the top of your screen.
2. After selecting "File" select "Open Data" from the options that
appear in the pull-down menu.
3. Follow the hierarchy of menu paths to the data of your choice.
4. When the hierarchy leads you to a topic "Scanned Documentation"
merely select that topic. The next topic should read "Page 1, Page
2,... etc." or "Paper 1 Page 1, Paper 1 Page 2, .... Paper 2 Page
1.... etc. You can select the pages manually, or create a "slide
show" under the Utilities option at the top of the screen. The
first time the .gif file displays it might be reduced in size. This
is a "feature" of current versions of GeoVu that might be improved
in the future. If you redisplay the image (by selecting "Search"
from the options at the top of the screen, then "Create" from the
menu thus pulled down, you can modify the parameter that sets the
sampling rate from "n" [usually 2, 3, 4, or 5] to 1). This will
give you full resolution display of the scanned documentation.
It should be noted that this scanned documentation is a compromise.
We originally attempted to use optical character recognition
software to convert the scanned documentation to more usable text.
However, the technology was too immature at the time of scanning
(1992) to use successfully. Indeed, as of this writing (late 1995)
the technology is still too immature for convenient application to
this problem.
Thus, we present the scanned documentation as images.
NOTE: Many of the original documents are not copyright, and may be
reproduced freely. However, several other documents ARE copyright.
The National Geophysical Data Center has obtained permission to
reproduce all documents with a valid copyright. However, this
permission does not pass automatically to anyone else. Thus, though
all of the data on this CD-ROM are unrestricted, much of the
scanned documentation (which contains copyright notices) may not be
distributed further, without permission of the copyright holder, or
without a dontribution made to the Copyright Clearance Center under
the rules noted in the individual papers. (Also note that a few
documents authored by U. S. Government employees or contractors as
part of their work for the Government, had copyrights claimed by
the journals that published the papers. Such documents are not
subject to copyright, and the copyright claims of said journals
have been determined to be meritless.)
*LW SCANNED DOCUMENTATION
LEGATES AND WILLMOTT CLIMATE
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*CORRECTED PRECIP_help
DATA ELEMENT: Gauge Corrected Precipitation (re-gridded)
STRUCTURE:
Raster Data Files: .5-degree 360x720 GED grid
(see User's Guide)
SERIES:
series of 12 characteristic months and characteristic year
SPATIAL META-DATA:
LWCPR00.DOC
file title : Legates & Willmott Annual Corrected Precip (mm/year)
data type : integer
file type : binary
columns : 720
rows : 360
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : 0.5000000
min. value : 0
max. value : 6626
value units : millimeters/year
value error : unknown
flag value : none
flag def'n : none
legend cats : 0
File Series Parameters:
File Month Minimum Maximum
LWCPR00 year cum. 0 6626
LWCPR01 January 0 1102
LWCPR02 February 0 625
LWCPR03 March 0 663
LWCPR04 April 0 573
LWCPR05 May 0 664
LWCPR06 June 0 1157
LWCPR07 July 0 1420
LWCPR08 August 0 1372
LWCPR09 September 0 857
LWCPR10 October 0 762
LWCPR11 November 0 897
LWCPR12 December 0 899
Standard Deviation:
LWCSD00 year cum. 0 2410
LWCSD01 January 0 255
LWCSD02 February 0 176
LWCSD03 March 0 261
LWCSD04 April 0 215
LWCSD05 May 0 264
LWCSD06 June 0 335
LWCSD07 July 0 506
LWCSD08 August 0 364
LWCSD09 September 0 261
LWCSD10 October 0 328
LWCSD11 November 0 258
LWCSD12 December 0 239
ATTRIBUTE META-DATA:
NONE
NOTES:
(1) Mean and standard deviation derived from 2x2 quadrant
average of the source grid, resulting in an
interpolated .5-degree (GED) grid with 1-deg. smoothing.
*CORRECTED PRECIP
LEGATES AND WILLMOTT CLIMATE
Annual #\data\ncillary\lwcpr00.img
January #\data\ncillary\lwcpr01.img
February #\data\ncillary\lwcpr02.img
March #\data\ncillary\lwcpr03.img
April #\data\ncillary\lwcpr04.img
May #\data\ncillary\lwcpr05.img
June #\data\ncillary\lwcpr06.img
July #\data\ncillary\lwcpr07.img
August #\data\ncillary\lwcpr08.img
September #\data\ncillary\lwcpr09.img
October #\data\ncillary\lwcpr10.img
November #\data\ncillary\lwcpr11.img
December #\data\ncillary\lwcpr12.img
Standard deviations re-gridding Corrected Precip #*STANDARD
DEVIATIONS RE-GRIDDING CORRECTED PRECIP
*STANDARD DEVIATIONS RE-GRIDDING CORRECTED PRECIP_help
Standard deviations from re-gridding Guage Corrected Precipitation
*STANDARD DEVIATIONS RE-GRIDDING CORRECTED PRECIP
CORRECTED PRECIP
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January #\data\ncillary\lwcsd01.img
February #\data\ncillary\lwcsd02.img
March #\data\ncillary\lwcsd03.img
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October #\data\ncillary\lwcsd10.img
November #\data\ncillary\lwcsd11.img
December #\data\ncillary\lwcsd12.img
*STANDARD ERROR FOR CORRECTED PRECIP_help
DATA ELEMENT: Standard Error for Gauge Corrected
Precipitation (re-gridded)
STRUCTURE:
Raster Data Files:.5-degree 360x720 GED grid (see User's Guide)
SERIES:
series of 12 characteristic months and characteristic year
SPATIAL META-DATA:
LWERR00.DOC
file title : Legates & Willmott Annual Standard Error (mm/year)
data type : integer
file type : binary
columns : 720
rows : 360
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : 0.5000000
min. value : 0
max. value : 344
value units : millimeters/year
value error : unknown
flag value : none
flag def'n : none
legend cats : 0
File Series Parameters:
File Month Minimum Maximum
LWERR00 year cum. 0 344
LWERR01 January 0 401
LWERR02 February 0 571
LWERR03 March 0 558
LWERR04 April 0 550
LWERR05 May 0 319
LWERR06 June 0 275
LWERR07 July 0 354
LWERR08 August 0 492
LWERR09 September 0 400
LWERR10 October 0 599
LWERR11 November 0 969
LWERR12 December 0 720
ATTRIBUTE META-DATA:
NONE
NOTES:
(1) Mean and standard deviation derived from 2x2 quadrant
average of the source grid, resulting in an
interpolated .5-degree (GED) grid with 1-deg.
smoothing.
(2) The corrected precipitation error data were
interpolated by a 2x2 r.m.s. filter.
*STANDARD ERROR FOR CORRECTED PRECIP
LEGATES AND WILLMOTT CLIMATE
Annual #\data\ncillary\lwerr00.img
January #\data\ncillary\lwerr01.img
February #\data\ncillary\lwerr02.img
March #\data\ncillary\lwerr03.img
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October #\data\ncillary\lwerr10.img
November #\data\ncillary\lwerr11.img
December #\data\ncillary\lwerr12.img
*MEASURED PRECIP_help
DATA ELEMENT: Measured Precipitation (re-gridded)
STRUCTURE:
Raster Data Files:0.5-degree 360x720 GED grid(see User's Guide)
SERIES:
series of 12 characteristic months and characteristic year
SPATIAL META-DATA:
LWMPR00.DOC
file title : Legates & Willmott Annual Measured Precipitation
(mm/year)
data type : integer
file type : binary
columns : 720
rows : 360
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : 0.5000000
min. value : 0
max. value : 6434
value units : millimeters/year
value error : unknown
flag value : none
flag def'n : none
legend cats : 0
File Series Parameters:
File Month Minimum Maximum
LWMPR00 year cum. 0 6434
LWMPR01 January 0 1048
LWMPR02 February 0 612
LWMPR03 March 0 616
LWMPR04 April 0 545
LWMPR05 May 0 646
LWMPR06 June 0 1129
LWMPR07 July 0 1378
LWMPR08 August 0 1327
LWMPR09 September 0 833
LWMPR10 October 0 739
LWMPR11 November 0 848
LWMPR12 December 0 876
Standard Deviation:
LWMSD00 year cum. 0 2362
LWMSD01 January 0 251
LWMSD02 February 0 172
LWMSD03 March 0 253
LWMSD04 April 0 210
LWMSD05 May 0 259
LWMSD06 June 0 330
LWMSD07 July 0 496
LWMSD08 August 0 357
LWMSD09 September 0 253
LWMSD10 October 0 321
LWMSD11 November 0 252
LWMSD12 December 0 233
ATTRIBUTE META-DATA:
NONE
NOTES:
(1) Mean and standard deviation derived from 2x2 quadrant
average of the source grid, resulting in an
interpolated .5-degree (GED) grid with 1-deg.
smoothing.
*MEASURED PRECIP
LEGATES AND WILLMOTT CLIMATE
Annual #\data\ncillary\lwmpr00.img
January #\data\ncillary\lwmpr01.img
February #\data\ncillary\lwmpr02.img
March #\data\ncillary\lwmpr03.img
April #\data\ncillary\lwmpr04.img
May #\data\ncillary\lwmpr05.img
June #\data\ncillary\lwmpr06.img
July #\data\ncillary\lwmpr07.img
August #\data\ncillary\lwmpr08.img
September #\data\ncillary\lwmpr09.img
October #\data\ncillary\lwmpr10.img
November #\data\ncillary\lwmpr11.img
December #\data\ncillary\lwmpr12.img
Standard deviations re-gridding Measured Precip
#*STANDARD DEVIATIONS RE-GRIDDING MEASURED PRECIP
*STANDARD DEVIATIONS RE-GRIDDING MEASURED PRECIP_help
Standard deviations from re-gridding Measured Precipitation
*STANDARD DEVIATIONS RE-GRIDDING MEASURED PRECIP
MEASURED PRECIP
Annual #\data\ncillary\lwmsd00.img
January #\data\ncillary\lwmsd01.img
February #\data\ncillary\lwmsd02.img
March #\data\ncillary\lwmsd03.img
April #\data\ncillary\lwmsd04.img
May #\data\ncillary\lwmsd05.img
June #\data\ncillary\lwmsd06.img
July #\data\ncillary\lwmsd07.img
August #\data\ncillary\lwmsd08.img
September #\data\ncillary\lwmsd09.img
October #\data\ncillary\lwmsd10.img
November #\data\ncillary\lwmsd11.img
December #\data\ncillary\lwmsd12.img
*TEMPERATURE_help
DATA ELEMENT: Surface Air Temperature (re-gridded)
STRUCTURE:
Raster Data Files:.5-degree 360x720 GED grid(see User's Guide)
SERIES:
series of 12 characteristic months and characteristic year
SPATIAL META-DATA:
LWTMP00.DOC
file title : Legates & Willmott Annual Temperature (0.1C)
data type : integer
file type : binary
columns : 720
rows : 360
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : 0.5000000
min. value : -569
max. value : 299
value units : 0.1 degrees celsius
value error : unknown
flag value : none
flag def'n : none
legend cats : 0
File Series Parameters:
File Month Minimum Maximum
LWTMP00 year cum. -569 299
LWTMP01 January -540 328
LWTMP02 February -503 323
LWTMP03 March -584 330
LWTMP04 April -666 339
LWTMP05 May -674 358
LWTMP06 June -702 399
LWTMP07 July -690 418
LWTMP08 August -718 395
LWTMP09 September -669 363
LWTMP10 October -596 319
LWTMP11 November -441 324
LWTMP12 December -468 336
Standard Deviation:
LWTSD00 year cum. 0 152
LWTSD01 January 0 146
LWTSD02 February 0 156
LWTSD03 March 0 182
LWTSD04 April 0 173
LWTSD05 May 0 161
LWTSD06 June 0 169
LWTSD07 July 0 155
LWTSD08 August 0 149
LWTSD09 September 0 156
LWTSD10 October 0 150
LWTSD11 November 0 147
LWTSD12 December 0 158
ATTRIBUTE META-DATA:
NONE
NOTES:
(1) Mean and standard deviation derived from 2x2 quadrant
average of the source grid, resulting in an
interpolated .5-degree (GED) grid with 1-deg. smoothing.
*TEMPERATURE
LEGATES AND WILLMOTT CLIMATE
Annual #\data\ncillary\lwtmp00.img
January #\data\ncillary\lwtmp01.img
February #\data\ncillary\lwtmp02.img
March #\data\ncillary\lwtmp03.img
April #\data\ncillary\lwtmp04.img
May #\data\ncillary\lwtmp05.img
June #\data\ncillary\lwtmp06.img
July #\data\ncillary\lwtmp07.img
August #\data\ncillary\lwtmp08.img
September #\data\ncillary\lwtmp09.img
October #\data\ncillary\lwtmp10.img
November #\data\ncillary\lwtmp11.img
December #\data\ncillary\lwtmp12.img
Standard deviations re-gridding Air Temp
#*STANDARD DEVIATIONS RE-GRIDDING AIR TEMP
*STANDARD DEVIATIONS RE-GRIDDING AIR TEMP_help
Standard deviations from re-gridding Surface Air Temperature
*STANDARD DEVIATIONS RE-GRIDDING AIR TEMP
TEMPERATURE
Annual #\data\ncillary\lwtsd00.img
January #\data\ncillary\lwtsd01.img
February #\data\ncillary\lwtsd02.img
March #\data\ncillary\lwtsd03.img
April #\data\ncillary\lwtsd04.img
May #\data\ncillary\lwtsd05.img
June #\data\ncillary\lwtsd06.img
July #\data\ncillary\lwtsd07.img
August #\data\ncillary\lwtsd08.img
September #\data\ncillary\lwtsd09.img
October #\data\ncillary\lwtsd10.img
November #\data\ncillary\lwtsd11.img
December #\data\ncillary\lwtsd12.img
*SOURCE EXAMPLES_help
DATA ELEMENT: SOURCE EXAMPLE: Average Monthly Air
Temperature and Precipitation (Source
Examples)
STRUCTURE:
Raster Data File: .5-degree, 361x721 centroid-registered
grid (non-GED registration convention -- see User's Guide)
SERIES:
Sample file for July
SPATIAL META-DATA:
LWSCP07.DOC
file title : Legates & Willmott Source Corrected Precipitation
July (mm/month)
data type : integer
file type : binary
columns : 721
rows : 361
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : 0.5000000
min. value : 0
max. value : 1540
value units : millimeters/month
value error : unknown
flag value : none
flag def'n : none
legend cats : 0
File Series Parameters:
File Variable Units Minimum Maximum
LWSCP07 Corr. Precip. mm/month 0 1540
LWSER07 Gauge error mm/month 0 376
LWSMP07 Meas. Precip. mm/month 0 1492
LWSTM07 Temperature C x 10 -693 442
ATTRIBUTE META-DATA:
NONE