*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 Paper 1 Page 1 #\document\ncillary\lw\lw1_01.gif Paper 1 Page 2 #\document\ncillary\lw\lw1_02.gif Paper 1 Page 3 #\document\ncillary\lw\lw1_03.gif Paper 1 Page 4 #\document\ncillary\lw\lw1_04.gif Paper 1 Page 5 #\document\ncillary\lw\lw1_05.gif Paper 1 Page 6 #\document\ncillary\lw\lw1_06.gif Paper 1 Page 7 #\document\ncillary\lw\lw1_07.gif Paper 1 Page 8 #\document\ncillary\lw\lw1_08.gif Paper 1 Page 9 #\document\ncillary\lw\lw1_09.gif Paper 1 Page 10 #\document\ncillary\lw\lw1_10.gif Paper 1 Page 11 #\document\ncillary\lw\lw1_11.gif Paper 1 Page 12 #\document\ncillary\lw\lw1_12.gif Paper 1 Page 13 #\document\ncillary\lw\lw1_13.gif Paper 1 Page 14 #\document\ncillary\lw\lw1_14.gif Paper 1 Page 15 #\document\ncillary\lw\lw1_15.gif Paper 1 Page 16 #\document\ncillary\lw\lw1_16.gif Paper 1 Page 17 #\document\ncillary\lw\lw1_17.gif Paper 2 Page 1 #\document\ncillary\lw\lw2_01.gif Paper 2 Page 2 #\document\ncillary\lw\lw2_02.gif Paper 2 Page 3 #\document\ncillary\lw\lw2_03.gif Paper 2 Page 4 #\document\ncillary\lw\lw2_04.gif Paper 2 Page 5 #\document\ncillary\lw\lw2_05.gif Paper 2 Page 6 #\document\ncillary\lw\lw2_06.gif Paper 2 Page 7 #\document\ncillary\lw\lw2_07.gif Paper 2 Page 8 #\document\ncillary\lw\lw2_08.gif Paper 3 Page 1 #\document\ncillary\lw\lw3_01.gif Paper 3 Page 2 #\document\ncillary\lw\lw3_02.gif Paper 3 Page 3 #\document\ncillary\lw\lw3_03.gif Paper 3 Page 4 #\document\ncillary\lw\lw3_04.gif Paper 3 Page 5 #\document\ncillary\lw\lw3_05.gif Paper 3 Page 6 #\document\ncillary\lw\lw3_06.gif Paper 3 Page 7 #\document\ncillary\lw\lw3_07.gif Paper 3 Page 8 #\document\ncillary\lw\lw3_08.gif Paper 3 Page 9 #\document\ncillary\lw\lw3_09.gif Paper 3 Page 10 #\document\ncillary\lw\lw3_10.gif Paper 3 Page 11 #\document\ncillary\lw\lw3_11.gif *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 Annual #\data\ncillary\lwcsd00.img January #\data\ncillary\lwcsd01.img February #\data\ncillary\lwcsd02.img March #\data\ncillary\lwcsd03.img April #\data\ncillary\lwcsd04.img May #\data\ncillary\lwcsd05.img June #\data\ncillary\lwcsd06.img July #\data\ncillary\lwcsd07.img August #\data\ncillary\lwcsd08.img September #\data\ncillary\lwcsd09.img 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 April #\data\ncillary\lwerr04.img May #\data\ncillary\lwerr05.img June #\data\ncillary\lwerr06.img July #\data\ncillary\lwerr07.img August #\data\ncillary\lwerr08.img September #\data\ncillary\lwerr09.img 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