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《用wgrib2 读取grib2文件说明》
wgrib2怎么安装 第一篇
Introduction to GRIB2 using the GFS forecasts
2/2013 Wesley Ebisuzaki
GRIB2 (grib edition 2) is a standard format sponsored by the WMO (UN's World Meteorological Organization) for the transmission of gridded data between the
national meteorological centers. In English, grib2 is a format for meteorological and oceanographic forecasts and analyses that is is used by the big guys that make the operational weather forecasts. If you want the model weather forecasts from a government meterological agency, the changes are that it will be available in grib format.
GRIB2 is a transmission format so compression is a high priority. Starting with a GFS forecast file, converting it to netcdf-3 increases the file size by 6.4 times.
-rwxr-xr-x 1 wd51we wd5 58043511 2013-02-08 09:55 gfs.t06z.pgrb2f12 (grib2) -rw-r--r-- 1 wd51we wd5 372295888 2013-02-08 10:06 gfs.t06z.pgrb2f12.nc (netcdf3)
Grib2 is a transmission format but can be used by application programs and common database functions can be accomplished by utilities/programs.
GRIB2 is defined endian independent and and computer word size independent.
However, 32-bit computer tend to limited to 2 GB files and grib2 software have been written assuming a word size of at least 32 bits.
What is in a GRIB2 file?
An easy way to see the contents of a grib2 files is to run wgrib2 on it. Wgrib2 is freely available for Windows, linux and Unix machines. Using a GFS forecast file,
bash-3.2$ wgrib2 gfs.t06z.pgrb2f12 1.1:0:d=2013020806:UGRD:planetary boundary layer:12 hour fcst: 1.2:0:d=2013020806:VGRD:planetary boundary layer:12 hour fcst: 2:232030:d=2013020806:VRATE:planetary boundary layer:12 hour fcst: 3:337239:d=2013020806:HGT:10 mb:12 hour fcst: 4:571416:d=2013020806:TMP:10 mb:12 hour fcst: 5:632506:d=2013020806:RH:10 mb:12 hour fcst: 6.1:647281:d=2013020806:UGRD:10 mb:12 hour fcst: 6.2:647281:d=2013020806:VGRD:10 mb:12 hour fcst: ... 312:56419187:d=2013020806:HGT:PV=-2e-06 (Km^2/kg/s) surface:12 hour fcst: 313:56671672:d=2013020806:PRES:PV=-2e-06 (Km^2/kg/s) surface:12 hour fcst:
314:56953195:d=2013020806:VWSH:PV=-2e-06 (Km^2/kg/s) surface:12 hour fcst: 315:57092940:d=2013020806:PRMSL:mean sea level:12 hour fcst: 316:57267394:d=2013020806:5WAVH:500 mb:12 hour fcst: 317:57345993:d=2013020806:GPA:1000 mb:12 hour fcst: 318:57710431:d=2013020806:GPA:500 mb:12 hour fcst: 319:57938644:d=2013020806:5WAVA:500 mb:12 hour fcst:
The format of the default inventory is
(message num)[.sub-message num]:(location):d=(reference time):(variable):(Z):(dtime)[:other information]
[...] are optional values
(...) are values as described by ...
underlined characters are literals
message num: message number =1..N messages contain a complete description of one or more fields submesage num: if the message contains more than 1 field, then submess num = 1..number of fields in the message
location: the byte location (starting from zero) of the start of the message.
reference time: usually the analysis time or the start of the forecast time, the format is YYYYMMDDHH
to see the minutes and seconds, use the -S option in wgrib2.
Variable: a short name of the variable. The variables names are not part of the WMO standard. Wgrib2 uses the
NCEP names
Z: the vertical coordinate. It can be a level or a layer. Examples include 300 mb, 2 m above ground, atmospheric
column, tropopause, 20 C oceanic isotherm and 10 m below the sea.
Dtime: a modifier of the reference time. Examples 12 hour forecast, 1 month average
other information: optional fields such as ensemble information, chemical species, probabilities. The “other information” is subject to more changes as grib2 format is augmented.
Interpretation
Here are lines 4 and 5 of the above inventory:
3:337239:d=2013020806:HGT:10 mb:12 hour fcst: 4:571416:d=2013020806:TMP:10 mb:12 hour fcst:
The first line says the message
“3” grib message number 3
“337239” message starts at byte location 337239 and ends at 571415
571415 is one less than the start of the next message
“d=2013020806” forecast started at 06Z Feb 8, 2013020805
“HGT” the field is the geopotential height in geopotential meters (see NCEP tables)
“10 mb” the field for 10 mb or 100 hPa.
“12 hour fcst” the field is a 12 hour forecast from the intial time 2013020806
Messages and Sub-messages
Grib files consist of a sequence of grib messages. Each message is a complete description of one or more fields. This simple structure means that you can make grib files by joining two grib files.
Combining two grib files.
Linux: cat grib2 grib2 > grib3
A grib message is a complete description of a field. In the following inventory, the 10 mb HGT occupies byte locations
337239 to 571415 (234177 bytes).
3:337239:d=2013020806:HGT:10 mb:12 hour fcst: 4:571416:d=2013020806:TMP:10 mb:12 hour fcst:
You can extract byte locations 337239 to 571415 by using the dd command
bash-3.2$ dd if=gfs.t06z.pgrb2f12 ibs=1 skip=337239 count=234177 of=hgt.grb ... bash-3.2$ wgrib2 hgt.grb 1:0:d=2013020806:HGT:10 mb:12 hour fcst:
Grib files can have submessages such as
6.1:647281:d=2013020806:UGRD:10 mb:12 hour fcst: 6.2:647281:d=2013020806:VGRD:10 mb:12 hour fcst:
Grib message 6 has two sub-messages. The first sub-message is the UGRD (zonal wind) and the second sub-message is VGRD (meridional wind). Sub-messages save space because they share a common grid definition. Submessages are often used to keep common variables together. For example, NCEP Operations usually keep the zonal and meridional winds in the same message as shown above. Note that in the above inventory, both fields start at the same byte location (647281).
Usually the grid defintion is on the order of 30 bytes, so using submessage only provides marginal savings. The only exception is for irregular grids where the latitude and longitude of each grid point is stored in the grid definition. In this case, the grid definition uses more space than the grid values. By using submessages, only one copy of the latitude longitude values need be saved.
Byte Location
Grib messages are like atoms. Each atom is compete and takes up a finite volume. If you had small fingers, you could grab that sodium atom and place it over there. A grib message has a starting byte location and an ending byte location.
Variables
Wgrib2 uses the NCEP variable names as given by
You can see the defintions by using the -v option.
bash-3.2$ wgrib2 -v gfs.t06z.pgrb2f12 | more 1.1:0:d=2013020806:UGRD U-Component of Wind [m/s]:planetary boundary layer:12 hour fcst: 1.2:0:d=2013020806:VGRD V-Component of Wind [m/s]:planetary boundary layer:12 hour fcst: 2:232030:d=2013020806:VRATE Ventilation Rate [m^2/s]:planetary boundary layer:12 hour fcst: 3:337239:d=2013020806:HGT Geopotential Height [gpm]:10 mb:12 hour fcst: 4:571416:d=2013020806:TMP Temperature [K]:10 mb:12 hour fcst:
Z
Grib messages store 2 dimensional grids. Usually the grids are horizontal (x-y, lat-lon). For a 3 dimensional fields, you have a set of grib2 message with varying vertical levels/layers. Levels use one fixed surface and layers used two fixed surfaces.
dtime
Column 3 of the inventory has the reference time which is typically the analysis or start of forecast tme (the time stamp of the intial conditions). In our GFS forecast, there are 3 different dtimes.
bash-3.2$ wgrib2 gfs.t06z.pgrb2f12 -match ":(TMP:2 m above ground|PRATE|APCP):"
195:35104909:d=2013020806:TMP:2 m above ground:12 hour fcst:
202:36504744:d=2013020806:PRATE:surface:6-12 hour ave fcst:
203:36620774:d=2013020806:APCP:surface:6-12 hour acc fcst:
The 2 m temperature is the 12 hour forecast
The precipitation rate (PRATE) is the average of the 6-12 hour forecast (6 hour average)
The accumulated precipitation (APCP) is the accumulation of the 6 to 12 hour forecast (6 hour accumulation)
Making smaller grib files
It is common to be overwhelmed by data volumes of the forecasts. NCEP could output higher
resolution output files but the storage space and bandwidth need to distribute these files to the forecast offices and the public would break the budget. The end user also can have the same problem if they try to save the forecasts. One way to save space is to save only the important fields. Suppose you only wanted the APCP (accumulated precipitation) and the 2 m temperature. bash-3.2$ wgrib2 gfs.t06z.pgrb2f12 -match ":(TMP:2 m above ground|APCP):" -\ grib gfs.t06z.pgrb2f12.small 195:35104909:d=2013020806:TMP:2 m above ground:12 hour fcst: 203:36620774:d=2013020806:APCP:surface:6-12 hour acc fcst: bash-3.2$ ls -l gfs.t06z.pgrb2f12*
-rwxr-xr-x 1 wd51we wd5 58043511 2013-02-08 09:55 gfs.t06z.pgrb2f12 -rw-r--r-- 1 wd51we wd5 264780 2013-02-08 15:31 gfs.t06z.pgrb2f12.small
By one command, the file has gone from 58 MB to 0.26 MB. Now suppose we are only interested in the region lon=-100 to -40 and lat=0 to 50. Turning on compression (-set_grib_type c3) and writing out a section of the grib file gives a 25 KB file.
bash-3.2$ wgrib2 gfs.t06z.pgrb2f12.small -set_grib_type c2 \ -small_grib -120:-40 0:50 gfs.t06z.pgrb2f12.small.region 1:0:d=2013020806:TMP:2 m above ground:12 hour fcst: 2:191860:d=2013020806:APCP:surface:6-12 hour acc fcst: bash-3.2$ ls -l *small* -rw-r--r-- 1 wd51we wd5 264780 2013-02-08 15:31 gfs.t06z.pgrb2f12.small -rw-r--r-- 1 wd51we wd5 24888 2013-02-08 15:45 gfs.t06z.pgrb2f12.small.region
To see the grid of the first grib message, use the -grid option and -d 1 to only view the first message.
bash-3.2$ wgrib2 gfs.t06z.pgrb2f12.small.region -grid -d 1 1:0:grid_template=0:winds(N/S): lat-lon grid:(161 x 101) units 1e-06 input WE:SN output WE:SN res 48 lat 0.000000 to 50.000000 by 0.500000 lon 240.000000 to 320.000000 by 0.500000 #points=16261
So in our example, the original GFS forecast was 58 MB. By selecting a few fields and restricting the domain, our hypothetical file is now svelte 25 KB. (Think boat.) Jpeg compression would produce a smaller file at hte cost of more cpu cycles to decode.
《使用R语言读取grib2格式文件的方法》
wgrib2怎么安装 第二篇
使用R读取grib2文件
HR
Thursday, October 08, 2015
这个笔记整理了如何读取grib2格式文件。 下面代码中的cmd字符串也可以在命令行工具中直接输入，效果相同。
首先需要下载wgrib2命令行程序，这里是链接。将其中的wgrib2.exe和其他所有dll文件下载到某个本地路径下，并且将这个路径添加到系统环境变量中（可能需要重启生效）。【wgrib2怎么安装】
完成上面步骤后，可以在windows打开cmd，输入wgrib2，看看能否运行。 下面的例子中构造的cmd命令都是在R中用system函数执行的，也可以在
windows的cmd中直接输入。 也可以使用windows命令行的升级版powershell。 下面的例子可以参考一下，特别是输入到csv文件。
显示文件清单(inventory) # 这个fname是我放文件的路径
fname <- 'F:/tfiles/grib2_test/z500.ensm.jan.cfsv2.data.grb2' cmd <- paste('wgrib2 ', fname)
print(cmd)
## [1] "wgrib2 F:/tfiles/grib2_test/z500.ensm.jan.cfsv2.data.grb2" inv <- system(cmd, intern = TRUE)
print(inv[1:10])
## [1] "1:0:d=1982010618:HGT:500 mb:0-1 month ave fcst:" ## [2] "2:49817:d=1982010618:HGT:500 mb:1-2 month ave fcst:" ## [3] "3:99481:d=1982010618:HGT:500 mb:2-3 month ave fcst:" ## [4] "4:148921:d=1982010618:HGT:500 mb:3-4 month ave fcst:" ## [5] "5:198423:d=1982010618:HGT:500 mb:4-5 month ave fcst:" ## [6] "6:247781:d=1982010618:HGT:500 mb:5-6 month ave fcst:" ## [7] "7:297284:d=1982010618:HGT:500 mb:6-7 month ave fcst:" ## [8] "8:338341:d=1982010618:HGT:500 mb:7-8 month ave fcst:" ## [9] "9:379422:d=1982010618:HGT:500 mb:8-9 month ave fcst:" ## [10] "10:428705:d=1982010618:HGT:500 mb:9-10 month ave fcst:" 例如上面清单中最后一行：
280:13184074:d=2009010618:HGT:500 mb:9-10 month ave fcst:
它的格式含义如下：
(msg|msg.submsg):(byte location):d=(YYYYMMDDHH):(variable):(level):(ftime):(optional attr)
•
•
•
•
•
•
• msg = message/record number starting from 1 submsg = submessage number starting from 1 (optional) byte location: byte location of the start of the message starting from 0 YYYYMMDDHH = reference time of the grib message, YYYY = year, MM = month (01..12), DD = day, HH = hour level = level/layer attributes, ex. "500 mb", "ground", "2 m above ground" ftime = time attributes, ex. "12 hour fcst", "anl", "0-6 hr ave fcst" optional attr: optional attributes that are needed to define the field such as ensemble memeber, chemical type (for concentration), probability range 上面的例子中没有最后的optional attr。
使用正则表达式提取一部分数据 cmd <- paste('wgrib2', fname, '-match ":(9-10 month ave fcst:)"') cat(cmd)
## wgrib2 F:/tfiles/grib2_test/z500.ensm.jan.cfsv2.data.grb2 -match ":(9-10 month ave fcst:)"
system(cmd, intern = TRUE)
## [1] "10:428705:d=1982010618:HGT:500 mb:9-10 month ave fcst:" ## [2] "20:914776:d=1983010618:HGT:500 mb:9-10 month ave fcst:" ## [3] "30:1358944:d=1984010618:HGT:500 mb:9-10 month ave fcst:" ## [4] "40:1840531:d=1985010618:HGT:500 mb:9-10 month ave fcst:" ## [5] "50:2311667:d=1986010618:HGT:500 mb:9-10 month ave fcst:" ## [6] "60:2790757:d=1987010618:HGT:500 mb:9-10 month ave fcst:" ## [7] "70:3268997:d=1988010618:HGT:500 mb:9-10 month ave fcst:" ## [8] "80:3747732:d=1989010618:HGT:500 mb:9-10 month ave fcst:" ## [9] "90:4234662:d=1990010618:HGT:500 mb:9-10 month ave fcst:" ## [10] "100:4704898:d=1991010618:HGT:500 mb:9-10 month ave fcst:" ## [11] "110:5175124:d=1992010618:HGT:500 mb:9-10 month ave fcst:" ## [12] "120:5662066:d=1993010618:HGT:500 mb:9-10 month ave fcst:" ## [13] "130:6132600:d=1994010618:HGT:500 mb:9-10 month ave fcst:" ## [14] "140:6610677:d=1995010618:HGT:500 mb:9-10 month ave fcst:" ## [15] "150:7080915:d=1996010618:HGT:500 mb:9-10 month ave fcst:" ## [16] "160:7551390:d=1997010618:HGT:500 mb:9-10 month ave fcst:" ## [17] "170:8020510:d=1998010618:HGT:500 mb:9-10 month ave fcst:" ## [18] "180:8498763:d=1999010618:HGT:500 mb:9-10 month ave fcst:"
## [19] "190:8968889:d=2000010618:HGT:500 mb:9-10 month ave fcst:" ## [20] "200:9439038:d=2001010618:HGT:500 mb:9-10 month ave fcst:" ## [21] "210:9908977:d=2002010618:HGT:500 mb:9-10 month ave fcst:" ## [22] "220:10378928:d=2003010618:HGT:500 mb:9-10 month ave fcst:" ## [23] "230:10857351:d=2004010618:HGT:500 mb:9-10 month ave fcst:" ## [24] "240:11327224:d=2005010618:HGT:500 mb:9-10 month ave fcst:" ## [25] "250:11797608:d=2006010618:HGT:500 mb:9-10 month ave fcst:" ## [26] "260:12275544:d=2007010618:HGT:500 mb:9-10 month ave fcst:" ## [27] "270:12719549:d=2008010618:HGT:500 mb:9-10 month ave fcst:" ## [28] "280:13184074:d=2009010618:HGT:500 mb:9-10 month ave fcst:" 使用for提取指定的数据 cmd <- paste('wgrib2', fname, '-for 1:3')
cat(cmd)
## wgrib2 F:/tfiles/grib2_test/z500.ensm.jan.cfsv2.data.grb2 -for 1:3 system(cmd, intern = TRUE)
## [1] "1:0:d=1982010618:HGT:500 mb:0-1 month ave fcst:"
## [2] "2:49817:d=1982010618:HGT:500 mb:1-2 month ave fcst:"
## [3] "3:99481:d=1982010618:HGT:500 mb:2-3 month ave fcst:"
cmd <- paste('wgrib2', fname, '-for 1:90:9')
cat(cmd)
## wgrib2 F:/tfiles/grib2_test/z500.ensm.jan.cfsv2.data.grb2 -for 1:90:9
system(cmd, intern = TRUE)
## [1] "1:0:d=1982010618:HGT:500 mb:0-1 month ave fcst:" ## [2] "10:428705:d=1982010618:HGT:500 mb:9-10 month ave fcst:" ## [3] "19:865637:d=1983010618:HGT:500 mb:8-9 month ave fcst:" ## [4] "28:1271688:d=1984010618:HGT:500 mb:7-8 month ave fcst:" ## [5] "37:1700586:d=1985010618:HGT:500 mb:6-7 month ave fcst:" ## [6] "46:2138511:d=1986010618:HGT:500 mb:5-6 month ave fcst:" ## [7] "55:2559867:d=1987010618:HGT:500 mb:4-5 month ave fcst:" ## [8] "64:2989028:d=1988010618:HGT:500 mb:3-4 month ave fcst:" ## [9] "73:3417926:d=1989010618:HGT:500 mb:2-3 month ave fcst:" ## [10] "82:3847050:d=1990010618:HGT:500 mb:1-2 month ave fcst:" 打印某个格点的值
cmd <- paste('wgrib2', fname, '-ij 1 1 -match ":(9-10 month ave fcst:)"')
cat(cmd)
## wgrib2 F:/tfiles/grib2_test/z500.ensm.jan.cfsv2.data.grb2 -ij 1 1 -match ":(9-10 month ave fcst:)"
system(cmd, intern = TRUE)
## [1] "10:428705:val=4894.24" "20:914776:val=4881.72"
## [3] "30:1358944:val=4897.78" "40:1840531:val=4896.65"
## [5] "50:2311667:val=4895.34" "60:2790757:val=4893.62"
## [7] "70:3268997:val=4868.71" "80:3747732:val=4890.9"
## [9] "90:4234662:val=4894.6" "100:4704898:val=4896.5"
## [11] "110:5175124:val=4883.06" "120:5662066:val=4871.52"
## [13] "130:6132600:val=4888.44" "140:6610677:val=4880.16"
## [15] "150:7080915:val=4909.38" "160:7551390:val=4878.94"
## [17] "170:8020510:val=4892.94" "180:8498763:val=4890.63"
## [19] "190:8968889:val=4896.03" "200:9439038:val=4883.31"
## [21] "210:9908977:val=4887.11" "220:10378928:val=4908.46"
## [23] "230:10857351:val=4881.15" "240:11327224:val=4874.53"
## [25] "250:11797608:val=4904.4" "260:12275544:val=4877.42"
## [27] "270:12719549:val=4913.26" "280:13184074:val=4891.47"
输出为csv文件 fout <- 'F:/tfiles/grib2_test/test.csv'
cmd <- paste('wgrib2', fname, '-match ":(6-7 month ave fcst:)"', '-match ":(d=2009010618)"', '-csv', fout)
cat(cmd)
## wgrib2 F:/tfiles/grib2_test/z500.ensm.jan.cfsv2.data.grb2 -match ":(6-7 month ave fcst:)" -match ":(d=2009010618)" -csv F:/tfiles/grib2_test/test.csv
system(cmd, intern = TRUE)
## [1] "277:13060769:d=2009010618:HGT:500 mb:6-7 month ave fcst:" data <- read.csv(fout, header = F)
head(data)
## V1 V2 V3 V4 V5 V6 V7 ## 1 2009-01-06 18:00:00 2009-01-06 18:00:00 HGT 500 mb 0 -90 4873.53 ## 2 2009-01-06 18:00:00 2009-01-06 18:00:00 HGT 500 mb 1 -90 4873.53 ## 3 2009-01-06 18:00:00 2009-01-06 18:00:00 HGT 500 mb 2 -90 4873.53 ## 4 2009-01-06 18:00:00 2009-01-06 18:00:00 HGT 500 mb 3 -90 4873.53 ## 5 2009-01-06 18:00:00 2009-01-06 18:00:00 HGT 500 mb 4 -90 4873.53 ## 6 2009-01-06 18:00:00 2009-01-06 18:00:00 HGT 500 mb 5 -90 4873.53 library(lattice)
contourplot(V7~V5+V6, data = data, region = T, cuts = 20)
输出为netcdf文件 fout <- 'F:/tfiles/grib2_test/test.nc'
cmd <- paste('wgrib2', fname, '-match ":(6-7 month ave fcst:)"', '-netcdf', fout)
cat(cmd)
## wgrib2 F:/tfiles/grib2_test/z500.ensm.jan.cfsv2.data.grb2 -match ":(6-7 month ave fcst:)" -netcdf F:/tfiles/grib2_test/test.nc
system(cmd, intern = TRUE)
## [1] "7:297284:d=1982010618:HGT:500 mb:6-7 month ave fcst:" ## [2] "17:775376:d=1983010618:HGT:500 mb:6-7 month ave fcst:" ## [3] "27:1227944:d=1984010618:HGT:500 mb:6-7 month ave fcst:" ## [4] "37:1700586:d=1985010618:HGT:500 mb:6-7 month ave fcst:" ## [5] "47:2188097:d=1986010618:HGT:500 mb:6-7 month ave fcst:" ## [6] "57:2658973:d=1987010618:HGT:500 mb:6-7 month ave fcst:" ## [7] "67:3137523:d=1988010618:HGT:500 mb:6-7 month ave fcst:" ## [8] "77:3616110:d=1989010618:HGT:500 mb:6-7 month ave fcst:" ## [9] "87:4094772:d=1990010618:HGT:500 mb:6-7 month ave fcst:" ## [10] "97:4581667:d=1991010618:HGT:500 mb:6-7 month ave fcst:"
《气象组织NCEP_GRIB2文档(原文)》
wgrib2怎么安装 第三篇
Introduction
Revision History
Section 0 - Indicator Section
Table 0.0 - Discipline of Processed Data
Section 1 - Identification Section
Table 1.0 - GRIB Master Tables Version Number
Table 1.1 - GRIB Local Tables Version Number
Table 1.2 - Significance of Reference Time
Table 1.3 - Production Status of Data
Table 1.4 - Type of Data【wgrib2怎么安装】
Section 2 - Local Use Section
Section 3 - Grid Definition Section
Table 3.0 - Source of Grid Definition
Table 3.1 - Grid Definition Template Number
Table 3.2 - Shape of the Earth
Table 3.3 - Resolution and Component Flags
Table 3.4 - Scanning Mode
Table 3.5 - Projection Center
Table 3.6 - Spectral Data Representation Type
Table 3.7 - Spectral Data Representation Mode
Table 3.8 - Grid Point Position
Table 3.9 - Numbering Order of Diamonds
Table 3.10 - Scanning Mode for One Diamond
Table 3.11 - Interpretation of List of Numbers at end of section 3
Table 3.15 - Physical Meaning of Vertical Coordinate
Table 3.20 - Type of Horizontal Line
Table 3.21 - Vertical Dimension Coordinate Values Definition
Section 4 - Product Definition Section
Table 4.0 - Product Definition Template Number
Table 4.1 - Parameter Category by Product Discipline
Table 4.2 - Parameter Number by Product Discipline and Parameter Category
Table 4.3 - Type of Generating Process
Table 4.4 - Indicator of Unit of Time Range
Table 4.5 - Fixed Surface Types and Units
Table 4.6 - Type of Ensemble Forecast
Table 4.7 - Derived Forecast
Table 4.8 - Clustering Method
Table 4.9 - Probability Type
Table 4.10 - Type of Statistical Processing
Table 4.11 - Type of Time Intervals
Table 4.12 - Operating Mode
Table 4.13 - Quality Control Indicator
Table 4.14 - Clutter Filter Indicator
Table 4.15 - Type of Spatial Processing used to arrive at given
data value from the source data
Table 4.201 - Precipitation Type
Table 4.202 - Precipitable Water Category
Table 4.203 - Cloud Type【wgrib2怎么安装】
Table 4.204 - Thunderstorm Coverage
Table 4.205 - Presence of Aerosol
Table 4.206 - Volcanic Ash
Table 4.207 - Icing
Table 4.208 - Turbulence
Table 4.209 - Planetary Boundary-Layer Regime
Table 4.210 - Contrail Intensity
Table 4.211 - Contrail Engine Type
Table 4.212 - Land Use
Table 4.213 - Soil Type
Table 4.215 - Remotely Sensed Snow Coverage
Table 4.216 - Elevation of Snow Covered Terrain
Table 4.217 - Cloud Mask Type
Table 4.218 - Pixel Scene Type
Table 4.219 - Cloud Top Height Quality Indicator
Table 4.220 - Horizontal Dimension Processed
Table 4.221 - Treatment of Missing Data
Table 4.222 - Categorical Result
Table 4.223 - Fire Detection Indicator
Table 4.224 - Categorical Outlook
Table 4.230 - Atmospheric Chemical or Physical Type
Section 5 - Data Representation Section
Table 5.0 - Data Representation Template Number
Table 5.1 - Type of Original Field Values
Table 5.2 - Matrix Coordinate Value Function Definition
Table 5.3 - Matrix Coordinate Parameter
Table 5.4 - Group Splitting Method
Table 5.5 - Missing Value Management for Complex Packing
Table 5.6 - Order of Spatial Differencing
Table 5.7 - Precision of Floating Point Numbers
Table 5.40 - Type of Compression
Section 6 - Bit Map Section
Table 6.0 - Bit Map Indicator
Section 7 - Data Section
Section 8 - End Section
Appendix A - Outline of WMO Headers Used With GRIB1 and GRIB2
Appendix B - Outline of WMO Headers for the EPA/CMAQ model
Appendix C - Definition of Commonly used NCEP Grids
GRIB2 - GRIB1 Local parameter conversion table
Disclaimer:
This web page and the pages it links to are for the use of NOAA employees and their customers to facilitate in the transfer of meteorological data in WMO GRIB2 format. Nothing in these pages should be considered official. To obtain official documentation on the WMO GRIB2 data standard, please visit the WMO web site.
/retype/zoom/68b633373968011ca3009188?pn=4&x=0&y=0&raww=512&rawh=199&o=jpg_6_0_______&type=pic&aimh=186.5625&md5sum=f1c9748d7d95f0914314771e71664ade&sign=c80f230071&zoom=&png=0-301&jpg=0-14770" target="_blank">本人了解的就这些了，最后说一下ubuntu是不支持。rpm的，那是fedora使用的安装包格式，效果类似于deb。