GFS/FNL dataset

News (2024 July)

RDA Data Services Unavailable July 30, 2024

New setup goes to

https://waipangsze.github.io/2024/08/16/GFS_FNL_RDA_upgrade/

GFS

The Global Forecast System (GFS)[1] is a National Centers for Environmental Prediction (NCEP) weather forecast model that generates data for dozens of atmospheric and land-soil variables, including temperatures, winds, precipitation, soil moisture, and atmospheric ozone concentration. The system couples four separate models (atmosphere, ocean model, land/soil model, and sea ice) that work together to accurately depict weather conditions.

Specifications

The GFS[2] [3] is run four times a day, producing forecasts up to 16 days in advance. The forecast component uses the Finite Volume Cubed (FV3) model with a resolution of ~13 km, with the atmosphere coupled to the NCEP Global Wave Model. In the vertical, the model is divided into 127 vertical layers. It produces hourly forecast output for the first 120 hours, then 3 hourly for days 5-16. Details on the June 2019 implementation of the initial FV3 version of the GFS (GFSv15) and the March 2021 implementation of GFSv16 can be found in the links listed below.

Download

NCEP GFS 0.25 Degree Global Forecast Grids Historical Archive ds084.1 | DOI: 10.5065/D65D8PWK > https://rda.ucar.edu/datasets/ds084.1/ > The NCEP operational Global Forecast System analysis and forecast grids are on a 0.25 by 0.25 global latitude longitude grid. Grids include analysis and forecast time steps at a 3 hourly interval from 0 to 240, and a 12 hourly interval from 240 to 384. Model forecast runs occur at 00, 06, 12, and 18 UTC daily.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
#!/bin/sh
#################################################################
# Csh Script (wpsze: to sh script) to retrieve 34 online Data files of 'ds084.1',
# total 7.16G. This script uses 'wget' to download data.
#
# Highlight this script by Select All, Copy and Paste it into a file;
# make the file executable and run it on command line.
#
# You need pass in your password as a parameter to execute
# this script; or you can set an environment variable RDAPSWD
# if your Operating System supports it.
#
# Contact rdahelp@ucar.edu (RDA help desk) for further assistance.
#################################################################

wget --no-check-certificate -O \
Authentication.log --save-cookies auth.rda_ucar_edu \
--article-data="email=**xxx@gmail.com**&passwd=**xxx**&action=login" https://rda.ucar.edu/cgi-bin/login

yyyy='2023'
mm='03'
dd='19'
hh='00'
yyyymm=${yyyy}

for gfsfile in $(seq 0 3 12); do # Forecast time = 12, 24, 36, 48, 60, 72, 84, 96, 108, 130, 142, 154
	tmp=$(printf "%03d" ${gfsfile})
	tmp="${yyyy}/${yyyy}${mm}${dd}/gfs.0p25.${yyyy}${mm}${dd}${hh}.f${tmp}.grib2"
	echo ${tmp}
	
	echo "downloading ..."
	wget --no-check-certificate -N --load-cookies auth.rda_ucar_edu https://rda.ucar.edu/data/ds084.1/${tmp}
done

If your operational process needs the format of GFS files like as > gfs_20170724_0000_0p25_000

1
2
3
4
5
6
7
8
9
10
11
#!/bin/sh

old_gfs=`ls ./*.grib2`

for eachfile in ${old_gfs}
do
   echo ${eachfile}
   echo ${eachfile:11:8}, ${eachfile:19:2}, ${eachfile:23:3}
   echo gfs_${eachfile:11:8}_00${eachfile:19:2}_0p25_${eachfile:23:3}
   ln -s ${eachfile} gfs_${eachfile:11:8}_00${eachfile:19:2}_0p25_${eachfile:23:3}
done

Usage of GFS on WRF/NWP

GFS Data > https://www2.mmm.ucar.edu/wrf/OnLineTutorial/DATA/GFS/gfs.php > GFS (Global Forecast System) is a model product from NCEP. > Type: GRIB1 / GRIB2 data

Resolution: > 0.25 deg global data > Output frequency 3 hourly > 34 pressure levels

Availability: > From NCAR's RDA site: https://rda.ucar.edu/datasets/ds084.1/

Vtable: Vtable.GFS

namelist.wps

1
2
3
4
5
# Edit namelist.wps
start_date = '2019-11-29_12:00:00',
end_date = '2019-12-01_00:00:00',
interval_seconds = 10800,
prefix = 'FILE',

Script

1
2
3
4
5
6
7
8
9
10
11
12
13
# Notes on running UNGRIB for this data
# Examine the GRIB files, e.g.,
# ./util/g2print.exe ../DATA/co_blizzard/gfs.0p25.2019112912.f000.grib2

ln -sf ungrib/Variable_Tables/Vtable.GFS Vtable
./link_grib.csh ../DATA/co_blizzard/gfs.0p25.2019

./ungrib.exe
# This will create an ungrib.log for your records.

# Examine the intermediate files, e.g.,
# ./util/rd_intermediate.exe FILE:2019-11-29_12
# ncl /util/plotfmt_ncl 'filename="FILE:2019-11-29_12"'

Usage of FNL on WRF/NWP

The NCEP FNL (Final) Operational Global Analysis[4] [5] [6] is on 1x1 degree grids are available every six hours. The analyses are from the NCEP Final Analyses (FNL). These were operationally prepared by NCEP, but are available for download from NCAR/RDA.

This product is from the Global Data Assimilation System (GDAS), which continuously collects observational data from the Global Telecommunications System (GTS), and other sources, for many analyses. The FNLs are made with the same model which NCEP uses in the Global Forecast System (GFS), but the FNLs are prepared about an hour or so after the GFS is initialized. The FNLs are delayed so that more observational data can be used. The GFS is run earlier in support of time critical forecast needs, and uses the FNL from the previous 6 hour cycle as part of its initialization.

FNL数据集和GFS数据集虽有联系，但在同一资料同化和预报系统中却有不同的产品。它们共享相同的基础模型和数据同化技术。它们包含相同的数据源——但是在gfs和fnl的初始条件中吸收的“真实”数据的数量有细微的差别。即使有ncep的巨大计算资源，运行一个全球nwp模型也需要时间。因此，他们需要尽早启动gfs来获得预报而不是后报。fnl是最终的分析结果，比gfs稍晚一些，以便能包括所有可用的观测数据。通常，fnl比gfs多摄取约10%的观察结果。虽然开始时间较晚，但仍有足够的时间，因此6小时的fnl6小时预报可作为下一个gfs资料同化周期的背景场例如，如果你想要00z的气球数据，你必须等待气球上升穿过大气层。对于能够到达平流层的大型氦气箱来说，这可能需要多达90分钟。然后气球的数据需要从世界各地传送到美国马里兰州的ncep中心。如果你想要00z的卫星数据，你必须等待卫星经过一个地面站，这样它才能下载数据。地面站然后通过陆地或海底电缆(如果有的话)传送数据，或者通过另一颗(通信)卫星传送数据。[7]

For further information about the FNL archives at NCAR: See, http://rda.ucar.edu/datasets/ds083.2.

Type: > GRIB2 data

Resolution: > 1deg global data > Output frequency 6 hourly > 34 pressure levels

Availability: > http://rda.ucar.edu/datasets/ds083.2 > Follow the tab to "Data Access -> Internet Download". You must register (it is free) to access the data.

Vtable: Vtable.GFS

namelist.wps

1
2
3
4
5
Edit namelist.wps
start_date = '2019-11-25_12:00:00',
end_date = '2019-11-27_00:00:00',
interval_seconds = 21600,
prefix = 'FILE',

Script

1
2
3
4
5
6
7
8
9
10
11
12
13
# Notes on running UNGRIB for this data
# Examine the GRIB files, e.g.,
# ./util/g2print.exe ../DATA/boulder_snow/fnl_20191125_12_00.grib2
ln -sf ungrib/Variable_Tables/Vtable.GFS Vtable

./link_grib.csh ../DATA/boulder_snow/fnl_2019

./ungrib.exe
# This will create an ungrib.log for your records.

# Examine the intermediate files, e.g.,
# ./util/rd_intermediate.exe FILE:2019-11-25_12
# ncl /util/plotfmt.ncl 'filename="FILE:2019-11-25_12"'

Read and Plot grib2 files

1
2
3
import xarray as xr
ds = xr.open_dataset('./fnl_20191125_12_00.grib2',engine='pynio')
ds
  1. GFS Data Access ↩
  2. GFS home page ↩
  3. Global Models Verification ↩
  4. FNL more ↩
  5. GFS vs FNL ↩
  6. Analysis, reanalysis, forecast—what’s the difference? ↩
  7. FNL再分析数据和GFS数据之间的区别和联系 ↩
NWP
#WRF #WPS #MPAS #IC/BC #NCEP
GFS/FNL dataset
https://waipangsze.github.io/2023/04/27/GFS_FNL/
Author
wpsze
Posted on
April 27, 2023
Updated on
October 8, 2024
Licensed under