This function downloads remote sensing data of GLDAS from NASA GSFC servers, extracts air temperature data from grids within a specified watershed shapefile, and then generates tables in a format that SWAT requires for minimum and maximum air temperature data input. The function also generates the air temperature stations file input (file with columns: ID, File NAME, LAT, LONG, and ELEVATION) for those selected grids that fall within the specified watershed.
Usage
GLDASwat(
Dir = "./SWAT_INPUT/",
watershed = "LowerMekong.shp",
DEM = "LowerMekong_dem.tif",
start = "2015-12-1",
end = "2015-12-3"
)Arguments
- Dir
A directory name to store gridded air temperature and air temperature stations files.
- watershed
A study watershed shapefile spatially describing polygon(s) in a geographic projection crs='+proj=longlat +datum=WGS84'.
- DEM
A study watershed digital elevation model raster in a geographic projection crs='+proj=longlat +datum=WGS84'.
- start
Beginning date for gridded air temperature data.
- end
Ending date for gridded air temperature data.
Value
A table that includes points ID, Point file name, Lat, Long, and Elevation information formatted to be read with SWAT, and
a scalar of maximum and minimum air temperature gridded data values at each point within the study watershed in ascii format needed by SWAT model weather inputs will be stored at Dir.
Details
A user should visit https://disc.gsfc.nasa.gov/information/documents Data Access document to register with the Earth Observing System Data and Information System (NASA Earthdata) and then authorize NASA GESDISC Data Access to successfully work with this function. The function accesses NASA Goddard Space Flight Center server address for GLDAS remote sensing data products at (https://hydro1.gesdisc.eosdis.nasa.gov/data/GLDAS/GLDAS_NOAH025_3H.2.1/). The function uses variable name ('Tair_f_inst') for air temperature in GLDAS data products. Units for gridded air temperature data are degrees in 'K'. The GLDASwat function outputs gridded air temperature (maximum and minimum) data in degrees 'C'.
The goal of the Global Land Data Assimilation System GLDAS is to ingest satellite and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes (Rodell et al., 2004). GLDAS dataset used in this function is the GLDAS Noah Land Surface Model L4 3 hourly 0.25 x 0.25 degree V2.1. The full suite of GLDAS datasets is available at https://hydro1.gesdisc.eosdis.nasa.gov/dods/. The GLDASwat finds the minimum and maximum air temperatures for each day at each grid within the study watershed by searching for minima and maxima over the three hours air temperature data values available for each day and grid.
The GLDASwat function relies on 'curl' tool to transfer data from NASA servers to a user machine, using HTTPS supported protocol. The 'curl' command embedded in this function to fetch GLDAS netcdf daily global files is designed to work seamlessly given that appropriate logging information are stored in the ".netrc" file and the cookies file ".urs_cookies" as explained in registering with the Earth Observing System Data and Information System. It is imperative to say here that a user machine should have 'curl' installed as a prerequisite to run GLDASwat.
The GLDAS V2.1 simulation started on January 1, 2000 using the conditions from the GLDAS V2.0 simulation. The GLDAS V2.1 simulation was forced with National Oceanic and Atmospheric Administration NOAA, Global Data Assimilation System GDAS atmospheric analysis fields (Derber et al., 1991), the disaggregated Global Precipitation Climatology Project GPCP precipitation fields (Adler et al., 2003), and the Air Force Weather Agency’s AGRicultural METeorological modeling system AGRMET radiation fields which became available for March 1, 2001 onward.
References
Adler, R. F., G. J. Huffman, A. Chang, R. Ferraro, P.-P. Xie, J. Janowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gruber, J. Susskind, P. Arkin, and E. Nelkin (2003), The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present), J. Hydrometeorol., 4, 1147-1167, doi:10.1175/1525-7541(2003)004<1147:tvgpcp>2.0.co;2.
Derber, J. C., D. F. Parrish, and S. J. Lord (1991), The New Global Operational Analysis System at the National Meteorological Center, Weather Forecast, 6, 538-547, doi:10.1175/1520-0434(1991)006<0538:tngoas>2.0.co;2.
Rodell, M., P. R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, K. Arsenault, B. Cosgrove, J. Radakovich, M. Bosilovich, J. K. Entin*, J. P. Walker, D. Lohmann, and D. Toll (2004), The Global Land Data Assimilation System, B. Am. Meteorol. Soc., 85, 381-394, doi:10.1175/bams-85-3-381.
Author
Ibrahim Mohammed, ibrahim.mohammed@ku.ac.ae