tsgettoolbox.ldas_nldas3_forcing

tsgettoolbox.ldas_nldas3_forcing(lat, lon, variables=None, startDate=None, endDate=None, time_interval='hourly')

NAmerica:0.01deg:2001-:HDM:NLDAS Meteorological Forcing (surface)

Description/Name	Spatial	Lat Range	Lon Range	Time
NLDAS V3 Forcing	0.01x0.01	7, 72	-169, -52	1 hr, daily, monthly 2001-01-01 to recent

Baldwin, M., and K.E. Mitchell, 1997: The NCEP hourly multi-sensor U.S. precipitation analysis for operations and GCIP research. Preprints, 13th AMS Conference on Hydrology, pp. 54-55, Am. Meteorol. Soc., Boston, Mass.

Berg, A.A., J.S. Famiglietti, J.P. Walker, and P.R. Houser, 2003: Impact of bias correction to reanalysis products on simulations of North American soil moisture and hydrological fluxes. J. Geophys. Res., 108(D16), 4490, doi:10.1029/2002JD003334.

Cosgrove, B.A., et al., 2003: Real-time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project. J. Geophys. Res., 108(D22), 8842, doi:10.1029/2002JD003118.

Daly, C., R.P. Neilson, and D.L. Phillips, 1994: A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteor., 33, 140-158, doi:10.1175/1520-0450(1994)033<0140:ASTMFM>2.0.CO;2

Fulton, R.A., J.P. Breidenbach, D.J. Seo, D.A. Miller, and T. O’Bannon, 1998: The WSR-88D rainfall algorithm. Weather and Forecasting, 13, 377-395.

Higgins, R.W., J.E. Janowiak and Y. Yao, 1996: A gridded hourly precipitation data base for the United States (1963-1993). NCEP/Climate Prediction Center Atlas No. 1.

Higgins, R.W., W. Shi, E. Yarosh, and R. Joyce, 2000: Improved United States precipitation quality control system and analysis. NCEP/Climate Prediction Center Atlas No. 7.

Mitchell, K.E., et al., 2004: The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J. Geophys. Res., 109, D07S90, doi:10.1029/2003JD003823.

Mo, K.C., L.-C. Chen, S. Shukla, T.J. Bohn, and D.P. Lettenmaier, 2012: Uncertainties in North American Land Data Assimilation Systems over the Contiguous United States. J. Hydrometeor, 13, 996-1009, doi:10.1175/JHM-D-11-0132.1

Pinker, R.T., et al., 2003: Surface radiation budgets in support of the GEWEX Continental-Scale International Project (GCIP) and the GEWEX Americas Prediction Project (GAPP), including the North American Land Data Assimilation System (NLDAS) project. J. Geophys. Res., 108(D22), 8844, doi:10.1029/2002JD003301.

Parameters:

• lat (float) – Latitude (required): Enter single geographic latitude point. Use positive values for the northern hemisphere and negative for the southern hemisphere. The valid range is specified in the table above.

• lon (float) – Longitude (required): Enter single geographic longitude point. Use positive for the eastern hemisphere and negative for the western hemisphere. The valid range is specified in the table above.

• variables (str) –

  For the command line a comma separated string of variable codes from the following table. Using the Python API a list of variable strings. Valid variable names are specified in the table below.

  ${units_table}

• startDate (str) –

  The start date of the time series.:

  Example: --startDate=2001-01-01T05
  

  If startDate and endDate are None, returns the entire series.

• endDate (str) –

  The end date of the time series.:

  Example: --endDate=2002-01-05T05
  

  If startDate and endDate are None, returns the entire series.

• time_interval (Literal['hourly', 'daily']) – The time interval of the data to retrieve. Can be either “hourly” or “daily”. Defaults to “hourly”.