About

WorldDailyMeteo: space-time interpolation of daily meteorological variables (GSOD) at 1 km resolution


Introduction

Hengl et al. (2011) describe a framework for space-time interpolation of daily measurements of meteorological variables by using time-series of MODIS images. This framework can now be implemented using global data sets to produce the new most accurate maps of meteorological/climatic variables (i.e. a new generation of the WorldClim.org repository; Hijmans et al 2005), and analyze temporal changes and trends. International dataset of interest are: the Global Surface Summary of Day (GSOD) product produced by the National Climatic Data Center (NCDC) and the European Climate Assessment (ECA). Both data sets are intended for free and unrestricted use in research, education, and other non-commercial activities. Description of GSOD data is available via the NCDC website. Likewise, MODIS atmospheric products are freely available via FTP or via the MODIS web services.

The objective of this project is to produce a time-series of predictions using automated global spatio-temporal statistics (spatio-temporal regression-kriging with the help of MODIS images and other freely available atmospheric images). For each meteo variable we fit a global space-time model (regression + variogram parameters) and then use those to predict values at daily interval and at resolution of 1/120 arcdegrees (or about 1 km).


Specifications

Targeted meteo variables (by priority):

  1. Mean temperature (degree C),
  2. Maximum temperature  (degree C),
  3. Minimum temperature (degree C),
  4. Precipitation amount (mm),
  5. Mean wind speed (.1 knots converted to m/s),
  6. Snow depth (cm),
  7. Meteo indicators (fog, rain, snow, hail, thunder, tornado) (8) Pressure (hPa).

 

Time period of interest: 2000 March 5 - today  (MODIS time series data)
Total temporal coverage: ca 4300 days
Target grid: W180 - E180, S90 - N90 (Global land areas)
1/120 decimal degrees (or about 1 km)
Grid properties: 43,200 by 21,600 pixels
(land mask about 160 million pixels)
Input data: about 10,000 meteo stations
(Global Surface Summary of Day (GSOD) and the European Climate Assessment (ECA))

 


WorldDailyMeteo products

Three groups of products can be traced via this website:

  • Daily predictions of key meteo variables at 1 km resolution (METEO1KM)
  • meteo package for R
  • Demo's and tutorials

The team (login)

Event Calendar

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Meteo package

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