Dr. Sumant Nigam, Professor

Dr. Alfredo Ruiz-Barradas, Assoc. Professor

Dr. Agniv Sengupta, Former Graduate Student (now Postdoc at JPL/Caltech)




Dept. of Atmospheric and Oceanic Science
3419 Atlantic Bldg., 4254 Stadium Drive
University of Maryland
College Park, MD 20742, USA

Landline:(301) 405-5381 (5391)
Mobile:   (202) 415-5626
Fax:        (301) 314-9482
Email:     nigam@umd.edu

The Laboratory for Experimental Hydroclimate Prediction seeks to develop subseasonal-to-seasonal forecasts of regional variations in precipitation, sea surface temperature (SST), surface air temperature (SAT), and soil moisture using influential climate system components with large thermal inertia as predictors.

A distinctive feature of the laboratory's prediction strategy is its statistical approach, rooted in innovative spatiotemporal analysis of the observational record. The deployed strategy is complementary to the commonly pursued dynamical prediction paradigm where similar influences find forecast expression from initialized integrations of the atmospheric and oceanic general circulation models. The skill of statistical forecasts provides an important evaluative benchmark for dynamical forecasting. The statistical forecasts generated by the laboratory are more skillful than previous ones, upping the ante for dynamical forecasting of regional hydroclimate variations.

Upper ocean temperatures, in particular, meet the criterion of an influential climate system component with large thermal inertia but reliable long-term observations are available mostly at the surface. The influence of sea surface temperature on regional and faraway hydroclimate is efficiently mined in this prediction effort.


  • South Asian Summer Monsoon Rainfall Forecast:       2020 Press Release

  • El Nino Southern Oscillation (ENSO) Forecast