Assessment of implementing satellite-derived land cover data in the eta model

Nicole P. Kurkowski, David J. Stensrud, Michael E. Baldwin

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

One of the challenges in land surface modeling involves specifying accurately the initial state of the land surface. Most efforts have focused upon using a multiyear climatology to specify the fractional coverage of vegetation. For example, the National Centers for Environmental Prediction (NCEP) Eta Model uses a 5-yr satellite climatology of monthly normalized difference vegetation index (NDVI) values to define the fractional vegetation coverage, or greenness, at 1/8° (approximately 14 km) resolution. These data are valid on the 15th of every month and are interpolated temporally for daily runs. Yet vegetation characteristics change from year to year and are influenced by short-lived events such as fires, crop harvesting, droughts, floods, and hailstorms that are missed using a climatological database. To explore the importance of the initial state vegetation characteristics on operational numerical weather forecasts, the response of the Eta Model to initializing fractional vegetation coverage directly from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) data is investigated. Numerical forecasts of the Eta Model, using both climatological and near-real-time values of fractional vegetation coverage, are compared with observations to examine the potential importance of variations in vegetation to forecasts of 2-m temperatures and dewpoint temperatures from 0 to 48 h for selected days during the 2001 growing season. Results show that use of the near-real-time vegetation fraction data improves the forecasts of both the 2-m temperature and dewpoint temperature for much of the growing season, highlighting the need for this type of information to be included in operational forecast models.

Original languageEnglish (US)
Pages (from-to)404-416
Number of pages13
JournalWeather and Forecasting
Volume18
Issue number3
DOIs
StatePublished - Jun 2003

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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