Effects of implementing MODIS land cover and albedo in MM5 at two contrasting US regions

Yucel I.

JOURNAL OF HYDROMETEOROLOGY, vol.7, no.5, pp.1043-1060, 2006 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 7 Issue: 5
  • Publication Date: 2006
  • Doi Number: 10.1175/jhm536.1
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1043-1060
  • Middle East Technical University Affiliated: Yes


This study implements a new land-cover classification and surface albedo from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) Mesoscale Model (MM5) and investigates its effects on regional near-surface atmospheric state variables as well as the planetary boundary layer evolution for two dissimilar U.S. regions. Surface parameter datasets are determined by translating the 17-category MODIS classes into the U.S. Geological Survey (USGS) and Simple Biosphere (SiB) categories available for use in MM5. Changes in land-cover specification or associated parameters affected surface wind, temperature, and humidity fields, which, in turn, resulted in perceivable alterations in the evolving structure of the planetary boundary layer. Inclusion of the MODIS albedo into the simulations enhanced these impacts further. Area-averaged comparisons with ground measurements showed remarkable improvements in near-surface temperature and humidity at both study areas when MM5 is initialized with MODIS land-cover and albedo data. Influence of both MODIS surface datasets is more significant at a semiarid location in the southwest of the United States than it is in a humid location in the mid-Atlantic region. Intense summertime surface heating at the semiarid location creates favorable conditions for strong land surface forcing. For example, when the simulations include MODIS land cover and MODIS albedo, respective error reduction rates were 6% and 11% in temperature and 2% and 2.5% in humidity in the southwest of the United States. Error reduction rates in near-surface atmospheric fields are considered important in the design of mesoscale weather simulations.