Importance of Surface Processes

Parameters such as the Normalized Vegetation (NDVI), Land Surface Temperature (LST), and Sea Surface Temperature (SST) are vital in understanding and modeling surface-atmosphere interaction. First, it is vital to understand the complexities involved in studies of surface characteristics (in particular, remote sensing studies). The land surface can be made up of sand, mud, swamp, grass, rock, etc. Each of these substances have different spectral properties and appear differently in remotely sensed data from aircraft and satellites. Therefore, it is necessary to identify each of these substances and account for their impact on the process or quantity being measured. With that in mind we will explore the different parameters our group has investigated.

NDVI is constructed using visible and near infrared data. Simply stated, chlorophyll, the green substance that is responsible for photosynthesis, reflects near infrared radiation more than it reflects visible radiation. Thus, it is possible to form a mathematically relationship which is high when green plants cover a pixel (digital picture element) and low when no green plants are present. This is important in meteorology because it determines the amount of energy going into the Earth’s surface (as well as that being reflected) to heat the atmosphere; i.e., when the NDVI is high LSTs are cooler and therefore since the atmosphere is heated from below it can be inferred that the air temperature is also cooler than it would be given the same conditions with a lower NDVI. LST is important because it determines the effective radiating temperature of the Earth’s surface which controls the surface air temperature as well as the clear sky Outgoing Longwave Radiation (OLR), which is important in the energy balance of the Earth. Finally, SST, in addition to it’s economic importance as a determining factor in type of fish and seafood in a given area, it also impacts the atmosphere through latent heat release during evaporation, and it can determine seasonal and interannual variability of the climate or a region or the globe (e.g., El Nino).

Last updated on: November 2, 1999