Details

Autor(en) / Beteiligte

• Bisht, Gautam
• Bras, Rafael L.

Titel

Estimation of net radiation from the MODIS data under all sky conditions: Southern Great Plains case study

Ist Teil von

• Remote sensing of environment, 2010-07, Vol.114 (7), p.1522-1534

Ort / Verlag

New York, NY: Elsevier Inc

Erscheinungsjahr

2010

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Net radiation is a key component in the surface radiation budget. Numerous studies have developed frameworks to estimate net radiation or its components (upwelling or downwelling longwave and/or shortwave radiation) from remote sensing data for clear sky conditions. Application of existing methodologies to estimate net radiation for cloudy sky conditions from remote sensing sensors remains a significant challenge. In this paper, we present a framework to estimate instantaneous and daily average net radiation under all sky conditions from using the data from the MODerate Resolution Imaging Spectroradiometer (MODIS), onboard from the Terra satellites. Bisht et al. (2005) methodology is used for the clear sky portion of the MODIS overpass; while for cloudy portion of the MODIS overpass an extension of Bisht et al. (2005) methodology is applied. The extension of Bisht et al. (2005) methodology utilizes the MODIS cloud data product (MOD06_L2) for cloud top temperature, cloud fraction, cloud emissivity, cloud optical thickness and land surface temperature for cloudy days. The methodology is applied over the Southern Great Plains (SGP) for a time period covering all seasons of 2006. During the MODIS-Terra overpasses in 2006 over the SGP, only 24% of day-overpasses and 9% of night-overpasses had 75% or more of the study region as cloud free. Thus, this proposed study is applicable to a large portion of the MODIS-Terra overpasses. The root mean square errors (RMSE) of instantaneous and daily average net radiation estimated under cloudy conditions using the MOD06_L2 product, comparing to ground-based measurements are 37 W m − 2 and 38 W m − 2 , respectively. The strength of the proposed methodology is that it can rely exclusively on remote sensing data in the absence of ancillary ground observations, thus it has a potential to estimate surface energy budget globally.