New method to estimate surface upwelling long-wave radiation from MODIS cloud-free data.

Area of Science:

• Earth Science
• Atmospheric Science
• Remote Sensing

Background:

• Surface upwelling longwave radiation (SULR) is crucial for the Earth's surface radiation budget and energy exchange.
• Current satellite-derived SULR products lack the resolution and accuracy required for high-resolution numerical models.

Purpose of the Study:

• To develop a precise and efficient method for estimating instantaneous clear-sky SULR using MODIS data.
• To address the limitations of existing SULR products in terms of spatial resolution and accuracy.

Main Methods:

• Introduced an equivalent temperature concept to develop a "split-window" atmospheric correction algorithm.
• Applied the algorithm to MODIS data, utilizing water vapor content (WVC) and thermal channel brightness temperatures.
• Validated the method using ground measurements from the SURFRAD network.

Main Results:

• Achieved root mean square errors (RMSEs) below 13 W/m² for SULR estimates under various conditions.
• Demonstrated high computational efficiency for estimating SULR from MODIS cloud-free data.
• The algorithm is particularly effective with MODIS data when WVC and thermal brightness temperatures are available.

Conclusions:

• The developed "split-window" algorithm offers a feasible and accurate approach for estimating clear-sky SULR from MODIS data.
• This method provides a valuable tool for improving surface radiation budget studies and climate modeling.
• The algorithm's efficiency and accuracy make it suitable for applications requiring high-resolution SULR data.