The MODIS cloud mask algorithm uses multiple cloud detection tests to determine the confidence that MODIS is observing clear skies. It is a global, single-pixel resolution product that utilizes up to 14 of MODIS's 36 spectral bands to maximize reliable cloud detection. The algorithm operates in near real time with limited computational resources and is used as an ancillary input for MODIS land, ocean, and atmosphere science algorithms. The MODIS cloud mask identifies several conceptual domains based on surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. Once a pixel is assigned to a domain, a series of threshold tests attempt to detect clouds. Each test returns a confidence level ranging from 1 (high confidence in clear skies) to 0 (low confidence). These tests are grouped to maximize independence, though few are completely independent. The minimum confidence from each group is used to determine the overall confidence in clear-sky conditions. The algorithm combines the results of these tests to determine the confidence of clear-sky conditions. The MODIS cloud mask algorithm is described in detail, including the input and output of the algorithm, the spectral tests used, and the confidence levels assigned. The algorithm uses a combination of spectral and brightness temperature tests to detect clouds, with different tests used for different cloud types. The algorithm also includes tests for detecting thin cirrus, low clouds, and high clouds. The algorithm is designed to provide four levels of confidence: confident clear, probably clear, undecided, and cloudy. The MODIS cloud mask is a 48-bit word for each field of view, with bits indicating various conditions such as day/night, Sun glint, snow/ice, and land/water. The algorithm also includes tests for detecting noncloud obstructions, thin cirrus, shadows, and temporal consistency. The algorithm is validated using existing remote sensing data sets and has been shown to be effective in detecting clouds under various conditions. The MODIS cloud mask algorithm is a key component of the MODIS instrument, providing essential information for land, ocean, and atmosphere science algorithms.The MODIS cloud mask algorithm uses multiple cloud detection tests to determine the confidence that MODIS is observing clear skies. It is a global, single-pixel resolution product that utilizes up to 14 of MODIS's 36 spectral bands to maximize reliable cloud detection. The algorithm operates in near real time with limited computational resources and is used as an ancillary input for MODIS land, ocean, and atmosphere science algorithms. The MODIS cloud mask identifies several conceptual domains based on surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. Once a pixel is assigned to a domain, a series of threshold tests attempt to detect clouds. Each test returns a confidence level ranging from 1 (high confidence in clear skies) to 0 (low confidence). These tests are grouped to maximize independence, though few are completely independent. The minimum confidence from each group is used to determine the overall confidence in clear-sky conditions. The algorithm combines the results of these tests to determine the confidence of clear-sky conditions. The MODIS cloud mask algorithm is described in detail, including the input and output of the algorithm, the spectral tests used, and the confidence levels assigned. The algorithm uses a combination of spectral and brightness temperature tests to detect clouds, with different tests used for different cloud types. The algorithm also includes tests for detecting thin cirrus, low clouds, and high clouds. The algorithm is designed to provide four levels of confidence: confident clear, probably clear, undecided, and cloudy. The MODIS cloud mask is a 48-bit word for each field of view, with bits indicating various conditions such as day/night, Sun glint, snow/ice, and land/water. The algorithm also includes tests for detecting noncloud obstructions, thin cirrus, shadows, and temporal consistency. The algorithm is validated using existing remote sensing data sets and has been shown to be effective in detecting clouds under various conditions. The MODIS cloud mask algorithm is a key component of the MODIS instrument, providing essential information for land, ocean, and atmosphere science algorithms.