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- Author or Editor: Hamid Norouzi x
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Abstract
Diurnal variations of land surface temperature (LST) play a vital role in a wide range of applications such as climate change assessment, land–atmosphere interactions, and heat-related health issues in urban regions. This study uses 15 years (2003–17) of daily observations of LST Collection 6 from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Aqua and the Terra satellites. A spline interpolation method is used to estimate half-hourly global LST from the MODIS measurements. A preliminary assessment of interpolated LST with hourly ground-based observations over selected stations of North America shows bias and an error of less than 1 K. Results suggest that the present interpolation method is capable of capturing the diurnal variations of LST reasonably well for different land-cover types. The diurnal cycle of LST and time of occurrence of maximum temperature are computed from the spatially and temporally consistent interpolated diurnal LST data at a global scale. Regions with higher variability in the timing of maximum LST hours and diurnal amplitude are identified in this study. The global desert regions show generally small variability of the monthly mean diurnal LST range, whereas larger areas of the global land exhibit rather higher variability in the diurnal LST range during the study period. Moreover, the changes in diurnal temperature range for the study period are examined for distinct land-cover types. Analysis of the 15-yr time series of the diurnal LST record shows an overall decrease of 0.5 K in amplitude over the Northern Hemisphere. However, the diurnal LST range shows variant changes in the Southern Hemisphere.
Abstract
Diurnal variations of land surface temperature (LST) play a vital role in a wide range of applications such as climate change assessment, land–atmosphere interactions, and heat-related health issues in urban regions. This study uses 15 years (2003–17) of daily observations of LST Collection 6 from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Aqua and the Terra satellites. A spline interpolation method is used to estimate half-hourly global LST from the MODIS measurements. A preliminary assessment of interpolated LST with hourly ground-based observations over selected stations of North America shows bias and an error of less than 1 K. Results suggest that the present interpolation method is capable of capturing the diurnal variations of LST reasonably well for different land-cover types. The diurnal cycle of LST and time of occurrence of maximum temperature are computed from the spatially and temporally consistent interpolated diurnal LST data at a global scale. Regions with higher variability in the timing of maximum LST hours and diurnal amplitude are identified in this study. The global desert regions show generally small variability of the monthly mean diurnal LST range, whereas larger areas of the global land exhibit rather higher variability in the diurnal LST range during the study period. Moreover, the changes in diurnal temperature range for the study period are examined for distinct land-cover types. Analysis of the 15-yr time series of the diurnal LST record shows an overall decrease of 0.5 K in amplitude over the Northern Hemisphere. However, the diurnal LST range shows variant changes in the Southern Hemisphere.
ABSTRACT
Most previous studies of extreme temperatures have primarily focused on atmospheric temperatures. Using 18 years of the latest version of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data, we globally investigate the spatial patterns of hot and cold extremes as well as diurnal temperature range (DTR). We show that the world’s highest LST of 80.8°C, observed in the Lut Desert in Iran and the Sonoran Desert in Mexico, is over 10°C above the previous global record of 70.7°C observed in 2005. The coldest place on Earth is Antarctica with the record low temperature of −110.9°C. The world’s maximum DTR of 81.8°C is observed in a desert environment in China. We see strong latitudinal patterns in hot and cold extremes as well as DTR. Biomes worldwide are faced with different levels of temperature extremes and DTR: we observe the highest zonal average maximum LST of 61.1° ± 5.3°C in the deserts and xeric shrublands; the lowest zonal average minimum LST of −66.6° ± 14.8°C in the tundra; and the highest zonal average maximum DTR of 43.5° ± 9.9°C in the montane grasslands and shrublands. This global exploration of extreme LST and DTR across different biomes sheds light on the type of extremes different ecosystems are faced with.
ABSTRACT
Most previous studies of extreme temperatures have primarily focused on atmospheric temperatures. Using 18 years of the latest version of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data, we globally investigate the spatial patterns of hot and cold extremes as well as diurnal temperature range (DTR). We show that the world’s highest LST of 80.8°C, observed in the Lut Desert in Iran and the Sonoran Desert in Mexico, is over 10°C above the previous global record of 70.7°C observed in 2005. The coldest place on Earth is Antarctica with the record low temperature of −110.9°C. The world’s maximum DTR of 81.8°C is observed in a desert environment in China. We see strong latitudinal patterns in hot and cold extremes as well as DTR. Biomes worldwide are faced with different levels of temperature extremes and DTR: we observe the highest zonal average maximum LST of 61.1° ± 5.3°C in the deserts and xeric shrublands; the lowest zonal average minimum LST of −66.6° ± 14.8°C in the tundra; and the highest zonal average maximum DTR of 43.5° ± 9.9°C in the montane grasslands and shrublands. This global exploration of extreme LST and DTR across different biomes sheds light on the type of extremes different ecosystems are faced with.
Abstract
Accurate estimation of passive microwave land surface emissivity (LSE) is crucial for numerical weather prediction model data assimilation, for microwave retrievals of land precipitation and atmospheric profiles, and for a better understanding of land surface and subsurface characteristics. In this study, global instantaneous LSE is estimated for a 9-yr period from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and for a 5-yr period from the Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors. Estimates of LSE from both sensors were obtained by using an updated algorithm that minimizes the discrepancy between the differences in penetration depths from microwave and infrared remote sensing observations. Concurrent ancillary datasets such as skin temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) and profiles of air temperature and humidity from the Atmospheric Infrared Sounder are used. The latest collection 6 of MODIS skin temperature is used for the LSE estimation, and the differences between collections 6 and 5 are also comprehensively assessed. Analyses reveal that the differences between these two versions of infrared-based skin temperatures could lead to approximately a 0.015 difference in passive microwave LSE values, especially in arid regions. The comparison of global mean LSE features from the combined use of AMSR-E and AMSR2 with an independent product—Tool to Estimate Land Surface Emissivity from Microwave to Submillimeter Waves (TELSEM2)—shows spatial pattern correlations of order 0.92 at all frequencies. However, there are considerable differences in magnitude between these two LSE estimates, possibly because of differences in incidence angles, frequencies, observation times, and ancillary datasets.
Abstract
Accurate estimation of passive microwave land surface emissivity (LSE) is crucial for numerical weather prediction model data assimilation, for microwave retrievals of land precipitation and atmospheric profiles, and for a better understanding of land surface and subsurface characteristics. In this study, global instantaneous LSE is estimated for a 9-yr period from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and for a 5-yr period from the Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors. Estimates of LSE from both sensors were obtained by using an updated algorithm that minimizes the discrepancy between the differences in penetration depths from microwave and infrared remote sensing observations. Concurrent ancillary datasets such as skin temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) and profiles of air temperature and humidity from the Atmospheric Infrared Sounder are used. The latest collection 6 of MODIS skin temperature is used for the LSE estimation, and the differences between collections 6 and 5 are also comprehensively assessed. Analyses reveal that the differences between these two versions of infrared-based skin temperatures could lead to approximately a 0.015 difference in passive microwave LSE values, especially in arid regions. The comparison of global mean LSE features from the combined use of AMSR-E and AMSR2 with an independent product—Tool to Estimate Land Surface Emissivity from Microwave to Submillimeter Waves (TELSEM2)—shows spatial pattern correlations of order 0.92 at all frequencies. However, there are considerable differences in magnitude between these two LSE estimates, possibly because of differences in incidence angles, frequencies, observation times, and ancillary datasets.
