No abstract

The overexploitation and misuse of natural resources in oaseshave put a significant strain on the ecosystem’s fragility. Therefore, a rigorous study of the ecological environment’s quality is required to assure the sustainability of oasis growth. The GEE platform has the features of timeliness and large data cloud processing, which accelerating the development of the remote sensing ecological index. The MODIS data of the research region from 2000 to 2020 were uploaded online to the GEE platform in order to calculate the humidity, greenness, dryness, and heat indices for each year. Principal component analysis was then used to develop the remote sensing ecological index after normalization. In addition, Pearson correlation coefficient, Moran’s I index, geo-detector, and the MK trend test were employed to determine the dependability of the RSEI comprehensive index, analyze the ecological environment status and its change trend in the Aksu River Basin from 2000 to 2020, and investigate the external driving factors of RSEI spatial heterogeneity. (1) The average correlation degree of RSEI is as high as 0.820, and the Moran’s I index is larger than 0.9118; thus, its practicability, dependability, and spatial rationality are enhanced. (2) The natural environment quality of Aksu basin is impacted in two ways by human influences. (1) The adoption of ecological protection measures to support the growth of groundwater reserves in the Aksu basin, increase plant covering, and so improve and enhance the ecological environment’s quality. Following the adoption of ecological protection measures, the average RSEI rose by 12.89%, the ecological quality of the farmland-based region improved considerably, and the quality of the ecological environment was enhanced. (2) Urban growth inhibits environmental progress. The acceleration of urbanization and the large rise in NDBSI have exerted pressure on the development of RSEI, while the growth of cities and towns has decreased the vegetation cover in urban areas and impeded the improvement of ecological environment quality. (3) Both human and environmental causes contribute to the regional variability of RSEI in Aksu Basin. The geographical heterogeneity is mostly caused by temperature and land use, with land use being the most important driver. Strengthening research on the connection between groundwater storage change, land use, vegetation cover, and NDBSI may facilitate the growth of regional green economies.

Abstract:In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regional cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. The cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.

Multiyear (2002-2011) wind observations from TIMED Doppler Interferometer (TIDI) onboard the thermosphere ionosphere mesosphere energetics and dynamics (TIMED) satellite are used for studying the typical structures and variations of mesospheric and lower thermospheric (MLT) mean zonal wind from 80 to 105 km in 120 °E meridian. Comparisons between TIDI measurements and empirical models indicate that TIDI is in good agreement with models in the extratropic regions especially in the middle and high latitudes, but significant differences occur mainly in the tropic regions. In the altitudes of TIDI's coverage from 80 to 105 km, monthly zonal winds are always westward over the tropical regions, forming an easterly band centered at the equator. Results from multiyear observations show complicated variations in the MLT tropical easterlies. The averaged width of easterlies is 37.5 degrees and corresponding variation is about 14 degrees.