Mapping evapotranspiration variability over a complex oasis-desert ecosystem based on automated calibration of Landsat 7 ETM+ data in SEBAL

Fragmented ecosystems of the desiccated Aral Sea seek answers to the profound local hydrologically- and water-related problems. Particularly, in the Small Aral Sea Basin (SASB), these problems are associated with low precipitation, increased temperature, land use and evapotranspiration (ET) changes. Here, the utility of high-resolution satellite dataset is employed to model the growing season dynamic of near-surface fluxes controlled by the advective effects of desert and oasis ecosystems in the SASB. This study adapted and applied the sensible heat flux calibration mechanism of Surface Energy Balance Algorithm for Land (SEBAL) to 16 clear-sky Landsat 7 ETM+ dataset, following a guided automatic pixels search from surface temperature T-s and Normalized Difference Vegetation Index NDVI (). Results were comprehensively validated with flux components and actual ET (ETa) outputs of Eddy Covariance (EC) and Meteorological Station (KZL) observations located in the desert and oasis, respectively. Compared with the original SEBAL, a noteworthy enhancement of flux estimations was achieved as follows: - desert ecosystem ETa R-2 = 0.94; oasis ecosystem ETa R-2 = 0.98 (P < 0.05). The improvement uncovered the exact land use contributions to ETa variability, with average estimates ranging from 1.24 mm to 6.98 mm . Additionally, instantaneous ET to NDVI (ETins-NDVI) ratio indicated that desert and oasis consumptive water use vary significantly with time of the season. This study indicates the possibility of continuous daily ET monitoring with considerable implications for improving water resources decision support over complex data-scarce drylands

The global spatiotemporal distribution of the mid-tropospheric CO2 concentration and analysis of the controlling factors

The atmospheric infrared sounder (AIRS) provides a robust and accurate data source to investigate the variability of mid-tropospheric CO2 globally. In this paper, we use the AIRS CO2 product and other auxiliary data to survey the spatiotemporal distribution characteristics of mid-tropospheric CO2 and the controlling factors using linear regression, empirical orthogonal functions (EOFs), geostatistical analysis, and correlation analysis. The results show that areas with low mid-tropospheric CO2 concentrations (20 degrees S-5 degrees N) (384.2 ppm) are formed as a result of subsidence in the atmosphere, the presence of the Amazon rainforest, and the lack of high CO2 emission areas. The areas with high mid-tropospheric CO2 concentrations (30 degrees N-70 degrees N) (382.1 ppm) are formed due to high CO2 emissions. The global mid-tropospheric CO2 concentrations increased gradually (the annual average rate of increase in CO2 concentration is 2.11 ppm/a), with the highest concentration occurring in spring (384.0 ppm) and the lowest value in winter (382.5 ppm). The amplitude of the seasonal variation retrieved from AIRS (average: 1.38 ppm) is consistent with that of comprehensive observation network for trace gases (CONTRAIL), but smaller than the surface ground stations, which is related to altitude and coverage. These results contribute to a comprehensive understanding of the spatiotemporal distribution of mid-tropospheric CO2 and related mechanisms

The temporal and spatial distributions of the near-surface CO2 concentrations in Central Asia and analysis of their controlling factors

As the main anthropogenic greenhouse gas that contributes most to global warming, CO2 plays an important role in climate changes in Central Asia. Due to the lack of studies of near-surface CO2 in this region, we first confirmed the applicability of the near-surface Greenhouse Gases Observing Satellite (GOSAT) CO2 data in Central Asia using atmospheric CO2 concentration data from nine ground-based station observations. We then analyzed the temporal and spatial distributions of the near-surface CO2 concentrations in Central Asia and their controlling factors using statistical analysis methods. The results show that the near-surface CO2 concentrations are high in the western part of this region and low in the east. From June 2009 to May 2013, the near-surface CO2 concentrations increased gradually, with the highest value being in spring and the lowest in autumn. The temporal distribution of CO2 concentrations is mainly affected by photosynthesis, respiration, and heating. The combined effect of terrestrial ecosystems and CO2 diffusion by wind is responsible for the higher near-surface CO2 concentration in the northern, western, and southwestern areas of the five Central Asian countries compared to the central, eastern, and southern areas, and energy consumption and wind are the major factors that affect the heterogeneity of the spatial distribution of the CO2 concentrations in Xinjiang

Balancing the Tradeoffs between Data Accessibility and Query Delay in Ad Hoc Networks

In mobile ad hoc networks, nodes move freely and link/node failures are common. This leads to frequent network partitions, which may significantly degrade the performance of data access in ad hoc networks. When the network partition occurs, mobile nodes in one network are not able to access data hosted by nodes in other networks. In this paper, we deal with this problem by applying data replication techniques. Existing data replication solutions in both wired or wireless networks aim at either reducing the query delay or improving the data accessibility. As both metrics are important for mobile nodes, we propose schemes to balance the tradeoffs between data accessibility and query delay under different system settings and requirements. Simulation results show that the proposed schemes can achieve a balance between these two metrics and provide satisfying system performance

Supporting Cooperative Caching in Ad Hoc Networks

Most researches in ad hoc networks focus on routing and not much work has been done on data access. A common technique used to improve the performance of data access is caching. Cooperative caching, which allows the sharing and coordination of cached data among multiple nodes, can further explore the potential of the caching techniques. Due to mobility and resource constraints of ad hoc networks, cooperative caching techniques designed for wired networks may not be applicable to ad hoc networks. In this paper, we design and evaluate cooperative caching techniques to efficiently support data access in ad hoc networks. We firs

Supporting Cooperative Caching in Ad Hoc Networks

Most researches in ad hoc networks focus on routing, and not much work has been done on data access. A common technique used to improve the performance of data access is caching. Cooperative caching, which allows the sharing and coordination of cached data among multiple nodes, can further explore the potential of the caching techniques. Due to mobility and resource constraints of ad hoc networks, cooperative caching techniques designed for wired network may not be applicable to ad hoc networks. In this paper, we design and evaluate cooperative caching techniques to efficiently support data access in ad hoc networks. We first propose two schemes: CacheData which caches the data, and CachePath which caches the data path. After analyzing the performance of those two schemes, we propose a hybrid approach (HybridCache) which can further improve the performance by taking advantage of CacheData and CachePath while avoiding their weaknesses. Simulation results show that the proposed schemes can significantly reduce the query delay and message complexity when compared to other caching schemes