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Thermal infrared (TIR) data, acquired by instruments on several NASA satellite platforms, are primarily used to estimate the surface temperature/emissivity of the Earth's land surface. One such instrument launched on NASA's Terra satellite in 1999 is the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), which has a spatial resolution of 90 m. Using ASTER data, NASA/Jet Propulsion Laboratory recently released the most detailed emissivity map of the Earth termed the ASTER Global Emissivity Dataset (ASTER GED) that was acquired by processing millions of cloud free ASTER scenes from 2000 to 2008. The ASTER GEDv3 provides an average emissivity at ~100 m and ~1 km, while GEDv4 provides a monthly emissivity from 2000 to 2015 at ~5 km spatial resolution in the wavelength range between 8 and 12 µm. Validation with lab spectra from four desert sites resulted in an average absolute band error of ~1%, compared to current heritage MODIS products that had average absolute errors of 2.4% (Collection 4) and 4.6% (Collection 5).

Remote sensing and GIS are important tools for studying land use/land cover (LULC) change and integrating the associated driving factors for deriving useful outputs. This study is based on utilization of Earth observation datasets over the highly urbanized Allahabad district in India. Allahabad district has experienced intense change in LULC in the last few decades. To monitor the changes, advanced techniques in remote sensing and GIS, such as Cellular Automata (CA)-Markov Chain Model (CAMCM) were used to identify the spatial and temporal changes that have occurred in LULC in this area. Two images, 1990 and 2000, were used for calibration and optimization of the Markovian algorithm, while 2010 was used for validating the predictions of CA-Markov using the ground based land cover image. After validating the model, plausible future LULC changes for 2020 were predicted using the CAMCM. Analysis of the LULC pattern maps, achieved through classification of multitemporal satellite datasets, indicated that the socio-economic and biophysical factors have greatly influenced the growth of agricultural lands and settlements in the area. The two urbanization indicators calculated in this study viz. Land Consumption Ratio (LCR) and Land Absorption Coefficient (LAC) were also used, which indicated a drastic change in the area in terms of urbanization. The predicted LULC scenario for year 2020 provides useful inputs to the LULC planners for effective and pragmatic management of the district and a direction for an effective land use policy making. Further suggestions for an effective policy making are also provided which can be used by government officials to protect this important land resource.

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The study of long-term precipitation record is critically important for a country, whose food security and economy rely on the timely availability of water. In this study, the historical 102-year (1901-2002) rainfall data of the Sindh River basin (SRB), India, were analyzed for seasonal and annual trends. The Mann-Kendall test and Sen's slope model were used to identify the trend and the magnitude of the change, respectively. Spatial interpolation technique such as Kriging was used for interpolating the spatial pattern over SRB in GIS environment. The analysis revealed the significantly increasing precipitation trend in both seasonal and annual rainfall in the span of 102 years.

The Weather Research and Forecasting (WRF) model's Advanced Research WRF (ARW) dynamic solver is one of the most popular regional numerical weather prediction models being used by operational and research personnel. In this study, we simulate a tropical cyclone to reproduce the track direction and strength of the storm that formed at low latitudes in the West Pacific Ocean. The cyclone is known as ''Haiyan'' and assessed as category-5 equivalent super typhoon status due to its strong sustained winds and gusts, making it the strongest tropical cyclone in the region. We study the sensitivity of three different model physics options: the microphysics schemes, the planetary boundary layer schemes, and the impact of cumulus parameterization schemes. The realism of the cyclone simulation for different physics options is assessed through the comparison between the model outputs and the best track data, which are taken from the Japan