Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores

The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5A degrees x 2.5A degrees grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO - June to October), non-monsoon season (JFMAMND - January to May, November, December) and for the entire year (''Annual''). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5A degrees grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.

Investigation of orographic features influencing spatial distribution of rainfall over the Western Ghats of India using satellite data

Using remotely sensed Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall and topographic data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM), the impact of oroghraphical aspects such as topography, spatial variability of elevation and altitude of apexes are examined to investigate capacious summer monsoon rainfall over the Western Ghats (WG) of India. TRMM 3B42 v7 rainfall data is validated with Indian Meteorological Department (IMD) gridded rainfall data at 0.5 degrees resolution over the WG. The analysis of spatial pattern of monsoon rainfall with orography of the WG ascertains that the grade of orographic precipitation depends mainly on topography of the mountain barrier followed by steepness of windward side slope and altitude of the mountain. Longer and broader, i.e. cascaded topography, elevated summits and gradually increasing slopes impel the enhancement in precipitation. Comparing topography of various states of the WG, it has been observed that windward side of Karnataka receives intense rainfall in the WG during summer monsoon. It has been observed that the rainfall is enhanced before the peak of the mountain and confined up to the height about 800m over the WG. In addition to this, the spatial distribution of heavy and very heavy rainfall events in the last 14 years has also been explored. Heavy and very heavy rain events on this hilly terrain are categorized with a threshold of precipitation (R) in the range 150>R>120mmday(-1) and exceeding 150mmday(-1) using probability distribution of TRMM 3B42 v7 rainfall. The areas which are prone to heavy precipitation are identified. The study would help policy makers to manage the hazard scenario and, to improve weather predictions on mountainous terrain of the WG.

Influence of soil pedological properties on termite mound stability

This study investigated the influence of soil properties on the density and shape of epigeous fungus-growing termite nests in a dry deciduous forest in Karnataka, India. In this environment, Odontotermes obesus produces cathedral shaped mounds. Their density, shape (height and volume) and soil physicochemical properties were analyzed in ferralsol and vertisol environments. No significant difference was observed in O. obesus mound density (n = 2.7 mound ha(-1) on average in the vertisol and ferralsol areas). This study also showed that O. obesus has a limited effect on soil physical properties. No differences in soil particle size, pH, or the C:N ratio and base saturation were measured whereas the C and N contents were reduced and CEC was higher in termite nest soils in both environments. Clay mineralogical composition was also measured, and showed the presence of higher amounts of smectite clays in termite nest soils, which thus explained the increasing CEC despite the reduced C and N content. However, the main difference was the shape of the termite mounds. The degradation of the nests created a hillock of eroded soil at the base of termite mounds in the vertisol while only a thin layer of eroded soil was observed in the ferralsol. The increased degradation of termite mounds in the vertisol is explained by the presence of smectites (2:1 swelling clays), which confer macroscopic swelling and shrinking characteristics to the soil. Soil shrinkage during the dry season leads to the formation of deep cracks in the termite mounds that allow rain to rapidly penetrate inside the mound wall and then breakdown unstable aggregates. In conclusion, it appears that despite a similar abundance, termite mound properties depend to a large extent on the soil properties of their environments. (C) 2015 Elsevier B.V. All rights reserved.

A low-power, low-cost soil-moisture sensor using dual-probe heat-pulse technique

This paper presents the development and testing of an integrated low-power and low-cost dual-probe heat-pulse (DPHP) soil-moisture sensor in view of the electrical power consumed and affordability in developing countries. A DPHP sensor has two probes: a heater and a temperature sensor probe spaced 3 mm apart from the heater probe. Supply voltage of 3.3V is given to the heater-coil having resistance of 33 Omega power consumption of 330 mW, which is among the lowest in this category of sensors. The heater probe is 40 mm long with 2 mm diameter and hence is stiff enough to be inserted into the soil. The parametric finite element simulation study was performed to ensure that the maximum temperature rise is between 1 degrees C and 5 degrees C for wet and dry soils, respectively. The discrepancy between the simulation and experiment is less than 3.2%. The sensor was validated with white clay and tested with red soil samples to detect volumetric water-content ranging from 0% to 30%. The sensor element is integrated with low-power electronics for amplifying the output from thermocouple sensor and TelosB mote for wireless communication. A 3.7V lithium ion battery with capacity of 1150 mAh is used to power the system. The battery is charged by a 6V and 300 mA solar cell array. Readings were taken in 30 min intervals. The life-time of DPHP sensor node is around 3.6 days. The sensor, encased in 30 mm x 20 mm x 10 mm sized box, and integrated with electronics was tested independently in two separate laboratories for validating as well as investigating the dependence of the measurement of soil-moisture on the density of the soil. The difference in the readings while repeating the experiments was found out to be less than 0.01%. Furthermore, the effect of ambient temperature on the measurement of soil-moisture is studied experimentally and computationally. (C) 2015 Elsevier B.V. All rights reserved.

Vegetation structure and composition of tropical evergreen and deciduous forests in Uttara Kannada District, Western Ghats under different disturbance regimes

In the present paper, we present the structure and composition of tropical evergreen and deciduous forests in the Western Ghats monitored under a long-term programme involving Indian Institute of Science, Earthwatch and volunteer investigators from HSBC. Currently, there is limited evidence on the status and dynamics of tropical forests in the context of human disturbance and climate change. Observations made in this study show that the `more disturbed' evergreen and one of the deciduous plots have low species diversity compared to the less-disturbed forests. There are also variations in the size class structure in the more and `less disturbed' forests of all the locations. The variation is particularly noticeable in the DBH size class 10 - 15 cm category. When biomass stock estimates are considered, there was no significant difference between evergreen and deciduous forests. The difference in biomass stocks between `less disturbed' and `more disturbed' forests within a forest type is also low. Thus, the biomass and carbon stock has not been impacted despite the dependence of communities on the forests. Periodic and long-term monitoring of the status and dynamics of the forests is necessary in the context of potential increased human pressure and climate change. There is, therefore, a need to inform the communities of the impact of extraction and its effect on regeneration so as to motivate them to adopt what may be termed as ``adaptive resource management'', so as to sustain the flow of forest products.

Moduli of equivariant sheaves and Kronecker-McKay modules

We extend Alvarez-Consul and King description of moduli of sheaves over projective schemes to moduli of equivariant sheaves over projective Gamma-schemes, for a finite group Gamma. We introduce the notion of Kronecker-McKay modules and construct the moduli of equivariant sheaves using a natural functor from the category of equivariant sheaves to the category of Kronecker-McKay modules. Following Alvarez-Consul and King, we also study theta functions and homogeneous co-ordinates of moduli of equivariant sheaves.

Comprehensive evaluation of multisatellite precipitation estimates over India using gridded rainfall data

This study presents a comprehensive evaluation of five widely used multisatellite precipitation estimates (MPEs) against 1 degrees x 1 degrees gridded rain gauge data set as ground truth over India. One decade observations are used to assess the performance of various MPEs (Climate Prediction Center (CPC)-South Asia data set, CPC Morphing Technique (CMORPH), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks, Tropical Rainfall Measuring Mission's Multisatellite Precipitation Analysis (TMPA-3B42), and Global Precipitation Climatology Project). All MPEs have high detection skills of rain with larger probability of detection (POD) and smaller ``missing'' values. However, the detection sensitivity differs from one product (and also one region) to the other. While the CMORPH has the lowest sensitivity of detecting rain, CPC shows highest sensitivity and often overdetects rain, as evidenced by large POD and false alarm ratio and small missing values. All MPEs show higher rain sensitivity over eastern India than western India. These differential sensitivities are found to alter the biases in rain amount differently. All MPEs show similar spatial patterns of seasonal rain bias and root-mean-square error, but their spatial variability across India is complex and pronounced. The MPEs overestimate the rainfall over the dry regions (northwest and southeast India) and severely underestimate over mountainous regions (west coast and northeast India), whereas the bias is relatively small over the core monsoon zone. Higher occurrence of virga rain due to subcloud evaporation and possible missing of small-scale convective events by gauges over the dry regions are the main reasons for the observed overestimation of rain by MPEs. The decomposed components of total bias show that the major part of overestimation is due to false precipitation. The severe underestimation of rain along the west coast is attributed to the predominant occurrence of shallow rain and underestimation of moderate to heavy rain by MPEs. The decomposed components suggest that the missed precipitation and hit bias are the leading error sources for the total bias along the west coast. All evaluation metrics are found to be nearly equal in two contrasting monsoon seasons (southwest and northeast), indicating that the performance of MPEs does not change with the season, at least over southeast India. Among various MPEs, the performance of TMPA is found to be better than others, as it reproduced most of the spatial variability exhibited by the reference.