Simulations of Cyclone Sidr in the Bay of Bengal with a high-resolution model: sensitivity to large-scale boundary forcing

The predictability of Cyclone Sidr in the Bay of Bengal was explored in terms of track and intensity using the Advanced Research Hurricane Weather Research Forecast (AHW) model. This constitutes the first application of the AHW over an area that lies outside the region of the North Atlantic for which this model was developed and tested. Several experiments were conducted to understand the possible contributing factors that affected Sidr??s intensity and track simulation by varying the initial start time and domain size. Results show that Sidr??s track was strongly controlled by the synoptic flow at the 500-hPa level, seen especially due to the strong mid-latitude westerly over north-central India. A 96-h forecast produced westerly winds over north-central India at the 500-hPa level that were notably weaker; this likely caused the modeled cyclone track to drift from the observed actual track. Reducing the model domain size reduced model error in the synoptic-scale winds at 500?hPa and produced an improved cyclone track. Specifically, the cyclone track appeared to be sensitive to the upstream synoptic flow, and was, therefore, sensitive to the location of the western boundary of the domain. However, cyclone intensity remained largely unaffected by this synoptic wind error at the 500-hPa level. Comparison of the high resolution, moving nested domain with a single coarser resolution domain showed little difference in tracks, but resulted in significantly different intensities. Experiments on the domain size with regard to the total precipitation simulated by the model showed that precipitation patterns and 10-m surface winds were also different. This was mainly due to the mid-latitude westerly flow across the west side of the model domain. The analysis also suggested that the total precipitation pattern and track was unchanged when the domain was extended toward the east, north, and south. Furthermore, this highlights our conclusion that Sidr was influenced from the west side of the domain. The displacement error was significantly reduced after the domain size from the western model boundary was decreased. Study results demonstrate the capability and need of a high-resolution mesoscale modeling framework for simulating the complex interactions that contribute to the formation of tropical cyclones over the Bay of Bengal region.     

Impact of cropping pattern changes on the exploitation of water resources: A remote sensing and GIS approach

A remote sensing-based approach was applied to study the impact of changes in cropping system on the exploitation of water resources in two districts namely Ludhiana in central Punjab and Muktsar in South-Western Punjab. Rice-wheat remained dominant rotation in Ludhiana while cottonwheat rotation was replaced partially by rice-wheat in Muktsar within a span of over five years (1998–99 to 2003–04). The solo rice-wheat system in Ludhiana district has resulted in large-scale ground water exploitation as is evident from the faster decline in water table (up to 0.9m year⁻¹) and higher tube-wells density (440 per 1000 ha). As a result, nearly 60 per cent of the total area of Ludhiana district has the water table depth greater than 10m and in some blocks, it has reached to a depth of 22 m. In Muktsar district, corresponding rise in water table is 0.2m per year and tube well density is 114 per 1000 ha. Irrigation water associated with paddy cultivation in Ludhiana and adjoining areas moves laterally through the buried paleo-channels of Sutlaj in the deeper soil profile and gets accumulated in the basin lands of Muktsar and adjoining areas and causes an extra water flux and subsequent rise in water table, recorded at 3 to 7m depth. To minimize the hydrological imbalance of the state, it is suggested to diversify some of the area in the central districts from irrigation water intensive rice-wheat system to less water intensive cropping system.     

New statistical models for long-range forecasting of southwest monsoon rainfall over India

The India Meteorological Department (IMD) has been issuing long-range forecasts (LRF) based on statistical methods for the southwest monsoon rainfall over India (ISMR) for more than 100 years. Many statistical and dynamical models including the operational models of IMD failed to predict the recent deficient monsoon years of 2002 and 2004. In this paper, we report the improved results of new experimental statistical models developed for LRF of southwest monsoon seasonal (June–September) rainfall. These models were developed to facilitate the IMD’s present two-stage operational forecast strategy. Models based on the ensemble multiple linear regression (EMR) and projection pursuit regression (PPR) techniques were developed to forecast the ISMR. These models used new methods of predictor selection and model development. After carrying out a detailed analysis of various global climate data sets; two predictor sets, each consisting of six predictors were selected. Our model performance was evaluated for the period from 1981 to 2004 by sliding the model training period with a window length of 23 years. The new models showed better performance in their hindcast, compared to the model based on climatology. The Heidke scores for the three category forecasts during the verification period by the first stage models based on EMR and PPR methods were 0.5 and 0.44, respectively, and those of June models were 0.63 and 0.38, respectively. Root mean square error of these models during the verification period (1981–2004) varied between 4.56 and 6.75% from long period average (LPA) as against 10.0% from the LPA of the model based on climatology alone. These models were able to provide correct forecasts of the recent two deficient monsoon rainfall events (2002 and 2004). The experimental forecasts for the 2005 southwest monsoon season based on these models were also found to be accurate.     

Fuzzy Based Approach for Moist Deciduous Forest Identification Using MODIS Temporal Data

Fuzzy based soft classification have been used immensely for handling the mixed pixel and hence to extract the single class of interest. The present research attempts to extract the moist deciduous forest from MODIS temporal data using the Possibilistic c-Means (PCM) soft classification approach. Temporal MODIS (7 dates) data were used to identify moist deciduous forest and temporal AWiFS (7 dates) data were used as reference data for testing. The Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Transformed Normalized Difference Vegetation Index (TNDVI) were used to generate the temporal vegetation indices for both the MODIS and the AWiFS datasets. It was observed from the research that the MODIS temporal NDVI data set1, which contain the minimum number of images and avoids the temporal images corresponding to the highest frequency stages of onset of greenness (OG) and end of senescence (ES) activity of moist deciduous forest have been found most suitable data set for identification of moist deciduous forest with the maximum fuzzy overall accuracy of 96.731 %.     

Recession of samudra tapu glacier, chandra river basin, Himachal Pradesh

Himalayas possess one of the largest resources of snow, ice and glaciers that act as a huge freshwater reservoir. Monitoring the glaciers is important to assess the overall reservoir health of the Himalayas. Samudra Tapu is one of the largest glaciers in Chandra basin of district Lahaul and Spiti, Himachal Pradesh. Based on the field investigations and the remote sensing techniques. features such as accumulation area, ablation area snowline/equilibrium line, moraine-dammed lakes and permanent snowfields were mapped. The glacial terminus was identified using moraine-dammed lake, as lake is located at down streamside of the terminus. The total recession of glacier during the period of 38 years (1962–2000) is about 742 m with an average rate of 19.5 m/yr. In addition, glacial extent is reduced from 73 to 65 km² between 1962 and 2000. suggesting overall deglaciation of 11%. During field investigation. three stages of glaciation using terminal moraine were identified. These moraines were mapped by merging LISS-II1 and PAN data. At the peak of glaciation. the glacial terminus was extended 3.18 km downstream of terminus position in year 2000. Total area during peak of glaciation period has been observed to be 77.67 km², which is 12.67 km² higher than the present glacier extent.     

Frequency response functions for arch dams: Hydrodynamic and foundation flexibility effects

The linear response of a selected arch dam to harmonic upstream, cross-stream or vertical ground motion is presented for a wide range of the important system parameters characterizing the properties of the dam, impounded water, reservoir boundary materials and foundation rock. Based on these frequency response functions, the hydrodynamic and foundation flexibility effects in the dynamic response of arch dams are investigated.