A P Dimri
Articles written in Journal of Earth System Science
Volume 121 Issue 2 April 2012 pp 329-344
Wintertime regional climate studies over the western Himalayas with ICTP-RegCM3 simulations through 22 years has shown systematic biases in precipitation and temperature fields. The model simulated precipitation shows systematically wet bias. In surface temperature simulations, positive and negative biases of 2°–4°C occurred. Experiment without (CONT) and with subBATS (SUB) shows that later scheme performs better, especially for precipitation. Apart from the role of topography and model internal variability, land surface characteristics also have profound impact on these climatic variables. Therefore, in the present study, impacts of land surface characteristics are investigated through cool/wet and warm/dry winter climate by CONT and SUB simulations to assess systematic biases. Since SUB experiment uses detailed land-use classification, systematic positive biases in temperature over higher elevation peaks are markedly reduced. The change has shown reduced excessive precipitation as well. Most of the surface characteristics show that major interplay between topography and western disturbances (WDs) takes place along the foothills rather than over the higher peaks of the western Himalayas.
Volume 121 Issue 4 August 2012 pp 963-973
During winter months (December, January, February – DJF), the western Himalayas (WH) receive precipitation from eastward moving extratropical cyclones, called western disturbances (WDs) in Indian parlance. Winter precipitation–moisture convergence–evaporation (P–C–E) cycle is analyzed for a period of 22 years (1981–2002: 1980(D)–1981(J, F) to 2001(D)–2002(J, F)) with observed and modelled (RegCM3) climatological estimates over WH. Remarkable model skills have been observed in depicting the hydrological cycle over WH. Although precipitation biases exist, similar spatial precipitation with well marked two maxima is simulated by the model. As season advances, temporal distribution shows higher precipitation in simulation than the observed. However, P–C–E cycle shows similar peaks of moisture convergence and evaporation in daily climatologies though with varying maxima/minima. In the first half of winter, evaporation over WH is mainly driven by ground surface and 2 m air temperature. Lowest temperatures during mid-winter correspond to lowest evaporation to precipitation ratio as well.
Volume 123 Issue 5 July 2014 pp 1147-1169
The temporal and spatial variability of the various meteorological parameters over India and its different subregions is high. The Indian subcontinent is surrounded by the complex Himalayan topography in north and the vast oceans in the east, west and south. Such distributions have dominant influence over its climate and thus make the study more complex and challenging. In the present study, the climatology and interannual variability of basic meteorological fields over India and its six homogeneous monsoon subregions (as defined by Indian Institute of Tropical Meteorology (IITM) for all the four meteorological seasons) are analysed using the Regional Climate Model Version 3 (RegCM3). A 22-year (1980–2001) simulation with RegCM3 is carried out to develop such understanding. The National Centre for Environmental Prediction/National Centre for Atmospheric Research, US (NCEP-NCAR) reanalysis 2 (NNRP2) is used as the initial and lateral boundary conditions. The main seasonal features and their variability are represented in model simulation. The temporal variation of precipitation, i.e., the mean annual cycle, is captured over complete India and its homogenous monsoon subregions. The model captured the contribution of seasonal precipitation to the total annual precipitation over India. The model showed variation in the precipitation contribution for some subregions to the total and seasonal precipitation over India. The correlation coefficient (CC) and difference between the coefficient of variation between model fields and the corresponding observations in percentage (COV) is calculated and compared. In most of the cases, the model could represent the magnitude but not the variability. The model processes are found to be more important than in the corresponding observations defining the variability. The model performs quite well over India in capturing the climatology and the meteorological process. The model shows good skills over the relevant subregions during a season.
Volume 124 Issue 7 October 2015 pp 1545-1561
A recent heavy precipitation event on 13 September 2012 and the associated landslide on 14 September 2012 is one of the most severe calamities that occurred over the Rudraprayag region in Uttarakhand, India. This heavy precipitation event is also emblematic of the natural hazards occuring in the Himalayan region. Study objectives are to present dynamical fields associated with this event, and understand the processes related to the severe storm event, using the Weather Research and Forecasting (WRF ver 3.4) model. A triple-nested WRF model is configured over the Uttarakhand region centered over Ukhimath (30° 30'N; 79° 15'E), where the heavy precipitation event is reported. Model simulation of the intense storm on 13 September 2012 is with parameterized and then with explicit convection are examined for the 3 km grid spacing domain. The event was better simulated without the consideration of convection parameterization for the innermost domain. The role of steep orography forcings is notable in rapid dynamical lifting as revealed by the positive vorticity and high reflectivity values and the intensification of the monsoonal storm. Incursion of moist air, in the lower levels, converges at the foothills of the mountains and rise along the orography to form the updraft zone of the storm. Such rapid unstable ascent leads to deep convection and increases the condensation rate of the water vapour forming clouds at a swift rate. This culminates into high intensity precipitation which leads to high amount of surface runoff over regions of susceptible geomorphology causing the landslide. Even for this intense and potentially unsual rainfall event, the processes involved appear to be the `classic' enhanced convective activity by orographic lifting of the moist air, as an important driver of the event.
Volume 124 Issue 7 October 2015 pp 1563-1572
This paper discusses the variation of dry bulb and dew point temperature (T and Td) on the days with and without thunderstorm (TSD and NTSD) over Bangalore during pre-monsoon season. The thermo-dynamic parameters like convective available potential energy (CAPE), convective inhibition energy (CIN), precipitable water content (PWC) and dynamical parameter vertical wind shear difference (VWS) are studied. The mean profiles of T, Td are generated using March–May upper air data of 1730 hrs IST from 2000–2007 for Bangalore. These are also generated on the TSD and NTSD respectively. It is found that the difference between mean profile of T for TSD/NTSD and seasonal mean is negative/positive till 200 hPa. On the other hand, the difference of the seasonal mean of Td and that of Td on the TSD/NTSD is found to be positive/negative till 300 hPa. These results are found to be significant at 99% confidence. It is found that T is less than the mean at surface till 600 hPa on TSD, whereas it is 0.5° C above average on the NTSD respectively. The difference between the Td on the TSD and mean Td is of the order of 3–5° C till 300 hPa. On the NTSD, this difference ranges between −1 and −2° C in the entire troposphere. The mean values of CAPE, CIN, PWC and VWS for Bangalore in pre-monsoon season are found to be 1324, 49.3 J/kg, 30 mm and −0.0007 s−1, respectively. These parameters were used as predictors for forecasting a thunderstorm. The critical success index and Heidke skill score were used for evaluating the forecast skill of the above parameters for 2 years from 2008 to 2009. CAPE and PWC are able to distinguish a TSD from that of a NTSD with 99% confidence. It is found that these scores are 0.44 and 0.35 for CAPE and 0.49 and 0.53 for precipitable water content.