Impact of variational assimilation technique on simulation of a heavy rainfall event over Pune,India

Prediction of heavy rainfall events due to severe convective storms in terms of their spatial and temporal scales is a challenging task for an operational forecaster. The present study is about a record-breaking heavy rainfall event observed in Pune (18°31′N, 73°55′E) on October 4, 2010. The day witnessed highest 24-h accumulated precipitation of 181.3 mm and caused flash floods in the city. The WRF model-based real-time weather system, operating daily at Centre for Development of Advanced Computing using PARAM Yuva supercomputer showed the signature of this convective event 4-h before, but failed to capture the actual peak rainfall and its location with reference to the city’s observational network. To investigate further, five numerical experiments were conducted to check the impact of assimilation of observations in the WRF model forecast. First, a control experiment was conducted with initialization using National Centre for Environmental Prediction (NCEP)’s Global Forecast System 0.5° data, while surface observational data from NCEP Prepbufr system were assimilated in the second experiment (VARSFC). In the third experiment (VARAMV), NCEP Prepbufr atmospheric motion vectors were assimilated. Fourth experiment (VARPRO) was assimilated with conventional soundings data, and all the available NCEP Prepbufr observations were assimilated in the fifth experiment (VARALL). Model runs were compared with observations from automated weather stations (AWS), synoptic charts of Indian Meteorological Department (IMD). Comparison of 24-h accumulated rainfall with IMD AWS 24-h gridded data showed that the fifth experiment (VARALL) produced better picture of heavy rainfall, maximum up to 251 mm/day toward the southern side, 31 km away from Pune’s IMD observatory. It was noticed that the effect of soundings observations experiment (VARPRO) caused heavy precipitation of 210 mm toward the southern side 49 km away from Pune. The wind analysis at 850 and 200 hPa indicated that the surface and atmospheric motion vector observations (VARAMV) helped in shifting its peak rainfall toward Pune, IMD observatory by 18 km, though VARALL over-predicted rainfall by 60 mm than the observed.     

Assimilation of Doppler weather radar observations in a mesoscale model for the prediction of rainfall associated with mesoscale convective systems

Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model prediction of convective events. This work is the first attempt in utilizing the India Meteorological Department (IMD) Doppler radar data in a numerical model for the prediction of mesoscale convective complexes around Chennai and Kolkata. Three strong convective events both over Chennai and Kolkata have been considered for the present study. The simulation experiments have been carried out using fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation approach is one of the most promising tools available for directly assimilating the mesoscale observations in order to improve the initial state. The horizontal wind derived from the DWR has been used alongwith other conventional and non-conventional data in the assimilation system. The preliminary results from the three dimensional variational (3DVAR) experiments are encouraging. The simulated rainfall has also been compared with that derived from the Tropical Rainfall Measuring Mission (TRMM) satellite. The encouraging result from this study can be the basis for further investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present study indicates that Doppler radar data assimilation improves the initial field and enhances the Quantitative Precipitation Forecasting (QPF) skill.     

Prediction of monsoon rainfall with a nested grid mesoscale limited area model

At the India Meteorological Department (IMD), New Delhi, a 12-level limited area model with 100 km horizontal resolution has been in use for weather forecasting. The present study uses this model together with a higher horizontal resolution (50 km) and vertical resolution (16-levels) model to examine the impact of increased resolution to simulate mesoscale features of rainfall during monsoon disturbances. The model was run for 22 days in the month of August 1997 and one week in September 1997 during three monsoon depressions and one cyclonic storm in the Bay of Bengal. The model results are compared with observations. The study shows that the model can capture mesoscale convective organization associated with monsoon depression.     

Simulation of a flood producing rainfall event of 29 July 2010 over north-west Pakistan using WRF-ARW model

Simulation of a flood producing rainfall event of 29 July 2010 over north-west Pakistan has been carried out using the Weather Research and Forecasting (WRF) model. This extraordinary rainfall event was localized over north-west Pakistan and recorded 274 mm of rainfall at Peshawar (34.02°N, 71.58°E), within a span of 24 h on that eventful day where monthly July normal rainfall is only 46.1 mm. The WRF model was run with the triple-nested domains of 27, 9, and 3 km horizontal resolution using Kain–Fritsch cumulus parameterization scheme having YSU planetary boundary layer. The model performance was evaluated by examining the different simulated parameters. The model-derived rainfall was compared with Pakistan Meteorological Department–observed rainfall. The model suggested that this flood producing heavy rainfall event over north-west region of Pakistan might be the result of an interaction of active monsoon flow with upper air westerly trough (mid-latitude). The north-west Pakistan was the meeting point of the southeasterly flow from the Bay of Bengal following monsoon trough and southwesterly flow from the Arabian Sea which helped to transport high magnitude of moisture. The vertical profile of the humidity showed that moisture content was reached up to upper troposphere during their mature stage (monsoon system usually did not extent up to that level) like a narrow vertical column where high amounts of rainfall were recorded. The other favourable conditions were strong vertical wind shear, low-level convergence and upper level divergence, and strong vorticity field which demarked the area of heavy rainfall. The WRF model might be able to simulate the flood producing rainfall event over north-west Pakistan and associated dynamical features reasonably well, though there were some spatial and temporal biases in the simulated rainfall pattern.     

On the dynamics of an extreme rainfall event in northern India in 2013

India experienced a heavy rainfall event in the year 2013 over Uttarakhand and its adjoining areas, which was exceptional as it witnessed the fastest monsoon progression. This study aims to explore the causative factors of this heavy rainfall event leading to flood and landslides which claimed huge loss of lives and property. The catastrophic event occurred from 14th to 17th June, 2013 during which the state received 375% more rainfall than the highest rainfall recorded during a normal monsoon season. Using the high resolution precipitation data and complementary parameters, we found that the mid-latitude westerlies shifted southward from its normal position during the intense flooding event. The southward extension of subtropical jet (STJ) over the northern part of India was observed only during the event days and its intensity was found to be increasing from 14th to 16th June. The classical theory of westward tilt of mid-latitude trough with height, which acts to intensify the system through the transfer of potential energy of the mean flow, is evident from analysis of relative vorticity at multiple pressure levels. On analysing the North Atlantic Oscillation (NAO), negative values were observed during the event days. Thus, the decrease in pressure gradient resulted in decrease of the intensity of westerlies which caused the cold air to move southward. During the event, as the cold air moved south, it pushed the mid-latitude westerlies south of its normal position during summer monsoon and created a conducive atmosphere for the intensification of the system.     

Synoptic conditions and potential causes of the extreme heavy rainfall event of January 2009 over Mindanao Island,Philippines

Natural Hazards - This study investigates the synoptic conditions that led to the heavy rainfall/flood (HRF) event in Mindanao Island, Philippines (122??127°E;...     

Planetary boundary layer over monsoon trough region in a high resolution primitive equation model

Numerical experiment with improved boundary layer physics has been performed to study the Planetary Boundary Layer (PBL) characteristics over the monsoon trough region. Details of the evolution and structure of the associated boundary layer processes in the monsoon trough and adjoining oceanic regions are examined by integrating the model up to a period of 48 hours. The model used for this study is a high resolution primitive equation, one with 0·5^o latitude/longitude horizontal resolution and 16 levels in the vertical (7 levels in the PBL). The boundary layer treatment in the model is based on the Monin-Obukhov similarity theory for the surface layer and Turbulent Kinetic Energy (TKE) formulation based onE-ε approach for the mixed layer. The model is integrated using the FGGE level IIIb analysis of European Centre for Medium Range Weather Forecasts (ECMWF), U.K. The study shows that the diurnal variation of TKE over land is a dominant feature comparing with that over the ocean. Along the monsoon trough region, TKE increases from the eastern end to the western side which is mainly associated with the enhancement of sensible heat flux as we move from the eastern wet land to the western desert sector. It may be noted that the low level wind maximum, which is a characteristic feature over the monsoon region, is well simulated by this improved model physics.     

Expected peak ground acceleration in Uttarakhand Himalaya,India region from a deterministic hazard model

A method of seismic zonation based on the deterministic modeling of rupture planes is presented. Finite rupture planes along identified lineaments are modeled in the Uttarakhand Himalaya based on the semi empirical technique of Midorikawa (Tectonophysics 218:287–295, 1993). The expected peak ground acceleration thus estimated from this technique is divided into different zones similar to zones proposed by the Bureau of Indian standard, BIS (Indian standards code of practice for earthquake-resistant design of structures, 2002). The proposed technique has been applied to Kumaon Himalaya area and the surrounding region for earthquakes of magnitude M > 6.0. Approximately 56000 km² study area is classified into the highest hazard zone V with peak accelerations of more than 400 cm/s². This zone V includes the cities of the Dharchula, Almora, Nainital, Haridwar, Okhimath, Uttarkashi, Pithorahargh, Lohaghat, Munsiari, Rudraprayag, and Karnprayag. The Sobla and Gopeshwar regions belong to zone IV, where peak ground accelerations of the order from 250 to 400 cm/s² can be expected. The prepared map shows that epicenters of many past earthquakes in this region lie in zone V, and hence indicating the utility of developed map in defining various seismic zones.     

Numerical simulation of cloud burst event on August 05, 2010, over Leh using WRF mesoscale model

Localized deep cumulus convective clouds have a capability of giving enormous amount of rainfall over a limited horizontal area, within a short span of time. Such types of extreme rainfall events are most common over the high elevated areas of Northern India during the Southwest monsoon season which causes widespread damage to the property and lives. Therefore, it is necessary to predict such extreme events accurately to avoid damage associated with them. The numerical mesoscale model Weather Research and Forecasting has been used to simulate the cloud burst event of Leh on August 05, 2010, so as to capture the main characteristics of the various parameters associated with this localized mesoscale phenomenon. The model has been integrated with four nested domains keeping Leh and its adjoining area as center. Two cloud microphysics parameterization schemes namely WSM3 and WSM6 have been used for the sensitivity experiments and results have been analyzed to examine the performance of both the schemes in capturing such extreme localized heavy rainfall events. Results show that the WSM6 microphysics was able to simulate the precipitation near to the observation. WSM3 microphysics simulated the location of the circulation near to the observation. In addition, the results also show that the maximum magnitudes of meridional and vertical wind as simulated with WSM3 microphysics are 12 and 4 m/s, respectively.     

Impact of monsoon rainfall on the total foodgrain yield over India

The study focuses on understanding the variations of precipitation during summer monsoon season and its impact on Kharif and Rabi foodgrain yield over India. Total foodgrain yield over India during Kharif (summer) season is directly affected by variations in the summer monsoon precipitation (June–September). An increase (decrease) in rainfall is generally associated with an increase (decrease) in foodgrain yield. A similar correspondence during the Rabi (winter) foodgrain yield is not evident. The Rabi crop is not directly affected by variations in the post-monsoon precipitation (October–December) alone, also the summer season precipitation influences the Rabi crop through water and soil moisture availability over many parts of India. Though the reduction of rainfall activity during the entire summer monsoon season leads to reduction in crop yields, the occurrence of prolonged rainfall breaks also causes adverse effect on the crop growth resulting in reduced crop yields.     

The effect of a surface data assimilation technique and the traditional four-dimensional data assimilation on the simulation of a monsoon depression over India using a mesoscale model

The objective of this study is to investigate the impact of a surface data assimilation (SDA) technique, together with the traditional four-dimensional data assimilation (FDDA), on the simulation of a monsoon depression that formed over India during the field phase of the 1999 Bay of Bengal Monsoon Experiment (BOBMEX). The SDA uses the analyzed surface data to continuously assimilate the surface layer temperature as well as the water vapor mixing ratio in the mesoscale model. The depression for the greater part of this study was offshore and since successful application of the SDA would require surface information, a method of estimating surface temperature and surface humidity using NOAA-TOVS satellites was used. Three sets of numerical experiments were performed using a coupled mesoscale model. The first set, called CONTROL, uses the NCEP (National Center for Environmental Prediction) reanalysis for the initial and lateral boundary conditions in the MM5 simulation. The second and the third sets implemented the SDA of temperature and moisture together with the traditional FDDA scheme available in the MM5 model. The second set of MM5 simulation implemented the SDA scheme only over the land areas, and the third set extended the SDA technique over land as well as sea. Both the second and third sets of the MM5 simulation used the NOAA-TOVS and QuikSCAT satellite and conventional upper air and surface meteorological data to provide an improved analysis. The results of the three sets of MM5 simulations are compared with one another and with the analysis and the BOBMEX 1999 buoy, ship, and radiosonde observations. The predicted sea level pressure of both the model runs with assimilation resembles the analysis closely and also captures the large-scale structure of the monsoon depression well. The central sea level pressures of the depression for both the model runs with assimilation were 2–4 hPa lower than the CONTROL. The results of both the model runs with assimilation indicate a larger spatial area as well as increased rainfall amounts over the coastal regions after landfall compared with the CONTROL. The impact of FDDA and SDA, the latter over land, resulted in reduced errors of the following: 1.45 K in temperature, 0.39 m s⁻¹ in wind speed, and 14° in wind direction compared with the BOBMEX buoy observation, and 1.43 m s⁻¹ in wind speed, 43° in wind direction, and 0.75% in relative humidity compared with the CONTROL. The impact of SDA over land and sea compared with SDA over land only showed a further marginal reduction of errors: 0.23 K in air temperature (BOBMEX buoy) and 1.33 m s⁻¹ in wind speed simulations.     

Reliability of reanalyses products in simulating precipitation and temperature characteristics over India

Various reanalyses have been utilized in numerous climate related researches around the globe, however, there exists considerable biasedness in these products, especially in precipitation and temperature data. The ability of these reanalysis products to simulate the precipitation and temperature patterns is observed to be satisfactory at global scale, while it differs significantly at regional scale, especially over regions of high spatio-temporal heterogeneity such as India. Therefore, it is essential to evaluate the applicability and robustness of reanalyses in climate related research. The annual and seasonal variability in spatio-temporal patterns and trends of precipitation and temperature data, with respect to the IMD gridded data over 34 yrs, are evaluated for six global reanalyses namely, NCEP/NCAR Reanalysis (NCEP R1), NCEP-DOE AMIP-2 Reanalysis (NCEP R2), Climate Forecast System Reanalysis (CFSR), ECMWF Interim Reanalysis (ERA-Interim), Modern Era Retrospective Analysis for Research and Application Land only model (MERRA-Land) and JMA 55-year Reanalysis (JRA-55). The ability of the reanalyses was tested based on several factors such as statistical and categorical indices, spells and trends, for annual and seasonal daily values. Several regional and seasonal differences were observed, particularly over high rainfall regions such as Western Ghats and northeastern India. MERRA-Land is found to give the best results for precipitation over India, which is attributed to the updated forcing data using gauge-based precipitation observations. Similarly, ERA-Interim and JRA-55 exhibit better performance for temperature than other datasets. All reanalyses failed to correctly reproduce the trends in IMD data, for both precipitation and temperature. These observations will provide a better perception on the reliability and applicability of reanalyses for climate and hydrological studies over India.     

Sea-breeze-initiated rainfall over the east coast of India during the Indian southwest monsoon

Sea-breeze-initiated convection and precipitation have been investigated along the east coast of India during the Indian southwest monsoon season. Sea-breeze circulation was observed on approximately 70–80% of days during the summer months (June–August) along the Chennai coast. Average sea-breeze wind speeds are greater at rural locations than in the urban region of Chennai. Sea-breeze circulation was shown to be the dominant mechanism initiating rainfall during the Indian southwest monsoon season. Approximately 80% of the total rainfall observed during the southwest monsoon over Chennai is directly related to convection initiated by sea-breeze circulation.     

Numerical investigation of the stability of landslide-affected slopes in Kerala,India, under extreme rainfall event

Natural Hazards - This study examines the stability and failure mechanisms of two landslide-affected slopes in Kerala, India, after an extreme rainfall event. The landslide was triggered by an...     

Simulation of severe thunder storm event: a case study over Pune,India

Numerical simulation of a typical tropical thunder storm event at Pune (18.53°N, 73.85°E), India, has been performed using the three nested domain configuration of Weather Research and Forecasting-Advanced Research Weather Model (version 3.2). The model simulations have been compared with observations. Sensitivity to cumulus parameterization schemes, namely Betts–Miller (BM), Grell–Devenyi (GD), and Kain–Fritsch (KF), for simulation of vertical structure and time evolution of weather parameters has been evaluated using observations from automatic weather station and global positioning system radiosonde ascents. Comparison of spatial distribution of 24-h accumulated rain with Tropical Rainfall Measuring Mission data shows that BM scheme could simulate better rain than GD and KF schemes. The BM scheme could well simulate the development of storm and heavy rain as it could generate sufficiently humid and deep layer in the lower and middle atmosphere, along with co-existence of updrafts and downdrafts and frozen hydrometeors at the middle level and rain water near the surface.