Impact of satellite soundings on the simulation of heavy rainfall associated with tropical depressions

The present study is carried out to examine the impact of temperature and humidity profiles from moderate resolution imaging spectroradiometer (MODIS) or/and atmospheric infrared sounder (AIRS) on the numerical simulation of heavy rainfall events over the India. The Pennsylvania State University–National Centre for Atmospheric Research fifth-generation mesoscale model (MM5) and its three-dimensional variational (3D-Var) assimilation technique is used for the numerical simulations. The heavy rainfall events occurred during October 26–29, 2005, and October 27–30, 2006, were chosen for the numerical simulations. The results showed that there were large differences observed in the initial meteorological fields from control experiment (CNT; without satellite data) and assimilation experiments (MODIS (assimilating MODIS data), AIRS; (assimilating AIRS data); BOTH (assimilating MODIS and AIRS data together)). The assimilation of satellite data (MODIS, AIRS, and BOTH) improved the predicted thermal and moisture structure of the atmosphere when compared to CNT. Among the experiments, the predicted track of tropical depressions from MODIS was closer to the observed track. Assimilation of MODIS data also showed positive impact on the spatial distribution and intensity of predicted rainfall associated with the depressions. The statistical skill scores obtained for different experiments showed that assimilation of satellite data (MODIS, AIRS, and BOTH) improved the rainfall prediction skill when compared to CNT. Root mean square error in quantitative rainfall prediction is less in the experiment which assimilated MODIS data when compared to other experiments.     

Rainfall analysis for Indian monsoon region using the merged rain gauge observations and satellite estimates: Evaluation of monsoon rainfall features

Objective analysis of daily rainfall at the resolution of 1° grid for the Indian monsoon region has been carried out merging dense land rainfall observations and INSAT derived precipitation estimates. This daily analysis, being based on high dense rain gauge observations was found to be very realistic and able to reproduce detailed features of Indian summer monsoon. The inter-comparison with the observations suggests that the new analysis could distinctly capture characteristic features of the summer monsoon such as north-south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough/low, over the east central parts of the country, over north-east India, along the foothills of Himalayas and over the north Bay of Bengal. When this product was used to assess the quality of other available standard climate products (CMAP and ECMWF reanalysis) at the gird resolution of 2.5°, it was found that the orographic heavy rainfall along Western Ghats of India was poorly identified by them. However, the GPCC analysis (gauge only) at the resolution of 1° grid closely discerns the new analysis. This suggests that there is a need for a higher resolution analysis with adequate rain gauge observations to retain important aspects of the summer monsoon over India. The case studies illustrated show that the daily analysis is able to capture large-scale as well as mesoscale features of monsoon precipitation systems. This study with data of two seasons (2001 and 2003) has shown sufficiently promising results for operational application, particularly for the validation of NWP models.     

Prediction of severe tropical cyclones over the Bay of Bengal during 2007–2010 using high-resolution mesoscale model

In this paper, the performance of a high-resolution mesoscale model for the prediction of severe tropical cyclones over the Bay of Bengal during 2007?C2010 (Sidr, Nargis, Aila, and Laila) is discussed. The advanced Weather Research Forecast (WRF) modeling system (ARW core) is used with a combination of Yonsei University PBL schemes, Kain-Fritsch cumulus parameterization, and Ferrier cloud microphysics schemes for the simulations. The initial and boundary conditions for the simulations are derived from global operational analysis and forecast products of the National Center for Environmental Prediction-Global Forecast System (NCEP-GFS) available at 1°lon/lat resolution. The simulation results of the extreme weather parameters such as heavy rainfall, strong wind and track of those four severe cyclones, are critically evaluated and discussed by comparing with the Joint Typhoon Warning Center (JTWC) estimated values. The simulations of the cyclones reveal that the cyclone track, intensity, and time of landfall are reasonably well simulated by the model. The mean track error at the time of landfall of the cyclone is 98?km, in which the minimum error was found to be for the cyclone Nargis (22?km) and maximum error for the cyclone Laila (304?km). The landfall time of all the cyclones is also fairly simulated by the model. The distribution and intensity of rainfall are well simulated by the model as well and were comparable with the TRMM estimates.     

陆面过程与天气研究

陆面作为大气运动的下边界,通过动量、热量及物质交换与大气发生复杂的相互作用。陆面过程被认为是影响天气气候的关键过程之一。关于陆面过程对气候的影响已经开展了大量较为深入的研究,相比之下,针对陆面过程对天气的影响研究并没有受到足够的重视。近年来,陆面过程与天气研究也开始受到了越来越多的关注。本文从陆面基本要素、下垫面构成、陆面诱发的局地环流3个方面,回顾了土壤湿度、地形、土地利用、山谷-平原环流等要素和过程对强对流、暴雨、台风、高温热浪等天气事件影响研究的相关进展,以期为今后的研究提供参考。需要指出,尽管此方面的研究已取得了一定进展,但关于陆面过程对天气,尤其是极端(高影响)天气的影响及机制还有待深入研究,进而从陆面过程的角度来理解重要天气形成、发生和发展的机理,从而为数值模式发展和天气预报业务提供更有力的科学支撑。     

Skills of different mesoscale models over Indian region during monsoon season: Forecast errors

Performance of four mesoscale models namely, the MM5, ETA, RSM and WRF, run at NCMRWF for short range weather forecasting has been examined during monsoon-2006. Evaluation is carried out based upon comparisons between observations and day-1 and day-3 forecasts of wind, temperature, specific humidity, geopotential height, rainfall, systematic errors, root mean square errors and specific events like the monsoon depressions.It is very difficult to address the question of which model performs best over the Indian region? An honest answer is ‘none’. Perhaps an ensemble approach would be the best. However, if we must make a final verdict, it can be stated that in general, (i) the WRF is able to produce best All India rainfall prediction compared to observations in the day-1 forecast and, the MM5 is able to produce best All India rainfall forecasts in day-3, but ETA and RSM are able to depict the best distribution of rainfall maxima along the west coast of India, (ii) the MM5 is able to produce least RMSE of wind and geopotential fields at most of the time, and (iii) the RSM is able to produce least errors in the day-1 forecasts of the tracks, while the ETA model produces least errors in the day-3 forecasts.     

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.     

A quick and low-cost technique to identify layers associated with heavy rainfall in sediment archives during the Anthropocene

Long-term records are needed to investigate the impact of extreme events in the current framework of global change. Sedimentary reconstruction with a high resolution remains difficult without conducting expensive, destructive and/or time-consuming analyses. In this study, high resolution CT-scan profiles (0·6 mm resolution) were used to investigate their potential for detecting flood deposits induced by heavy rainfall events. This method was applied to a sediment core dated with fallout radionuclides – covering a 120 year period – collected in a pond draining a small forested catchment (French Massif Central – Central France). Between 1960 and 2017, 28 layers were deposited. Seventy-six percent of these deposits were correlated to the occurrence of heavy rainfall (>50 mm) recorded during one or two consecutive days. The remainder of the deposits detected with the Computer Tomography (CT) scanner (n = 5) were not correlated to weather events. They mainly occurred in response to landscape management operations (for example, afforestation works as a result of the major 1999 storm). This period was indeed characterized by an increase in the delivery of ¹³⁷Cs-enriched sediment, demonstrating a greater topsoil contribution to sediment during major forest management operations. The intensity of detrital layers has significantly decreased throughout time after a major land use change that took place in 1948 and land abandonment. The frequency of heavy rainfall and associated detrital deposits has nevertheless increased by 60% and 75%, respectively, between the years 1960 and 2017. These results outline the potential of CT-scan for reconstructing long-term flood deposits associated with heavy precipitation.     

Variation of coastal atmospheric boundary layer characteristics with convective activity along the west coast of India during the Arabian Sea Monsoon Experiment (ARMEX) 2002

This paper investigates the characteristic features of the coastal atmospheric boundary layer (CABL) along the west coast of India during the south-west monsoon (SWM) 2002. Extensive surface and upper-air findings were obtained during the same period from the Arabian Sea Monsoon Experiment (ARMEX; 15th June to 15th August 2002) 2002. The operational general circulation model (GCM) of the National Centre for Medium Range Weather Forecasting (NCMRWF) was used in this study to see the spatial variation of the CABL during two specific convective episodes that led to heavy rainfall along the west coast of India. The impact of a non-local closure (NLC) scheme employed in the NCMRWF GCM was carried out in simulating the CABL. The same episodes were also simulated using a similar parameterization scheme employed in the high resolution mesoscale modelling system (MM5). The diurnal variation of CABL is better represented from MM5 simulation. Comparing the MM5 simulation with that of the coarser grid NCMRWF GCM, we observed that the NCMRWF GCM underestimates the values of both latent heat flux (LHF) and the coastal atmospheric boundary layer height (CABLH). Results from MM5 therefore indicate that the best way to move forward in addressing the short-comings of coarse grid-scale GCMs is to provide a parameterization of the diurnal effects associated with convection processes.     

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.     

Role of land state in a high resolution mesoscale model for simulating the Uttarakhand heavy rainfall event over India

In 2013, Indian summer monsoon witnessed a very heavy rainfall event (>30 cm/day) over Uttarakhand in north India, claiming more than 5000 lives and property damage worth approximately 40 billion USD. This event was associated with the interaction of two synoptic systems, i.e., intensified subtropical westerly trough over north India and north-westward moving monsoon depression formed over the Bay of Bengal. The event had occurred over highly variable terrain and land surface characteristics. Although global models predicted the large scale event, they failed to predict realistic location, timing, amount, intensity and distribution of rainfall over the region. The goal of this study is to assess the impact of land state conditions in simulating this severe event using a high resolution mesoscale model. The land conditions such as multi-layer soil moisture and soil temperature fields were generated from High Resolution Land Data Assimilation (HRLDAS) modelling system. Two experiments were conducted namely, (1) CNTL (Control, without land data assimilation) and (2) LDAS, with land data assimilation (i.e., with HRLDAS-based soil moisture and temperature fields) using Weather Research and Forecasting (WRF) modelling system. Initial soil moisture correlation and root mean square error for LDAS is 0.73 and 0.05, whereas for CNTL it is 0.63 and 0.053 respectively, with a stronger heat low in LDAS. The differences in wind and moisture transport in LDAS favoured increased moisture transport from Arabian Sea through a convectively unstable region embedded within two low pressure centers over Arabian Sea and Bay of Bengal. The improvement in rainfall is significantly correlated to the persistent generation of potential vorticity (PV) in LDAS. Further, PV tendency analysis confirmed that the increased generation of PV is due to the enhanced horizontal PV advection component rather than the diabatic heating terms due to modified flow fields. These results suggest that, two different synoptic systems merged by the strong interaction of moving PV columns resulted in the strengthening and further amplification of the system over the region in LDAS. This study highlights the importance of better representation of the land surface fields for improved prediction of localized anomalous weather event over India.     

Simulation of Heavy Precipitation Associated with an Intense Western Disturbance over Western Himalayas

Northern India is comprised of complex Himalayan mountain ranges having different altitude and orientations. This highly variable terrain is responsible for complexity of the weather systems passing over the region. During winter season, large amount of precipitation is received in this region due to eastward moving low pressure synoptic weather systems called Western Disturbances (WDs). Such heavy precipitation over the region lead to landslides and trigger avalanches in snow bound regions. This causes heavy damage to properties and human lives and therefore poses a great natural hazard threat. In this study an attempt is made to simulate a heavy precipitation event associated with an intense WD using a state of the art mesoscale model. Some important model simulated fields are compared with verifying analysis. Precipitation and circulation features associated with the intense WD are well simulated by the model. Forecast errors indicate that the high resolution mesoscale model could simulate the weather associated with the WD with reasonable accuracy.     

Simulation of high-impact tropical weather events: comparative analysis of three heavy rainfall events

Episodes of heavy rainfall, although relatively rare, significantly contribute to the hydrological cycle due to the large quantum of rainfall in a short span of time. Accurate simulation of such heavy or extreme rainfall events therefore is an important benchmark for a model. Here, we consider the simulation of three heavy rainfall events (Mumbai, Bangalore and Chennai) that occurred over the Indian monsoon region in different geographical locations and seasons during 2005, using a mesoscale meteorological model, namely MM5V3. Simulations have been carried out at high resolution (2 km) to resolve orographic features and land–ocean gradients over the event locations with a 3-nest, 2-way configuration. The primary objective of this study is to carry out a multi-event, multi-location evaluation of the model configuration for simulating a class of heavy rainfall events and to compare some important meteorological features of the events. Our results have shown that a very high relative humidity, low-level convergence, convective instability in terms of equivalent potential temperature, high vertical velocity, smaller mixing ratio at low level and higher mixing ratio at upper level essentially dominated and sustained the convective dynamics in all the three events. It was also found that the latent heat flux (LHF) dominated coastal events (Mumbai and Chennai) with relatively much higher values compared to sensible heat flux (SHF) throughout the event life cycle. In the case of the Bangalore event, both LHF and SHF are comparable during the event life cycle.     

Impact of climate change on extreme rainfall events and flood risk in India

The occurrence of exceptionally heavy rainfall events and associated flash floods in many areas during recent years motivate us to study long-term changes in extreme rainfall over India. The analysis of the frequency of rainy days, rain days and heavy rainfall days as well as one-day extreme rainfall and return period has been carried out in this study to observe the impact of climate change on extreme rainfall events and flood risk in India. The frequency of heavy rainfall events are decreasing in major parts of central and north India while they are increasing in peninsular, east and north east India. The study tries to bring out some of the interesting findings which are very useful for hydrological planning and disaster managements. Extreme rainfall and flood risk are increasing significantly in the country except some parts of central India.     

不同类型降雨过程中GPS可降水量的特征分析

利用成都地基GPS观测网2007年8月21日～2008年11月30日观测数据,结合地面自动气象站网资料反演GPS大气可降水量(P_WV)。选取夏季暴雨,秋季绵雨和冬季雨雪天气过程分析GPSP_WV在不同类型降雨天气过程中的演变特征及日变化规律。结果表明,发生在不同季节的暴雨对应PWV的演变有所不同,盛夏暴雨发生在P_WV由峰值向波谷变化过程中,夏末的暴雨则出现在由波谷向波峰转变阶段,降雨前GPSP_WV的增减速率可很好地预示其后的暴雨强度。在秋季绵雨中P_WV的连续大幅递增或递减可作为降雨开始或结束的预报依据。GPSP_WV在降雨天气分析及预报中具有重要的指示意义。     

Application of radar wind profiler data in analyzing the process of torrential rains in Urumqi Xinjiang,China

To deeply understand the micro-/mesoscale dynamic characteristics of the torrential rain process in Urumqi and improve the levels of torrential rain monitoring, forecasting and early warning, this paper analyzed the wind profile features and related scientific problems of three typical torrential rain events seen in 2013–2015 in this region. The research results suggested that: (1) Radar wind profiler can record in detail the movement condition of the atmosphere during the process of torrential rains. Carrying out detailed analyses on the wind profile data is conductive to the improvement in monitoring, forecasting and warning to torrential rain event at a single observation station. (2) When Urumqi experiences heavy rain weather, noticeable wind shear is usually observed above the observation station. In the upper air, it is southwest wind, while in the lower air it is northwest wind, which is the typical wind profile pattern for heavy rain events in the Urumqi region. (3) Obvious northwest low-level jet stream is found to go together with precipitation, and the jet is positively correlated with precipitation intensity. The velocity of low-level jet stream greatly impacts the amount and intensity of precipitation. (4) The rainstorm weather phenomena are clearly presented by the time–height chart of radar reflectivity factors. The high reflectivity values correspond positively to the height range of cloud–rain particles as well as the duration and intensity of precipitation, so it can be used as a reference index of precipitation monitoring and early warning. In a word, this research deepens on the recognition to the micro-/mesoscale weather systems during the process of heavy rains in Urumqi. Moreover, it would contribute to the application improvement of wind profiler data in analyzing the heavy rainfalls in this region.     

The simulation of heavy rainfall episode over Mumbai: impact of horizontal resolutions and cumulus parameterization schemes

In this study, the simulation of an extreme weather event like heavy rainfall over Mumbai (India) on July 26, 2005 has been attempted with different horizontal resolutions using the Advanced Research Weather Research Forecast model version 2.0.1 developed at the National Center for Atmospheric Research (NCAR), USA. The study uses the Betts–Miller–Janjic (BMJ) and the Grell–Devenyi ensemble (GDE) cumulus parameterization schemes in single and nested domain configurations. The model performance was evaluated by examining the different predicted parameters like upper and lower level circulations, moisture, temperature, and rainfall. The large-scale circulation features, moisture, and temperature were compared with the National Centers for Environmental Prediction analyses. The rainfall prediction was assessed quantitatively by comparing rainfall from the Tropical Rainfall Measuring Mission products and the observed station values reported in the Indian Daily Weather Reports from India Meteorological Department (IMD). The quantitative validation of the simulated rainfall was done by calculating the categorical skill scores like frequency bias, threat scores (TS), and equitable threat scores (ETS). It is found that in all simulations, both in single and nested domains, the GDE scheme has outperformed the BMJ scheme for the simulation of rainfall for this specific event.     

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.     

Some characteristics of very heavy rainfall over Orissa during summer monsoon season

Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features of very heavy rainfall (24 hours rainfall ≥125 mm) over Orissa during summer monsoon season (June–September) by analysing 20 years (1980–1999) daily rainfall data of different stations in Orissa. The principal objective of this study is to find out the role of synoptic scale monsoon disturbances in spatial and temporal variability of very heavy rainfall over Orissa. Most of the very heavy rainfall events occur in July and August. The region, extending from central part of coastal Orissa in the southeast towards Sambalpur district in the northwest, experiences higher frequency and higher intensity of very heavy rainfall with less interannual variability. It is due to the fact that most of the causative synoptic disturbances like low pressure systems (LPS) develop over northwest (NW) Bay of Bengal with minimum interannual variation and the monsoon trough extends in west-northwesterly direction from the centre of the system. The very heavy rainfall occurs more frequently with less interannual variability on the western side of Eastern Ghat during all the months and the season except September. It occurs more frequently with less interannual variability on the eastern side of Eastern Ghat during September. The NW Bay followed by Gangetic West Bengal/Orissa is the most favourable region of LPS to cause very heavy rainfall over different parts of Orissa except eastern side of Eastern Ghat. The NW Bay and west central (WC) Bay are equally favourable regions of LPS to cause very heavy rainfall over eastern side of Eastern Ghat. The frequency of very heavy rainfall does not show any significant trend in recent years over Orissa except some places in north-east Orissa which exhibit significant rising trend in all the monsoon months and the season as a whole.     

An operational multiscale system for hazards prediction, mapping, and response

By definition, a crisis is a situation that requires assistance to be managed. Hence, response to a crisis involves the merging of local and non-local emergency response personnel. In this situation, it is critical that each participant: (1) know the roles and responsibilities of each of the other participants; (2) know the capabilities of each of the participants; and (3) have a common basis for action. For many types of natural disasters, this entails having a common operational picture of the unfolding events, including detailed information on the weather, both current and forecasted, that may impact on either the emergency itself or on response activities. The Consequences Assessment Tool Set (CATS) is a comprehensive package of hazard prediction models and casualty and damage assessment tools that provides a linkage between a modeled or observed effect and the attendant consequences for populations, infrastructure, and resources, and, hence, provides the common operational picture for emergency response. The Operational Multiscale Environment model with Grid Adaptivity (OMEGA) is an atmospheric simulation system that links the latest methods in computational fluid dynamics and high-resolution gridding technologies with numerical weather prediction to provide specific weather analysis and forecast capability that can be merged into the geographic information system framework of CATS. This paper documents the problem of emergency response as an end-to-end system and presents the integrated CATS–OMEGA system as a prototype of such a system that has been used successfully in a number of different situations.     

Location-specific weather predictions for Sriharikota (13.72°N, 80.22°E) through numerical atmospheric models during satellite launch campaigns

Accurate knowledge of different meteorological parameters over a launch site is very crucial for efficient management of satellite launch operations. Local weather over the Indian satellite launch site located at Sriharikota High Altitude Range (SHAR: 13.72°N, 80.22°E) is very much dependent on the atmospheric circulation prevailing over the Bay of Bengal oceanic region and topography-induced convective activities. With a view to providing severe weather threat prediction in terms of launch commit criteria (LCC), two numerical atmospheric models namely high-resolution regional model (HRM) and advanced regional prediction system (ARPS) are made operational over SHAR in a synoptic and mesoscale domain, respectively. In the present research article, two launch campaigns through Polar Satellite Launch Vehicle (PSLV-C11 and PSLV-C12) when contrasting weather conditions prevailed over the launch site are chosen for demonstration of potential of two models in providing location-specific short-to-medium-range weather predictions meeting the needs of LCC. In the case of PSLV-C11 campaign, when the launch site underwent frequent thundershower-associated rainfall, ARPS model–derived meteorological fields were effectively used in prediction of probability of the wet spells. On the other hand, Bay of Bengal underwent severe cyclonic storm during PSLV-C12 campaign, and its formation was reasonable captured through HRM simulations. It is concluded that a combination of HRM and ARPS provide reliable short-to-medium-range weather prediction over SHAR, which has got profound importance in launch-related activities.