Riverine flood assessment in Jhang district in connection with ENSO and summer monsoon rainfall over Upper Indus Basin for 2010

Pakistan has experienced severe floods over the past decades due to climate variability. Among all the floods, the flood of 2010 was the worst in history. This study focuses on the assessment of (1) riverine flooding in the district Jhang (where Jhelum and Chenab rivers join, and the district was severely flood affected) and (2) south Asiatic summer monsoon rainfall patterns and anomalies considering the case of 2010 flood in Pakistan. The land use/cover change has been analyzed by using Landsat TM 30 m resolution satellite imageries for supervised classification, and three instances have been compared, i.e., pre-flooding, flooding, and post-flooding. The water flow accumulation, drainage density and pattern, and river catchment areas have been calculated by using Shutter Radar Topography Mission digital elevation model 90 m resolution. The standard deviation of south Asiatic summer monsoon rainfall patterns, anomalies and normal (1979–2008) has been calculated for July, August, and September by using rainfall data set of Era interim (0.75° × 0.75° resolution). El Niño Southern Oscillation has also been considered for its role in prevailing rainfall anomalies during the year 2010 over Upper Indus Basin region. Results show the considerable changing of land cover during the three instances in the Jhang district and water content in the rivers. Abnormal rainfall patterns over Upper Indus Basin region prevailed during summer monsoon months in the year 2010 and 2011. The El Niño (2009–2010) and its rapid phase transition to La Niña (2011–2012) may be the cause of severity and disturbances in rainfall patterns during the year 2010. The Geographical Information System techniques and model based simulated climate data sets have been used in this study which can be helpful in developing a monitoring tool for flood management.     

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.     

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.     

Meteorological features associated with unprecedented precipitation over India during 1st week of March 2015

Unprecedented precipitation along with heavy falls occurred over many parts of India from 28th February to 2nd March 2015. Many of the stations of northwest and central India received an all time high 24 hr cumulative precipitation of March during this period. Even the national capital, New Delhi, broke all the previous historical 24 hr rainfall records of the last 100 years to the rainfall record in March 2015. Due to this event, huge loss to agricultural and horticultural crops occurred in several parts of India. In the present study, an attempt is made to understand the various meteorological features associated with this unprecedented precipitation event over India. It occurred due to the presence of an intense western disturbance (WD) over Afghanistan and neighbouring areas in the form of north–south oriented deep trough in westerlies in middle and upper tropospheric levels with its southern end deep in the Arabian Sea, which pumped huge moisture feed over Indian region. Also, there was a jet stream with core wind speed up to 160 knots that generated high positive divergence at upper tropospheric level over Indian region; along with this there was high magnitude of negative vertical velocity and velocity convergence were there at middle tropospheric level. It caused intense upward motion and forced lower levels air to rise and strengthen the lower levels cyclonic circulations (CCs)/Lows. Moreover, the induced CCs/Lows at lower tropospheric levels associated with WD were more towards south of its normal position. Additionally, there was wind confluence over central parts of India due to westerlies in association with WD and easterlies from anticyclone over north Bay of Bengal. Thus, intense WD along with wind confluence between westerlies and easterlies caused unprecedented precipitation over India during the 1st week of March 2015.     

Rainfall threshold determination for flash flood warning in mountainous catchments with consideration of antecedent soil moisture and rainfall pattern

Flash flood disaster is a prominent issue threatening public safety and social development throughout the world, especially in mountainous regions. Rainfall threshold is a widely accepted alternative to hydrological forecasting for flash flood warning due to the short response time and limited observations of flash flood events. However, determination of rainfall threshold is still very complicated due to multiple impact factors, particular for antecedent soil moisture and rainfall patterns. In this study, hydrological simulation approach (i.e., China Flash Flood-Hydrological Modeling System: CNFF-HMS) was adopted to capture the flash flood processes. Multiple scenarios were further designed with consideration of antecedent soil moisture and rainfall temporal patterns to determine the possible assemble of rainfall thresholds by driving the CNFF-HMS. Moreover, their effects on rainfall thresholds were investigated. Three mountainous catchments (Zhong, Balisi and Yu villages) in southern China were selected for case study. Results showed that the model performance of CNFF-HMS was very satisfactory for flash flood simulations in all these catchments, especially for multimodal flood events. Specifically, the relative errors of runoff and peak flow were within?±?20%, the error of time to peak flow was within?±?2 h and the Nash–Sutcliffe efficiency was greater than 0.90 for over 90% of the flash flood events. The rainfall thresholds varied between 93 and 334 mm at Zhong village, between 77 and 246 mm at Balisi village and between 111 and 420 mm at Yu village. Both antecedent soil moistures and rainfall temporal pattern significantly affected the variations of rainfall threshold. Rainfall threshold decreased by 8–38 and 0–42% as soil saturation increased from 0.20 to 0.50 and from 0.20 to 0.80, respectively. The effect of rainfall threshold was the minimum for the decreasing hyetograph (advanced pattern) and the maximum for the increasing hyetograph (delayed pattern), while it was similar for the design hyetograph and triangular hyetograph (intermediate patterns). Moreover, rainfall thresholds with short time spans were more suitable for early flood warning, especially in small rural catchments with humid climatic characteristics. This study was expected to provide insights into flash flood disaster forecasting and early warning in mountainous regions, and scientific references for the implementation of flash flood disaster prevention in China.     

On the impacts of ENSO and Indian Ocean dipole events on sub-regional Indian summer monsoon rainfall

The relative impacts of the ENSO and Indian Ocean dipole (IOD) events on Indian summer (June–September) monsoon rainfall at sub-regional scales have been examined in this study. GISST datasets from 1958 to 1998, along with Willmott and Matsuura gridded rainfall data, all India summer monsoon rainfall data, and homogeneous and sub-regional Indian rainfall datasets were used. The spatial distribution of partial correlations between the IOD and summer rainfall over India indicates a significant impact on rainfall along the monsoon trough regions, parts of the southwest coastal regions of India, and also over Pakistan, Afghanistan, and Iran. ENSO events have a wider impact, although opposite in nature over the monsoon trough region to that of IOD events. The ENSO (IOD) index is negatively (positively) correlated (significant at the 95% confidence level from a two-tailed Student t-test) with summer monsoon rainfall over seven (four) of the eight homogeneous rainfall zones of India. During summer, ENSO events also cause drought over northern Sri Lanka, whereas the IOD events cause surplus rainfall in its south. On monthly scales, the ENSO and IOD events have significant impacts on many parts of India. In general, the magnitude of ENSO-related correlations is greater than those related to the IOD. The monthly-stratified IOD variability during each of the months from July to September has a significant impact on Indian summer monsoon rainfall variability over different parts of India, confirming that strong IOD events indeed affect the Indian summer monsoon.

Development of a flood forecasting system using IFAS: a case study of scarcely gauged Jhelum and Chenab river basins

Development of a well-calibrated, distributed hydrological model for flood forecasting based on rainfall and snowmelt is quite challenging, especially when in situ data is limited or unavailable. This paper presents the study carried out to parameterise the Integrated Flood Analysis System (IFAS) model for the trans-boundary, scarcely gauged catchments of Jhelum and Chenab rivers in Pakistan. Rainfall-runoff analysis was performed with a two-layered tank configuration, integrating snowmelt and dam and barrage operation from the very upstream in India to Trimmu Barrage in Pakistan. A grid size of 5?×?5 km was considered. Global map topography, land cover and soil data was utilised. The model was tested considering different magnitudes of floods of the years 2014, 2015 and 2017. The results showed that the satellite rainfall product, i.e. Global Satellite Mapping of Precipitation (GSMaP-NRT), underestimated the rainfall volume, compared to the ground-gauged rainfall. The GSMaP-IF correction method showed poor performance owing to the lack of ground observatory rainfall data for correcting the trans-boundary part of the basin. The GSMaP-Type1 correction method showed good results, except for the confluence point where complex flow conditions were not properly reproduced by the model. In addition, the incorporation of dam and barrages in the model improved the simulated flow results. It is concluded that the satellite rainfall estimates must be corrected to improve the results. Snowmelt module estimated the snowmelt contribution as 3 to 7% and 4 to 23% of the average daily discharge during the monsoon season at Mangla Dam and Marala Barrage, respectively, during 2014 and 2015. This study assessed various correction methods and concluded that the model and methodology used in the study functioned well with suitable precipitation.     

Relationship between atmospheric conditions at Dhaka, Bangladesh, and rainfall at Cherrapunjee, India

To improve flood forecasting, the understanding of the atmospheric conditions associated with severe rainfall is crucial. We analysed the atmospheric conditions at Dhaka, Bangladesh, using upper-air soundings. We then compared these conditions with daily rainfall variations at Cherrapunjee, India, which is a main source of floodwater to Bangladesh, and a representative sample of exceptionally heavy rainfall events. The analysis focussed on June and July 2004. June and July are the heaviest rainfall months of the year at Cherrapunjee. July 2004 had the fourth-heaviest monthly rainfall of the past 31 years, and severe floods occurred in Bangladesh. Active rainfall periods at Cherrapunjee corresponded to “breaks” in the Indian monsoon. The monsoon trough was located over the Himalayan foothills, and strong westerly winds dominated up to 7 km at Dhaka. Near-surface wind below 1 km had southerly components, and the wind profile had an Ekman spiral structure. The results suggest that rainfall at Cherrapunjee strongly depends on the near-surface wind speed and wind direction at Dhaka. Lifting of the near-surface southerly airflow by the Meghalaya Plateau is considered to be the main contributor to severe rainfall at Cherrapunjee. High convective available potential energy (CAPE) also contributes to intense rainfall.     

Trends and extreme value analysis of rainfall pattern over homogeneous monsoon regions of India

Trends of pre-monsoon, monsoon and post-monsoon rainfall pattern were studied on decadal basis over different homogeneous monsoon regions in India for the period 1871–2008. It is attempted to understand the relation of monsoon rainfall with the global teleconnections of El Niño and La Niña, for which the correlation analysis has been carried out with Darwin pressure and Niño 3.4 sea surface temperature (Niño 3.4 SST). The correlation analysis inferred that the significant correlations were observed when monsoon rainfall is related to ENSO indices on decadal scale than on annual ones. The study also found that the north-west region is more affected by the moderate El Niño years compared to strong El Niño years. The regions Central North-East and North-East could not make any difference among weak, moderate and strong La Niña events. The authors also have carried out the extreme value analysis over different homogeneous monsoon regions of India as well as for whole India. The results show that the return values of rainfall are increasing with the return periods for the forthcoming 10, 20, 50 and 100 years. The heterogeneity in number of threshold years that were recorded for the extreme rainfall over north-east (humid climatic type) and north-west (arid climatic type) described the climate variability. The results of the present study may be useful for the policy makers in understanding the rainfall exceedance in different return periods for planning the risk management strategies.     

Field monitoring of groundwater responses to heavy rainfalls and the early warning of the Kualiangzi landslide in Sichuan Basin,southwestern China

The Kualiangzi landslide was triggered by heavy rainfalls in the “red beds” area of Sichuan Basin in southwestern China. Differing from other bedrock landslides, the movement of the Kualiangzi landslide was controlled by the subvertical cracks and a subhorizontal bedding plane (dip angle < 10°). The ingress of rainwater in the cracks formed a unique groundwater environment in the slope. Field measurement for rainfall, groundwater movement, and slope displacement has been made for the Kualiangzi landslide since 2013. The field monitoring system consists of two rainfall gauges, seven piezometers, five water-level gauges, and two GPS data loggers. The equipments are embedded near a longitudinal section of the landslide, where severe deformation has been observed in the past 3 years. The groundwater responses to four heavy rainfall events were analyzed between June 16 and July 24 in 2013 coincided with the flood season in Sichuan. Results showed that both of the water level and the pore-water pressure increased after each rainfall event with delay in the response time with respect to the precipitation. The maximum time lag reached 35 h occurred in a heavy rainfall event with cumulative precipitation of 127 mm; such lag effect was significantly weakened in the subsequent heavy rainfall events. In each presented rainfall event, longer infiltration period in the bedrock in the upper slope increased the response time of groundwater, compared to that of in the gravels in the lower slope. A translational landslide conceptual model was built for the Kualiangzi landslide, and the time lag was attributed to the gradual formation of the uplift pressure on the slip surface and the softening of soils at the slip surface. Another important observation is the effect on the slope movement which was caused by the water level (H _w) in the transverse tension trough developed at the rear edge of the landslide. Significant negative correlation was found for H _w and the slope stability factor (F _s), in particular for the last two heavy rainfall events, of which the drastic increase of water level caused significant deterioration in the slope stability. The rapid drop (Δ?=?22.5 kPa) of pore-water pressure in the deep bedrock within 1 h and the large increase (Δ?=?87.3 mm) of surficial displacement were both monitored in the same period. In the end, a four-level early warning system is established through utilizing H _w and the displacement rate D _r as the warning indicators. When the large deformation occurred in flood season, the habitants at the leading edge of the landslide can be evacuated in time.     

Analysis of soil boundary conditions of flash floods in a small basin in SW Hungary

Flash floods are one of the most significant natural hazards of today. Due to the complexity of flash flood triggering factors, to prevent or mitigate flood triggered losses, numeric model based flood forecasting models are capable tools to predict stream water levels. The main goal of the current research was to reproduce two flow peaks with the HEC-HMS rainfall-runoff model and test the model sensitivity for various input parameters. To obtain sufficient input data, we monitored soil depth, maximum infiltration rate, soil moisture content, rainfall, time of concentration and flow. To obtain input data, parameters were calculated, measured in the Sás Valley experimental watershed (SW Hungary) or optimized with the built in function of the HEC-HMS. Soil moisture was monitored in the 1.7 km2 pilot catchment over the period between September 2008 and September 2009. HEC-HMS had a good performance reproducing the two events, however simulated flow time series are highly influenced by the antecedent soil moisture, infiltration rate and canopy storage. Outflow modeled data were verified for two flood events (June 4, 2008 and July 9, 2009). The HEC-HMS was over-sensitive for input soil moisture and with increasing input rainfall and increasing outflow, larger simulation errors were observed.     

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.     

Flood events, fatalities and damages in India from 1978 to 2006

High temporal and spatial variability of rainfall qualifies India to be highly vulnerable to floods. Recurring floods of various magnitudes play havoc with the lives and property of the people, leading to unplanned development and unchecked environmental degradation, thwarting and retarding the overall development of the country. Therefore, the purpose of the present study is to analyze the types and trends in terms of flood events, frequency, number of people killed, injured, missing and economic damage both in space and time on the basis of a nationwide database published by India Meteorological Department, Pune, from 1978 to 2006. Analysis of these long-term data has revealed that 2,443 flood events claimed about 44,991 lives with the average of 1,551 lives each year. In terms of population size, these figures translate into a loss of 1.5 human lives per million of the population. A majority (56 %) of flood fatalities were caused during severe flood events. However, the frequency of these events was just 19 % in comparison with heavy rainfall events (65 %). In spatial context, flood-related fatalities are distributed all over the country with highest fatalities in Uttar Pradesh (17 %), Maharashtra (13 %), and Bihar and Gujarat (10 % each). Most fatalities occurred during the summer season monsoon months of August (30 %) followed by July (29 %) and September (20 %). The country suffered a cumulative flood-related economic loss of about 16 billion US$ between 1978 and 2006 and a maximum economic loss of 1.6 billion US$ in the year 2000 alone. The study further suggests that both flood events and fatalities have increased in India over a period of time.     

Summer monsoon rainfall scenario over Bangladesh using a high-resolution AGCM

Summer monsoon rainfall was simulated by a global 20 km-mesh atmospheric general circulation model (AGCM), focusing on the changes in the summer monsoon rainfall of Bangladesh. Calibration and validation of AGCM were performed over Bangladesh for generating summer monsoon rainfall scenarios. The model-produced summer monsoon rainfall was calibrated with a ground-based observational data in Bangladesh during the period 1979–2003. The TRMM 3B43 V6 data are also used for understanding the model performance. The AGCM output obtained through validation process made it confident to be used for near future and future summer monsoon rainfall projection in Bangladesh. In the present-day (1979–2003) climate simulations, the high-resolution AGCM produces the summer monsoon rainfall better as a spatial distribution over SAARC region in comparison with TRMM but magnitude may be different. Summer monsoon rainfall projection for Bangladesh was experimentally obtained for near future and future during the period 2015–2034 and 2075–2099, respectively. This work reveals that summer monsoon rainfall simulated by a high-resolution AGCM is not directly applicable to application purpose. However, acceptable performance was obtained in estimating summer monsoon rainfall over Bangladesh after calibration and validation. This study predicts that in near future, summer monsoon rainfall on an average may decrease about ?0.5 % during the period 2015–2034 and future summer monsoon rainfall may increase about 0.4 % during the period 2075–2099.     

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.     

Hydraulic routing of extreme floods in a large ungauged river and the estimation of associated uncertainties: a case study of the Damodar River, India

Many developing countries are very vulnerable to flood risk since they are located in climatic zones characterised by extreme precipitation events, such as cyclones and heavy monsoon rainfall. Adequate flood mitigation requires a routing mechanism that can predict the dynamics of flood waves as they travel from source to flood-prone areas, and thus allow for early warning and adequate flood defences. A number of cutting edge hydrodynamic models have been developed in industrialised countries that can predict the advance of flood waves efficiently. These models are not readily applicable to flood prediction in developing countries in Asia, Africa and Latin America, however, due to lack of data, particularly terrain and hydrological data. This paper explores the adaptations and adjustments that are essential to employ hydrodynamic models like LISFLOOD-FP to route very high-magnitude floods by utilising freely available Shuttle Radar Topographic Mission digital elevation model, available topographical maps and sparse network of river gauging stations. A 110 km reach of the lower Damodar River in eastern India was taken as the study area since it suffers from chronic floods caused by water release from upstream dams during intense monsoon storm events. The uncertainty in model outputs, which is likely to increase with coarse data inputs, was quantified in a generalised likelihood uncertainty estimation framework to demonstrate the level of confidence that one can have on such flood routing approaches. Validation results with an extreme flood event of 2009 reveal an encouraging index of agreement of 0.77 with observed records, while most of the observed time series records of a 2007 major flood were found to be within 95 % upper and lower uncertainty bounds of the modelled outcomes.     

An investigation on the dynamic and scale interactive processes for estimating the predictability of cloudburst over elevated orography

The cloudburst is defined as a heavy downpour at a very high rainfall rate over small spatio-temporal scale. The Indian states of Uttarakhand (30°15′N; 79°15′E) and Himachal Pradesh (32°29′N; 75°10′E) are prone to cloudburst due to its geographical setup. The large-scale monsoon flow along with elevated orography makes cloudburst phenomena frequent a well as severe over the regions. However, cloudburst and the heavy rainfall events occasionally, become difficult to distinguish. The present study attempts to identify the processes associated with cloudburst over elevated orography and compare it with one of the most debated event of 2013 which was reported as heavy rainfall but, not a cloudburst by Indian Meteorological Department (IMD). The temporal variations of rainfall and cloud-top pressure (CTP) are considered to identify the genesis of the event. The vertical developments of the system along with large-scale circulation pattern are estimated in the present study. The result of the study reveals that the mid-tropospheric dry entrainment, low-level temperature inversion and cloud height clearly distinguish the “cloudburst” and “heavy rainfall” events and confirms that the system of 2013 was indeed a heavy rainfall event and not a cloudburst.     

The Indian summer monsoon as revealed by the NCMRWF system

In this study, we present the mean seasonal features of the Indian summer monsoon circulation in the National Centre for Medium Range Weather Forecasting (NCMRWF) global data assimilation and forecast system. The large-scale budgets of heat and moisture are examined in the analyzed and model atmosphere. The daily operational analyses and forecasts (day 1 through day 5) produced for the summer seasons comprising June, July and August of 1995 and 1993 have been considered for the purpose. The principal aim of the study is two-fold. Primarily, to comprehend the influence of the systematic errors over the Indian summer monsoon, secondarily, to analyze the performance of the model in capturing the interseasonal variability. The heat and moisture balances show reduction in the influx of heat and moisture in the model forecasts compared to the analyzed atmosphere over the monsoon domain. Consequently, the diabatic heating also indicates reducing trend with increase in the forecast period. In effect, the strength of Indian summer monsoon, which essentially depends on these parameters, weakens considerably in the model forecasts. Despite producing feeble monsoon circulation, the model captures interseasonal variability realistically. Although, 1995 and 1993 are fairly normal monsoon seasons, the former received more rainfall compared to the latter in certain pockets of the monsoon domain. This is clearly indicated by the analyzed and model atmosphere in terms of energetics.     

Relative role of sea surface temperature and snow on Indian summer monsoon seasonal simulation using a GCM

Indian summer monsoon is a global scale phenomenon controlled by different land, ocean, and atmospheric parameters. Sea surface temperature (SST) and snow are two of the major parameters, which may alter the spatial and temporal patterns of circulation and rainfall during Indian summer monsoon. In the current paper, we study the monsoon variability using long integrations (20 years) of the Indian Institute of Technology Delhi (IITD) Spectral model at T80L18 resolution with observed and climatological SST and snow. Study shows response of IITD GCM in simulating the Indian summer monsoon rainfall and circulation relative to the snow and SST as boundary conditions. The model’s response to SST and snow is examined by conducting four types of experiments by varying observed and climatological values of snow and SST. This paper discusses the seasonal total rainfall for country as a whole and 850 and 200 hPa wind for the period of 20 years starting from 1985 to 2004. The model has been integrated in the ensemble mode with five different initial conditions from the last week of April and first week of May. The model is able to capture the climatological patterns of seasonal total rainfall and averaged wind at lower and upper levels. Observed snow in the presence of climatological SST as a boundary condition shows much impact on rainfall and circulation than observed SST in the presence of climatological snow. Model performance is good in simulating the normal and excess monsoon conditions; it shows poor skill in capturing deficit monsoon years.     

Extraction of soil moisture from RADARSAT-1 and its role in the formation of the 6 December 2008 landslide at Bukit Antarabangsa,Kuala Lumpur

Active microwave has a huge potential in the estimation of soil moisture especially over large areas where the meteorological observations are seldom. The large contrast in dielectric constant between different types of soil is considered as the main factor for measuring the moisture content. This study is aimed at the extraction of soil moisture over the areas of Bukit Antarabangsa, Malaysia using active microwave remote sensing technique in order to examine the impact of moisture content dynamically on landslides occurrence, which have been a basic challenge that threaten Bukit Antarabangsa area, particularly in falling of monsoon seasons. This study addressed a specific event that took place in 6 December 2008 due to a very high level of precipitation that resulted in a raise in ground water table causing the occurrence of landslide. One Radarsat-1 image acquired in July 2008 before the landslide was used for generating the moisture content map. The resultant moisture content map showed a reasonable distribution of the moisture concentrated over the forest areas which has previous records landslides. Moreover, it was found that the previous landslide events were within the high moisture zone indicating the presence of high moisture content. Subsequently, three moisture maps were extracted from Landsat-7 ETM+, which were then used for validation process. A statistically based validation technique was used by calculating area under the curve that correlates the high moisture values of three images. In order to validate the Landsat-7 ETM+ moisture content, monthly rainfall data was plotted against the high moisture values derived from three Landsat-7 images. The validation result indicated an acceptable compatibility. The spatial relation between high moisture areas in Landsat-7 ETM+ images along the year resulted in a good fitting in the high–low moisture distribution areas with sensitivity ranged of 60–70 %. Finally, the moisture content map generated by Radarsat-1 was validated using a landslide inventory map. The resultant validation produced an area under curve of 0.704 (70 %).