Cloudburst Events Research Articles

Synoptic forcing and thermo-dynamical processes during cloudburst event over Sauni Binsar, Uttarakhand, India

Cloud bursts have become a pressing concern with their devastating impact and increasing frequency over the Himalayan region. Therefore, understanding the physical mechanisms associated with their occurrence is essential and urgent. Our investigation into the physical mechanisms of a cloud burst over Sauni Binsar, Uttarakhand, India, which occurred on 10 June 2021 around 06 UTC, is a step towards addressing this urgency. On the day of the cloud burst, there was a continuous accumulation/stagnation (at 850 hPa) of moist air over Sauni Binsar due to the northward propagation of the southwest monsoon, leading to atmospheric column supersaturation. The advection of warm air (dry) from the monsoon heat low at higher (700 hPa) caused potential instability over this region. Orographic lifting and a gradual increase in convergence over this region caused moist convection. Further, the analysis of Richardson's number indicated that turbulence was maximum in the middle and upper troposphere. Just a few hours before the cloud burst event (02–06 UTC 10 June 2021), the decrease in potential vorticity indicates the squashing of the moist columns and the decrease in the vorticity. The sudden squashing of the supersaturated atmospheric column might have caused enormous rainfall (Cloud burst) over the Sauni Binsar region.

A comprehensive study of atmospheric dynamics associated with cloudburst events in 2022 over Indian Himalayan Region

A comprehensive study of atmospheric dynamics associated with cloudburst events in 2022 over Indian Himalayan Region

Multiscale dynamics of transient merging between western disturbances and monsoonal lows: Connections to the July 2023 flood in Himachal Pradesh

The Himachal Pradesh region experienced an unprecedented 436% more rainfall than normal from July 7th to 10th, 2023, resulting in devastating landslides, flash floods, and significant socio-economic losses. Using rainfall observations and reanalysis data, this study investigates the dynamics of the extreme precipitation event that caused the disastrous 2023 flood in Himachal Pradesh, India. Prior to the flood, moderate rainfall events saturated the mountainsides, making them more vulnerable to landslides and flash floods. Local features such as rapid convergence, vertical velocity, relative humidity, relative vorticity, and moisture flux accumulation were observed to decrease following the extreme precipitation event, indicating a short-duration cloud burst event. Further, the study reveals a large-scale circulation pattern linking the extratropic and monsoonal low, which is favorable for extreme precipitation in the Himachal Pradesh region. This pattern includes a transient merging of eastward-propagating trough in the mid-upper-level, which extends southward and a monsoon low moving westward across India. The key elements of this transient merging feature consist of a Rossby wave train structure and a blocking high west of the features. The Rossby wave breaking effect occurred downstream of the blocking high two days prior to extreme precipitation event occurrence. This allowed high potential vorticity stratospheric air to intrude the equator and troposphere, causing surface pressure change and enhanced vertical motion, thereby advecting high amount of moisture causing extreme precipitation leading to catastrophic floods. Overall, the findings of this study hold direct implications for early warning systems and disaster preparedness in the face of extreme precipitation-induced flood situations triggered by such transient merging features.

Comprehensive study of extreme rainfall events using model simulations and remotely sensed observations

ABSTRACTIn the present work, a detailed examination of extreme rainfall events (EREs) has been carried out using weather research and forecasting (WRF) model and remotely sensed observations over the Northwest Himalayan region. We performed high-resolution model simulations and studied EREs in association with fine-resolution Indian National Satellite System (INSAT-3D) observations. Remarkable variations noted in the remotely sensed outgoing longwave radiation and rainfall in association with model simulations during the formation of cloudburst events may be utilized to give an alert over the locations potentially affected by the EREs. We found that the fine-scale structure of various physical quantities during the formation of the cloudburst events endures remarkable variations in close agreement with the satellite-based observations. Results obtained in the present study show a promising pathway for the study, analysis and now-casting of extremely heavy rainfall events based on model simulations in conjunction with remotely sensed observations.

Satellite sensed summer monsoon torrential rain events characteristics along the Himalayan regions of North India and their dynamics

In the past three decades, the total number of extreme rainfall events over northern India has increased, which majorly caused flooding and landslides over the Himalayan foothills and the north Indian region. Some extreme events are reported as torrential rainfall or cloudburst events; others are linked with large-scale weather systems. In this article, we identified extreme precipitation events over northern India during the summer monsoon season using satellite-sensed high-resolution precipitation. Historically noted cloudbursts were selected from these extreme events to study the mechanisms behind their development. The cloudburst events were classified into five primary classes, C1, C2, C3, C4, and C5, based on the large-scale weather systems in the lower, middle, and upper troposphere. A detailed understanding of each class of cloudburst has been carried out to know the precursors for their formation, the dynamical mechanism involved in their development, and the thermodynamic features responsible for causing extreme rainfall. It is found that cloudburst events of classes C1, C2, and C3 are seen during the active monsoon season. Classes C4 and C5 cloudburst events are linked with the monsoon hiatus/break period. In the active monsoon season, these cloudburst events are associated with lower atmosphere cyclonic circulation over the head Bay of Bengal in class C1, and cyclonic circulation centered over Central India in class C2, and East-West oriented low-pressure conveyor system over central India in class C3. Additionally, thermodynamic analysis of each class revealed that class C1, C2, and C3 cloudbursts were associated with the moist instability of the atmosphere during the cloudburst events, where orographic forcing created potential instability and made them intense and overwhelming.

Studying the evolution of Uttarkashi cloudburst event from reanalysis datasets–A case study

In recent years, the frequency and severity of cloudburst considerably increased over southern rim of Himalayas due to hot climate that leads to loss of human lives and damage properties. The observed rainfall data shows that cloudburst events with heavy rainfall ∼ 100–200 mm/day are common over the Himalayan region during the summer monsoon period. It is very necessary to understand the mechanisms associated with such type of short span of high impact localised weather events over the regions where observations are limited. Therefore, one of best way to study the mechanism associated with the formation and development of cloudburst is using the available high resolution reanalysis datasets. An effort is made to understand the role of atmospheric conditions that control the evolution of cloudburst event by considering two reanalyses datasets such as high resolution IMDAA and ERA5 reanalyses. The present study analysed a cloudburst case that occurred on 3rd August 2012 at 10 pm with heavy rainfall of ∼ 100 mm in a very short span of time over the Uttarkashi district. Various dynamic and thermodynamic parameters are calculated from the two datasets with an aim of determining the best representation of severity of the cloudburst event. It is noticed that the evolution of dynamic and thermodynamic variables is well represented in the high resolution IMDAA dataset as compared to the ERA5 dataset. The amount and spatial distribution of rainfall from IMDAA reanalyses are well comparable with satellite estimated rainfall (GPM), having better correlation (0.60) with the observed rainfall as compared to the ERA5 (0.28). The rainfall time bias over the Uttarkashi district is larger in ERA5 reanalyses (∼ 5 h) than in the IMDAA (∼ 3 h). The ERA5 is not able to capture such type of localise high rainfall event due to its low resolution, compared to high resolution reanalyses (12 km) of IMDAA. The observations also indicate that the moisture flux from the Bay of Bengal (BoB) and Arabian Sea interacted with northwesterly dry air over Uttarkashi and the orographic uplifting resulted the cloudburst. Overall, results show that the eveolution and mechanism associated with the cloudburst is better represented in IMDAA than the ERA5. More cases are required to be studied to further support the findings of this study.

Students’ explanations of a complex natural phenomenon using mathematical modeling as a design feature in a model-based inquiry unit

This research investigates the ways in which mathematical modelling as a design feature support or constrain students’ understandings and explanations of a complex natural phenomenon and how students experience the relevance of mathematical modelling in a model-based inquiry (MBI) unit. To support lower secondary students in using mathematical modelling, we developed an MBI unit based on a complex natural phenomenon, a cloudburst event, in which mathematical modelling was essential to understanding and explaining the phenomenon. The research took place in two Danish schools and the unit comprised 12 lessons over a period of one week. The sample group consisted of 40 students in the 14–16 years age group. For the analysis of the students’ mathematical modelling, the research used an adaptation of the modelling cycle proposed by Blum and Leiß (2005) to interpret the students’ artefacts. A subset of participants (n = 7) was also interviewed about their models to gain insights into how students experience the relevance of mathematical modelling in the MBI unit. Results show that the majority of the students – 37 out of 40 – were able to understand the mathematical problem from the anchoring phenomenon and model the phenomenon from a mathematical perspective, but we also see that a small number of students have problems in completing all the facets of the mathematical modelling cycle and are not able to validate the solution of the mathematical problem in relation to the anchoring phenomenon. Students expressed that their own modelling process along with the mathematical modelling helped them better understand the various elements of the anchoring phenomenon.

Performance evaluation of high‐resolution IMDAA and IMERG for detecting cloudburst events over the Northwest Himalayas

AbstractThe main goal of this research is to assess the Indian Monsoon Data Assimilation and Analysis (IMDAA), a recently established high‐resolution (0.12° × 0.12°) reanalysis dataset, for observing cloudburst events over the Northwest Himalaya (NWH). In addition, a high‐resolution (0.1° × 0.1°) satellite estimate, the Integrated Multi‐satellitE Retrievals for Global Precipitation Measurement (GPM) version 6 (IMERG‐V06B) (Final run), is validated against the IMDAA. The following is a summary of our significant findings. (1) Reanalysis data from the IMDAA detects 11 out of 16 cloudburst incidences. In addition, 10 events captured in the IMERG‐V06B data are a subset of those captured by IMDAA. According to contingency measures, the probability of detection (POD) of IMERG‐V06B at 99.99th percentile is 33.33%–63.39% along the geographical extent of NWH. When utilizing the improved probability of detection (IPOD) to account for time, the possibility of IMERG‐V06B detecting cloudburst occurrences ranges from 41.24% to 68.25%. (2) According to the finding, the IMDAA accurately detects cloudburst events in Jammu and Kashmir (J&K), where data from the India Metrological Department (IMD) at a resolution of 0.25° × 0.25° have underperformed. As a result, we can deduce that IMDAA can be used to observe extreme events in the Himalayas. IMERG‐V06B is also relevant satellite data for monitoring cloudburst events and validating climate models.

Real-time control enhanced blue-green infrastructure towards torrential events: A smart predictive solution

Climate change-induced storms have posed a threat to current urban stormwater systems. As a critical flood control measure, passive urban blue-green infrastructure (BGI) is incapable of effectively utilizing available storage capacity to mitigate peak flows during cloudburst events. At storm peak times, landscape-based BGI may overflow to the drainage system, contributing to downstream flooding risks. To alleviate the effect, this research investigated an adaptive RTC solution that would predischarge the BGI and initiate runoff detention during the most vulnerable period of peak intensity. A case study of a RTC-enhanced landscape detention basin in Tongzhou, Beijing, was conducted using 2D1D modeling. To minimize peak-time overflow under extreme conditions, the studied smart BGI equipped with sensors and electronically movable gates was actuated by both rule-based control (RBC) and model predictive control (MPC) algorithms. Modeling results indicate that the proposed predictive solutions reduced catchment peak outflow by 7.6% to 45.1% over the passive system during three historical cloudburst events. This proposal proves that similar RTC applications could be scaled up to additional landscape projects to increase urban sustainability towards climate change and extreme precipitation.

An Investigation of Cloudburst-triggered Landslides and Flash Floods in Arakot Region of Uttarkashi District, Uttarakhand

Abstract A cloudburst event occurred at around 04:00hrs (IST), on 18, August 2019, elicited landslides and flash floods, at Tikochi and Makudi village under the Arakot region of Uttarkashi District, Uttarakhand, India. This heavy rain has caused a massive flash flood in Arakot Nala and induced a major landslide downstream. This flash flood has caused the death of 19 people, 8 were missings, and 15 were injured, affecting 38 villages (70 km2 area) and stranding more than 400 people at various places. These flash floods have caused irreparable damage to the livestock, infrastructures, environment, and properties in the Uttarakhand and Himachal states and estimated economic losses of about Rs ~175 crores. During the same period, heavy rainfall also made havoc across north India. Meanwhile, the rescue and evacuation process in the region has been carried out by the Indo-Tibetan Border Police (ITBP), National Disaster Response Force (NDRF), and State Disaster Response Force (SDRF). However, it will take a lot of time to bring the situation in the region to normalcy. The study has suggested that pragmatic check dam policy and logical shifting of the people should be exercised in a safe and stable area before the onset of the monsoon season in the hazard-prone areas. An early warning system (EWS), installation of Doppler radar, and lightning sensors, which would be helpful for policymakers, planners, practitioners, and technologists will aid to minimize the disaster risk and sustainable development within the region. Although an EWS alone can not stop a similar type of disaster but would be very helpful in minimizing the loss of human lives, livestock, biodiversity, infrastructure (civilian and strategic), and land holding in the hilly region.

On the Potentials and Limitations of Attributing a Small‐Scale Climate Event

AbstractIntense convective storms can be hazardous when occurring over large populated cities. In a changing climate, decision makers and the general public increasingly need to be able to better understand if and to what extent these storms are influenced by anthropological climate change and what to expect as climate continues to warm. Unfortunately due to their limited ability to resolve small‐scale features in models, convective storms remain a challenge to the modeling community. Here, we use a forecast‐ensemble based method using a convection permitting model with full data‐assimilation, to assess the risk of exceeding certain precipitation thresholds related to a critical cloudburst event that occurred over Copenhagen, Denmark. Our results show that this set‐up is representing well the overall observed intensities. By adapting a pseudo‐global warming approach, we show that both the risk for flooding and the risk for reaching unprecedented precipitation intensity increases resulting from further warming.

Revisiting the 1993 Extreme Precipitation in Central Nepal: Synoptic Feature and Numerical Simulation

The cloudburst event occurred on 19-20 July 1993, creating a devastating flash flood over south-central Nepal. The storm killed hundreds of people, and damaged millions of dollars of properties. This study focused on the synoptic and thermodynamics that triggered the cloudburst in central Nepal, bringing 540 mm of rainfall over a small region in less than 24 hours. Moreover, it investigates the primary reason for the particular extremest event in Nepal. Our results show the strong upward motion transported the significant moisture that led to favorable condition for development of thick cloud cover, producing a record-breaking precipitation during that event over central Nepal. Likewise, the monsoon trough with negative sea level pressure anomaly over central Nepal located east of the upper-level trough further suggests a westward tilt with height in the disturbances associated with cloudburst on the event day. Further, we also simulate the extreme precipitation events over the region using Weather Research Forecast (WRF) model however, it underestimated the precipitation amount with slight shift in event location. The model simulates the actual thermodynamics, but it fails to produce the actual precipitation. Moreover, it is difficult to simulate the actual topography over the complex region where orography plays an essential role in producing high precipitation.

Mainstreaming climate resilience: A GIS-based methodology to cope with cloudbursts in Turin, Italy

Cities play an increasingly significant role in the challenges posed by climate change, mainly due to their role in economic and demographic drivers. It is generally agreed that the intensification of climate change effects, such as extreme weather events, requires strengthening in the mechanisms of adaptation and the endogenous self-organization of urban systems. An operative way to adapt is by mainstreaming climate resilience, i.e., the iterative process of integrating climate change considerations into policymaking, budgeting, implementation, and monitoring processes at national and subnational levels. This paper falls under this heading, and it aims at building an innovative methodology to experiment with data-driven approaches to support the resilient transition of the city of Turin in Italy. The process aims to create territorial knowledge of specific weather phenomenon, that cloudburst events are, by filling the gap of existing hazard information with original vulnerability datasets. The proposed approach will create a hydraulic vulnerability map by identifying cloudburst vulnerable areas with a GIS-based spatial overlay. The paper will employ an array of datasets combined with original modelling techniques elaborated with the help of the open-source InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) software program. The results allow us to understand what would happen if the urban water network failed to discharge during a phenomenon of intense rain and, consequently, which city areas should undergo adaptation and transformation to reduce their flooding vulnerability.

Cloudburst events observed over Uttarakhand during monsoon season 2017 and their analysis

Cloudburst is an extreme weather event characterised by the occurrence of a large amount of rainfall over a small area within a short span of time with a rainfall of 100 mm or more in one hour. It is responsible for flash flood, inundation of low lying areas and landslides in hills causing extensive damages to life and property. During monsoon season 2017 five number of cloudburst events are observed over Uttarakhand and analysed. Self Recording Rain Gauge (SRRG) and 15 minutes interval data from the newly installed General Packet Radio Service (GPRS) based Automatic Weather Station (AWS) are able to capture the cloudburst events over some areas in Uttarakhand. In this paper, an attempt has been made to find out the significant synoptic and thermodynamic conditions associated with the occurrence of the cloudburst events in Uttarakhand. These 5 cases of cloudburst events that are captured during the month of June, July and August 2017 in Uttarakhand are studied in detail. Synoptically, it is observed that the existence of trough at mean sea level from Punjab to head Bay of Bengal running close to Uttarakhand, the movement of Western Disturbance over north Pakistan and adjoining Jammu & Kashmir and existence of cyclonic circulation over north Rajasthan and neighbourhood are favourable conditions. Also, the presence of strong south-westerly wind flow from the Arabian Sea across West Rajasthan and Haryana on upper air charts are found during these events. Thermodynamically, the Convective Available Potential Energy (CAPE) is found to be high (more than 1100 J/Kg) during most of the cases and vertically integrated precipitable water content (PWC) is more than 55mm. The GPRS based AWS system can help in prediction of the cloud burst event over the specified location with a lead time upto half to one hour in association with radar products.

Cloudburst-disaster modelling. A new open-source catastrophe model

Cloudburst flash floods cause big casualties and economic losses. This study primarily investigated if a cloudburst catastrophe (cat) model could be constructed to meaningfully assess such a hazard, exposure and vulnerability in Swedish urban context. Rainfall intensity was used directly as hazard measure, bypassing hydraulic water-level modelling, to predict vulnerability. The Splash (Swedish pluvial modelling analysis and safety handling) cloudburst-disaster model was constructed using the Oasis Loss Modelling Framework, and was based on individual property values and building locations, property-level insurance-loss data, high-resolution geographical data, and rainfall data from a dense municipal gauge network in the city of Jönköping. One major cloudburst event was used to derive a vulnerability curve. The following two events were used for validation and supported the hypothesis that the vulnerability curve changed with time because of municipal flood-risk-reduction measures after the first event. A faulty rain gauge during the first event, replaced by a trustworthy private gauge, clarified the very high sensitivity to cloudburst input. Given the limited amount of loss data, our results were uncertain but they pointed towards possible ways to further this study with other loss data at other locations, possibly using more easily available aggregated loss data. We concluded that a cat model based only on rainfall intensity provided acceptable results, thus providing an opening for future, simplified cloudburst cat models applicable in most geographical contexts where reliable cloudburst data are available, especially in cities with limited topographic data and hydraulic-modelling capacity.

Analysis of pluvial flood damage costs in residential buildings – A case study in Malmö

Pluvial flood damage to residential buildings causes a significant part of direct tangible flood losses. In this study, we investigate the non-hazard variables and sewer system types in relation to damage costs in the city of Malmö, Sweden. A comprehensive data set of around 1000 records of direct damage to residential buildings from a cloudburst event on 31 August 2014 in Malmö, Sweden has been analysed at property scale with no lumping together of data. The results show that properties connected to combined sewer systems are much more exposed to pluvial flood damage than properties connected to separated sewer systems, with the ratio of the number of claims being close to three. The analysis of building-specific variables shows no clear statistical relationships to the damage costs. To further the understanding of damage costs caused by urban pluvial flooding, it is necessary to extend the group of explanatory variables to include information about the socio-economic background of households, the actual value of assets in basements and the precautionary measures taken by house owners.

Kerala floods in consecutive years - Its association with mesoscale cloudburst and structural changes in monsoon clouds over the west coast of India

Kerala, located at the southwest tip of India, witnessed disastrous floods during the monsoon seasons of two consecutive years, 2018 and 2019. This paper provides a detailed analysis of these two flood events using data from multiple sources. The unusually unstable and convective nature of the 2019 event, as detectable in its higher cloud tops and evidently fuelled by anomalously warm local sea temperatures, raises concerns regarding the changing patterns of rainfall over the southern parts of the west coast of India. Specifically, our analysis reveals that the flood of 2019 in Kerala satisfies the criteria for a mesoscale cloudburst (MsCB) event, more common in the north but a very rare and never before reported phenomenon in the Kerala region. Rainfall exceeding 50 mm in 2 h has been reported from many places between 8.00 and 22.00 UTC on the August 8, 2019. Satellite-derived rainfall and cloud microphysical parameters further reveal the uniqueness of the 2019 MsCB event. If 2019 is a harbinger of how global warming may continue to affect this region, transformations of the cloud structure and the recurrence and character of intense rainfall events could pose a major threat to the highly vulnerable Western Ghats ecosystems.

Performance-Based Planning to Reduce Flooding Vulnerability Insights from the Case of Turin (North-West Italy)

Climate change impacts urban areas with greater frequency and exposes continental cities located on floodplains to extreme cloudbursts events. This scenario requires developing specific flooding vulnerability mitigation strategies that improve local knowledge of flood-prone areas at the urban scale and supersede the traditional hazard approach based on the classification of riverine buffers. Moreover, decision-makers need to adopt performance-based strategies for contrasting climate changes and increasing the resilience of the system. This research develops the recent Flooding Risk Mitigation model of InVEST (Integrated Evaluation of Ecosystem Services and Trade-off), where cloudburst vulnerability results from the soil’s hydrological conductivity. It is based on the assumption that during cloudburst events, all saturated soils have the potential for flooding, regardless of the distance to rivers or channels, causing damage and, in the worst cases, victims. The model’s output gives the run-off retention index evaluated in the catchment area of Turin (Italy) and its neighborhoods. We evaluated the outcome to gain specific insight into potential land use adaptation strategies. The index is the first experimental biophysical assessment developed in this area, and it could prove useful in the revision process of the general town plan underway.

Urban policy adaptation toward managing increasing pluvial flooding events under climate change

Climate change is increasing the frequency and intensity of heavy rainfall events. In urban areas, these cloudbursts cause localized flooding and disrupt urban life. However, there is no universal method for urban rainfall adaptation. Here, we demonstrate that while six developed cities; New York City, Vancouver, Sydney, Auckland, Copenhagen and Amsterdam, each present a different management approach toward cloudburst events, these six cities also use a mixture of five common policy alternatives to manage stormwater runoff. Thus, while individual cities might pursue different management approaches toward pluvial flooding, the repetition of the policy alternatives across these six cities indicates the foundation of a global consensus toward the policy adaptation techniques available. As climate change continues to impact our urban environments, it is important to identify and understand policy tools for effective adaptation, ensuring knowledge can be transferred across all cities facing an unpredictable future.

Performance Analysis of IMD High-Resolution Gridded Rainfall (0.25° × 0.25°) and Satellite Estimates for Detecting Cloudburst Events over the Northwest Himalayas

AbstractThe presence of a sparse rain gauge network in complex terrain like the Himalayas has encouraged the present study for the concerned evaluation of Indian Meteorological Department (IMD) ground-based gridded rainfall data for highly prevalent events like cloudbursts over the northwest Himalayas (NWH). To facilitate the abovementioned task, we intend to evaluate the performance of these observations at 0.25° × 0.25° (latitude–longitude) resolution against a predefined threshold (i.e., 99.99th percentile), thereby initially comprehending the success of IMD data in capturing the cloudburst events reported in media during 2014–16. Further, seven high-resolution satellite products, namely, CMORPH V0.x, PERSIANN-CDR, TMPA 3B42RT V7, IMERG V06B, INSAT-3D multispectral rainfall (IMR), CHIRPS V.2, and PERSIANN-CCS are evaluated against the IMD dataset. The following are our main results. 1) Six out of 18 cloudburst events are detected using IMD gridded data. 2) The contingency statistics at the 99.99th percentile reveal that the probability of detection (POD) of TMPA varies from 19.4% to 53.9% over the geographical stretch of NWH, followed by PERSIANN-CDR (18.6%–48.4%) and IMERG (4.9%–17.8%). 3) A new metric proposed as improved POD (IPOD) has been developed in this work, which takes into account the temporal lag that exists between observed and satellite estimates during an event period. Results show that for an event analysis IPOD provides a better comparison. The IPOD for TMPA is 32.8%–74.4%, followed by PERSIANN-CDR (34.4%–69.11%) and IMERG (15.3%–39.0%). 4) The conclusion stands as precipitation estimates obtained from CHIRPS are most suitable for monitoring cloudburst events over NWH with IPOD of 60.5%–78.6%.