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.

Incremental Learning with Neural Network Algorithm for the Monitoring Pre-Convective Environments Using Geostationary Imager

Early warning of severe weather caused by intense convective weather systems is challenging. To help such activities, meteorological satellites with high temporal and spatial resolution have been utilized for the monitoring of instability trends along with water vapor variation. The current study proposes a retrieval algorithm based on an artificial neural network (ANN) model to quickly and efficiently derive total precipitable water (TPW) and convective available potential energy (CAPE) from Korea’s second geostationary satellite imagery measurements (GEO-KOMPSAT-2A/Advanced Meteorological Imager (AMI)). To overcome the limitations of the traditional static (ST) learning method such as exhaustive learning, impractical, and not matching in a sequence data, we applied an ANN model with incremental (INC) learning. The INC ANN uses a dynamic dataset that begins with the existing weight information transferred from a previously learned model when new samples emerge. To prevent sudden changes in the distribution of learning data, this method uses a sliding window that moves along the data with a window of a fixed size. Through an empirical test, the update cycle and the window size of the model are set to be one day and ten days, respectively. For the preparation of learning datasets, nine infrared brightness temperatures of AMI, six dual channel differences, temporal and geographic information, and a satellite zenith angle are used as input variables, and the TPW and CAPE from ECMWF model reanalysis (ERA5) data are used as the corresponding target values over the clear-sky conditions in the Northeast Asia region for about one year. Through the accuracy tests with radiosonde observation for one year, the INC NN results demonstrate improved performance (the accuracy of TPW and CAPE decreased by approximately 26% and 26% for bias and about 13% and 12% for RMSE, respectively) when compared to the ST learning. Evaluation results using ERA5 data also reveal more stable error statistics over time and overall reduced error distribution compared with ST ANN.

A forecasting aspect of thundersquall over Calcutta and its parameterisation during pre-monsoon season

Severe thunderstorms accompanied by squalls are the most hazardous weather phenomena during pre-monsoon season in north-eastern region of India. An attempt has been made in this paper to study some parameters for forecasting thundersqualls over Calcutta (Airport) during pre-monsoon season. Parameterisation of thermodynamic components alongwith the synoptic support during thundersqualls over Calcutta has been discussed here. A forecasting aspect for propagation speed of thunderstorm cell at Calcutta in pre-monsoon season has been examined with respect to radar-echo positions, mid-level winds and convective available potential energy (CAPE). Occurrences of multiple thundersqualls over Calcutta Airport within a few hours’ interval have been discussed and examined through hodograph analysis, radar observations and synoptic situations.

Measure of CINE - A relevant parameter for forecasting pre-monsoon thunderstorms over GWB

A method of testing the significance of Z- Statistic is introduced in this paper to discern the role of Convective Available Potential Energy (CAPE) and Convective Inhibition Energy (CINE) in forecasting the occurrence of pre-monsoon thunderstorms over Gangetic West Bengal (GWB). The result reveals that a negative correlation exists between CAPE and CINE. It further indicates that a range for the lower values of CINE can be fixed where the frequency of occurrence of such storms will be maximum, but such range, either for lower or for higher values of CAPE, is not possible. The paper, thus, ends with a very interesting finding that a measure of CINE is the only relevant parameter whereas CAPE has no significant role in forecasting the occurrence of pre-monsoon thunderstorms over GWB, which is in contrast to the concept of severe thunderstorms of Great Plains of America.

Geo-Hydrological Events and Temporal Trends in CAPE and TCWV over the Main Cities Facing the Mediterranean Sea in the Period 1979–2018

The Mediterranean region is regarded as the meeting point between Europe, Africa and the Middle East. Due to favourable climatic conditions, many civilizations have flourished here. Approximately, about half a billion people live in the Mediterranean region, which provides a key passage for trading between Europe and Asia. Belonging to the middle latitude zone, this region experiences high meteorological variability that is mostly induced by contrasting hot and cold air masses that generally come from the west. Due to such phenomenon, this region is subject to frequent intensive precipitation events. Besides, in this complex physiographic and orographic region, human activities have contributed to enhance the geo-hydrologic risk. Further, in terms of climate change, the Mediterranean is a hot spot, probably exposing it to future damaging events. In this framework, this research focuses on the analysis of precipitation related events recorded in the EM–DAT disasters database for the period 1979–2018. An increasing trend emerges in both event records and related deaths. Then a possible linkage with two meteorological variables was investigated. Significant trends were studied for CAPE (Convective Available Potential Energy) and TCWV (Total Column Water Vapor) data, as monthly means in 100 km2 cells for 18 major cities facing the Mediterranean Sea. The Mann–Kendall trend test, Sen’s slope estimation and the Hurst exponent estimation for the investigation of persistency in time series were applied. The research provides new evidence and quantification for the increasing trend of climate related disasters at the Mediterranean scale: recorded events in 1999–2018 are about four times the ones in 1979–1998. Besides, it relates this rise with the trend of two meteorological variables associated with high intensity precipitation events, which shows a statistically significative increasing trend in many of the analysed cities facing the Mediterranean Sea.

Inter-Zone Differences of Convective Development in a Convection Outbreak Event over Southeastern Coast of China: An Observational Analysis

Among the densely-populated coastal areas of China, the southeastern coast has received less attention in convective development despite having been suffering from significantly increasing thunderstorm activities. The convective complexity under such a region with extremely complex underlying and convective conditions deserves in-depth observational surveys. This present study examined a high-impact convection outbreak event with over 40 hail reports in the southeastern coast of China on 6 May 2020 by focusing on contrasting the convective development (from convective initiation to supercell occurrences) among three adjacent convection-active zones (north (N), middle (M), and south (S)). The areas from N to S featured overall flatter terrain, higher levels of free convection, lower relative humidity, larger convective inhibition, more convective available potential energy, and greater vertical wind shears. With these mesoscale environmental variations, distinct inter-zone differences in the convective development were observed with the region’s surveillance radar network and the Himawari-8 geostationary satellite. Convection initiated in succession from N to S and began with more warm-rain processes in N and M and more ice-phase processes in S. The subsequent convection underwent more vigorous vertical growth from N to S. The extremely deep convection in S was characterized by the considerably strong precipitation above the freezing level, echo tops of up to 18 km, and a great amount of deep (even overshooting) and thick convective clouds with significant cloud-top glaciation. Horizontal anvil expansion in convective clouds was uniquely apparent over S. From N to S, more pronounced mesocyclone and weak-echo region signatures indicated high risks of severe supercell hailstorms. These results demonstrate the strong linkage between the occurrence likelihood of severe convection and associated weather (such as supercells and hailstones) and the early-stage convective development that can be well-captured by high-resolution observations and may facilitate fine-scale convection nowcasting.

Indications of a Decrease in the Depth of Deep Convective Cores with Increasing Aerosol Concentration During the CACTI Campaign

An aerosol indirect effect on deep convective cores (DCCs), by which increasing aerosol concentration increases cloud-top height via enhanced latent heating and updraft velocity, has been proposed in many studies. However, the magnitude of this effect remains uncertain due to aerosol measurement limitations, modulation of the effect by meteorological conditions, and difficulties untangling meteorological and aerosol effects on DCCs. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in 2018-19 produced concentrated aerosol and cloud observations in a location with frequent DCCs, providing an opportunity to examine the proposed aerosol indirect effect on DCC depth in a rigorous and robust manner. For periods throughout the campaign with well mixed boundary layers, we analyze relationships that exist between aerosol variables (condensation nuclei concentration >10 nm, 0.4% cloud condensation nuclei concentration, 55-1000 nm aerosol concentration, and aerosol optical depth) and meteorological variables [level of neutral buoyancy (LNB), convective available potential energy, mid-level relative humidity, and deep layer vertical wind shear] with the maximum radar echo top height and cloud-top temperature (CTT) of DCCs. Meteorological variables such as LNB and deep-layer shear are strongly correlated with DCC depth. LNB is also highly correlated with three of the aerosol variables. After accounting for meteorological correlations, increasing values of the aerosol variables (with the exception of one formulation of AOD) are generally correlated at a statistically significant level with a warmer CTT of DCCs. Therefore, for the study region and period considered, increasing aerosol concentration is mostly associated with a decrease in DCC depth.

A diagnostic study of contrasting rainfall epochs over Mumbai

An attempt has made to diagnose the synoptic features and some dynamic and thermodynamic parameters associated with contrasting rainfall situations (on consecutive days) during the monsoon season, over Mumbai. Study has been made for two contrasting monsoon years, viz. 1987 (Bad monsoon year) and 1988 (Good monsoon year). For this study RS data of Mumbai have been used. In many cases heavy rainfall on an isolated day over Mumbai is associated with the following synoptic systems (a) a trough on sea level chart running along west coast through Maharashtra Coast and (b) a cyclonic circulation (CYCIR) over Gujarat in the lower/middle tropospheric level. At least one of the above two systems ceased to exist on the days of light rainfall. Weighted average value of moist static energy is more on the day of heavy rainfall. In most of the cases convective available potential energy (CAPE) is also more on the day of heavy rainfall. LFC, on most of the cases, is seen to have lowered down on the days of heavy rainfall. Variation in upper air flow pattern and scorer parameter also gave very interesting clues to variation of rainfall on contrasting days.

Terrain Effects on Regional Precipitation in a Warm Season over Qinling-Daba Mountains in Central China

The terrain effects of Qinling–Daba Mountains on reginal precipitation during a warm season were investigated in a two-month day-to-day experiment using the Weather Research and Forecasting (WRF) model. According to the results from the terrain sensitivity experiment with lowered mountains, Qinling–Daba Mountains have been found to have an obvious effect on both the spatial-temporal distribution and diurnal cycle of reginal precipitation from July to August in 2019, where the Qinling Mountains mainly enhanced the precipitation around 34° N, and the Daba Mountains mainly enhanced it around 32° N at the time period of early morning and midnight. Horizontal distribution of water vapor and convective available potential energy (CAPE), as well as cross section of vertical velocity of wind and potential temperature has been studied to examine the key mechanisms for these two mountains’ effect. The existence of Qinling Mountains intercepted transportation of water vapor from South to North in the lower troposphere to across 34° N and caused an obvious enhancement of CAPE in the neighborhood, while the Daba Mountains intercepted the northward water vapor transportation to across 32° N and caused an enhanced CAPE nearby. The time period of the influence is in a good accordance with the diurnal cycle. In the cross-section, the existence of Qinling Mountains and Daba Mountains are found to stimulate the upward motion and unstable environment effectively at around 34° N and 32° N, separately. As a result, the existence of the two mountains lead to a favorable environment in water vapor, thermodynamic, and dynamic conditions for this warm season precipitation.

How well are hazards associated with derechos reproduced in regional climate simulations?

An 11-member ensemble of convection-permitting regional simulations of the fast-moving and destructive derecho of June 29 – 30, 2012 that impacted the northeastern urban corridor of the US is presented. This event generated 1100 reports of damaging winds, significant wind gusts over an extensive area of up to 500,000 km2, caused several fatalities and resulted in widespread loss of electrical power. Extreme events such as this are increasingly being used within pseudo-global warming experiments that seek to examine the sensitivity of historical, societally-important events to global climate non-stationarity and how they may evolve as a result of changing thermodynamic and dynamic context. As such it is important to examine the fidelity with which such events are described in hindcast experiments. The regional simulations presented herein are performed using the Weather Research and Forecasting (WRF) model. The resulting ensemble is used to explore simulation fidelity relative to observations for wind gust magnitudes, spatial scales of convection (as manifest in high composite reflectivity), and both rainfall and hail production as a function of model configuration (microphysics parameterization, lateral boundary conditions (LBC), start date, and use of nudging). We also examine the degree to which each ensemble member differs with respect to key mesoscale drivers of convective systems (e.g. convective available potential energy and vertical wind shear) and critical manifestations of deep convection; e.g. vertical velocities, cold pool generation, and how those properties relate to correct characterization of the associated atmospheric hazards (wind gusts and hail). Here, we show that the use of a double-moment, 7-class scheme with number concentrations for all species (including hail and graupel) results in the greatest fidelity of model simulated wind gusts and convective structure against the observations of this event. We further show very high sensitivity to the LBC employed and specifically that simulation fidelity is higher for simulations nested within ERA-Interim than ERA5.