Climatological Features of Squall Line at the Borneo Coastline during Southwest Monsoon

Borneo Squall Line (BSL) is a disaster risk associated with intense rain and wind gust that affect the activities and residence near the northern coast of Borneo. Using 3-hourly rainfall from Tropical Rainfall Measuring Mission (TRMM) 3B42V7 during southwest monsoon season (May–September) from 1998–2018, a total of 629 squall days were identified. Their monthly and annual average was 6 and 30 days, respectively, with July representing the month with the highest number of squall line days. BSL is frequently initiated during midnight/predawn and terminated in the morning. Composite analyses of BSL days using the daily winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim revealed that lower tropospheric wind convergence is a crucial controlling factor for BSL formation. The position of the monsoon trough closer to the equatorial South China Sea (SCS), and strong westerly and south-westerly winds played an important role in creating this wind convergence region. Analyses of tropical cyclone (TC) data from the Regional Specialized Meteorological Centre (RSMC), Tokyo showed that nearly 72% of BSL occurred with the presence of TC. Spectral analysis exhibited prominent frequencies mainly in the 3–4- and 6-year time scale, which likely reflected the influence of interannual modulation of El-Niño Southern Oscillation (ENSO). Correlation coefficient between squall days and Sea Surface Temperature (SST) anomalies indicated that BSL increased after La-Niña events. This study is expected to have implications for real-time squall line forecasting in Malaysia and contributes toward a better understanding of BSL.

Geometric and Physical Characteristics of Precipitation Clouds in Tibetan Plateau

This paper examines the basic geometric and physical characteristics of precipitation clouds over the Tibetan Plateau, based on the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data from 1998 to 2015, using the minimum bounding rectangle (MBR) method. The results show that about 60% of the precipitation clouds occur with a scale of approximately 18 km (length) and 15 km (width), and the proportion of precipitation clouds with a length longer than 100 km and a width wider than 90 km is less than 1%. Most of the precipitation cloud exhibits a shape between square and long strips in the horizontal direction and lanky in the vertical direction. The average rainfall intensity of precipitation clouds is between 0.5 and 6 mm h−1. The average length and width of precipitation clouds show a logarithmic, linear relationship. The distribution of raindrops in precipitation clouds is relatively compact. With the expansion of the area, the precipitation clouds gradually become squatty. The relationship between physical and geometric parameters of precipitation clouds shows that with the precipitation cloud area expanding, the average rainfall rate of precipitation clouds also increases. Heavy convective rainfall is more likely to occur in larger precipitation clouds. For the precipitation clouds of the same size, the area fraction and contribution of convective precipitation are lower than that of stratiform precipitation.

Spatio-temporal Variability of Lightning Climatology and Its Association With Thunderstorm Indices Over India

Lightning is an electrical discharge - a'spark' or 'flash' as charged regions in the atmosphere instantly balance themselves through this discharge. It is a beautiful and deadly naturally occurring phenomenon. In June 2020, more than a hundred people died in the state Bihar of India only in three days’ span due to lightning events. In this work, Lightning Imaging Sensor (LIS) information from the Tropical Rainfall Measuring Mission (TRMM) satellite with a very high spatial resolution of 0.1 X 0.1 degree has been utilized to create the climatology of India for 16 years from 1998 to 2013. Diurnal, monthly, and seasonal variations in the occurrence of lightning flash rate density have also been analyzed. TRMM satellite low-resolution monthly time series (LRMTS) with 2.5-degree resolution datasets have been used for lightning trend analysis. The diurnal lightning event mainly occurs in the afternoon/evening (1400-1900 Hrs) time duration around 0.001 flashes/km2/hr. The highest lightning occurred in May (0.04 flashes/km2/day) and the least in December (0.005 flashes/km2/day). The distribution of lightning flash counts by season over India landmass is mainly in pre-monsoon (MAM) ranges from 0.248 – 0.491 flashes/km2/day, and monsoon (JJA) ranges from 0.284 – 0.451 flashes/km2/day and decreases afterward. Spatially, the distribution of lightning flashes mainly at North-Eastern region along with Bangladesh, Bihar, Jharkhand, Orissa, and Jammu & Kashmir region. The CAPE and K Index have positively correlated with the flash rate density seasonally but CAPE is more significantly correlated. This study also focused on finding of lightning hotspots region of India district wise and Rajouri district in Jammu and Kashmir got the highest lightning with 121 flashes/km2/yr.

A case study for cyclone ‘Aila’ for forecasting rainfall using satellite derived rain rate data

caxky dh [kkM+h esa cuus ,oa tehu ls Vdjkus okys pØokrh; rwQkuksa ds ifj.kkeLo:i Hkkjh o"kkZ dh otg ls if’pe caxky ds rV lesr Hkkjr ds iwohZ rV ds yksxksa dh tku eky dks dkQh [krjk jgrk gSA tehu ls Vdjkus okys m".kdfVca/kh; pØokrh rwQkuksa dh otg ls gksus okyh o"kkZ dh ek=k dk iwokZuqeku djuk cgqr dfBu gSA m".kdfVca/kh; pØokrh; rwQkuksa ds nk;js esa vkus okys o"kkZ okys {ks=ksa esa laHkkfor pØokrh; rwQku ls gksus okys o"kkZ lap;u dk iwokZuqeku djus ds fy, mixzg ls izkIr o"kkZ njksa dk mi;ksx fd;k tk ldrk gSA bl 'kks/k i= esa ‘vkbyk’ ds m".kdfVca/kh; o"kkZ ekiu fe’ku ¼Vh- vkj- ,e- ,e-½] mixzg o"kkZ nj vk¡dM+ksa rFkk rwQku ds ns[ks x, ekxZ dk mi;ksx djrs gq, m".kdfVca/kh; pØokr ‘vkbyk’ ds tehu ls Vdjkus ls 24 ?kVsa igys rVh; LVs’kuksa ij o"kkZ dk vkdyu djus dk iz;kl fd;k x;k gSA la;qDr jkT; vesfjdk esa fodflr lqifjfpr rduhd ds vk/kkj ij m".kdfVca/kh; pØokr ‘vkbyk’ ds tehu ls Vdjkus ds 24 ?kaVs igys m".kdfVca/kh; o"kkZ foHko ¼Vh- vkj- ,- ih-½ iwokZuqeku fo’ks"k :i ls rwQku dh fn’kk ds lkeus vkus okys rVh; {ks=ksa ds fy, vPNh o"kkZ dk iwokZuqeku miyC/k djkrk gSA Major threat to the life and property of people on the east coast of India, including West Bengal Coast, is due to very heavy rainfall from landfalling tropical cyclones originated over Bay of Bengal. Forecasting magnitude of rainfall from landfalling tropical cyclones is very difficult. Satellite derived rain rates over the raining areas of tropical cyclones can be used to forecast potential tropical cyclone rainfall accumulations. In the present study, an attempt has been made to estimate 24 hours rainfall over coastal stations before landfall of tropical Cyclone ‘Aila’ using Tropical Rainfall Measuring Mission (TRMM) satellite rain rates data and observed storm track of Aila. Forecast Tropical Rainfall Potential (TRaP), 24 hours prior to landfall for the tropical cyclone ‘Aila’ based on well known technique developed in USA, provides a good rainfall forecast especially for the coastal areas lying at the head of direction of the storm.

EFECTO DE LA CORRIENTE EN CHORRO DE BAJOS NIVELES EN LA OCURRENCIA DE PRECIPITACIÓN EN LA SELVA DEL PERÚ

Se analizó la corriente en chorro de América del Sur (SALLJ, siglas en inglés) y la ocurrencia de precipitación sobre la selva del Perú, tomando en cuenta los datos del modelo atmosférico Global Forecast System (GFS) y datos de precipitación acumulada estimado por el satélite Tropical Rainfall Measuring Mission (TRMM) en los veranos australes comprendidos entre los años 2005 y 2014. Se utilizó la distribución de Weibull para el análisis estadístico del viento meridional del norte y el test estadístico no paramétrico de correlación de Kendall para asociar los eventos SALLJ definidos por los criterios de Whiteman et al. (1997) y Bonner (1968). Los resultados revelan que el comportamiento promedio de la componente meridional del viento fluctúa entre 1.2 y 11.7 m/s con variaciones de +/- 3.2 m/s, registrando un viento máximo de 21.4 m/s. De un total de 39 casos, el 53.8% se identificó con las condiciones propuestas por Whiteman y un 46.2% con las condiciones de Bonner. Se registró una precipitación máxima de 64.00 mm/día y mayor número de días con precipitaciones asociadas a eventos SALLJ para las 00 UTC.

Evaluation of Seasonal, Drought, and Wet Condition Effects on Performance of Satellite-Based Precipitation Data over Different Climatic Conditions in Iran

The Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) are the most important and widely used data sources in several applications—e.g., forecasting drought and flood, and managing water resources—especially in the areas with sparse or no other robust sources. This study explored the accuracy and precision of satellite data products over a span of 18 years (2000–2017) using synoptic ground station data for three regions in Iran with different climates, namely (a) humid and high rainfall, (b) semi-arid, and (c) arid. The results show that the monthly precipitation products of GPM and TRMM overestimate the rainfall. On average, they overestimated the precipitation amount by 11% in humid, by 50% in semi-arid, and by 43% in arid climate conditions compared to the ground-based data. This study also evaluated the satellite data accuracy in drought and wet conditions based on the standardized precipitation index (SPI) and different seasons. The results showed that the accuracy of satellite data varies significantly under drought, wet, and normal conditions and different timescales, being lowest under drought conditions, especially in arid regions. The highest accuracy was obtained on the 12-month timescale and the lowest on the 3-month timescale. Although the accuracy of the data is dependent on the season, the seasonal effects depend on climatic conditions.

Comparison of forecasting accuracy for Madden Julian Oscillation (MJO) and Convectively Coupled Equatorial Waves (CCEW) using Tropical Rainfall Measuring Mission (TRMM) and ERA-Interim precipitation forecast data for Indonesia

Tropical Rainfall Measuring Mission (TRMM) and ERA-Interim forecast data analyzed using second-order autoregressive AR(2) and space-time-spectra analysis methods (respectively) revealed contrasting results for predicting Madden Julian Oscillation (MJO) and Convectively Coupled Equatorial Waves (CCEW) phenomena over Indonesia. This research used the same 13-year series of daily TRMM 3B42 V7 derived datasets and ERA-Interim reanalysis model datasets from the European Center for Medium-Range Weather Forecasts (ECMWF) for precipitation forecasts. Three years (2016 to 2018) of the filtered 3B42 and ERA-Interim forecast data was then used to evaluate forecast accuracy by looking at correlation coefficients for forecast leads from day +1 through day +7. The results revealed that rainfall estimation data from 3B42 provides better results for the shorter forecast leads, particularly for MJO, equatorial Rossby (ER), mixed Rossby-gravity (MRG), and inertia-gravity phenomena in zonal wavenumber 1 (IG1), but gives poor correlation for Kelvin waves for all forecast leads. A consistent correlation for all waves was achieved from the filtered ERA-Interim precipitation forecast model, and although this was quite weak for the first forecast leads it did not reach a negative correlation in the later forecast leads except for IG1. Furthermore, Root Mean Square Error (RMSE) was also calculated to complement forecasting skills for both data sources, with the result that residual RMSE for the filtered ERA-Interim precipitation forecast was quite small during all forecast leads and for all wave types. These findings prove that the ERA-Interim precipitation forecast model remains an adequate precipitation model in the tropics for MJO and CCEW forecasting, specifically for Indonesia.

Identification of key parameters producing rainfall

o"kkZ ds eq[; izkpyksa dk irk yxkus ds fy, bl 'kks/k i= ls 'kks/kdrkZvksa us m".kdfVca/kh; o"kkZ ekiu fe’ku ¼Vh- vkj- ,e- ,e-½ mixzg vk¡dM+k vk/kkj dh tk¡p dh gSA bl rF; dks le>us ds mijkUr fd c<+us okys ok;q iklZy ds }kjk ikuh ds ok"ihdj.k] ok"i ds la?kuu vkSj m"ek ÅtkZ ds laogu ls es?k cursa gS vkSj o"kkZ gksrh gSA 'kks/kdrkZvksa us ok;qeaMy dh fofHkUu Å¡pkbZ;ksa ij o"kkZ izfØ;k ds eq[; lg;ksfx;ksa ds :i esa es?k nzo ty ¼lh-,y-MCY;w-½] o"kZ.k ty ¼ih-MCY;w-½ rFkk xqIr m"ek ¼,y-,p-½ ds ckjs esa tkudkjh izkIr djuh vkjaHk dj nh gSSA bu vk¡dM+ksa dks cgq lekJ;.k fun’kZ esa Mkyk x;k gSA ;g ik;k x;k gSS fd o"kkZ vkSj bu izkpyksa esa egRoiw.kZ lglaca/k gSA blls LFkkfir gq, dk;kZRed laca/kksa ls fdlh Hkh le; o"kkZ dk vkdyu fd;k tk ldrk gS c’krZs dkWyeuj lh-,y-MCY;w-] ih-MCY;w- vkSj ,y-,p- eku miyC?k gksaA ,d ;k nks ds LFkku ij bu lHkh rhuksa izkpyksa dks cgq lekJ;.k fun’kZ esa 'kkfey djus ds QyLo:i o"kkZ dk csgrj iwokZuqeku yxk;k tk ldk gSA lh- ,y- MCY;w-] ,y- ,p- vkSj ih- MCY;w- ds chp egRoiw.kZ lglaca/k gSaA In search of the key parameters causing rainfall, the authors have explored Tropical Rainfall Measuring Mission (TRMM) satellite data base. By realizing the fact that evaporation of water, condensation of vapour and transport of heat energy by a rising air parcel are all about formation of cloud and rain, the authors have started their quest considering cloud liquid water (CLW), precipitation water (PW) and latent heat (LH) at different altitudes of the atmosphere as major contributors to rainfall mechanism. These data have been fitted to multiple regressions. It is found that significant correlations exist between rainfall and these parameters. The functional relationships so established are able to estimate surface rainfall at any instant, provided columnar CLW, PW and LH values are available. Inclusion of all the three parameters in multiple regression leads to better predictability of rainfall, instead of one or two. Significant correlations exist between CLW, LH and PW.

Evidence for the breakdown of an Angkorian hydraulic system, and its historical implications for understanding the Khmer Empire

This paper examines the construction and design of a 7-km long embankment, probably builtfor King Jayavarman IV between 928 and 941 CE, as part of a new capital. We calculate thatthe capacities of the outlets were too small, and conclude that the embankment failed, probablywithin a decade of construction, so that the benefits of the reservoir stored by the embankmentand the access road on top of it were lessened substantially. We explain how the design wassub-optimal for construction, and that while the layout had a high aesthetic impact, theprocesses for ensuring structural integrity were poor. Simple and inexpensive steps to securethe weir were not undertaken. We speculate that this early failure may have contributed to thedecision to return the royal court and the capital of the Khmer Empire to the Angkor region,marking a critically important juncture in regional history.Abbreviations: APHRODITE, Asian Precipitation – Highly Resolved Observational DataIntegration Towards Evaluation (of Water Resources); ARI, annual recurrence interval; ASL,above sea level; DIAS, Data Integration and Analysis System; EFEO, École françaised'Extrême-Orient; GPR, ground penetrating radar; HEC-GeoRAS, Hydrologic EngineeringCenter: GIS tools for support of HEC-RAS; HEC-RAS, Hydrologic Engineering Center: RiverAnalysis System; HEC-HMS, Hydrologic Engineering Center: Hydrologic Modeling System;MCS, mesoscale convective system; RMSE, root mean square error; SRTM, NASA ShuttleRadar Topography Mission; TRMM, Tropical Rainfall Measuring Mission

Lightning Climatology and Human Vulnerability to Lightning Hazards in a School Community: A Case Study in Sri Lanka using LIS Data from TRMM Satellite

This study reported lightning climatology and human vulnerability to lightning in a 20 km × 20 km high-density school area in Colombo city in Sri Lanka from 1998 to 2014 using Lightning Imaging Sensor (LIS) flash data of NASA’s Tropical Rainfall Measuring Mission (TRMM). An average annual flash density recorded over the study area was 9.43 flashes km-2 year-1. A maximum of 49% lightning flashes happened during the first inter-monsoon season. There were only 4% lightning flashes that occurred during 06.00-12.00 LT and during 18.00-24.00 LT, it was 67%, whereas 94% of lightning flashes within a day had occurred after 14.00 LT. It is recommended that, without having proper lightning hazard preventive measures, schools in the study area should avoid or minimalize scheduling their outdoor activities in high lightning risk months of April and November. Especially, after-school outdoor activities should be planned with proper safety measures during the aforementioned months as per the diurnal analysis. Moreover, May to September and December to February were the months with the least lightning risk levels. It is recommended to follow the proposed five-level lightning safety guideline which includes, schedule outdoor activities by considering the variation of lightning activities, follow the 30-30 rule whenever required, avoid staying at the most hazardous locations which are vulnerable to lightning accidents, crouching action if required and providing first-aid whenever necessary. Not only for the Sri Lankan context but also the study is crucial and highly applicable for all schools and other institutes especially in other tropical countries.