Orographic Rainfall

Ever wondered how a mountain range can create both a lush forest on one side and a desert on the other? Dive into the fascinating world of meteorology with the Interactive Orographic Cloud Formation Simulator! This dynamic tool brings the atmospheric process of orographic lifting to life.

You can take control of key variables like wind speed, air moisture, and mountain height to watch exactly how air cools as it rises, leading to condensation, cloud formation, and precipitation. See the rain shadow effect form in real-time, explaining the vast differences in climate across a mountain range.

Textbooks often use confusing cross-sections to explain the rain shadow effect; this simulator lets you control the weather. By visiting the link, you gain access to an interactive tool that allows you to manipulate atmospheric dynamics and observe the cause and effect directly.

Understanding long-term precipitation patterns in semi-arid river basins is vital for sustainable water resource management, especially under the influence of global climate change. This study investigates the spatiotemporal dynamics of precipitation concentration, extreme precipitation events, and meteorological droughts in the Shilabati River basin, West Bengal, India, from 1970 to 2022. High-resolution daily precipitation and temperature datasets from the India Meteorological Department (IMD) were analyzed using key climate indices, including the Precipitation Concentration Index (PCI), Seasonality Index (SI), and drought indicators such as the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). The IMD datasets are bias-corrected and validated against observed data. Serial independence was assessed through the autocorrelation test, and change points were detected using Mann-Whitney-Pettitt (MWP). The trends and magnitudes were evaluated using the Modified Mann-Kendall (MMK) test and Sen's slope estimator. Previous studies have predominantly focused on administrative unit-based analyses, often neglecting basin-level investigations. Addressing this gap, the study reveals a significant decline (p < 0.05) in annual precipitation, accompanied by marked interannual variability. Elevated PCI values (> 15) and high seasonality (SI = 0.80-0.99) above the state average (PCI = 10-15; SI = 0.66-0.99) highlight strong monsoonal influence, with pronounced seasonality and extended dry spells. Extreme precipitation events are concentrated downstream, with higher values in indices such as, Rx5day, R10mm, R20mm, and PRCPTOT, while severe drought conditions dominate the middle to upper-middle basins. These insights provide a nuanced understanding of regional precipitation and drought patterns, offering critical inputs for policy-making, water resource management, and sustainable land-use planning. Collaborative efforts with stakeholders to implement drought management and community-based adaptation strategies are essential to address the ecological and socioeconomic challenges specific to the Shilabati basin.

Understanding long-term precipitation patterns in semi-arid river basins is vital for sustainable water resource management, especially under the influence of global climate change. This study investigates the spatiotemporal dynamics of precipitation concentration, extreme precipitation events, and meteorological droughts in the Shilabati River basin, West Bengal, India, from 1970 to 2022. High-resolution daily precipitation and temperature datasets from the India Meteorological Department (IMD) were analyzed using key climate indices, including the Precipitation Concentration Index (PCI), Seasonality Index (SI), and drought indicators such as the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). The IMD datasets are bias-corrected and validated against observed data. Serial independence was assessed through the autocorrelation test, and change points were detected using Mann-Whitney-Pettitt (MWP). The trends and magnitudes were evaluated using the Modified Mann-Kendall (MMK) test and Sen's slope estimator. Previous studies have predominantly focused on administrative unit-based analyses, often neglecting basin-level investigations. Addressing this gap, the study reveals a significant decline (p < 0.05) in annual precipitation, accompanied by marked interannual variability. Elevated PCI values (> 15) and high seasonality (SI = 0.80-0.99) above the state average (PCI = 10-15; SI = 0.66-0.99) highlight strong monsoonal influence, with pronounced seasonality and extended dry spells. Extreme precipitation events are concentrated downstream, with higher values in indices such as, Rx5day, R10mm, R20mm, and PRCPTOT, while severe drought conditions dominate the middle to upper-middle basins. These insights provide a nuanced understanding of regional precipitation and drought patterns, offering critical inputs for policy-making, water resource management, and sustainable land-use planning. Collaborative efforts with stakeholders to implement drought management and community-based adaptation strategies are essential to address the ecological and socioeconomic challenges specific to the Shilabati basin.

The investigation of extreme weather phenomena is an important scientific field that incorporates multiple disciplines due to their significant impacts on various sectors and society as a whole. There is evidence to support the occurrence of severe weather events in different regions of the world. In India, major precipitation events, such as the Mumbai floods in 2005 and the Kerala floods in 2018, often occur during the southwest monsoon season, leading to significant impacts. This statement is also applicable to states like Arunachal Pradesh, Nagaland, and Manipur in the northeast region. Intense precipitation events caused significant impacts in Meghalaya from June 16th to June 18th, 2022.These events resulted in a significant socioeconomic and human impact, including infrastructure damage, displacement of communities, and around 90 reported fatalities in Assam and Meghalaya. These two states are susceptible to flooding and erosion, and they consistently face intense and periodic floods on an annual basis. Analysis of the 2022 rainfall data reveals that over 4.8 million individuals were adversely impacted in the majority of districts in Assam and Meghalaya. Specifically, 79 % of the total 43 districts were affected. This study analyzed the meteorological aspects of exceptional heavy rainfall events in Meghalaya from June 16th to 18th, 2022, to understand their significant impact on the environment and society. The extreme weather event in Meghalaya was a result of a well-marked low pressure area, a significant influx of moisture from the Bay of Bengal (BoB), favourable dynamics and thermodynamics conditions, and a supportive cloud top temperature (CTT) that collectively intensified the heavy rainfall. The study's findings can provide valuable insights for disaster managers and forecasters, enabling them to better prepare for and respond to extreme rainfall events in the northeast region of the country.

This study aims to perform observational data analyses, including European Centre for Medium-Range Weather Forecasts data, radar reflectivity, rainfall data, and numerical simulations with the Weather Research and Forecasting model to examine the orographic effects on a localized heavy rainfall episode which produced up to 204 and 161.5 mm over southwestern Taiwan on 27 and 28 June 2008, respectively. We found that the continuous inland-transport of moist air or inland-movement of convection from the nearby ocean to southwestern Taiwan occur on both days. The orographic lifting on the moist air and convection generates heavy rainfall over sloped areas on 27 June when the relatively fast southwesterly low-level wind prevails (~10 m s -1 ). The cool air near the foothill facilitates the new development of convection on the upstream side of the old convection over the slope and produces heavy rainfall over lowlands near the foothill. On 28 June, the convection, which is embedded in a relatively slow southwesterly moist airflow, is enhanced over the low-level convergence areas in the lowlands due to the prevailing southwesterly wind. This wind is deflected by the orographic effect and produces heavy rainfall. In addition, the cool air from sloped areas enhances the offshore flow which interacts with the prevailing wind to strengthen the low-level convergence over lowlands and coasts.

Somalia has a long history of experiencing frequent droughts. Drought is one of the worst natural hazards in Somalia and affects the lives and livelihoods of millions of Somalis, yet limited drought research is done in the country. This study investigated long-term trends and emerging signals of change in drought and its meteorological drivers from observations in Somalia's rainy seasons of MAM and SON from 1901 to 2018. Trends were assessed using a modified Mann-Kendall trend test with Sen's slope estimator. The signal-to-noise ratio of drought and its meteorological drivers relative to the early industrial period were also estimated by regressing these local climate variations onto smoothed annual GMST. The results of trend analysis revealed statistically significant increases in drought and decreasing precipitation for the MAM season in Somaliland and east and central Somalia, while in south Somalia, these trends were not significant. For the SON season, drought increased slightly in Somaliland and decreased slightly in southern Somalia. The results of regression analysis showed that no signal of drought and precipitation change emerged from the background noise of variability, while unusual (S/N > 1) seasonal temperature and PET conditions emerged relative to the early industrial era in the observations in Somalia. Across the country, the MAM SPI-3, SPEI-3, precipitation, temperature, and PET had a statistically significant relationship with the GMST except for the MAM precipitation in the southern region of Somalia, while in the SON season, no significant relationship with the GMST was observed. The results suggest that the decreasing trend in MAM precipitation was the main driver of the increasing MAM seasonal drought, while the increasing PET driven by the rising temperature was the main driver of the SON seasonal drought. The results of this study provide critical information for assessing climate change impacts, planning for adaptation, and communicating with the public.

A dinâmica Tropical esta bastante atrelada a valores pluviometricos elevados, que podem deflagrar transtornos a populacao e a economia local, devido ao desencadeamento de movimentos gravitacionais de massa (MGM) e alagamentos de cursos fluviais. O presente trabalho tem por objetivo analisar a geneses das chuvas no litoral sul do estado do Rio de Janeiro (Municipios de Parati, Angra dos Reis, Rio Claro e Mangaratiba) no periodo correspondente aos anos de 1996 a 2014, que corresponde a serie mais completa de dados encontrada, em busca da definicao de limiares de chuvas que estejam relacionados a estes eventos.

Drought, a recurring natural phenomenon in South Asia's monsoon climate, presents challenges in delineating its spatio-temporal patterns within complex topographies. This study investigated the impact of the orographic barrier in the rice-dominated agricultural region of northeastern India and Bangladesh on drought characteristics during 1951-2020, employing the relative Standardised Precipitation Index (rSPI) and relative Standardised Precipitation-Evapotranspiration Index (rSPEI) across 3-, 6-, and 12month scales. The results indicate that even in the rainiest region of the world, droughts extend beyond the limits of the dry season inherent in the monsoon regime. These mostly regional droughts exhibit weak correlations with the core of the Indian subcontinent and other parts of Bangladesh. The region's orographic barrier has a greater influence on drought intensity than on frequency. The rSPI index, which depends solely on rainfall, may overestimate drought intensity and frequency in regions with high seasonal/annual rainfall and substantial intermonthly variability. In contrast, the rSPEI index, which depends on both rainfall and potential evapotranspiration (PET), better reflects the spatial variation of drought in complex terrain, identifying the leeward hinterland of the orographic barrier as the most drought-prone area. The two indices give similar results for drought characteristics away from the barrier. Furthermore, the orographic barrier exerts a negligible influence on the trends in rSPI and rSPEI. Principal component analysis (PCA) highlights the influences of the rainfall coefficient of variation and elevation on rSPI, while the PET coefficient of variation strongly influences rSPEI. Strategies to minimise the adverse effects of drought in complex topography and year-round cropping should be local and season-specific. These include using shorter-growing, drought-resistant rice varieties and adjusting planting schedules in rain shadow areas during the summer monsoon. These efforts should be complemented by integrating indigenous irrigation methods with modern practices such as roof water harvesting and tube wells in winter.

A presente pesquisa aborda a relação entre precipitação e altimetria na área situada entre o Vale do Rio Tietê (Depressão do Médio Tietê) e a Serra da Mantiqueira (Planalto de Serra Negra/Lindóia), no estado de São Paulo. A análise foi realizada por meio da elaboração de um Modelo Digital de Terreno (MDT), produzido utilizando-se o software Surfer, interpolando dados referentes à altitude e pluviosidade. Os mapas e os dados avaliados revelam a influência da orografia na intensificação da pluviometria do local em questão, mais marcadamente nos períodos mais chuvosos.

In the EFFS Project, an attempt has been made to develop a general framework to study the predictability of severe convective rainfall events in the presence of orography. Convective activity is embedded in orographic rainfall and can be thought as the result of several physical mechanisms. Quantifying its variability on selected area and time scales requires choosing the best physical representation of the rainfall variability on these scales. The main goal was (i) to formulate a meaningful set of experiments to compute the oscillation of variance due to convection inside model forecasts in the presence of orography and (ii) to give a statistical measure of it that might be of value in the operational use of atmospheric data. The study has been limited to atmospheric scales that span the atmosphere from 2 to 200 km and has been focused on extreme events with deep convection. Suitable measures of the changing of convection in the presence of orography have been related to the physical properties of the rainfall environment. Preliminary results for the statistical variability of the convective field are presented.

TANDARD normals of rainfall (SNOR) in Israel show large local vari-S abilities which might be attributed to the topographical parameters of the gauging system. An obvious topographical parameter is the station elevation. Williams and Peck (1962) examined the precipitation pattern in the Wasatch mountain region in the United States and found that west of the divide each rise of 100 m in elevation accompanied an increase of 46 mm in SNOR. Duckstein, Fogel and Thomas ( I 973) have pointed out that increased rainfall on high elevation areas might be connected to two effects; ( I ) increase of rain events on high elevation areas, (2) increase of rainfall quantity per event on high elevation areas. Assuming linearity with elevation of these two effects they have found a weak quadratic dependence of rainfall quantities on elevation. On the average, it was found that for summer rains on the Santa Catalina mountain in the United States, each rise of 100 m in elevation induced an increase of 8.2 mm in SNOR. Bradley and Barry (1973) have found 76 per cent correlation between SNOR values and height for south-west Colorado, United States. Each 100 m rise resulted in 25 mm increase in SNOR. Sakakibara and Takeda (1973) have analysed the orographic effects on rainfall quantities of Typhoon number 7002.

This study aims to perform observational data analyses, including European Centre for Medium-Range Weather Forecasts data, radar reflectivity, rainfall data, and numerical simulations with the Weather Research and Forecasting model to examine the orographic effects on a localized heavy rainfall episode which produced up to 204 and 161.5 mm over southwestern Taiwan on 27 and 28 June 2008, respectively. We found that the continuous inland-transport of moist air or inland-movement of convection from the nearby ocean to southwestern Taiwan occur on both days. The orographic lifting on the moist air and convection generates heavy rainfall over sloped areas on 27 June when the relatively fast southwesterly low-level wind prevails (~10 m s −1). The cool air near the foothill facilitates the new development of convection on the upstream side of the old convection over the slope and produces heavy rainfall over lowlands near the foothill. On 28 June, the convection, which is embedded in a relatively slow southwesterly moist airflow, is enhanced over the low-level convergence areas in the lowlands due to the prevailing southwesterly wind. This wind is deflected by the orographic effect and produces heavy rainfall. In addition, the cool air from sloped areas enhances the offshore flow which interacts with the prevailing wind to strengthen the low-level convergence over lowlands and coasts.

A high-resolution meso-7 scale indexing of the orographic precipitation over the Judean Mountains in Israel suggests a positive urban precipitation anomaly in Jerusalem. The urban rainfall enhancement for three case studies is found to be 20-30 per cent as compared to only about 10% for the annual normals. The role of the urban 'heat island' and the larger supply of artificial nuclei is discussed. The method presented here is a primary attempt to separate quantitatively urban precipitation effects over highly complex terrain, by applying a physical model.

Orographic rainfall is usually occurred in Sylhet and adjoining area, Bangladesh. It is very important to study the thermodynamic features of orographic rainfall. An attempt has been made to simulate a heavy rainfall event of 17 May 2016 over Bangladesh using WRF model. The simulation was conducted using WRF-ARW for 48 and 72 hours. The model was run on a single domain of 10 km horizontal resolution with WRF Single-Moment 3-class (WSM3) microphysics and Kain-Fritsch cumulus schemes. The model performance was evaluated by examining the different predicted parameters like mean sea level pressure, , wind pattern, upper and lower level circulations, moisture, wind shear, vorticity, Maximum Convective Available Potential Energy (MCAPE) and rainfall pattern. The present results indicate that the WRF model with high horizontal resolution was able to simulate the heavy rainfall event reasonably well. The analysis shows that the CAPE of magnitude 1500-2500 J/Kg, positive vorticity in order of (6-10) x10-5 s-1 and relative humidity of 80-100% up to 200 hPa level are responsible for the occurring of heavy rainfall.