26 research outputs found
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Climate change over Leh (Ladakh), India
Mountains over the world are considered as the indicators of climate change. The Himalayas are comprised of five ranges, viz., Pir Panjal, Great Himalayas, Zanskar, Ladhak, and Karakorum. The Ladakh region lies in the northernmost state of India, Jammu and Kashmir, in the Ladhak range. It has a unique cold-arid climate and lies immediately south of the Karakorum range. With scarce water resources, such regions show high sensitivity and vulnerability to the change in climate and need urgent attention. The objective of this study is to understand the climate of the Ladakh region and to characterize its changing climate. Using different temperature and precipitation datasets over Leh and surrounding regions, we statistically analyze the current trends of climatic patterns over the region. The study shows that the climate over Leh shows a warming trend with reduced precipitation in the current decade. The reduced average seasonal precipitation might also be associated with some indications of reducing number of days with higher precipitation amounts over the region
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Numerical simulation of a rare winter hailstorm event over Delhi, India on 17 January 2013
This study analyzes the cause of the rare occurrence of a winter hailstorm over New Delhi/NCR (National Capital Region), India. The absence of increased surface temperature or low level of moisture incursion during winter cannot generate the deep convection required for sustaining a hailstorm. Consequently, NCR shows very few cases of hailstorms in the months of December-January-February, making the winter hail formation a question of interest. For this study, a recent winter hailstorm event on 17 January 2013 (16:00–18:00 UTC) occurring over NCR is investigated. The storm is simulated using the Weather Research and Forecasting (WRF) model with the Goddard Cumulus Ensemble (GCE) microphysics scheme with two different options: hail and graupel. The aim of the study is to understand and describe the cause of hailstorm event during over NCR with a comparative analysis of the two options of GCE microphysics. Upon evaluating the model simulations, it is observed that the hail option shows a more similar precipitation intensity with the Tropical Rainfall Measuring Mission (TRMM) observation than the graupel option does, and it is able to simulate hail precipitation. Using the model-simulated output with the hail option; detailed investigation on understanding the dynamics of hailstorm is performed. The analysis based on a numerical simulation suggests that the deep instability in the atmospheric column led to the formation of hailstones as the cloud formation reached up to the glaciated zone promoting ice nucleation. In winters, such instability conditions rarely form due to low level available potential energy and moisture incursion along with upper level baroclinic instability due to the presence of a western disturbance (WD). Such rare positioning is found to be lowering the tropopause with increased temperature gradient, leading to winter hailstorm formation
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Predictability of South China Sea summer monsoon onset
Predicting monsoon onset is crucial for agriculture and socioeconomic planning in countries where millions rely on the timely arrival of monsoon rains for their livelihoods. In this study we demonstrate useful skill in predicting year to year variations in South China Sea summer monsoon onset at up to 3 months lead time using the GloSea5 seasonal forecasting system. The main source of predictability comes from skilful prediction of Pacific sea surface temperatures associated with El Niño and La Niña. The South China Sea summer monsoon onset is a known indicator of the broadscale seasonal transition that represents the first stage of the onset of the Asian summer monsoon as a whole. Subsequent development of rainfall across East Asia is influenced by sub-seasonal variability and synoptic events that reduce predictability, but interannual variability in the broadscale monsoon onset for East Asian summer monsoon still provides potentially useful information for users about possible delays or early occurrence of the onset of rainfall over East Asia
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Cloudbursts in Indian Himalayas: a review
Cloudbursts in and around the southern rim of the Indian Himalayas are elusive in terms of their position and time of occurrences. Most of the reported cloudbursts are in the interior of the Himalayas and hence their observation itself is limited. Most of these events are reported once their affect in terms of loss to life and property is experienced in the downstream habitats. In addition, they are mostly associated with flash floods as an impact of the torrential precipitation. The principal understanding of the cloudburst is associated with sudden heavy deluge of precipitation in very less time interval over a very small area. Except this understanding and India Meteorology Department (IMD) definition of > 100 mm/h precipitation over a geographical region of approximately 20–30 km2, nothing much else is known about these events. There are a very few studies carried out on understanding of these events. Present paper synthesizes the available information and research on cloudburst events and tries to define it based on associated dynamics, thermodynamics and physical processes leading to a cloudburst event. Thus in the present work, characterizations and impacts of cloudburst leading from precipitation to dynamical to thermodynamical to large scale forcings to orographical forcings to followed geomorphology to impacts are intertwined to present comprehensive portray of it. Most of the cloudburst events are seen occurring in the elevation range of 1000 m to 2500 m within the valley folds of the southern rim of the Indian Himalayas. Apart from some of the large scale flow shown by few of the studies, it is found that cloudburst events are convectively triggered followed by orographically locked systems. These intertwined mechanisms lead cloudburst events to form. Amiss of any one of these mechanisms will not lead the cloudburst mechanism to form. These interactions in the present paper established the vagaries associated with the cloudburst events
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Subseasonal prediction performance for austral summer South American rainfall
Skilful and reliable predictions of week-to-week rainfall variations in South America, two to three weeks ahead, are essential to protect lives, livelihoods and ecosystems. We evaluate forecast performance for weekly rainfall in extended austral summer (November-March) in four contemporary subseasonal systems, including a new Brazilian model, at 1-5 week leads for 1999-2010. We measure performance by the correlation coefficient (in time) between predicted and observed rainfall; we measure skill by the Brier Skill Score for rainfall terciles against a climatological reference forecast. We assess unconditional performance (i.e., regardless of initial condition) and conditional performance based on the initial phase of the Madden-Julian Oscillation (MJO) and the El Nino--Southern Oscillation (ENSO). All models display substantial mean rainfall biases, including dry biases in Amazonia and wet biases near the Andes, which are established by Week 1 and vary little thereafter. Unconditional performance extends to Week 2 in all regions except for Amazonia and the Andes, but to Week 3 only over northern, northeastern and southeastern South America. Skill for upper- and lower-tercile rainfall extends only to Week 1. Conditional performance is not systematically or significantly higher than unconditional performance; ENSO and MJO events provide limited "windows of opportunity" for improved S2S predictions that are region- and model-dependent. Conditional performance may be degraded by errors in predicted ENSO and MJO teleconnections to regional rainfall, even at short lead times
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Indian summer monsoon onset forecast skill in the UK Met Office initialized coupled seasonal forecasting system (GloSea5-GC2)
Accurate and precise forecasting of the Indian monsoon is important for the socio-economic security of India, with improvements in agriculture and associated sectors from prediction of the monsoon onset. In this study we establish the skill of the UK Met Office coupled initialized global seasonal forecasting system, GloSea5-GC2, in forecasting Indian monsoon onset. We build on previous work that has demonstrated the good skill of GloSea5 at forecasting interannual variations of the seasonal mean Indian monsoon using measures of large-scale circulation and local precipitation. We analyze the summer hindcasts from a set of three springtime start-dates in late April/early May for the 20-year hindcast period (1992-2011). The hindcast set features at least fifteen ensemble members for each year and is analyzed using five different objective monsoon indices. These indices are designed to examine large and local-scale measures of the monsoon circulation, hydrological changes, tropospheric temperature gradient, or rainfall for single value (area-averaged) or grid-point measures of the Indian monsoon onset. There is significant correlation between onset dates in the model and those found in reanalysis. Indices based on large-scale dynamic and thermodynamic indices are better at estimating monsoon onset in the model rather than local-scale dynamical and hydrological indices. This can be attributed to the model's better representation of large-scale dynamics compared to local-scale features. GloSea5 may not be able to predict the exact date of monsoon onset over India, but this study shows that the model has a good ability at predicting category-wise monsoon onset, using early, normal or late tercile categories. Using a grid-point local rainfall onset index, we note that the forecast skill is highest over parts of central India, the Gangetic plains, and parts of coastal India - all zones of extensive agriculture in India. El Niño Southern Oscillation (ENSO) forcing in the model improves the forecast skill of monsoon onset when using a large-scale circulation index, with late monsoon onset coinciding with El Niño conditions and early monsoon onset more common in La Niña years. The results of this study suggest that GloSea5's ensemble-mean forecast may be used for reliable Indian monsoon onset prediction a month in advance despite systematic model errors
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Inter-comparison of physical processes associated with winter and non-winter hailstorms using the weather research and forecasting (WRF) model
Hailstorms are more frequent during non-winter whereas rare during winters due to the absence of increased surface temperature or low level of moisture incursion. This study shows a inter-comparison in the dynamics of winter and non-winter hailstorms reported over New Delhi, India using numerical simulation method. Non-winter hailstorms, formed due to increased instability due to low level convection and moisture incursion. Whereas rare instability conditions form due to low level available potential energy and moisture incursion along with upper level baroclinic instability due to the presence of western disturbance, led to winter hailstorm
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