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Precipitation

About: Precipitation is a research topic. Over the lifetime, 32861 publications have been published within this topic receiving 990496 citations. The topic is also known as: rain & rainfall.


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TL;DR: In this article, it was shown that mesoscale convective systems are triggered by nocturnal downslope flows and by diurnally triggered disturbances propagating away from mountain ranges.
Abstract: [1] Precipitation over and near mountains is not caused by topography but, rather, occurs when storms of a type that can occur anywhere (deep convection, fronts, tropical cyclones) form near or move over complex terrain. Deep convective systems occurring near mountains are affected by channeling of airflow near mountains, capping of moist boundary layers by flow subsiding from higher terrain, and triggering to break the cap when low-level flow encounters hills near the bases of major mountain ranges. Mesoscale convective systems are triggered by nocturnal downslope flows and by diurnally triggered disturbances propagating away from mountain ranges. The stratiform regions of mesoscale convective systems are enhanced by upslope flow when they move over mountains. In frontal cloud systems, the poleward flow of warm-sector air ahead of the system may rise easily over terrain, and a maximum of precipitating cloud occurs over the first rise of terrain, and rainfall is maximum on ridges and minimum in valleys. If the low-level air ahead of the system is stable, blocking or damming occurs. Shear between a blocked layer and unblocked moist air above favors turbulent overturning, which can accelerate precipitation fallout. In tropical cyclones, the tangential winds encountering a mountain range produce a gravity wave response and greatly enhanced upslope flow. Depending on the height of the mountain, the maximum rain may occur on either the windward or leeward side. When the capped boundary layer of the eye of a tropical cyclone passes over a mountain, the cap may be broken with intense convection resulting.

600 citations

Journal ArticleDOI
TL;DR: In this paper, a correction technique is proposed in order to adjust the simulated values according to the observed ones, which is useful to feed impact models which are sensitive to threshold values, but the correction does not reduce, and may enhance in some cases, the uncertainty about the climate projections.

600 citations

Journal ArticleDOI
TL;DR: A model for calculating daily microclimate conditions in mountainous terrain is presented and maximum–minimum daily air temperatures, precipitation, and dew point are extrapolated from valley stations.
Abstract: A model for calculating daily microclimate conditions in mountainous terrain is presented. Maximum–minimum daily air temperatures, precipitation, and dew point are extrapolated from valley stations...

598 citations

Journal ArticleDOI
TL;DR: In this paper, the authors conduct regional climate simulations with and without land-atmosphere coupling for four selected major summer heat waves in 1976, 1994, 2003, and 2005.
Abstract: [1] Most of the recent European summer heat waves have been preceded by a pronounced spring precipitation deficit. The lack of precipitation and the associated depletion of soil moisture result in reduced latent cooling and thereby amplify the summer temperature extremes. In order to quantify the contribution of land-atmosphere interactions, we conduct regional climate simulations with and without land-atmosphere coupling for four selected major summer heat waves in 1976, 1994, 2003, and 2005. The coupled simulation uses a fully coupled land-surface model, while in the uncoupled simulation the mean seasonal cycle of soil moisture is prescribed. The experiments reveal that land-atmosphere coupling plays an important role for the evolution of the investigated heat waves both through local and remote effects. During all simulated events soil moisture-temperature interactions increase the heat wave duration and account for typically 50–80% of the number of hot summer days. The largest impact is found for daily maximum temperatures during heat wave episodes.

597 citations

Journal ArticleDOI
TL;DR: In this paper, the authors used observations and high-resolution modeling to show that rainfall changes related to rising temperatures depend on the available atmospheric moisture, and that the scaling rates between extreme precipitation and temperature are strongly dependent on the region, temperature, and moisture availability.
Abstract: Climate change is causing increases in extreme rainfall across the United States. This study uses observations and high-resolution modelling to show that rainfall changes related to rising temperatures depend on the available atmospheric moisture. Extreme precipitation intensities have increased in all regions of the Contiguous United States (CONUS)1 and are expected to further increase with warming at scaling rates of about 7% per degree Celsius (ref. 2), suggesting a significant increase of flash flood hazards due to climate change. However, the scaling rates between extreme precipitation and temperature are strongly dependent on the region, temperature3, and moisture availability4, which inhibits simple extrapolation of the scaling rate from past climate data into the future5. Here we study observed and simulated changes in local precipitation extremes over the CONUS by analysing a very high resolution (4 km horizontal grid spacing) current and high-end climate scenario that realistically simulates hourly precipitation extremes. We show that extreme precipitation is increasing with temperature in moist, energy-limited, environments and decreases abruptly in dry, moisture-limited, environments. This novel framework explains the large variability in the observed and modelled scaling rates and helps with understanding the significant frequency and intensity increases in future hourly extreme precipitation events and their interaction with larger scales.

595 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20237,839
202214,365
20212,302
20201,964
20191,942
20181,773