scholarly journals Sensitivities of Extreme Precipitation to Global Warming Are Lower over Mountains than over Oceans and Plains

2016 ◽  
Vol 29 (13) ◽  
pp. 4779-4791 ◽  
Author(s):  
Xiaoming Shi ◽  
Dale Durran
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Static Stability ◽  
Induced Response ◽  
Model Simulations ◽  
Fractional Rate ◽  
Rate Of Increase ◽  
Climate Model Simulations ◽  
Almost All

Abstract Climate-model simulations predict an intensification of extreme precipitation in almost all areas of the world under global warming. Local variations in the magnitude of this intensification are evident in these simulations, but most previous efforts to understand the factors responsible for the changes in extreme precipitation focused on zonal averages and neglected zonal variations, leading to uncertainties in the understanding and estimation of regional responses. Here the spatial heterogeneity of the warming-induced response of midlatitude extreme precipitation is studied in climate-model simulations with idealized orography on the western margins of otherwise flat continents. It is shown that the sensitivity of extreme precipitation to warming (i.e., its fractional rate of increase in intensity with global-mean surface temperature) is ~3% K−1 lower over the mountains than the oceans and plains. This difference in sensitivity is primarily produced by differences in the dynamics governing vertical ascent over the three regions. In these extreme events, mountain-wave dynamics control the moist ascent over the mountains, and the sensitivity of this ascent to global warming is mainly controlled by changes in upper-level dry static stability and the cross-mountain winds. In contrast, midlatitude cyclone dynamics govern moist ascent over the oceans and plains. Ascending motions in intense midlatitude cyclones are sensitive to the ratio of the moist static stability in their saturated cores to the dry stability in surrounding regions. This ratio decreases in the warmer world, intensifying the maximum vertical velocities while reducing the horizontal extent of the regions of the rising air within the cyclone.

scholarly journals Weather extremes over Europe under 1.5 and 2.0 °C global warming from HAPPI regional climate ensemble simulations

2021 ◽  
Vol 12 (2) ◽  
pp. 457-468
Author(s):  
Kevin Sieck ◽  
Christine Nam ◽  
Laurens M. Bouwer ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Global Warming ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Apparent Temperature ◽  
Climate Indices ◽  
Weather Extremes ◽  
Near Surface ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. This paper presents a novel dataset of regional climate model simulations over Europe that significantly improves our ability to detect changes in weather extremes under low and moderate levels of global warming. This is a unique and physically consistent dataset, as it is derived from a large ensemble of regional climate model simulations. These simulations were driven by two global climate models from the international HAPPI consortium. The set consists of 100×10-year simulations and 25×10-year simulations, respectively. These large ensembles allow for regional climate change and weather extremes to be investigated with an improved signal-to-noise ratio compared to previous climate simulations. To demonstrate how adaptation-relevant information can be derived from the HAPPI dataset, changes in four climate indices for periods with 1.5 and 2.0 ∘C global warming are quantified. These indices include number of days per year with daily mean near-surface apparent temperature of >28 ∘C (ATG28); the yearly maximum 5-day sum of precipitation (RX5day); the daily precipitation intensity of the 50-year return period (RI50yr); and the annual consecutive dry days (CDDs). This work shows that even for a small signal in projected global mean temperature, changes of extreme temperature and precipitation indices can be robustly estimated. For temperature-related indices changes in percentiles can also be estimated with high confidence. Such data can form the basis for tailor-made climate information that can aid adaptive measures at policy-relevant scales, indicating potential impacts at low levels of global warming at steps of 0.5 ∘C.

Exposure analysis of Chinese railways under the Change of Extreme-Precipitation in the future

2020 ◽  
Author(s):  
Jing Zhao ◽  
Kai liu ◽  
Ming Wang
Keyword(s):  
Global Warming ◽  
Return Period ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Precipitation Amount ◽  
Extreme Rainfall ◽  
Railway Planning ◽  
The Future ◽  
Railway System ◽  
Climate Model Simulations

<p>Abstract: Rainfall-induced disaster is the most frequent disaster affected Chinese Railway System. Climate change will lead to more extreme rainfall in the future. A better understanding of extreme precipitation in the future and the exposure of railway infrastructures to extreme precipitation will facilitate railway planning and disaster risk management. This paper employs climate model simulations to calculate the changes of the extreme precipitation under different global warming scenarios. The return periods of the present 50-yr/100-yr return-period precipitation amount in the future are obtained. Based on this, the changes of the exposure of Chinese railways to extreme precipitation are analyzed. The results reveal that 58.61% (55.46) of China’s region will experience an increase in the 50-yr(100-yr) return-period precipitation under 1.5°C warming in comparison with the present period (2001–2020), the value will be 64.44% and 59.53% due to the additional 0.5°C warming. By calculating the exposure of Chinese railways, we found that 28.49% (32.15) of China's railways are in the region where 50-yr return-period rainfall at this stage will occur less than 20 years under 1.5°C (2.0°C) warming, and 36.85% (41.39)of China's railways are in the region where 100-yr return-period rainfall at this stage will occur less than 50 years under 1.5°C (2.0°C) warming in the future. This study quantified the exposure of China’s railway to extreme precipitation under the 1.5°C/2.0°C global warming. The results provided in this study have profound significance for the fortification planning of China's railway system for rainfall-induced disasters and provide useful experience for other countries.</p>

scholarly journals Diagnosing ENSO and Global Warming Tropical Precipitation Shifts Using Surface Relative Humidity and Temperature

2018 ◽  
Vol 31 (4) ◽  
pp. 1413-1433 ◽  
Author(s):  
Alexander Todd ◽  
Matthew Collins ◽  
F. Hugo Lambert ◽  
Robin Chadwick
Keyword(s):  
Global Warming ◽  
Relative Humidity ◽  
Climate Model ◽  
Southern Oscillation ◽  
Precipitation Change ◽  
Method Performance ◽  
Model Simulations ◽  
Tropical Precipitation ◽  
Climate Model Simulations ◽  
Precipitation Changes

Large uncertainty remains in future projections of tropical precipitation change under global warming. A simplified method for diagnosing tropical precipitation change is tested here on present-day El Niño–Southern Oscillation (ENSO) precipitation shifts. This method, based on the weak temperature gradient approximation, assumes precipitation is associated with local surface relative humidity (RH) and surface air temperature (SAT), relative to the tropical mean. Observed and simulated changes in RH and SAT are subsequently used to diagnose changes in precipitation. Present-day ENSO precipitation shifts are successfully diagnosed using observations (correlation r = 0.69) and an ensemble of atmosphere-only (0.51 ≤ r ≤ 0.8) and coupled (0.5 ≤ r ≤ 0.87) climate model simulations. RH ( r = 0.56) is much more influential than SAT ( r = 0.27) in determining ENSO precipitation shifts for observations and climate model simulations over both land and ocean. Using intermodel differences, a significant relationship is demonstrated between method performance over ocean for present-day ENSO and projected global warming ( r = 0.68). As a caveat, the authors note that mechanisms leading to ENSO-related precipitation changes are not a direct analog for global warming–related precipitation changes. The diagnosis method presented here demonstrates plausible mechanisms that relate changes in precipitation, RH, and SAT under different climate perturbations. Therefore, uncertainty in future tropical precipitation changes may be linked with uncertainty in future RH and SAT changes.

scholarly journals Global Warming and Western North Pacific Typhoon Activity from an Observational Perspective

2004 ◽  
Vol 17 (23) ◽  
pp. 4590-4602 ◽  
Author(s):  
Johnny C. L. Chan ◽  
Kin Sik Liu
Keyword(s):  
Global Warming ◽  
El Niño ◽  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
Climate Model ◽  
El Nino ◽  
Interannual Variations ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract Based on results from climate model simulations, many researchers have suggested that because of global warming, the sea surface temperature (SST) will likely increase, which will then lead to an increase in the intensity of tropical cyclones (TCs). This paper reports results of a study of the relationship between SST and observed typhoon activity (which is used as a proxy for the intensity of TCs averaged over a season) over the western North Pacific (WNP) for the past 40 yr. The average typhoon activity over a season is found to have no significant relationship with SST in the WNP but increases when the SST over the equatorial eastern Pacific Ocean is above normal. The mean annual typhoon activity is generally higher (lower) during an El Niño (La Niña) year. Such interannual variations of typhoon activity appear to be largely constrained by the large-scale atmospheric factors that are closely related to the El Niño–Southern Oscillation (ENSO) phenomenon. These large-scale dynamic and thermodynamic factors include low-level relative vorticity, vertical wind shear, and moist static energy. Such results are shown to be physically consistent with one another and with those from previous studies on the interannual variations of TC activity. The results emphasize the danger of drawing conclusions about future TC intensity based on current climate model simulations that are not designed to make such predictions.

scholarly journals Mechanisms of Global Warming Impacts on Robustness of Tropical Precipitation Asymmetry

2008 ◽  
Vol 21 (21) ◽  
pp. 5585-5602 ◽  
Author(s):  
Pei-Hua Tan ◽  
Chia Chou ◽  
Jien-Yi Tu
Keyword(s):  
Global Warming ◽  
Water Vapor ◽  
Climate Model ◽  
Hadley Circulation ◽  
The Other ◽  
Multimodel Ensemble ◽  
Model Simulations ◽  
Tropical Precipitation ◽  
Precipitation Anomalies ◽  
Climate Model Simulations

Abstract Hemispherically and temporally asymmetric tropical precipitation responses to global warming are evaluated in 13 different coupled atmosphere–ocean climate model simulations. In the late boreal summer, hemispherical averages of the tropical precipitation anomalies from the multimodel ensemble show a strong positive trend in the Northern Hemisphere and a weak negative trend in the Southern Hemisphere. In the late austral summer, on the other hand, the trends are reversed. This implies that the summer hemisphere becomes wetter and the winter hemisphere becomes a little drier in the tropics. Thus, the seasonal range of tropical precipitation, differences between wet and dry seasons, is increased. Zonal averages of the precipitation anomalies from the multimodel ensemble also reveal a meridional movement, which basically follows the seasonal migration of the main convection zone. Similar asymmetric features can be found in all 13 climate model simulations used in this study. Based on the moisture budget analysis, the vertical moisture advection associated with mean circulation is the main contribution for the robustness of the asymmetric distribution of the tropical precipitation anomalies. Under global warming, tropospheric water vapor increases as the temperature rises and most enhanced water vapor is in the lower troposphere. The ascending motion of the Hadley circulation then transports more water vapor upward, that is, anomalous moisture convergence, and enhances precipitation over the main convection zones. On the other hand, the thermodynamic effect associated with the descending motion of the Hadley circulation, that is, anomalous moisture divergence, reduces the precipitation over the descending regions.

scholarly journals Return levels of sub-daily extreme precipitation over Europe

2020 ◽  
Author(s):  
Benjamin Poschlod ◽  
Ralf Ludwig ◽  
Jana Sillmann
Keyword(s):  
Observational Data ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Internal Variability ◽  
Return Level ◽  
Data Set ◽  
Model Simulations ◽  
Return Levels ◽  
Climate Model Simulations ◽  
Precipitation Events

Abstract. Information on the frequency and intensity of extreme precipitation is required by public authorities, civil security departments and engineers for the design of buildings and the dimensioning of water management and drainage schemes. Especially for sub-daily resolution, at which many extreme precipitation events occur, the observational data are sparse in space and time, distributed heterogeneously over Europe and often not publicly available. We therefore consider it necessary to provide an impact-orientated data set of 10-year rainfall return levels over Europe based on climate model simulations and evaluate its quality. Hence, to standardize procedures and provide comparable results, we apply a high-resolution single-model large ensemble (SMILE) of the Canadian Regional Climate Model version 5 (CRCM5) with 50 members in order to assess the frequency of heavy precipitation events over Europe between 1980 and 2009. The application of a SMILE enables a robust estimation of extreme rainfall return levels with the 50 members of 30-year climate simulations providing 1500 years of rainfall data. As the 50 members only differ due to the internal variability of the climate system, the impact of internal variability on the return level values can be quantified. We present 10-year rainfall return levels of hourly to 24-hourly duration with a spatial resolution of 0.11° (12.5 km), which are compared to a large data set of observation-based rainfall return levels of 16 European countries. This observation-based data set was newly compiled and homogenized for this study from 32 different sources. The rainfall return levels of the CRCM5 are able to reproduce the general spatial pattern of extreme precipitation for all sub-daily durations with centred Pearson product-moment coefficients of linear correlation > 0.7 for the area covered with observations. Also, the rainfall intensity of the observational data set is in the range of the climate model generated intensities in 52 % (77 %, 79 %, 84 %, 78 %) of the area for hourly (3-hourly, 6-hourly, 12-hourly, 24-hourly) durations. This results in biases between −19.3 % (hourly) to +8.0 % (24-hourly) averaged over the study area. The range, which is introduced by the application of 50 members, shows a spread of −15 % to +18 % around the median. We conclude that our data set shows good agreement with the observations for 3-hourly to 24-hourly durations in large parts of the study area. Though, for hourly duration and topographically complex regions such as the Alps and Norway, we argue that higher-resolution climate model simulations are needed to improve the results. The 10-year return level data are publicly available (Poschlod, 2020; https://doi.org/10.5281/zenodo.3878887).

scholarly journals Weather extremes over Europe under 1.5 °C and 2.0 °C global warming from HAPPI regional climate ensemble simulations

2020 ◽  
Author(s):  
Kevin Sieck ◽  
Christine Nam ◽  
Laurens M. Bouwer ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Global Warming ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Apparent Temperature ◽  
Weather Extremes ◽  
Data Set ◽  
Near Surface ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. This paper presents a novel data set of regional climate model simulations over Europe that significantly improves our ability to detect changes in weather extremes under low and moderate levels of global warming. The data set provides a unique and physically consistent data set, as it is derived from a large ensemble of regional climate model simulations. These simulations were driven by two global climate models from the international HAPPI consortium. The set consists of 100 × 10-year simulations and 25 × 10-year simulations, respectively. These large ensembles allow for regional climate change and weather extremes to be investigated with an improved signal-to-noise ratio compared to previous climate simulations. The changes in four climate indices for temperature targets of 1.5 °C and 2.0 °C global warming are quantified: number of days per year with daily mean near-surface apparent temperature of > 28 °C (ATG28); the yearly maximum 5-day sum of precipitation (RX5day); the daily precipitation intensity of the 50-yr return period (RI50yr); and the annual Consecutive Dry Days (CDD). This work shows that even for a small signal in projected global mean temperature, changes of extreme temperature and precipitation indices can be robustly estimated. For temperature related indices changes in percentiles can also be estimated with high confidence. Such data can form the basis for tailor-made climate information that can aid adaptive measures at a policy-relevant scales, indicating potential impacts at low levels of global warming at steps of 0.5 °C.

Forced monsoon rainfall changes and the moist static energy budget: the Sahel and elsewhere

2020 ◽  
Author(s):  
Spencer Hill
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Monsoon Rainfall ◽  
Dominant Factor ◽  
Sahara Desert ◽  
Moist Static Energy ◽  
Model Simulations ◽  
Future Global Warming ◽  
Climate Model Simulations ◽  
Static Energy

<p>The Sahel is the semi-arid, transitional region separating the Sahara Desert from humid equatorial Africa, i.e. the poleward-most region to which appreciable rains from the West African monsoon extend during northern summer.  The severe drought it experienced in the 1970s and 1980s was one of the 20th century's most striking (and devastating) hydroclimatic events worldwide.  In climate model simulations of future global warming, Sahelian rainfall does anything from intense drying to even greater wettening depending on which climate model is used.  In this talk, I present recent research on rainfall in the Sahel using the moist static energy (MSE) budget -- what are the physical factors that drive its variations, and how do we expect them to change as the planet warms --- and the extent to which inferences from the Sahel can or cannot extend to other regions and other external forcings.<br><br>Using climate model simulations both of Earth's present-day conditions and of future global warming, I show that the drying influence of the Sahara Desert is a dominant factor in present-day and that this influence is strengthened with warming due to an increasing difference in moisture between the desert and the Sahel.  This enhancement of an existing moisture (and energy) gradient is a robust response of the atmosphere to mean ocean surface warming and has a firm theoretical basis.  By comparing climate model simulations of the present-day Sahel climate to real-world observations, I argue that this Sahara-driven drying mechanism is overly strong in those models that dry the Sahel most in future simulations.  This response to mean warming of global sea surface temperatures (SSTs) is readily explained using the MSE budget, whereas the Sahel rainfall response to changes in the spatial pattern of SSTs (such as during the 1970s-80s drought) are more easily interpreted via the popular energetic framework for Intertropical Convergence Zone (ITCZ) shifts.  I discuss the interplay between these and other theoretical frameworks for forced monsoon rainfall changes in the Sahel and other monsoon regions and offer ideas for refining and extending those theories.</p>

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