scholarly journals Projected Midlatitude Continental Summer Drying: North America versus Europe

2009 ◽  
Vol 22 (11) ◽  
pp. 2813-2833 ◽  
Author(s):  
David P. Rowell
Keyword(s):  
North America ◽  
Climate Model ◽  
Coupled Model ◽  
Extreme Rainfall ◽  
Summer Rainfall ◽  
High Elevation ◽  
Eastern North America ◽  
Surface Hydrology ◽  
Extreme Rainfall Events ◽  
Common Signal

Abstract A common signal in climate model projections is a decline in average summer rainfall over midlatitude continents due to anthropogenic warming. Most models suggest this rainfall decline will be less severe over North America than over Europe. This study aims to understand this difference in continental response and make inferences about its reliability. Data are primarily derived from a “perturbed physics” ensemble of models [Quantifying Uncertainty in Model Predictions project, subensemble S4 (QUMP-S4)] and are also compared with data from a multimodel ensemble [the Coupled Model Intercomparison Project phase 3 (CMIP3)]. A description of the uncertainty of predicted summer rainfall decline over both continents and its broad similarity between the two ensembles suggests the possibility that the QUMP-S4 ensemble may include many of the mechanisms that cause the differential continental response in the CMIP3 ensemble. Analysis of the QUMP-S4 mechanisms and their variability across the ensemble lead to the following conclusions. Over western North America, it is judged that the change in summer rainfall is more uncertain than models suggest, with a decline that could be either more or less severe than that over Europe. This is due to the western North American region’s dependence on uncertain modeling of high-elevation winter–spring surface hydrology. Over eastern North America, it seems likely that summer rainfall will decline. In particular, this decline is likely to be less severe than that over continental Europe since this difference primarily depends on reliable aspects of the models. However, a further, but speculative, conclusion is that these mechanisms could also lead to a larger increase in extreme rainfall events over eastern North America than over Europe.

scholarly journals Effects of Climate Change on Wind-Driven Heavy-Snowfall Events over Eastern North America

2018 ◽  
Vol 31 (22) ◽  
pp. 9037-9054 ◽  
Author(s):  
Tyler P. Janoski ◽  
Anthony J. Broccoli ◽  
Sarah B. Kapnick ◽  
Nathaniel C. Johnson
Keyword(s):  
North America ◽  
Greenhouse Gas ◽  
Climate Model ◽  
Extreme Values ◽  
Global Climate Model ◽  
High Elevation ◽  
Eastern North America ◽  
Winter Storms ◽  
Extreme Wind ◽  
Wind Events

Eastern North America contains densely populated, highly developed areas, making winter storms with strong winds and high snowfall among the costliest storm types. For this reason, it is important to determine how the frequency of high-impact winter storms, specifically, those combining significant snowfall and winds, will change in this region under increasing greenhouse gas concentrations. This study uses a high-resolution coupled global climate model to simulate the changes in extreme winter conditions from the present climate to a future scenario with doubled CO2 concentrations (2XC). In particular, this study focuses on changes in high-snowfall, extreme-wind (HSEW) events, which are defined as the occurrence of 2-day snowfall and high winds exceeding thresholds based on extreme values from the control simulation, where greenhouse gas concentrations remain fixed. Mean snowfall consistently decreases across the entire region, but extreme snowfall shows a more inconsistent pattern, with some areas experiencing increases in the frequency of extreme-snowfall events. Extreme-wind events show relatively small changes in frequency with 2XC, with the exception of high-elevation areas where there are large decreases in frequency. As a result of combined changes in wind and snowfall, HSEW events decrease in frequency in the 2XC simulation for much of eastern North America. Changes in the number of HSEW events in the 2XC environment are driven mainly by changes in the frequency of extreme-snowfall events, with most of the region experiencing decreases in event frequency, except for certain inland areas at higher latitudes.

CLIMATOLOGY OF EXTREME RAINFALL EVENTS IN EASTERN AND NORTHERN SANTA CATARINA STATE, BRAZIL: PRESENT AND FUTURE CLIMATE

2013 ◽  
Vol 31 (3) ◽  
pp. 413 ◽  
Author(s):  
André Becker Nunes ◽  
Gilson Carlos Da Silva
Keyword(s):  
Climate Model ◽  
Climate Modeling ◽  
Linear Trend ◽  
Extreme Rainfall ◽  
Eastern Region ◽  
Santa Catarina ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
History Of ◽  
Santa Catarina State

ABSTRACT. The eastern region of Santa Catarina State (Brazil) has an important history of natural disasters due to extreme rainfall events. Floods and landslides are enhancedby local features such as orography and urbanization: the replacement of natural surface coverage causing more surface runoff and, hence, flooding. Thus, studies of this type of events – which directly influence life in the towns – take on increasing importance. This work makes a quantitative analysis of occurrences of extreme rainfall events in the eastern and northern regions of Santa Catarina State in the last 60 years, through individual analysis, considering the history of floods ineach selected town, as well as an estimate through to the end of century following regional climate modeling. A positive linear trend, in most of the towns studied, was observed in the results, indicating greater frequency of these events in recent decades, and the HadRM3P climate model shows a heterogeneous increase of events for all towns in the period from 2071 to 2100.Keywords: floods, climate modeling, linear trend. RESUMO. A região leste do Estado de Santa Catarina tem um importante histórico de desastres naturais ocasionados por eventos extremos de precipitação. Inundações e deslizamentos de terra são potencializados pelo relevo acidentado e pela urbanização das cidades da região: a vegetação nativa vem sendo removida acarretando um maior escoamento superficial e, consequentemente, em inundações. Desta forma, torna-se de suma importância os estudos acerca deste tipo de evento que influencia diretamente a sociedade em geral. Neste trabalho é realizada uma análise quantitativa do número de eventos severos de precipitação ocorridos nas regiões leste e norte de Santa Catarina dos últimos 60 anos, por meio de uma análise pontual, considerandoo histórico de inundações de cada cidade selecionada, além de uma projeção para o fim do século de acordo com modelagem climática regional. Na análise dos resultados observou-se uma tendência linear positiva na maioria das cidades, indicando uma maior frequência deste tipo de evento nas últimas décadas, e o modelo climático HadRM3P mostra um aumento heterogêneo no número de eventos para todas as cidades no período de 2071 a 2100.Palavras-chave: inundações, modelagem climática, tendência linear.

scholarly journals Systematic Climate Model Rainfall Biases over Southern Africa: Links to Moisture Circulation and Topography

2018 ◽  
Vol 31 (18) ◽  
pp. 7533-7548 ◽  
Author(s):  
C. Munday ◽  
R. Washington
Keyword(s):  
Southern Africa ◽  
Climate Models ◽  
Climate Model ◽  
Regional Scale ◽  
Model Development ◽  
Coupled Model ◽  
Climate Science ◽  
Summer Rainfall ◽  
Southwest Indian Ocean ◽  
Low Level

An important challenge for climate science is to understand the regional circulation and rainfall response to global warming. Unfortunately, the climate models used to project future changes struggle to represent present-day rainfall and circulation, especially at a regional scale. This is the case in southern Africa, where models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) overestimate summer rainfall by as much as 300% compared to observations and tend to underestimate rainfall in Madagascar and the southwest Indian Ocean. In this paper, we explore the climate processes associated with the rainfall bias, with the aim of assessing the reliability of the CMIP5 ensemble and highlighting important areas for model development. We find that the high precipitation rates in models that are wet over southern Africa are associated with an anomalous northeasterly moisture transport (~10–30 g kg−1 s−1) that penetrates across the high topography of Tanzania and Malawi and into subtropical southern Africa. This transport occurs in preference to a southeasterly recurvature toward Madagascar that is seen in drier models and reanalysis data. We demonstrate that topographically related model biases in low-level flow are important for explaining the intermodel spread in rainfall; wetter models have a reduced tendency to block the oncoming northeasterly flow compared to dry models. The differences in low-level flow among models are related to upstream wind speed and model representation of topography, both of which should be foci for model development.

scholarly journals Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 degrees’ warmer worlds – How anthropogenic aerosols change the story

2018 ◽  
Author(s):  
Ruksana H. Rimi ◽  
Karsten Haustein ◽  
Emily J. Barbour ◽  
Sarah N. Sparrow ◽  
Sihan Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Model ◽  
Substantial Reduction ◽  
Extreme Rainfall ◽  
Extreme Weather Events ◽  
Future Climate Change ◽  
Anthropogenic Aerosols ◽  
Extreme Rainfall Events ◽  
Rainfall Events

Abstract. Anthropogenic climate change is likely to increase the frequency of extreme weather events in future. Previous studies have robustly shown how and where climate change has already changed the risks of weather extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of seasonal extreme rainfall events in Bangladesh under the Paris Agreement temperature goals of 1.5 °C and 2 °C warming above pre-industrial levels. In particular, we investigate the influence of anthropogenic aerosols on these risks given their likely future reduction and resulting amplification of global warming. Using large ensemble regional climate model simulations from weather@home under different forcing scenarios, we compare the risks of rainfall events under pre-industrial (natural), current (actual), 1.5 °C, and 2.0 °C warmer and greenhouse gas only (anthropogenic aerosols removed) conditions. We find that the risk of a 1 in 100 year rainfall event has already increased significantly compared with pre-industrial levels across parts of Bangladesh, with additional increases likely for 1.5 and 2.0 degree warming (of up to 5.5 times higher, with an uncertainty range of 3.5 to 7.8 times). Impacts were observed during both the pre-monsoon and monsoon periods, but were spatially variable across the country in terms of the level of impact. Results also show that reduction in anthropogenic aerosols plays an important role in determining the overall future climate change impacts; by exacerbating the effects of GHG induced global warming and thereby increasing the rainfall intensity. We highlight that the net aerosol effect varies from region to region within Bangladesh, which leads to different outcomes of aerosol reduction on extreme rainfall statistics, and must therefore be considered in future risk assessments. Whilst there is a substantial reduction in the impacts resulting from 1.5 °C compared with 2 °C warming, the difference is spatially and temporally variable, specifically with respect to seasonal extreme rainfall events.

The Continuum of Hydroclimate Variability in Western North America during the Last Millennium

2013 ◽  
Vol 26 (16) ◽  
pp. 5863-5878 ◽  
Author(s):  
Toby R. Ault ◽  
Julia E. Cole ◽  
Jonathan T. Overpeck ◽  
Gregory T. Pederson ◽  
Scott St. George ◽  
...  
Keyword(s):  
North America ◽  
Null Hypothesis ◽  
Climate Model ◽  
Power Spectra ◽  
Low Frequency ◽  
Coupled Model ◽  
Power Laws ◽  
Western North America ◽  
The Future ◽  
Paleoclimate Records

Abstract The distribution of climatic variance across the frequency spectrum has substantial importance for anticipating how climate will evolve in the future. Here power spectra and power laws (β) are estimated from instrumental, proxy, and climate model data to characterize the hydroclimate continuum in western North America (WNA). The significance of the estimates of spectral densities and β are tested against the null hypothesis that they reflect solely the effects of local (nonclimate) sources of autocorrelation at the monthly time scale. Although tree-ring-based hydroclimate reconstructions are generally consistent with this null hypothesis, values of β calculated from long moisture-sensitive chronologies (as opposed to reconstructions) and other types of hydroclimate proxies exceed null expectations. Therefore it may be argued that there is more low-frequency variability in hydroclimate than monthly autocorrelation alone can generate. Coupled model results archived as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) are consistent with the null hypothesis and appear unable to generate variance in hydroclimate commensurate with paleoclimate records. Consequently, at decadal-to-multidecadal time scales there is more variability in instrumental and proxy data than in the models, suggesting that the risk of prolonged droughts under climate change may be underestimated by CMIP5 simulations of the future.

Startegic framework for integrated flood Disaster modelling over Bangalore city of India

2021 ◽  
Author(s):  
Smrati Purwar ◽  
Gyanendranath Mohapatra ◽  
Rakesh Vasudevan
Keyword(s):  
Urban Landscape ◽  
Flash Flood ◽  
Warning System ◽  
Extreme Rainfall ◽  
High Elevation ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Bangalore City ◽  
Societal Relevance ◽  
The Impact

<p>Hydro-meteorological disasters, particularly the extreme rainfall events (EREs) and associated flash floods, are very frequent in the major metro cities in India during recent years and in many occasions they cause massive destruction to life and property which in long run make adverse socio-economic impacts over the country. Hence, it makes formost importance and has great societal relevance to modellers working such area to develop an advance prediction system for such disasters in India.A strategic framework combining modelling and data analytics is integral part of developing advanced warning system for preparedness during such disasters. In this study, the role of landuse/landcover like built-up, vegetation, barrenland and waterbodies over the Bangalore city in flash flood occurrence is examined using multispectral spatio-temporal satellite data.The recent LULC map evidences a drastic changes in urban landscape that resulted in loss of natural drainage and waterbeds causing frequent floods. Digital Elevation Map (DEM) is analysed to know the  low-lying and high elevation topography compared with  Mean Sea Level(MSL)to quantify the impact of flooding during Extreme Rainfall Events(ERE) on the different part of the Bangalore city. Using Triangular Irregular Network (TIN), flood simulation is carried out for highland and lowlandarea  to study immediate affected areas during EREs Storm Water Modelling  is carried out for different regions in the city to obtain flood pattern, time and volume during selected EREs. The framework developed and simulation results are very useful in generation of management and mitigation strategy by various user agencies.</p>

scholarly journals Identifying the origins of extreme rainfall using storm track classification

2019 ◽  
Vol 22 (2) ◽  
pp. 296-309
Author(s):  
Andrew Paul Barnes ◽  
Marcus Suassuna Santos ◽  
Carlos Garijo ◽  
Luis Mediero ◽  
Ilaria Prosdocimi ◽  
...  
Keyword(s):  
Storm Track ◽  
Extreme Rainfall ◽  
Summer Rainfall ◽  
Flood Frequency ◽  
Trajectory Data ◽  
Northern Spain ◽  
Data Set ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Frequency Distributions

Abstract Identifying patterns in data relating to extreme rainfall is important for classifying and estimating rainfall and flood frequency distributions routinely used in civil engineering design and flood management. This study demonstrates the novel use of several self-organising map (SOM) models to extract the key moisture pathways for extreme rainfall events applied to example data in northern Spain. These models are trained using various subsets of a backwards trajectory data set generated for extreme rainfall events between 1967 and 2016. The results of our analysis show 69.2% of summer rainfall extremes rely on recirculatory moisture pathways concentrated on the Iberian Peninsula, whereas 57% of winter extremes rely on deep-Atlantic pathways to bring moisture from the ocean. These moisture pathways have also shown differences in rainfall magnitude, such as in the summer where peninsular pathways are 8% more likely to deliver the higher magnitude extremes than their Atlantic counterparts.

Extreme Snow Events along the Coast of the Northeast United States: Analysis of Observations and HiRAM Simulations

2019 ◽  
Vol 32 (21) ◽  
pp. 7561-7574
Author(s):  
Guoxing Chen ◽  
Wei-Chyung Wang ◽  
Lijun Tao ◽  
Huang-Hsiung Hsu ◽  
Chia-Ying Tu ◽  
...  
Keyword(s):  
United States ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Extreme Rainfall ◽  
Atmospheric Model ◽  
Pressure System ◽  
Extreme Rainfall Events ◽  
Northeast United States ◽  
Spatial Coverage

Abstract This study used both observations and global climate model simulations to investigate the characteristics of winter extreme snowfall events along the coast (the Interstate 95 corridor) of the northeast United States where several mega-cities are located. Observational analyses indicate that, during 1980–2015, 110 events occurred when four coastal cities—Boston, New York City, Philadelphia, and Washington, D.C.—had either individually or collectively experienced daily snowfall exceeding the local 95th percentile thresholds. Boston had the most events, with a total of 69, followed by 40, 36, and 30 (moving southward) in the other three cities. The associated circulations at 200 and 850 hPa were categorized via K-means clustering. The resulting three composite circulations are characterized by the strength and location of the jet at 200 hPa and the coupled low pressure system at 850 hPa: a strong jet overlying the cities coupled with an inland trough, a weak and slightly southward shifted jet coupled with a cyclone at the coast, and a weak jet stream situated to the south of the cities coupled with a cyclone over the coastal oceans. Comparative analyses were also conducted using the GFDL High Resolution Atmospheric Model (HiRAM) simulation of the same period. Although the simulated extreme events do not provide one-to-one correspondence with observations, the characteristics nevertheless show consistency notably in total number of occurrences, intraseasonal and multiple-year variations, snow spatial coverage, and the associated circulation patterns. Possible future change in extreme snow events was also explored utilizing the HiRAM RCP8.5 (2075–2100) simulation. The analyses suggest that a warming global climate tends to decrease the extreme snowfall events but increase extreme rainfall events.

scholarly journals Projections of North American Snow from NA-CORDEX and their Uncertainties, with a Focus on Model Resolution

2021 ◽  
Author(s):  
Rachel McCrary ◽  
Linda Mearns ◽  
Mimi Hughes ◽  
Sébastien Biner ◽  
Melissa Bukovsky
Keyword(s):  
North America ◽  
North American ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
High Elevation ◽  
Climate Impacts ◽  
Global Climate Models ◽  
High Latitudes ◽  
Model Resolution

Abstract Snow is important for many physical, social, and economic sectors in North America. In a warming climate, the characteristics of snow will likely change in fundamental ways, therefore compelling societal need for future projections of snow. However many stakeholders require climate change information at finer resolutions that global climate models (GCMs) can provide. The North American Coordinated Regional Downscaling Experiment (NA-CORDEX) provides an ensemble of regional climate model (RCMs) simulations at two resolutions (~0.5º and ~0.25º) designed to help serve the climate impacts and adaptation communities. This is the first study to examine the differences in end-of-21st-century projections of snow from the NA-CORDEX RCMs and their driving GCMs. We find the broad patterns of change are similar across RCMs and GCMs: snow cover retreats, snow mass decreases everywhere except at high latitudes, and the duration of the snow covered season decreases. Regionally, the spatial details, magnitude, percent, and uncertainty of future changes varies between the GCM and RCM ensemble, but are similar between the two resolutions of the RCM ensembles. Increases in winter snow amounts at high latitudes is a robust response across all ensembles. Percent snow losses are found to be more substantial in the GCMs than the RCMs over most of North America, especially in regions with high-elevation topography. Specifically, percent snow losses decrease with increasing elevation as the model resolution becomes finer.

scholarly journals Urban-climate interactions during summer over eastern North America

2021 ◽  
Author(s):  
Seok-Geun Oh ◽  
Laxmi Sushama
Keyword(s):  
Heat Stress ◽  
North America ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Urban Climate ◽  
Eastern North America ◽  
Urban Regions ◽  
Urban Representation ◽  
Climate Interactions

Abstract The urban heat island is a representative urban climate characteristic, which can affect heat-stress conditions and extreme precipitation that are closely connected with human life. Better understanding of urban-climate interactions, therefore, is crucial to ultimately support better planning and adaptation in various application fields. This study assesses urban-climate interactions during summer for eastern North America using regional climate model simulations at 0.22° resolution. Two regional climate model experiments, with and without realistic representation of urban regions, are performed for the 1981–2010 period. Comparison of the two experiments shows higher mean temperatures and reduced mean precipitation in the simulation with realistic urban representation, which can be attributed primarily to reduced albedo and soil moisture for the urban regions in this simulation. Furthermore, the mean temperature and precipitation in the simulation with improved urban representation is also closer to that observed. Analysis of short-duration precipitation extremes for climatologically different sub-regions, however, suggests that, for higher temperatures, the magnitudes of precipitation extremes are generally higher in the simulation with realistic urban representation, particularly for coastal urban regions, and are collocated with higher values of convective available potential energy and cloud fraction. Enhanced sea and lake breezes associated with lower sea level pressure found around these regions, contribute additional water vapor and further enhance dynamic convective development, leading to higher precipitation intensities. Analysis of temperature extremes clearly demonstrates that urban regions experience aggravated heat-stress conditions due to relatively higher temperatures despite reduced relative humidity. Double the number of extreme heat spells lasting six or more days are noted for the coastal urban regions in the study domain. This study, in addition to demonstrating the differences in urban-climate interactions for climatologically different regions, also demonstrates the need for better representation of urban regions in climate models to generate realistic climate information.

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