Sentences with phrase «modelled precipitation extremes»
The researchers found that there were some improvements in the representation of climate extremes in global climate models, reflected in the closer correspondence of modelled precipitation extremes and those from simulations, and the decreased spread of values from the newer climate models.
https://www.pacificclimate.org/ Not exact matches
They were in less agreement about how intense rain or snow will be when it does fall, although there is general consensus among models that the most extreme precipitation will become more frequent.
While the models do not reliably track individual extreme weather events, they do reproduce the jet stream patterns and temperature scenarios that in the real world lead to torrential rain for days, weeks of broiling sun and absence of precipitation.
Computer models showed a reduction in what Edwards called «extreme precipitation events» in the fall season in western South Dakota when compared to climate conditions in the 1800s.
As the 2014 Intergovernmental Panel on Climate Change report notes, models predict that increasing temperature ought to cause greater precipitation extremes in both directions — both drought and flooding, though there are likely more areas of heavy precipitation.
Daniel Swain and colleagues model how the frequency of these rapid, year - to - year transitions from extreme dry to wet conditions — which they dub «precipitation whiplash events» — may change in California's future as a consequence of man - made warming.
Climate model projections show a warmer Montana in the future, with mixed changes in precipitation, more extreme events, and mixed certainty on upcoming drought.
Durman, C.F., et al., 2001: A comparison of extreme European daily precipitation simulated by a global model and regional climate model for present and future climates.
His work mainly focuses on remote sensing of precipitation, hydrologic applications, and the analysis of extreme weather and climatic events using observation and models.
Using high - resolution modeling with theoretical and statistical analysis, researchers revealed a direct link between in - cloud processes and the frequency of precipitation extremes.
The report, «Atmospheric Warming and the Amplification of Precipitation Extremes,» previewed in Science Express this Thursday, August 7, and published in an upcoming issue of Science, found that both observations and models indicated an increase in heavy rainstorms in response to a warmer climate.
Mean temperature, mean monthly precipitation, frequency of hot / cold days / nights, and indices of extreme precipitation are all estimated for each country based on observed and modeled data.
Because of the limited availability of daily observations, however, most previous studies have examined only the potential detectability of changes in extreme precipitation through model — model comparisons (12 — 15).
Changes in extreme precipitation projected by models, and thus the impacts of future changes in extreme precipitation, may be underestimated because models seem to underestimate the observed increase in heavy precipitation with warming.
At the tail end of the full paper, capping a paragraph about a weak spot in the analysis — that the observed trend in extreme precipitation events exceeds what is produced by various climate models — comes a sentence about uncertainties:
Without El Niño and La Niña feeding into the climate model, the frequency of extreme precipitation in California stayed constant for the simulation's century and a half.
2: Our Changing Climate, Key Message 5).2 Regional climate models (RCMs) using the same emissions scenario also project increased spring precipitation (9 % in 2041 - 2062 relative to 1979 - 2000) and decreased summer precipitation (by an average of about 8 % in 2041 - 2062 relative to 1979 - 2000) particularly in the southern portions of the Midwest.12 Increases in the frequency and intensity of extreme precipitation are projected across the entire region in both GCM and RCM simulations (Figure 18.6), and these increases are generally larger than the projected changes in average precipitation.12, 2
Precipitation extremes and their potential future changes were predicted using six - member ensembles of general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5).
Given the different responses of high - and low - resolution models to CO2 forcing, the authors emphasize the importance of model choice for any study of extreme precipitation.
For example, the two models with the highest resolution (FLOR and HiFLOR) show increased extreme precipitation during the Atlantic hurricane season in the U.S. southeast.
Results show that higher - resolution models significantly improve the simulation of mean precipitation, the distribution of precipitation, and spatial patterns, intensity and seasonality of precipitation extremes.
In response to 2xCO2 forcing, all models show a mean intensification of precipitation extremes, of approximately 3 - 4 % / K.
There is a minimum model resolution that is needed to capture weather phenomena generating precipitation extremes, for example for simulating tropical cyclones or precipitation enhancement over mountains.
This study employed three newly developed global coupled climate models to study the impact of horizontal atmospheric model resolution (tile size) on precipitation extremes.
This requires considerable integrity in the model's ability to simulate both, but models typically have great difficulty in simulating extremes well (Lin et al. 2006; Kharin et al. 2007) especially throughout the tropics for precipitation.
More accurate and reliable precipitation data would be invaluable, not only for the study of climate trends and variability, but also as inputs to hydrological and ecological models and for model validation, characterization of extreme events, and flood and drought forecasting.
The US CLIVAR Extremes Working Group was formed to evaluate whether current climate models produce extremes for the right reasons and whether they can be used for predicting and projecting short - term extremes in temperature and precipitation over North Extremes Working Group was formed to evaluate whether current climate models produce extremes for the right reasons and whether they can be used for predicting and projecting short - term extremes in temperature and precipitation over North extremes for the right reasons and whether they can be used for predicting and projecting short - term extremes in temperature and precipitation over North extremes in temperature and precipitation over North America.
Reviewing the first one in 2000, myself and Chip Knappenberger discovered that the science team just happened to choose the two most extreme models (for temperature and precipitation) out of the 14 they considered.
Regional climate simulations, driven by two «well performing» dynamically downscaled IPCC models, also shows an amplification of historical summer temperature and precipitation extremes is occurring in conjunction with the Pacific sea surface temperature influence on US regional climate.
Output from global circulation models indicates that climate variability will continue to be an important characteristic of the region in the future [52], but that climate change may increase the risk of extreme climatic events such as multi-decade droughts and extreme winter precipitation [53], [54].
Recently developed convection - permitting models better simulate extreme precipitation, but simulations are not yet widely available due to their computational cost, and they have their own uncertainties.
Using an ensemble of four high resolution (~ 25 km) regional climate models, this study analyses the future (2021 - 2050) spatial distribution of seasonal temperature and precipitation extremes in the Ganges river basin based on the SRES A1B emissions scenario.
the model does not simulate any dependence of Northern England precipitation on the state of El Niño, with a correlation coefficient of r = 0.01 and no visual indications that extreme events behave differently than the mean.
Another study examined the potential flood damage impacts of changes in extreme precipitation events using the Canadian Climate Centre model and the IS92a emissions scenario for the metropolitan Boston area in the north - eastern USA (Kirshen et al., 2005b).
PDRMIP investigates the role of various drivers of climate change for mean and extreme precipitation changes, based on multiple climate model output and energy budget analyses.
This demonstrates the importance of model physics for teleconnections to extreme precipitation.
For terrestrial British Columbia, precipitation averages and extremes can be simulated more accurately within individual regions by using gridded downscaling to increase the resolution of both global and regional climate models.
In this study, evidence for a nonlinear association between ENSO and precipitation extremes is reassessed by fitting stationary and linear / nonlinear GEV regression models, with the Niño3.4 index as a covariate, to 1 -, 5 -, and 10 - day extended winter precipitation maxima.
CAS = Commission for Atmospheric Sciences CMDP = Climate Metrics and Diagnostic Panel CMIP = Coupled Model Intercomparison Project DAOS = Working Group on Data Assimilation and Observing Systems GASS = Global Atmospheric System Studies panel GEWEX = Global Energy and Water Cycle Experiment GLASS = Global Land - Atmosphere System Studies panel GOV = Global Ocean Data Assimilation Experiment (GODAE) Ocean View JWGFVR = Joint Working Group on Forecast Verification Research MJO - TF = Madden - Julian Oscillation Task Force PDEF = Working Group on Predictability, Dynamics and Ensemble Forecasting PPP = Polar Prediction Project QPF = Quantitative precipitation forecast S2S = Subseasonal to Seasonal Prediction Project SPARC = Stratospheric Processes and their Role in Climate TC = Tropical cyclone WCRP = World Climate Research Programme WCRP Grand Science Challenges • Climate Extremes • Clouds, Circulation and Climate Sensitivity • Melting Ice and Global Consequences • Regional Sea - Ice Change and Coastal Impacts • Water Availability WCRP JSC = Joint Scientific Committee WGCM = Working Group on Coupled Modelling WGSIP = Working Group on Subseasonal to Interdecadal Prediction WWRP = World Weather Research Programme YOPP = Year of Polar Prediction
Regional Climate Models projections are used to provide projections of changes in temperature, precipitation, and indices of extremes.
For terrestrial British Columbia, precipitation averages and extremes can be simulated more accurately within individual regions by using gridded downscaling to increase the resolution of regional climate models.
While researchers have identified teleconnections between El Niño - Southern Oscillation (ENSO) and extended winter precipitation extremes in North America using generalized extreme value (GEV) models, the regional form of the statistical relationship remains an open question.
This report discusses our current understanding of the mechanisms that link declines in Arctic sea ice cover, loss of high - latitude snow cover, changes in Arctic - region energy fluxes, atmospheric circulation patterns, and the occurrence of extreme weather events; possible implications of more severe loss of summer Arctic sea ice upon weather patterns at lower latitudes; major gaps in our understanding, and observational and / or modeling efforts that are needed to fill those gaps; and current opportunities and limitations for using Arctic sea ice predictions to assess the risk of temperature / precipitation anomalies and extreme weather events over northern continents.
The first (2000) Assessment used the two most extreme models of the 14 considered for temperature and precipitation.
We are not aware of any other study that has documented the impact of the precipitation simulation imperfections on GCMs» predictions of surface air temperature, but the ability of such flawed models to predict global warming and its extremes could be compromised.
Bracken C., B. Rajagopalan, L. Cheng, W. Kleiber and S. Gangopadhyay (August 2016): Spatial Bayesian hierarchical modeling of precipitation extremes over a large domain.
Further investigation using high - resolution modeling approaches that better resolve the boundary conditions and fine - scale physical processes (44 ⇓ — 46) and / or using analyses that focus on the underlying large - scale climate dynamics of individual extreme events (8) could help to overcome the limitations of simulated precipitation and temperature in the current generation of global climate models.
Future change of precipitation extremes in Europe: Intercomparison of scenarios from regional climate models.
Although the global models have improved over time (Chapter 8), they still have limitations that affect the simulation of extreme events in terms of spatial resolution, simulation errors, and parametrizations that must represent processes that can not yet be included explicitly in the models, particularly dealing with clouds and precipitation (Meehl et al., 2000d).
Understanding and modeling the fundamental processes that govern the large precipitation variability and extremes in the western U.S. is a critical test for the ability of climate models to predict the regional water cycle, including floods and droughts.