scholarly journals Computation of extreme heat waves in climate models using a large deviation algorithm

2017 ◽  
Vol 115 (1) ◽  
pp. 24-29 ◽  
Author(s):  
Francesco Ragone ◽  
Jeroen Wouters ◽  
Freddy Bouchet
Keyword(s):  
Statistical Physics ◽  
Climate Models ◽  
Large Deviation ◽  
Heat Waves ◽  
Rare Event ◽  
Teleconnection Pattern ◽  
Extreme Heat ◽  
Sampling Efficiency ◽  
Wide Range ◽  
The Impact

Studying extreme events and how they evolve in a changing climate is one of the most important current scientific challenges. Starting from complex climate models, a key difficulty is to be able to run long enough simulations to observe those extremely rare events. In physics, chemistry, and biology, rare event algorithms have recently been developed to compute probabilities of events that cannot be observed in direct numerical simulations. Here we propose such an algorithm, specifically designed for extreme heat or cold waves, based on statistical physics. This approach gives an improvement of more than two orders of magnitude in the sampling efficiency. We describe the dynamics of events that would not be observed otherwise. We show that European extreme heat waves are related to a global teleconnection pattern involving North America and Asia. This tool opens up a wide range of possible studies to quantitatively assess the impact of climate change.

Studying heat waves and warm summers in numerical climate models with a rare event algorithm

2020 ◽  
Author(s):  
Francesco Ragone ◽  
Freddy Bouchet
Keyword(s):  
Extreme Events ◽  
Statistical Physics ◽  
Climate Models ◽  
Rare Events ◽  
Large Deviation ◽  
Heat Waves ◽  
Rare Event ◽  
Climate Science ◽  
Computational Effort ◽  
Climate Modelling

<div> <div> <div> <div> <p>Extreme events are a major topic of interest in climate science. Studying rare extreme events with complex numerical climate models is computationally challenging, since in principle very long simulations are needed to sample a sufficient number of events to provide a reliable statistics. This problem can be tackled using rare event algorithms, numerical tools developed in the past decades in mathematics and statistical physics, dedicated to the reduction of the computational effort required to sample rare events in dynamical systems. Typically they are designed as genetic algorithms, in which a set of suppression and cloning rules are applied to an ensemble simulation in order to focus the computational effort on the trajectories leading to the events of interest. Recently we showed the great potential of rare event algorithms for climate modelling, applying a rare event algorithm to study extremes of European surface temperature in Plasim, an intermediate complexity model, in absence of external time dependent forcings (no seasonal and daily cycles). Here we go beyond these limitations, studying extreme heat waves and warm summers in the Northern extratropics in fully realistic conditions including daily and seasonal cycles, both in Plasim and in the state of the art Earth system model CESM. We show how the algorithm allows to sample extreme events characterised by persistency on different time scales, discussing links with large deviation theory. We show how one can characterise the statistics of heat waves and warm summers with extremely large return times, with computational costs orders of magnitude smaller than with direct sampling, and reach ultra rare events that would have been impossible to observe otherwise. We analyse the emergence of teleconnection patterns during the extreme events and their relation to the dynamics of planetary waves. Finally we discuss how these results open the way to the systematic application of these techniques to a vast range of applicative and theoretical studies.</p> </div> </div> </div> </div>

Abstract P069: Heat, Heat Waves and Hospital Admissions in Indianapolis, Indiana

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Yi Wang
Keyword(s):  
Myocardial Infarction ◽  
Heart Failure ◽  
Relative Risk ◽  
Heat Wave ◽  
Hospital Admissions ◽  
Heat Waves ◽  
Global Climate ◽  
Extreme Heat ◽  
Apparent Temperature ◽  
The Impact

Background: The association between heat and hospital admissions is well studied, but in Indiana where the regulatory agencies cites lack of evidence for global climate change, local evidence of such an association is critical for Indiana to mitigate the impact of increasing heat. Methods: Using a distributed-lag non-linear model, we studied the effects of moderate (31.7 °C or 90 th percentile of daily mean apparent temperature (AT)), severe (33.5 °C or 95 th percentile of daily mean apparent temperature (AT)) and extreme (36.4 °C or 99 th percentile of AT) heat on hospital admissions (June-August 2007-2012) for cardiovascular (myocardial infarction, myocardial infarction, heart failure) and heat-related diseases in Indianapolis, Indiana located in Marion County. We also examined the added effects of moderate heat waves (AT above the 90 th percentile lasting 2-6 days), severe heat waves (AT above the 95 th percentile lasting 2-6 days) and extreme heat waves (AT above the 99 th percentile lasting 2-6 days). In sensitivity analysis, we tested robustness of our results to 1) different temperature and lag structures and 2) temperature metrics (daily min, max and diurnal temperature range). Results: The relative risks of moderate heat, relative to 29.2°C (75 th percentile of AT), on admissions for cardiovascular disease (CVD), myocardial infarction (MI), heart failure (HF), and heat-related diseases (HD) were 0.98 (0.67, 1.44), 6.28 (1.48, 26.6), 1.38 (0.81, 2.36) and 1.73 (0.58, 5.11). The relative risk of severe heat on admissions for CVD, MI, HF, and HD were 0.93 (0.60, 1.43), 4.46 (0.85, 23.4), 1.30 (0.72, 2.34) and 2.14 (0.43, 10.7). The relative risk of extreme heat were 0.79 (0.26, 2.39), 0.11 (0.087, 1.32), 0.68 (0.18, 2.61), and 0.32 (0.005, 19.5). We also observed statistically significant added effects of moderate heat waves lasting 4 or 6 days on hospital admission for MI and HD and extreme heat waves lasting 4 days on hospital admissions for HD. Results were strengthened for people older than 65. Conclusions: Moderate heat wave lasting 4-6 days were associated with increased hospital admissions for MI and HD diseases and extreme heat wave lasting 4 days were associated with increased admissions for HD.

NUKLEUS - User-relevant and applicable kilometer-scale climate information for Germany

2021 ◽  
Author(s):  
Kevin Sieck ◽  
Bente Tiedje ◽  
Hendrik Feldmann ◽  
Joaquim Pinto
Keyword(s):  
Climate Models ◽  
Local Scale ◽  
Easy Access ◽  
Climate Information ◽  
Post Processing ◽  
Last Mile ◽  
Wide Range ◽  
Impact Modelling ◽  
The Impact ◽  
Impact Models

<p>Given the current developments in climate science it becomes more a more feasible to provide climate information at the kilometer-scale from convection-permitting climate simulations. This progress will enable many users to directly feed high-resolution climate information into their impact-models for climate impact studies at the local scale. Examples include urban heat stress at street level or the design of drainage systems for future precipitation extremes. Within the RegIKlim (Regional information for action on climate change) consortium, the NUKLEUS (Actionable local climate information for Germany) project will not only provide climate information at the local scale, but also to co-develop interfaces between climate and impact models, in order to fulfil the needs of the impact modelling community as good as possible. Within the RegIKlim consortium, the impact modelling community is organised in six “model regions” across Germany, which cover a wide range of geographical and socio-economic conditions.</p><p>For the NUKLEUS project, the baseline will be the latest generation of EURO-CORDEX downscaled CMIP6 simulations, which will be further refined to roughly 3 km horizontal resolution and 30-year time-slices for Germany with convection-permitting climate models (ICON CLM, COSMO-CLM, REMO-NH) and statistical-dynamical downscaling approaches. A detailed analysis on the performance of the multi-model mini-ensemble is planned to assess the quality of the provided data. At the interface to the users, we will follow three different approaches to provide usable climate information at the kilometer-scale. One is to provide easy-access to data and post-processing opportunities using the FREVA system. FREVA offers various access-levels from shell to web-based, which serves different levels of user-expertise. In addition, it provides a transparent way of post-processing data by workflow sharing mechanisms. The second one is to develop appropriate additional downscaling methods for the “last mile” where needed. For this “last mile”, we will apply dynamical and statistical methods such as urban climate models and/or weather generators. With the third approach we explicitly aim at integrating a collected user-feedback into the regional modelling systems used within NUKLEUS. Specifically, we intend to identify and incorporate data processing that is best done during the simulation permanently into the models. Examples are wind speeds at rotor heights of windmills or high frequency precipitation sums. NUKLEUS is a contribution to the German research program RegIKlim funded by the Federal Ministry of Education and Research (BMBF).</p>

scholarly journals Economics of the disintegration of the Greenland ice sheet

2019 ◽  
Vol 116 (25) ◽  
pp. 12261-12269 ◽  
Author(s):  
William Nordhaus
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Social Cost ◽  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Reduced Form ◽  
Small Contribution ◽  
Wide Range ◽  
The Impact

Concerns about the impact on large-scale earth systems have taken center stage in the scientific and economic analysis of climate change. The present study analyzes the economic impact of a potential disintegration of the Greenland ice sheet (GIS). The study introduces an approach that combines long-run economic growth models, climate models, and reduced-form GIS models. The study demonstrates that social cost–benefit analysis and damage-limiting strategies can be usefully extended to illuminate issues with major long-term consequences, as well as concerns such as potential tipping points, irreversibility, and hysteresis. A key finding is that, under a wide range of assumptions, the risk of GIS disintegration makes a small contribution to the optimal stringency of current policy or to the overall social cost of climate change. It finds that the cost of GIS disintegration adds less than 5% to the social cost of carbon (SCC) under alternative discount rates and estimates of the GIS dynamics.

Forecasting climate extremes to aid decisions on multi-week timescales

2020 ◽  
Author(s):  
Catherine de Burgh-Day ◽  
Debbie Hudson ◽  
Oscar Alves ◽  
Morwenna Griffiths ◽  
Andrew Marshall ◽  
...  
Keyword(s):  
Extreme Events ◽  
Extreme Event ◽  
Heat Waves ◽  
Climate Extremes ◽  
Extended Period ◽  
Extreme Heat ◽  
Financial Loss ◽  
Defensive Responses ◽  
Using Data ◽  
The Impact

<p>Extreme events such as droughts, heat waves and floods can have significant and long lasting financial, infrastructural and environmental impacts. While probabilistic seasonal outlooks are commonplace, there are relatively few probabilistic outlooks available on multiweek timescales. Additionally, many services focus on the middle of the distribution of possible outcomes – e.g., forecasts of probability of above or below median, or probability of mean conditions exceeding some threshold. These do not encompass the types of extreme events that can be the most damaging, such as several consecutive days of extreme heat, unusually large numbers of cold days in a season, or an extended period where rainfall is in the lowest decile of historical years.</p><p>Advance warning of extreme events that impact particular industries enable managers to put in place response measures which can help to reduce their losses. This can involve:</p><ul><li>Active responses which aim to reduce the severity of the impact. For example, losses in dairy production due to extreme heat can be mitigated by adjusting grazing rotations such that cows are in shadier paddocks during these events</li> <li>Defensive responses which aim to account for any losses incurred due to an event. For example, the purchase of new farm equipment can be deferred if a forecast extreme event indicates a likely unavoidable financial loss in the near future</li> </ul><p>To meet this need, the Australian Bureau of Meteorology is developing a suite of forecast products communicating risk of extreme events using data from the Bureau’s new seasonal forecasting system ACCESS-S. Each prototype forecast product is trialed with external users through a webpage to assess usefulness and popularity.</p>

scholarly journals A Statistical–Dynamical Methodology to Downscale Regional Climate Projections to Urban Scale

2020 ◽  
Vol 59 (6) ◽  
pp. 1109-1123 ◽  
Author(s):  
François DuchÊne ◽  
Bert Van Schaeybroeck ◽  
Steven Caluwaerts ◽  
Rozemien De Troch ◽  
Rafiq Hamdi ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Heat Waves ◽  
Regional Climate ◽  
Wave Number ◽  
Surface Model ◽  
Climate Projections ◽  
Short Period ◽  
The Impact

AbstractThe demand of city planners for quantitative information on the impact of climate change on the urban environment is increasing. However, such information is usually extracted from decadelong climate projections generated with global or regional climate models (RCMs). Because of their coarse resolution and unsuitable physical parameterization, however, their model output is not adequate to be used at city scale. A full dynamical downscaling to city level, on the other hand, is computationally too expensive for climatological time scales. A statistical–dynamical computationally inexpensive method is therefore proposed that approximates well the behavior of the full dynamical downscaling approach. The approach downscales RCM simulations using the combination of an RCM at high resolution (H-RES) and a land surface model (LSM). The method involves the setup of a database of urban signatures by running an H-RES RCM with and without urban parameterization for a relatively short period. Using an analog approach, these signatures are first selectively added to the long-term RCM data, which are then used as forcing for an LSM using an urban parameterization in a stand-alone mode. A comparison with a full dynamical downscaling approach is presented for the city of Brussels, Belgium, for 30 summers with the combined ALADIN–AROME model (ALARO-0) coupled to the Surface Externalisée model (SURFEX) as H-RES RCM and SURFEX as LSM. The average bias of the nocturnal urban heat island during heat waves is vanishingly small, and the RMSE is strongly reduced. Not only is the statistical–dynamical approach able to correct the heat-wave number and intensities, it can also improve intervariable correlations and multivariate and temporally correlated indices, such as Humidex.

scholarly journals An observation-constrained multi-physics WRF ensemble for simulating European mega heat waves

2015 ◽  
Vol 8 (7) ◽  
pp. 2285-2298 ◽  
Author(s):  
A. I. Stegehuis ◽  
R. Vautard ◽  
P. Ciais ◽  
A. J. Teuling ◽  
D. G. Miralles ◽  
...  
Keyword(s):  
Heat Wave ◽  
Land Surface ◽  
Western Europe ◽  
Climate Models ◽  
Climate Model ◽  
Heat Waves ◽  
Regional Climate ◽  
Shortwave Radiation ◽  
Cold Bias ◽  
The Impact

Abstract. Many climate models have difficulties in properly reproducing climate extremes, such as heat wave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, in combination with the NOAH land-surface scheme, with the goal of detecting the most sensitive physics and identifying those that appear most suitable for simulating the heat wave events of 2003 in western Europe and 2010 in Russia. In total, 55 out of 216 simulations combining different atmospheric physical schemes have a temperature bias smaller than 1 °C during the heat wave episodes, the majority of simulations showing a cold bias of on average 2–3 °C. Conversely, precipitation is mostly overestimated prior to heat waves, and shortwave radiation is slightly overestimated. Convection is found to be the most sensitive atmospheric physical process impacting simulated heat wave temperature across four different convection schemes in the simulation ensemble. Based on these comparisons, we design a reduced ensemble of five well performing and diverse scheme configurations, which may be used in the future to perform heat wave analysis and to investigate the impact of climate change during summer in Europe.

scholarly journals Contributions of Climate Feedbacks to Changes in Atmospheric Circulation

2017 ◽  
Vol 30 (22) ◽  
pp. 9097-9118 ◽  
Author(s):  
Paulo Ceppi ◽  
Theodore G. Shepherd
Keyword(s):  
Water Vapor ◽  
Atmospheric Circulation ◽  
Surface Albedo ◽  
Climate Models ◽  
Cmip5 Models ◽  
Climate Feedbacks ◽  
Wide Range ◽  
Radiative Feedbacks ◽  
Opposing Effects ◽  
The Impact

The projected response of the atmospheric circulation to the radiative changes induced by CO2 forcing and climate feedbacks is currently uncertain. In this modeling study, the impact of CO2-induced climate feedbacks on changes in jet latitude and speed is assessed by imposing surface albedo, cloud, and water vapor feedbacks as if they were forcings in two climate models, CAM4 and ECHAM6. The jet response to radiative feedbacks can be broadly interpreted through changes in midlatitude baroclinicity. Clouds enhance baroclinicity, favoring a strengthened, poleward-shifted jet; this is mitigated by surface albedo changes, which have the opposite effect on baroclinicity and the jet, while water vapor has opposing effects on upper- and lower-level baroclinicity with little net impact on the jet. Large differences between the CAM4 and ECHAM6 responses illustrate how model uncertainty in radiative feedbacks causes a large spread in the baroclinicity response to CO2 forcing. Across the CMIP5 models, differences in shortwave feedbacks by clouds and albedo are a dominant contribution to this spread. Forcing CAM4 with shortwave cloud and albedo feedbacks from a representative set of CMIP5 models yields a wide range of jet responses that strongly correlate with the meridional gradient of the anomalous shortwave heating and the associated baroclinicity response. Differences in shortwave feedbacks statistically explain about 50% of the intermodel spread in CMIP5 jet shifts for the set of models used, demonstrating the importance of constraining radiative feedbacks for accurate projections of circulation changes.

scholarly journals The effect of forced change and unforced variability in heat waves, temperature extremes, and associated population risk in a CO<sub>2</sub>-warmed world

2021 ◽  
Vol 21 (15) ◽  
pp. 11889-11904
Author(s):  
Jangho Lee ◽  
Jeffrey C. Mast ◽  
Andrew E. Dessler
Keyword(s):  
Heat Waves ◽  
Southern Oscillation ◽  
Extreme Heat ◽  
Max Planck ◽  
Extreme Heat Events ◽  
Heat Extremes ◽  
The Impact ◽  
Global Population ◽  
Heat Events ◽  
Impacts Of Climate Change

Abstract. This study investigates the impact of global warming on heat and humidity extremes by analyzing 6 h output from 28 members of the Max Planck Institute Grand Ensemble driven by forcing from a 1 % yr−1 CO2 increase. We find that unforced variability drives large changes in regional exposure to extremes in different ensemble members, and these variations are mostly associated with El Niño–Southern Oscillation (ENSO) variability. However, while the unforced variability in the climate can alter the occurrence of extremes regionally, variability within the ensemble decreases significantly as one looks at larger regions or at a global population perspective. This means that, for metrics of extreme heat and humidity analyzed here, forced variability in the climate is more important than the unforced variability at global scales. Lastly, we found that most heat wave metrics will increase significantly between 1.5 and 2.0 ∘C, and that low gross domestic product (GDP) regions show significantly higher risks of facing extreme heat events compared to high GDP regions. Considering the limited economic adaptability of the population to heat extremes, this reinforces the idea that the most severe impacts of climate change may fall mostly on those least capable of adapting.

scholarly journals Human and natural drivers of the recent contrasting trends between daytime and nighttime hot extremes

2021 ◽  
Author(s):  
Sang-Wook Yeh ◽  
Eun-Hye Lee ◽  
Seung-Ki Min
Keyword(s):  
Climate Models ◽  
Heat Waves ◽  
Low Frequency ◽  
Extreme Heat ◽  
Boreal Summer ◽  
Human Society ◽  
Sudden Increase ◽  
Tropical Night ◽  
Extreme Heat Events ◽  
Heat Events

Abstract The frequency and duration of extreme heat events, including heat waves (HWs, daytime hot extremes) and tropical night (TNs), are increasing significantly as the climate warms, adversely affecting human health, agriculture, and energy consumption. Although many detection and attribution studies have examined extreme heat events, the underlying mechanisms associated with the recent increase in HWs and TNs remain unclear. In this study, we analyze the controlling factors behind the distinct increases in HW and TN events over the Northern Hemisphere during boreal summer (June to August). We found that the occurrence of HW events has been increasing gradually since 1980, mostly due to anthropogenic forcing. However, the occurrence of TN events increased abruptly during the late 1990s and has changed little since then. We demonstrate that this sudden increase in TN events is closely associated with low frequency variability in sea surface temperature, including the Pacific Decadal Oscillation, indicating its natural origin. We further found that CMIP5 climate models fail to capture the observed non-linear increases in TN events, implying potentially large uncertainty in future projections of nighttime heat events and its impacts on human society and ecosystem.

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