scholarly journals Response of Vertical Velocities in Extratropical Precipitation Extremes to Climate Change

2020 ◽  
Vol 33 (16) ◽  
pp. 7125-7139 ◽  
Author(s):  
Ziwei Li ◽  
Paul A. O’Gorman
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Extreme Event ◽  
Static Stability ◽  
Precipitation Extremes ◽  
Positive Contribution ◽  
Latent Heating ◽  
Upward Motion ◽  
Horizontal Length ◽  
Omega Equation

AbstractPrecipitation extremes intensify in most regions in climate model projections. Changes in vertical velocities contribute to the changes in intensity of precipitation extremes but remain poorly understood. Here, we find that midtropospheric vertical velocities in extratropical precipitation extremes strengthen overall in simulations of twenty-first-century climate change. For each extreme event, we solve the quasigeostrophic omega equation to decompose this strengthening into different physical contributions. We first consider a dry decomposition in which latent heating is treated as an external forcing of upward motion. Much of the positive contribution to upward motion from increased latent heating is offset by negative contributions from increases in dry static stability and changes in the horizontal length scale of vertical velocities. However, taking changes in latent heating as given is a limitation when the aim is to understand changes in precipitation, since latent heating and precipitation are closely linked. Therefore, we also perform a moist decomposition of the changes in vertical velocities in which latent heating is represented through a moist static stability. In the moist decomposition, changes in moist static stability play a key role and contributions from other factors such as changes in the depth of the upward motion increase in importance. While both dry and moist decompositions are self-consistent, the moist dynamical perspective has greater potential to give insights into the causes of the dynamical contributions to changes in precipitation extremes in different regions.

scholarly journals Attributing compound events to anthropogenic climate change

2021 ◽  
pp. 1-45
Author(s):  
Jakob Zscheischler ◽  
Flavio Lehner
Keyword(s):  
Climate Change ◽  
South Africa ◽  
Climate Model ◽  
Extreme Event ◽  
Synthetic Data ◽  
Anthropogenic Climate Change ◽  
Anthropogenic Influence ◽  
Western Cape ◽  
Event Attribution ◽  
Compound Events

AbstractExtreme event attribution answers the question whether and by how much anthropogenic climate change has contributed to the occurrence or magnitude of an extreme weather event. It is also used to link extreme event impacts to climate change. Impacts, however, are often related to multiple compounding climate drivers. Because extreme event attribution typically focuses on univariate assessments, these assessments might only provide a partial answer to the question of anthropogenic influence to a high-impact event. We present a theoretical extension to classical extreme event attribution for certain types of compound events. Based on synthetic data we illustrate how the bivariate fraction of attributable risk (FAR) differs from the univariate FAR depending on the extremeness of the event as well as the trends in and dependence between the contributing variables. Overall, the bivariate FAR is similar in magnitude or smaller than the univariate FAR if the trend in the second variable is comparably weak and the dependence between both variables is moderate or high, a typical situation for temporally co-occurring heatwaves and droughts. If both variables have similarly large trends or the dependence between both variables is weak, bivariate FARs are larger and are likely to provide a more adequate quantification of the anthropogenic influence. Using multiple climate model large ensembles, we apply the framework to two case studies, a recent sequence of hot and dry years in the Western Cape region of South Africa and two spatially co-occurring droughts in crop-producing regions in South Africa and Lesotho.

scholarly journals Modelling the impact of superimposed ice on the mass balance of an Arctic glacier under scenarios of future climate change

2005 ◽  
Vol 42 ◽  
pp. 277-283 ◽  
Author(s):  
Andrew Wright ◽  
Jemma Wadham ◽  
Martin Siegert ◽  
Adrian Luckman ◽  
Jack Kohler
Keyword(s):  
Climate Change ◽  
Mass Balance ◽  
Climate Model ◽  
Global Climate Model ◽  
Balance Model ◽  
Explicit Calculation ◽  
Future Climate Change ◽  
Glacier Mass Balance ◽  
Positive Contribution ◽  
The Impact

AbstractA surface-energy/mass-balance model with an explicit calculation of meltwater refreezing and superimposed ice formation is applied to midre Lovénbreen, Spitsbergen, Svalbard. The model is run with meteorological measurements to represent the present climate, and run with scenarios taken from global climate model predictions based on the IS92a emissions scenario to represent future climates. Model results indicate that superimposed ice accounts for on average 37% of the total net accumulation under present conditions. The model is found to be highly sensitive to changes in the mean annual air temperature and much less sensitive to changes in the total annual precipitation. A 0.5˚C decade–1 temperature increase is predicted to cause an average mass-balance change of –0.43 ma–1, while a 2% decade–1 increase in precipitation will result in only a +0.02 ma–1 change in mass balance. An increase in temperature results in a significant decrease in the size of the accumulation area at midre Lovénbreen and hence a similar decrease in the net volume of superimposed ice. The model predicts, however, that the relative importance of superimposed ice will increase to account for >50% of the total accumulation by 2050. The results show that the refreezing of meltwater and in particular the formation of superimposed ice make an important positive contribution to the mass balance of midre Lovénbreen under present conditions and will play a vital future role in slowing down the response of glacier mass balance to climate change.

scholarly journals Climate change increases the probability of heavy rains like those of storm Desmond in the UK – an event attribution study in near-real time

2015 ◽  
Vol 12 (12) ◽  
pp. 13197-13216 ◽  
Author(s):  
G. J. van Oldenborgh ◽  
F. E. L. Otto ◽  
K. Haustein ◽  
H. Cullen
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Extreme Event ◽  
Initial Assessment ◽  
Model Simulations ◽  
Event Attribution ◽  
Climate Model Simulations ◽  
Using Data ◽  
The Uk ◽  
Precipitation Events

Abstract. On 4–6 December 2015, the storm "Desmond" caused very heavy rainfall in northern England and Scotland, which led to widespread flooding. Here we provide an initial assessment of the influence of anthropogenic climate change on the likelihood of one-day precipitation events averaged over an area encompassing northern England and southern Scotland using data and methods available immediately after the event occurred. The analysis is based on three independent methods of extreme event attribution: historical observed trends, coupled climate model simulations and a large ensemble of regional model simulations. All three methods agree that the effect of climate change is positive, making precipitation events like this about 40 % more likely, with a provisional 2.5–97.5 % confidence interval of 5–80 %.

scholarly journals Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?

2016 ◽  
Author(s):  
Hossein Tabari ◽  
Rozemien De Troch ◽  
Olivier Giot ◽  
Rafiq Hamdi ◽  
Piet Termonia ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Spatial Resolution ◽  
Impact Analysis ◽  
Climate Models ◽  
Climate Model ◽  
Daily Precipitation ◽  
Reanalysis Data ◽  
Precipitation Extremes ◽  
Added Value

Abstract. This study explores whether climate models with higher spatial resolution provide higher accuracy for precipitation simulations and/or different climate change signals. The outputs from two convection-permitting climate models (ALARO and CCLM) with a spatial resolution of 3–4 km are compared with those from the coarse scale driving models or reanalysis data for simulating/projecting daily and sub-daily precipitation quantiles. The high-resolution ALARO and CCLM models reveal an added value to capture sub-daily precipitation extremes during summer compared to the driving GCMs and reanalysis data. Further validation of historical climate simulations based on design precipitation statistics derived from intensity–duration–frequency (IDF) curves shows a better match of the convection-permitting model results with the observations-based IDF statistics. Results moreover indicate that one has to be careful in assuming spatial scale independency of climate change signals for the delta change downscaling method, as high-resolution models may show larger changes in extreme precipitation. These larger changes appear to be dependent on the climate model, since such intensification is not observed for the ALARO model.

scholarly journals Pathways and pitfalls in extreme event attribution

2021 ◽  
Vol 166 (1-2) ◽  
Author(s):  
Geert Jan van Oldenborgh ◽  
Karin van der Wiel ◽  
Sarah Kew ◽  
Sjoukje Philip ◽  
Friederike Otto ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Extreme Event ◽  
Climate Change Impacts ◽  
Climate Science ◽  
Companion Paper ◽  
Lessons Learned ◽  
Future Climate Change ◽  
Practical Applications ◽  
Event Attribution

AbstractThe last few years have seen an explosion of interest in extreme event attribution, the science of estimating the influence of human activities or other factors on the probability and other characteristics of an observed extreme weather or climate event. This is driven by public interest, but also has practical applications in decision-making after the event and for raising awareness of current and future climate change impacts. The World Weather Attribution (WWA) collaboration has over the last 5 years developed a methodology to answer these questions in a scientifically rigorous way in the immediate wake of the event when the information is most in demand. This methodology has been developed in the practice of investigating the role of climate change in two dozen extreme events world-wide. In this paper, we highlight the lessons learned through this experience. The methodology itself is documented in a more extensive companion paper. It covers all steps in the attribution process: the event choice and definition, collecting and assessing observations and estimating probability and trends from these, climate model evaluation, estimating modelled hazard trends and their significance, synthesis of the attribution of the hazard, assessment of trends in vulnerability and exposure, and communication. Here, we discuss how each of these steps entails choices that may affect the results, the common problems that can occur and how robust conclusions can (or cannot) be derived from the analysis. Some of these developments also apply to other attribution methodologies and indeed to other problems in climate science.

scholarly journals An Investigation of cold-wet Compound Events in Greece

2021 ◽  
Author(s):  
Iason Markantonis ◽  
Diamando Vlachogiannis ◽  
Thanasis Sfetsos ◽  
Ioannis Kioutsioukis ◽  
Nadia Politi
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Extreme Event ◽  
Global Climate ◽  
Global Climate Model ◽  
Horizontal Resolution ◽  
Daily Minimum Temperature ◽  
Historical Period ◽  
Compound Events

<p>Climate change is set to affect extreme climate and meteorological events. The combination of interacting physical processes (climate drivers) across various spatial and temporal scales resulting to an extreme event is referred to as compound event. So far, climate change impacts on compound events in Greece such as daily cold-wet events have not been explored. The complex geography and topography of Greece forms a variety of regions with different local climate and a great range in daily minimum temperature and precipitation distributions. This leads to the assumption that there we will also observe a variety in the distribution of cold-wet events depending on the region. Aim of our study in this work is first to identify the cold-wet events based on observational data and then to examine the predictive capability of regional different climate models and ERA-Interim against observations from the Hellenic National Meteorological Service (HNMS) stations for the occurrence of cold-wet compound events in the present climate. The study will focus on the colder and wetter period of the year (November-April) to determine the extremes for this period. Specifically, the datasets employed are from two EURO-CORDEX Regional Climate Models (RCMs) with 0.11° horizontal resolution and validated ERA-Interim Reanalysis downscaled with the Weather Research and Forecasting (WRF) model at 5km horizontal resolution, for the historical period 1980-2004. In particular, the RCM datasets analyses have been produced from SMHI-RCA4 driven by MPI-M-MPI-ESM-LR Global Climate Model (GCM) and CLMcom-CLM-CCLM4-8-17 driven by MOHC-HadGEM2-ES GCM. After the comparison with the observations, the gridded data from the models will give us the ability to observe the spatial distribution of the compound events.</p>

Flood hazard estimation and climate change: impacts and uncertainties for Irish catchments using CMIP6

2020 ◽  
Author(s):  
Hadush Meresa ◽  
Conor Murphy ◽  
Rowan Fealy
Keyword(s):  
Climate Change ◽  
Flood Risk ◽  
Climate Model ◽  
Extreme Event ◽  
Flood Hazard ◽  
Coupled Model ◽  
Climate Change Impacts ◽  
Heavy Precipitation ◽  
Atmospheric Temperature ◽  
Projected Changes

<p>In the coming decades, climate change will likely become a complex issue affecting hydrological regimes and flood hazard conditions. According to the IPCC reports, significant changes in atmospheric temperature, precipitation, humidity, and circulation are expected which may lead to extreme events including flood, droughts, heatwaves, heavy precipitation, and more intense cyclones. Although the effects of climate change on flood hazard indices is subject to large uncertainty, the evaluation of high-flows plays a crucial role in flood risk planning and extreme event management. With the advent of the Coupled Model Intercomparison Project Phase 6 (CMIP6), flood managers are interested to know how changes in catchment flood risk are expected to alter relative to previous assessments. Here we examine catchment based projected changes in flood quantiles and extreme high flow events for Irish catchments, selected to be representative of the range of hydrological conditions on the island. Conceptual hydrological models, together with different downscaling techniques are used to examine changes in flood risk projected from the CMIP6 archive for mid and end of century. Results will inform the range of plausible changes expected for policy relevant flood indices, the sensitivity of findings to use of different climate model ensembles and inform the tailoring of adaptation plans to account for the new generation of climate model outputs.</p>

scholarly journals Robustness of Future Changes in Local Precipitation Extremes

2008 ◽  
Vol 21 (17) ◽  
pp. 4280-4297 ◽  
Author(s):  
Elizabeth J. Kendon ◽  
David P. Rowell ◽  
Richard G. Jones ◽  
Erasmo Buonomo
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Relative Effectiveness ◽  
Natural Variability ◽  
Precipitation Extremes ◽  
Adaptation To Climate Change ◽  
Full Spectrum ◽  
Mitigation And Adaptation ◽  
Climate Noise

Abstract Reliable projections of future changes in local precipitation extremes are essential for informing policy decisions regarding mitigation and adaptation to climate change. In this paper, the extent to which the natural variability of the climate affects one’s ability to project the anthropogenically forced component of change in daily precipitation extremes across Europe is examined. A three-member ensemble of the Hadley Centre Regional Climate Model (HadRM3H) is used and a statistical framework is applied to estimate the uncertainty due to the full spectrum of climate variability. In particular, the results and understanding presented here suggest that annual to multidecadal natural variability may contribute significant uncertainty. For this ensemble projection, extreme precipitation changes at the grid-box level are found to be discernible above climate noise over much of northern and central Europe in winter, and parts of northern and southern Europe in summer. The ability to quantify the change to a reasonable level of accuracy is largely limited to regions in northern Europe. In general, where climate noise has a significant component varying on decadal time scales, single 30-yr climate change projections are insufficient to infer changes in the extreme tail of the underlying precipitation distribution. In this context, the need for ensembles of integrations is demonstrated and the relative effectiveness of spatial pooling and averaging for generating robust signals of extreme precipitation change is also explored. The key conclusions are expected to apply more generally to other models and forcing scenarios.

Forecast-based attribution of a winter heatwave within the limit of predictability

2021 ◽  
Vol 118 (49) ◽  
pp. e2112087118
Author(s):  
Nicholas J. Leach ◽  
Antje Weisheimer ◽  
Myles R. Allen ◽  
Tim Palmer
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Extreme Event ◽  
False Negative ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Climate Change Signal ◽  
Weather Events ◽  
Medium Range ◽  
The Impact

Attribution of extreme weather events has expanded rapidly as a field over the past decade. However, deficiencies in climate model representation of key dynamical drivers of extreme events have led to some concerns over the robustness of climate model–based attribution studies. It has also been suggested that the unconditioned risk-based approach to event attribution may result in false negative results due to dynamical noise overwhelming any climate change signal. The “storyline” attribution framework, in which the impact of climate change on individual drivers of an extreme event is examined, aims to mitigate these concerns. Here we propose a methodology for attribution of extreme weather events using the operational European Centre for Medium-Range Weather Forecasts (ECMWF) medium-range forecast model that successfully predicted the event. The use of a successful forecast ensures not only that the model is able to accurately represent the event in question, but also that the analysis is unequivocally an attribution of this specific event, rather than a mixture of multiple different events that share some characteristic. Since this attribution methodology is conditioned on the component of the event that was predictable at forecast initialization, we show how adjusting the lead time of the forecast can flexibly set the level of conditioning desired. This flexible adjustment of the conditioning allows us to synthesize between a storyline (highly conditioned) and a risk-based (relatively unconditioned) approach. We demonstrate this forecast-based methodology through a partial attribution of the direct radiative effect of increased CO2 concentrations on the exceptional European winter heatwave of February 2019.

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