Robin T. Clark

Skillful long‐range prediction of European and North American winters

This work was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101), the UK Public Weather Service research program, and the European Union Framework 7 SPECS project. Leon Hermanson was funded as part of his Research Fellowship by Willis as part of Willis Research Network (WRN).

Modeling Northern Hemisphere Summer Heat Extreme Changes and Their Uncertainties Using a Physics Ensemble of Climate Sensitivity Experiments

Abstract Changes in extreme daily temperature events are examined using a perturbed physics ensemble of global model simulations under present-day and doubled CO2 climates where ensemble members differ in their representation of various physical processes. Modeling uncertainties are quantified by varying poorly constrained model parameters that control atmospheric processes and feedbacks and analyzing the ensemble spread of simulated changes. In general, uncertainty is up to 50% of projected changes in extreme heat events of the type that occur only once per year. Large changes are seen in distributions of daily maximum temperatures for June, July, and August with significant shifts to warmer conditions. Changes in extremely hot days are shown to be significantly larger than changes in mean values in some regions. The intensity, duration, and frequency of summer heat waves are expected to be substantially greater over all continents. The largest changes are found over Europe, North and South America, and ...

Simulation and Projection of the Southern Hemisphere Annular Mode in CMIP5 Models

Climate variability in the Southern Hemisphere (SH) extratropical regions is dominated by the SH annular mode(SAM). FuturechangesintheSAMcouldhavealargeinfluenceontheclimateoverbroadregions.Inthis paper, the authors utilized model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to examine projected future changes in the SAM during the austral summer [December‐February (DJF)]. To start off, first, the ability of the models in reproducing the recently observed spatial and temporal variability was assessed. The 12CMIP5 models examined were found to reproduce the SAM’s spatial pattern reasonably well in terms of both the symmetrical and the asymmetric component. The CMIP5 models show an improvement over phase 3 of CMIP (CMIP3) in simulating the seesaw structure of the SAM and also give improvements inthe recentlyobserved positiveSAM trend.However,onlyhalfthe models appeared tobeable tocapturetwomajorrecentdecadalSAMphases.Then,thefutureSAMtrendsanditssensitivitytogreenhouse gas (GHG) concentrations using simulations based on the representative concentration pathways 4.5 (RCP4.5) and8.5(RCP8.5)wereexplored.WithRCP4.5,averyweaknegativetrendforthiscenturyisfound.Conversely, with RCP8.5,a significant positivetrend wasprojected,with amagnitudesimilartotherecentlyobserved trend. Finally, model uncertainty in the future SAM projections was quantified by comparing projections from the individual CMIP5 models. The results imply the response of SH polar region stratospheric temperature to GHGs could be a significant controlling factor on the future evolution of the SAM.

Multi-model multi-analysis ensembles in quasi-operational medium-range forecasting

Ensemble prediction systems (EPS) for medium-range forecasting attempt to account for uncertainty in numerical weather prediction (NWP) by sampling the distribution function of future atmospheric states. Forecast uncertainty derives from uncertainty in both the analysed initial conditions (analysis errors) and in the forecast evolution (model errors). Current operational systems are primarily based on sampling the analysis errors through initial-condition perturbations with, at best, only limited sampling of model errors. One approach to sampling model errors and also to widening the sampling of analysis errors, is to include more than one NWP model, and more than one operational analysis to which perturbations are added, in the ensemble system. Previous work has demonstrated from a small number of case-studies that this multi-model multi-analysis ensemble (MMAE) approach can perform significantly better than a single-model system such as the Ensemble Prediction System (EPS) run by the ECMWF (European Centre for Medium-Range Weather Forecasts). In this study a MMAE was created by combining the ECMWF ensemble with an ensemble using the Met Office model and analysis, and was run daily for a year to assess the benefits over a larger, quasi-operational sample of forecasts. The results are compared with the operational ECMWF EPS which includes the latest upgrades, including stochastic physics which makes some allowance for uncertainty due to model errors. Results show that both for probabilistic forecasts (assessed by Brier skill scores and relative operating characteristics) and for deterministic forecasts based on the ensemble mean (assessed by root-mean square errors) the MMAE has increased forecast skill relative to the EPS. These improvements are obtained with no overall increase in ensemble size. Ensemble spread is also greater in the MMAE, and the increased skill is believed to be due to the additional model producing solutions which are synoptically more different than those produced by a single model ensemble. Benefits of the MMAE vary both in time and with geographical region, depending on which individual ensemble system performs better in particular synoptic situations. It is found that the MMAE almost always performs as well as the best individual ensemble, and on occasions better than either of them.

European wind variability over 140 yr

Abstract. We present initial results of a study on the variability of wind speeds across Europe over the past 140 yr, making use of the recent Twentieth Century Reanalysis data set, which includes uncertainty estimates from an ensemble method of reanalysis. Maps of the means and standard deviations of daily wind speeds, and the Weibull-distribution parameters, show the expected features, such as the strong, highly-variable wind in the north-east Atlantic. We do not find any clear, strong long-term trends in wind speeds across Europe, and the variability between decades is large. We examine how different years and decades are related in the long-term context, by looking at the ranking of annual mean wind speeds. Picking a region covering eastern England as an example, our analyses show that the wind speeds there over the past ~ 20 yr are within the range expected from natural variability, but do not span the full range of variability of the 140-yr data set. The calendar-year 2010 is however found to have the lowest mean wind speed on record for this region.

Using the Twentieth Century Reanalysis to assess climate variability for the European wind industry

We characterise the long-term variability of European near-surface wind speeds using 142 years of data from the Twentieth Century Reanalysis (20CR), and consider the potential of such long-baseline climate data sets for wind energy applications. The low resolution of the 20CR would severely restrict its use on its own for wind farm site-screening. We therefore perform a simple statistical calibration to link it to the higher-resolution ERA-Interim data set (ERAI), such that the adjusted 20CR data has the same wind speed distribution at each location as ERAI during their common period. Using this corrected 20CR data set, wind speeds and variability are characterised in terms of the long-term mean, standard deviation and corresponding trends. Many regions of interest show extremely weak trends on century timescales, but contain large multidecadal variability. Since reanalyses such as ERAI are often used to provide the background climatology for wind farm site assessments, but contain only a few decades of data, our results can be used as a way of incorporating decadal-scale wind climate variability into such studies, allowing investment risks for wind farms to be reduced.

Future projections of temperature-related climate change impacts on the railway network of Great Britain

Great Britain’s main line railway network is known to experience various temperature-related impacts, e.g. track buckling and overhead power line sag at high ambient temperatures. Climate change could alter the frequency of occurrence of these impacts. We have therefore investigated the climate change impact on various temperature-related issues, identified during workshops with rail industry specialists, using a perturbed physics ensemble (PPE) of the Met Office’s regional climate model (RCM), HadRM3. We have developed novel approaches to combine RCM data with railway industry knowledge, typically by identifying key meteorological thresholds of interest and analysing exceedance of these out to the 2040s. We performed a statistical analysis of the projected changes for each issue, via bootstrapping of the unperturbed PPE member. Although neither the PPE nor the bootstrapping analysis samples the full range of uncertainty in the projections, they nonetheless provide complementary perspectives on the suitability of the projections for use in decision-making. Our main findings include projected increases in the summertime occurrence of temperature conditions associated with (i) track buckling, (ii) overhead power line sag, (iii) exposure of outdoor workers to heat stress, and (iv) heat-related delays to track maintenance; and (v) projected decreases in the wintertime occurrence of temperatures conditions associated with freight train failure owing to brake problems. For (i), the statistical significance varied with track condition and location; for (ii) and (iii), with location; and for (iv) and (v), projected changes were significant across Great Britain. As well as assessing the changes in climate-related hazard, information about the vulnerability of the network to past temperature-related incidents has been summarised. Combining the hazard and vulnerability elements will eventually support a climate risk assessment for the industry.

Influences of Circulation and Climate Change on European Summer Heat Extremes

AbstractAtmospheric circulation patterns occurring on the warmest 10% of summer days for a region of Europe severely impacted by the 2003 heatwave have been identified using a perturbed parameter ensemble of regional high-resolution climate model simulations for the recent past. Changes in the frequency and duration of these circulation types, driven by the simulations following a moderate transient pathway of anthropogenic emissions, are then shown for the period 2070 to 2100. Increases in the future probability of hot days are then attributed separately to changes in the frequency and temperature intensity of the circulation types. Changes in temperature intensity are found to have an effect 2 to 3 times larger than in frequency.The authors then consider how model uncertainty in changes of future temperature within circulation patterns compares to the uncertainty irrespective of circulation, in an attempt to exclude contributions to the overall uncertainty arising from changes in circulation. Within ind...

Transient climate changes in a perturbed parameter ensemble of emissions-driven earth system model simulations

We describe results from a 57-member ensemble of transient climate change simulations, featuring simultaneous perturbations to 54 parameters in the atmosphere, ocean, sulphur cycle and terrestrial ecosystem components of an earth system model (ESM). These emissions-driven simulations are compared against the CMIP3 multi-model ensemble of physical climate system models, used extensively to inform previous assessments of regional climate change, and also against emissions-driven simulations from ESMs contributed to the CMIP5 archive. Members of our earth system perturbed parameter ensemble (ESPPE) are competitive with CMIP3 and CMIP5 models in their simulations of historical climate. In particular, they perform reasonably well in comparison with HadGEM2-ES, a more sophisticated and expensive earth system model contributed to CMIP5. The ESPPE therefore provides a computationally cost-effective tool to explore interactions between earth system processes. In response to a non-intervention emissions scenario, the ESPPE simulates distributions of future regional temperature change characterised by wide ranges, and warm shifts, compared to those of CMIP3 models. These differences partly reflect the uncertain influence of global carbon cycle feedbacks in the ESPPE. In addition, the regional effects of interactions between different earth system feedbacks, particularly involving physical and ecosystem processes, shift and widen the ESPPE spread in normalised patterns of surface temperature and precipitation change in many regions. Significant differences from CMIP3 also arise from the use of parametric perturbations (rather than a multimodel ensemble) to represent model uncertainties, and this is also the case when ESPPE results are compared against parallel emissions-driven simulations from CMIP5 ESMs. When driven by an aggressive mitigation scenario, the ESPPE and HadGEM2-ES reveal significant but uncertain impacts in limiting temperature increases during the second half of the twenty-first century. Emissions-driven simulations create scope for development of errors in properties that were previously prescribed in coupled ocean–atmosphere models, such as historical CO2 concentrations and vegetation distributions. In this context, historical intra-ensemble variations in the airborne fraction of CO2 emissions, and in summer soil moisture in northern hemisphere continental regions, are shown to be potentially useful constraints, subject to uncertainties in the relevant observations. Our results suggest that future climate-related risks can be assessed more comprehensively by updating projection methodologies to support formal combination of emissions-driven perturbed parameter and multi-model earth system model simulations with suitable observational constraints. This would provide scenarios underpinned by a more complete representation of the chain of uncertainties from anthropogenic emissions to future climate outcomes.

Increasing Flash Floods in a Drying Climate over Southwest China

In a globally warming world, subtropical regions are generally expected to become drier while the tropics and mid–high latitudes become wetter. In line with this, Southwest China, close to 25°N, is expected to become increasingly prone to drought if annual mean precipitation decreases. However, despite this trend, changes in the temporal distribution of moisture supply might actually result in increased extreme rainfall in the region, whose climate is characterized by distinct dry and wet seasons. Using hourly and daily gauge observations, rainfall intensity changes since 1971 are examined for a network of 142 locations in the region. From the analysis, dry season changes are negligible but wet season changes exhibit a significantly strong downward trend [−2.4% (10 yr)−1], particularly during the past 15 years [−17.7% (10 yr)−1]. However, the intensity of events during the wettest of 5% hours appears to steadily increase during the whole period [1.4% (10 yr)−1], tying in with government statistical reports of recent droughts and flooding. If the opposing trends are a consequence of a warming climate, it is reasonable to expect the contradictory trend to continue with an enhanced risk of flash flooding in coming decades in the region concerned.摘要在全球变暖的背景下, 通常认为副热带地区降水减少, 热带和中高纬度降水增加. 基于此, 对于中国西南地区, 降水减少, 干旱的潜在风险是增加的、洪涝的潜在风险应该是减少的. 本文研究发现一个有意思的现象, 对于西南这样一个干湿季特别分明的地区, 即便降水在减少, 强降水的风险并没有减少. 通过逐小时等高时空分辨率的降水资料分析发现, 近些年西南地区呈现的降水减少趋势, 主要是由于雨季降水的减少造成的, 干季的降水变化不大, 对全年降水的贡献也不大. 而雨季降水虽然明显减少, 但是雨季强降水并没有减少, 无论是强度大于95%分位的降水事件, 还是降水大于20mm每小时的事件, 都呈增加趋势, 这对于地形复杂的西南地区, 无疑增大了洪涝相关的灾害风险. 相关学者关于未来预估都有类似的结论. 因此, 这种相反的变化趋势(总降水减少, 但强降水增加)对于地方政府适应气候变化而言, 洪涝灾害防御工作和干旱同样值得重视.