Improved confidence in climate change projections of precipitation evaluated using daily statistics from the PRUDENCE ensemble

An ensemble of regional climate modelling simulations from the European framework project PRUDENCE are compared across European sub-regions with observed daily precipitation from the European Climate Assessment dataset by characterising precipitation in terms of probability density functions (PDFs). Models that robustly describe the observations for the control period (1961–1990) in given regions as well as across regions are identified, based on the overlap of normalised PDFs, and then validated, using a method based on bootstrapping with replacement. We also compare the difference between the scenario period (2071–2100) and the control period precipitation using all available models. By using a metric quantifying the deviation over the entire PDF, we find a clearly marked increase in the contribution to the total precipitation from the more intensive events and a clearly marked decrease for days with light precipitation in the scenario period. This change is tested to be robust and found in all models and in all sub-regions. We find a detectable increase that scales with increased warming, making the increase in the PDF difference a relative indicator of climate change level. Furthermore, the crossover point separating decreasing from increasing contributions to the normalised precipitation spectrum when climate changes does not show any significant change which is in accordance with expectations assuming a simple analytical fit to the precipitation spectrum.     

Comparison of dryland climate change in observations and CMIP5 simulations

A comparison of observations with 20 climate model simulations from the Coupled Model Intercomparison Project, Phase5(CMIP5) revealed that observed dryland expansion amounted to 2.61 × 106km2 during the 58 years from 1948 to 2005,which was four times higher than that in the simulations(0.55 × 106km2). Dryland expansion was accompanied by a decline in aridity index(AI)(drying trend) as a result of decreased precipitation and increased potential evapotranspiration across all dryland subtype areas in the observations, especially in the semi-arid and dry subhumid regions. However, the CMIP5multi-model ensemble(MME) average performed poorly with regard to the decreasing trends of AI and precipitation. By analyzing the factors controlling AI, we found that the overall bias of AI in the simulations, compared with observations, was largely due to limitations in the simulation of precipitation. The simulated precipitation over global drylands was substantially overestimated compared with observations across all subtype areas, and the spatial distribution of precipitation in the MME was largely inconsistent in the African Sahel, East Asia, and eastern Australia, where the semi-arid and dry subhumid regions were mainly located.     

Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results

Four high resolution atmospheric general circulation models (GCMs) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre sea surface temperature and sea-ice extent. The response over Europe, calculated as the difference between the 2071–2100 and the 1961–1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs—in particular in terms of precipitation—is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes. The temperature response is larger than the systematic error. The situation is different for precipitation. The model bias is twice as large as the climate response. The confidence in PRUDENCE results comes from the fact that the models have a similar response to the IPCC-SRES A2 forcing, whereas their systematic errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs.     

Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

The study examines future scenarios of precipitation extremes over Central Europe in an ensemble of 12 regional climate model (RCM) simulations with the 25-km resolution, carried out within the European project ENSEMBLES. We apply the region-of-influence method as a pooling scheme when estimating distributions of extremes, which consists in incorporating data from a ‘region’ (set of gridboxes) when fitting an extreme value distribution in any single gridbox. The method reduces random variations in the estimates of parameters of the extreme value distribution that result from large spatial variability of heavy precipitation. Although spatial patterns differ among the models, most RCMs simulate increases in high quantiles of precipitation amounts when averaged over the area for the late-twenty-first century (2070–2099) climate in both winter and summer. The sign as well as the magnitude of the projected change vary only little for individual parts of the distribution of daily precipitation in winter. In summer, on the other hand, the projected changes increase with the quantile of the distribution in all RCMs, and they are negative (positive) for parts of the distribution below (above) the 98% quantile if averaged over the RCMs. The increases in precipitation extremes in summer are projected in spite of a pronounced drying in most RCMs. Although a rather general qualitative agreement of the models concerning the projected changes of precipitation extremes is found in both winter and summer, the uncertainties in climate change scenarios remain large and would likely further increase considerably if a more complete ensemble of RCM simulations driven by a larger suite of global models and with a range of possible scenarios of the radiative forcing is available.     

Climate change in Central America and Mexico: regional climate model validation and climate change projections

Central America has high biodiversity, it harbors high-value ecosystems and it??s important to provide regional climate change information to assist in adaptation and mitigation work in the region. Here we study climate change projections for Central America and Mexico using a regional climate model. The model evaluation shows its success in simulating spatial and temporal variability of temperature and precipitation and also in capturing regional climate features such as the bimodal annual cycle of precipitation and the Caribbean low-level jet. A variety of climate regimes within the model domain are also better identified in the regional model simulation due to improved resolution of topographic features. Although, the model suffers from large precipitation biases, it shows improvements over the coarse-resolution driving model in simulating precipitation amounts. The model shows a dry bias in the wet season and a wet bias in the dry season suggesting that it??s unable to capture the full range of precipitation variability. Projected warming under the A2 scenario is higher in the wet season than that in the dry season with the Yucatan Peninsula experiencing highest warming. A large reduction in precipitation in the wet season is projected for the region, whereas parts of Central America that receive a considerable amount of moisture in the form of orographic precipitation show significant decreases in precipitation in the dry season. Projected climatic changes can have detrimental impacts on biodiversity as they are spatially similar, but far greater in magnitude, than those observed during the El Ni?o events in recent decades that adversely affected species in the region.     

Consequences of climate change for the soil climate in Central Europe and the central plains of the United States

This study aims to evaluate soil climate quantitatively under present and projected climatic conditions across Central Europe (12.1°–18.9° E and 46.8°–51.1° N) and the U.S. Central Plains (90°–104° W and 37°–49° N), with a special focus on soil temperature, hydric regime, drought risk and potential productivity (assessed as a period suitable for crop growth). The analysis was completed for the baselines (1961–1990 for Europe and 1985–2005 for the U.S.) and time horizons of 2025, 2050 and 2100 based on the outputs of three global circulation models using two levels of climate sensitivity. The results indicate that the soil climate (soil temperature and hydric soil regimes) will change dramatically in both regions, with significant consequences for soil genesis. However, the predicted changes of the pathways are very uncertain because of the range of future climate systems predicted by climate models. Nevertheless, our findings suggest that the risk of unfavourable dry years will increase, resulting in greater risk of soil erosion and lower productivity. The projected increase in the variability of dry and wet events combined with the uncertainty (particularly in the U.S.) poses a challenge for selecting the most appropriate adaptation strategies and for setting adequate policies. The results also suggest that the soil resources are likely be under increased pressure from changes in climate.     

Economic impacts of climate change in Europe: sea-level rise

This paper uses two models to examine the direct and indirect costs of sea-level rise for Europe for a range of sea-level rise scenarios for the 2020s and 2080s: (1) the DIVA model to estimate the physical impacts of sea-level rise and the direct economic cost, including adaptation, and (2) the GTAP-EF model to assess the indirect economic implications. Without adaptation, impacts are quite significant with a large land loss and increase in the incidence of coastal flooding. By the end of the century Malta has the largest relative land loss at 12% of its total surface area, followed by Greece at 3.5% land loss. Economic losses are however larger in Poland and Germany (483 and483 and 391 million, respectively). Coastal protection is very effective in reducing these impacts and optimally undertaken leads to protection levels that are higher than 85% in the majority of European states. While the direct economic impact of sea-level rise is always negative, the final impact on countries’ economic performances estimated with the GTAP-EF model may be positive or negative. This is because factor substitution, international trade, and changes in investment patterns interact with possible positive implications. The policy insights are (1) while sea-level rise has negative and huge direct economic effects, overall effects on GDP are quite small (max −0.046% in Poland); (2) the impact of sea-level rise is not confined to the coastal zone and sea-level rise indirectly affects landlocked countries as well (Austria for instance loses −0.003% of its GDP); and (3) adaptation is crucial to keep the negative impacts of sea-level rise at an acceptable level.     

Validation of present-day regional climate simulations over Europe: LAM simulations with observed boundary conditions

 Nested limited-area modelling is one method of down-scaling general circulation model (GCM) climate change simulations. To give credibility to this method the nested limited-area model (LAM) must be shown to simulate local present-day climate conditions fairly accurately. Here seven different European limited-area models driven by observed boundary conditions (operational weather forecast analyses) are validated against observations, and inter-compared for summer and winter months. Relatively large biases are found. In summer large positive surface air temperature biases are found over southeast Europe. The main reason is deficiencies in the surface hydrological schemes causing an unrealistic drying of the soil. In at least one of the models, most likely several of them, an additional factor is an overestimation of incoming solar radiation. Apart from excessive precipitation in mountainous areas in some models they generally show a negative bias due to the drying and decreased advection from the Atlantic. In winter most models have a positive precipitation bias which seems to be caused by an enhancement of advection from the Atlantic and enhanced cyclone activity. Surface air temperature biases are negative probably due to an underestimation of the incoming longwave radiation. Received: 11 December 1996 / Accepted: 17 March 1997     

Socioeconomic geography of climate change views in Europe

Climate change views have their socioeconomic foundations but also specific geographies. In merging these perspectives, this analysis uses ESS Round 8 data from 23 European countries to examine whether climate change scepticism and concern, pro-environmental personal norm and a willingness to engage in energy-saving behaviour exhibit, first, urban–rural and/or regional differences, and second, if these attitudes can be explained at individual level by socioeconomic position and wellbeing resources. We find that climate change scepticism and concern do exhibit urban–rural differences, where living in a country village is associated with greater climate scepticism and lower concern compared to living in a big city. Also, higher climate change concern and pro-environmental norms are associated with living in a region with constant population growth. These geographical differences are independent of individual-level socioeconomic attributes as well as one’s political orientation. Additionally, the results show that both climate change attitudes and reporting energy-saving behaviour are strongly stratified by level of education and reveal that those in lower income deciles feel less pro-environmental norm but nonetheless report greater engagement with energy-saving behaviour. In sum, the results highlight that climate change mitigation is not a uniform project either spatially or within certain socioeconomic strata. Hence, our results suggest that socioeconomic disadvantage (belonging to the lowest education and income levels) and spatial marginalisation (living in more rural surroundings and declining regions) should be better acknowledged when reworking climate change and environmental policies in the EU.     

Uncertainties linked to land-surface processes in climate change simulations

 The impact of climate change on the hydrology of continental surfaces is critical for human activities but the response of the surface to this perturbation may also affect the sensitivity of the climate. This complex feedback is simulated in general circulation models (GCMs) used for climate change predictions by their land-surface schemes. The present study attempts to quantify the uncertainty associated with these schemes and what impact it has on our confidence in the simulated climate anomalies. Four GCMs, each coupled to two different land-surface schemes, are used to explore the spectrum of uncertainties. It is shown that, in this sample, surface processes have a significant contribution to our ability to predict surface temperature changes and perturbations of the hydrological cycle in an environment with doubled greenhouse gas concentration. The results reveal that the uncertainty introduced by land-surface processes in the simulated climate is different from its impact on the sensitivity of GCMs to climate change, indeed an alteration of the surface parametrization with little impact on model climate can affect sensitivity significantly. This result leads us to believe that the validation of land-surface schemes should not be limited to the current climate but should also cover their sensitivity to variations in climatic forcing. Received: 24 June 1999 / Accepted: 20 April 2000     

Uncertainties in the regional climate models simulations of South-Asian summer monsoon and climate change

The uncertainties in the regional climate models (RCMs) are evaluated by analyzing the driving global data of ERA40 reanalysis and ECHAM5 general circulation models, and the downscaled data of two RCMs (RegCM4 and PRECIS) over South-Asia for the present day simulation (1971–2000) of South-Asian summer monsoon. The differences between the observational datasets over South-Asia are also analyzed. The spatial and the quantitative analysis over the selected climatic regions of South-Asia for the mean climate and the inter-annual variability of temperature, precipitation and circulation show that the RCMs have systematic biases which are independent from different driving datasets and seems to come from the physics parameterization of the RCMs. The spatial gradients and topographically-induced structure of climate are generally captured and simulated values are within a few degrees of the observed values. The biases in the RCMs are not consistent with the biases in the driving fields and the models show similar spatial patterns after downscaling different global datasets. The annual cycle of temperature and rainfall is well simulated by the RCMs, however the RCMs are not able to capture the inter-annual variability. ECHAM5 is also downscaled for the future (2071–2100) climate under A1B emission scenario. The climate change signal is consistent between ECHAM5 and RCMs. There is warming over all the regions of South-Asia associated with increasing greenhouse gas concentrations and the increase in summer mean surface air temperature by the end of the century ranges from 2.5 to 5 °C, with maximum warming over north western parts of the domain and 30 % increase in rainfall over north eastern India, Bangladesh and Myanmar.     

极值统计理论的进展及其在气候变化研究中的应用

提出一种利用重现期方法构建区域性暴雨过程的评估模型,用于全面评估暴雨过程发生的频率和强度。基于2011—2021年重庆市114次区域性暴雨过程的小时雨量数据及暴雨灾情数据,利用概率分布函数拟合、重现期计算、相关分析等方法,构建区域性暴雨过程的重现期评估模型,并开展业务检验。结果表明：(1)利用自建的重现期计算公式,得到暴雨过程特征量的重现值与原始值的误差小于10%,重现期计算结果准确性较高。(2)构建的重现期评估模型与直接经济损失的正相关系数可通过0.001显著性水平检验,较现行业务指标提高16%。(3)历史回算和独立样本检验结果显示,重现期评估模型与业务指标评估等级一致率达70%,模型稳定性强且能反映事件发生频率和强度,可为区域性暴雨过程评估提供新思路。

     

Europe adapts to climate change: Comparing National Adaptation Strategies

For the last two decades, European climate policy has focused almost exclusively on mitigation of climate change. It was only well after the turn of the century, with impacts of climate change increasingly being observed, that adaptation was added to the policy agenda and EU Member States started to develop National Adaptation Strategies (NASs). This paper reviews seven National Adaptation Strategies that were either formally adopted or under development by Member States at the end of 2008. The strategies are analysed under the following six themes. Firstly, the factors motivating and facilitating the development of a national adaptation strategy. Secondly, the scientific and technical support needed for the development and implementation of such a strategy. Thirdly, the role of the strategy in information, communication and awareness-raising of the adaptation issue. Fourthly, new or existing forms of multi-level governance to implement the proposed actions. Fifthly, how the strategy addresses integration and coordination with other policy domains. Finally, how the strategy suggests the implementation and how the strategy is evaluated. The paper notes that the role of National Adaptation Strategies in the wider governance of adaptation differs between countries but clearly benchmarks a new political commitment to adaptation at national policy levels. However, we also find that in most cases approaches for implementing and evaluating the strategies are yet to be defined. The paper concludes that even though the strategies show great resemblance in terms of topics, methods and approaches, there are many institutional challenges, including multi-level governance and policy integration issues, which can act as considerable barriers in future policy implementation.     

Simulated climate and CO2—Induced climate change over Western Europe

The use of a relatively high resolution general circulation model (the Meteorological Office 5-layer model) to determine climate changes for impact studies is evaluated. The simulation of present day climate over Western Europe is assessed by comparing not only different seasons with climatological data, but also the mean annual cycle and the frequency of extreme events. It is found that while the broad features of the simulation are satisfactory, the model produces too many cold episodes in spring, and an excessive number of wet days over northern Europe. When atmospheric CO₂ concentrations are quadrupled, and sea surface temperatures and sea ice extents changed appropriately, the number of cold episodes is reduced and precipitation is less frequent in summer and autumn over much of Europe, and throughout the year in the south. The relevance of both the model data and the statistical tests to climate impact studies is discussed.     

Analyses of rainfall extremes in East Africa based on observations from rain gauges and climate change simulations by CORDEX RCMs

Climate Dynamics - This study derived twelve Extreme Rainfall Indices (ERIs) such as the Maximum Dry Spell (MDS) and Maximum Wet Spell (MWS) from daily rainfall observed over the period...     

Integrated scenarios of acidification and climate change in Asia and Europe

Two integrated assessment models, one for climate change on a global scale (IMAGE 2) and another for the regional analysis of the impacts of acidifying deposition (RAINS), have been linked to assess the impacts of reducing sulphur emission on ecosystems in Asia and Europe. While such reductions have the beneficial effect of reducing the deposition of acidifying compounds and thus the exceedance of critical loads of ecosystems, they also reduce the global level of sulphate aerosols and thus enhance the impact of increased emissions of greenhouse gases, and consequently increase the risk of potential vegetation changes. The calculations indicate that about 70% of the ecosystems in Asia would be affected by either acid deposition or climate change in the year 2100 (up from 20% in 1990) for both sulphur emission scenarios (controlled and uncontrolled), whereas in Europe the impacted area would remain at a level of about 50%, with a dip early next century. More generally, the effects of reducing sulphur emissions and thus enhancing climate change would about balance for the Asian region, whereas for Europe the desirable impact of sulphur emission reductions would greatly outweigh its undesirable effects.     

An intercomparison of regional climate simulations for Europe: assessing uncertainties in model projections

Ten regional climate models (RCM) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre boundary conditions. The response over Europe, calculated as the difference between the 2071–2100 and the 1961–1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance in eight sub-European boxes. Four sources of uncertainty can be evaluated with the material provided by the PRUDENCE project. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30). Model uncertainty is due to the fact that the models use different techniques to discretize the equations and to represent sub-grid effects. Radiative uncertainty is due to the fact that IPCC-SRES A2 is merely one hypothesis. Some RCMs have been run with another scenario of greenhouse gas concentration (IPCC-SRES B2). Boundary uncertainty is due to the fact that the regional models have been run under the constraint of the same global model. Some RCMs have been run with other boundary forcings. The contribution of the different sources varies according to the field, the region and the season, but the role of boundary forcing is generally greater than the role of the RCM, in particular for temperature. Maps of minimum expected 2m temperature and precipitation responses for the IPCC-A2 scenario show that, despite the above mentioned uncertainties, the signal from the PRUDENCE ensemble is significant.