Impact of ECMWF,NCEP, and NCMRWF global model analysis on the WRF model forecast over Indian Region

The global model analysis has significant impact on the mesoscale model forecast as global model provides initial condition (IC) and lateral boundary conditions (LBC) for the mesoscale model. With this objective, four operational global model analyses prepared from the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS), NCEP Global Forecasting System (GFS), and National Centre for Medium Range Weather Forecasting (NCMRWF) are used daily to generate IC and LBC of the mesoscale model during 13th December 2012 to 13th January 2013. The Weather Research and Forecasting (WRF) model version 3.4, broadly used for short-range weather forecast, is adopted in this study as mesoscale model. After initial comparison of global model analyses with Atmospheric Infrared Sounder (AIRS) retrieved temperature and moisture profiles, daily WRF model forecasts initialized from global model analyses are compared with in situ observations and AIRS profiles. Results demonstrated that forecasts initialized from the ECMWF analysis are closer to AIRS-retrieved profiles and in situ observations compared to other global model analyses. No major differences are occurred in the WRF model forecasts when initialized from the NCEP GDAS and GFS analyses, whereas these two analyses have different spatial resolutions and observations used for assimilation. Maximum RMSD is seen in the NCMRWF analysis-based experiments when compared with AIRS-retrieved profiles. The rainfall prediction is also improved when WRF model is initialized from the ECMWF analysis compared to the NCEP and NCMRWF analyses.     

Evaluating regional climate model estimates against site-specific observed data in the UK

This paper compares precipitation, maximum and minimum air temperature and solar radiation estimates from the Hadley Centre’s HadRM3 regional climate model (RCM), (50 × 50 km grid cells), with observed data from 15 meteorological station in the UK, for the period 1960–90. The aim was to investigate how well the HadRM3 is able to represent weather characteristics for a historical period (hindcast) for which validation data exist. The rationale was to determine if the HadRM3 data contain systematic errors and to investigate how suitable the data are for use in climate change impact studies at particular locations. Comparing modelled and observed data helps assess and quantify the uncertainty introduced to climate impact studies. The results show that the model performs very well for some locations and weather variable combinations, but poorly for others. Maximum temperature estimations are generally good, but minimum temperature is overestimated and extreme cold events are not represented well. For precipitation, the model produces too many small events leading to a serious under estimation of the number of dry days (zero precipitation), whilst also over- or underestimating the mean annual total. Estimates represent well the temporal distribution of precipitation events. The model systematically over-estimates solar radiation, but does produce good quality estimates at some locations. It is concluded that the HadRM3 data are unsuitable for detailed (i.e. daily time step simulation model based) site-specific impacts studies in their current form. However, the close similarity between modelled and observed data for the historical case raises the potential for using simple adjustment methods and applying these to future projection data.     

Regional climate model sensitivity to domain size

Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere.     

The relative influence of soil moisture and SST in climate predictability explored within ensembles of AMIP type experiments

Three ensembles of AMIP-type simulations using the Arpege-climat coupled land–atmosphere model have been designed to assess the relative influence of SST and soil moisture (SM) on climate variability and predictability. The study takes advantage of the GSWP2 land surface reanalysis covering the 1986–1995 period. The GSWP2 forcings have been used to derive a global SM climatology that is fully consistent with the model used in this study. One ensemble of ten simulations has been forced by climatological SST and the simulated SM is relaxed toward the GSWP2 reanalysis. Another ensemble has been forced by observed SST and SM is evolving freely. The last ensemble combines the observed SST forcing and the relaxation toward GSWP2. Two complementary aspects of the predictability have been explored, the potential predictability (analysis of variance) and the effective predictability (skill score). An analysis of variance has revealed the effects of the SST and SM boundary forcings on the variability and potential predictability of near-surface temperature, precipitation and surface evaporation. While in the tropics SST anomalies clearly maintain a potentially predictable variability throughout the annual cycle, in the mid-latitudes the SST forced variability is only dominant in winter and SM plays a leading role in summer. In a similar fashion, the annual cycle of the hindcast skill (evaluated as the anomalous correlation coefficient of the three ensemble means with respect to the “observations”) indicates that the SST forcing is the dominant contributor over the tropical continents and in the winter mid-latitudes but that SM is supporting a significant part of the skill in the summer mid-latitudes. Focusing on boreal summer, we have then investigated different aspects of the SM and SST contribution to climate variations in terms of spatial distribution and time-evolution. Our experiments suggest that SM is potentially an additional source of climate predictability. A realistic initialization of SM and a proper representation of the land–atmosphere feedbacks seem necessary to improve state-of-the-art dynamical seasonal predictions, but will be actually efficient only in the areas where SM anomalies are themselves predictable at the monthly to seasonal timescale (since remote effects of SM are probably much more limited than SST teleconnections).     

Growth and Interactions of Multi-Source Perturbations in Convection-Allowing Ensemble Forecasts

This study investigated the growth of forecast errors stemming from initial conditions (ICs), lateral boundary conditions (LBCs), and model (MO) perturbations, as well as their interactions, by conducting seven 36 h convection- allowing ensemble forecast (CAEF) experiments. Two cases, one with strong-forcing (SF) and the other with weak-forcing (WF), occurred over the Yangtze-Huai River basin (YHRB) in East China, were selected to examine the sources of uncertainties associated with perturbation growth under varying forcing backgrounds and the influence of these back- grounds on growth. The perturbations exhibited distinct characteristics in terms of temporal evolution, spatial propagation, and vertical distribution under different forcing backgrounds, indicating a dependence between perturbation growth and forcing background. A comparison of the perturbation growth in different precipitation areas revealed that IC and LBC perturbations were significantly influenced by the location of precipitation in the SF case, while MO perturbations were more responsive to convection triggering and dominated in the WF case. The vertical distribution of perturbations showed that the sources of uncertainties and the performance of perturbations varied between SF and WF cases, with LBC perturbations displaying notable case dependence. Furthermore, the interactions between perturbations were considered by exploring the added values of different source perturbations. For the SF case, the added values of IC, LBC, and MO perturbations were reflected in different forecast periods and different source uncertainties, suggesting that the combination of multi-source perturbations can yield positive interactions. In the WF case, MO perturbations provided a more accurate estimation of uncertainties downstream of the Dabie Mountain and need to be prioritized in the research on perturbation development.     

Validation of the nesting technique in a regional climate model and sensitivity tests to the resolution of the lateral boundary conditions during summer

The ability of a regional climate model (RCM) to successfully reproduce the fine-scale features of a regional climate during summer is evaluated using an approach nick-named the “Big-Brother Experiment” (BBE). The BBE establishes a reference virtual-reality climate with a RCM applied on a large and high-resolution domain: this simulation is called the Big-Brother (BB) simulation. This reference simulation is then downgraded by filtering small-scale features that are unresolved in today’s global objective analyses. The resulting fields are then used as nesting data to drive the same RCM, which is integrated, at the same high resolution as the BB, only over a sub-area of the larger BB domain, hence, producing the Little-Brother simulation (LB). With the BBE approach, differences between the two simulated climates (BB and LB) can be unambiguously attributed to errors associated with the dynamical downscaling technique, and not to model errors or observational limitations. The current study focuses on the summer over the West Coast of North America. Results of the stationary and transient parts of the fields, decomposed by horizontal scales, are presented for the month of July, for 5 consecutive years (1990–1994). Three degrees of spatial filtering (roughly equivalent to the global spectral resolution of T30, T60 and T360) as well as two update intervals (3 and 6 h) of the lateral boundary conditions (LBC) have been employed. This study establishes that the maximum acceptable resolution of driving data for summer is T30, with improved results employing the T60 resolution of LBC. There is little improvement by reducing the time interval from 6 h to 3 h. These results are generally in agreement with previous studies carried out for winter. The good correlation between LB and BB simulations is more difficult to achieve during the summer season, mostly due to weaker control exerted by LBC. Poor correlations are more pronounced for the transient parts than they are for the stationary parts of the fields. This is especially true for the precipitation field, where differences can be attributed to higher temporal variability during the summer due to the presence of convection.     

Soil moisture memory and West African monsoon predictability: artefact or reality?

Besides sea surface temperature (SST), soil moisture (SM) exhibits a significant memory and is likely to contribute to atmospheric predictability at the seasonal timescale. In this respect, West Africa was recently highlighted as a “hot spot” where the land–atmosphere coupling could play an important role, through the recycling of precipitation and the modulation of the meridional gradient of moist static energy. Particularly intriguing is the observed relationship between summer monsoon rainfall over Sahel and the previous second rainy season over the Guinean Coast, suggesting the possibility of a soil moisture memory beyond the seasonal timescale. The present study is aimed at revisiting this question through a detailed analysis of the instrumental record and a set of numerical sensitivity experiments. Three ensembles of global atmospheric simulations have been designed to assess the relative influence of SST and SM boundary conditions on the West African monsoon predictability over the 1986–1995 period. On the one hand, the results indicate that SM contributes to rainfall predictability at the end and just after the rainy season over the Sahel, through a positive soil-precipitation feedback that is consistent with the “hot spot” hypothesis. On the other hand, SM memory decreases very rapidly during the dry season and does not contribute to the predictability of the all-summer monsoon rainfall. Though possibly model dependent, this conclusion is reinforced by the statistical analysis of the summer monsoon rainfall variability over the Sahel and its link with tropical SSTs. Our results indeed suggest that the apparent relationship with the previous second rainy season over the Guinean Coast is mainly an artefact of rainfall teleconnections with tropical modes of SST variability both at interannual and multi-decadal timescales.     

Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models

Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961–1990) and projections for the IPCC A2 high emission scenario for 2071–2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5°N–15°S band, both in summer and especially in winter, reaching up to 6–8°C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4°C and in winter between 3 and 5°C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of model runs for some regions, as the Northwest coast of Peru-Ecuador, northern Argentina, Eastern Amazonia and Northeast Brazil, whereas for other regions they are less robust as in Pantanal region of West Central and southeastern Brazil.     

EXPERIMENTAL STUDY OF THE ROLE OF INITIAL AND BOUNDARY CONDITIONS IN MESOSCALE NUMERICAL WEATHER PREDICTION

~~EXPERIMENTAL STUDY OF THE ROLE OF INITIAL AND BOUNDARY CONDITIONS IN MESOSCALE NUMERICAL WEATHER PREDICTION@闫敬华$Guangzhou Institute of Tropical & Marine Meteorology, CMA, Guangzhou 510080 China @Detlev Majewski$Duetscher Wetterdinst, Offenbach, Germany~~National Project "973" (Research on Heavy Rain in China) and BMBF of Germany (WTZ- Project CHN01/106)…     

CLM4.0模式对中国区域土壤湿度的数值模拟及评估研究

本文利用普林斯顿大学全球大气强迫场资料,驱动公用陆面过程模式（Community Land Model version 4.0,CLM4.0）模拟了中国区域1961～2010年土壤湿度的时空变化。将模拟结果与观测结果、美国国家环境预报中心再分析数据（National Centers for Environmental Prediction Reanalysis,NCEP）和高级微波扫描辐射计（Advanced Microwave Scanning Radiometer-EOS,AMSR-E）反演的土壤湿度进行了对比分析,结果表明CLM4.0模拟结果可以反映出中国区域观测土壤湿度的空间分布和时空变化特征,但东北、江淮和河套三个地区模拟值相对于观测值在各层次均系统性偏大。模拟与NCEP再分析土壤湿度的空间分布基本一致,与AMSR-E的反演值在35°N以北的分布也基本一致;从1961～2010年土壤湿度模拟结果分析得出,各层土壤湿度空间分布从西北向东南增加。低值区主要分布在新疆、青海、甘肃和内蒙古西部地区。东北平原、江淮地区和长江流域为高值区。土壤湿度数值总体上从浅层向深层增加。不同深度土壤湿度变化趋势基本相同。除新疆西部和东北部分地区外,土壤湿度在35°N以北以减少趋势为主,30°N以南的长江流域、华南及西南地区以增加为主。在全球气候变暖的背景下,CLM4.0模拟的夏季土壤湿度在不同程度上响应了降水的变化。中国典型干旱区和半干旱区土壤湿度减小,湿润区增加。其中湿润区土壤湿度对降水的响应最为显著,其次是半干旱区和干旱区。     

Using regional climate model data to simulate historical and future river flows in northwest England

Daily rainfall and temperature data were extracted from the multi-ensemble HadRM3H regional climate model (RCM) integrations for control (1960–1990) and future (2070–2100) time-slices. This dynamically downscaled output was bias-corrected on observed mean statistics and used as input to hydrological models calibrated for eight catchments which are critical water resources in northwest England. Simulated daily flow distributions matched observed from Q₉₅ to Q₅, suggesting that RCM data can be used with some confidence to examine future changes in flow regime. Under the SRES A2 (UKCIP02 Medium-High) scenario, annual runoff is projected to increase slightly at high elevation catchments, but reduce by ~16% at lower elevations. Impacts on monthly flow distribution are significant, with summer reductions of 40–80% of 1961–90 mean flow, and winter increases of up to 20%. This changing seasonality has a large impact on low flows, with Q₉₅ projected to decrease in magnitude by 40–80% in summer months, with serious consequences for water abstractions and river ecology. In contrast, high flows (> Q₅) are projected to increase in magnitude by up to 25%, particularly at high elevation catchments, providing an increased risk of flooding during winter months. These changes will have implications for management of water resources and ecologically important areas under the EU Water Framework Directive.     

Impact of surface heterogeneity on a buoyancy-driven convective boundary layer in light winds

Land-use practices such as deforestation or agricultural management may affect regional climate, ecosystems and water resources. The present study investigates the impact of surface heterogeneity on the behaviour of the atmospheric boundary layer (ABL), at a typical spatial scale of 1 km. Large-eddy simulations, using an interactive soil–vegetation–atmosphere surface scheme, are performed to document the structure of the three-dimensional flow, as driven by buoyancy forces, over patchy terrain with different surface characteristics (roughness, soil moisture, temperature) on each individual patch. The patchy terrain consists of striped and chessboard patterns. The results show that the ABL strongly responds to the spatial configuration of surface heterogeneities. The stripe configuration made of two patches with different soil moisture contents generates the development of a quasi- two-dimensional inland breeze, whereas a three-dimensional divergent flow is induced by chessboard patterns. The feedback of such small-scale atmospheric circulations on the surface fluxes appears to be highly non-linear. The surface sensible and latent heat fluxes averaged over the 25-km² domain may vary by 5% with respect to the patch arrangement.     

不同初始场及其扰动对WRF 模拟暴雨的影响

使用ERA-interim和FNL再分析资料分别驱动WRF,对2013年7月12—13日的一次暴雨过程进行数值模拟,详细比较了WRF模拟结果之间的差异。结果表明:(1)两种资料在次天气尺度上存在着较大差异,并由此造成了模拟结果之间的差异,ERA-interim作为初始场对降水的模拟优于FNL资料,反映了WRF对初、边界条件的敏感性;(2)从区域总降水量来看,湿度场扰动对降水量的影响最大,其次是风场扰动和温度场扰动,最小的是侧边界扰动;(3)从降水误差来看,湿度场扰动引起的降水误差最大,在积分20 h内风场扰动的降水误差大于温度场,积分21~24 h则相反,侧边界扰动引起的降水误差在前期比较小且增长缓慢,积分一段时间之后与单个气象要素扰动引起的降水误差相当。     

The WAMME regional model intercomparison study

Results from five regional climate models (RCMs) participating in the West African Monsoon Modeling and Evaluation (WAMME) initiative are analyzed. The RCMs were driven by boundary conditions from National Center for Environmental Prediction reanalysis II data sets and observed sea-surface temperatures (SST) over four May–October seasons, (2000 and 2003–2005). In addition, the simulations were repeated with two of the RCMs, except that lateral boundary conditions were derived from a continuous global climate model (GCM) simulation forced with observed SST data. RCM and GCM simulations of precipitation, surface air temperature and circulation are compared to each other and to observational evidence. Results demonstrate a range of RCM skill in representing the mean summer climate and the timing of monsoon onset. Four of the five models generate positive precipitation biases and all simulate negative surface air temperature biases over broad areas. RCM spatial patterns of June–September mean precipitation over the Sahel achieve spatial correlations with observational analyses of about 0.90, but within two areas south of 10°N the correlations average only about 0.44. The mean spatial correlation coefficient between RCM and observed surface air temperature over West Africa is 0.88. RCMs show a range of skill in simulating seasonal mean zonal wind and meridional moisture advection and two RCMs overestimate moisture convergence over West Africa. The 0.5° computing grid enables three RCMs to detect local minima related to high topography in seasonal mean meridional moisture advection. Sensitivity to lateral boundary conditions differs between the two RCMs for which this was assessed. The benefits of dynamic downscaling the GCM seasonal climate prediction are analyzed and discussed.     

Simulation of monsoon depressions using MM5: sensitivity to cumulus parameterization schemes

Summary The sensitivity of the simulation of the monsoon depressions to the cumulus parameterization schemes used in a numerical model is studied using the Pennsylvania State University – National Center for Atmospheric Research (PSU-NCAR) model MM5 version 3.6.2. Three different cases of monsoon depressions were studied with a two way interacting domains of 45 km and 15 km resolutions. Two different cumulus parameterization schemes namely Grell (GR) and Kain-Fritsch (KF) were used for the sensitivity study. The model was integrated for 48 hours with the initial and boundary conditions of European Center for Medium Range Weather Forecasting Reanalysis (ERA-40) data. The results show that both the schemes are able to simulate the large scale features of the monsoon depressions realistically. However, both the schemes failed to simulate the exact location of the depression after 24- and 48-hour simulation. The rainfall simulations of both the schemes were very different. The model with the GR scheme tends to over predict the rainfall. The KF scheme could simulate the distribution of the rainfall comparable to the observations. The KF scheme could simulate the maximum observed rainfall but due to locational errors of the simulated depression, the location of the maximum rainfall was not exact. It is also seen that the resolution of the model has a positive impact on the rainfall simulation. The GR and KF schemes were able to realistically simulate the apparent heat sources, but the apparent moisture profile simulated with KF scheme was more comparable to the verifying analysis. The root mean square errors of mean sea-level pressure, temperature, zonal wind and meridional wind were smaller for KF simulation compared to the GR simulation. Permanent affiliation: Center for Development of Advanced Computing, Pune University Campus, Ganeshkhind, Pune-411 007, India.     

Assessment of regional seasonal predictability using the PRECIS regional climate modeling system over South America

The purpose of this study was to evaluate the accuracy and skill of the UK Met Office Hadley Center Regional Climate Model (HadRM3P) in describing the seasonal variability of the main climatological features over South America and adjacent oceans, in long-term simulations (30 years, 1961–1990). The analysis was performed using seasonal averages from observed and simulated precipitation, temperature, and lower- and upper-level circulation. Precipitation and temperature patterns as well as the main general circulation features, including details captured by the model at finer scales than those resolved by the global model, were simulated by the model. However, in the regional model, there are still systematic errors which might be related to the physics of the model (convective schemes, topography, and land-surface processes) and the lateral boundary conditions and possible biases inherited from the global model.     

Contribution of realistic soil moisture initial conditions to boreal summer climate predictability

Seasonal climate forecasts mainly rely on the atmospheric sensitivity to its lower boundary conditions and on their own predictability. Besides sea surface temperature (SST), soil moisture (SM) may be an additional source of climate predictability particularly during boreal summer in the mid-latitudes. In this work, we investigate the role of SM initial conditions on near-surface climate predictability during ten boreal summer seasons using three complementary ensembles of AMIP-type simulations performed with the Arpège-Climat atmospheric general circulation model. First we have conducted an assessment of the SM predictability itself through a comparison of simple empirical SM models with Arpège-Climat. The statistical and dynamical models reveal similar SM prediction skill patterns but the Arpège-Climat reaches higher scores suggesting that it is at least suitable to explore the influence of SM initialization on atmospheric predictability. Then we evaluate the relationships between SM predictability and some near surface atmospheric predictability. While SM initialization obviously improves the predictability of land surface evaporation, it has no systematic influence on the precipitation and near surface temperature skills. Nevertheless, the summer hindcast skill is clearly improved during specific years and over certain regions (mainly north America and eastern Europe in the Arpège-Climat model), when and where the SM forcing is sufficiently widespread and strong. In this case, a significant impact is also found on the occurrence of heat waves and heavy rains, whose predictability at the seasonal timescale is a crucial challenge for years to come.     

Downward transport and modification of tropospheric ozone through moist convection

This study estimated the largely unstudied downward transport and modification of tropospheric ozone associated with tropical moist convection using a coupled meteorology-chemistry model. High-resolution cloud resolving model simulations were conducted for deep moist convection events over West Africa during August 2006 to estimate vertical transport of ozone due to convection. Model simulations realistically reproduced the characteristics of deep convection as revealed by the estimated spatial distribution of temperature, moisture, cloud reflectivity, and vertical profiles of temperature and moisture. Also, results indicated that vertical transport reduced ozone by 50% (50 parts per billion by volume, ppbv) in the upper atmosphere (12–15 km) and enhanced ozone by 39% (10 ppbv) in the lower atmosphere (<2 km). Field observations confirmed model results and indicated that surface ozone levels abruptly increased by 10–30 ppbv in the area impacted by convection due to transport by downdrafts from the upper troposphere. Once in the lower troposphere, the lifetime of ozone decreased due to enhanced dry deposition and chemical sinks. Ozone removal via dry deposition increased by 100% compared to non-convective conditions. The redistribution of tropospheric ozone substantially changed hydroxyl radical formation in the continental tropical boundary layer. Therefore, an important conclusion of this study is that the redistribution of tropospheric ozone, due to deep convection in non-polluted tropical regions, can simultaneously reduce the atmospheric loading of ozone and substantially impact the oxidation capacity of the lower atmosphere via the enhanced formation of hydroxyl radicals.     

Causes and uncertainty of future summer drying over Europe

Previous studies have shown that the continuing rise in anthropogenic emissions is likely to cause continental European summers to become substantially drier over the coming century. Since this predicted decline in rainfall and soil moisture (SM) would bring significant stress to society and ecosystems, it is essential that its reliability or otherwise is properly assessed. One approach is to gain a better understanding of the model’s mechanisms of regional climate change and integrate this with a knowledge of the model’s strengths and weaknesses. Here we propose a methodology that partitions some of the mechanisms of regional climate change, and apply it to the problem of summer drying over continental Europe. Earlier work suggests that a plausible partition of the mechanisms of future mid-latitude continental summer drying might be as follows: (a) an earlier and more rapid decline in SM during spring, leading to lower SM in summer, and hence less convective rainfall (‘Spring SM’); (b) a larger land–sea contrast in lower tropospheric summer warming, leading to reduced relative humidity in air advected onto the continent, and so reduced rainfall (‘Warming’); (c) other large-scale atmospheric changes, including remotely forced circulation changes (‘Large-Scale’); and (d) a positive feedback mechanism in summer, whereby the reduced rainfall dries the soil further, so reducing convective activity further (‘Summer SM Feedback’). We attempt to isolate these mechanisms by integrating a geographic subset of the high resolution global atmospheric model HadAM3P to assess their relative importance in generating the projected European summer drying. Each mechanism is approximately represented (and so isolated) using an appropriate mix of inputs to the model, with some matching a control integration and others matching a future scenario integration. These mixed inputs are: atmospheric composition (CO₂, aerosol and ozone), surface boundary data (SM and SSTs), and lateral boundary data (temperature, moisture, winds, and surface pressure). We describe this methodology and the experimental suite in some detail, as well as the constraints on our ability to fully separate these mechanisms. It is also shown that the separation of mechanisms is not compromised by interactions between them. For continental and southeastern Europe, it is found that both the ‘Warming’ and ‘Spring SM’ mechanisms are the primary drivers of the projected summer drying. ‘Summer SM Feedback’ plays an important secondary role, and ‘Large-Scale’ mechanisms, as represented here, have least influence. Since the two dominant mechanisms depend on processes in which we have reasonable confidence, this gives us high confidence in the sign of the projected summer drying over continental and southeastern Europe. Nevertheless, uncertainties in model formulation and future anthropogenic emissions mean that the magnitude of this future rainfall anomaly remains unclear. Over Great Britain and southern Scandinavia, our experiments show that the rainfall anomaly is dominated by opposing effects from the ‘Warming’ and ‘Large-Scale’ mechanisms, which in this area dictate increased and decreased rainfall respectively. Given this rivalry, and also that we have low confidence in the ‘Large-Scale’ mechanism, this suggests that even the sign of the projected drying here is uncertain.     

Impact of soil moisture�Catmosphere coupling on European climate extremes and trends in a regional climate model

Processes acting at the interface between the land surface and the atmosphere have a strong impact on the European summer climate, particularly during extreme years. These processes are to a large extent associated with soil moisture (SM). This study investigates the role of soil moisture?Catmosphere coupling for the European summer climate over the period 1959?C2006 using simulations with a regional climate model. The focus of this study is set on temperature and precipitation extremes and trends. The analysis is based on simulations performed with the regional climate model CLM, driven with ECMWF reanalysis and operational analysis data. The set of experiments consists of a control simulation (CTL) with interactive SM, and sensitivity experiments with prescribed SM: a dry and a wet run to determine the impact of extreme values of SM, as well as experiments with lowpass-filtered SM from CTL to quantify the impact of the temporal variability of SM on different time scales. Soil moisture?Cclimate interactions are found to have significant effects on temperature extremes in the experiments, and impacts on precipitation extremes are also identified. Case studies of selected major summer heat waves reveal that the intraseasonal and interannual variability of SM account for 5?C30% and 10?C40% of the simulated heat wave anomaly, respectively. For extreme precipitation events on the other hand, only the wet-day frequency is impacted in the experiments with prescribed soil moisture. Simulated trends for the past decades, which appear consistent with projected changes for the 21st century, are identified to be at least partly linked to SM-atmosphere feedbacks.