Present climate trend analysis of the Etesian winds in the Aegean Sea

Wildfires are a common experience in Alaska where, on average, 3,775?km² burn annually. More than 90% of the area consumed occurs in Interior Alaska, where the summers are relatively warm and dry, and the vegetation consists predominantly of spruce, birch, and cottonwood. Summers with above normal temperatures generate an increased amount of convection, resulting in more thunderstorm development and an amplified number of lightning strikes. The resulting dry conditions facilitate the spread of wildfires started by the lightning. Working with a 55-year dataset of wildfires for Alaska, an increase in the annual area burned was observed. Due to climate change, the last three decades have shown to be warmer than the previous decades. Hence, in the first 28?years of the data, two fires were observed with an area burned greater than 10,000?km², while there were four in the last 27?years. Correlations between the Palmer Drought Severity Index and the Canadian Drought Code, against both the number of wildfires and the area burned, gave relatively low but in some cases significant correlation values. Special emphasis is given to the fire season of 2004, in which a record of 27,200?km² burned. These widespread fires were due in large part to the unusual weather situation. Owing to the anticyclonic conditions of the summer of 2004, the composite anomaly of the 500?mb geopotential height showed above normal values. The dominance of a ridge pattern during summer resulted in generally clear skies, high temperatures, and below normal precipitation. Surface observations confirmed this; the summer of 2004 was the warmest and third driest for Interior Alaska in a century of climate observations. The fires lasted throughout the summer and only the snowfalls in September terminated them (at least one regenerated in spring 2005). Smoke from the forest fires affected the air quality. This could be demonstrated by measurements of visibility, fine particle matter, transmissivity of the atmosphere, and CO concentration.     

ENSO anomalies over the Western United States: present and future patterns in regional climate simulations

Surface temperature, precipitation, specific humidity and wind anomalies associated with the warm and cold phases of ENSO simulated by WRF and HadRM are examined for the present and future decades. WRF is driven by ECHAM5 and CCSM3, respectively, and HadRM is driven by HadCM3. For the current decades, all simulations show some capability in resolving the observed warm-dry and cool-wet teleconnection patterns over the PNW and the Southwest U.S. for warm and cold ENSO. Differences in the regional simulations originate primarily from the respective driving fields. For the future decades, the warm-dry and cool-wet teleconnection patterns in association with ENSO are still represented in ECHAM5-WRF and HadRM. However, there are indications of changes in the ENSO teleconnection patterns for CCSM3-WRF in the future, with wet anomalies dominating in the PNW and the Southwest U.S. for both warm and cold ENSO, in contrast to the canonical patterns of precipitation anomalies. Interaction of anomalous wind flow with local terrain plays a critical role in the generation of anomalous precipitation over the western U.S. Anomalous dry conditions are always associated with anomalous airflow that runs parallel to local mountains and wet conditions with airflow that runs perpendicular to local mountains. Future changes in temperature and precipitation associated with the ENSO events in the regional simulations indicate varying responses depending on the variables examined as well as depending on the phase of ENSO.     

Spatial analysis of future East Asian seasonal temperature using two regional climate model simulations

CORDEX-East Asia, a branch of the coordinated regional climate downscaling experiment (CORDEX) initiative, provides high-resolution climate simulations for the domain covering East Asia. This study analyzes temperature data from regional climate models (RCMs) participating in the CORDEX - East Asia region, accounting for the spatial dependence structure of the data. In particular, we assess similarities and dissimilarities of the outputs from two RCMs, HadGEM3-RA and RegCM4, over the region and over time. A Bayesian functional analysis of variance (ANOVA) approach is used to simultaneously model the temperature patterns from the two RCMs for the current and future climate. We exploit nonstationary spatial models to handle the spatial dependence structure of the temperature variable, which depends heavily on latitude and altitude. For a seasonal comparison, we examine changes in the winter temperature in addition to the summer temperature data. We find that the temperature increase projected by RegCM4 tends to be smaller than the projection of HadGEM3-RA for summers, and that the future warming projected by HadGEM3-RA tends to be weaker for winters. Also, the results show that there will be a warming of 1-3°C over the region in 45 years. More specifically, the warming pattern clearly depends on the latitude, with greater temperature increases in higher latitude areas, which implies that warming may be more severe in the northern part of the domain.     

A review on vegetation models and applicability to climate simulations at regional scale

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson’s rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.     

利用区域气候模式预估未来登陆中国热带气旋活动

鉴于热带气旋(TC)对我国沿海地区的影响,研究全球变暖背景下未来登陆我国TC活动的变化,对于我国沿海地区的防灾减灾具有重要意义。基于CMIP5中全球气候模式HadGEM2-ES数据,文中利用区域气候模式RegCM4开展了历史时期和3种情景(RCP2.6、RCP4.5和RCP8.5)下未来东亚区域气候的动力降尺度模拟,检验了模式对历史登陆我国TC活动及其相关大尺度环境场的模拟能力,并预估了3种情景下2030—2039年、2050—2059年和2089—2098年,登陆我国TC的路径、强度和频率的变化特征。结果表明:模式能合理地再现东亚区域历史时期(1986—2005年)大气环流场的空间结构以及登陆我国TC的特征;在3种情景下未来登陆我国TC的平均强度和数量均有不同程度的增加,尤其是台风及以上级别TC的总数明显增加,其中RCP8.5情景最突出,到21世纪末期(2089—2098年)登陆我国TC的平均强度、台风及以上级别TC总数的年平均值较历史时期将分别增加7.56%和1.05个;不同情景下未来登陆我国TC的路径均有不同程度的北移趋势,且全球升温的幅度越大,北移趋势越明显,这可能与未来中国近海显著变暖和垂直风切变减弱有关。未来我国沿海地区尤其是中高纬度很可能将面临日益严峻的TC灾害风险,亟需尽快开展防灾减灾及对策研究。     

A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.     

Evaluating uncertainties in regional climate simulations over South America at the seasonal scale

This work focuses on the evaluation of different sources of uncertainty affecting regional climate simulations over South America at the seasonal scale, using the MM5 model. The simulations cover a 3-month period for the austral spring season. Several four-member ensembles were performed in order to quantify the uncertainty due to: the internal variability; the definition of the regional model domain; the choice of physical parameterizations and the selection of physical parameters within a particular cumulus scheme. The uncertainty was measured by means of the spread among individual members of each ensemble during the integration period. Results show that the internal variability, triggered by differences in the initial conditions, represents the lowest level of uncertainty for every variable analyzed. The geographic distribution of the spread among ensemble members depends on the variable: for precipitation and temperature the largest spread is found over tropical South America while for the mean sea level pressure the largest spread is located over the southeastern Atlantic Ocean, where large synoptic-scale activity occurs. Using nudging techniques to ingest the boundary conditions reduces dramatically the internal variability. The uncertainty due to the domain choice displays a similar spatial pattern compared with the internal variability, except for the mean sea level pressure field, though its magnitude is larger all over the model domain for every variable. The largest spread among ensemble members is found for the ensemble in which different combinations of physical parameterizations are selected. The perturbed physics ensemble produces a level of uncertainty slightly larger than the internal variability. This study suggests that no matter what the source of uncertainty is, the geographical distribution of the spread among members of the ensembles is invariant, particularly for precipitation and temperature.     

Fine-resolution regional climate model simulations of the impact of climate change on tropical cyclones near Australia

Fine-resolution regional climate simulations of tropical cyclones (TCs) are performed over the eastern Australian region. The horizontal resolution (30 km) is fine enough that a good climatological simulation of observed tropical cyclone formation is obtained using the observed tropical cyclone lower wind speed threshold (17 m s^–1). This simulation is performed without the insertion of artificial vortices (bogussing). The simulated occurrence of cyclones, measured in numbers of days of cyclone activity, is slightly greater than observed. While the model-simulated distribution of central pressures resembles that observed, simulated wind speeds are generally rather lower, due to weaker than observed pressure gradients close to the centres of the simulated storms. Simulations of the effect of climate change are performed. Under enhanced greenhouse conditions, simulated numbers of TCs do not change very much compared with those simulated for the current climate, nor do regions of occurrence. There is a 56% increase in the number of simulated storms with maximum winds greater than 30 m s^–1 (alternatively, a 26% increase in the number of storms with central pressures less than 970 hPa). In addition, there is an increase in the number of intense storms simulated south of 30°S. This increase in simulated maximum storm intensity is consistent with previous studies of the impact of climate change on tropical cyclone wind speeds.     

嵌套域大小对区域气候模式模拟效果的影响

This paper presents a numerical study on the 1998 summer rainfall over the Yangtze River valley in central and eastern China, addressing effect of a nested area size on simulations in terms of the technique of nesting a regional climate model (RCM) upon a general circulation model (GCM). Evidence suggests that the size exerts greater impacts upon regional climate of the country, revealing that a larger nested size is su perior to a small one for simulation in mitigating errors of GCM-provided lateral boundary forcing. Also,simulations show that the RCM should incorporate regions of climate systems of great importance into study and a low-resolution GCM yields more pronounced errors as a rule when used in the research of the Tibetan Plateau, and, in contrast, our PσRCM can do a good job in describing the plateau′s role in a more realistic and accurate way. It is for this reason that the tableland should be included in the nested area when the RCM is employed to investigate the regional climate. Our PσRCM nesting upon a GCM reaches morerealistic results compared to a single GCM used.     

Interannual variability and regional climate simulations

Summary An assessment is made of a regional climate model's skill in simulating the mean climatology and the interannual variability experienced in a specific region. To this end two ensembles comprising three realizations of month-long January and July simulations are undertaken with a limited are a operational NWP model. The modelling suite is driven at its lateral boundaries by analysed meteorological fields and the computational domain covers Europe and the North-western Atlantic with a horizontal resolution of 56 km.Validation is performed against both operational ECMWF analyses and objectively analysed precipitation fields from a network of ~ 1400 SYNOP rain gauge stations. Analysis of the simulated ensemble-mean climatology indicates that the model successfully reproduces both the winter and summer distributions of the primary dynamical and thermodynamical field, and also provides a reasonable representation of the measured precipitation over most of Europe. Typically the domain averaged model-biases are below 0.5 K for temperature and 0.1 g/kg for specific humidity. Analysis of the interannual variability reveals that the model captures the wintertime changes including that of the precipitation distribution, but in contrast the summertime precipitation totals for the individual years is not simulated satisfactorily and only partially reproduces the observed regional interannual variability.The latter shortcomings are related to the following factors. Firstly the model bias in the dynamical fields is somewhat larger for summer than winter, while at the same time summertime interannual variability is associated with weaker effects in the dynamical fields. Secondly the summertime precipitation distribution is more substantially affected by small-scale moist convection and surface hydrological processes. Together these two factors suggest that summertime precipitation over continental extratropical land masses might be intrinsically less predictable than wintertime synoptic scale precipitation.With 17 Figures     

Resolution effects on regional climate model simulations of seasonal precipitation over Europe

We analyze a set of nine regional climate model simulations for the period 1961–2000 performed at 25 and 50 km horizontal grid spacing over a European domain in order to determine the effects of horizontal resolution on the simulation of precipitation. All of the models represent the seasonal mean spatial patterns and amount of precipitation fairly well. Most models exhibit a tendency to over-predict precipitation, resulting in a domain-average total bias for the ensemble mean of about 20% in winter (DJF) and less than 10% in summer (JJA) at both resolutions, although this bias could be artificially enhanced by the lack of a gauge correction in the observations. A majority of the models show increased precipitation at 25 km relative to 50 km over the oceans and inland seas in DJF, JJA, and ANN (annual average), although the response is strongest during JJA. The ratio of convective precipitation to total precipitation decreases over land for most models at 25 km. In addition, there is an increase in interannual variability in many of the models at 25 km grid spacing. Comparison with gridded observations indicates that a majority of models show improved skill in simulating both the spatial pattern and temporal evolution of precipitation at 25 km compared to 50 km during the summer months, but not in winter or on an annual mean basis. Model skill at higher resolution in simulating the spatial and temporal character of seasonal precipitation is found especially for Great Britain. This geographic dependence of the increased skill suggests that observed data of sufficient density are necessary to capture fine-scale climate signals. As climate models increase their horizontal resolution, it is thus a key priority to produce high quality fine scale observations for model evaluation.     

Evaluation of regional climate simulations over the CORDEX-EA-II domain using the COSMO-CLM model

The COSMO-CLM (CCLM) model is applied to perform regional climate simulation over the second phase of CORDEX-East Asia (CORDEX-EA-II) domain in this study. Driven by the ERAInterim reanalysis data, the model was integrated from 1988 to 2010 with a high resolution of 0.22°. The model’s ability to reproduce mean climatology and climatic extremes is evaluated based on various aspects. The CCLM model is capable of capturing the basic features of the East Asia climate, including the seasonal mean patterns, interannual variations, annual cycles and climate extreme indices for both surface air temperature and precipitation. Some biases are evident in certain areas and seasons. Warm and wet biases appear in the arid and semi-arid areas over the northwestern and northern parts of the domain. The simulated climate over the Tibetan Plateau is colder and wetter than the observations, while South China, East China, and India are drier. The model biases may be caused by the simulated anticyclonic and cyclonic biases in low-level circulations, the simulated water vapor content biases, and the inadequate physical parameterizations in the CCLM model. A parallel 0.44° simulation is conducted and the comparison results show some added value introduced by the higher resolution 0.22° simulation. As a result, the CCLM model could be an adequate member for the next stage of the CORDEX-EA project, while further studies should be encouraged.     

Interannual variability of rainfall over the Sahel based on multiple regional climate models simulations

We analyse the interannual variability of the averaged summer monsoon rainfall over the Sahel from multiple regional climate models driven by the ERA-interim reanalysis and seek to provide effective information for future modelling work. We find that the majority of the models are able to reproduce the rainfall variability with correlation coefficient exceeding 0.5 compared with observations. This is due to a good representation of the dynamics of the main monsoon features of the West African climate such as the monsoon flux, African Easterly Jet (AEJ) and Tropical Easterly Jet (TEJ). Among the models, only HIRHAM fails to reproduce the rainfall variability exhibiting hence a correlation coefficient of ?0.2. This deficiency originates from the fact that HIRHAM does not properly capture the variability of monsoon flow and the relationship between rainfall and the AEJ dynamic. We conclude that a good performance of a regional climate model in simulating the monsoon dynamical features variability is of primary importance for a better representation of the interannual variability of rainfall over the Sahel.     

Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

Theoretical and Applied Climatology - The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model...     

Convective and stratiform precipitation characteristics in an ensemble of regional climate model simulations

We apply a recently proposed algorithm for disaggregating observed precipitation data into predominantly convective and stratiform, and evaluate biases in characteristics of parameterized convective (subgrid) and stratiform (large-scale) precipitation in an ensemble of 11 RCM simulations for recent climate in Central Europe. All RCMs have a resolution of 25 km and are driven by the ERA-40 reanalysis. We focus on mean annual cycle, proportion of convective precipitation, dependence on altitude, and extremes. The results show that characteristics of total precipitation are often better simulated than are those of convective and stratiform precipitation evaluated separately. While annual cycles of convective and stratiform precipitation are reproduced reasonably well in most RCMs, some of them consistently and substantially overestimate or underestimate the proportion of convective precipitation throughout the year. Intensity of convective precipitation is underestimated in all RCMs. Dependence on altitude is also simulated better for stratiform and total precipitation than for convective precipitation, for which several RCMs produce unrealistic slopes. Extremes are underestimated for convective precipitation while they tend to be slightly overestimated for stratiform precipitation, thus resulting in a relatively good reproduction of extremes in total precipitation amounts. The results suggest that the examined ensemble of RCMs suffers from substantial deficiencies in reproducing precipitation processes and support previous findings that climate models’ errors in precipitation characteristics are mainly related to deficiencies in the representation of convection.     

On the linear response of tropical African climate to SST changes deduced from regional climate model simulations

Summary Previous studies have highlighted the crucial role of sea surface temperature (SST) anomalies in the tropical Atlantic region in forcing the summer monsoon rainfall over subsaharan West Africa. Understanding the physical processes, relating SST variations to changes in the amount and distribution of African rainfall, is a key factor in improving weather and climate forecasts in this highly vulnerable region. Here, we present sensitivity experiments from a regional climate model with prescribed warmer tropical SSTs, according to enhanced greenhouse conditions at the end of the 21st century. This dynamical downscaling approach provides information about the nonlinear response of the atmosphere to oceanic heating. It has been suggested that the response is at least partly accounted for by the linear theory of tropical dynamics, involving a Kelvin and Rossby wave response to a tropical heat source. We compute the major modes of the linear Matsuno-Gill model for geopotential height and horizontal wind components and project the simulated response patterns onto these linear modes, in order to evaluate to which extent the simple linear theory may explain the SST-induced climate anomalies over Africa. A multivariate Hotelling T² test is used to evaluate whether these anomalies are statistically significant. Forcing the regional climate model by warmer SSTs leads to substantial climate anomalies over tropical Africa: Rainfall is increases over the Guinea Coast region (GCR) and tropical East Africa, but decreases over the Congo Basin and the Sahel Zone (SHZ). At the 850 hPa level, a trough develops over southern West Africa and the Gulf of Guinea, and is associated with stronger surface wind convergence over the GCR. These changes in the atmospheric dynamics strongly project onto the leading modes of the linear Matsuno-Gill model at various zonal wave numbers. The corresponding atmospheric heating pattern is highly reminiscent of the simulated nonlinear model reponse. The T² test statistics reveal that the SST forcing induces a statistically significant climate anomaly over tropical Africa if the climate state vector is reduced by projecting the simulated data onto the leading 10 linear modes. It is also shown that the linear response prevails in a long-term simulation with more realistic lower and lateral boundary conditions. Thus, linear tropical dynamics are assumed to be a major physical process on the ground of the prominent SST-African rainfall relationship.     

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution part 2: historical and future simulations of precipitation

This paper presents the first multi-model ensemble of 10-year, “convection-permitting” kilometer-scale regional climate model (RCM) scenario simulations downscaled from selected CMIP5 GCM projections for historical and end of century time slices. The technique is to first downscale the CMIP5 GCM projections to an intermediate 12–15 km resolution grid using RCMs, and then use these fields to downscale further to the kilometer scale. The aim of the paper is to provide an overview of the representation of the precipitation characteristics and their projected changes over the greater Alpine domain within a Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study and the European Climate Prediction system project, tasked with investigating convective processes at the kilometer scale. An ensemble of 12 simulations performed by different research groups around Europe is analyzed. The simulations are evaluated through comparison with high resolution observations while the complementary ensemble of 12 km resolution driving models is used as a benchmark to evaluate the added value of the convection-permitting ensemble. The results show that the kilometer-scale ensemble is able to improve the representation of fine scale details of mean daily, wet-day/hour frequency, wet-day/hour intensity and heavy precipitation on a seasonal scale, reducing uncertainty over some regions. It also improves the representation of the summer diurnal cycle, showing more realistic onset and peak of convection. The kilometer-scale ensemble refines and enhances the projected patterns of change from the coarser resolution simulations and even modifies the sign of the precipitation intensity change and heavy precipitation over some regions. The convection permitting simulations also show larger changes for all indices over the diurnal cycle, also suggesting a change in the duration of convection over some regions. A larger positive change of frequency of heavy to severe precipitation is found. The results are encouraging towards the use of convection-permitting model ensembles to produce robust assessments of the local impacts of future climate change.