A multi-physics ensemble of regional climate change projections over the Iberian Peninsula

This study illustrates the sensitivity of regional climate change projections to the model physics. A single-model (MM5) multi-physics ensemble of regional climate simulations over the Iberian Peninsula for present (1970–1999) and future (2070–2099 under the A2 scenario) periods is assessed. The ensemble comprises eight members resulting from the combination of two options of parameterization schemes for the planetary boundary layer, cumulus and microphysics. All the considered combinations were previously evaluated by comparing hindcasted simulations to observations, none of them providing clearly outlying climates. Thus, the differences among the various ensemble members (spread) in the future projections could be considered as a matter of uncertainty in the change signals (as similarly assumed in multi-model studies). The results highlight the great dependence of the spread on the synoptic conditions driving the regional model. In particular, the spread generally amplifies under the future scenario leading to a large spread accompanying the mean change signals, as large as the magnitude of the mean projected changes and analogous to the spread obtained in multi-model ensembles. Moreover, the sign of the projected change varies depending on the choice of the model physics in many cases. This, together with the fact that the key mechanisms identified for the simulation of the climatology of a given period (either present or future) and those introducing the largest spread in the projected changes differ significantly, make further claims for efforts to better understand and model the parameterized subgrid processes.     

A multi-physics ensemble of present-day climate regional simulations over the Iberian Peninsula

This work assesses the influence of the model physics in present-day regional climate simulations. It is based on a multi-phyiscs ensemble of 30-year long MM5 hindcasted simulations performed over a complex and climatically heterogeneous domain as the Iberian Peninsula. The ensemble consists of eight members that results from combining different parametrization schemes for modeling the Planetary Boundary Layer, the cumulus and the microphysics processes. The analysis is made at the seasonal time scale and focuses on mean values and interannual variability of temperature and precipitation. The objectives are (1) to evaluate and characterize differences among the simulations attributable to changes in the physical options of the regional model, and (2) to identify the most suitable parametrization schemes and understand the underlying mechanisms causing that some schemes perform better than others. The results confirm the paramount importance of the model physics, showing that the spread among the various simulations is of comparable magnitude to the spread obtained in similar multi-model ensembles. This suggests that most of the spread obtained in multi-model ensembles could be attributable to the different physical configurations employed in the various models. Second, we obtain that no single ensemble member outperforms the others in every situation. Nevertheless, some particular schemes display a better performance. On the one hand, the non-local MRF PBL scheme reduces the cold bias of the simulations throughout the year compared to the local Eta model. The reason is that the former simulates deeper mixing layers. On the other hand, the Grell parametrization scheme for cumulus produces smaller amount of precipitation in the summer season compared to the more complex Kain-Fritsch scheme by reducing the overestimation in the simulated frequency of the convective precipitation events. Consequently, the interannual variability of precipitation (temperature) diminishes (increases), which implies a better agreement with the observations in both cases. Although these features improve in general the accuracy of the simulations, controversial nuances are also highlighted.     

Physically based evaluation of climate models over the Iberian Peninsula

A novel approach is proposed for evaluating regional climate models based on the comparison of empirical relationships among model outcome variables. The approach is actually a quantitative adaptation of the method for evaluating global climate models proposed by Betts (Bull Am Meteorol Soc 85:1673–1688, 2004). Three selected relationships among different magnitudes involved in water and energy land surface budgets are firstly established using daily re-analysis data. The selected relationships are obtained for an area encompassing two river basins in the southern Iberian Peninsula corresponding to 2 months, representative of dry and wet seasons. The same corresponding relations are also computed for each of the thirteen regional simulations of the ENSEMBLES project over the same area. The usage of a metric based on the Hellinger coefficient allows a quantitative estimation of how well models are performing in simulating the relations among surface magnitudes. Finally, a series of six rankings of the thirteen regional climate models participating in the ENSEMBLES project is obtained based on their ability to simulate such surface processes.     

Changes in the onset and length of seasons from an ensemble of regional climate models over Spain for future climate conditions

This study analyses the length and onset of the four seasons based on the annual climatic cycle of maximum and minimum temperatures. Previous studies focused over climatically homogeneous mid-high latitude areas, employing fixed temperature thresholds (related to climatic features such as freezing point) that can be inadequate when different climate conditions are present. We propose a method related to the daily minimum and maximum temperature 25th and 75th point-dependent climatic percentiles. It is applied to an ensemble of regional climate models (RCMs) of 25-km horizontal resolution over the peninsular Spain and Balearic Islands, where a large variety of climatic regimes, from alpine to semi-desertic conditions, are present. First, baseline climate (1961–2000) ERA40-forced RCM simulations are successfully compared with the Spain02 daily observational database, following astronomical season length (around 90 days). This result confirms the validity of the proposed method and capability of the RCMs to describe the seasonal features. Future climate global climate model-forced RCMs (2071–2100) compared with present climate (1961–1990) simulations indicate the disappearance of winter season, a summer enlargement (onset and end) and a slight spring and autumn increase.     

Validation of IPCC AR4 models over the Iberian Peninsula

This paper reports analysis of the ability of 24 coupled global climate models that were used in the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change to simulate the current monthly seasonal cycle of sea level pressure, surface air temperature and precipitation over the Iberian Peninsula in the last two decades of the twentieth century. The period investigated runs from 1979 to 1998. In order to assess the performance of the models, averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles, whilst PDFs are also obtained using the data from the ERA40 reanalysis and the Global Precipitation Climatology Project. We found that simulated PDFs generally provided a better fit to actual PDFs than seasonal cycles do. This conclusion indicates that when evaluating model performance, the climate variability as measured by means of PDFs is not the only climatic element that should be tested. Regarding the comparison based on the seasonal cycle, results also show that the root mean square skill score is more useful than the r skill score. To rank the AR4 models, sea level pressure, surface air temperature and precipitation variables were selected and a group of five AR4 models were identified as the models which best reproduce current climate in the area: MIROC3.2-HIRES, MPI-ECHAM5, GFDL-CM2.1, BCCR-BCM2.0 and UKMO-HADGEM1. The rank obtained should not be understood in a hierarchical manner because there is a certain degree of internal variability in the model ensembles. Finally, it should be noted that these results are in good agreement with other classifications found in the scientific literature.     

Changes in rainfall regime over Burkina Faso under the climate change conditions simulated by 5 regional climate models

Sahelian rainfall has recorded a high variability during the last century with a significant decrease (more than 20 %) in the annual rainfall amount since 1970. Using a linear regression model, the fluctuations of the annual rainfall from the observations over Burkina Faso during 1961–2009 period are described through the changes in the characteristics of the rainy season. The methodology is then applied to simulated rainfall data produced by five regional climate models under A1B scenario over two periods: 1971–2000 as reference period and 2021–2050 as projection period. As found with other climate models, the projected change in annual rainfall for West Africa is very uncertain. However, the present study shows that some features of the impact of climate change on rainfall regime in the region are robust. The number of the low rainfall events (0.1–5 mm/d) is projected to decrease by 3 % and the number of strong rainfall events (>50 mm/d) is expected to increase by 15 % on average. In addition, the rainy season onset is projected by all models to be delayed by one week on average and a consensus exists on the lengthening of the dry spells at about 20 %. Furthermore, the simulated relationship between changed annual rainfall amounts and the number of rain days or their intensity varies strongly from one model to another and some changes do not correspond to what is observed for the rainfall variability over the last 50 years.     

Assessing future changes in seasonal climatic extremes in the Ganges river basin using an ensemble of regional climate models

Using an ensemble of four high resolution (~25 km) regional climate models, this study analyses the future (2021–2050) spatial distribution of seasonal temperature and precipitation extremes in the Ganges river basin based on the SRES A1B emissions scenario. The model validation results (1989–2008) show that the models simulate seasonality and spatial distribution of extreme temperature events better than precipitation. The models are able to capture fine topographical detail in the spatial distribution of indices based on their ability to resolve processes at a higher regional resolution. Future simulations of extreme temperature indices generally agree with expected warming in the Ganges basin, with considerable seasonal and spatial variation. Significantly warmer summers in the central part of the basin along with basin-wide increase in night temperature are expected during the summer and monsoon months. An increase in heavy precipitation indices during monsoon, coupled with extended periods without precipitation during the winter months; indicates an increase in the incidence of extreme events.     

Analysis and mapping of present and future drought conditions over Greek areas with different climate conditions

Estimation of drought in a certain temporal and spatial scale is crucial in climate change studies. The current study targets on three agricultural areas widespread in Greece, Ardas River Basin in Northeastern Greece, Sperchios River Basin in Central Greece, and Geropotamos River Basin in Crete Island in South Greece that are characterized by diverse climates as they are located in various regions. The objective is to assess the spatiotemporal variation of drought conditions prevailing in these areas. The Standardized Precipitation Index (SPI) was used to identify and assess the present and future drought conditions. Future simulated data were derived from a number of Regional Climatic Models (RCMs) from the ENSEMBLES European Project. The analysis was performed for the future periods of 2021–2050 and 2071–2100, implementing A1B and B1 scenarios. The spatial analysis of the drought conditions was performed using a combined downscaling technique and the Ordinary Kriging. The Mann-Kendall test was implemented for trend investigation. During both periods and scenarios, drought conditions will tend to be more severe in the upcoming years. The decrease of the SPI values in the Sperchios River Basin is expected to be the strongest, as it is the only study area that will show a negative balance (in SPI values), regarding the drought conditions. For the Ardas and the Geropotamos River Basins, a great increase of the drought conditions will occur during the 2021–2050 period, while for 2071–2100 period, the decrease will continue but it will be tempered. Nevertheless, the situation in all study areas according to the SPI classification is characterized as “Near-normal”, in terms of drought conditions.     

Error characteristics of high resolution regional climate models over the Alpine area

This study describes typical error ranges of high resolution regional climate models operated over complex orography and investigates the scale-dependence of these error ranges. The results are valid primarily for the European Alpine region, but to some extent they can also be transferred to other orographically complex regions of the world. We investigate the model errors by evaluating a set of 62 one-year hindcast experiments for the year 1999 with four different regional climate models. The analysis is conducted for the parameters mean sea level pressure, air temperature (mean, minimum and maximum) and precipitation (mean, frequency and intensity), both as an area average over the whole modeled domain (the “Greater Alpine Region”, GAR) and in six subregions. The subregional seasonal error ranges, defined as the interval between the 2.5th percentile and the 97.5th percentile, lie between ?3.2 and +2.0 K for temperature and between ?2.0 and +3.1 mm/day (?45.7 and +94.7%) for precipitation, respectively. While the temperature error ranges are hardly broadened at smaller scales, the precipitation error ranges increase by 28%. These results demonstrate that high resolution RCMs are applicable in relatively small scale climate impact studies with a comparable quality as on well investigated larger scales as far as temperature is concerned. For precipitation, which is a much more demanding parameter, the quality is moderately degraded on smaller scales.     

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.     

River discharge and freshwater runoff to the Barents Sea under present and future climate conditions

River discharge forms a major freshwater input into the Arctic Ocean, and as such it has the potential to influence the oceanic circulation. As the hydrology of Arctic river basins is dominated by cryospheric processes such as snow accumulation and snowmelt, it may also be highly sensitive to a change in climate. Estimating the water balance of these river basins is therefore important, but it is complicated by the sparseness of observations and the large uncertainties related to the measurement of snowfalls. This study aims at simulating the water balance of the Barents Sea drainage basin in Northern Europe under present and future climate conditions. We used a regional climate model to drive a large-scale hydrological model of the area. Using simulated precipitation derived from a climate model led to an overestimation of the annual discharge in most river basins, but not in all. Under the B2 scenario of climate change, the model simulated a 25% increase in freshwater runoff, which is proportionally larger than the projected precipitation increase. As the snow season is 30–50 day shorter, the spring discharge peak is shifted by about 2–3 weeks, but the hydrological regime of the rivers remains dominated by snowmelt.     

Performance of ENSEMBLES regional climate models over Central Europe using various metrics

We show the evaluation of ENSEMBLES regional climate models (RCMs) driven by reanalysis ERA40 over a region centered at the Czech Republic. Attention is paid especially to the model ALADIN-CLIMATE/CZ, being used as the basis of the new climate change scenarios simulation for the Czech Republic. The validation criteria used here are based on monthly or seasonal mean air temperature and precipitation. We concentrate not only on spatiotemporal mean values but also on temporal standard deviation, inter-annual variability, the mean annual cycle, and the skill of the models to represent the observed spatial patterns of these quantities. Model ALADIN-CLIMATE/CZ performs quite well in comparison to the other RCMs; we find its performance satisfactory for further use for impact studies. However, it is also shown that the results of evaluation of the RCMs’ skill in simulating observed climate strongly depend on the criteria incorporated for the evaluation.     

Future changes in drought characteristics over South Korea using multi regional climate models with the standardized precipitation index

In this study, the projection of future drought conditions is estimated over South Korea based on the latest and most advanced sets of regional climate model simulations under the Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios, within the context of the national downscaling project of the Republic of Korea. The five Regional Climate Models (RCMs) are used to produce climate-change simulations around the Korean Peninsula and to estimate the uncertainty associated with these simulations. The horizontal resolution of each RCM is 12.5 km and model simulations are available for historical (1981-2010) and future (2021-2100) periods under forcing from the RCP4.5 and RCP8.5 scenarios. To assess the characteristics of drought on multiple time scales in the future, we use Standardized Precipitation Indices for 1-month (SPI- 1), 6-month (SPI-6) and 12-month (SPI-12). The number of drought months in the future is shown to be characterized by strong variability, with both increasing and decreasing trends among the scenarios. In particular, the number of drought months over South Korea is projected to increase (decrease) for the period 2041-2070 in the RCP8.5 (RCP4.5) scenario and increase (decrease) for the period 2071-2100 in the RCP4.5 (RCP8.5) scenario. In addition, the percentage area under any drought condition is overall projected to gradually decrease over South Korea during the entire future period, with the exception of SPI-1 in the RCP4.5 scenario. Particularly, the drought areas for SPI-1 in the RCP4.5 scenario show weakly positive long-term trend. Otherwise, future changes in drought areas for SPI-6 and SPI-12 have a marked downward trend under the two RCP scenarios.     

Comparison of four ensemble methods combining regional climate simulations over Asia

A number of uncertainties exist in climate simulation because the results of climate models are influenced by factors such as their dynamic framework, physical processes, initial and driving fields, and horizontal and vertical resolution. The uncertainties of the model results may be reduced, and the credibility can be improved by employing multi-model ensembles. In this paper, multi-model ensemble results using 10-year simulations of five regional climate models (RCMs) from December 1988 to November 1998 over Asia are presented and compared. The simulation results are derived from phase II of the Regional Climate Model Inter-comparison Project (RMIP) for Asia. Using the methods of the arithmetic mean, the weighted mean, multivariate linear regression, and singular value decomposition, the ensembles for temperature, precipitation, and sea level pressure are carried out. The results show that the multi-RCM ensembles outperform the single RCMs in many aspects. Among the four ensemble methods used, the multivariate linear regression, based on the minimization of the root mean square errors, significantly improved the ensemble results. With regard to the spatial distribution of the mean climate, the ensemble result for temperature was better than that for precipitation. With an increasing number of models used in the ensembles, the ensemble results were more accurate. Therefore, a multi-model ensemble is an efficient approach to improve the results of regional climate simulations.     

Sensitivity of the Iberian Peninsula climate to a land degradation

Two six-year simulations, a land degradation scenario and a control, were performed by applying a regional climate model nested in ECMWF analyzed data to the Iberian Peninsula. The simulated time period (1993-98) includes extremely anomalous dry and rainy years. The land degradation scenario assumed a decrease in vegetation cover and an alteration of the soil properties resulting from future increases of greenhouse gases and human activity. Simulation results show that the impact of land degradation on the climate of the Iberian Peninsula depends on local factors (the intensity of degradation and geographical location) but some noticeable non-local effects are also present. Local factors result in an increase of the surface temperature which is almost linearly related to the degradation intensity. A stronger decrease in precipitation is observed in the less degraded regions, indicating that non-local effects are more relevant to changes in precipitation. The highest sensitivity to land degradation is observed in the summer season, consisting of an increase in 2 m temperature and a reduction in precipitation. In winter, the rainiest season on the Iberian Peninsula, the impact of land degradation on precipitation is almost negligible.     

Analysis of the present and future winter Pacific-North American teleconnection in the ECHAM5 global and RegCM3 regional climate models

We use the NCEP/NCAR Reanalysis (NCEP) and the MPI/ECHAM5 general circulation model to drive the RegCM3 regional climate model to assess the ability of the models to reproduce the spatiotemporal aspects of the Pacific-North American teleconnection (PNA) pattern. Composite anomalies of the NCEP-driven RegCM3 simulations for 1982–2000 indicate that the regional model is capable of accurately simulating the key features (500-hPa heights, surface temperature, and precipitation) of the positive and negative phases of the PNA with little loss of information in the downscaling process. The basic structure of the PNA is captured in both the ECHAM5 global and ECHAM5-driven RegCM3 simulations. The 1950–2000 ECHAM5 simulation displays similar temporal and spatial variability in the PNA index as that of NCEP; however, the magnitudes of the positive and negative phases are weaker than those of NCEP. The RegCM3 simulations clearly differentiate the climatology and associated anomalies of snow water equivalent and soil moisture of the positive and negative PNA phases. In the RegCM3 simulations of the future (2050–2100), changes in the location and extent of the Aleutian low and the continental high over North America alter the dominant flow patterns associated with positive and negative PNA modes. The future projections display a shift in the patterns of the relationship between the PNA and surface climate variables, which suggest the potential for changes in the PNA-related surface hydrology of North America.     

On the ability of the regional climate model RIEMS to simulate the present climate over Asia

A continuous 10-year simulation in Asia for the period of 1 July 1988 to 31 December 1998 was conducted using the Regional Integrated Environmental Model System (RIEMS) with NCEP Reanalysis II data as the driving fields. The model processes include surface physics state package (BATS 1e), a Holtslag explicit planetary boundary layer formulation, a Grell cumulus parameterization, and a modified radiation package (CCM3). Model-produced surface temperature and precipitation are compared with observations from 1001 meteorology stations distributed over Asia and with the 0.5 × 0.5 CRU gridded dataset. The analysis results show that: (1) RIEMS reproduces well the spatial pattern and the seasonal cycle of surface temperature and precipitation; (2) When regionally averaged, the seasonal mean temperature biases are within 1–2C. For precipitation, the model tends to give better simulation in winter than in summer, and seasonal precipitation biases are mostly in the range of ?12%–50%; (3) Spatial correlation coefficients between observed and simulated seasonal precipitation are higher in north of the Yangtze River than in the south and higher in winter than in summer; (4) RIEMS can well reproduce the spatial pattern of seasonal mean sea level pressure. In winter, the model-simulated Siberian high is stronger than the observed. In summer, the simulated subtropical high is shifted northwestwards; (5) The temporal evolution of the East Asia summer monsoon rain belt, with steady phases separated by more rapid transitions, is reproduced.     

First-order impacts on winter and summer crops assessed with various high-resolution climate models in the Iberian Peninsula

The first-order or initial agricultural impacts of climate change in the Iberian Peninsula were evaluated by linking crop simulation models to several high-resolution climate models (RCMs). The RCMs provided the daily weather data for control, and the A2 and B2 IPCC scenarios. All RCMs used boundary conditions from the atmospheric general circulation model (AGCM) HadAM3 while two were also bounded to two other AGCMs. The analyses were standardised to control the sources of variation and uncertainties that were added in the process. Climatic impacts on wheat and maize of climate were derived from the A2 scenario generated by RCMs bounded to HadAM3. Some results derived from B2 scenarios are included for comparisons together with impacts derived from RCMs using different boundary conditions. Crop models were used as impact models and yield was used as an indicator that summarised the effects of climate to quantify initial impacts and differentiate among regions. Comparison among RCMs was made through the choice of different crop management options. All RCM-crop model combinations detected crop failures for winter wheat in the South under control and future scenarios, and projected yield increases for spring wheat in northern and high altitude areas. Although projected impacts differed among RCMs, similar trends emerged for relative yields for some regions. RCM-crop model outputs compared favourably to others using European Re-Analysis data (ERA-15), establishing the feasibility of using direct daily outputs from RCM for impact analysis. Uncertainties were quantified as the standard deviation of the mean obtained for all RCMs in each location and differed greatly between winter (wheat) and summer (maize) seasons, being smaller in the latter.     

The dry and hot American Southwest under the present and future climates

由于正在持续的特大干旱,更频繁的洪水,热浪以及导致空气污染的山火,美国西南部目前正在经历气候危机.这些气候危机主要与水文气候过程相关,尤其是气候系统各圈层之间的水汽通量.本研究主要讨论目前一些水文系统的科学基站以及物理驱动因素,比如北美夏季风以及太平洋北美遥相关.本研究指出降水以及气温对于干旱的相对作用的理论和工具.确定内部变率和外部强迫对于美国西南部水文气候系统的相对作用尤为重要.展望未来,需要研究高分辨率模拟系统,加强降水以及温度对于水文气候系统相对作用的理解,外部强迫的作用以及通过科学家以及其他利益相关者之间的合作.