Climate Model COSMO-CLM Research Articles

A Three-Year Climatology of the Wind Field Structure at Cape Baranova (Severnaya Zemlya, Siberia) from SODAR Observations and High-Resolution Regional Climate Model Simulations during YOPP

Measurements of the atmospheric boundary layer (ABL) structure were performed for three years (October 2017–August 2020) at the Russian observatory “Ice Base Cape Baranova” (79.280° N, 101.620° E) using SODAR (Sound Detection And Ranging). These measurements were part of the YOPP (Year of Polar Prediction) project “Boundary layer measurements in the high Arctic” (CATS_BL) within the scope of a joint German–Russian project. In addition to SODAR-derived vertical profiles of wind speed and direction, a suite of complementary measurements at the observatory was available. ABL measurements were used for verification of the regional climate model COSMO-CLM (CCLM) with a 5 km resolution for 2017–2020. The CCLM was run with nesting in ERA5 data in a forecast mode for the measurement period. SODAR measurements were mostly limited to wind speeds <12 m/s since the signal was often lost for higher winds. The SODAR data showed a topographical channeling effect for the wind field in the lowest 100 m and some low-level jets (LLJs). The verification of the CCLM with near-surface data of the observatory showed good agreement for the wind and a negative bias for the 2 m temperature. The comparison with SODAR data showed a positive bias for the wind speed of about 1 m/s below 100 m, which increased to 1.5 m/s for higher levels. In contrast to the SODAR data, the CCLM data showed the frequent presence of LLJs associated with the topographic channeling in Shokalsky Strait. Although SODAR wind profiles are limited in range and have a lot of gaps, they represent a valuable data set for model verification. However, a full picture of the ABL structure and the climatology of channeling events could be obtained only with the model data. The climatological evaluation showed that the wind field at Cape Baranova was not only influenced by direct topographic channeling under conditions of southerly winds through the Shokalsky Strait but also by channeling through a mountain gap for westerly winds. LLJs were detected in 37% of all profiles and most LLJs were associated with channeling, particularly LLJs with a jet speed ≥ 15 m/s (which were 29% of all LLJs). The analysis of the simulated 10 m wind field showed that the 99%-tile of the wind speed reached 18 m/s and clearly showed a dipole structure of channeled wind at both exits of Shokalsky Strait. The climatology of channeling events showed that this dipole structure was caused by the frequent occurrence of channeling at both exits. Channeling events lasting at least 12 h occurred on about 62 days per year at both exits of Shokalsky Strait.

Simulation of chemical transport model estimates by means of a neural network using meteorological data

Chemical substances of either anthropogenic or natural origin affect air quality and, as a consequence, also the health of the population. Therefore, there is a high demand for reliable air quality scenarios that can support possible management decisions. However, generating long term assessments of air quality assuming different emission scenarios is still a great challenge when using detailed atmospheric chemistry models. In this study, we test machine learning technique based on neural networks (NN) to emulate process-oriented modeling outcomes. A successfully calibrated NN might estimate concentrations of chemical substances in the air several orders faster than the original model and with reasonably small errors. We designed a simple recurrent 3-layer NN to reproduce daily mean concentrations of NO2, SO2 and C2H6 over Europe as simulated by the Community Multiscale Air Quality model (CMAQ). The general structure of the NN can be shown to approximate a continuity equation. Inputs of the network are daily mean meteorological state variables, taken from the climate model COSMO-CLM. The proposed NN emulates CMAQ outputs with an error not exceeding the difference between CMAQ and other known chemical transport models.

Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

Impact of Environmental Conditions on Grass Phenology in the Regional Climate Model COSMO-CLM

Feedbacks of plant phenology to the regional climate system affect fluxes of energy, water, CO2, biogenic volatile organic compounds as well as canopy conductance, surface roughness length, and are influencing the seasonality of albedo. We performed simulations with the regional climate model COSMO-CLM (CCLM) at three locations in Germany covering the period 1999 to 2015 in order to study the sensitivity of grass phenology to different environmental conditions by implementing a new phenology module. We provide new evidence that the annually-recurring standard phenology of CCLM is improved by the new calculation of leaf area index (LAI) dependent upon surface temperature, day length, and water availability. Results with the new phenology implemented in the model show a significantly higher correlation with observations than simulations with the standard phenology. The interannual variability of LAI improves the representation of vegetation in years with extremely warm winter/spring (e.g., 2007) or extremely dry summer (e.g., 2003) and shows a more realistic growth period. The effect of the newly implemented phenology on atmospheric variables is small but tends to be positive. It should be used in future applications with an extension on more plant functional types.

Impact of Air Conditioning Systems on the Outdoor Thermal Environment during Summer in Berlin, Germany.

This study investigates the effect of anthropogenic heat emissions from air conditioning systems (AC) on air temperature and AC energy consumption in Berlin, Germany. We conduct simulations applying the model system CCLM/DCEP-BEM, a coupled system of the mesoscale climate model COSMO-CLM (CCLM) and the urban Double Canyon Effect Parameterization scheme with a building energy model (DCEP-BEM), for a summer period of 2018. The DCEP-BEM model is designed to explicitly compute the anthropogenic heat emissions from urban buildings and the heat flux transfer between buildings and the atmosphere. We investigate two locations where the AC outdoor units are installed: either on the wall of a building (VerAC) or on the rooftop of a building (HorAC). AC waste heat emissions considerably increase the near-surface air temperature. Compared to a reference scenario without AC systems, the VerAC scenario with a target indoor temperature of 22 results in a temperature increase of up to . The increase is more pronounced during the night and for urban areas. The effect of HorAC on air temperature is overall smaller than in VerAC. With the target indoor temperature of 22 , an urban site’s daily average AC energy consumption per floor area of a room is , which is 35% more than that of a suburban site. This energy-saving results from the urban heat island effect and different building parameters between both sits. The maximum AC energy consumption occurs in the afternoon. When the target indoor temperature rises, the AC energy consumption decreases at a rate of about 16% per 2 change in indoor temperature. The nighttime near-surface temperature in VerAC scenarios shows a declining trend ( per 2 change) with increasing target indoor temperature. This feature is not obvious in HorAC scenarios which further confirms that HorAC has a smaller impact on near-surface air temperature.

Assessment of Regional Climate Model Simulations of the Katabatic Boundary Layer Structure over Greenland

The parameterization of the boundary layer is a challenge for regional climate models of the Arctic. In particular, the stable boundary layer (SBL) over Greenland, being the main driver for substantial katabatic winds over the slopes, is simulated differently by different regional climate models or using different parameterizations of the same model. However, verification data sets with high-resolution profiles of the katabatic wind are rare. In the present paper, detailed aircraft measurements of profiles in the katabatic wind and automatic weather station data during the experiment KABEG (Katabatic wind and boundary-layer front experiment around Greenland) in April and May 1997 are used for the verification of the regional climate model COSMO-CLM (CCLM) nested in ERA-Interim reanalyses. CCLM is used in a forecast mode for the whole Arctic with 15 km resolution and is run in the standard configuration of SBL parameterization and with modified SBL parameterization. In the modified version, turbulent kinetic energy (TKE) production and the transfer coefficients for turbulent fluxes in the SBL are reduced, leading to higher stability of the SBL. This leads to a more realistic representation of the daily temperature cycle and of the SBL structure in terms of temperature and wind profiles for the lowest 200 m.

Skill and added value of the MiKlip regional decadal prediction system for temperature over Europe

In recent years, several decadal prediction systems have been developed to provide multi-year predictions of the climate for the next 5–10 years. On the global scale, high decadal predictability has been identified for the North Atlantic sector, often extending over Europe. The first full regional hindcast ensemble, derived from dynamical downscaling, was produced within the German MiKlip project (‘decadal predictions’). The ensemble features annual starting dates from 1960 to 2017, with 10 decadal hindcasts per starting year. The global component of the prediction system uses the MPI-ESM-LR and the downscaling is performed with the regional climate model COSMO-CLM (CCLM). The present study focusses on a range of aspects dealing with the skill and added value of regional decadal temperature predictions over Europe. The results substantiate the added value of the regional hindcasts compared to the forcing global model as well as to un-initialized simulations. The results show that the hindcasts are skilful both for annual and seasonal means, and that the scores are comparable for different observational reference data sets. The predictive skill increases from earlier to more recent start-years. A recalibration of the simulation data generally improves the skill further, which can also be transferred to more user-relevant variables and extreme values like daily maximum temperatures and heating degree-days. These results provide evidence of the potential for the regional climate predictions to provide valuable climate information on the decadal time-scale to users.

Impacts of global warming of 1.5 °C and 2.0 °C on precipitation patterns in China by regional climate model (COSMO-CLM)

Regional precipitation patterns may change in a warmer climate, thereby increasing flood and drought risks. In this paper, annual, annual maximum, intense, heavy, moderate, light, and trace precipitation are employed as indicators to assess changes in precipitation patterns under two scenarios in which the global mean temperature increases by 1.5°C and 2.0°C relative to pre-industrial levels using the regional climate model COSMO-CLM (CCLM). The results show that annual precipitation in China will be approximately 2.5% higher under 1.5°C warming relative to the present-day baseline (1980–2009), although it will decrease by approximately 4.0% under an additional 0.5°C increase in global mean temperature. This trend is spatially consistent for regions with annual precipitation of 400–800mm, which has experienced a drying trend during the past half century; thus, limiting global warming to 1.5°C may mitigate these drying conditions. The annual maximum precipitation continues to increase from present day levels to the 2.0°C warming scenario. Relative to the baseline period, the frequency of trace and light precipitation days exhibits a negative trend, while that of moderate, heavy, and intense precipitation days has a positive trend under the 1.5°C warming scenario. For the 2.0°C warming world, the frequency of days is projected to decrease for all precipitation categories, although the intensity of intense precipitation increases. Spatially, a decrease in the number of precipitation days is expected to continue in central and northern China, where a drying trend has persisted over the past half century. Southeastern China, which already suffers greatly from flooding, is expected to face more heavy and intense precipitation with an additional 0.5°C increase in global mean temperature. Meanwhile, the intensity of intense precipitation is expected to increase in northern China, and the contribution of light and moderate precipitation to the annual precipitation is expected to decrease in southeastern China. Therefore, flood risk in northern China and drought risk in southern China should draw more attention for a global air temperature increase from 1.5°C to 2.0°C.

Projection of actual evapotranspiration using the COSMO-CLM regional climate model under global warming scenarios of 1.5 °C and 2.0 °C in the Tarim River basin, China

Actual evapotranspiration (ETa) is an important component of the water cycle. The goals for limiting global warming to below 2.0°C above pre-industrial levels and aspiring to 1.5°C were negotiated in the Paris Agreement in 2015. In this study, outputs from the regional climate model COSMO-CLM (CCLM) for the Tarim River basin (TRB) were used to calculate ETa with an advection-aridity model, and changes in ETa under global warming scenarios of 1.5°C (2020 to 2039) and 2.0°C (2040 to 2059) were analyzed. Comparison of warming at the global and regional scale showed that regional 1.5°C warming would occur later than the global average, while regional 2.0°C warming would occur earlier than the global average. For global warming of 1.5°C, the average ETa in the TRB is about 222.7mm annually, which represents an increase of 6.9mm relative to the reference period (1986–2005), with obvious increases projected for spring and summer. The greatest increases in ETa were projected for the northeast and southwest. The increment in the annual ETa across the TRB considering a warming of 1.5°C was 4.3mm less than that for a warming of 2.0°C, and the reduction between the two levels of warming was most pronounced in the summer, when ETa was 3.4mm smaller. The reduction in the increment of annual ETa for warming of 1.5°C relative to warming of 2.0°C was most pronounced in the southwest and northeast, where it was projected to be 8.2mm and 9.3mm smaller, respectively. It is suggested that the higher ETa under a warming of 2.0°C mainly results from an increase in the sunshine duration (net radiation) in the southwestern basin and an increase in precipitation in the northeastern basin. Vapor is removed from the limited surface water supplies by ETa. The results of this study are therefore particularly relevant for water resource planning in the TRB.

Exposure of population to droughts in the Haihe River Basin under global warming of 1.5 and 2.0 °C scenarios

Based on outputs from regional climate model COSMO-CLM (CCLM), climate conditions in the Haihe River Basin (HRB) under the 1.5 and 2.0 °C global warming scenarios were projected. Drought characteristics were analyzed by the Standardized Precipitation Evapotranspiration Index (SPEI), and population exposure to regional droughts in the warming world were then assessed by a combination of the population in 2010. It was revealed that both annual precipitation and potential evapotranspiration will increase in the 1.5 °C warming level relative to the reference period of 1986–2005 in the HRB. But annual precipitation was projected to decrease in the 2.0 °C warming level, although potential evapotranspiration was projected to increase. The temperature in the HRB was projected to rise faster than the global mean, and the timing of the regional 2.0 °C warming level will come earlier. Under the global warming of 1.5 °C, intensity and coverage of droughts in the HRB exhibit no significant trends relative to 1986–2005, while the drought frequency might decrease to a certain degree. Under the global warming of 2.0 °C, intensity and coverage of droughts will increase notably. In particular, drought coverage in the 2.0 °C level will be 1.9 times larger than that of the 1.5 °C scenario. Drought frequency under the 2.0 °C warming scenario will increase relative to the 1.5 °C warming scenario but still be less than that of the reference period. As a result, population exposure to droughts in the 1.5 °C warming level could be reduced by 30.4% relative to the 1986–2005 period, but increase by 74.8% in the 2.0 °C warming level. Seasonally, an increasing trend of exposure to severe droughts in summer, autumn and winter was projected in the 1.5 °C global warming level, while that to extreme droughts in summer and winter will decrease. Under 2.0 °C global warming scenario, increasing trend of severe and extreme droughts was projected in spring, autumn and winter. And the exposure to extreme droughts in autumn and winter might be doubled relative to the reference period. Similar spatial distribution patterns were found for population exposure in 1.5 °C and 2 °C global warming levels with high values projected in south and central basin but low in north and west. But the difference is, less population will be exposed to droughts in most area of HRB under 1.5 °C warming scenario, while population exposure will be larger under 2.0 °C global warming scenario relative to 1986–2005. The additional 0.5 °C from 1.5 °C to 2.0 °C will obviously increase the drought risks, especially in the southern and central HRB. Considering the projections that more drought risks might exist under the 2.0 °C warming scenario than in the 1.5 °C level, a perspective to keep the increase in global mean temperature below 2.0 °C and limit it to 1.5 °C, has far-reaching implications to socioeconomic development in the HRB.

Analysis of future drought characteristics in China using the regional climate model CCLM

In this paper, the intensity, area and duration of future droughts in China are analyzed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SPI and SPEI are used to evaluate the simulation ability of drought characteristics with the regional climate model COSMO-CLM (CCLM). The projected intensity and duration of future drought events are analyzed for the period 2016–2050 under three different respective concentration pathways (RCPs). The simulated and projected drought events are analyzed by applying the intensity-area-duration method. The results show that CCLM has a robust capability to simulate the average drought characteristics, while some regional disparities are not well captured, mainly the simulation of more drought events of shorter duration in Northwest China. For the future period 2016–2050, more intense dryness conditions are projected for China. An increase in evapotranspiration is found all over China, while a reduction in precipitation is apparent in the southern river basins. The increase in evapotranspiration plays an important role in the changes of future droughts over the northern river basins and southern river basins. Under RCP2.6, drought events of longer duration and with higher frequency are projected for the southwest and southeast of China. Under RCP4.5 and RCP8.5, a continuing tendency to more dry conditions is projected along a dryness band stretching from the southwest to the northeast of China. More frequent drought events of longer duration are projected in the southwestern river basins. For all future droughts, larger extents are projected, especially for events with long-term duration. The projected long-term drought events will occur more often and more severe than during the baseline period, and their central locations will likely shift towards Southeast China. The results of this study can be used to initiate and strengthen drought adaptation measures at regional and local scale, especially in the south of China.

Simulation and projection of climatic changes in the Indus River Basin, using the regional climate model COSMO‐CLM

ABSTRACTIn this article, the analysis of simulated and projected climatic changes in the Indus River Basin (IRB) is presented. The performance of the regional climate model COSMO‐CLM (CCLM) driven by the global circulation model MPI‐ESM‐LR is evaluated on the ability of reproducing temperature, precipitation, and wind pattern for the period 1961–2005. There exist quantitative biases, especially in precipitation pattern, which are associated to the diverse reproduction of the atmospheric circulation by the global circulation model. The overall results show that CCLM is able to satisfyingly capture the dominant spatial characteristics in annual temperature and precipitation time series, including the warming trend, and the seasonal variations.The changes in precipitation and temperature over the IRB are projected for the mid‐ (2046–2065) and late‐21st century (2081–2100). Relative to the baseline period (1986–2005), the average annual temperature will increase during the mid‐ and late‐21st century over the whole basin. Extreme temperature events, i.e. heat waves, are more likely to occur. An increase in summer temperature is also projected especially in the upper IRB, where the persistent increase is likely to cause further melting of glaciers. The annual precipitation will decrease in both the mid‐ and late‐21st century with significant spatial changes. A decrease in the monsoon precipitation is also projected, particularly in the central and southern plains of lower altitudes, which might be highly related to the reduction of wet air from the Indian Ocean and the increment in outflow to the east of the IRB. For winter and spring precipitation, except for the late‐21st century under the representative climate pathway (RCP) 2.6, a decreasing trend is projected, which might be caused by the reduction of water vapour from the west. This will further weaken the availability of water resources in these seasons, especially in the upper IRB of higher altitudes.

A model-based climatology analysis of wind power resources at 100-m height over the Bohai Sea and the Yellow Sea

China has set ambitious goals for the development of offshore wind energy to meet the increasing energy demand of coastal provinces. Many studies have assessed the potential offshore wind energy in Chinese territorial waters. However, few studies have focused on the climatology, variability, and extreme climate of wind speeds and wind power, especially at hub height in this area. This type of study is important for selecting promising sites for offshore wind farms. In the present study, a 35-year (1979–2013) high-resolution (7km) wind hindcast over the Bohai Sea and the Yellow Sea (BYS) at 100-m height was constructed using the regional climate model COSMO-CLM (CCLM) driven by the ERA-Interim reanalysis dataset. The quality of wind speeds reconstructed by CCLM was assessed by a comparison with observation data at several stations. After verification, the climatology, variability, and extreme climate of winds over the BYS were spatially and temporally investigated. The results show that the 35-year mean wind speed is mostly between 7.0 and 7.5m/s; in the coastal areas of the BYS, the mean is less than 7.0m/s, and in the remote offshore areas, the mean is greater than 7.5m/s. The daily mean wind speed is stronger (weaker) in winter (summer) half year, with stronger (weaker) spatial variability. Wind power density is mainly 300–500W/m2. The interannual variability of annual mean wind speed and the wind power are in the range of 0.1–0.3m/s and 10–40W/m2, respectively. Decadal variances of the mean wind speed and the wind power are roughly within ±2% and ±5%, respectively, with a stronger variability along the southwestern coasts of the Yellow Sea. The distribution patterns of extreme winds (i.e., 5, 10, 30, and 50-year return values) are generally similar, with strength increasing from the northwest to the southeast. The wind energy characteristics for water areas and potential wind farm sites are summarized.

Simulated and projected climate extremes in the Tarim River Basin using the regional climate model CCLM

The reduction of uncertainty in simulations and projections of regional climate models is a critical issue for regional climate impact studies, especially in the context of climate extremes. In this study, the regional climate model COSMO-CLM (CCLM) is evaluated in terms of daily precipitation and temperature characteristics, in order to obtain reliable projections of climate extremes for the Tarim River Basin (TRB) in Northwest China. The results show that CCLM can acceptably reproduce the annual cycle of maximum and minimum temperature, as well as the spatial distribution of precipitation pattern. Nonetheless, some systematic biases have been encountered. The equidistant cumulative distribution function matching method has been applied, which led to an efficient reduction of the systematic biases of observed and simulated climate variables. The bias correction has further been applied to climate projections for the period of 2016–2035 under the Representative Concentration Pathway 4.5. The projected indices of climate extremes as calculated from the bias-corrected CCLM projections show that most of the TRB is likely to experience a decrease in daily temperature range, and an increase in minimum temperature as well as consecutive wet days. The total precipitation on very wet days is projected to slightly increase at most stations, while the annual total precipitation will mostly increase in the southwestern parts of the TRB. The findings on the spatial–temporal patterns of these climate extremes will enable decision makers, especially in the water and agricultural sectors, to adapt and be better prepared for future climate impacts in the region.

High-resolution atmospheric reconstruction for Europe 1948–2012: coastDat2

Abstract. The coastDat data sets were produced to give a consistent and homogeneous database mainly for assessing weather statistics and climate changes since 1948, e.g., in frequencies of extremes for Europe, especially in data sparse regions. A sequence of numerical models was employed to reconstruct all aspects of marine climate (such as storms, waves, surges, etc.) over many decades. The acronym coastDat stands for the set of consistent ocean and atmospheric data, where the atmospheric data where used as forcing for the reconstruction of the sea state. Here, we describe the atmospheric part of coastDat2 (Geyer and Rockel, 2013; doi:10.1594/WDCC/coastDat-2_COSMO-CLM). It consists of a regional climate reconstruction for the entire European continent, including the Baltic Sea and North Sea and parts of the Atlantic. The simulation was done for 1948 to 2012 with the regional climate model COSMO-CLM (CCLM) and a horizontal grid size of 0.22 degree in rotated coordinates. Global reanalysis data of NCEP1 were used as forcing and spectral nudging was applied. To meet the demands on the coastDat data set about 70 variables are stored hourly.

A regional climate model hindcast for Siberia: analysis of snow water equivalent

Abstract. This study analyzes the added value of a regional climate model hindcast with respect to snow water equivalent (SWE) for Siberia when compared to SWE estimates from forcing NCEP-R. In addition, we examine the discrepancies of simulated SWE to several recent reanalysis products (NCEP-R2 NCEP-CFSR, ERA-Interim). We apply the regional climate model COSMO-CLM (CCLM) to a 50 km grid spacing using NCEP-R1 as driving force to obtain a 63 yr (1948 to 2010) gridded dataset of historical SWE. Simulated regional climate data is necessary because of the absence of station data in that region. To perform large-scale assessments we use the satellite-derived daily SWE product of ESA DUE GlobSnow from 1987 to 2010. Russian station SWE data is used for cross-checking the findings. In January (mid-winter), the SWE hindcast is in good agreement with GlobSnow, whereas it overestimates SWE during the melting season. CCLM shows a clear added value in providing realistic SWE information compared to the driving reanalysis. The temporal consistency of CCLM is higher than that presented by ERA-Interim and NCEP-R2.

Regional dynamical downscaling with CCLM over East Asia

Inspired by the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX), the hindcast (1971–2000) and projection (2021–2050) simulations based on a resolution of \(0.44^\circ\) over the East Asia domain are performed with the regional climate model COSMO-CLM (CCLM). The simulations are driven by ERA-40 reanalysis data and output of the global climate model ECHAM5. This is the first time that the CCLM is adapted and evaluated for the East Asia Monsoon region; the setup is considered a starting point for further improvements in this region by the CCLM community. The evaluation results show that the CCLM is able to reasonably capture the climate features in this region, especially the monsoon dynamics on small scales. However, total precipitation in the northern part of the domain, over the Tibetan Plateau, and over east Indonesia has a pronounced wet bias. The projected climate change under the A1B scenario indicates an overall annual surface temperature increase of 1–2 K, but no significant precipitation changes.

Simulated and projected climate extremes in the Zhujiang River Basin, South China, using the regional climate model COSMO‐CLM

ABSTRACTThis study presents a detailed analysis of simulated and projected climate extremes in the Zhujiang River Basin (ZRB). Daily output from the regional climate model COSMO‐CLM (CCLM), driven by the ECHAM5 general circulation model, is used. The hindcast simulation covers the period from 1961 to 2000 while the projection concentrates on the near future period from 2011 to 2050. Spatio‐temporal statistical characteristics are investigated for three temperature and three precipitation indicators. The six simulated annual and monthly indicators are statistically compared with synoptic observations. The analysis is based on daily values of 195 grid points and 192 meteorological stations.The findings are presented and interpreted in terms of the model's capability. Compared to observations, slightly higher values for temperature indicators and slightly lower values for precipitation indicators are simulated. With the resulting good similarities in the spatial variation and trends, we conclude that CCLM is able to satisfyingly reproduce climate extreme for the simulated period. Therefore, our analyses show that CCLM can be used to project climate extremes in the ZRB for the period from 2011 to 2050. The projected changes indicate warmer and wetter conditions in the northern and southern regions, especially in winter and spring. This includes more intense rainfall events, which might potentially increase the risk of flooding in the central parts of the basin in these seasons. Warmer and dryer conditions can be expected in the western and eastern parts of the region, especially in summer and fall. These lower precipitation amounts but warmer temperatures will probably increase the evapotranspiration, which potentially leads to a higher risk of drought. Regarding these findings in climate extremes, adverse consequences in various sectors, such as agriculture, water, and energy should be anticipated.

Regional climate modelling over complex terrain: an evaluation study of COSMO-CLM hindcast model runs for the Greater Alpine Region

In this study the results of the regional climate model COSMO-CLM (CCLM) covering the Greater Alpine Region (GAR, 4°–19°W and 43°–49°N) were evaluated against observational data. The simulation was carried out as a hindcast run driven by ERA-40 reanalysis data for the period 1961–2000. The spatial resolution of the model data presented is approx. 10 km per grid point. For the evaluation purposes a variety of observational datasets were used: CRU TS 2.1, E-OBS, GPCC4 and HISTALP. Simple statistics such as mean biases, correlations, trends and annual cycles of temperature and precipitation for different sub-regions were applied to verify the model performance. Furthermore, the altitude dependence of these statistical measures has been taken into account. Compared to the CRU and E-OBS datasets CCLM shows an annual mean cold bias of −0.6 and −0.7 °C, respectively. Seasonal precipitation sums are generally overestimated by +8 to +23 % depending on the observational dataset with large variations in space and season. Bias and correlation show a dependency on altitude especially in the winter and summer seasons. Temperature trends in CCLM contradict the signals from observations, showing negative trends in summer and autumn which are in contrast to CRU and E-OBS.

A Double-Canyon Radiation Scheme for Multi-Layer Urban Canopy Models

We develop a double-canyon radiation scheme (DCEP) for urban canopy models embedded in mesoscale numerical models based on the Building Effect Parametrization (BEP). The new scheme calculates the incoming and outgoing longwave and shortwave radiation for roof, wall and ground surfaces for an urban street canyon characterized by its street and building width, canyon length, and the building height distribution. The scheme introduces the radiative interaction of two neighbouring urban canyons allowing the full inclusion of roofs into the radiation exchange both inside the canyon and with the sky. In contrast to BEP, we also treat direct and diffuse shortwave radiation from the sky independently, thus allowing calculation of the effective parameters representing the urban diffuse and direct shortwave radiation budget inside the mesoscale model. Furthermore, we close the energy balance of incoming longwave and diffuse shortwave radiation from the sky, so that the new scheme is physically more consistent than the BEP scheme. Sensitivity tests show that these modifications are important for urban regions with a large variety of building heights. The evaluation against data from the Basel Urban Boundary Layer Experiment indicates a good performance of the DCEP when coupled with the regional weather and climate model COSMO-CLM.