Search

Attribution studies in climate science aim for scientifically ascertaining the influence of climatic variations on natural or anthropogenic factors. Many of those studies adopt the concept of Granger causality to infer statistical cause-effect relationships, while utilizing traditional autoregressive models. In this article, we investigate the potential of state-of-the-art time series classification techniques to enhance causal inference in climate science. We conduct a comparative experimental study of different types of algorithms on a large test suite that comprises a unique collection of datasets from the area of climate-vegetation dynamics. The results indicate that specialized time series classification methods are able to improve existing inference procedures. Substantial differences are observed among the methods that were tested.

As high-resolution climate models become increasingly complex, it should be carefully assessed to what extent the improved physics in such models justifies the large computational cost that the complexity imposes. This paper presents a detailed sensitivity study of convective precipitationcharacteristics to the number of prognostic moments in bulk microphysics schemes using a highresolution convection-resolving climate model. It is shown that 1-moment and 2-moment microphysics schemes produce more similar surface precipitation characteristics for a composite of 20 real-case convective simulations in Belgium than for many idealized studies conducted before. In the baseline 2-moment scheme,size sorting of particles is counteracted by collisional drop breakup to produce mean drop sizes that are similar to those in the 1-moment version of the scheme. Hence, fallout, evaporationand surface rain rates are very similar between the two versions of the scheme. Conversely, larger sensitivities of precipitation extremes were found to the treatment of drop breakup and the shape of the particle size distributions. Consistent with previous studies, domain-averaged and peak precipitation increased monotonically with increasing breakup equilibrium diameter Deq. Further, it is shown that a negative exponential size distribution results in excessive radar reflectivities for light rain rates. Surface precipitation and the joint distribution of reflectivity and rain rate are best reproduced by a 2-moment version of the scheme that applies gamma distributions with a diagnostic shape parameter for all particles and a large Deq. However, given the large sensitivities and uncertainties associated with collisional drop breakup and size sorting, it is likely that the full potential of improved physics in a 2-moment scheme will remain underexposed as long as these processes are not better understood.

Urban residents are exposed to higher levels of heat stress in comparison to the rural population. As this phenomenon could be enhanced by both global greenhouse gas emissions (GHG) and urban expansion, urban planners and policymakers should integrate both in their assessment. One way to consider these two concepts is by using urban climate models at a high resolution. In this study, the influence of urban expansion and GHG emission scenarios is evaluated at 100 m spatial resolution for the city of Brussels (Belgium) in the near (2031-2050) and far (2081-2100) future. Two possible urban planning scenarios (translated into local climate zones, LCZs) in combination with two representative concentration pathways (RCPs 4.5 and 8.5) have been implemented in the urban climate model UrbClim. The projections show that the influence of GHG emissions trumps urban planning measures in each period. In the near future, no large differences are seen between the RCP scenarios; in the far future, both heat stress and risk values are twice as large for RCP 8.5 compared to RCP 4.5. Depending on the GHG scenario and the LCZ type, heat stress is projected to increase by a factor of 10 by 2090 compared to the present-day climate and urban planning conditions. The imprint of vulnerability and exposure is clearly visible in the heat risk assessment, leading to very high levels of heat risk, most notably for the North Western part of the Brussels Capital Region. The results demonstrate the need for mitigation and adaptation plans at different policy levels that strive for lower GHG emissions and the development of sustainable urban areas safeguarding livability in cities.

Assessment of surface urban heat islands (SUHI) has been hampered by the lack of a consistent framework to permit consistent interpretation between cities. Local Climate Zones (LCZ) are a universal description of local scale landscape types based on expected variation at neighbourhood scale (≥1km2) in and around cities. In this study, we investigate the suitability of the LCZ scheme for SUHI studies based on 50 cities from across the globe. For comparability we use an annual temperature cycle model for MODIS land surface temperature (LST) at different overpass times and multi-year mean Landsat 8 LST. The SUHI analysis shows significant differences in the intra-urban estimate of SUHI for different built LCZ types. Substantial variability of SUHI within LCZ classes and between cities exists and SUHI patterns vary by time of day. Landsat derived estimates have very high correlations to those from MODIS at a similar time. The use of an LCZ approach combined with annual SUHI estimates provides a promising approach for a consistent and comprehensive SUHI analysis framework subject to further work to assess the spatial scale of matching LST and LCZ data, filter for topographic effects, and include the phenological status.

Since 2012, Local Climate Zones (LCZ) have been used for numerous studies related to urban environment. In 2015, this use amplified because a method to map urban areas in LCZs was introduced by the World Urban Database and Access Portal Tools (WUDAPT). However in 2017, the first HUMan INfluence EXperiment showed that these maps often have poor or low quality. Since the maps are used in different applications such as urban modelling and land use/land cover change studies, it is of the utmost importance to improve mapping accuracies and a second experiment was launched. In HUMINEX 2.0, the focus lies on providing guidelines on the use of the mapping protocol based on the results of both HUMINEX 1.0 and 2.0. The results showed that: (1) it is important to follow the mapping protocol as strictly as possible, (2) a reasonable amount of time should be spent on the mapping procedure, (3) all users should perform a driving test, and (4) training area sets should be stored in the WUDAPT database for other users.

[1] This paper explores a statistical regression approach to downscale large-scale global circulation model output to the wind speed distribution at the hub-height of tall wind turbines. The methodology is developed for Cabauw, using observational, ERA-Interim and ECHAM5 data. The regression analysis is based on the parameters of the probability distribution functions (pdfs) and includes a variable evaluation prior to the development of the statistical models. During winter ECHAM5 performs very well in representing the ERA-Interim wind speed pdf at hub-height. However, during summer, the hub-height wind speed pdf is not well represented by ECHAM5. A regression analysis shows that during summer-day the hub-height wind speed is strongly linked to the wind speed at higher, skillfully represented levels. The summer-day hub-height wind speed can therefore be skillfully predicted using wind speed pdf parameters of higher levels (R 2 of the model using 500m wind speed scale parameter as a predictor is 0.84). During the summer-night, the stable boundary layer is much shallower and the statistical model shows that solely the higher level wind speed is not able to skillfully predict the hub-height wind speed pdf (R 2 of 0.59). Including temperature information in the downscaling model substantially improves the prediction of the summer-night hub-height wind speed pdf (R 2 adjusted of 0.68).

A single-layer urban canopy model Community Land Model Urban (CLMU) is evaluated over two contrasting urban environments of Toulouse (France) and Melbourne (Australia). For the latter, three measurement sites are available characterized by a varying amount of vegetation, which supports a detailed assessment of the representation of urban vegetation in CLMU. For Toulouse, observed roof, wall and road surface temperatures allow for a detailed evaluation of the anthropogenic heat parameterization. Overall, CLMU performs well in simulating the canyon and urban surface temperatures, anthropogenic heat flux and urban energy balance, with an overall better performance for the dense old city centre of Toulouse in comparison to the more vegetated sites in Melbourne. Results for the latter sites reveal that the pervious road fraction provides a reasonable approximation of vegetation in the urban canyon while the tile approach often results in an underestimation of latent heat fluxes. A detailed analysis of the radiative, turbulent and anthropogenic heat fluxes as well as surface temperatures for Toulouse point to a complex interaction between urban surfaces and canyon properties. Decoupling the roof from the urban canyon to the atmosphere aloft is shown to be important. Our findings suggest that more evaluation is necessary for contrasting urban geometries in order to obtain a better understanding of the interaction between the roof surface on the one hand and canyon air and air aloft on the other hand. The results simultaneously reveal a trade-off in errors between surface temperatures, radiative and turbulent fluxes and anthropogenic heat which again stresses the importance of the intended model application. Also, our results suggest that model complexity should, perhaps, relate to the site complexity. These results provide a robust basis for the construction of additional sensitivity experiments, tailored towards the intended application for urban climate mitigation studies.

Precipitation amounts over East Africa have been declining over the last decades. These changes and future climate change over the region are highly debated. This study analyzes drivers of future precipitation changes over East Africa by applying a classification of circulation patterns on 15 historical and future members of the COordinated Regional climate Downscaling EXperiment. Typical circulation types (CTs) are obtained. Under a high emission scenario, changes in the frequency of occurrence of these CTsattribute for23%of the total change in precipitation over East Africa by the end of the century. The remaining part (77%) is not related to East African synoptics, e.g. changes in moisture content, local/mesoscale feedbacks, and changes in moisture influx. These other effects comprise increases in precipitation close to the equator and the Somali region, while decreases are found over northwestern Ethiopia, the Sudan region and the lake areas. journal_title: Environmental Research Letters article_type: lett article_title: Drivers of future changes in East African precipitation copyright_information: © 2016 IOP Publishing Ltd license_information: cc-by Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. date_received: 2016-03-02 date_accepted: 2016-10-21 date_epub: 2016-11-08 ispartof: Environmental Research Letters vol:11 issue:11 status: published

The regional non-hydrostatic climate model COSMO-CLM is increasingly being used on fine spatial scales of 1–5 km. Such applications require a detailed differentiation between the parameterization for natural and urban land uses. Since 2010, three parameterizations for urban land use have been incorporated into COSMO-CLM. These parameterizations vary in their complexity, required city parameters and their computational cost. We perform model simulations with the COSMO-CLM coupled to these three parameterizations for urban land in the same model domain of Berlin on a 1-km grid and compare results with available temperature observations. While all models capture the urban heat island, they differ in spatial detail, magnitude and the diurnal variation. ispartof: Meteorologische Zeitschrift vol:25 issue:2 pages:231-244 status: published

This paper presents the Semi-empirical URban-canopY parametrization SURY, which bridges the gap between bulk urban land-surface schemes and explicit-canyon schemes. Based on detailed observational studies, modelling experiments and available parameter inventories, it offers a robust translation of urban canopy parameters containing the three-dimensional information into bulk parameters. It is extremely suitable for an intrinsic representation of canopy-dependent urban physics in existing bulk urban land-surface schemes of atmospheric models. At the same time, it delivers high efficiency in terms of computational cost for long-term climate modelling and numerical weather prediction. SURY enables versatility and consistency in choosing between the urban canopy parameters from bottom-up inventories and bulk parameters from top-down estimates. SURY is tested for Belgium at 2.8 km resolution with the COSMO-CLM model (version 5.0_clm6) that is extended with the bulk urban land-surface scheme TERRA_URB (version 2). The model reproduces very well the urban heat islands observed from in-situ urban-climate observations, satellite imagery and tower observations, which is in contrast to the original COSMO-CLM model without an urban land-surface scheme. As an application of SURY, the sensitivity of the COSMO-CLM model in terms of land-surface temperatures, air temperatures and associated urban heat islands is quantified for the urban canopy parameter ranges from the Local Climate Zones classification system. On the one hand, their city-scale effect shows that additional urban canopy information has potential for improving regional atmospheric modelling. On the other hand, the model performance and its sensitivity to the different urban canopy parameters largely depend on the temperature quantity considered. Such an ambiguity demonstrates that a multi-variable model evaluation is a requirement for improving and comparing online urban atmospheric modelling strategies.

Urban tree planting initiatives are being actively promoted as a planning tool to enable urban areas to adapt to and mitigate against climate change, enhance urban sustainability and improve human health and well-being. However, opportunities for creating new areas of green space within cities are often limited and tree planting initiatives may be constrained to kerbside locations. At this scale, the net impact of trees on human health and the local environment is less clear, and generalised approaches for evaluating their impact are not well developed. In this review, we use an urban ecosystems services framework to evaluate the direct, and locally-generated, ecosystems services and disservices provided by street trees. We focus our review on the services of major importance to human health and well-being which include ‘climate regulation’, ‘air quality regulation’ and ‘aesthetics and cultural services’. These are themes that are commonly used to justify new street tree or street tree retention initiatives. We argue that current scientific understanding of the impact of street trees on human health and the urban environment has been limited by predominantly regional-scale reductionist approaches which consider vegetation generally and/or single out individual services or impacts without considering the wider synergistic impacts of street trees on urban ecosystems. This can lead planners and policymakers towards decision making based on single parameter optimisation strategies which may be problematic when a single intervention offers different outcomes and has multiple effects and potential trade-offs in different places. We suggest that a holistic approach is required to evaluate the services and disservices provided by street trees at different scales. We provide information to guide decision makers and planners in their attempts to evaluate the value of vegetation in their local setting. We show that by ensuring that the specific aim of the intervention, the scale of the desired biophysical effect and an awareness of a range of impacts guide the choice of i) tree species, ii) location and iii) density of tree placement, street trees can be an important tool for urban planners and designers in developing resilient and resourceful cities in an era of climatic change. Electronic supplementary material The online version of this article (doi:10.1186/s12940-016-0103-6) contains supplementary material, which is available to authorized users.

Convection-permitting climate model are promising tools for improved representation of extremes, but the number of regions for which these models have been evaluated are still rather limited to make robust conclusions. In addition, an integrated interpretation of near-surface characteristics (typically temperature and precipitation) together with cloud properties is limited. The objective of this paper is to comprehensively evaluate the performance of a ‘state-of-the-art’ regional convection-permitting climate model for a mid-latitude coastal region with little orographic forcing. For this purpose, an 11-year integration with the COSMO-CLM model at Convection-Permitting Scale (CPS) using a grid spacing of 2.8 km was compared with in-situ and satellite-based observations of precipitation, temperature, cloud properties and radiation (both at the surface and the top of the atmosphere). CPS clearly improves the representation of precipitation, in especially the diurnal cycle, intensity and spatial distribution of hourly precipitation. Improvements in the representation of temperature are less obvious. In fact the CPS integration overestimates both low and high temperature extremes. The underlying cause for the overestimation of high temperature extremes was attributed to deficiencies in the cloud properties: The modelled cloud fraction is only 46 % whereas a cloud fraction of 65 % was observed. Surprisingly, the effect of this deficiency was less pronounced at the radiation balance at the top of the atmosphere due to a compensating error, in particular an overestimation of the reflectivity of clouds when they are present. Overall, a better representation of convective precipitation and a very good representation of the daily cycle in different cloud types were demonstrated. However, to overcome remaining deficiencies, additional efforts are necessary to improve cloud characteristics in CPS. This will be a challenging task due to compensating deficiencies that currently exist in ‘state-of-the-art’ models, yielding a good representation of average climate conditions. In the light of using the CPS models to study climate change it is necessary that these deficiencies are addressed in future research. ispartof: Climate Dynamics vol:47 issue:9 pages:3191-3202 status: published

This paper presents the Semi-empirical URban canopY parametrization (SURY) v1.0, which bridges the gap between bulk urban land-surface schemes and explicit-canyon schemes. Based on detailed observational studies, modelling experiments and available parameter inventories, it offers a robust translation of urban canopy parameters – containing the three-dimensional information – into bulk parameters. As a result, it brings canopy-dependent urban physics to existing bulk urban land-surface schemes of atmospheric models. At the same time, SURY preserves a low computational cost of bulk schemes for efficient numerical weather prediction and climate modelling at the convection-permitting scales. It offers versatility and consistency for employing both urban canopy parameters from bottom-up inventories and bulk parameters from top-down estimates. SURY is tested for Belgium at 2.8 km resolution with the COSMO-CLM model (v5.0_clm6) that is extended with the bulk urban land-surface scheme TERRA_URB (v2.0). The model reproduces very well the urban heat islands observed from in situ urban-climate observations, satellite imagery and tower observations, which is in contrast to the original COSMO-CLM model without an urban land-surface scheme. As an application of SURY, the sensitivity of atmospheric modelling with the COSMO-CLM model is addressed for the urban canopy parameter ranges from the local climate zones of http://WUDAPT.org. City-scale effects are found in modelling the land-surface temperatures, air temperatures and associated urban heat islands. Recommendations are formulated for more precise urban atmospheric modelling at the convection-permitting scales. It is concluded that urban canopy parametrizations including SURY, combined with the deployment of the WUDAPT urban database platform and advancements in atmospheric modelling systems, are essential. ispartof: Geoscientific Model Development vol:9 issue:9 pages:3027-3054 status: published

Urban drainage infrastructure is generally designed to rapidly export stormwater away from the urban environment to minimize flood risk created by extensive impervious surface cover. This deficit is resolved by importing high-quality potable water for irrigation. However, cities and towns at times face water restrictions in response to drought and water scarcity. This can exacerbate heating and drying, and promote the development of unfavourable urban climates. The combination of excessive heating driven by urban development, low water availability and future climate change impacts could compromise human health and amenity for urban dwellers. This paper draws on existing literature to demonstrate the potential of Water Sensitive Urban Design (WSUD) to help improve outdoor human thermal comfort in urban areas and support Climate Sensitive Urban Design (CSUD) objectives within the Australian context. WSUD provides a mechanism for retaining water in the urban landscape through stormwater harvesting and reuse while also reducing urban temperatures through enhanced evapotranspiration and surface cooling. Research suggests that WSUD features are broadly capable of lowering temperatures and improving human thermal comfort, and when integrated with vegetation (especially trees) have potential to meet CSUD objectives. However, the degree of benefit (the intensity of cooling and improvements to human thermal comfort) depends on a multitude of factors including local environmental conditions, the design and placement of the systems, and the nature of the surrounding urban landscape. We suggest that WSUD can provide a source of water across Australian urban environments for landscape irrigation and soil moisture replenishment to maximize the urban climatic benefits of existing vegetation and green spaces. WSUD should be implemented strategically into the urban landscape, targeting areas of high heat exposure, with many distributed WSUD features at regular intervals to promote infiltration and evapotranspiration, and maintain tree health.

Regime-dependent evaluation is a relatively new approach to assess model performance. It consists of classifying the model biases according to a discrete number of regimes and evaluating model output within each regime. In this paper, the regimes are firstly defined by the large-scale atmospheric circulation, based on the objective Jenkinson-Collison classification technique which distinguishes synoptic patterns by strength, direction and vorticity of the geostrophic flow. Eight directional and two vorticity circulation regimes (circulation types) are specified. In this way, it is possible to quantify the model performance for cases with for example westerly winds only, or with cyclonic circulation only. A second regime classification is based on temperature, which allows for detection of temperature-dependent model performance. Modelled accumulated precipitation (mm/6 h) is evaluated with rain gauges for the years 2007 and 2008. Two variants of the COSMO model are evaluated: a fine-resolution version (2.8 km, COSMO-DE) and a coarse-resolution version (7 km, COSMO-EU). In COSMO-EU, a windward/leeward effect becomes visible since circulation is related to dominant wind direction, hence to windward and lee side of orography. In COSMO-DE, no circulation dependent but a height-related bias is identified and further explored, making use of temperature-dependent evaluation which unveils a positive model bias related to solid precipitation.

Although mesoscale convective systems (MCSs) are the main source of precipitation in the semi-arid Sahel region, the relationship between MCS characteristics and their generated precipitation remain unclear. However, a thorough understanding of this relation is essential to work towards a classification scheme for MCSs and eventually to improve quantitative precipitation estimates in which cloud parameters are used as proxy variables for the total or maximum intense rainfall from a system. Accordingly, this study aims to analyse the cloud parameters and rain variables distributions and their concurrence before quantifying the relationships between them. This is done using hourly EUMETSAT's Meteosat-8 infrared (10.8 µm) images, 3-hourly precipitation data from National Aeronautics and Space Administration (NASA)'s Tropical Rainfall Measuring Mission and an MCS tracking algorithm. The period of interest extends from 1 June till 22 September 2006 and the area of interest covers the Lake Chad region. Results indicate that MCSs in the Sahel region generally show a maximum cloud coverage around 57 000 km2, a life duration of 9 h, an embedded convective core during 6 h and precipitation peaks around 12.3 mm h−1. A recurrent sequence of cloud and rain variables is also noticed; maximum in cloud coverage is mostly preceded by a minimum in brightness temperature in the cold convective core and is followed by a peak in precipitation. Longer-lived and larger MCSs as well as MCSs embedding very cold and long-lived convective cores exhibit an increased likelihood to induce more intense precipitation. Focussing on the characteristics of the cold convective core rather than on the characteristics of the entire system appears to be more relevant to predict the precipitation as the former are better correlated with the generated precipitation and can be used as proxy parameter for estimations of maximum intense precipitation using two-dimensional nonlinear regression models. Copyright © 2011 Royal Meteorological Society

The objective Lamb circulation type (CT) classification method, based on the strength, direction and vorticity of the geostrophic flow, is applied to Belgium. Eleven different large-scale synoptic circulation patterns are derived on a daily scale for the period 1962 and 1999. The circulation patterns are subsequently related to precipitation amount and occurrence for six stations characterising different regions in Belgium, namely coastal, flat and hilly areas. Based on precipitation occurrence and intensity, five wet classes are defined, which are responsible for 83% of the total precipitation amount. It is shown that a regression model based on CT as predictors represents precipitation variability better in winter and autumn than in spring and summer. On the monthly scale and in winter, CTs explain 60.3% of the precipitation variability.

Many strategies exist to combat soil degradation through erosion and compaction on agricultural fields. One of these strategies is conservation agriculture (CA). Reduced or no-tillage techniques, together with crop residue management and crop rotation are the pillars of CA. The term reduced tillage covers a range of tillage practices but it never involves inverting the soil. In this way, soil disturbance is minimised and crop residues are left on the soil. Studies in many European countries have shown that CA can indeed be very effective in combating soil erosion. However, soil and water conservation do not appear as main drivers in farmers’ decisions to shift or not to CA. Economic factors tend to be more important, but there are a lot of uncertainties on this domain. Studies show that production costs are mostly reduced, mainly by reduced fuel costs. Although many European studies have investigated the effect of reduced soil tillage on crop yields, a lot of uncertainties still exist. Most of the studies only cover a small range of field experiments, in one region. We present a meta-regression analysis (47 European studies, 563 observations) that compares crop yields under conventional tillage (CT), reduced tillage (RT) and no-tillage (NT) techniques. We analysed the possible influence on the relative yield ((RT or NT)/CT) of crop type, tillage depth, crop rotation, climate, CT yield and length of application of RT or NT. Our analysis shows that, while the introduction of conservation tillage in Europe may indeed have some negative effect on yields, these effects can be expected to be limited: the overall average reduction we found was ca. 4.5%. NT reduces crop yield on average with 8.5%. However, RT leads to a reduction in crop yields for maize and winter cereals only. By applying a linear mixed model, the importance of tillage depth and crop type as classification effects could be confirmed. Surprisingly, no-tillage did perform worse under drier climatic conditions. Negative effects such as an increased prevalence of pests and a lower quality of seed placement seem to outweigh possible gains due to increased water availability. On clay and sandy soils, however, this negative effect of no-tillage is counteracted, and all conservation tillage techniques perform better under drier climatic conditions. Another important finding is that, in cereals only rotations, relative yields under conservation tillage tend to decrease with time. Our analysis shows that conservation tillage is certainly a viable option for European agriculture from the viewpoint of agricultural productivity. Potential negative effects on agricultural productivity can be strongly reduced by applying sufficiently deep tillage and using a crop rotation including crops other than cereals.

In spite of the strict EU regulations, concentrations of surface ozone and PM10 often exceed the pollution standards for the Netherlands and Europe. Their concentrations are controlled by (precursor) emissions, social and economic developments and a complex combination of meteorological actors. This study tackles the latter, and provides insight in the meteorological processes that play a role in O3 and PM10 levels in rural mid-latitudes sites in the Netherlands. The relations between meteorological actors and air quality are studied on a local scale based on observations from four rural sites and are determined by a comprehensive correlation analysis and a multiple regression (MLR) analysis in 2 modes, with and without air quality variables as predictors. Furthermore, the objective Lamb Weather Type approach is used to assess the influence of the large-scale circulation on air quality. Keeping in mind its future use in downscaling future climate scenarios for air quality purposes, special emphasis is given to an appropriate selection of the regressor variables readily available from operational meteorological forecasts or AOGCMs (Atmosphere-Ocean coupled General Circulation Models). The regression models perform satisfactory, especially for O3, with an (R2 of 57.0% and 25.0% for PM10. Including previous day air quality information increases significantly the models performance by 15% (O3) and 18% (PM10). The Lamb weather types show a seasonal distinct pattern for high (low) episodes of average O3 and PM10 concentrations, and these are clear related with the meteorology-air quality correlation analysis. Although using a circulation type approach can provide important additional physical relations forward, our analysis reveals the circulation method is limited in terms of short-term air quality forecast for both O3 and PM10 (R2 between 0.12 and 23%). In summary, it is concluded that the use of a regression model is more promising for short-term downscaling from climate scenarios than the use of a weather type classification approach.

The computational cost still remains a limiting factor for performing convection-permitting climate simulations. Choosing a model set-up with the lowest computational cost without deteriorating the model performances is, therefore, of relevance before starting any decadal simulations at convection-permitting scale (CPS). In this study three different strategies that aim at reducing this computational cost are evaluated. These strategies are (1) excluding graupel in the microphysical scheme, (2) reducing the nesting steps to downscale from ERA-Interim scale to CPS and (3) reducing the domain size. To test these strategies, the COSMO-CLM regional model was integrated over a four-month summer period for Belgium and evaluated using both radar and rain-gauges precipitation data. It was found that excluding the graupel parametrization at CPS induces a dry bias, but that excluding the graupel parametrization in the parent nest of the CPS simulation does not impact daily accumulated precipitation. In addition, it was also found that the best downscaling strategy is to use two nesting steps, in our case 25 km and 2.8 km. The 7 km nest was found to be redundant. Finally, it was found that a minimum distance of ∼ 150 km between the evaluation domain and the lateral boundary is needed for daily precipitation to converge towards observed values. This indicates that the domain size must be large enough for the model to spin-up convective precipitation and in our case a domain size of 180 × 180 grid-points was found to be necessary. Our recommendations for CPS simulations at lowest computational cost are therefore (1) to include graupel parametrization at CPS but not in the parent nest, (2) to use two nesting steps to downscale from ERA-Interim to CPS and (3) to use a domain size large enough to allow for 150 km spatial spin-up. ispartof: Meteorologische Zeitschrift vol:25 issue:2 pages:149-163 status: published

© 2015 American Meteorological Society. Although the African Great Lakes are important regulators for the East African climate, their influence on atmospheric dynamics and the regional hydrological cycle remains poorly understood. This study aims to assess this impact by comparing a regional climate model simulation that resolves individual lakes and explicitly computes lake temperatures to a simulation without lakes. The Consortium for Small-Scale Modelling model in climate mode (COSMO-CLM) coupled to the Freshwater Lake model (FLake) and Community Land Model (CLM) is used to dynamically downscale a simulation from the African Coordinated Regional Downscaling Experiment (CORDEX-Africa) to 7-km grid spacing for the period of 1999-2008. Evaluation of the model reveals good performance compared to both in situ and satellite observations, especially for spatiotemporal variability of lake surface temperatures (0.68-K bias), and precipitation (-116mmyr-1 or8% bias). Model integrations indicate that the four major African Great Lakes almost double the annual precipitation amounts over their surface but hardly exert any influence on precipitation beyond their shores. Except for Lake Kivu, the largest lakes also cool the annual near-surface air by-0.6 to-0.9Kon average, this time with pronounced downwind influence. The lake-induced cooling happens during daytime, when the lakes absorb incoming solar radiation and inhibit upward turbulent heat transport. At night, when this heat is released, the lakes warm the near-surface air. Furthermore, Lake Victoria has a profound influence on atmospheric dynamics and stability, as it induces circular airflow with over-lake convective inhibition during daytime and the reversed pattern at night. Overall, this study shows the added value of resolving individual lakes and realistically representing lake surface temperatures for climate studies in this region. ispartof: Journal of Climate vol:28 issue:10 pages:4061-4085 status: published

In order to develop climate resilient urban areas and reduce emissions, several opportunities exist starting from conscious planning and design of green (and blue) spaces in these landscapes. Green urban infrastructure has been regarded as beneficial, e.g. by balancing water flows, providing thermal comfort. This article explores the existing evidence on the contribution of green spaces to climate change mitigation and adaptation services. We suggest a framework of ecosystem services for systematizing the evidence on the provision of bio-physical benefits (e.g. CO2 sequestration) as well as social and psychological benefits (e.g. improved health) that enable coping with (adaptation) or reducing the adverse effects (mitigation) of climate change. The multi-functional and multi-scale nature of green urban infrastructure complicates the categorization of services and benefits, since in reality the interactions between various benefits are manifold and appear on different scales. We will show the relevance of the benefits from green urban infrastructures on three spatial scales (i.e. city, neighborhood and site specific scales). We will further report on co-benefits and trade-offs between the various services indicating that a benefit could in turn be detrimental in relation to other functions. The manuscript identifies avenues for further research on the role of green urban infrastructure, in different types of cities, climates and social contexts. Our systematic understanding of the bio-physical and social processes defining various services allows targeting stressors that may hamper the provision of green urban infrastructure services in individual behavior as well as in wider planning and environmental management in urban areas.

To date, evaluation studies of global circulation models (GCMs) generally focus on large-scale circulation variables. However, since the resolution of GCMs is increasing and their interaction with the surface is improving, GCM representations of near-surface variables are becoming increasingly realistic. For downscaling practices, this implies that near-surface variables might become suitable as predictors in statistical models, and might increase the added value of dynamical models. This study focuses on the representation of wind and temperature in the lowest 1.5 km of the atmosphere over Europe as simulated by 6 of the earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 5. The evaluation is based on the representation of the variables’ probability density functions (PDFs) using ERA-Interim reanalysis data as the reference. The PDF biases are analyzed according to their scale and origin. Above coastal bays and capes, small-scale biases in the ESMs result in unskillful wind speed PDFs up to 400 m. High orography affects wind speeds throughout the lowest 1.5 km of the atmosphere, especially during summer and night. Apart from these small-scale biases, the surface wind speed PDFs north of 45°N are well represented by all the ESMs. Therefore, these PDFs can be considered skillful inputs for statistical downscaling practices. South of 45° N, winds are affected by a large-scale bias originating from errors in the representation of the large-scale circulation, especially during winter. For temperature, near-surface levels as well as upper-atmospheric levels are affected by small-scale and large-scale biases. Large-scale biases are adopted by the downscaling models, underlining the importance of model evaluation before downscaling. ispartof: Climate Research vol:61 issue:1 pages:41-56 status: published

The urban heat island (UHI) over Paris during summer 2006 was simulated using the Advanced Regional Prediction System (ARPS) updated with a simple urban parametrization at a horizontal resolution of 1km. Two integrations were performed, one with the urban land cover of Paris and another in which Paris was replaced by cropland. The focus is on a five-day clear-sky period, for which the UHI intensity reaches its maximum. The diurnal evolution of the UHI intensity was found to be adequately simulated for this five day period. The maximum difference at night in 2m temperature between urban and rural areas stemming from the urban heating is reproduced with a relative error of less than 10%. The UHI has an ellipsoidal shape and stretches along the prevailing wind direction. The maximum UHI intensity of 6.1K occurs at 23:00 UTC located 6 km downstream of the city centre and this largely remains during the whole night. An idealized one-column model study demonstrates that the nocturnal differential sensible heat flux, even though much smaller than its daytime value, is mainly responsible for the maximum UHI intensity. The reason for this nighttime maximum is that additional heat is only affecting a shallow layer of 150m. An air uplift is explained by the synoptic east wind and a ramp upwind of the city centre, which leads to a considerable nocturnal adiabatic cooling over cropland. The idealized study demonstrates that the reduced vertical adiabatic cooling over the city compared to cropland induces an addiational UHI build-up of 25%. The UHI and its vertical extent is affected by the boundary-layer stability, nocturnal low-level jet and radiative cooling as well. Therefore, improvements of representing these boundary-layer features in atmospheric models are important for UHI studies. ispartof: Atmospheric Chemistry and Physics vol:13 issue:17 pages:8525-8541 status: published

This study aims to compare and validate two soil-vegetation-atmosphere-transfer (SVAT) schemes: TERRA-ML and the Community Land Model (CLM). Both SVAT schemes are run in standalone mode (decoupled from an atmospheric model) and forced with meteorological in-situ measurements obtained at several tropical African sites. Model performance is quantified by comparing simulated sensible and latent heat fluxes with eddy-covariance measurements. Our analysis indicates that the Community Land Model corresponds more closely to the micrometeorological observations, reflecting the advantages of the higher model complexity and physical realism. Deficiencies in TERRA-ML are addressed and its performance is improved: (1) adjusting input data (root depth) to region-specific values (tropical evergreen forest) resolves dry-season underestimation of evapotranspiration; (2) adjusting the leaf area index and albedo (depending on hard-coded model constants) resolves overestimations of both latent and sensible heat fluxes; and (3) an unrealistic flux partitioning caused by overestimated superficial water contents is reduced by adjusting the hydraulic conductivity parameterization. CLM is by default more versatile in its global application on different vegetation types and climates. On the other hand, with its lower degree of complexity, TERRA-ML is much less computationally demanding, which leads to faster calculation times in a coupled climate simulation.

In the framework of the COST733 Action "Harmonisation and Applications of Weather Types Classifications for European Regions" a new circulation type classification software (hereafter, referred to as cost733class software) is developed. The cost733class software contains a variety of (European) classification methods and is flexible towards choice of domain of interest, input variables, time step, number of circulation types, sequencing and (weighted) target variables. This work introduces the capabilities of the cost733class software in which the resulting circulation types (CTs) from various circulation type classifications (CTCs) are applied on observed summer surface ozone concentrations in Central Europe. Firstly, the main characteristics of the CTCs in terms of circulation pattern frequencies are addressed using the baseline COST733 catalogue (cat 2.0), at present the latest product of the new cost733class software. In a second step, the probabilistic Brier skill score is used to quantify the explanatory power of all classifications in terms of the maximum 8 hourly mean ozone concentrations exceeding the 120-mu g/m(3) threshold; this was based on ozone concentrations from 130 Central European measurement stations. Averaged evaluation results over all stations indicate generally higher performance of CTCs with a higher number of types. Within the subset of methodologies with a similar number of types, the results suggest that the use of CTCs based on optimisation algorithms are performing slightly better than those which are based on other algorithms (predefined thresholds, principal component analysis and leader algorithms). The results are further elaborated by exploring additional capabilities of the cost733class software. Sensitivity experiments are performed using different domain sizes, input variables, seasonally based classifications and multiple-day sequencing. As an illustration, CTCs which are also conditioned towards temperature with various weights are derived and tested similarly. All results exploit a physical interpretation by adapting the environment-to-circulation approach, providing more detailed information on specific synoptic conditions prevailing on days with high surface ozone concentrations. This research does not intend to bring forward a favourite classification methodology or construct a statistical ozone forecasting tool but should be seen as an introduction to the possibilities of the cost733class software. It this respect, the results presented here can provide a basic user support for the cost733class software and the development of a more user- or application-specific CTC approach. Theoretical and Applied Climatology

To assess regional air quality, a high spatial and temporal resolution of data is necessary in order to develop strategies that follow the European Directives on Air Quality. Moreover, in order to make projections for future air quality levels, a robust methodology is needed that succeeds in reconstructing present-day air quality levels. At present, climate projections for meteorological variables are available from Atmospheric-Ocean Coupled Global Climate Models (AOGCMs) but the temporal and spatial resolution is insufficient for air quality assessment. Therefore, a variety of methods are tested in this paper in their ability to hindcast daily mean levels of O3 and PM10 from observed meteorological data. The methods are based on a multiple linear regression technique combined with the automated Lamb weather classification. Moreover, we studied whether the above-mentioned multiple regression analysis still holds when driven by operational ECMWF (European Center for Medium-Range Weather Forecast) meteorological data. The main results show that a weather type classification prior to the regression analysis is superior to a simple linear regression approach. In contrast to PM10 downscaling, seasonal characteristics should be taken into account during the downscaling of O3 time series. Furthermore, our analysis validates the strength of the observation-based regression to hindcast O3 concentrations even when applied on low-resolution gridded data as available from AOGCMs. Although part of the explained variance is lost due to a lower variability of the meteorological predictors and model deficiencies, this regression-circulation pattern tool is able to reproduce the relevant statistical properties of the observed O3 distributions important in terms of European air quality Directives and air quality mitigation strategies. For PM10, the situation is different as a regression-based approach using only meteorology data was found to be insufficient to explain the observed PM10 variability. ispartof: Atmospheric Environment vol:44 issue:10 pages:1341-1355 status: published

Using the synoptic-regression based approach developed in Part I of this research, this study estimates future maximum 8 hourly mean O3 levels under the future A1B scenario for a rural background area situated in The Netherlands. The statistical downscaling tool was used to downscale the Atmospheric-Ocean Coupled General Circulation Model (AOGCM) ECHAM5-MPI/OM for the present-day 20 Century (20C) control run (1991-2000) and two future A1B scenario periods (2051-2060 and 2091-2100). First, the statistical downscaling tool is evaluated in terms of downscaled O3 levels for the present-day climate, using a long record of observed O3 concentrations. Afterwards, these findings are used to introduce a bias correction on future estimates of O3 concentrations under a changing climate. For the future A1B scenario, overall O3 levels could increase with 2.8 and 10.9 µg/m³, for the period 2051-2060 and 2091-2100 period respectively, against the present-day 10-year average of 54.1 µg/m³, with a more pronounced effect in summer. Together with the mean properties, the number of days with high levels (> 120 µg/m³) of O3 could increase with 7.3 days yr-1 and 20.7 days yr-1 by the 2050s and 2090s respectively. Increase in summer O3 levels are especially due to a decrease in cloud cover associated with an increase in shortwave downward radiation and an increase in maximum temperature. Hereby, the extreme summer of 2003 is been shown to be an example of how future European summers (in terms of O3) may look like under a changing change. Next to that, some other issues are put forward to be considered in the prospects of future ozone projections and mitigation in Western and Central Europe. ispartof: Atmospheric Environment vol:44 issue:10 pages:1356-1366 status: published

We review recent advances in classifications of circulation patterns as a specific research area within synoptic climatology. The review starts with a general description of goals of classification and the historical development in the field. We put circulation classifications into a broader context within climatology and systematize the varied methodologies and approaches. We characterize three basic groups of classifications: subjective (also called manual), mixed (hybrid), and objective (computer-assisted, automated). The roles of cluster analysis and principal component analysis in the classification process are clarified. Several recent methodological developments in circulation classifications are identified and briefly described: the introduction of nonlinear methods, objectivization of subjective catalogs, efforts to optimize classifications, the need for intercomparisons of classifications, and the progress toward an optimum, if possible unified, classification method. Among the recent tendencies in the applications of circulation classifications, we mention a more extensive use in climate studies, both of past, present, and future climates, innovative applications in the ensemble forecasting, increasing variety of synoptic-climatological investigations, and steps above from the troposphere. After introducing the international activity within the field of circulation classifications, the COST733 Action, we briefly describe outputs of the inventory of classifications in Europe, which was carried out within the Action. Approaches to the evaluation of classifications and their mutual comparisons are also reviewed. A considerable part of the review is devoted to three examples of applications of circulation classifications: in historical climatology, in analyses of recent climate variations, and in analyses of outputs from global climate models.

During the ESCOMPTE campaign (Experience sur Site pour COntraindre les Modeles de Pollution atmospherique et de Transport d'Emissions), a 4-day intensive observation period was selected to evaluate the Advanced Regional Prediction System (ARPS), a nonhydrostatic meteorological mesoscale model that was optimized with a parameterization for thermal roughness length to better represent urban surfaces. The evaluation shows that the ARPS model is able to correctly reproduce temperature, wind speed, and direction for one urban and two rural measurements stations. Furthermore, simulated heat fluxes show good agreement compared to the observations, although simulated sensible heat fluxes were initially too low for the urban stations. In order to improve the latter, different roughness length parameterization schemes were tested, combined with various thermal admittance values. This sensitivity study showed that the Zilitinkevich scheme combined with and intermediate value of thermal admittance performs best. ispartof: Journal of geophysical research-atmospheres vol:113 issue:D16 pages:1-19 status: published

We review recent advances in classifications of circulation patterns as a specific research area within synoptic climatology. The review starts with a general description of goals of classification and the historical development in the field. We put circulation classifications into a broader context within climatology and systematize the varied methodologies and approaches. We characterize three basic groups of classifications: subjective (also called manual), mixed (hybrid), and objective (computer-assisted, automated). The roles of cluster analysis and principal component analysis in the classification process are clarified. Several recent methodological developments in circulation classifications are identified and briefly described: the introduction of nonlinear methods, objectivization of subjective catalogs, efforts to optimize classifications, the need for intercomparisons of classifications, and the progress toward an optimum, if possible unified, classification method. Among the recent tendencies in the applications of circulation classifications, we mention a more extensive use in climate studies, both of past, present, and future climates, innovative applications in the ensemble forecasting, increasing variety of synoptic-climatological investigations, and steps above from the troposphere. After introducing the international activity within the field of circulation classifications, the COST733 Action, we briefly describe outputs of the inventory of classifications in Europe, which was carried out within the Action. Approaches to the evaluation of classifications and their mutual comparisons are also reviewed. A considerable part of the review is devoted to three examples of applications of circulation classifications: in historical climatology, in analyses of recent climate variations, and in analyses of outputs from global climate models.

Several both subjective and objective methods for the classification of circulation patterns into categories have been developed over the past century. In this study, we used the automated Lamb weather type (WT) classification method, based on Mean Sea Level Pressure (MSLP) to examine present and future circulation patterns above Western and Central Europe. First, the European Center for Medium-Range Weather Forecast 40-year reanalysis data (ECMWF – ERA40) is used to evaluate the occurring WTs within the newly developed ECHAM5-MPI/OM model for the period 1961-2000. Our analysis shows that the ECHAM5 model is capable of reproducing circulation patterns for the October to April season. For the remaining part of the year, there are some significant differences in eastern and western directional circulation types. Therefore, in the second part of this study, past, present and future ECHAM5 pressure fields are investigated for the autumn and winter season only. Finally, long-term trends of MSLP fields of the A1B scenario simulation using ECHAM5-MPI/OM for the period 1860-2100 show a significant increase in western circulation and anticyclonic weather types over Western and Central Europe, accompanied by a decrease in eastern circulation and cyclonic weather types. ispartof: International Journal of Climatology vol:29 issue:12 pages:1796-1810 status: published

It is common practice to use a 30-year period to derive climatological values, as recommended by the World Meteorological Organization. However this convention relies on important assumptions, of which the validity can be examined by deriving the uncertainty inherent to using a limited time-period for deriving climatological values. In this study a new method, aiming at deriving this uncertainty, has been developed with an application to precipitation for a station in Europe (Westdorpe) and one in Africa (Gulu). The weather generator framework is used to produce synthetic daily precipitation time-series that can also be regarded as alternative climate realizations. The framework consists of an improved Markov model, which shows good performance in reproducing the 5-day precipitation variability. The sub-seasonal, seasonal and the inter-annual signals are introduced in the weather generator framework by including covariates. These covariates are derived from an empirical mode decomposition analysis with an improved stability and significance assessment. Introducing covariates was found to substantially improve the monthly precipitation variability for Gulu. From the weather generator, 1,000 synthetic time-series were produced. The divergence between these time-series demonstrates an uncertainty, inherent to using a 30-year period for mean precipitation, of 11 % for Westdorpe and 15 % for Gulu. The uncertainty for precipitation 10-year return levels was found to be 37 % for both sites. ispartof: Climate Dynamics vol:44 issue:1 pages:495-508 status: published

Antarctic ice sheet mass loss is currently equivalent to around 1 mm year−1 of global mean sea level rise. Most mass is lost due to sub-ice shelf melting and calving of icebergs. Ice sheet models of the Antarctic ice sheet have thus largely concentrated on parameterising sub-shelf and calving processes. However, surface mass balance (SMB) is also of crucial importance in controlling the stability and evolution of the vast Antarctic ice sheet. In this paper we compare the performance of five different regional climate models (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM and RACMO2.3p2) in simulating the near surface climate and SMB of Antarctica. Our results show that, when regional climate models (RCMs) are forced by the ERA-Interim reanalysis, the integrated Antarctic ice sheet ensemble mean annual SMB is 2329 ± 94 Gigatonnes (Gt) year−1 over the common 1987 to 2015 period. However, individual model estimates vary from 1961 ± 70 to 2519 ± 118 Gt year−1. The large differences are mostly explained by different SMB estimates in West Antarctica and the peninsula as well as around the Transantarctic mountains. The calculated annual average SMB is very sensitive to the period chosen but over the climatological mean period of 1980 to 2010 the ensemble mean is 2486 Gt year−1. The interannual variability in SMB is consistent between the models and dominated by variability in the driving ERA-Interim reanalysis. The declining trend in Antarctic SMB reported in other studies is also very sensitive to period chosen and models disagree on the sign and magnitude of the trend in Antarctic SMB over the ERA-Interim period. Evaluation of models shows that they simulate Antarctic climate well when compared with daily observed temperature (Pearson correlation of 0.85 and higher) and pressure (bias ranges from −0.39 hPa in HIRHAM5 to −6.01 hPa in MAR with a mean of −3.49 hPa over all models) and nudged models, constrained within the domain as well as at lateral boundaries, perform better than un-nudged models. We compare modelled surface mass balance with a large dataset of observations which, though biased by undersampling in some regions, indicates that many of the biases in modelled SMB are common between models. The inclusion of drifting snow schemes improves modelled SMB on ice sheet slopes between 1000 and 2000 m where strong katabatic winds form but other regions where precipitation rates are high lack observations needed for the evaluation of different SMB estimates. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution is therefore factored into our analysis. The majority of the different values for continental SMB are due to differences in modelled precipitation at relatively few grid points in coastal areas. Our analysis suggests that targeting coastal areas for observational campaigns will be key to improving and refining estimates of the total surface mass balance of Antarctica.