COSMO-BEP-Tree v1.0: a coupled urban climate model  with explicit representation of street trees

Abstract. Street trees are more and more regarded as an effective measure to reduce excessive heat in urban areas. However, the vast majority of mesoscale urban climate models do not represent street trees in an explicit manner and, for example, do not take the important effect of shading by trees into account. In addition, urban canopy models that take interactions of trees and urban fabrics directly into account are usually limited to the street or neighbourhood scale and hence cannot be used to analyse the citywide effect of urban greening. In order to represent the interactions between street trees, urban elements and the atmosphere in realistic regional weather and climate simulations, we coupled the Building Effect Parameterisation with Trees (BEP-Tree) vegetated urban canopy model and the Consortium for Small-scale Modeling (COSMO) mesoscale weather and climate model. The performance and applicability of the coupled model, named COSMO-BEP-Tree, are demonstrated over the urban area of Basel, Switzerland, during the heatwave event of June–July 2015. Overall, the model compared well with measurements of individual components of the surface energy balance and with air and surface temperatures obtained from a flux tower, surface stations and satellites. Deficiencies were identified for nighttime air temperature and humidity, which can mainly be traced back to limitations in the simulation of the nighttime stable boundary layer in COSMO. The representation of street trees in the coupled model generally improved the agreement with observations. Street trees produced large changes in simulated sensible and latent heat flux, and wind speed. Within the canopy layer, the presence of street trees resulted in a slight reduction in daytime air temperature and a very minor increase in nighttime air temperature. The model was found to realistically respond to changes in the parameters defining the street trees: leaf area density and stomatal conductance. Overall, COSMO-BEP-Tree demonstrated the potential of (a) enabling city-wide studies on the cooling potential of street trees and (b) further enhancing the modelling capabilities and performance in urban climate modelling studies.

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COSMO-BEP-Tree v1.0: a coupled urban climate model with explicit representation of street trees

10.5194/gmd-2019-220 ◽

2019 ◽

Author(s):

Gianluca Mussetti ◽

Dominik Brunner ◽

Stephan Henne ◽

Jonas Allegrini ◽

E. Scott Krayenhoff ◽

...

Keyword(s):

Air Temperature ◽

Climate Model ◽

Urban Climate ◽

Coupled Model ◽

Urban Canopy ◽

Climate Modelling ◽

Street Trees ◽

Night Time ◽

Effective Measure ◽

Weather And Climate

Abstract. Street trees are more and more regarded as an effective measure to reduce excessive heat in urban areas. However, the vast majority of mesoscale urban climate models do not represent street trees in an explicit manner and for example do not take the important effect of shading by trees into account. In addition, urban canopy models that take interactions of trees and urban fabrics directly into account are usually limited to the street or neighbourhood scale and, hence, cannot be used to analyse the citywide effect of urban greening. In order to represent the interactions between street trees, urban elements and the atmosphere in realistic regional weather and climate simulations, we coupled the vegetated urban canopy model BEP-Tree and the mesoscale weather and climate model COSMO. The performance and applicability of the coupled model, named COSMO-BEP-Tree, are demonstrated over the urban area of Basel, Switzerland, during the heatwave event of June–July 2015. Overall, the model compared well with measurements of individual components of the surface energy balance and with air and surface temperatures obtained from a flux tower, surface stations and satellites. Deficiencies were identified for night-time air temperature and humidity, which can mainly be traced back to limitations in the simulation of the night-time stable boundary layer in COSMO. The representation of street trees in the coupled model generally improved the agreement with observations. Street trees produced large changes in simulated sensible and latent heat flux, and wind speed. Within the canopy layer, the presence of street trees resulted in a slight reduction in daytime air temperature and a very minor increase in night-time air temperature. The model was found to realistically respond to changes in the parameters defining the street trees: leaf area density and stomatal conductance. Overall, COSMO-BEP-Tree demonstrated the potential of (a) enabling city-wide studies on the cooling potential of street trees and (b) further enhancing the modelling capabilities and performance in urban climate modelling studies.

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Evaluating the Urban Canopy Scheme TERRA_URB in the COSMO Model for Selected European Cities

10.5194/ems2021-303 ◽

2021 ◽

Author(s):

Valeria Garbero ◽

Massimo Milelli ◽

Francesca Bassani ◽

Edoardo Bucchignani ◽

Paola Mercogliano ◽

...

Keyword(s):

Air Temperature ◽

Weather Prediction ◽

Urban Climate ◽

Urban Canopy ◽

Anthropogenic Heat ◽

Climate Modelling ◽

Model Framework ◽

European Cities ◽

Cosmo Model ◽

Anthropogenic Heat Flux

Nowadays, cities are the preferred location for more than half of the human population and the places where major human-perceived climate change impacts occur. In an increasingly urbanized world, it is essential to represent such areas adequately in Numerical Weather Prediction (NWP) models, not only to correctly forecast air temperature, but also the human heat stress and the micro-climate phenomena induced by the cities. Among them, the best known is the Urban Heat Island (UHI) effect, which refers to the significantly higher temperatures experienced by a metropolitan area than its rural surroundings. Currently, the COSMO model employs a zero-order urban description, which is unable to correctly reproduce the UHI effect: cities are simply represented as natural lands with increased surface roughness length and reduced vegetation cover. However, the reproduction of the urban climate features in NWP and regional climate models is possible with the use of the so-called urban canopy models, that are able to parameterize the interaction between the urbanized surface and the overlying atmosphere. In this context, a new bulk parameterization scheme, TERRA_URB (TU), has been developed within the COSMO Consortium. TU offers an intrinsic representation of urban physics: the effect of buildings, streets and other man-made layers on the surface-atmosphere interaction is described by parameterizing the impervious water balance, translating the 3D urban-canopy parameters into bulk parameters with the Semi-empirical Urban canopy parameterization (SURY) and using the externally calculated anthropogenic heat flux as additional heat source. In this work, we present high-resolution simulations with the TU scheme, for different European cities, Turin, Naples and Moscow. An in-depth evaluation and verification of the performances of the recent COSMO version with TU scheme and new implemented physical parameterizations, such the ICON-like surface-layer turbulence scheme and the new formulation of the surface temperature, have been carried out. The validation concerned the 2-meter temperature and was performed for 1- or 2-week selected periods over the 3 European cities characterized by different environment and climate, namely the Moscow megacity in Russia and Turin and Naples in Italy. Even if the three domains are morphologically different, the results follow a common behavior. In particular, the activation of TERRA_URB provides a substantial improvement in capturing the UHI intensity and improving air temperature forecasts in urban areas. Potential benefits in the model performance also arise from a new turbulence scheme and the representation of skin-layer temperature (for vegetation). Our model framework provides promising perspectives for enhancing urban climate modelling, although further investigations are needed.

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Modelling the cooling potential of street trees at city-scale with COSMO-BEP-Tree

10.5194/egusphere-egu2020-19013 ◽

2020 ◽

Author(s):

Gianluca Mussetti ◽

Dominik Brunner ◽

Stephan Henne ◽

Scott Krayenhoff ◽

Jan Carmeliet

Keyword(s):

Thermal Comfort ◽

Air Temperature ◽

Current Knowledge ◽

Urban Climate ◽

Mitigation Strategies ◽

Climate Simulation ◽

Street Trees ◽

Near Surface ◽

Weather And Climate ◽

The Impact

Street trees are more and more regarded as a potential measure to mitigate the excessive heat in urban areas resulting from climate change and the urban heat island. However, the current knowledge of the cooling effect of street trees relies on studies at the micro-scale while potential interactions at the city-scale are yet to be understood. In fact, the vast majority of large-scale modelling studies only represent street trees outside the street canyon, neglecting important effects such as the shading and sheltering.In order to explicitly represent street trees in coupled urban climate simulation, the multi-layer urban canopy model BEP-Tree was coupled with the regional weather and climate model COSMO-CLM. The coupled model, named COSMO-BEP-Tree, enabled simulating the radiative, flow and energy interactions between street trees, canyon surfaces and the atmosphere during weather and climate simulations. In this study, COSMO-BEP-Tree is used to model the cooling potential of street trees during a heatwave event in Basel, Switzerland. The impact of street trees is explored in terms of near-surface air temperature and thermal comfort. The impact of greening scenarios is simulated and compared with other heat mitigation strategies.The results highlight contrasting urban climate effects of street trees during daytime and night-time, where different processes become dominant. The daytime cooling was primarily a local effect and proportional to the local density of street trees.&#160; In contrast, the impact was more widespread at night, where city-scale interactions become important. Beside air temperature, the model results suggest a significant impact of street trees on wind speed and canyon surface temperature. Owing to these effects, street trees produced a larger impact on thermal comfort than on air temperature. Finally, the need for further model development with respect to urban hydrology is outlined.

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Are detailed urban canopy parameters necessary for modelling the urban climate in Africa?

10.5194/egusphere-egu2020-17692 ◽

2020 ◽

Author(s):

Oscar Brousse ◽

Jonas Van de Walle ◽

Lien Arnalsteen ◽

Matthias Demuzere ◽

Wim Thiery ◽

...

Keyword(s):

Climate Model ◽

Urban Climate ◽

Urban Canopy ◽

Sub Saharan Africa ◽

Climate Modelling ◽

Local Climate ◽

African Cities ◽

Local Climate Zones ◽

The City

Local Climate Zones (LCZ) have now been widely accepted and used by the urban climate community (Ching et al., 2018). However, their use over Sub-Saharan Africa has still been limited because of data scarcity in the region. Brousse et al. (2019, 2020) demonstrated the added value of applying spatially variant urban canyon parameters derived from LCZ in the urban climate model TERRA_URB &#8211; embedded in the COSMO-CLM model. Despite its promising results, thermal and morphological parameters extracted out of the ranges proposed by Stewart and Oke (2012) are mostly derived from Western cities. Hence, uncertainties related to the use of unascertained urban forms and functions of African cities for urban climate modelling have not yet been evaluated.To quantify the sensitivity of the model to more representative urban canopy parameters of African cities, this study sets up a methodology for: (i) obtaining from in situ measurements archetypal parameters of LCZ classes for Kampala (Uganda); and (ii) simulating the potential effect of the newly defined urban structure on the local climate.In situ data were obtained during field work held in the summer months of 2018. A representative sample of 1300 measurement points was selected throughout the city of Kampala, for which both quantitative (road width, distance between houses, heights of buildings) and qualitatively estimated (vegetation fraction, road-wall-roof material) variables were collected.&#160; These variables enabled the development of an updated LCZ map of the city of Kampala.To evaluate the model&#8217;s sensitivity to the new spatially explicit urban morphological and thermal parameters, this new information was fed into the TERRA_URB scheme at a horizontal resolution of 1 km for a 3-months period (December 2017 &#8211; February 2018). The run was nested within a 12 km simulation forced by ERA-Interim reanalysis data. Results show tangible effects of the updated parameters on the 2-meter air temperature, land surface temperature and surface energy balance components. Still, no major improvements in model skill compared to the default LCZ framework proposed by Brousse et al. (2020) were found. [1]&#160;[WT2]&#160;This study is among the first studies to test the sensitivity of an urban climate model to more realistic urban parameters in Africa and aims at triggering more research to be done in the area with a variety of urban climate models.

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Advantages of using a fast urban canopy model as compared to a full mesoscale model to simulate the urban heat island of Barcelona

10.5194/gmd-2016-10 ◽

2016 ◽

Cited By ~ 3

Author(s):

M. García-Díez ◽

D. Lauwaet ◽

H. Hooyberghs ◽

J. Ballester ◽

K. De Ridder ◽

...

Keyword(s):

Simple Model ◽

Land Surface ◽

Climate Model ◽

Mesoscale Model ◽

Urban Climate ◽

Urban Canopy ◽

Forecast Model ◽

Reanalysis Data ◽

Urban Canopy Model ◽

Canopy Model

Abstract. As most of the population lives in urban environments, the simulation of the urban climate has become a key problem in the framework of the climate change impact assessment. However, the high computational power required by these simulations is a severe limitation. Here we present a study on the performance of a Urban Climate Model (UrbClim), designed to be several orders of magnitude faster than a full-fledge mesoscale model. The simulations are validated with station data and with land surface temperature observations retrieved by satellites. To explore the advantages of using a simple model like UrbClim, the results are compared with a simulation carried out with a state-of-the-art mesoscale model, the Weather Research and Forecasting model, using an Urban Canopy model. The effect of using different driving data is explored too, by using both relatively low resolution reanalysis data (70 km) and a higher resolution forecast model (15 km). The results show that, generally, the performance of the simple model is comparable to or better than the mesoscale model. The exception are the winds and the day-to-day correlation in the reanalysis driven run, but these problems disappear when taking the boundary conditions from the higher resolution forecast model.

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Implementation of an Urban Parameterization Scheme into the Regional Climate Model COSMO-CLM

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-0209.1 ◽

2013 ◽

Vol 52 (10) ◽

pp. 2296-2311 ◽

Cited By ~ 28

Author(s):

Kristina Trusilova ◽

Barbara Früh ◽

Susanne Brienen ◽

Andreas Walter ◽

Valéry Masson ◽

...

Keyword(s):

Spatial Resolution ◽

Climate Model ◽

Spatial Scales ◽

Regional Climate ◽

Coupled Model ◽

Urban Land ◽

Urban Land Use ◽

Small Scale ◽

Model Simulations ◽

Scale Modelling

AbstractAs the nonhydrostatic regional model of the Consortium for Small-Scale Modelling in Climate Mode (COSMO-CLM) is increasingly employed for studying the effects of urbanization on the environment, the authors extend its surface-layer parameterization by the Town Energy Budget (TEB) parameterization using the “tile approach” for a single urban class. The new implementation COSMO-CLM+TEB is used for a 1-yr reanalysis-driven simulation over Europe at a spatial resolution of 0.11° (~12 km) and over the area of Berlin at a spatial resolution of 0.025° (~2.8 km) for evaluating the new coupled model. The results on the coarse spatial resolution of 0.11° show that the standard and the new models provide 2-m temperature and daily precipitation fields that differ only slightly by from −0.1 to +0.2 K per season and ±0.1 mm day−1, respectively, with very similar statistical distributions. This indicates only a negligibly small effect of the urban parameterization on the model's climatology. Therefore, it is suggested that an urban parameterization may be omitted in model simulations on this scale. On the spatial resolution of 0.025° the model COSMO-CLM+TEB is able to better represent the magnitude of the urban heat island in Berlin than the standard model COSMO-CLM. This finding shows the importance of using the parameterization for urban land in the model simulations on fine spatial scales. It is also suggested that models could benefit from resolving multiple urban land use classes to better simulate the spatial variability of urban temperatures for large metropolitan areas on spatial scales below ~3 km.

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Modelling rain heterogeneities within an urban neighbourhood

10.5194/egusphere-egu21-7806 ◽

2021 ◽

Author(s):

Karolin S. Ferner ◽

K. Heinke Schlünzen ◽

Marita Boettcher

Keyword(s):

Wind Speed ◽

Urban Areas ◽

Climate Model ◽

Numerical Models ◽

Urban Climate ◽

Cloud Microphysics ◽

In Situ Measurements ◽

Small Scale ◽

Atmospheric Processes

Urbanisation locally modifies the regional climate: an urban climate develops. For example, the average wind speed in cities is reduced, while the gustiness is increased. Buildings induce vertical winds, which influence the falling of rain. All these processes lead to heterogeneous patterns of rain at ground and on building surfaces. The small-scale spatial rain heterogeneities may cause discomfort for people. Moreover, non-uniform wetting of buildings affects their hydrothermal performance and durability of their facades.Measuring rain heterogeneities between buildings is, however, nearly impossible. Building induced wind gusts negatively influence the representativeness of in-situ measurements, especially in densely urbanised areas. Weather radars are usually too coarse and, more importantly, require an unobstructed view over the domain and thus do not measure ground precipitation in urban areas. Consequently, researchers turn to numerical modelling in order to investigate small-scale precipitation heterogeneities between buildings.In building science, numerical models are used to investigate rain heterogeneities typically focussing on single buildings and vertical facades. Only few studies were performed for more than a single building or with inclusion of atmospheric processes such as radiation or condensation. In meteorology, increasing computational power now allows the use of small-scale obstacle-resolving models resolving atmospheric processes while covering neighbourhoods.In order to assess rain heterogeneities between buildings we extended the micro-scale and obstacle-resolving transport- and stream model MITRAS (Salim et al. 2019). The same cloud microphysics parameterisation as in its mesoscale sister model METRAS (Schl&#252;nzen et al., 2018) was applied and boundary conditions for cloud and rain water content at obstacle surfaces were introduced. MITRAS results are checked for plausibility using radar and in-situ measurements (Ferner et al., 2021). To our knowledge MITRAS is the first numerical urban climate model that includes rain and simulates corresponding processes.Model simulations were initialised for various wind speeds and mesoscale rain rates to assess their influence on the heterogeneity of falling rain in a domain of 1.9 x 1.7 km&#178; around Hamburg City Hall. We investigated how wind speed or mesoscale rain rate influence the precipitation patterns at ground and at roof level. Based on these results we assessed the height dependence of precipitation. First analyses show that higher buildings receive more rain on their roofs than lower buildings; the results will be presented in detail in our talk.Ferner, K.S., Boettcher, M., Schl&#252;nzen, K.H. (2021): Modelling the heterogeneity of rain in an urban neighbourhood. Publication in preparationSalim, M.H., Schl&#252;nzen, K.H., Grawe, D., Boettcher, M., Gierisch, A.M.U., Fock B.H. (2018): The microscale obstacle-resolving meteorological model MITRAS v2.0: model theory. Geosci. Model Dev., 11, 3427&#8211;3445, https://doi.org/10.5194/gmd-11-3427-2018.Schl&#252;nzen, K.H., Boettcher, M., Fock, B.H., Gierisch, A.M.U., Grawe, D., and Salim, M. (2018): Scientific Documentation of the Multiscale Model System M-SYS. Meteorological Institute, Universit&#228;t Hamburg. MEMI Technical Report 4

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Atmospheric Blocking and Mean Biases in Climate Models

Journal of Climate ◽

10.1175/2010jcli3728.1 ◽

2010 ◽

Vol 23 (23) ◽

pp. 6143-6152 ◽

Cited By ~ 134

Author(s):

Adam A. Scaife ◽

Tim Woollings ◽

Jeff Knight ◽

Gill Martin ◽

Tim Hinton

Keyword(s):

Climate Change ◽

Climate Models ◽

Climate Model ◽

Horizontal Resolution ◽

Small Scale ◽

Model Data ◽

Atmospheric Blocking ◽

Intergovernmental Panel ◽

Weather And Climate ◽

Main Culprit

Abstract Models often underestimate blocking in the Atlantic and Pacific basins and this can lead to errors in both weather and climate predictions. Horizontal resolution is often cited as the main culprit for blocking errors due to poorly resolved small-scale variability, the upscale effects of which help to maintain blocks. Although these processes are important for blocking, the authors show that much of the blocking error diagnosed using common methods of analysis and current climate models is directly attributable to the climatological bias of the model. This explains a large proportion of diagnosed blocking error in models used in the recent Intergovernmental Panel for Climate Change report. Furthermore, greatly improved statistics are obtained by diagnosing blocking using climate model data corrected to account for mean model biases. To the extent that mean biases may be corrected in low-resolution models, this suggests that such models may be able to generate greatly improved levels of atmospheric blocking.

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A systematic analysis of the performance of the IPSL-CM5A-LR model for decadal temperature predictions over Europe

10.5194/egusphere-egu2020-17561 ◽

2020 ◽

Author(s):

Giovanni Sgubin ◽

Didier Swingedouw ◽

Juliette Mignot ◽

Leonard Borchert ◽

Thomas Noël ◽

...

Keyword(s):

Air Temperature ◽

Large Scale ◽

Impact Analysis ◽

Climate Model ◽

Added Value ◽

Climate Projections ◽

Climate Modelling ◽

Adaptation Measures ◽

Windows Of Opportunity ◽

Skill Scores

Reliable climate predictions over a time-horizon of 1-10 year are crucial for stakeholders and policymakers, as it is the time span for relevant decisions of public and private for infrastructures and other business planning. This promoted, about a decade ago, the development of a new family of climate model: the Decadal Climate Predictions (DCP). Similarly to climate projections, the DCP consists in forced simulations of climate, but initialised from a specific observed climatic state, which potentially represents an added value. Being a relatively new branch of climate modelling the effective application of DCP to impact analysis supporting operational adaptation measures is still conditional on their evaluation.Here we contribute to this evaluation by exploring the performance of the IPSL-CM5A-LR DCP system in predicting the air temperature over Europe.&#160; Our assessment of the potentiality of the DCP system follows two main steps: (1) the comparison between the simulated large-scale air temperature from hindcasts and the observations from mid-1900 to present day, i.e. NOAA-20CR dataset, which defines a prediction skill, calculated through both the Anomaly Correlation Coefficient (ACC) and the Root Mean Square Error (RMSE); (2) the detection of the &#8220;windows of opportunity&#8221;, i.e. specific conditions under which the DCP performs better. The exploration of the windows of opportunity stems from a systematic detection that evaluates the DCP skills for each combination of periods, lead times and seasons. Our analysis involves both raw simulations and de-biased simulations, i.e. outputs data that have been adjusted through the quantile-quantile method.Our results evidence a significant added value over most of Europe with respect to non-initialised historical simulations.&#160; Significant skill scores have been generally found over the Mediterranean sector of Europe and UK, while the performance over the rest of Europe results rather conditional on the season and on the period considered. The best predicted months appear to be those between spring and autumn, while low skills have been found for winter months. Also, the predictions appear to be more performant after the &#8217;80, when a rapid warming signal characterised the temperature over Europe: this shift is well reproduced in the initialised simulations. Finally, skill anomalies between raw and debiased outputs are generally minimal. Nevertheless, debiased data show an overall higher RMSE skill, while ACC skill appears to be slightly higher in winter and slightly lower in summer. These findings may be useful for the exploitation of the IPSL DCP for near-term timescale impact analysis over Europe. Also, our systematic approach for the exploration of the windows of opportunity may be at the base of similar investigations applied to other DCP systems.

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Impact of Urban Canopy Parameters on a Megacity’s Modelled Thermal Environment

Atmosphere ◽

10.3390/atmos11121349 ◽

2020 ◽

Vol 11 (12) ◽

pp. 1349

Author(s):

Mikhail Varentsov ◽

Timofey Samsonov ◽

Matthias Demuzere

Keyword(s):

Urban Areas ◽

Climate Model ◽

Thermal Environment ◽

Weather Prediction ◽

Urban Canopy ◽

Anthropogenic Heat ◽

Climate Modelling ◽

Local Climate ◽

Anthropogenic Heat Flux ◽

Local Climate Zones

Urban canopy parameters (UCPs) are essential in order to accurately model the complex interplay between urban areas and their environment. This study compares three different approaches to define the UCPs for Moscow (Russia), using the COSMO numerical weather prediction and climate model coupled to TERRA_URB urban parameterization. In addition to the default urban description based on the global datasets and hard-coded constants (1), we present a protocol to define the required UCPs based on Local Climate Zones (LCZs) (2) and further compare it with a reference UCP dataset, assembled from OpenStreetMap data, recent global land cover data and other satellite imagery (3). The test simulations are conducted for contrasting summer and winter conditions and are evaluated against a dense network of in-situ observations. For the summer period, advanced approaches (2) and (3) show almost similar performance and provide noticeable improvements with respect to default urban description (1). Additional improvements are obtained when using spatially varying urban thermal parameters instead of the hard-coded constants. The LCZ-based approach worsens model performance for winter however, due to the underestimation of the anthropogenic heat flux (AHF). These results confirm the potential of LCZs in providing internationally consistent urban data for weather and climate modelling applications, as well as supplementing more comprehensive approaches. Yet our results also underline the continued need to improve the description of built-up and impervious areas and the AHF in urban parameterizations.

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