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
Cities over the world are expanding
During the past 3 decades, a vast amount of urban land-surface schemes
have been developed. They enable the convection-permitting atmospheric models
to resolve the heterogeneity of cities with applications for heat stress
assessment and the development of urban climate adaptation and mitigation
strategies
First, the complex schemes are hindered by the lack of urban canopy
parameters, which include information about three-dimensional urban
morphology and material properties. Detailed parameter inventories are
available for specific urban sites. On the one hand, they are suitable for
extensive offline evaluations of the urban land-surface schemes
Second, explicit-canyon schemes are computationally demanding compared to
bulk schemes. Complex schemes could lead up to 15 % of total
computational cost of an atmospheric model
This paper presents the Semi-empirical URban canopY-parametrization (SURY)
(Sect. It offers a translation of urban canopy parameters containing the
three-dimensional information into bulk parameters. The translation is
based on detailed observational studies, modelling experiments and available
parameter inventories. It brings canopy-dependent urban physics – which used to be reserved for the
explicit-canyon schemes – to existing urban bulk urban land-surface schemes
It preserves the low computation cost and low complexity of the bulk
schemes. It provides versatility in employing either urban canopy parameters from bottom-up inventories or bulk parameters from top-down estimates.
As a result, SURY bridges the gap between bulk schemes and explicit-canyon schemes by providing robust canopy-dependent urban physics and parameter versatility for convection-permitting atmospheric modelling at a low computational cost.
SURY is implemented in the COSMO(-CLM) model (Sect.
In this section, the SURY is
described. The translation of urban canopy parameters into urban bulk
parameters is based on the urban physical processes with regard to the ground
heat transfer, the surface-radiation exchanges and the surface-layer
turbulent transport for momentum, heat and moisture: the bulk thermal
parameter values take into account enhanced ground heat transport and storage
due to the increased contact surface with the atmosphere
The upper panel shows the urban canopy
parameters. They are taken as input for the SURY. The default urban canopy parameters correspond to the
recommended values for the medium urban category in
A new methodology is developed for translating the urban canopy parameters
into bulk (effective) thermal parameters for heat capacity and heat
conductivity. The latter is taken into account in the
slab representation, which considers the one-dimensional heat equation
of a vertical column commonly used in existing land-surface schemes. In the
methodology, the buildings and pavements are considered as massive
impermeable structures stacked on the natural soil. It takes into account the
three-dimensional surface curvature of the urban canopy, which results in a
larger contact surface with the atmosphere than a slab surface enhancing the
ground heat flux. As denoted by
In the case of an idealized urban canopy with parallel urban canyons,
straight roads and flat roofs, SAI can be obtained from geometrical
considerations:
A methodology is presented that simultaneously takes into account the bulk
surface thermal properties of the urban canopy (derived above) and those of
the natural soil below the urban canopy. Therefore, vertical profiles of the
bulk thermal parameters
An analogous formulation is considered for the vertical profile of the bulk
heat conductivity
The default urban canopy parameters (see also Table
The bulk surface thermal admittance is expressed as
It needs to be noted that the presented methodology above assumes a homogeneous surface temperature of the urban canopy. This is also case for the next section with regard to the surface radiation properties. Consequentially, the scheme does not explicitly represent the temperature variety among the different elements in the urban canopy resulting from shadowing and the heterogeneous thermal and radiative properties. Therefore, urban-physical processes resulting from such variety are not explicitly resolved. This choice was made for providing consistency with the bulk urban land-surface schemes employing bulk parameters.
In this section, the methodology for deriving the bulk (or effective) albedo
Instead of implementing a computationally demanding explicit-canyon radiation
scheme, an approximation for
This closely matches the numerical estimation with a maximal error of
The robustness of the Eqs. (
The default urban canopy parameters (see also Table
Following
As before, the default value for
The COSMO model
The ground heat and water transport and the representation of vegetation and
snow cover are resolved by the soil–vegetation–atmosphere transfer (SVAT)
module TERRA_ML
In the original COSMO(-CLM) model, cities are represented by natural land
surfaces with an increased surface roughness length and a reduced vegetation
cover. However, in this representation, urban areas are still treated as
water-permeable soil with aerodynamic, radiative and thermal parameters
similar to the surrounding natural land. Therefore, this basic representation
could not reliably capture the urban physics and associated urban-climatic
effects including urban heat islands. In order to tackle this issue, the bulk
scheme TERRA_URB
The COSMO(-CLM) model that implements SURY in its urban land-surface module
TERRA_URB v2.0 is set up for the reference simulation over Belgium; see
Fig.
Domain composite of the impervious surface area, vegetation cover and orography
(indicated with the shading) for the reference (REF) model setup of the COSMO-CLM model coupled to
TERRA_URB v2.0 at 2.8 km resolution over Belgium.
The arrows directed upwards indicate the locations of the in situ
observations located in the urban area of Antwerp (left; Royal Lyceum of
Antwerp) and in the rural area of Vremde (right; Organic Farm van
Leemputten). The arrows directed downwards indicate the locations of the
tower observations located at a flat industrial terrain in Zwijndrecht
(left arrow) of the Flemish Environmental Agency and at an rural area
(right arrow) of the Belgian Nuclear Research Center (SCK
Overview of parameter sensitivity
experiments. Seven couples of experiments (AL, AH, BL, BH, CL, CH, DL, DH,
EL, EH, FL, FH, FL, GH) are performed for which the default urban canopy
parameters are modified to the values in the low (L) and high (H) columns.
Except for the AHE, L and H correspond to the
minimum and maximum values of the urban canopy parameter ranges for the local
climate zones of compact low-rise and mid-rise defined in
In addition to the REF and STD setup described above, a range of
online-coupled sensitivity experiments are performed. Starting from REF
for each sensitivity simulation, the parameters for the urban canopy are
changed according to the minimum (low scenarios; L) and maximum values
(high scenarios; H) of the urban canopy parameter ranges derived from the
local climate zones of compact low-rise and mid-rise in
Modelled horizontal profiles of screen-level (top panels) and surface (bottom panels) temperatures at noon (left panels) and midnight (right panels), averaged for 21 July to 20 August 2012.
24 h running averages and mean diurnal
cycle for modelled (thick lines) and observed (OBS; blue stars) temperatures
during mid-summer (21 July to 20 August 2012) at the Royal Lyceum for
Antwerp (urban), the Organic Farm Van Leemputten (rural) and their
difference (the urban heat island effect of Antwerp). The simulation with the
COSMO-CLM model coupled to the standard land-surface module TERRA_ML without
urban parametrization is indicated with STD (black), whereas the reference
simulation with the COSMO-CLM model plus TERRA_URB v2.0 with urban
parametrization is indicated with REF (red). The dotted lines indicate the
range between the 16th and 84th percentile of the observed temperatures,
whereas the grey and light red areas indicate the ranges for the simulations STD
and REF, respectively. An overview of the canopy parameter sensitivity
simulations
(AL, AH, BL, BH, etc.) can be found in Table
The modelled screen-level air temperature and the associated CLUHI is
evaluated against in situ measurements for an urban and a rural site in
Antwerp. These were performed using platinum resistance thermometers supplied
by Campbell Scientific. The sensors were mounted in an actively ventilated
radiation shield (Young 43503) to reduce heating effects by radiation loading
on the sensor and stagnant air inside the shield. The sensor plus radiation
shield setups were deployed side by side during a test phase during 1 week
at the end of June 2012. The root mean square difference on the 15 min
temperature averages during this week was found lower than 0.04
As demonstrated recently by
In order to evaluate the nocturnal boundary-layer temperature and BLUHI in
the model, observations from two meteorological towers within the province of
Antwerp (Belgium) are used. The first tower of the Flemish Environmental
Agency (VMM) is 160 m high and located on an industrial site in Zwijndrecht
(geographical coordinates:
The averaged LST and screen-level temperatures for the day- and night-time from
the REF simulation during the summer evaluation period are shown in Fig.
Daily averages for modelled and observed
temperatures (unit: K) during mid-summer (21 July to 20 August 2012) at
the Royal Lyceum for Antwerp (urban), the Organic Farm Van Leemputten
(rural) and their difference (the urban heat island effect of Antwerp). Each
first row shows results of the observations. Each second row shows results
for COSMO-CLM model without urban parametrization (L column), for COSMO-CLM
plus TERRA_URB v2.0 (H column) and their absolute difference (
Idem Table
Idem Table
The model evaluation of the screen-level air temperature and the CLUHI for
Antwerp is displayed in Fig.
For the urban site, reference model REF agrees well with the observed
temperatures with a mean bias (MB) of
The CLUHI intensity (1.74 K), calculated from the observed difference
between the urban station and the rural station, is well reproduced by REF
(1.56 K) with a very good
The model is evaluated with LSTs derived from the MODIS satellite described
in Sect.
For the NU class, a negative bias of
The model results are evaluated with observations of the nocturnal
boundary-layer described in Sect.
Evaluation of modelled land-surface temperatures
against MODIS satellite observations. A distinction is made between four
urban classes: no urban (NU) with impervious surface area (ISA)
The REF simulation is capable of capturing the temperature profiles and the
variability of both towers. For the industrial site, the model profile
matches well that of the observations with a positive bias of 0.41 K.
A higher positive temperature bias is found
for the rural site (0.73 K), which generally stems from the temperature
overestimation near the ground. Therefore, the increasing temperature with
height (
Modelled and observed temperatures
(in K) vertically averaged for the nocturnal (0 h) tower profiles at the VMM
industrial site in Zwijndrecht and at the SCK
The model sensitivity experiment in response to the different urban input
parameters is performed by means of model-bias analysis. Therefore, the model
output and performance statistics in terms of the observed temperature
quantities (described in Sect.
Observed (stars) and modelled (lines)
nocturnal (0 h) vertical profiles for VMM industrial site in Zwijndrecht and
the SCK
With respect to the screen-level temperature and CLUHI intensity for Antwerp,
the sensitivity range is generally larger during the evening and during the
night when the CLUHI remains close to its maximum. The largest
sensitivity range for the diurnal cycle is found for the parameters
AHE and (to a smaller extent) the thermal parameters, which are the
surface heat conductivity and heat capacity. A medium sensitivity range
to the diurnal cycle is found for the building height, canyon height-to-width ratio and the
roof fraction. The overall lowest model sensitivity is found from the albedo, yet
at day-time, when overall sensitivity changes are the lowest, it is
higher than the sensitivity from the thermal parameters.
For the daily averaged CLUHI, the magnitudes of the different sensitivities are comparable.
A more detailed description of the
different parameter sensitivities is found below:
An increased AHE obviously leads to an increase in screen-level urban
temperatures and heat island intensity. Even though the AHE is higher
during the day, the sensitivity range from AHE is the largest during the
night because of the confinement in the nocturnal boundary layer A diurnal change in sign of the sensitivity is found for the thermal
parameters: lower thermal parameter values led to a temperature increase
during the day followed by a decrease during the night. This is due to the
fact that a smaller portion of excess heat is needed to heat up the urban
canopy during the day, hence leading to higher day-time temperatures. At the
same time, less excess heat buffering in the urban canopy occurs which
lowers the temperatures at night-time. The sign change results in a
relatively low sensitivity of the daily-mean temperature, even though the
day- and night-time sensitivities are relatively high. An overall decrease in day- and night-time CLUHI appears
from the decrease in building height. The consequential lower roughness
length (Eq. Both the increase in roof fraction and surface albedo lead to an
overall decrease in nocturnal and day-time UHI, because they both increase
effective albedo according to Eq. ( A lower canyon height-to-width ratio
Application outline of the SURY. The main application flow of SURY is indicated with full arrows, whereas optional application flows are indicated with dashed arrows.
The sensitivity results for LST sensitivity are consistent with the
sensitivity to the screen-level temperatures. For example, lower surface heat
conductivity or heat capacity leads to higher urban LSTs and SUHI at
day-time and lower urban LSTs and SUHI at night-time. However, the
hierarchy of sensitivity to LST and SUHI is different from that of the
screen-level temperature: the largest sensitivity range for the urban LST and
SUHI now relates to the thermal parameters and not to the change in AHE, which
now has a medium sensitivity range. This is explained by the fact that AHE is
considered as a heat source to the first atmospheric model layer (see
Appendix
Analysis of the model biases and Taylor plots for each of the temperature quantities (not shown) demonstrate that the model performance change for each of the parameter sensitivity runs is ambiguous and depends on the temperature quantity considered. On the one hand, parameter changes leading to a better performance in CLUHI and BLUHI sometimes lead to worse performance in terms of absolute temperatures. In particular, a decrease in the value of the thermal parameters leads to a lower positive model bias and better model performance in terms of absolute screen-level temperatures, but a larger negative bias and worse model performance in terms of CLUHI. On the other hand, the performance change between the SUHI and CLUHI may lead to a divergent behaviour as well: an overall improvement in the CLUHI (lower positive day-time bias; lower negative night-time bias) by increasing the value of the thermal parameters leads to an overall deterioration of the SUHI (higher day-time negative bias; higher night-time positive bias). Finally, the day- and night-time performance changes are also divergent. For example, increasing the albedo leads to an overall deteriorated performance in day-time LST and SUHI, but leads to an improved night-time performance.
SURY is developed for efficiently representing canopy-dependent urban physics in atmospheric models. The methodology bridges the gap between bulk and explicit-canyon schemes in atmospheric models. The urban canopy parameters are translated into bulk parameters. The latter can be easily taken into account in bulk urban land-surface schemes in existing atmospheric models. The urban canopy parameters as input for SURY include the canyon height-to-width ratio, the building height, the roof fraction, the short-wave albedo, thermal emissivity and the heat conductivity and heat capacity. The output parameters of SURY include bulk albedo, bulk emissivity, aerodynamic and thermal roughness length and vertical profiles of the bulk heat conductivity and heat capacity. The methodology delivers theoretical and empirically verified robustness that is based on detailed urban observational and modelling experiments. Additional model robustness has been provided by comparing existing bulk parameters from top-down estimates with those translated from bottom-up urban canopy parameter inventories.
The outline of SURY implemented in an atmospheric model system is given in
Fig. SURY allows to employ detailed bottom-up data sets representing the
variation in residential, commercial and industrial areas, as soon as they
are available from WUDAPT or any other newly available data set. Still, one can fall back on the
bulk parameters when the detailed information is missing. Such a parameter
versatility enhances the overall applicability of the bulk land-surface
schemes. It also enables the analysis of the propagation of uncertainty in
the input parameters by comparing simulations using bulk parameter
estimates with those using urban canopy parameter data sets. SURY v1.0 enables the comparison and consolidation
between bottom-up urban canopy parameter data sets (translating them to
bulk parameters) and top-down bulk parameter data sets. This provides a way to
verify consistency of the parameter data sets. It should be noted that such a
parameter consolidation has been done in Sect. SURY combined with a bulk urban land-surface parametrization is
beneficial for efficient convection-permitting atmospheric modelling
applications. In particular, the bulk albedo approximation avoids explicit
numerical computation of the complex canyon radiation trapping, hence largely
reduces the computational demand compared to other explicit-canyon radiation
models. In case of the COSMO(-CLM) model, one only measures a computational
overhead of 7 % over the original COSMO(-CLM) model without urban
land-surface parametrization. The majority of the computational overhead
stems from the implementation of the tile approach in TERRA_URB and the
overhead from SURY itself is negligible. As SURY translates urban canopy parameters into bulk parameters, it can be
easily applied for intrinsic implementation of urban physical processes and
their dependency on urban canopy parameters in existing atmospheric models
already employing a bulk urban land-surface scheme.
An intrinsic implementation instead of an external urban land-surface
parametrization preserves consistency between the representation of the
different physical processes and features in urban environments on the one
hand and those of natural environments on the other hand.
Therefore, it is assured that the contrasts in model response
between urban areas and natural areas only stems from the differential
land-surface parameter values. In this way, artificial discrepancies
that arise from possible different formulations between an external
land-surface module resolving the urban areas and an internal
land-surface module resolving the natural areas are
avoided. Furthermore, it allows for the transparent application of intrinsic features
of the host atmospheric model in the urban-physics modelling, such as the
representation of vegetation (shading) in the urban canopy. In the
case of the COSMO(-CLM) model, these features include the multi-layer snow
representation and the TKE-based surface-layer turbulent transfer scheme.
SURY is evaluated in online mode with the COSMO(-CLM) model. To this end, the COSMO(-CLM) model is extended with the bulk urban land-surface scheme TERRA_URB v2.0, which allows for taking urban bulk parameters from SURY v1.0 into account. An online model evaluation over the Belgian urban extent during summer 2012 demonstrates that the model is capable of capturing urban climate characteristics. The model captures well the daily and diurnal variability of the UHIs in terms of land-surface temperatures, screen-level temperatures and nocturnal boundary-layer temperatures. Therefore, most of the negative temperature biases occurring for the urban areas in the original COSMO(-CLM) model without urban parametrization are alleviated.
Although TERRA_URB v2.0 implementing SURY v1.0 offers a general model
improvement with regard to urban temperatures and urban heat islands, it
could not alleviate other systematic errors in the COSMO(-CLM) model. Such
systematic errors include an overall underestimation of the diurnal cycle
of absolute temperatures, particularly an overestimation of the nocturnal
temperatures. This is in agreement with previous evaluations (regarding
summer) of the COSMO-CLM model
The model sensitivity is investigated for which SURY takes urban canopy
parameter ranges of the local climate zones of compact low-rise and
compact mid-rise in
The following recommendations are made with regard to future urban-climate research:
To date, limitations in either accuracy, detail, variety or coverage exist in
urban canopy parameter inventories. The aforementioned city-scale model
sensitivity on the urban canopy parameter uncertainty indicate that climate
modulations are expected from city heterogeneity. Therefore, advancements in
detailed parameter databases that represent the urban canopy variation in
residential, commercial and industrial areas support more reliable urban
climate modelling and numerical weather prediction systems at the convection
permitting scales. This is further supported by the findings from the model
intercomparison project of Peer-based networks that facilitate the deployment of the
spatially detailed parameter databases have great potential for more precise
urban climate modelling. Particularly, such a framework is provided by the
World Urban Database and Access Portal Tools ( As SURY allows for verifying consistency between urban canopy parameters
and bulk parameters, its application is recommended in the WUDAPT
framework. In turn, this allows urban-climate research for more precise
climate assessment. Moreover, it will lead to more consistency in the
comparison of bulk schemes with explicit-canyon schemes in future urban
model intercomparison projects. The model performance largely depends on the temperature quantity considered. In
particular, parameter settings leading to better UHI sometimes lead to
worse absolute temperatures and vice versa, which is also the case for
day-time temperatures vs. night-time temperatures, and land-surface
temperatures vs. air temperatures. This ambiguity demonstrates that a
multi-variable model evaluation is a requirement for improving and
comparing urban-climate modelling strategies. Some of the aforementioned model errors exceed the model
sensitivity range with regard to the urban canopy parameter uncertainty. This
demonstrates that the majority of the model uncertainty may not be related to
urban canopy parameter uncertainty, but may result from deficiencies in the
land-surface module and other aspects of the coupled atmospheric model.
Such systematic errors may also cause the ambiguity in model
performance and its sensitivity to the urban parameters.
In addition to the advancements of urban canopy parametrizations and the
expansion of more detailed parameter databases, ongoing improvements in
atmospheric modelling systems are also essential for more precise
urban-climate modelling assessment. Regarding the representation of urban
heat islands, focus should be given to those components that improve the
representation of the surface fields and boundary-layer characteristics,
such as the stability of the nocturnal temperature profiles. In view of the advantages listed above, consideration of employing SURY is
recommended for numerical weather prediction and long-term regional climate
modelling applications at the convection-permitting scales. Besides the
presented implementation in the COSMO-CLM model, this can also be achieved by
applying SURY in other existing urban bulk land-surface schemes for intrinsic
implementation in atmospheric models. Herein, it should be kept in mind that
SURY's semi-explicit nature implies some limitations with respect to complex
urban physical processes in an urban environment.
Particularly, the heterogeneity of the urban canopy induces micro-scale dynamic and physical
processes in the urban canopy, such as shadowing, buoyancy flows and the
complex inner-building heat and moisture transfer. As SURY does not resolve
the full heterogeneity, the propagating micro-scale features – such as
heterogeneous temperatures patterns at the street level and canyon wind gusts
– are not represented. In case there is need for a more detailed urban-climate
impact assessment that explicitly accounts for such features, one requires
more detailed urban-physics modelling with higher complexity. They include
the more explicit radiation schemes allowing heterogeneous temperatures
between sun-lit and shaded facets
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. They allow for more precise urban weather forecasting and assessment of climate change, mitigation and adaptation at the scales of cities.
SURY is provided as a documented Python module
This appendix describes TERRA_URB v2.0, the bulk urban
land-surface scheme of the COSMO(-CLM) model. Modifications to the
surface-layer turbulent transport scheme of the COSMO(-CLM) model, the
modified surface evaporation and transpiration, the anthropogenic heat
emission, the tile approach and the additional surface input parameters are
successively given in the subsections below. Bulk parameters are calculated
from the urban canopy parameters with the SURY described in Sect.
In contrast to its previous version employing the
similarity-based turbulent transfer scheme of
In contrast to its previous version only considering the water on the
impervious surfaces, TERRA_URB v2.0 is also capable of explicitly
representing the water-permeable surfaces (bare soil), vegetation and snow in
the urban canopy. The evapotranspiration is obtained in a similar way as
the natural land in the standard soil module TERRA_ML
In addition to the standard surface module TERRA_ML, the evaporation from
the water storage
The evaporation from the water storage
The evaporative area fraction
The amount of water
Default values for
TERRA_URB accounts for AHE from human
activity, which includes the energy dissipation from combustion and
electricity consumption. It originates from heating and cooling (such as air
conditioning) of buildings and traffic, but also from domestic, industrial
and agricultural activity
TERRA_URB makes a distinction between the urban canopy and natural land cover. This is done for each grid cell with a tile approach. Herein TERRA_URB is called twice, once for the urban canopy and once for the natural land cover specifying a different set of bulk parameters. On the one hand, the surface input parameters for the urban canopy are obtained from urban canopy parameters with SURY. On the other hand, surface input parameters for the natural land cover are provided by standard input parameters of the COSMO(-CLM) model. In this way, the ground heat and moisture transport and land–atmosphere exchanges in terms turbulent transport of momentum, heat and moisture are determined separately for each tile. The coupling to the atmospheric model is achieved by weighting each of the land–atmosphere fluxes according to the fractions of the urban canopy and natural land cover. The radiation exchanges are determined by grid cell averaged value of albedo and emissivity, which is weighted according to the respective tile fraction.
In addition to the land-surface parameters for the standard COSMO(-CLM) model
without urban land-surface parametrization described in
Sect.
The ISA field is obtained from the European soil sealing data set
representative for the year 2006 of the European Environmental Agency at
100 m resolution
The AHF field is obtained from the global data set of
The work described in this paper has received funding from the Belgian Science Policy Office through its Science for a Sustainable Development Programme under contracts SD/CS/041/MACCBET and BR/143/A2/CORDEX.be. It has also received funding from the Flemish regional government through a contract as an FWO (Fund for Scientific Research) post-doctoral position. The computational resources and services used in this work were also provided by the Hercules Foundation and the Flemish Government (Department of Economics, Sciences and Innovation – EWI). Additional assistance of resources was provided at the NCI National Facility systems at the Australian National University through the National Computational Merit Allocation Scheme supported by the Australian Government. We would like to thank Gianluca Mussetti (Swiss Federal Laboratories for Materials Science and Technology – EMPA) and Johan Zürger (Austrian Institute of Technology – AIT) for testing TERRA_URB for regional-climate modelling over Zürich and Vienna. We also acknowledge Jürgen Helmert and Burkhardt Rockel for providing support in extending the EXTPAR input parameter tool, and the COSMO consortium and CLM community for their support. Finally, we wish to thank Chunlei Meng, Yi-Ying Chen and the other reviewers for their insightful suggestions to the manuscript. Edited by: M.-H. Lo Reviewed by: C. Meng, Y.-Y. Chen, and three anonymous referees