A comprehensive indoor-outdoor urban climate model with hydrology: The Vertical City Weather Generator (VCWG v2.0.0)

2021 ◽  
pp. 108406
Author(s):  
Mohsen Moradi ◽  
E. Scott Krayenhoff ◽  
Amir A. Aliabadi
2016 ◽  
Author(s):  
M. García-Díez ◽  
D. Lauwaet ◽  
H. Hooyberghs ◽  
J. Ballester ◽  
K. De Ridder ◽  
...  

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.


2021 ◽  
Author(s):  
Karolin S. Ferner ◽  
K. Heinke Schlünzen ◽  
Marita Boettcher

<p>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.</p><p>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.</p><p>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.</p><p>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 (Schlünzen 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.</p><p>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 km² 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.</p><p>Ferner, K.S., Boettcher, M., Schlünzen, K.H. (2021): Modelling the heterogeneity of rain in an urban neighbourhood. Publication in preparation</p><p>Salim, M.H., Schlünzen, 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, 3427–3445, https://doi.org/10.5194/gmd-11-3427-2018.</p><p>Schlünzen, 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, Universität Hamburg. MEMI Technical Report 4</p>


2021 ◽  
Author(s):  
Antonina Kriuger ◽  
Alexander Reinbold ◽  
Martina Schubert-Frisius ◽  
Jörg Cortekar

<p>Cities are particularly vulnerable to climate change. At the same time, cities change slowly. Accordingly, preparatory measures to adapt to climate change have to be taken urgently. High-performance urban climate models with various applications can form the basis for prospective planning decisions, however, as of today no such model exists that can be easily applied outside of the scientific community. Therefore, the funding program Urban Climate Under Change [UC]<sup>2</sup> aims to further develop the new urban climate model PALM-4U (Parallelized Large-Eddy Simulation Model for Urban Applications) into a practice-oriented and user-friendly product that meets the needs of municipalities and other practical users in addition to scientific research.</p><p>Specifically, the high-performance model PALM-4U allows simulation of entire large cities comprising the area over 1.000 km<sup>2</sup> with a grid size of down to few meters. One of our goals within the project ProPolis is to design and test the practical implementation of PALM-4U in standard and innovative application fields which include thermal comfort (indices like PT, PET, UTCI), cold air balance (source areas, reach and others), local wind comfort (indices derived from medium winds and gusts) as well as dispersion of pollutants.</p><p>In close cooperation with our practice partners, we explore the potential of PALM-4U to support the urban planning processes in each specific application setting. Additionally, with development of the fit for purpose graphic user interface, manuals and trainings we aim to enable practitioners to apply the model for their individual planning questions and adaptation measures.</p><p>In our presentation, we will show an application case of PALM-4U in a major German city. We will investigate the effect of a planned development area on the local climate and the impact of different climate change adaptation measures (such as extensive vs. intensive green roofs). The comparative simulations of the current state and planning scenarios with integrated green and blue infrastructure should provide arguments for the municipal decision making in consideration of climate change aspects in a densely built-up environment, e.g. urban heat stress.</p>


2019 ◽  
Vol 28 (2) ◽  
pp. 105-119 ◽  
Author(s):  
Björn Maronga ◽  
Günter Gross ◽  
Siegfried Raasch ◽  
Sabine Banzhaf ◽  
Renate Forkel ◽  
...  

2016 ◽  
Vol 29 (5) ◽  
pp. 1605-1615 ◽  
Author(s):  
Jan Rajczak ◽  
Sven Kotlarski ◽  
Christoph Schär

Abstract Climate impact studies constitute the basis for the formulation of adaptation strategies. Usually such assessments apply statistically postprocessed output of climate model projections to force impact models. Increasingly, time series with daily resolution are used, which require high consistency, for instance with respect to transition probabilities (TPs) between wet and dry days and spell durations. However, both climate models and commonly applied statistical tools have considerable uncertainties and drawbacks. This paper compares the ability of 1) raw regional climate model (RCM) output, 2) bias-corrected RCM output, and 3) a conventional weather generator (WG) that has been calibrated to match observed TPs to simulate the sequence of dry, wet, and very wet days at a set of long-term weather stations across Switzerland. The study finds systematic biases in TPs and spell lengths for raw RCM output, but a substantial improvement after bias correction using the deterministic quantile mapping technique. For the region considered, bias-corrected climate model output agrees well with observations in terms of TPs as well as dry and wet spell durations. For the majority of cases (models and stations) bias-corrected climate model output is similar in skill to a simple Markov chain stochastic weather generator. There is strong evidence that bias-corrected climate model simulations capture the atmospheric event sequence more realistically than a simple WG.


2021 ◽  
Author(s):  
Qifen Yuan ◽  
Thordis L. Thorarinsdottir ◽  
Stein Beldring ◽  
Wai Kwok Wong ◽  
Chong-Yu Xu

Abstract. Climate change impact assessment related to floods, infrastructure networks and water resources management applications requires realistic simulations of high-resolution gridded precipitation series under a future climate. This paper proposes to produce such simulations by combining a weather generator for high-resolution gridded daily precipitation, trained on historical observation-based gridded data product, with coarser scale climate change information obtained using a regional climate model. The climate change information can be added to various components of the weather generator, related to both the probability of precipitation as well as the amount of precipitation on wet days. The information is added in a transparent manner, allowing for an assessment of the plausibility of the added information. In a case study of nine hydrological catchments in central Norway with the study areas covering 1000–5500 km2, daily simulations are obtained on a 1 km grid for a period of 19 years. The method yields simulations with realistic temporal and spatial structures and outperforms empirical quantile delta mapping in terms of marginal performance.


2013 ◽  
Vol 10 (6) ◽  
pp. 7857-7896 ◽  
Author(s):  
M. T. Taye ◽  
P. Willems

Abstract. Methods from two statistical downscaling categories were used to investigate the impact of climate change on high rainfall and flow extremes of the upper Blue Nile basin. The main downscaling differences considered were on the rainfall variable while a generally similar method was applied for temperature. The applied downscaling methods are a stochastic weather generator, LARS-WG, and an advanced change factor method, the Quantile Perturbation Method (QPM). These were applied on 10 GCM runs and two emission scenarios (A1B and B1). The downscaled rainfall and evapotranspiration were input into a calibrated and validated lumped conceptual model. The future simulations were conducted for 2050s and 2090s horizon and were compared with 1980–2000 control period. From the results all downscaling methods agree in projecting increase in temperature for both periods. Nevertheless, the change signal on the rainfall was dependent on the climate model and the downscaling method applied. LARS weather generator was good for monthly statistics although caution has to be taken when it is applied for impact analysis dealing with extremes, as it showed a deviation from the extreme value distribution's tail shape. Contrary, the QPM method was good for extreme cases but only for good quality daily climate model data. The study showed the choice of downscaling method is an important factor to be considered and results based on one downscaling method may not give the full picture. Regardless, the projections on the extreme high flows and the mean main rainy season flow mostly showed a decreasing change signal for both periods. This is either by decreasing rainfall or increasing evapotranspiration depending on the downscaling method.


2019 ◽  
Vol 201 ◽  
pp. 53-69 ◽  
Author(s):  
Anita Bokwa ◽  
Jan Geletič ◽  
Michal Lehnert ◽  
Maja Žuvela-Aloise ◽  
Brigitta Hollósi ◽  
...  

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