Mesoscale Climate Model Research Articles

Impacts of land use on climate in the Taihu Basin based on WRF model

The impacts of land use on the climate in the Taihu Basin were quantitatively simulated using the mesoscale climate model named Weather Research and Forecasting (WRF) model. Results showed that (1) cities with large or increasing areas of construction land had considerably higher temperature increases than other regions; (2) coastal cities to the east of the Taihu Basin, such as Shanghai, Suzhou, Jiaxing, and Taizhou had the highest wind speeds, while cities far from the coast to the west, such as Nanjing, Hangzhou, and Huzhou, experienced reduced wind speeds; The main wind direction over the Taihu Lake was southeast, with an increase in wind speed variation, but wind speeds decreased in 2019; (3) Areas near water or with large water areas had lower temperatures, while areas near forests or construction sites had higher temperatures. Although the area of construction land increased as cities developed, the increase in temperature was not significant; (4) As urbanization accelerated, temperature differences in some areas gradually decreased, and overall temperatures increased. As urban development reached a certain level, the impact of increased construction land on temperature gradually decreased, but the region exhibited an overall high temperature, leading to a reduction in the urban heat island effect.

Urban Wind Corridors Analysis via Network Theory

We develop a new model for urban wind corridors analysis and detection of urban wind ventilation potential based on concepts and principles of network theory. Our approach is based solely on data extracted from spatial urban features that are easily obtained from a 3D model of the city. Once the spatial features have been extracted, we embed them onto a graph topology. This allows us to use theories and techniques of network theory, and in particular graph theory. Utilizing such techniques, we perform end-to-end network flow analysis of the wind potential across the city and, in particular, estimate the locations, strengths, and paths of the wind corridors. To calibrate our model, we use a dataset generated by a meso-scale climate model and estimate the model parameters by projecting the wind vector field of the climate model onto a graph, thus providing a meaningful comparison of the two models under a new metric. We illustrate our modeling approach on the city of Singapore and explain how the results are useful for climate-informed urban design.

The impact of a shadows scheme on a Mars mesoscale climate model

Latitude and topography affect the amount of shadow cast on a landscape, which in turn can influence where water, ice or snow are stable. For martian climate models, whose output sometimes disagrees with observational data, we show that adding the ability to represent shadows generated by topography and understanding how they interact with relevant modelled variables can be important. We included a shadows scheme in a Mars mesoscale climate model and report on the impact that shadows had on surface temperature, and the resultant impact on one variable – surface water ice, and its accumulation or ablation in the study area of Lyot crater. Incorporating a scheme simulating shadows cast by topographical features had a measurable effect, increasing by up to 83% the amount of surface ice that the model predicted would be found in shadowed areas. The largest differences in ice content between simulations with and without shadows were found in those areas with the greatest amount of shadow.

Influence of Thermal Air Pollution on the Urban Climate (Estimates Using the COSMO-CLM Model)

It is well known that large cities and urban agglomerations not only make a decisive contribution to the growth of greenhouse gases in the atmosphere, but also significantly shape their own climate by transforming the underlying surface of urban areas, as well as thermal, gas and aerosol pollution of the urban boundary layer of the atmosphere. The most powerful manifestation of the city’s influence on local and regional climate processes is the thermal pollution of the atmosphere created by anthropogenic heat fluxes forming primarily due to the energy consumption of the urban economy. This paper summarizes the results of the work of the authors on numerical modeling of the influence of anthropogenic heat fluxes (thermal pollution of the urban atmosphere) on the climatic characteristics of urban agglomerations using the COSMO-CLM mesoscale climate model. The work was carried out as part of the Analysis of an impact of the regional climate change on the residential and commercial energy consumption of Russian megacities project of the Russian Science Foundation.

On the winter overcooling penalty of super cool photonic materials in cities

Daytime radiative coolers appear to be the most triumphant and promising technology for urban thermal management, as they could improve the thermal field of the cities, especially during the summertime. However, during the colder months, it can lead to an overcooling penalty, a widely overlooked phenomenon. This study aims to determine the cooling penalty derived from using super-cool materials (SCMs) at a city scale. We used a mesoscale urban modeling system to assess the overcooling of three broadband SCM emitters with different reflectivity and emissivity values. A significant change was found in radiation and energy balance compared to the control case (CTRL) during the daytime and nighttime. Under the most reflective and emissive SCM scenario, the maximum decrease of net radiation at peak hour was 354.9 Wm−2, therefore choosing a scenario with lower albedo values for walls and ground would be more beneficial. The mean decrease of ambient temperature, surface temperature, roof temperature and canopy were 2.8 °C, 4.7 °C, 12.9 °C and 6 °C, respectively. This SCMs assessment is a first stride to understand better the unexplored behavior of the boundary layer meteorology and its depiction in the mesoscale climate model for winter seasons. The implementation of SCMs during winter could create an inversion layer near the surface, leading to a buildup of stagnant air over the urban environment, resulting in heating during the night in the winter seasons as usual with SCMs as with the CTRL. Further research is needed on material development to modulate materials’ spectral configuration to address overcooling during the winter and improve SCMs’ year-round performance at city scale.

Modeling Seasonal Variation in Urban Weather in Sub-Tropical Region of Delhi

Complexity and heterogeneity of urban areas lead to difficulty in urban weather simulations and climate modeling. Diversity and size of urban areas necessitate to downscale global climate models to urban scale (~ hundreds of meters) and to enhance urban parameterization in the models to realistically simulate urban weather conditions. Hence, in this study, a methodology has been developed to generate multi-class urban land use land cover (LULC) by employing Resourcesat-2 LISS IV data. Weather Research and Forecast (WRF) model which is also a mesoscale numerical weather prediction and regional climate model was utilized to downscale the meteorological parameters up to 0.5 km grid resolution. Multi-class urban LULC prepared with improved urban parameters and updated Land Surface Parameters (LSPs) was ingested in model for Delhi to evaluate the model performance in three dominant seasons, i.e., summer, monsoon and winter. Evaluation of model performance with ground observation data revealed that multi-class urban LULC along with updated LSPs provided improved RMSE values of 2.31° C, 1.79 m/s and 0.94 mbar as compared to ingestion of multi-class urban LULC only (RMSE values of 3.42° C, 3.72 m/s and 1.58 mbar) for temperature at 2 m, wind speed and surface pressure, respectively. Temperature is found to be highest in summer season (38.58° C) and lowest in winter season while relative humidity is highest in monsoon season (~ 88%) and lowest in summer season (~ 30%). The study highlights the importance of ingestion of updated LSPs along with updated multi-class urban LULC for enhanced model performance.

Integration of a Building Energy Model in an Urban Climate Model and its Application

We report the ability of an urban canopy model, coupled with a regional climate model, to simulate energy fluxes, the intra-urban variability of air temperature, urban-heat-island characteristics, indoor temperature variation, as well as anthropogenic heat emissions, in Berlin, Germany. A building energy model is implemented into the Double Canyon Effect Parametrization, which is coupled with the mesoscale climate model COSMO-CLM (COnsortium for Small-scale MOdelling in CLimate Mode) and takes into account heat generation within buildings and calculates the heat transfer between buildings and the urban atmosphere. The enhanced coupled urban model is applied in two simulations of 24-day duration for a winter and a summer period in 2018 in Berlin, using downscaled reanalysis data to a final grid spacing of 1 km. Model results are evaluated with observations of radiative and turbulent energy fluxes, 2-m air temperature, and indoor air temperature. The evaluation indicates that the improved model reproduces the diurnal characteristics of the observed turbulent heat fluxes, and considerably improves the simulated 2-m air temperature and urban heat island in winter, compared with the simulation without the building energy model. Our set-up also estimates the spatio–temporal variation of wintertime energy consumption due to heating with canyon geometry. The potential to save energy due to the urban heat island only becomes evident when comparing a suburban site with an urban site after applying the same grid-cell values for building and street widths. In summer, the model realistically reproduces the indoor air temperature and its temporal variation.

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

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

A one-dimensional model of turbulent flow through “urban” canopies (MLUCM v2.0): updates based on large-eddy simulation

Abstract. In mesoscale climate models, urban canopy flow is typically parameterized in terms of the horizontally averaged (1-D) flow and scalar transport, and these parameterizations can be informed by computational fluid dynamics (CFD) simulations of the urban climate at the microscale. Reynolds averaged Navier–Stokes simulation (RANS) models have previously been employed to derive vertical profiles of turbulent length scale and drag coefficient for such parameterization. However, there is substantial evidence that RANS models fall short in accurately representing turbulent flow fields in the urban roughness sublayer. When compared with more accurate flow modeling such as large-eddy simulations (LES), we observed that vertical profiles of turbulent kinetic energy and associated turbulent length scales obtained from RANS models are substantially smaller specifically in the urban canopy. Accordingly, using LES results, we revisited the urban canopy parameterizations employed in the one-dimensional model of turbulent flow through urban areas and updated the parameterization of turbulent length scale and drag coefficient. Additionally, we included the parameterization of the dispersive stress, previously neglected in the 1-D column model. For this objective, the PArallelized Large-Eddy Simulation Model (PALM) is used and a series of simulations in an idealized urban configuration with aligned and staggered arrays are considered. The plan area density (λp) is varied from 0.0625 to 0.44 to span a wide range of urban density (from sparsely developed to compact midrise neighborhoods, respectively). In order to ensure the accuracy of the simulation results, we rigorously evaluated the PALM results by comparing the vertical profiles of turbulent kinetic energy and Reynolds stresses with wind tunnel measurements, as well as other available LES and direct numerical simulation (DNS) studies. After implementing the updated drag coefficients and turbulent length scales in the 1-D model of urban canopy flow, we evaluated the results by (a) testing the 1-D model against the original LES results and demonstrating the differences in predictions between new (derived from LES) and old (derived from RANS) versions of the 1-D model, and (b) testing the 1-D model against LES results for a test case with realistic geometries. Results suggest a more accurate prediction of vertical turbulent exchange in urban canopies, which can consequently lead to an improved prediction of urban heat and pollutant dispersion at the mesoscale.

Modeling the relationship between the urban development and subsurface warming in seven Asian megacities

The authors used a mesoscale climate model, CSU-MM and digital land-use data from seven Asian megacities to simulate ground surface temperature (Tsfc) related to urbanization for three discrete years of the 20th century. The variability of Tsfc was compared with the measured vertical profiles of subsurface temperature in the targeted megacities, which were expected to record the historical time-series of Tsfc. Considering a calm and clear day of the hottest season, results showed that Tsfc increased about 1.1 K 100 y−1 during the 20th century. Considering the seasonal climate variability, simulations were run for three additional cases (rainy day in the hottest season; clear day and rainy day in the coldest or rainy season) for each year in each megacity. The difference between the rates of change of Tsfc in Bangkok (0.9 K 100 y−1) and Tokyo (1.9 K 100 y−1) is considerable, which suggests that the differences of annual climatic variability are important for the analyses of urban subsurface warming. The authors conclude historical digital land-use data are useful to study past urban climate change in numerical simulation, and difference of annual climatic variability brings the difference of subsurface warming in each megacity.

The application of high-resolution atmospheric modelling to weather and climate variability in vineyard regions

<p>Grapevines are highly sensitive to environmental conditions, with variability in weather and climate (particularly temperature) having a significant influence on wine quality, quantity and style. Improved knowledge of spatial and temporal variations in climate and their impact on grapevine response allows better decision-making to help maintain a sustainable wine industry in the context of medium to long term climate change. This paper describes recent research into the application of mesoscale weather and climate models that aims to improve our understanding of climate variability at high spatial (1 km and less) and temporal (hourly) resolution within vineyard regions of varying terrain complexity. The Weather Research and Forecasting (WRF) model has been used to simulate the weather and climate in the complex terrain of the Marlborough region of New Zealand. The performance of the WRF model in reproducing the temperature variability across vineyard regions is assessed through comparison with automatic weather stations. Coupling the atmospheric model with bioclimatic indices and phenological models (e.g. Huglin, cool nights, Grapevine Flowering Véraison model) also provides useful insights into grapevine response to spatial variability of climate during the growing season, as well as assessment of spatial variability in the optimal climate conditions for specific grape varieties.</p>

UrbClim – A fast urban boundary layer climate model

We present a new urban climate model, further referred to as UrbClim, designed to cover agglomeration-scale domains at a spatial resolution of a few hundred metres. This model is composed of a land surface scheme containing simple urban physics, coupled to a 3-D atmospheric boundary layer module. In the land surface scheme, urban terrain is represented as an impermeable slab with appropriate parameter values for albedo, emissivity, and aerodynamic and thermal roughness length, and accounting for anthropogenic heat fluxes. The UrbClim model is subject to several validation exercises, using observations from Toulouse (France), Ghent and Antwerp (Belgium), and Bilbao (Spain), and considering turbulent energy fluxes, wind speed, and urban–rural temperatures. Despite its simplicity, UrbClim is found to be of the same level of accuracy than more sophisticated models, including for the complex terrain characterizing the Bilbao area. At the same time, it is faster than high-resolution mesoscale climate models by at least two orders of magnitude. Because of that, the model is well suited for long time integrations, in particular for applications in urban climate projections.

Evaluation of the coupled COSMO‐CLM/DCEP model with observations from BUBBLE

AbstractThe urban canopy scheme DCEP coupled with the mesoscale climate model COSMO‐CLM is evaluated extensively against data from the Basel Urban Boundary Layer Experiment (BUBBLE) for the period 20 June 2002 to 10 July 2002. The urban canopy parameters required for this purpose are based on a 3D building dataset of the canton of Basel‐Stadt (Switzerland) and land‐use data for Basel and its surroundings. The simulated radiative and energy fluxes as well as near‐surface air temperatures and wind velocities are compared with the measurements. The results indicate a good online performance of the model system which is comparable with the offline performance of other urban canopy schemes in terms of the fluxes. DCEP is able to simulate typical characteristics of the urban boundary layer, in contrast to the default bulk‐transfer scheme of COSMO‐CLM.

Groundwater flow across spatial scales: importance for climate modeling

Current regional and global climate models generally do not represent groundwater flow between grid cells as a component of the water budget. We estimate the magnitude of between-cell groundwater flow as a function of grid cell size by aggregating results from a numerical model of equilibrium groundwater flow run and validated globally. We find that over a broad range of cell sizes spanning that of state-of-the-art regional and global climate models, mean between-cell groundwater flow magnitudes scale with the reciprocal of grid cell length. We also derive this scaling a priori from a simple statistical model of a flow network. We offer operational definitions of ‘significant’ groundwater flow contributions to the grid cell water budget in both relative and absolute terms (between-cell flow magnitude exceeding 10% of local recharge or 10 mm y−1, respectively). Groundwater flow is a significant part of the water budget, as measured by a combined test requiring both relative and absolute significance, over 42% of the land area at 0.1° grid cell size (typical of regional and mesoscale models), decreasing to 1.5% at 1° (typical of global models). Based on these findings, we suggest that between-cell groundwater flow should be represented in regional and mesoscale climate models to ensure realistic water budgets, but will have small effects on water exchanges in current global models. As well, parameterization of subgrid moisture heterogeneity should include the effects of within-cell groundwater flow.

The importance of land cover change across urban–rural typologies for climate modeling

Land cover changes affect local surface energy balances by changing the amount of solar energy reflected, the magnitude and duration over which absorbed energy is released as heat, and the amount of energy that is diverted to non-heating fluxes through evaporation. However, such local influences often are only crudely included in climate modeling exercises, if at all. A better understanding of local land conversion dynamics can serve to inform inputs for climate models and increase the role for land use planning in climate management policy. Here we present a new approach for projecting and incorporating metropolitan land cover change into mesoscale climate and other environmental assessment models. Our results demonstrate the relative contributions of different land development patterns to land cover change and conversion and suggest that regional growth management strategies serving to increase settlement densities over time can have a significant influence on the rate of deforestation per unit of population growth. Employing the approach presented herein, the impacts of land conversion on climate change and on parallel environmental systems and services, such as ground water recharge, habitat provision, and food production, may all be investigated more closely and managed through land use planning.

The integrated WRF/Urban modeling system and its application to monitoring urban heat island in Jakarta-Indonesia

Population growth and urbanization will impact on city development through constructions of buildings, parking lots, streets, highways and driveways. These changes lead to the Urban Heat Island (UHI), which is an important factor for future urban planning. In this context, mesoscale climate models such as the Weather Research and Forecasting (WRF) model are useful for studying the potential deficit in open green areas. The analysis of remote sensing images can provide input data indispensable to such climate model studies. In this work, we analyze the land use/land cover information inside and around the city of Jakarta, Indonesia, to study how the land use (LU) change affects UHI that is characterized by the highest surface air temperature (Ta) of 306 K. It is found that LU modification with the addition of 25% urban area will expand the UHI area by around 43 km 2 (5%). On the contrary, with the addition of 58, 95 and 440% vegetation (grassland) in the urban area, the UHI area is reduced significantly, which are 255 km 2 (48%), 289 km 2 (54%) and 466 km² (88%), respectively. This indicates that the addition of more area with open green coverage results in more reduction of UHI area. The quantitative features of this relationship will be useful for urban planners to control the UHI effects that might degrade the living conditions in this megacity.

Modeling the water isotopes in Greenland precipitation 1959–2001 with the meso-scale model REMO-iso

[1] Ice core studies have proved the δ18O in Greenland precipitation to be correlated to the phase of the North Atlantic Oscillation (NAO). This subject has also been investigated in modeling studies. However, these studies have either had severe biases in the δ18O levels, or have not been designed to be compared directly with observations. In this study we nudge a meso-scale climate model fitted with stable water isotope diagnostics (REMO-iso) to follow the actual weather patterns for the period 1959–2001. We evaluate this simulation using meteorological observations from stations along the Greenland coast, and δ18O from several Greenland ice core stacks and Global Network In Precipitation (GNIP) data from Greenland, Iceland and Svalbard. The REMO-iso output explains up to 40% of the interannual δ18O variability observed in ice cores, which is comparable to the model performance for precipitation. In terms of reproducing the observed variability the global model, ECHAM4-iso performs on the same level as REMO-iso. However, REMO-iso has smaller biases in δ18O and improved representation of the observed spatial δ18O-temperature slope compared to ECHAM4-iso. Analysis of the main modes of winter variability of δ18O shows a coherent signal in Central and Western Greenland similar to results from ice cores. The NAO explains 20% of the leading δ18O pattern. Based on the model output we suggest that methods to reconstruct the NAO from Greenland ice cores employ both δ18O and accumulation records.

Aeolian dunes as ground truth for atmospheric modeling on Mars

Martian aeolian dunes preserve a record of atmosphere/surface interaction on a variety of scales, serving as ground truth for both Global Climate Models (GCMs) and mesoscale climate models, such as the Mars Regional Atmospheric Modeling System (MRAMS). We hypothesize that the location of dune fields, expressed globally by geographic distribution and locally by dune centroid azimuth (DCA), may record the long‐term integration of atmospheric activity across a broad area, preserving GCM‐scale atmospheric trends. In contrast, individual dune morphology, as expressed in slipface orientation (SF), may be more sensitive to localized variations in circulation, preserving topographically controlled mesoscale trends. We test this hypothesis by comparing the geographic distribution, DCA, and SF of dunes with output from the Ames Mars GCM and, at a local study site, with output from MRAMS. When compared to the GCM: 1) dunes generally lie adjacent to areas with strongest winds, 2) DCA agrees fairly well with GCM modeled wind directions in smooth‐floored craters, and 3) SF does not agree well with GCM modeled wind directions. When compared to MRAMS modeled winds at our study site: 1) DCA generally coincides with the part of the crater where modeled mean winds are weak, and 2) SFs are consistent with some weak, topographically influenced modeled winds. We conclude that: 1) geographic distribution may be valuable as ground truth for GCMs, 2) DCA may be useful as ground truth for both GCM and mesoscale models, and 3) SF may be useful as ground truth for mesoscale models.

위성영상 해상풍 축출에 의한 수치바람모의 검증

As a part of effort to establish an offshore wind resource assessment system of the Korean Peninsula, a numeric wind simulation using mesoscale climate model MM5 and a spatial distribution of offshore wind extracted from SAR remote-sensing satellite image is compared and analyzed. According to the analyzed results, the numeric wind simulation is found to have wind speed over predication tendency at the coastal sea area. Therefore, it is determined that a high-resolution wind simulation is required for complicated coastal landforms. The two methods are verified as useful ways to identify the spatial distribution of offshore wind by mutual complementation and if the meteor-statistical comparative analysis is performed in the future using adequate number of satellite images, it is expected to derive a general methodology enabling systematic validation and correction of the numeric wind simulation.

Hydrologic drainage of the Greenland Ice Sheet

AbstractA simple hydrologic drainage network for the Greenland Ice Sheet is modelled from available digital elevation models (DEMs) of bedrock, and surface topography and assumptions of hydrostatic water pressure, uniform hydraulic conductivity, and no conduit flow within the ice sheet. As such, it is a first‐order model best suited for broad‐scale hydrological assessment. Results identify 293 distinct hydrologic basins (185–117 000 km2) together with their ‘realized’ (wet) and ‘unrealized’ (dry) drainage patterns. Intersection with 1991–2000 Polar MM5 (PMM5) mesoscale climate model hindcasts of meltwater runoff suggest that these basins route varying amounts of water to the ice edge, ranging from 0 to 16 km3 annually and totalling 242 km3/year for the entire ice sheet. Regionally speaking, average annual volumetric meltwater production (km3/year) is highest in southwest and lowest in northeast Greenland, with greater hydrologic activity in western regions than in eastern regions for a given latitude. The extent to which meltwater truly reaches the ice margin as modelled is difficult to test. However, the simulated flow outlet locations show qualitative agreement with the locations of 460 observed meltwater outlets (proglacial lakes, streams, and rivers; and sediment plumes into fjörds) mapped continuously along the ice sheet perimeter. On average, about 36% of the modelled drainage network was activated (i.e. received water) over the 1991–2000 study period. Remaining areas, barring dynamic changes to ice‐surface topography, would presumably activate if surface melt penetrates deeper into the ice sheet interior. Both new datasets are freely available for scientific use at the National Snow and Ice Data Center (ftp://sidads.colorado.edu/pub/DATASETS/parca/nsidc‐0372‐hydrologic‐outlets; ftp://sidads.colorado.edu/pub/DATASETS/parca/nsidc‐0371‐hydrologic‐sub‐basins). Copyright © 2009 John Wiley & Sons, Ltd.