scholarly journals Nature-based cooling potential: a multi-type green infrastructure evaluation in Toronto, Ontario, Canada

Author(s):  
Vidya Anderson ◽  
William A. Gough

AbstractThe application of green infrastructure presents an opportunity to mitigate rising temperatures using a multi-faceted ecosystems-based approach. A controlled field study in Toronto, Ontario, Canada, evaluates the impact of nature-based solutions on near surface air temperature regulation focusing on different applications of green infrastructure. A field campaign was undertaken over the course of two summers to measure the impact of green roofs, green walls, urban vegetation and forestry systems, and urban agriculture systems on near surface air temperature. This study demonstrates that multiple types of green infrastructure applications are beneficial in regulating near surface air temperature and are not limited to specific treatments. Widespread usage of green infrastructure could be a viable strategy to cool cities and improve urban climate.

2020 ◽  
Author(s):  
Gianluca Mussetti ◽  
Dominik Brunner ◽  
Stephan Henne ◽  
Scott Krayenhoff ◽  
Jan Carmeliet

<p><span>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.</span></p><p><span>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. </span></p><p><span>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.</span></p><p><span>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.  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. </span></p>


Author(s):  
P. A. Clark

Short lead-time forecasts using the operational United Kingdom variable-resolution (UKV) configuration of the Met Office’s numerical weather prediction model, with horizontal grid-length 1.5 km over the UK, with and without a representation of the 20 March 2015 eclipse, have been used to simulate the impact of the eclipse on UK weather. The major impact was surface-driven through changes to surface heat and moisture fluxes that changed the boundary-layer development. In cloud-free areas, the nocturnal stable boundary layer persisted or quickly re-established during the eclipse. Surface temperatures were reduced by 7–8°C, near-surface air temperature by 1–3°C, and near-surface winds were backed, typically by 20°. Impacts on wind speed were small and variable, and would have been very difficult to detect. Smaller impacts occurred beneath cloud. However, the impact was enhanced because most of the incoming radiation that reached the surface was driving surface sensible heat flux rather than moisture flux, and the near-surface air temperature impact (0.5–1° C ) agrees reasonably well with observations. The modelled impact of the eclipse was substantially reduced in urban areas due to their large thermal inertia. Experience from other assessments of the model suggests that this lack of response may be exaggerated. Surface impacts propagated upwards and downstream with time, resulting in a complex pattern of response, though generally near-surface temperature differences persisted for many hours after the eclipse. The impact on atmospheric pressure fields was insufficient to account for any significant perturbations to the wind field when compared with the direct impacts of surface stress and boundary-layer mixing. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’.


2017 ◽  
Vol 18 (11) ◽  
pp. 2991-3012 ◽  
Author(s):  
Ning Zhang ◽  
Yan Chen ◽  
Ling Luo ◽  
Yongwei Wang

Abstract Cool roofs and green roofs are two popular methods to mitigate the urban heat island and improve urban climates. The effectiveness of different urban heat island mitigation strategies in the summer of 2013 in the Yangtze River delta, China, is investigated using the Weather Research and Forecasting (WRF) Model coupled with a physically based single-layer urban canopy model. The modifications to the roof surface changed the urban surface radiation balance and then modified the local surface energy budget. Both cool roofs and green roofs led to a lower surface skin temperature and near-surface air temperature. Increasing the roof albedo to 0.5 caused a similar effectiveness as covering 25% of urban roofs with vegetation; increasing the roof albedo to 0.7 caused a similar near-surface air temperature decrease as 50% green roof coverage. The near-surface relative humidity increased in both cool roof and green roof experiments because of the combination of the impacts of increases in specific humidity and decreases in air temperature. The regional impacts of cool roofs and green roofs were evaluated using a regional effect index. A regional impact was found for near-surface air temperature and specific/relative humidity when the percentage of roofs covered with high-albedo materials or green roofs reached a higher fraction (greater than 50%). The changes in the vertical profiles of temperature cause a more stable atmospheric boundary layer over the urban area; at the same time, the crossover phenomena occurred above the boundary layer due to the decrease in vertical wind speed.


2020 ◽  
Vol 21 (8) ◽  
pp. 1705-1722 ◽  
Author(s):  
Randal D. Koster ◽  
Siegfried D. Schubert ◽  
Anthony M. DeAngelis ◽  
Andrea M. Molod ◽  
Sarith P. Mahanama

AbstractPast studies have shown that accurate soil moisture initialization can contribute significant skill to near-surface air temperature (T2M) forecasts at subseasonal leads. The mechanisms by which soil moisture contributes such skill are examined here with a simple water balance–based model that captures the essence of soil moisture behavior in a state-of-the-art subseasonal-to-seasonal (S2S) forecasting system. The simple model successfully transforms initial soil moisture contents into average “forecast” evapotranspiration (ET) values at 16–30-day lead that agree well, during summer, with the values forecast by the full NASA GEOS S2S system, indicating that soil moisture initialization dominates over forecast meteorological conditions in determining ET fluxes at subseasonal leads. When the simple model’s ET anomalies are interpreted in terms of T2M anomalies, a similar conclusion is reached for T2M: soil moisture initialization explains much (about 50% in the eastern half of the continental United States) of the T2M anomaly values produced by the full GEOS S2S system at 16–30-day lead, and the T2M forecasts produced by the simple model capture about one-half of the skill attained by the full system. The simple model’s framework is particularly conducive to an analysis of uncertainty in forecasts. Drier soils are generally found to induce larger uncertainty in ET (and thus T2M) forecasts, a result linked to the functional form relating ET to soil moisture in the simple model and verified by an analysis of the ensemble spreads within the forecasts produced by the full GEOS S2S system.


2021 ◽  
Author(s):  
Zhaomin Ding ◽  
Renguang Wu

AbstractThis study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.


2007 ◽  
Vol 46 (10) ◽  
pp. 1587-1605 ◽  
Author(s):  
J-F. Miao ◽  
D. Chen ◽  
K. Borne

Abstract In this study, the performance of two advanced land surface models (LSMs; Noah LSM and Pleim–Xiu LSM) coupled with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3.7.2, in simulating the near-surface air temperature in the greater Göteborg area in Sweden is evaluated and compared using the GÖTE2001 field campaign data. Further, the effects of different planetary boundary layer schemes [Eta and Medium-Range Forecast (MRF) PBLs] for Noah LSM and soil moisture initialization approaches for Pleim–Xiu LSM are investigated. The investigation focuses on the evaluation and comparison of diurnal cycle intensity and maximum and minimum temperatures, as well as the urban heat island during the daytime and nighttime under the clear-sky and cloudy/rainy weather conditions for different experimental schemes. The results indicate that 1) there is an evident difference between Noah LSM and Pleim–Xiu LSM in simulating the near-surface air temperature, especially in the modeled urban heat island; 2) there is no evident difference in the model performance between the Eta PBL and MRF PBL coupled with the Noah LSM; and 3) soil moisture initialization is of crucial importance for model performance in the Pleim–Xiu LSM. In addition, owing to the recent release of MM5, version 3.7.3, some experiments done with version 3.7.2 were repeated to reveal the effects of the modifications in the Noah LSM and Pleim–Xiu LSM. The modification to longwave radiation parameterizations in Noah LSM significantly improves model performance while the adjustment of emissivity, one of the vegetation properties, affects Pleim–Xiu LSM performance to a larger extent. The study suggests that improvements both in Noah LSM physics and in Pleim–Xiu LSM initialization of soil moisture and parameterization of vegetation properties are important.


2021 ◽  
Author(s):  
Thordis Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad

<p>Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.</p><p>Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.</p><p>To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.</p><p>The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.</p>


2017 ◽  
Vol 10 (8) ◽  
pp. 3085-3104 ◽  
Author(s):  
Min Huang ◽  
Gregory R. Carmichael ◽  
James H. Crawford ◽  
Armin Wisthaler ◽  
Xiwu Zhan ◽  
...  

Abstract. Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ∼ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.


2005 ◽  
Vol 18 (16) ◽  
pp. 3217-3228 ◽  
Author(s):  
D. W. Shin ◽  
S. Cocke ◽  
T. E. LaRow ◽  
James J. O’Brien

Abstract The current Florida State University (FSU) climate model is upgraded by coupling the National Center for Atmospheric Research (NCAR) Community Land Model Version 2 (CLM2) as its land component in order to make a better simulation of surface air temperature and precipitation on the seasonal time scale, which is important for crop model application. Climatological and seasonal simulations with the FSU climate model coupled to the CLM2 (hereafter FSUCLM) are compared to those of the control (the FSU model with the original simple land surface treatment). The current version of the FSU model is known to have a cold bias in the temperature field and a wet bias in precipitation. The implementation of FSUCLM has reduced or eliminated this bias due to reduced latent heat flux and increased sensible heat flux. The role of the land model in seasonal simulations is shown to be more important during summertime than wintertime. An additional experiment that assimilates atmospheric forcings produces improved land-model initial conditions, which in turn reduces the biases further. The impact of various deep convective parameterizations is examined as well to further assess model performance. The land scheme plays a more important role than the convective scheme in simulations of surface air temperature. However, each convective scheme shows its own advantage over different geophysical locations in precipitation simulations.


2018 ◽  
Vol 33 ◽  
pp. 01004 ◽  
Author(s):  
Alla Kopeva ◽  
Olga Ivanova ◽  
Olga Khrapko

The purpose of this study is to identify the facilities of green infrastructure that are able to improve living conditions in an urban environment in high-rise residential apartments buildings on steep slopes in the city of Vladivostok. Based on the analysis of theoretical sources and practices that can be observed in the world, green infrastructure facilities have been identified. These facilities meet the criteria of the sustainable development concept, and can be used in the city of Vladivostok. They include green roofs, green walls, and greening of disturbed slopes. All the existing high-rise apartments buildings situated on steep slopes in the city of Vladivostok, have been studied. It is concluded that green infrastructure is necessary to be used in new projects connected with designing and constructing of residential apartments buildings on steep slopes, as well as when upgrading the projects that have already been implemented. That will help to regulate the ecological characteristics of the sites. The results of the research can become a basis for increasing the sustainability of the habitat, and will facilitate the adoption of decisions in the field of urban design and planning.


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