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In this study, localised and non-uniform urban morphology (UM) and urban fraction (UF) parameters are implemented in a single-layer urban canopy scheme in the Weather Research and Forecasting (WRF) mesoscale meteorological model. The purpose of this research is to evaluate the effect of the refined parameterisation scheme on the simulation of dynamic and thermal fields in the urban canopy of the Guangzhou metropolitan area. The results showed that, compared with the default urban canopy parameters of the WRF model, using the localised UM parameters resulted in the most significant improvement in the 10 m wind speed simulation. In urban districts, the mean bias between the observed and simulated 10 m wind speed was reduced significantly by 59% from 2.63 m/s to 1.09 m/s during the daytime. For the thermal environment simulation during the daytime, higher UF and UM values resulted in lower surface albedos and generated narrower street canyons compared with the default modelling setting, which caused more heat to be trapped in the urban canopy and ultimately led to an increase in the surface skin temperature (TSK) and a largely increased ground heat flux (GRD). As a result, at night, more heat was transferred from the ground to the surface, producing a higher TSK. The effect of the localised UF on the sensible heat flux (HFX) was closely related to the near-surface temperature gradient. The UM caused the HFX to increase during the daytime, which was related to the near-surface heat exchange coefficient in the lower model layers. As the high-resolution UM significantly altered the urban geometry, the dynamic environment simulation resulted in a large increase in friction velocity and a decrease in wind speed. [ABSTRACT FROM AUTHOR]

Abstract The European Space Agency recently launched the Sentinel mission to perform terrestrial observations in support of tasks such as monitoring forests, detecting land-cover changes, and managing natural disasters. The resolution of these satellite images can be as high as 10 m depending on the bands. In this study, we used the red and near-infrared bands in 10-m resolution from Sentinel-2 images to calculate the Normalized Difference Vegetation Index (NDVI) and estimate of the green vegetation fraction in urban areas within the Pearl River Delta region (PRD). We used vegetation coverage obtained from high-resolution Google satellite images as a reference to validate the vegetation estimates derived from the Sentinel-2 images, and found the correlation between the two to be as high as 0.97. As such, information from the Sentinel-2 imagery can supplement the urban canopy parameters (UCPs) derived from the World Urban Database and Access Portal Tools (WUDAPT) level-0 dataset, which is used in urban meteorological models. The rapid retrieval and open-source nature of the methodology supports high-resolution urban climate modeling studies.

Both the European Space Agency's soil moisture and ocean salinity (SMOS) mission and the National Aeronautics and Space Administration's soil moisture active passive (SMAP) mission employ L-band (1.413 GHz) radiometers to observe brightness temperatures at ∼40-km spatial resolution to subsequently derive global soil moisture every two to three days with a target accuracy of 0.04 m3/m3. However, the man-made structures that dominate urban areas in many of the SMOS and SMAP radiometers pixels may confound the interpretation of their radiometric observations if not taken into account, and thus, degrade the soil moisture retrieval accuracy. This paper investigates the effect that urban areas are expected to have on the SMOS and SMAP soil moisture retrieval accuracy using experimental data from the Australian airborne field campaigns performed over the past six years. Taking the total radiometric error budgets for the SMOS (3.95 K) and the SMAP (1.3 K) missions as conservative benchmarks for radiometric “error” that can be tolerated to achieve the 0.04 m3/m3 target accuracy, urban fraction thresholds of 6.6% and 2.2% were obtained for the SMOS and SMAP pixels, respectively, under warm dry (soil moisture < 0.15 m3/m3) conditions, increasing to 16.8% and 5.2% under cold and/or wet conditions. These results have been extrapolated globally, assuming that the microwave behavior of the cities analyzed here is representative of those elsewhere, to identify the SMOS and SMAP pixels that are expected to be adversely affected by urban areas if not explicitly taken into account in retrieval algorithms. [ABSTRACT FROM AUTHOR]

This study aims to improve the representation of urban surfaces by implementing the Town Energy Balance (TEB) model for urban surface simulation, and the Canadian Land Surface Scheme (CLASS) for the simulation of natural surfaces. The study is conducted over eastern North American continent selected for its higher urban fractions. Seven sets of simulations with different initial and boundary conditions were conducted, and comparisons were made between urban and non-urban fractions using selected meteorological and energy variables such as temperature, surface albedo, and the turbulent latent and sensible heat fluxes. Results indicated that the realistic representation of urban surfaces by TEB resolved urban radiation and turbulent energy partitioning better than the bare soil formulation representation of urban regions by CLASS - an overall improvement of the mean land surface temperature by about 2 °C. The model also produced an annual mean surface temperature of up to a maximum of 4 °C higher over urban than non-urban regions in the current climate. Diurnal cycle of the urban heat island intensity is higher in the second half of the day than early mornings, and seasonally, the urban heat island intensity is higher in summer than in winter pertaining to maximum solar radiation during the day and in summer. Most of the incident solar radiation on urban surfaces are stored during the day and released at night causing thermal discomfort to urban residents. The urban canopy model TEB also simulated the strong correlation between the urban heat island effect and the turbulent energy fluxes relatively well. Furthermore, projections were made in to the future because the urban canopy model TEB has demonstrated sufficient performance over urban regions for the current climate. Projections show that urban land surfaces will get warmer by up to a maximum of 6 °C in the mid-century (1941–1970) and by up to a maximum of 13 °C at the end of 2100 under RCP8.5 emissions scenario. However, the projection of urban-rural heat island contrast is very low, but significant enough to warm urban regions to cause urban thermal discomfort. The differences in temperature and energy partitions between urban and rural regions show that the realistic representation of urban surfaces in climate models would improve the performance of NWP models. Therefore, climate models should take into account the effects of urban surfaces to appropriately investigate the impact of built-in urban environments on weather and climate, and in turn the effect of these weather and climate changes on urban community. [ABSTRACT FROM AUTHOR]

The European Space Agency recently launched the Sentinel mission to perform terrestrial observations in support of tasks such as monitoring forests, detecting land-cover changes, and managing natural disasters. The resolution of these satellite images can be as high as 10 m depending on the bands. In this study, we used the red and near-infrared bands in 10-m resolution from Sentinel-2 images to calculate the Normalized Difference Vegetation Index (NDVI) and estimate of the green vegetation fraction in urban areas within the Pearl River Delta region (PRD). We used vegetation coverage obtained from high-resolution Google satellite images as a reference to validate the vegetation estimates derived from the Sentinel-2 images, and found the correlation between the two to be as high as 0.97. As such, information from the Sentinel-2 imagery can supplement the urban canopy parameters (UCPs) derived from the World Urban Database and Access Portal Tools (WUDAPT) level-0 dataset, which is used in urban meteorological models. The rapid retrieval and open-source nature of the methodology supports high-resolution urban climate modeling studies. [ABSTRACT FROM AUTHOR]