An integrated wind risk warning model for urban rail transport in Shanghai, China

The integrated wind risk warning model for rail transport presented has four elements: Background wind data, a wind field model, a vulnerability model, and a risk model. Background wind data uses observations in this study. Using the wind field model with effective surface roughness lengths, the background wind data are interpolated to a 30-m resolution grid. In the vulnerability model, the aerodynamic characteristics of railway vehicles are analyzed with CFD (Computational Fluid Dynamics) modelling. In the risk model, the maximum value of three aerodynamic forces is used as the criteria to evaluate rail safety and to quantify the risk level under extremely windy weather. The full model is tested for the Shanghai Metro Line 16 using wind conditions during Typhoon Chan-hom. The proposed approach enables quick quantification of real- time safety risk levels during typhoon landfall, providing sophisticated warning information for rail vehicle operation safety

Characterization of energy flux partitioning in urban environments: links with surface seasonal properties

A better understanding of links between the properties of the urban environment and the exchange to the atmosphere is central to a wide range of applications. The numerous measurements of surface energy balance data in urban areas enable intercomparison of observed fluxes from distinct environments. This study analyzes a large database in two new ways. First, instead of normalizing fluxes using net all-wave radiation only the incoming radiative fluxes are used, to remove the surface attributes from the denominator. Second, because data are now available year-round, indices are developed to characterize the fraction of the surface (built; vegetation) actively engaged in energy exchanges. These account for shading patterns within city streets and seasonal changes in vegetation phenology; their impact on the partitioning of the incoming radiation is analyzed. Data from 19 sites in North America, Europe, Africa, and Asia (including 6-yr-long observation campaigns) are used to derive generalized surface–flux relations. The midday-period outgoing radiative fraction decreases with an increasing total active surface index, the stored energy fraction increases with an active built index, and the latent heat fraction increases with an active vegetated index. Parameterizations of these energy exchange ratios as a function of the surface indices [i.e., the Flux Ratio–Active Index Surface Exchange (FRAISE) scheme] are developed. These are used to define four urban zones that characterize energy partitioning on the basis of their active surface indices. An independent evaluation of FRAISE, using three additional sites from the Basel Urban Boundary Layer Experiment (BUBBLE), yields accurate predictions of the midday flux partitioning at each location

Net carbon dioxide emissions from central London

Carbon dioxide (CO2) emissions from cities drive increased global atmospheric CO2 concentrations and associated climate change. Urban CO2 emissions can be evaluated using an inventory approach (summing all know emissions and sequestrations of CO 2 within a defined area), and/or a micrometeorological approach (summing the exchanges of CO2 through the sides of a defined volume of air, and the change in the total stored within the volume). Generally the micrometeorological approach, with the assumption that only the net turbulent vertical flux of CO2 is significant on annual timescales, is preferred. This study evaluates that assumption with respect to storage and vertical advection of CO2, and calculates net CO 2 emissions in central London using both methods for June 2012 to May 2013. Data sources include an eddy covariance system, switched horizontal and vertical CO 2 profiles, traffic counts and vegetation surveys. Annual total emissions were 51.4 and 53.5 kg CO2 m−2 y−1, (micrometeorological and inventory methods, respectively), i.e., within 4%, (1.3% with the assumption that the net vertical turbulent flux is the only non-negligible micrometeorological term). This study supports the use of vertical fluxes calculated from eddy covariance measurements at a single location to estimate total emissions from high density urban environments

Urban storage heat flux variability explored using satellite, meteorological and geodata

The storage heat flux (ΔQS) is the net flow of heat stored within a volume that may include the air, trees, buildings and ground. Given the difficulty of measurement of this important and large flux in urban areas, we explore the use of Earth Observation (EO) data. EO surface temperatures are used with ground-based meteorological forcing, urban morphology, land cover and land use information to estimate spatial variations of ΔQS in urban areas using the Element Surface Temperature Method (ESTM). First, we evaluate ESTM for four “simpler” surfaces. These have good agreement with observed values. ESTM coupled to SUEWS (an urban land surface model) is applied to three European cities (Basel, Heraklion, London), allowing EO data to enhance the exploration of the spatial variability in ΔQS. The impervious surfaces (paved and buildings) contribute most to ΔQS. Building wall area seems to explain variation of ΔQS most consistently. As the paved fraction increases up to 0.4, there is a clear increase in ΔQS. With a larger paved fraction, the fraction of buildings and wall area is lower which reduces the high values of ΔQS

Investigation of the impact of anthropogenic heat flux within an urban land surface model and PILPS-urban

Results from the first international urban model comparison experiment (PILPS-Urban) suggested that models which neglected the anthropogenic heat flux within the surface energy balance performed at least as well as models that include the source term, but this could not be explained. The analyses undertaken show that the results from PILPS-Urban were masked by the signal from including vegetation, which was identified in PILPS-Urban as being important. Including the anthropogenic heat flux does give improved performance, but the benefit is small for the site studied given the relatively small magnitude of this flux relative to other terms in the surface energy balance. However, there is no further benefit from including temporal variations in the flux at this site. The importance is expected to increase at sites with a larger anthropogenic heat flux and greater temporal variations

Key conclusions of the first international urban land surface model comparison project

he first international urban land surface model comparison was designed to identify three aspects of the urban surface-atmosphere interactions: (1) the dominant physical processes, (2) the level of complexity required to model these, and 3) the parameter requirements for such a model. Offline simulations from 32 land surface schemes, with varying complexity, contributed to the comparison. Model results were analysed within a framework of physical classifications and over four stages. The results show that the following are important urban processes; (i) multiple reflections of shortwave radiation within street canyons, (ii) reduction in the amount of visible sky from within the canyon, which impacts on the net long-wave radiation, iii) the contrast in surface temperatures between building roofs and street canyons, and (iv) evaporation from vegetation. Models that use an appropriate bulk albedo based on multiple solar reflections, represent building roof surfaces separately from street canyons and include a representation of vegetation demonstrate more skill, but require parameter information on the albedo, height of the buildings relative to the width of the streets (height to width ratio), the fraction of building roofs compared to street canyons from a plan view (plan area fraction) and the fraction of the surface that is vegetated. These results, whilst based on a single site and less than 18 months of data, have implications for the future design of urban land surface models, the data that need to be measured in urban observational campaigns, and what needs to be included in initiatives for regional and global parameter databases

Modelling the partitioning of turbulent fluxes at urban sites with varying vegetation cover

Inclusion of vegetation is critical for urban land surface models (ULSM) to represent reasonably the turbulent sensible and latent heat flux densities in an urban environment. Here the Joint UK Land Environment Simulator (JULES), an ULSM, is used to simulate the Bowen ratio at a number of urban and rural sites with vegetation cover varying between 1% and 98%. The results show that JULES is able to represent the observed Bowen ratios, but only when the additional anthropogenic water supplied into the urban ecosystem is considered. The impact of the external water use (irrigation, street cleaning), for example, on the surface energy flux partitioning can be as substantial as that of the anthropogenic heat flux on the sensible and latent heat fluxes. The Bowen ratio varies from 1-2 when the plan area vegetation fraction is between 30% and 70%. However, when the vegetation fraction is less than 20%, the Bowen ratios increase substantially (2-10) and have greater sensitivity to assumptions about external water use. As there are few long term observational sites with vegetation cover less than 30%, there is a clear need for more measurement studies in such environments

Temperature trends at the Mauna Loa observatory, Hawaii

Observations at the Mauna Loa Observatory, Hawaii, established the systematic increase of anthropogenic CO2 in the atmosphere. For the same reasons that this site provides excellent globally averaged CO2 data, it may provide temperature data with global significance. Here, we examine hourly temperature records, averaged annually for 1977-2006, to determine linear trends as a function of time of day. For night-time data (22:00 to 06:00 LST (local standard time)) there is a near-uniform warming of 0.040 degrees C yr(-1). During the day, the linear trend shows a slight cooling of -0.014 degrees C yr(-1) at 12:00 LST (noon). Overall, at Mauna Loa Observatory, there is a mean warming trend of 0.021 degrees C yr(-1). The dominance of night-time warming results in a relatively large annual decrease in the diurnal temperature range (DTR) of -0.050 degrees C yr(-1) over the period 1977-2006. These trends are consistent with the observed increases in the concentrations of CO2 and its role as a greenhouse gas (demonstrated here by first-order radiative forcing calculations), and indicate the possible relevance of the Mauna Loa temperature measurements to global warming.</p

Impacts of urban expansion on relatively smaller surrounding cities during heat waves

Urban-induced thermal stress can threaten human health, especially during heat waves (HWs). The growth of cities further exacerbates this effect. Here, weather research and forecasting (WRF) with an urban canopy model (UCM) is used to assess the effects of megacities and their growth on the thermal regime of proximal cities during heat waves. Analysis of the heat fluxes shows that advection impacts cities downwind. Results indicate that as urban areas change size (50%−100% and 100−150% of their current size), the local 2 m temperature increases by 2.7 and 1.7 °C, and the 2 m specific humidity decreases by 2.1 and 1.4 g kg−1, respectively. A small city downwind is impacted with a 0.3−0.4 °C increase in 2 m temperature. Green roof is a potential mitigation strategy for these regions (i.e., beyond the megacity). With 50% green roofs in an urban area, a 0.5 °C decrease in 2 m temperature and 0.6 g kg−1 increase in specific humidity is simulated. Urbanization upwind of a megacity will contribute to regional climate change

Network optimization for enhanced resilience of urban heat island measurements

The urban heat island is a well-known phenomenon that impacts a wide variety of city operations. With greater availability of cheap meteorological sensors, it is possible to measure the spatial patterns of urban atmospheric characteristics with greater resolution. To develop robust and resilient networks, recognizing sensors may malfunction, it is important to know when measurement points are providing additional information and also the minimum number of sensors needed to provide spatial information for particular applications. Here we consider the example of temperature data, and the urban heat island, through analysis of a network of sensors in the Tokyo metropolitan area (Extended METROS). The effect of reducing observation points from an existing meteorological measurement network is considered, using random sampling and sampling with clustering. The results indicated the sampling with hierarchical clustering can yield similar temperature patterns with up to a 30% reduction in measurement sites in Tokyo. The methods presented have broader utility in evaluating the robustness and resilience of existing urban temperature networks and in how networks can be enhanced by new mobile and open data sources