Urban Climate

Climate surface parameters in urban areas and the urban energy budget are influenced by the urban spatial characteristics. Thus, to model the urban energy budget, a characterization of the urban surface is required. Within the H2020 Project URBANFLUXES it is aimed model the urban energy budget and especially the anthropogenic heat flux using earth observation (EO) data. EO data is especially valuable for the mapping of the urban surface characteristics. The main advantage to do so is the transferability to any city, because objective input data can be generated. The EO methods for URBANFLUXES are developed and applied to three cities: Basel, London and Heraklion.

A requirements catalogue has been defined to ensure the EO products are adapted to the needs of the subsequent energy budget models. The required products are divided in morphological parameters and surface parameters. The morphological parameters describe the vertical structure of the urban area and require a detailed digital surface model. For URBANFLUXES, in addition to the surface and elevation models also the building height, sky view factor, building fraction (plan area index) and frontal area index are derived. The surface parameters describe characteristics such as land cover fractions, phenology (NDVI, LAI), albedo and surface temperature. The parameters that are related to vegetation have a higher variability through the year than the built up area. Therefore these parameters are derived multiple times per year, but also at a lower spatial resolution. All products are transferred to the same spatial grid. Various sources of EO data at different spatial and temporal resolution are used, depending on the requirements.

As basis for the morphological parameters a lidar DSM and derived DEM is available for the city of Basel and London. For Heraklion a DSM and DEM derived from stereo imagery is available. From the DEM and DSM, the sky view factor, plan area index and frontal area index are calculated according to Lindberg and Grimmond (2010) and Grimmond and Oke (1999). The results are aggregated to a 100 m grid. For the calculation of the surface parameters of Basel it is made use of data of Landsat 8 and Spot 5. The land cover fractions are calculated using a neural network approach (Del Frate et al. 2007)To describe the phenology time series of NDVI are calculated on the Landsat data. Also the albedo is calculated on the Landsat 8. Surface temperature is derived in local scale from the synergistic use of Landsat and MODIS acquisitions (Mitraka et al., 2015). All methodologies are implemented in a way that enables switching to the Sentinel 2/3 data as soon as the data becomes available.

The resulting EO products are the input for urban climate models to enable the estimation of anthropogenic heat flux. But they are also used as input for the classification of Local Climate Zones (LCZ). Stewart and Oke (2012) formally defined LCZ as regions of uniform surface cover, structure, material, and human activity that span hundreds of meters to several kilometers in horizontal scale. After successful classification and combination with the modelling results of the URBANFLUXES project, the LCZ could be used as an indicator for regions with certain anthropogenic heat flux characteristics.

References

Del Frate, F. , F. Pacifici, G. Schiavon, C. Solimini, 2007. Use of neural networks for automatic classification from high resolution imagery. IEEE Transactions on Geoscience and Remote Sensing,  45, 800-809

Grimmond, C.S.B., Oke, T.R.,1999.  Aerodynamic Properties of Urban Areas Derived from Analysis of Surface Form. Journal of Applied Meteorology, 38, 1262-1292

Lindberg, F. and Grimmond, C. S. B., 2010,. Continuous Sky View Factor from High Resolution Urban Digital Elevation Models. Climate Res., 42, 177 - 183.

Mitraka, Z., Chrysoulakis, N., Doxani, G., Del Frate, F., Berger, M., 2015. Urban Surface Temperature Time Series Estimation at the Local Scale by Spatial-Spectral Unmixing of Satellite Observations. Remote Sensing, 7(4), 4139–4156.

Stewart, I. D. and Oke, T. R., 2012. Local Climate Zones for Urban Temperature Studies. Bulletin of the American Meteorological Society, 93, 1879 - 1900

The recently launched H2020-Space project URBANFLUXES (URBan ANthrpogenic heat FLUX from Earth observation Satellites) investigates the potential of Copernicus Sentinels to retrieve anthropogenic heat flux, as a key component of the Urban Energy Budget (UEB). Temperatures in cities are predicted to rise even more in the future, resulting in increased energy demand for cooling systems in low and mid-latitude cities, modifying UEB. A positive feedback cycle occurs in many urban areas, where higher temperatures result in more energy being used for cooling, which in turn adds to heat emissions and increases temperatures further during periods with increased heat wave risk. It is expected that without mitigation measures, energy demand will continue to increase during the warmest months. URBANFLUXES advances the current knowledge of the impacts of UEB fluxes on urban heat island and consequently on energy consumption in cities. This will lead to the development of tools and strategies to mitigate these effects, improving thermal comfort and energy efficiency. In URBANFLUXES, the anthropogenic heat flux is estimated as a residual of UEB. Therefore, the rest UEB components, namely, the net all-wave radiation, the net change in heat storage and the turbulent sensible and latent heat fluxes are independently estimated from Earth Observation (EO), whereas the advection term is included in the error of the anthropogenic heat flux estimation from the UEB closure. A dense network of conventional meteorological stations is used in each case study city: London, Basel and Heraklion. EO data is initially analysed to map urban surface morphology and cover, whilst a new approach has been developed to define Local Climate Zones (LCZ). Using the LCZ as a framework, advanced EO-based methods are used to estimate UEB fluxes: a sophisticated radiative transfer model (Discrete Anisotropic Radiative Transfer) is employed to simulate the net all-wave radiation; the computation of the storage term is based on the Element Surface Temperature Method, supported by the auxiliary datasets; and the estimation of the turbulent heat fluxes is based on the Aerodynamic Resistance Method, supported by standard meteorological measurements. In-situ flux measurements (Eddy Covariance, scintilometry) and bottom-up approaches (inventories, building energy models) are used to evaluate URBANFLUXES outcomes, whereas uncertainties are specified and analysed. The project exploits Sentinels observations, which provide improved data quality, coverage and revisit times and increase the value of EO data for scientific work and future emerging applications. These observations can reveal novel scientific insights for the detection and monitoring of the spatial distribution of the urban energy budget fluxes in cities, thereby generating new EO opportunities. URBANFLUXES thus exploits the European capacity for space-borne observations to enable the development of operational services in the field of urban environmental monitoring and energy efficiency in cities. It is therefore expected to prepare the ground for further innovative exploitation of European space data in scientific activities (climate variability studies at local and regional scales) and future and emerging applications (sustainable urban planning, mitigation technologies) to benefit climate change mitigation/adaptation and civil protection.

In the context of global climate change, most Mediterranean cities have undergone significant warming during last decades which is more pronounced in the summer. Urban Heat Island phenomenon has an additive effect on the regional warming. Meanwhile, the increase in the mean air temperature is accompanied by the increase in the frequency of hot extremes. Therefore, appraisal and quantification of spatially distributed heat wave risk are required to develop innovative tools and services for the subsequent design of targeted measures and strategies. This was the motivation behind the development of a fully automated system for the continuous monitoring of Land Surface and Air Temperatures (LST and AT, respectively) of European cities in real time every 5 minutes at 1km resolution.

Realizing the importance of monitoring the thermal urban environment and the existing gap in data and system availability, the Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing of the National Observatory of Athens (IAASARS/NOA) has developed a system for continuous monitoring the urban thermal environment at high spatial and temporal resolution. This work presents a system based on the data acquired by Meteosat Second Generation 2 – Spinning Enhanced Visible and Infrared Imager (MSG2-SEVIRI) Rapid Scanning Service (RSS) downscaled to 1 km. It is using several algorithms developed by our team as well as products and procedures from Eumetsat Satellite Application Facility on support to Nowcasting/ and Very Short-Range Forecasting (SAFNWC version MSG v2013). In the current implementation, Numerical Weather Predictions (NWP) necessary for SAFNWC are retrieved from the Global Forecasting System (GFS of the U.S. National Climatic Data Centre) for the entire Earth with a grid size of 0.25 degrees.

The developed system comprises five major modules, namely: i) SEVIRI image acquisition, ii) nowcasting of clouds and other atmospheric parameters, iii) derivation of LST and AT from clear sky thermal infrared radiances; iv) sharpening of LST using Support Vector Regression Machines (SVM) and iterative gradient boosting; and v) resampling of AT to 1km. For the demanding retrieval of AT, a first guess atmospheric profile is utilized from GFS and subsequently the radiances at satellite are simulated by RTTOV radiative transfer model. The solution is iterated until the simulated and measured radiances converge.

The system offers four significant advantages: 1) it exploits the high temporal resolution of SEVIRI RSS imagery (5 min), 2) it enhances the spatial resolution of the retrieved temperatures (LST and AT) down to 1 km, 3) it covers a large number of cities around the world, and 4) the derived products are available in real time.

Higher-level products are also produced at the same resolution: Heat Wave Hazard, Cooling Degrees and Discomfort indices. The system as well as the products obtained for 15 cities during summer 2015 will be presented. An initial assessment will also be presented. The system is developed as part of TREASURE project (Thermal Risk rEduction Actions and tools for SecURE cities) funded by the General Directorate for Humanitarian Aid and Civil Protection (ECHO/SUB/2014/695561).

TREASURE web site: http://treasure.eu-project-sites.com/ | Twitter: @TREASURE_Proj

Data collected by Earth Observation (EO) satellites provide a valuable source of information for understanding, monitoring, modelling and thus protecting the urban environment. The increasing availability of EO systems and the advances in remote sensing techniques increase the opportunities for monitoring the urban environment and its thermal behaviour. Several parameters related to the urban climate can be derived from EO data, providing valuable support for advanced urban studies and climate modelling. Recently, attention has been drawn to the quantitative description of the urban thermal patterns and their correlations to fundamental surface descriptors. A detailed classification scheme of Local Climate Zones (LCZ) was introduced (Steward and Oke, 2012), based on various former typologies, which explicitly defines urban landscapes according to their thermal properties. The individual classes aim to have relatively homogenous air temperature within the canopy layer and they are defined by fact sheets with both qualitative and quantitative properties.
In this study, EO data are used to derive quantitative information for discriminating between the LCZ and a methodology to combine the different scales and delineate the zones is developed. A set of parameters is estimated from EO data and the methodology is applied to three case studies of the URBANFLUXES project, i.e. Heraklion, Greece, Basel, Switzerland and London, UK. Parameters like the impervious and the pervious surface fraction and the surface albedo were quantified using satellite data. Combining ancillary information for the morphology of the city, parameters like the buildings density and the mean building height and the canyon aspect ratio are also quantified for the study sites. A methodology to handle the different scales of the EO products was established and a Graphical User Interface (GUI) was built to outline the possible LCZ.
References:
Stewart, I. D., & Oke, T. R. (2012). Local Climate Zones for Urban Temperature Studies. Bulletin of the American Meteorological Society, 93(12), 1879–1900.

Detailed information about the layout internal structure of urban areas is needed urgently for a number of applications including planning, energy consumption, and climate impact assessment. While there have been large improvements in the global derivation of urban built-up areas from space, ­­the internal differentiation of cities according to their morphology or form remains a challenging task. The complexity of urban structures, the heterogeneity of materials, and the multiplicity of spectral properties pose problems in finding a consistent method for the derivation of urban structural types (UST). Accordingly, various typologies – each specific to the characteristics of a particular area of interest – have been used in the past, which severely limits the comparability of such studies among different locations. Hence a common and generic description of urban structures would be an essential first step towards a universal mapping scheme that characterizes the internal configuration of urban areas.

In urban climatology the Local Climate Zone (LCZ) scheme has recently been introduced to facilitate communication of urban surface characteristics for heat island studies.  The scheme provides a good framework for the discretization of urban areas on a kilometric scale, is largely free of cultural or climatic bias and additionally delivers a large number of quantitative properties for each of its constituent classes. Furthermore, it has been demonstrated that LCZs can be classified in a satisfactory manner using freely available satellite space borne data from both multispectral or SAR sensors such as Landsat 8 and Sentinel 1 & 2, provided sufficient training data for a specific city are available.

In this presentation the LCZ scheme is highlighted and its advantages as a standard for UST classification in urban remote sensing are stressed and discussed. The World Urban Database and Access Portal Tools (WUDAPT) initiative is introduced, which aims to collect information about the form and function of urban areas on a global scale using remote sensing and crowdsourcing. Finally, initial results from various cities are presented.