scholarly journals Influence of high-resolution surface databases on the modeling of local atmospheric circulation systems

2013 ◽  
Vol 6 (4) ◽  
pp. 6659-6715
Author(s):  
L. M. S. Paiva ◽  
G. C. R. Bodstein ◽  
L. C. G. Pimentel
Keyword(s):  
Atmospheric Circulation ◽  
Urban Areas ◽  
Initial Conditions ◽  
European Space Agency ◽  
Parametric Models ◽  
Lateral Boundary Condition ◽  
United States Geological Survey ◽  
Area Index ◽  
Regional Prediction ◽  
Local Atmospheric Circulation

Abstract. Large-eddy simulations are performed using the Advanced Regional Prediction System (ARPS) code at horizontal grid resolutions as fine as 300 m to assess the influence of detailed and updated surface databases on the modeling of local atmospheric circulation systems of urban areas with complex terrain. Applications to air pollution and wind energy are sought. These databases are comprised of 3 arc-sec topographic data from the Shuttle Radar Topography Mission, 10 arc-sec vegetation type data from the European Space Agency (ESA) GlobCover Project, and 30 arc-sec Leaf Area Index and Fraction of Absorbed Photosynthetically Active Radiation data from the ESA GlobCarbon Project. Simulations are carried out for the Metropolitan Area of Rio de Janeiro using six one-way nested-grid domains that allow the choice of distinct parametric models and vertical resolutions associated to each grid. ARPS is initialized using the Global Forecasting System with 0.5°-resolution data from the National Center of Environmental Prediction, which is also used every 3 h as lateral boundary condition. Topographic shading is turned on and two soil layers with depths of 0.01 and 1.0 m are used to compute the soil temperature and moisture budgets in all runs. Results for two simulated runs covering the period from 6 to 7 September 2007 are compared to surface and upper-air observational data to explore the dependence of the simulations on initial and boundary conditions, topographic and land-use databases and grid resolution. Our comparisons show overall good agreement between simulated and observed data and also indicate that the low resolution of the 30 arc-sec soil database from United States Geological Survey, the soil moisture and skin temperature initial conditions assimilated from the GFS analyses and the synoptic forcing on the lateral boundaries of the finer grids may affect an adequate spatial description of the meteorological variables.

scholarly journals Influence of high-resolution surface databases on the modeling of local atmospheric circulation systems

2014 ◽  
Vol 7 (4) ◽  
pp. 1641-1659 ◽  
Author(s):  
L. M. S. Paiva ◽  
G. C. R. Bodstein ◽  
L. C. G. Pimentel
Keyword(s):  
High Resolution ◽  
Observational Data ◽  
Atmospheric Circulation ◽  
Potential Temperature ◽  
European Space Agency ◽  
Parametric Models ◽  
Lateral Boundary Condition ◽  
Area Index ◽  
Regional Prediction ◽  
Local Atmospheric Circulation

Abstract. Large-eddy simulations are performed using the Advanced Regional Prediction System (ARPS) code at horizontal grid resolutions as fine as 300 m to assess the influence of detailed and updated surface databases on the modeling of local atmospheric circulation systems of urban areas with complex terrain. Applications to air pollution and wind energy are sought. These databases are comprised of 3 arc-sec topographic data from the Shuttle Radar Topography Mission, 10 arc-sec vegetation-type data from the European Space Agency (ESA) GlobCover project, and 30 arc-sec leaf area index and fraction of absorbed photosynthetically active radiation data from the ESA GlobCarbon project. Simulations are carried out for the metropolitan area of Rio de Janeiro using six one-way nested-grid domains that allow the choice of distinct parametric models and vertical resolutions associated to each grid. ARPS is initialized using the Global Forecasting System with 0.5°-resolution data from the National Center of Environmental Prediction, which is also used every 3 h as lateral boundary condition. Topographic shading is turned on and two soil layers are used to compute the soil temperature and moisture budgets in all runs. Results for two simulated runs covering three periods of time are compared to surface and upper-air observational data to explore the dependence of the simulations on initial and boundary conditions, grid resolution, topographic and land-use databases. Our comparisons show overall good agreement between simulated and observational data, mainly for the potential temperature and the wind speed fields, and clearly indicate that the use of high-resolution databases improves significantly our ability to predict the local atmospheric circulation.

scholarly journals Correlating elements content in mosses collected in 2015 across Germany with spatially associated characteristics of sampling sites and their surroundings

2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Stefan Nickel ◽  
Winfried Schröder
Keyword(s):  
Land Use ◽  
Population Density ◽  
Atmospheric Deposition ◽  
Vegetation Structure ◽  
Urban Areas ◽  
Explanatory Power ◽  
Spatial Density ◽  
Area Index ◽  
Explanatory Variables ◽  
Tree Layer

Abstract Background The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis. Results The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N. Conclusions For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.

scholarly journals Urban Thematic Exploitation Platform - supporting urban research with EO data processing, integrative data analysis and reporting

2020 ◽  
Author(s):  
Felix Bachofer ◽  
Thomas Esch ◽  
Jakub Balhar ◽  
Martin Boettcher ◽  
Enguerran Boissier ◽  
...  
Keyword(s):  
Urban Areas ◽  
High Performance ◽  
Service Providers ◽  
Research Output ◽  
European Space Agency ◽  
Data Access ◽  
Well Being ◽  
Product Portfolio ◽  
Source Information ◽  
End To End

<p>Urbanization is among the most relevant global trends that affects climate, environment, as well as health and socio-economic development of a majority of the global population. As such, it poses a major challenge for the current urban population and the well-being of the next generation. To understand how to take advantage of opportunities and properly mitigate to the negative impacts of this change, we need precise and up-to-date information of the urban areas. The Urban Thematic Exploitation Platform (UrbanTEP) is a collaborative system, which focuses on the processing of earth observation (EO) data and delivering multi-source information on trans-sectoral urban challenges.</p><p>The U-TEP is developed to provide end-to-end and ready-to-use solutions for a broad spectrum of users (service providers, experts and non-experts) to extract unique information/ indicators required for urban management and sustainability. Key components of the system are an open, web-based portal connected to distributed high-level computing infrastructures and providing key functionalities for</p><p>i) high-performance data access and processing,</p><p>ii) modular and generic state-of-the art pre-processing, analysis, and visualization,</p><p>iii) customized development and sharing of algorithms, products and services, and</p><p>iv) networking and communication.</p><p>The service and product portfolio provides access to the archives of Copernicus and Landsat missions, Datacube technology, DIAS processing environments, as well as premium products like the World Settlement Footprint (WSF). External service providers, as well as researchers can make use of on-demand processing of new data products and the possibility of developing and deploying new processors. The onboarding of service providers, developers and researchers is supported by the Network of Resources program of the European Space Agency (ESA) and the OCRE initiative of the European Commission.</p><p>In order to provide end-to-end solutions, the VISAT tool on UrbanTEP allows analyzing and visualizing project-related geospatial content and to develop storylines to enhance the transport of research output to customers and stakeholders effectively. Multiple visualizations (scopes) are already predefined. One available scope exemplary illustrates the exploitation of the WSF-Evolution dataset by analyzing the settlement and population development for South-East Asian countries from 1985 to 2015 in the context of the Sustainable Development Goal (SDG) 11.3.1 indicator. Other open scopes focus on urban green, functional urban areas, land-use and urban heat island modelling (e.g.).</p>

scholarly journals ROAD TEMPERATURE MODELLING WITHOUT IN-SITU SENSORS

2017 ◽  
Vol 12 (4) ◽  
pp. 241-247 ◽  
Author(s):  
Karol Opara ◽  
Jan Zieliński
Keyword(s):  
Energy Balance ◽  
Urban Areas ◽  
Initial Conditions ◽  
Forecast Error ◽  
Weather Data ◽  
Forecast Errors ◽  
The Road ◽  
In Situ Sensors ◽  
Pavement Temperature

Modelling of the pavement temperature facilitates winter road maintenance. It is used for predicting the glaze formation and for scheduling the spraying of the de-icing brine. The road weather is commonly forecasted by solving the energy balance equations. It requires setting the initial vertical profile of the pavement temperature, which is often obtained from the Road Weather Information Stations. The paper proposes the use of average air temperature from seven preceding days as a pseudo-observation of the subsurface temperature. Next, the road weather model is run with a few days offset. It first uses the recent, historical weather data and then the available forecasts. This approach exploits the fact that the energy balance models tend to “forget” their initial conditions and converge to the baseline solution. The experimental verification was conducted using the Model of the Environment and Temperature of Roads and the data from a road weather station in Warsaw over a period of two years. The additional forecast error introduced by the proposed pseudo-observational initialization averages 1.2 °C in the first prediction hour and then decreases in time. The paper also discusses the use of Digital Surface Models to take into account the shading effects, which are an essential source of forecast errors in urban areas. Limiting the use of in-situ sensors opens a perspective for an economical, largescale implementation of road meteorological models.

scholarly journals Análise da Variação Espaço-Temporal das Áreas Verdes e da Qualidade Ambiental em Áreas Urbanas, Recife-PE (Analysis of the Time-Space Variation of Green Areas and the Environmental Quality in Urban Areas, Recife-PE)

2015 ◽  
Vol 7 (6) ◽  
pp. 1196
Author(s):  
Tiago Henrique de Oliveira ◽  
José Gleidson Dantas ◽  
Josiclêda Domiciano Galvíncio ◽  
Rejane Magalhães de Mendonça Pimentel ◽  
Milton Botler
Keyword(s):  
Land Use ◽  
Environmental Quality ◽  
Urban Areas ◽  
Rapid Change ◽  
Large Temperature ◽  
Natural Soil ◽  
Area Index ◽  
Time Space ◽  
Green Areas ◽  
Spatio Temporal

As rápidas mudanças do uso e cobertura do solo em ambiente urbano apresentam grande impacto nas relações entre os ciclos energéticos e hidrológicos sobre a superfície. O município do Recife, através da Lei de Uso e Ocupação do Solo de 1996 (Lei nº 16.176/96) define área verde como “toda área de domínio público ou privado, em solo natural,onde predomina qualquer forma de vegetação, distribuída em seus diferentes estratos: Arbóreo, Arbustivo e Herbáceo /Forrageira, nativa ou exótica”. O objetivo deste artigo é analisar a variação espacial das áreas verdes disponíveis no município do Recife e a evolução espaço-temporal da qualidade ambiental na RPA 4 através do computo do Índice de umidade (NDWI), Índice de Área Foliar (IAF) e Temperatura da superfície em imagens TM Landsat. Foi realizada uma classificação supervisionada na ortofotocarta Recife onde as áreas verdes foram exportadas para polígonos, permitindo a sua quantificação. Para as imagens TM foi aplicada parte da metodologia SEBAL. As áreas verdes ocupam 45,58% do Recife. Os transectos lineares e perfis permitiram visualizar mais facilmente as mudanças espaço-temporais ocorridos na RPA-4. Foi visualizada grande diferença de temperatura entre as áreas vegetadas e as áreas mais urbanizadas. Palavras-chave: Uso e ocupação do solo; área urbana, áreas vegetadas, sensoriamento remoto; MAXVER. A B S T R A C T The rapid change of use and land cover in urban environment poses great impact on relations between energy and hydrological cycles on the surface. The municipality of Recife, through the Land Use Legislation from 1996 (Law No. 16.176/96) defines green area as ";;;;;;any public or private domain area, in natural soil, where overcrows any form of vegetation, distributed in its different layers: Arboreal, shrubby and Herbaceous Forage, native or exotic";;;;;;. The goal of this paper is to analyze the spatial variation of available green areas in the city of Recife and the spatio-temporal evolution of environmental quality in the Political Administrative Region 4, known as RPA-4, through the calculation of moisture content (NDWI), leaf area index (LAI) and the surface temperature from Landsat TM images. Supervised classification was performed on orthophoto Reef where the green areas were exported to polygons, allowing its quantification. For the TM images, it has been applied the methodology SEBAL. The green areas occupy 45.58% of Recife. The linear transects and profiles allowed to show more easily space-time changes occurring in the RPA-4. Large temperature differences have been displayed between the most vegetated areas and more urbanized areas. Key-words: Land use; urban areas; vegetated area, remote sensing; MAXVER.

scholarly journals Analysis of Total Column CO<sub>2</sub> and CH<sub>4</sub> Measurements in Berlin with WRF-GHG

2019 ◽  
Author(s):  
Xinxu Zhao ◽  
Julia Marshall ◽  
Stephan Hachinger ◽  
Christoph Gerbig ◽  
Jia Chen
Keyword(s):  
Urban Areas ◽  
Initial Conditions ◽  
Ghg Emissions ◽  
Concentration Field ◽  
Weather Research And Forecasting ◽  
Background Concentration ◽  
Wind Fields ◽  
Simulated Wind ◽  
Global Population ◽  
Good Agreement

Abstract. Though they cover less than 3 % of the global land area, urban areas are responsible for over 70 % of the global greenhouse gas (GHG) emissions and contain 55 % of the global population. A quantitative tracking of GHG emissions in urban areas is therefore of great importance, with the aim of accurately assessing the amount of emissions and identifying the emission sources. The Weather Research and Forecasting model (WRF) coupled with GHG modules (WRF-GHG) developed for mesoscale atmospheric GHG transport, can predict column-averaged abundances of CO2 and CH4 (XCO2 and XCH4). In this study, we use WRF-GHG to model the Berlin area at a high spatial resolution of 1 km. The simulated wind and concentration fields were compared with the measurements from a campaign performed around Berlin in 2014 (Hase et al., 2015). The measured and simulated wind fields mostly demonstrate good agreement and the simulated XCO2 agrees well with the measurement. In contrast, a bias in the simulated XCH4 of around 2.7 % is found, caused by relatively high initialization values for the background concentration field. We find that an analysis using differential column methodology (DCM) works well for the XCH4 comparison, as corresponding background biases then cancel out. From the tracer analysis, we find that the enhancement of XCH4 is highly dependent on human activities. The XCO2 signal in the vicinity of Berlin is dominated by anthropogenic behavior rather than biogenic activities. We conclude that DCM is an effective method for comparing models to observations independently of biases caused, e.g., by initial conditions. It allows us to use our high resolution WRF-GHG model to detect and understand sources of GHG emissions quantitatively in urban areas.

Assessing Seismic Resilience of School Educational Sector. An attempt to establish the initial conditions in Calabria Region, Southern Italy

2021 ◽  
Author(s):  
Cora Fontana ◽  
Eleonora Cianci ◽  
Massimiliano Moscatelli
Keyword(s):  
Urban Areas ◽  
Southern Italy ◽  
Initial Conditions ◽  
Risk Mitigation ◽  
School Buildings ◽  
Calabria Region ◽  
Structural Improvement ◽  
First Case ◽  
School Sector ◽  
Seismic Resilience

&lt;p&gt;School education constitutes one of the strategic functions to be recovered after an earthquake. The structural improvement of school buildings together with the strengthening of the administrators&amp;#8217; capacity to react positively following an earthquake are key factors that contribute to social vulnerability&amp;#8217;s reduction. Nevertheless, in Italy, the issue of risk reduction policies related to school sector is not yet consolidated in the institutional agendas. Observing the last major Italian earthquakes what remains predominant is school buildings&amp;#8217; damage degree with consequent interruption of the system functionality. Among the causes: the building heritage vulnerability and the lack of risk mitigation policies, capable of building a resilient community for future earthquakes. That of resilience is considered a relevant paradigm to address the issue of how to strengthen the school sector&amp;#8217;s capacity to ensure the buildings physical safety and to guarantee the maintenance of the school function, looking at pre and post-event phases.&lt;/p&gt;&lt;p&gt;The paper proposes a set of indicators and a methodology for a preliminary assessment of the educational sector&amp;#8217;s seismic resilience, in terms of initial conditions. The method has been tested on a first case study: Calabria Region, Southern Italy. The results show that spatial differences in the educational sector&amp;#8217;s seismic resilience are evident. Except for some large urban areas, the less resilient areas are grouped mainly in the southern part of the Region, while the most resilient ones are located mostly in the central-northern sector. The ambition is to identify a repeatable approach, useful as guidelines for school seismic prevention policies.&lt;/p&gt;

scholarly journals High-resolution mapping of the NO<sub>2</sub> spatial distribution over Belgian urban areas based on airborne APEX remote sensing

2017 ◽  
Vol 10 (5) ◽  
pp. 1665-1688 ◽  
Author(s):  
Frederik Tack ◽  
Alexis Merlaud ◽  
Marian-Daniel Iordache ◽  
Thomas Danckaert ◽  
Huan Yu ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Urban Areas ◽  
High Spatial Resolution ◽  
European Space Agency ◽  
Correlation Coefficients ◽  
Time Frame ◽  
Quantitative Information ◽  
Data Sets ◽  
Vertical Column

Abstract. We present retrieval results of tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs), mapped at high spatial resolution over three Belgian cities, based on the DOAS analysis of Airborne Prism EXperiment (APEX) observations. APEX, developed by a Swiss-Belgian consortium on behalf of ESA (European Space Agency), is a pushbroom hyperspectral imager characterised by a high spatial resolution and high spectral performance. APEX data have been acquired under clear-sky conditions over the two largest and most heavily polluted Belgian cities, i.e. Antwerp and Brussels on 15 April and 30 June 2015. Additionally, a number of background sites have been covered for the reference spectra. The APEX instrument was mounted in a Dornier DO-228 aeroplane, operated by Deutsches Zentrum für Luft- und Raumfahrt (DLR). NO2 VCDs were retrieved from spatially aggregated radiance spectra allowing urban plumes to be resolved at the resolution of 60  ×  80 m2. The main sources in the Antwerp area appear to be related to the (petro)chemical industry while traffic-related emissions dominate in Brussels. The NO2 levels observed in Antwerp range between 3 and 35  ×  1015 molec cm−2, with a mean VCD of 17.4 ± 3.7  ×  1015 molec cm−2. In the Brussels area, smaller levels are found, ranging between 1 and 20  ×  1015 molec cm−2 and a mean VCD of 7.7 ± 2.1  ×  1015 molec cm−2. The overall errors on the retrieved NO2 VCDs are on average 21 and 28 % for the Antwerp and Brussels data sets. Low VCD retrievals are mainly limited by noise (1σ slant error), while high retrievals are mainly limited by systematic errors. Compared to coincident car mobile-DOAS measurements taken in Antwerp and Brussels, both data sets are in good agreement with correlation coefficients around 0.85 and slopes close to unity. APEX retrievals tend to be, on average, 12 and 6 % higher for Antwerp and Brussels, respectively. Results demonstrate that the NO2 distribution in an urban environment, and its fine-scale variability, can be mapped accurately with high spatial resolution and in a relatively short time frame, and the contributing emission sources can be resolved. High-resolution quantitative information about the atmospheric NO2 horizontal variability is currently rare, but can be very valuable for (air quality) studies at the urban scale.

scholarly journals Classification of Urban Area Using Multispectral Indices for Urban Planning

2020 ◽  
Vol 12 (15) ◽  
pp. 2503 ◽  
Author(s):  
Philip Lynch ◽  
Leonhard Blesius ◽  
Ellen Hines
Keyword(s):  
Land Cover ◽  
Urban Area ◽  
Urban Areas ◽  
Unsupervised Classification ◽  
Condition Index ◽  
The United States ◽  
United States Geological Survey ◽  
Classification Schemes ◽  
Florida Department

An accelerating trend of global urbanization accompanying population growth makes frequently updated land use and land cover (LULC) maps critical. LULC maps have been widely created through the classification of remotely sensed imagery. Maps of urban areas have been both dichotomous (urban or non-urban) and entailing of discrete urban types. This study incorporated multispectral built-up indices, designed to enhance satellite imagery, for introducing new urban classification schemes. The indices examined are the new built-up index (NBI), the built-up area extraction index (BAEI), and the normalized difference concrete condition index (NDCCI). Landsat Level-2 data covering the city of Miami, FL, USA was leveraged with geographic data from the Florida Geospatial Data Library and Florida Department of Environmental Protection to develop and validate new methods of supervised and unsupervised classification of urban area. NBI was used to extract discrete urban features through object-oriented image analysis. BAEI was found to possess properties for visualizing and tracking urban development as a low-high gradient. NDCCI was composited with NBI and BAEI as the basis for a robust urban intensity classification scheme superior to that of the United States Geological Survey National Land Cover Database 2016. BAEI, implemented as a shadow index, was incorporated in a novel infill geosimulation of high-rise construction. The findings suggest that the proposed classification schemes are advantageous to the process of creating more detailed cartography in response to the increasing global demand.

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