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.

scholarly journals Analysis of total column CO<sub>2</sub> and CH<sub>4</sub> measurements in Berlin with WRF-GHG

2019 ◽  
Vol 19 (17) ◽  
pp. 11279-11302 ◽  
Author(s):  
Xinxu Zhao ◽  
Julia Marshall ◽  
Stephan Hachinger ◽  
Christoph Gerbig ◽  
Matthias Frey ◽  
...  
Keyword(s):  
Urban Areas ◽  
Initial Conditions ◽  
Ghg Emissions ◽  
Weather Research And Forecasting ◽  
Wind Fields ◽  
High Background ◽  
Simulated Wind ◽  
Global Population ◽  
Total Column ◽  
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. The simulated XCO2 shows quite similar trends with the measurement but with approximately 1 ppm bias, while a bias in the simulated XCH4 of around 2.7 % is found. The bias could potentially be the result of relatively high background concentrations, the errors at the tropopause height, etc. We find that an analysis using differential column methodology (DCM) works well for the XCH4 comparison, as corresponding background biases are then canceled out. From the tracer analysis, we find that the enhancement of XCH4 is highly dependent on human activities. The XCO2 enhancement 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 major sources of GHG emissions in urban areas.

Evaluation of the Surface Wind Field over Land in WRF Simulations of Hurricane Wilma (2005). Part I: Model Initialization and Simulation Validation

2021 ◽  
Author(s):  
David S. Nolan ◽  
Brian D. McNoldy ◽  
Jimmy Yunge
Keyword(s):  
Wind Field ◽  
Urban Areas ◽  
Initial Conditions ◽  
Surface Wind ◽  
South Florida ◽  
Wind Fields ◽  
Near Surface ◽  
Hurricane Wilma ◽  
Wind Analysis ◽  
Forecasting System

AbstractWhile global and regional dynamical models are used to predict the tracks and intensities of hurricanes over the ocean, these models are not currently used to predict the wind field and other impacts over land. This two-part study performs detailed evaluations of the near-surface, over-land wind fields produced in simulations of Hurricane Wilma (2005) as it traveled across South Florida. This first part describes the production of two high-resolution simulations using the Weather Research and Forecasting Model (WRF), using different boundary layer parameterizations available in WRF: the Mellor-Yamada-Janjić (MYJ) scheme and the Yonsei University (YSU) scheme. Initial conditions from the Global Forecasting System (GFS) are manipulated with a vortex bogussing technique to modify the initial intensity, size, and location of the cyclone. It is found possible through trial and error to successfully produce simulations using both the YSU and MYJ schemes that closely reproduce the track, intensity, and size of Wilma at landfall. For both schemes the storm size and structure also show good agreement with the wind fields diagnosed by H*WIND and the Tropical Cyclone Surface Wind Analysis (TCSWA). Both over water and over land, the YSU scheme has stronger winds over larger areas than MYJ, but the surface winds are more reduced in areas of greater surface roughness, particularly in urban areas. Both schemes produced very similar inflow angles over land and water. The over-land wind fields are examined in more detail in the second part of this study.

scholarly journals A Combined Approach to Improving the Regional Model Forecasts for the Rainy Season in China

2017 ◽  
Vol 145 (11) ◽  
pp. 4593-4603
Author(s):  
Yanfeng Zhao ◽  
Donghai Wang ◽  
Jianjun Xu
Keyword(s):  
Rainy Season ◽  
Large Scale ◽  
Initial Conditions ◽  
Wrf Model ◽  
Regional Model ◽  
Weather Research And Forecasting ◽  
Small Scale ◽  
Wind Fields ◽  
Accumulated Rainfall ◽  
Combined Forecasting

A combined forecasting methodology, into which the spectral nudging, lateral boundary filtering, and update initial conditions methods are incorporated, was employed in the regional Weather Research and Forecasting (WRF) Model. The intent was to investigate the potential for improving the prediction capability for the rainy season in China via using as many merits of the global model having better predictability as it does for the large-scale circulation and of the regional model as it does for the small-scale features. The combined methodology was found to be successful in improving the prediction of the regional atmospheric circulation and precipitation. It performed best for the larger magnitude precipitation, the relative humidity above 800 hPa, and wind fields below 300 hPa. Furthermore, the larger the magnitude and the longer the lead time, the more obvious is the improvement in terms of the accumulated rainfall of persistent severe rainfall events.

scholarly journals Dynamics of Cloud-Top Generating Cells in Winter Cyclones. Part I: Idealized Simulations in the Context of Field Observations

2016 ◽  
Vol 73 (4) ◽  
pp. 1507-1527 ◽  
Author(s):  
Jason M. Keeler ◽  
Brian F. Jewett ◽  
Robert M. Rauber ◽  
Greg M. McFarquhar ◽  
Roy M. Rasmussen ◽  
...  
Keyword(s):  
Vertical Velocity ◽  
Radiative Forcing ◽  
Initial Conditions ◽  
Vertical Wind Shear ◽  
Weather Research And Forecasting ◽  
Velocity Spectrum ◽  
Latent Heating ◽  
Heating Rates ◽  
Winter Storms ◽  
Radiation Parameterizations

Abstract This paper assesses the influence of radiative forcing and latent heating on the development and maintenance of cloud-top generating cells (GCs) in high-resolution idealized Weather Research and Forecasting Model simulations with initial conditions representative of the vertical structure of a cyclone observed during the Profiling of Winter Storms campaign. Simulated GC kinematics, structure, and ice mass are shown to compare well quantitatively with Wyoming Cloud Radar, cloud probe, and other observations. Sensitivity to radiative forcing was assessed in simulations with longwave-only (nighttime), longwave-and-shortwave (daytime), and no-radiation parameterizations. The domain-averaged longwave cooling rate exceeded 0.50 K h−1 near cloud top, with maxima greater than 2.00 K h−1 atop GCs. Shortwave warming was weaker by comparison, with domain-averaged values of 0.10–0.20 K h−1 and maxima of 0.50 K h−1 atop GCs. The stabilizing influence of cloud-top shortwave warming was evident in the daytime simulation’s vertical velocity spectrum, with 1% of the updrafts in the 6.0–8.0-km layer exceeding 1.20 m s−1, compared to 1.80 m s−1 for the nighttime simulation. GCs regenerate in simulations with radiative forcing after the initial instability is released but do not persist when radiation is not parameterized, demonstrating that radiative forcing is critical to GC maintenance under the thermodynamic and vertical wind shear conditions in this cyclone. GCs are characterized by high ice supersaturation (RHice &gt; 150%) and latent heating rates frequently in excess of 2.00 K h−1 collocated with vertical velocity maxima. Ice precipitation mixing ratio maxima of greater than 0.15 g kg−1 were common within GCs in the daytime and nighttime simulations.

Deceleration of sliding motorcycles (mainly scooters) in accident reconstructions

2017 ◽  
Vol 232 (7) ◽  
pp. 866-876 ◽  
Author(s):  
Carlo Cialdai ◽  
Dario Vangi ◽  
Antonio Virga
Keyword(s):  
Urban Areas ◽  
Test Session ◽  
Road Accidents ◽  
Factors Affecting ◽  
Different Types ◽  
Energy Dissipated ◽  
Comparison Of The Results ◽  
Two Wheeler ◽  
The Impact ◽  
Good Agreement

This paper presents an analysis of the situation in which a two-wheeler (i.e. a motorcycle, where the term motorcycles includes scooters) falls over to the side and then successively slides; this typically occurs in road accidents involving this type of vehicle. Knowing the deceleration rate of the sliding phase allows the kinetic energy dissipated and the speed of the motorcycle just before the fall to the ground to be calculated. These parameters are very important in the analysis and reconstruction of accidents. The work presented in this paper was developed in two experimental test sessions on fully faired motorcycles which are mainly of the scooter type and widely used in urban areas. In the first session, sliding tests were carried out, with the speed in the range 10–50 km/h, on three different types of road surface. Analysis of the evidence allowed the dissipative main phases of motion of the motorcycle (the impact with the ground, the rebounds and the stabilized swiping) to be identified and some factors affecting the phenomenon to be studied. The coefficient of average deceleration was calculated using two typical equations. The second test session consisted of drag tests. In these tests, the motorcycle, which had previously laid on its side, was dragged for a few metres at a constant speed of about 20 km/h, while the drag force was measured. A comparison of the results obtained in these tests with those obtained in the sliding tests yielded very good agreement in the coefficients of deceleration.

scholarly journals Welcome to the Ziggurat Journal of Materials Technology - a New Open Access Journal

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Jürgen Bast
Keyword(s):  
Urban Areas ◽  
Technological Progress ◽  
High Stress ◽  
Scientific Work ◽  
Open Access Journal ◽  
Human Society ◽  
New Materials ◽  
Wide Range ◽  
Global Population

Dear readers, authors and colleagues, Technological progress plays an essential role in the development of human society. The increasing global population and its mobility, the expansion of urban areas, climate protection and the conservation of fossil resources present challenges that can only be overcome by the improvement of existing resources and the development of new components, materials and production processes. Conventional materials have quickly reached their limit as new mechanisms are developed. These fields of application require the supply of new materials working in aggressive environments at extreme temperatures and high stress. These new materials are also expected to automatically alert us when critical loads are reached to avoid accidents caused by failures. This is the first issue of the Ziggurat Journal of Materials Technology, and we hope that you are satisfied with the content. The title of the journal primarily suggests materials technology; however, we strive to present a broad range of topics, including questions about the interaction between design, material, manufacturing and energy. The efficient interaction between these parameters results in components that are optimally designed and economically feasible. The idea for this journal resulted from the editors' realisation of the large knowledge potential that is being developed at colleges and universities around the world by scholars and PhD students. These clients must have the opportunity to publish their work and get in touch with other scientists. We want to reach out to young researchers and encourage them to present their work to a wide range of readers. Furthermore, a scientific career today requires evidence of publications that withstand the corresponding assessments of specialist colleagues and meet the criteria of good scientific work. In this context, the submitted articles will be subjected to a strict review. The principal objective is not to criticise work but rather to provide advice on how to improve the quality of the work presented. With this in mind, we would like to invite you to submit articles and use this journal as a reference for your ongoing scientific work.

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 Assessing the Potential of a Long-Term Climate Forecast for Cuba Using the WRF Model

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Lourdes Álvarez-Escudero ◽  
Yandy G. Mayor ◽  
Israel Borrajero-Montejo ◽  
Arnoldo Bezanilla-Morlot
Keyword(s):  
Mesoscale Model ◽  
Initial Conditions ◽  
Wrf Model ◽  
Reanalysis Data ◽  
Weather Research And Forecasting ◽  
Tropical Storms ◽  
Precipitation Regime ◽  
Wide Debate ◽  
One Year ◽  
Cumulative Precipitation

Seasonal climatic prediction studies are a matter of wide debate all over the world. Cuba, a mainly agricultural nation, should greatly benefit from the knowledge, which is available months in advance of the precipitation regime and allows for the proper management of water resources. In this work, a series of six experiments were made with a mesoscale model WRF (Weather Research and Forecasting Model) that produced a 15-month forecast for each month of cumulative precipitation starting at two dates, and for three non-consecutive years with different meteorological characteristics: one dry year (2004), one year that started dry and turned rainy (2005), and one year where several tropical storms occurred (2008). ERA-Interim reanalysis data were used for the initial and border conditions and experiments started 1 month before the beginning of the rainy and the dry seasons, respectively. In a general sense, the experience of using WRF indicated that it was a valid resource for seasonal forecast, since the results obtained were in the same range as those reported by the literature for similar cases. Several limitations were revealed by the results: the forecasts underestimated the monthly cumulative precipitation figures, tropical storms entering through the borders sometimes followed courses different from the real courses inside the working domain, storms that developed inside the domain were not reproduced by WRF, and differences in initial conditions led to significantly different forecasts for the corresponding time steps (nonlinearity). Changing the model parameterizations and initial conditions of the ensemble forecast experiments was recommended.

scholarly journals Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and CH4 in situ observations in summer 2018

2020 ◽  
Author(s):  
Theresa Klausner ◽  
Mariano Mertens ◽  
Heidi Huntrieser ◽  
Michal Galkowski ◽  
Gerrit Kuhlmann ◽  
...  
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Urban Areas ◽  
Ghg Emissions ◽  
Capital City ◽  
Detailed Knowledge ◽  
Emission Flux ◽  
Gas Emissions ◽  
Mixing Ratios

&lt;p&gt;Urban areas are recognised as a significant source of greenhouse gas emissions (GHG), such as carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) and methane (CH&lt;sub&gt;4&lt;/sub&gt;). The total amount of urban GHG emissions, especially for CH&lt;sub&gt;4&lt;/sub&gt;, however, is not well quantified. Here we report on airborne in situ measurements using a Picarro G1301-m analyser aboard the DLR Cessna Grand Caravan to study GHG emissions downwind of the German capital city Berlin. In total, five aircraft-based mass balance experiments were conducted in July 2018 within the Urban Climate Under Change [UC]&lt;sup&gt;2&lt;/sup&gt; project. The detection and isolation of the Berlin plume was often challenging because of comparatively small GHG signals above variable atmospheric background concentrations. However, on July 20&lt;sup&gt;th&lt;/sup&gt; enhancements of up to 4 ppm CO&lt;sub&gt;2&lt;/sub&gt; and 21 ppb CH&lt;sub&gt;4&lt;/sub&gt; were observed over a horizontal extent of roughly 45 to 65 km downwind of Berlin. These enhanced mixing ratios are clearly distinguishable from the background and can partly be assigned to city emissions. The estimated CO&lt;sub&gt;2&lt;/sub&gt; emission flux of 1.39 &amp;#177; 0.75 t s&lt;sup&gt;-1 &lt;/sup&gt;is in agreement with current inventories, while the CH&lt;sub&gt;4&lt;/sub&gt; emission flux of 5.20 &amp;#177; 1.61 kg s&lt;sup&gt;-1&lt;/sup&gt; is almost two times larger than the highest reported value in the inventories. We localized the source area with HYSPLIT trajectory calculations and the high resolution numerical model MECO(n) (down to ~1 km), and investigated the contribution from sewage-treatment plants and waste deposition to CH&lt;sub&gt;4&lt;/sub&gt;, which are treated differently by the emission inventories. Our work highlights the importance of a) strong CH&lt;sub&gt;4&lt;/sub&gt; sources in the surroundings of Berlin and b) a detailed knowledge of GHG inflow mixing ratios to suitably estimate emission rates.&lt;/p&gt;

scholarly journals Effects of land use and water quality on greenhouse gas emissions from an urban river system

2020 ◽  
Author(s):  
Long Ho ◽  
Ruben Jerves-Cobo ◽  
Matti Barthel ◽  
Johan Six ◽  
Samuel Bode ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Urban Areas ◽  
Anthropogenic Activities ◽  
Ghg Emissions ◽  
Flow Characteristics ◽  
River System ◽  
Urban River ◽  
Polluted Water ◽  
Land Use Types

Abstract. Rivers act as a natural source of greenhouse gases (GHGs) that can be released from the metabolisms of aquatic organisms. Anthropogenic activities can largely alter the chemical composition and microbial communities of rivers, consequently affecting their GHG emissions. To investigate these impacts, we assessed the emissions of CO2, CH4, and N2O from Cuenca urban river system (Ecuador). High variation of the emissions was found among river tributaries that mainly depended on water quality and neighboring landscapes. By using Prati and Oregon Indexes, a clear pattern was observed between water quality and GHG emissions in which the more polluted the sites were, the higher were their emissions. When river water quality deteriorated from acceptable to very heavily polluted, their global warming potential (GWP) increased by ten times. Compared to the average estimated emissions from global streams, rivers with polluted water released almost double the estimated GWP while the proportion increased to ten times for very heavily polluted rivers. Conversely, the GWP of good-water-quality rivers was half of the estimated GWP. Furthermore, surrounding land-use types, i.e. urban, roads, and agriculture, significantly affected the river emissions. The GWP of the sites close to urban areas was four time higher than the GWP of the nature sites while this proportion for the sites close to roads or agricultural areas was triple and double, respectively. Lastly, by applying random forests, we identified dissolved oxygen, ammonium, and flow characteristics as the main important factors to the emissions. Conversely, low impact of organic matter and nitrate concentration suggested a higher role of nitrification than denitrification in producing N2O. These results highlighted the impacts of land-use types on the river emissions via water contamination by sewage discharges and surface runoff. Hence, to estimate of the emissions from global streams, both their quantity and water quality should be included.

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