Impact of anthropogenic heat emissions on meteorological parameters and air quality in Beijing using a high-resolution model simulation

2021 ◽  
Vol 16 (4) ◽  
Author(s):  
Hengrui Tao ◽  
Jia Xing ◽  
Gaofeng Pan ◽  
Jonathan Pleim ◽  
Limei Ran ◽  
...  
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Meteorological Parameters ◽  
Model Simulation ◽  
Anthropogenic Heat ◽  
Resolution Model ◽  
High Resolution Model

An Assessment of Winter Orographic Precipitation and Cloud-Seeding Potential in Wyoming

2020 ◽  
Vol 59 (7) ◽  
pp. 1217-1238 ◽  
Author(s):  
Sarah A. Tessendorf ◽  
Kyoko Ikeda ◽  
Courtney Weeks ◽  
Roy Rasmussen ◽  
Jamie Wolff ◽  
...  
Keyword(s):  
High Resolution ◽  
Model Simulation ◽  
Orographic Precipitation ◽  
Atmospheric Conditions ◽  
Cloud Seeding ◽  
Mountain Ranges ◽  
Precipitation Patterns ◽  
Resolution Model ◽  
Orographic Clouds ◽  
High Resolution Model

AbstractThis paper presents an evaluation of the precipitation patterns and seedability of orographic clouds in Wyoming using SNOTEL precipitation data and a high-resolution multiyear model simulation over an 8-yr period. A key part of assessing the potential for cloud seeding is to understand the natural precipitation patterns and how often atmospheric conditions and clouds meet cloud-seeding criteria. The analysis shows that high-resolution model simulations are useful tools for studying patterns of orographic precipitation and establishing the seedability of clouds by providing information that is either missed by or not available from current observational networks. This study indicates that the ground-based seeding potential in some mountain ranges in Wyoming is limited by flow blocking and/or prevailing winds that were not normal to the barrier to produce upslope flow. Airborne seeding generally had the most potential for all of the mountain ranges that were studied.

scholarly journals Unraveling Climatic Wind and Wave Trends in the Red Sea Using Wave Spectra Partitioning

2018 ◽  
Vol 31 (5) ◽  
pp. 1881-1895 ◽  
Author(s):  
Sabique Langodan ◽  
Luigi Cavaleri ◽  
Angela Pomaro ◽  
Jesus Portilla ◽  
Yasser Abualnaja ◽  
...  
Keyword(s):  
High Resolution ◽  
Mediterranean Sea ◽  
Red Sea ◽  
Model Simulation ◽  
Wave Spectra ◽  
Weather Pattern ◽  
Partition Technique ◽  
Resolution Model ◽  
High Resolution Model ◽  
Sea Wind

The wind and wave climatology of the Red Sea is derived from a validated 30-yr high-resolution model simulation. After describing the relevant features of the basin, the main wind and wave systems are identified by using an innovative spectral partition technique to explain their genesis and characteristics. In the northern part of the sea, wind and waves of the same intensity are present throughout the year, while the central and southern zones are characterized by a marked seasonality. The partition technique allows the association of a general decrease in the energy of the different wave systems with a specific weather pattern. The most intense decrease is found in the northern storms, which are associated with meteorological pulses from the Mediterranean Sea.

scholarly journals Nudging technique for scale bridging in air quality/climate atmospheric composition modelling

2012 ◽  
Vol 12 (8) ◽  
pp. 3677-3685 ◽  
Author(s):  
A. Maurizi ◽  
F. Russo ◽  
M. D'Isidoro ◽  
F. Tampieri
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Hot Spot ◽  
Atmospheric Composition ◽  
Po Valley ◽  
Model Response ◽  
Wide Range ◽  
Resolution Model ◽  
High Resolution Model ◽  
One Year

Abstract. The interaction between air quality and climate involves dynamical scales that cover a very wide range. Bridging these scales in numerical simulations is fundamental in studies devoted to megacity/hot-spot impacts on larger scales. A technique based on nudging is proposed as a bridging method that can couple different models at different scales. Here, nudging is used to force low resolution chemical composition models with a run of a high resolution model on a critical area. A one-year numerical experiment focused on the Po Valley hot spot is performed using the BOLCHEM model to asses the method. The results show that the model response is stable to perturbation induced by the nudging and that, taking the high resolution run as a reference, performances of the nudged run increase with respect to the non-forced run. The effect outside the forcing area depends on transport and is significant in a relevant number of events although it becomes weak on seasonal or yearly basis.

scholarly journals Emissions Preparation and Analysis for Multiscale Air Quality Modelling over the Athabasca Oil Sands Region of Alberta, Canada

2018 ◽  
Author(s):  
Junhua Zhang ◽  
Michael D. Moran ◽  
Qiong Zheng ◽  
Paul A. Makar ◽  
Pegah Baratzadeh ◽  
...  
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Field Study ◽  
Oil Sands ◽  
Surface Mining ◽  
So2 Emissions ◽  
Emissions Inventory ◽  
Athabasca Oil Sands Region ◽  
Resolution Model ◽  
High Resolution Model

Abstract. The oil sands of Alberta, Canada are classified as unconventional oil, but they are also the third-largest oil reserves in the world, behind only Venezuela and Saudi Arabia. We describe here a six-year effort to improve the emissions data used for air quality (AQ) modelling of the roughly 100 km x 100 km oil extraction and processing industrial complex operating in the Athabasca Oil Sands Region (AOSR) of north-eastern Alberta. The objective of this work was to review the available emissions data, provide information for comparison with observation-based emissions estimates, and generate model-ready emissions files for the Global Environmental Multiscale–Modelling Air-quality and CHemistry (GEM-MACH) AQ modelling system for application to the AOSR. GEM-MACH was used to produce nested AQ forecasts during an AQ field study carried out in the AOSR in summer 2013 as well as ongoing experimental forecasts since then and retrospective model simulations and analyses for the field-study period. This paper discusses the generation of GEM-MACH emissions input files, in particular for a high-resolution model domain with 2.5-km grid spacing covering much of western Canada and centred over the AOSR. Prior to the field study, ten pre-2013 national, provincial, or sub-provincial emissions inventories for up to seven criteria-air-contaminant species (NOx, VOC, SO2, NH3, CO, PM2.5, and PM10) that covered the AOSR study area and that had been compiled for various purposes were reviewed, and then a detailed hybrid emissions inventory was created by combining the best available emissions data from some of these ten inventories. After the field study, additional sources of emissions-related data became available, including 2013 hourly SO2 and NOx emissions and stack characteristics for large point sources measured by Continuous Emission Monitoring Systems, 2013-specific national inventories, daily reports of SO2 emissions from one AOSR facility for a one-week period during the field campaign when that facility experienced upset conditions, aircraft measurements of VOC and PM2.5 concentrations from the 2013 field campaign and derived estimates of their emissions, and measurements of chemical composition of dust collected from various AOSR sites. These new data were used to generate updated emissions input files for various post-campaign GEM-MACH sensitivity studies. Their inclusion resulted in some significant emissions revisions, including a reduction in total VOC and SO2 emissions from surface mining facilities of about 40 % and 20 %, respectively, and a ten-fold increase in PM2.5 emissions based on aircraft observations. In addition, standard emissions processing approaches could not provide an accurate representation of emissions from such large, unconventional emissions sources as AOSR surface mines. In order to generate more accurate high-resolution, model-ready emissions files, AOSR-specific improvements were made to the emissions processing methodology. To account for the urban-scale spatial extent of the AOSR mining facilities and the high-resolution 2.5-km model grid, novel facility-specific gridded spatial surrogate fields were generated using spatial information from GIS (geographic information system) shapefiles and satellite images to allocate emissions spatially within each mining facility. Facility- and process-specific temporal profiles and VOC speciation profiles were also developed. The pre-2013 vegetation and land-use data bases normally used to estimate biogenic emissions and meteorological surface properties were modified to account for the rapid change of land use in the study area due to marked, year-by-year changes in surface mining activities, including the 2013 opening of a new mine. Lastly, mercury emissions data were also processed to support AOSR mercury modelling activities. The combination of emissions inventory updates and methodological improvements to emissions processing has resulted in a more representative and more accurate set of emissions input files to support AQ modelling to predict the ecosystem impacts of AOSR air pollutant emissions. Seven other papers in this special issue used some of these new sets of emissions input files.

scholarly journals Representativity error for temperature and humidity using the Met Office high‐resolution model†

2013 ◽  
Vol 140 (681) ◽  
pp. 1189-1197 ◽  
Author(s):  
J. A. Waller ◽  
S. L. Dance ◽  
A. S. Lawless ◽  
N. K. Nichols ◽  
J. R. Eyre
Keyword(s):  
High Resolution ◽  
Temperature And Humidity ◽  
Resolution Model ◽  
High Resolution Model
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