scholarly journals Assessment of the Weather Research and Forecasting model implementation in Cuba addressed to diagnostic air quality modeling

2013 ◽  
Vol 4 (1) ◽  
pp. 64-74 ◽  
Author(s):  
Leonor Turtos Carbonell ◽  
Gil Capote Mastrapa ◽  
Yasser Fonseca Rodriguez ◽  
Lourdes Alvarez Escudero ◽  
Madeleine Sanchez Gacita ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Quality Modeling ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Quality Modeling ◽  
Weather Research

scholarly journals Why do models perform differently on particulate matter over East Asia? A multi-model intercomparison study for MICS-Asia III

2020 ◽  
Vol 20 (12) ◽  
pp. 7393-7410 ◽  
Author(s):  
Jiani Tan ◽  
Joshua S. Fu ◽  
Gregory R. Carmichael ◽  
Syuichi Itahashi ◽  
Zhining Tao ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
East Asia ◽  
Dust Emission ◽  
Sulfur Oxidation ◽  
Atmospheric Modeling ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Air Quality Prediction ◽  
Weather Research

Abstract. This study compares the performance of 12 regional chemical transport models (CTMs) from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III) on simulating the particulate matter (PM) over East Asia (EA) in 2010. The participating models include the Weather Research and Forecasting model coupled with Community Multiscale Air Quality (WRF-CMAQ; v4.7.1 and v5.0.2), the Regional Atmospheric Modeling System coupled with CMAQ (RAMS-CMAQ; v4.7.1 and v5.0.2), the Weather Research and Forecasting model coupled with chemistry (WRF-Chem; v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASA-Unified WRF (NU-WRF). This study investigates three model processes as the possible reasons for different model performances on PM. (1) Models perform very differently in the gas–particle conversion of sulfur (S) and oxidized nitrogen (N). The model differences in sulfur oxidation ratio (50 %) are of the same magnitude as that in SO42- concentrations. The gas–particle conversion is one of the main reasons for different model performances on fine mode PM. (2) Models without dust emission modules can perform well on PM10 at non-dust-affected sites but largely underestimate (up to 50 %) the PM10 concentrations at dust sites. The implementation of dust emission modules in the models has largely improved the model accuracies at dust sites (reduce model bias to −20 %). However, both the magnitude and distribution of dust pollution are not fully captured. (3) The amounts of modeled depositions vary among models by 75 %, 39 %, 21 % and 38 % for S wet, S dry, N wet and N dry depositions, respectively. Large inter-model differences are found in the washout ratios of wet deposition (at most 170 % in India) and dry deposition velocities (generally 0.3–2 cm s−1 differences over inland regions).

Sensitivity of the Weather Research and Forecast/Community Multiscale Air Quality modeling system to MODIS LAI, FPAR, and albedo

2015 ◽  
Vol 120 (16) ◽  
pp. 8491-8511 ◽  
Author(s):  
Limei Ran ◽  
Robert Gilliam ◽  
Francis S. Binkowski ◽  
Aijun Xiu ◽  
Jonathan Pleim ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Quality Modeling ◽  
Quality Modeling ◽  
Modis Lai ◽  
Weather Research ◽  
Weather Research And Forecast

scholarly journals Comment on “Simulation of Surface Ozone Pollution in the Central Gulf Coast Region Using WRF/Chem Model: Sensitivity to PBL and Land Surface Physics”

2011 ◽  
Vol 2011 ◽  
pp. 1-3 ◽  
Author(s):  
Jonathan E. Pleim
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Land Surface ◽  
Gulf Coast ◽  
Surface Ozone ◽  
Air Quality Modeling ◽  
Weather Research And Forecasting ◽  
Ozone Pollution ◽  
Quality Modeling ◽  
Gulf Coast Region

A recently published meteorology and air quality modeling study has several serious deficiencies deserving comment. The study uses the weather research and forecasting/chemistry (WRF/Chem) model to compare and evaluate boundary layer and land surface modeling options. The most serious of the study's deficiencies is reporting WRF/Chem results for both meteorological and chemical quantities using the asymmetric convective model version 2 (ACM2). While the ACM2 is a valid model option for WRF, it has not yet been implemented for the chemical portion of the WRF/Chem model. Hence, the reported air quality modeling results using ACM2 are invalid. Furthermore, publication of these results gives the erroneous impression that the ACM2 model is not well suited for air quality applications when, in fact, it is the default boundary layer model in the community multiscale air quality (CMAQ) model.

scholarly journals Land-Use Improvements in the Weather Research and Forecasting Model over Complex Mountainous Terrain and Comparison of Different Grid Sizes

2021 ◽  
Author(s):  
Alessio Golzio ◽  
Silvia Ferrarese ◽  
Claudio Cassardo ◽  
Gugliemina Adele Diolaiuti ◽  
Manuela Pelfini
Keyword(s):  
Boundary Layer ◽  
Land Use ◽  
Land Cover ◽  
Mixing Layer ◽  
Local Area ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Mountainous Terrain ◽  
Weather Research

AbstractWeather forecasts over mountainous terrain are challenging due to the complex topography that is necessarily smoothed by actual local-area models. As complex mountainous territories represent 20% of the Earth’s surface, accurate forecasts and the numerical resolution of the interaction between the surface and the atmospheric boundary layer are crucial. We present an assessment of the Weather Research and Forecasting model with two different grid spacings (1 km and 0.5 km), using two topography datasets (NASA Shuttle Radar Topography Mission and Global Multi-resolution Terrain Elevation Data 2010, digital elevation models) and four land-cover-description datasets (Corine Land Cover, U.S. Geological Survey land-use, MODIS30 and MODIS15, Moderate Resolution Imaging Spectroradiometer land-use). We investigate the Ortles Cevadale region in the Rhaetian Alps (central Italian Alps), focusing on the upper Forni Glacier proglacial area, where a micrometeorological station operated from 28 August to 11 September 2017. The simulation outputs are compared with observations at this micrometeorological station and four other weather stations distributed around the Forni Glacier with respect to the latent heat, sensible heat and ground heat fluxes, mixing-layer height, soil moisture, 2-m air temperature, and 10-m wind speed. The different model runs make it possible to isolate the contributions of land use, topography, grid spacing, and boundary-layer parametrizations. Among the considered factors, land use proves to have the most significant impact on results.

scholarly journals Emission Inventories and Particulate Matter Air Quality Modeling over the Pearl River Delta Region

2021 ◽  
Vol 18 (8) ◽  
pp. 4155
Author(s):  
Diogo Lopes ◽  
Joana Ferreira ◽  
Ka In Hoi ◽  
Ka-Veng Yuen ◽  
Kai Meng Mok ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pearl River Delta ◽  
Air Quality Modeling ◽  
Pearl River ◽  
Emission Inventories ◽  
Atmospheric Emission ◽  
The Pearl River Delta ◽  
Quality Modeling ◽  
The Pearl River

The Pearl River Delta (PRD) region is located on the southeast coast of mainland China and it is an important economic hub. The high levels of particulate matter (PM) in the atmosphere, however, and poor visibility have become a complex environmental problem for the region. Air quality modeling systems are useful to understand the temporal and spatial distribution of air pollution, making use of atmospheric emission data as inputs. Over the years, several atmospheric emission inventories have been developed for the Asia region. The main purpose of this work is to evaluate the performance of the air quality modeling system for simulating PM concentrations over the PRD using three atmospheric emission inventories (i.e., EDGAR, REAS and MIX) during a winter and a summer period. In general, there is a tendency to underestimate PM levels, but results based on the EDGAR emission inventory show slightly better accuracy. However, improvements in the spatial and temporal disaggregation of emissions are still needed to properly represent PRD air quality. This study’s comparison of the three emission inventories’ data, as well as their PM simulating outcomes, generates recommendations for future improvements to atmospheric emission inventories and our understanding of air pollution problems in the PRD region.

Indoor air quality modeling: Compartmental approach with reactive chemistry

1982 ◽  
Vol 8 (1-6) ◽  
pp. 461-471 ◽  
Author(s):  
H. Özkaynak ◽  
P.B. Ryan ◽  
G.A. Allen ◽  
W.A. Turner
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Air Quality Modeling ◽  
Quality Modeling

Parallelization Strategies for the GPS Radio Occultation Data Assimilation with a Nonlocal Operator in the Weather Research and Forecasting Model

2014 ◽  
Vol 31 (9) ◽  
pp. 2008-2014 ◽  
Author(s):  
Xin Zhang ◽  
Ying-Hwa Kuo ◽  
Shu-Ya Chen ◽  
Xiang-Yu Huang ◽  
Ling-Feng Hsiao
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Observation Operator ◽  
Gps Radio Occultation ◽  
Phase Observation ◽  
Excess Phase ◽  
Weather Research

Abstract The nonlocal excess phase observation operator for assimilating the global positioning system (GPS) radio occultation (RO) sounding data has been proven by some research papers to produce significantly better analyses for numerical weather prediction (NWP) compared to the local refractivity observation operator. However, the high computational cost and the difficulties in parallelization associated with the nonlocal GPS RO operator deter its application in research and operational NWP practices. In this article, two strategies are designed and implemented in the data assimilation system for the Weather Research and Forecasting Model to demonstrate the capability of parallel assimilation of GPS RO profiles with the nonlocal excess phase observation operator. In particular, to solve the parallel load imbalance problem due to the uneven geographic distribution of the GPS RO observations, round-robin scheduling is adopted to distribute GPS RO observations among the processing cores to balance the workload. The wall clock time required to complete a five-iteration minimization on a demonstration Antarctic case with 106 GPS RO observations is reduced from more than 3.5 h with a single processing core to 2.5 min with 106 processing cores. These strategies present the possibility of application of the nonlocal GPS RO excess phase observation operator in operational data assimilation systems with a cutoff time limit.

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