Atmosphere data assimilation system for the Siberian region with the WRF-ARW model and three-dimensional variational analysis WRF 3D-Var

Zaripov, R. B.; Martynova, Yu. V.; Krupchatnikov, V. N.; Петров, А. П.

doi:10.3103/s1068373916110091

Cited by 7 publications

(3 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The average elevation is approximately 400 m. Chengdu is currently the largest economy in the Sichuan Basin. As of 2017, Chengdu had a resident population of 16.04 million and a GDP (Gross Domestic Product) of 1388.9 billion.…”

Section: Study Areamentioning

confidence: 99%

“…The WRF model can be applied not only to the prediction of climate change but also to climate analyses, and the WRF meteorological numerical simulation model consists of two modules. The WRF Preprocessing System (WPS) module is a data preprocessing system for FNL meteorological data in the WRF model, and WRFV3 is a parallel module in the WRF model [16,17]. The WRF numerical model has a very wide spatial simulation scale.…”

Section: Mesoscale Meteorological Model Numerical Simulationmentioning

confidence: 99%

See 1 more Smart Citation

Study on Land-use Changes and Their Impacts on Air Pollution in Chengdu

et al. 2019

View full text Add to dashboard Cite

The expansion of urban areas and the increase in the number of buildings and urbanization characteristics, such as roads, affect the meteorological environment in urban areas, resulting in weakened pollutant dispersion. First, this paper uses GIS (geographic information system) spatial analysis technology and landscape ecology analysis methods to analyze the dynamic changes in land cover and landscape patterns in Chengdu as a result of urban development. Second, the most appropriate WRF (Weather Research and Forecasting) model parameterization scheme is selected and screened. Land-use data from different development stages in the city are included in the model, and the wind speed and temperature results simulated using new and old land-use data (1980 and 2015) are evaluated and compared. Finally, the results of the numerical simulations by the WRF-Chem air quality model using new and old land-use data are coupled with 0.25 • × 0.25 • -resolution MEIC (Multi-resolution Emission Inventory for China) emission source data from Tsinghua University. The results of the sensitivity experiments using the WRF-Chem model for the city under different development conditions and during different periods are discussed. The meteorological conditions and pollution sources remained unchanged as the land-use data changed, which revealed the impact of urban land-use changes on the simulation results of PM 2.5 atmospheric pollutants. The results show the following. (1) From 1980 to 2015, the land-use changes in Chengdu were obvious, and cultivated land exhibited the greatest changes, followed by forestland. Under the influence of urban land-use dynamics and human activities, both the richness and evenness of the landscape in Chengdu increased.(2) The microphysical scheme WSM3 (WRF Single-Moment 3 class) and land-surface scheme SLAB (5-layer diffusion scheme) were the most suitable for simulating temperatures and wind speeds in the WRF model. The wind speed and temperature simulation results using the 2015 land-use data were better than those using the 1980 land-use data when assessed according to the coincidence index and correlation coefficient. (3) The WRF-Chem simulation results obtained for PM 2.5 using the 2015 land-use data were better than those obtained using the 1980 land-use data in terms of the correlation coefficient and standard deviation. The concentration of PM 2.5 in urban areas was higher than that in the suburbs, and the concentration of PM 2.5 was lower on Longquan Mountain in Chengdu than in the surrounding areas.

show abstract

Section: Study Areamentioning

confidence: 99%

Section: Mesoscale Meteorological Model Numerical Simulationmentioning

confidence: 99%

Study on Land-use Changes and Their Impacts on Air Pollution in Chengdu

et al. 2019

View full text Add to dashboard Cite

show abstract

“…On the basis of Bayes' theorem, Lorenc (1986) gave an analysis method for estimating the initial-value, which is now known as 3D-Var and widely used all over the world (Chouinard, 2003;Brousseau et al, 2015;Liu et al, 2016;Zaripov et al, 2016;Wang et al, 2017). In his paper, Lorenc laid the mathematical foundation of 3D-Var.…”

Section: Introductionmentioning

confidence: 99%

A Preliminary Study on Dimension-Reduction Algorithm for Variational Methods in Three Dimensions

Chen¹

2018

Preprint

View full text Add to dashboard Cite

Numerical weather prediction is an initial-value problem, for determination of the initial conditions, there are many methods and one of the most classical methods is variational methods in three dimensions, or 3D-Var. In this approach, with a defined cost function proportional to the square of the distance between the analysis and both the background and the observations, one can obtain the analysis. In the cost function, the background and the observations are reshaped to vectors; within this step, the order of the background error covariance matrix and the observational error covariance matrix becomes huge, which is not convenient to one to obtain the analysis. In this paper, according to the matrix analysis approach, we put forward some possible improvements to the dimension-reduction algorithm of 3D-Var, so that provide some references for data assimilation.

show abstract

Comparing the performances of WRF QPF and PERSIANN-CCS QPEs in karst flood simulation and forecasting by coupling the Karst-Liuxihe model

Yuan

Sun

et al. 2021

Front. Earth Sci.

View full text Add to dashboard Cite

Atmosphere data assimilation system for the Siberian region with the WRF-ARW model and three-dimensional variational analysis WRF 3D-Var

Cited by 7 publications

References 27 publications

Study on Land-use Changes and Their Impacts on Air Pollution in Chengdu

Study on Land-use Changes and Their Impacts on Air Pollution in Chengdu

A Preliminary Study on Dimension-Reduction Algorithm for Variational Methods in Three Dimensions

Comparing the performances of WRF QPF and PERSIANN-CCS QPEs in karst flood simulation and forecasting by coupling the Karst-Liuxihe model

Contact Info

Product

Resources

About