The development of METAL-WRF Regional Model for the description of dust mineralogy in the atmosphere

The mineralogical composition of airborne dust particles is an important but often neglected parameter for several physiochemical processes, such as atmospheric radiative transfer and ocean biochemistry. We present the development of the METAL-WRF module for the simulation of the composition of desert dust minerals in atmospheric aerosols. The new development is based on the GOCART-AFWA dust module of WRF-Chem. A new wet deposition scheme has been implemented in the dust module alongside the existing dry deposition scheme. The new model includes separate prognostic fields for nine (9) minerals: illite, kaolinite, smectite, calcite, quartz, feldspar, hematite, gypsum, and phosphorus, derived from the GMINER30 database and also iron derived from the FERRUM30 database. Two regional model sensitivity studies are presented for dust events that occurred in August and December 2017, which include a comparison of the model versus elemental dust composition measurements performed in the North Atlantic (at Izaña Observatory, Tenerife Island) and in the eastern Mediterranean (at Agia Marina Xyliatos station, Cyprus Island). The results indicate the important role of dust minerals, as dominant aerosols, for the greater region of North Africa, South Europe, the North Atlantic, and the Middle East, including the dry and wet depositions away from desert sources. Overall, METAL-WRF was found to be capable of reproducing the relative abundances of the different dust minerals in the atmosphere. In particular, the concentration of iron (Fe), which is an important element for ocean biochemistry and solar absorption, was modeled in good agreement with the corresponding measurements at Izaña Observatory (22% overestimation) and at Agia Marina Xyliatos site (4% overestimation). Further model developments, including the implementation of newer surface mineralogical datasets, e.g., from the NASA-EMIT satellite mission, can be implemented in the model to improve its accuracy.This study was supported by the Hellenic Foundation for Research and Innovation project Mineralogy of Dust Emissions and Impacts on Environment and Health (MegDeth - HFRI no. 703). Part of this study was conducted within the framing of the AERO-EXTREME (PID2021-125669NB-I00) project funded by the State Research Agency/Agencia Estatal de Investigación of Spain and the European Regional Development Funds

Modelado de la concentración de partículas PM10 en Costa Rica mediante el uso del modelo WRF-Chem

RESUMEN En el presente trabajo de investigación se analizan, por primera vez en el país, los niveles de concentración de PM10, utilizando simulaciones numéricas realizadas con el modelo WRF (Weather Research and Forecasting) y su acople químico. Además, se utilizan mediciones de PM10 provenientes de la Red de Monitoreo de Partículas de la Universidad Nacional, para evaluar el desempeño del modelo. En cuanto a las variables meteorológicas, los datos de Reanálisis ERAInterim provenientes del ECMWF con resolución de 0,75 grados proveen las condiciones iniciales y de frontera para el modelo WRF-Chem. El modelado se realizó durante el periodo del 01 al 15 de agosto del año 2013, tiempo en el cual se presenció un evento de intrusión de polvos provenientes del desierto de Sahara y el Sahel en la Capa Límite Atmosférica de Costa Rica. El dominio seleccionado para este proyecto va desde una latitud de 0° a 40°N, y una longitud desde los 40°E hasta los 90°O, con una resolución espacial de 25 x 25 Km. Para las simulaciones, se utilizaron 3 distintos esquemas de polvo: GOCART, GOCART con modificaciones AFWA, y GOCART con modificaciones UoC. Todos los esquemas evidenciaron niveles de concentración de PM10 durante el periodo del evento de intrusión de polvo al sector costarricense. Lo anterior permitió visualizar el transporte de polvo desde la región africana hasta el Caribe y Centroamérica, atravesando el Océano Atlántico producto de las condiciones meteorológicas. En cuanto a las mediciones, el esquema de polvo AFWA obtuvo la mejor correlación; sin embargo, en relación con los demás parámetros estadísticos calculados, el esquema UoC obtuvo el mejor desempeño en la evaluación realizada. El error medio para este esquema obtuvo resultados muy acertados con respecto a las referencias consultadas. Algunos otros parámetros como la desviación estándar y la raíz del error cuadrático medio confirman que el esquema UoC obtuvo los resultados más favorables. El análisis de lluvia y viento se utilizó como herramienta para la búsqueda de posibles errores en los resultados obtenidos. Por un lado, se concluyó que la lluvia modelada fue ligeramente distinta en relación con las observaciones, siendo esta una posible causa de error debido a la estrecha relación que tienen los aerosoles con esta variable. Por otro lado, la magnitud de viento simulada no presentó grandes diferencias respecto a las mediciones observadas. El trabajo presentado es un primer paso hacia una gestión más efectiva de la calidad del aire en Costa Rica, debido a que el modelo toma en cuenta variables meteorológicas y características geográficas que permiten representar la contaminación atmosférica con un criterio técnico más completo. Los mandatarios encargados de la legislación ambiental y salud podrían utilizar como base este estudio para promover actividades operativas y de pronóstico de contaminantes atmosféricos que afectan la salud humana.ABSTRACT In this study, for the first time in the country, the PM10 concentration levels are analyzed, using numerical simulations performed with the WRF (Weather Research and Forecasting) model and its chemical coupling. Furthermore, PM10 measurements from the Particle Monitoring Network of the Universidad Nacional of Costa Rica are used to evaluate the performance of the model. Regarding the meteorological variables, the ERA-Interim Reanalysis data from the ECMWF with a resolution of 0.75 degrees provide the initial and boundary conditions for the WRFChem model. The modeling was carried out from 1 to 15 August 2013. During this period, an event of dust intrusion from the Sahara and Sahel desert was witnessed in the Atmospheric Boundary Layer of Costa Rica. The domain selected for this project ranges from a latitude of 0 ° to 40 ° N, and a longitude from 40 ° E to 90 ° W, with a spatial resolution of 25 x 25 km. For the simulations, three different dust schemes were used: GOCART, GOCART with AFWA modifications, and GOCART with UoC modifications. All the schemes showed PM10 concentration levels, during the period of the dust intrusion event, in the Costa Rican sector. This allowed to visualize the dust transport from the African region to the Caribbean and Central American one, crossing the Atlantic Ocean due to weather conditions. The AFWA dust scheme obtained the best correlation in terms of measurements; however, regarding the other statistical parameters calculated, the UoC scheme obtained the best performance in the evaluation carried out. The mean error for this scheme obtained very accurate results with respect to the references consulted. Some other parameters such as the standard deviation and the root mean square error confirmed that the UoC scheme obtained the most favorable results. The analysis of rain accumulation and wind magnitude was used as a tool to search for possible errors in the results obtained. On one hand, it was concluded that the modeled rain was slightly different regarding the observations, being a possible cause of error due to the close relationship that aerosols have with this variable in the atmospheric system. On the other hand, the simulated wind magnitude did not show major differences with the observed measurements. The work presented is a first step towards a more effective management of air quality in Costa Rica, since the model takes into consideration meteorological variables and geographical features that allow air pollution representation with a more comprehensive technical criterion. The leaders responsible for the environmental and health legislation could use this study as a basis to promote operating and forecasting activities of air pollutants that affect human health.RESUMO No presente trabalho, os níveis de concentração de PM10 são analisados pela primeira vez no país, usando simulações numéricas realizadas com o modelo WRF (Weather Research and Forecasting) e seu acoplamento químico. Além disso, as medições de PM10 da Rede de Monitoramento de Partículas da Universidade Nacional da Costa Rica são usadas para avaliar o desempenho do modelo. Com relação às variáveis meteorológicas, os dados de Reanálise ERAInterim do ECMWF com uma resolução de 0,75 graus fornecem as condições iniciais e de fronteira para o modelo WRF-Chem. A modelagem foi realizada de 1 a 15 de agosto de 2013, período em que um evento de intrusão de poeiras do deserto do Saara e do Sahel foi testemunhado na Camada Limite Atmosférica da Costa Rica. O domínio selecionado para este projeto vai de uma latitude de 0 ° a 40 ° N e uma longitude de 40 ° E a 90 ° W, com uma resolução espacial de 25 x 25 km. Para as simulações, foram utilizados três esquemas de poeira diferentes: GOCART, GOCART com modificações AFWA e GOCART com modificações UoC. Todos os esquemas mostraram níveis de concentração de PM10 durante o período do evento de intrusão de poeira no setor da Costa Rica. Isso permitiu visualizar o transporte de poeira da região da África até o Caribe e a América Central, atravessando o Oceano Atlântico devido às condições climáticas. Quanto às medições, o esquema de poeira AFWA obteve a melhor correlação; no entanto, em relação aos demais parâmetros estatísticos calculados, o esquema UoC obteve o melhor desempenho na avaliação realizada. O erro médio deste esquema obteve resultados muito precisos com respeito às referências consultadas. Alguns outros parâmetros, como o desvio padrão e a raiz do erro quadrático médio, confirmam que o esquema UoC obteve os resultados mais favoráveis. A análise da precipitação acumulada e da magnitude do vento foi utilizada como ferramenta para buscar possíveis erros nos resultados obtidos. Por um lado, concluiu-se que a precipitação modelada foi ligeiramente diferente em relação às observações, sendo esta uma possível causa de erro devido à estreita relação que os aerossóis mantêm com essa variável no sistema atmosférico. Por outro lado, a magnitude do vento simulada não apresentou grandes diferenças em relação às medições observadas. O trabalho apresentado é o primeiro passo para uma gestão mais eficaz da qualidade do ar na Costa Rica, dado que o modelo leva em consideração variáveis meteorológicas e características geográficas que permitem representar a poluição atmosférica com um critério técnico mais completo. Os mandatários responsáveis pela legislação ambiental e de saúde poderiam usar este estudo como base para promover atividades operacionais e de previsão de poluentes atmosféricos que afetam a saúde humana.Centro Nacional de Alta Tecnología//CeNAT/Costa RicaUCR::Vicerrectoría de Investigación::Sistema de Estudios de Posgrado::Ciencias Básicas::Maestría Académica en Ciencias de la Atmósfer

Remote Sensing of Precipitation: Volume 2

Precipitation is a well-recognized pillar in global water and energy balances. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earth’s atmosphere–ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne

Extension of WRF-Chem for birch pollen modelling – a case study for Poland.

In recent years, allergies due to airborne pollen have shown an increasing trend, along with the severity of allergic symptoms in most industrialised countries, while synergism with other common atmospheric pollutants has also been identified as affecting the overall quality of citizenly’ life. In this study we propose the state-of-the-art WRF-Chem model, which is a complex Eulerian meteorological model integrated on-line with atmospheric chemistry. We used a combination of the WRF-Chem extended towards birch pollen, and the emission module based on heating degree days, which has not been tested before. The simulations were run for the moderate season in terms of birch pollen concentrations (year 2015) and high season (year 2016) over Central Europe, which were validated against 11 observational stations located in Poland. The results show that there is a big difference in the model’s performance for the two modelled years. In general, the model overestimates birch pollen concentrations for the moderate season and highly underestimates birch pollen concentrations for the year 2016. The model was able to predict birch pollen concentrations for first allergy symptoms (above 20 pollen m-3) as well as for severe symptoms (above 90 pollen m-3) with Probability of Detection at 0.78 and 0.68 and Success Ratio at 0.75 and 0.57, respectively for the year 2015. However, the model failed to reproduce these parameters for the year 2016. The results indicate the potential role of correcting the total seasonal pollen emission in improving the model’s performance, especially for specific years in terms of pollen productivity. The application of chemical transport models such as WRF-Chem for pollen modelling provides a great opportunity for simultaneous simulations of chemical air pollution and allergic pollen with one goal, which is a step forward for studying and understanding the co-exposure of these particles in the air

The impact of data assimilation into the meteorological WRF model on birch pollen modelling

We analyse the impact of ground-based data assimilation to theWeather Research and Forecasting (WRF) meteorological model on parameters relevant for birch pollen emission calculations. Then, we use two different emission databases (BASE – no data assimilation, OBSNUD – data assimilation for the meteorological model) in the chemical transport model and evaluate birch pollen concentrations. Finally, we apply a scaling factor for the emissions (BASE and OBSNUD), based on the ratio between simulated and observed seasonal pollen integral (SPIn) to analyse its impact on birch concentrations over Central Europe. Assimilation of observational data significantly reducesmodel overestimation of air temperature,which is themain parameter responsible for the start of pollen emission and amount of released pollen. The results also show that a relatively small bias in air temperature from the model can lead to significant differences in heating degree days (HDD) value. This may cause the HDD threshold to be attained several days earlier/later than indicated from observational data which has further impact on the start of pollen emission. Even though the bias for air temperature was reduced for OBSNUD, the model indicates a start for the birch pollen season that is too early compared to observations. The start date of the seasonwas improved at two of the 11 stations in Poland. Data assimilation does not have a significant impact on the season's end or SPIn value. The application of the SPIn factor for the emissions results in a much closer birch pollen concentration level to observations even though the factor does not improve the start or end of the pollen season. The post-processing of modelled meteorological fields, such as the application of bias correction, can be considered as a way to further improve the pollen emission modelling

Modelling the atmospheric controls and climate impact of mineral dust in the Sahara Desert

Mineral dust aerosols play an important role in climate and the Earth's energy budget. The effect of dust on the radiative forcing is uncertain due to the complexity of particle properties and the complexity to quantify and discriminate preferential dust sources. This research considers the potential of two Regional Climate Models (RCM’s): The Weather Research and Forecasting model (WRF-Chem) and the Regional Climate Model (RegCM3) both with an integrated dust module. Numerical sensitivity experiments are performed to quantify the ability of both models to simulate sources, the magnitude of dust emission, the transport in 3-dimensions and the subsequent impact on the radiative forcing. Particular emphasis is given to preferential source regions within the Sahara and Sahel in North Africa including the Bodélé Depression in Northern Chad. To account for the distribution of preferential dust source regions, soil texture characteristics were modified in dust source regions in RegCM3. As for WRF-Chem GOCART scheme, a new higher resolution erodible fraction map is tested. Moreover, the sensitivity of the results to the specification of aerosol optical properties to evaluate the impacts of optical characteristics on the radiative forcing was considered for the RegCM3. Finally, model outputs are compared to in-situ data: weather stations (WMO) and AERONET and satellite estimates: MODIS, MISR, OMI, CALIPSO and SEVIRI. Results show that both models represent the space/time structure of near-surface meteorology well. The tuning of preferential dust sources tested in this research provides a more realistic representation of local dust sources, emissions and resulting AOT. This suggest that in the absence of truly accurate soil maps at high resolution, further refinements to preferential sources map and its implementation in dust models can lead to useful improvements in simulation of dust processes and dust forecast accuracy

The impact of using assimilated Aeolus wind data on regional WRF-Chem dust simulations

Land–atmosphere interactions govern the process of dust emission and transport. An accurate depiction of these physical processes within numerical weather prediction models allows for better estimating the spatial and temporal distribution of the dust burden and the characterisation of source and recipient areas. In the presented study, the ECMWF-IFS (European Centre for Medium-Range Weather Forecast – Integrated Forecasting System) outputs, produced with and without the assimilation of Aeolus quality-assured Rayleigh–clear and Mie–cloudy horizontal line-of-sight wind profiles, are used as initial or boundary conditions in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate 2-month periods in the spring and autumn of 2020, focusing on a case study in October. The experiments have been performed over the broader eastern Mediterranean and Middle East (EMME) region, which is frequently subjected to dust transport, as it encompasses some of the most active erodible dust sources. Aerosol- and dust-related model outputs (extinction coefficient, optical depth and concentrations) are qualitatively and quantitatively evaluated against ground- and satellite-based observations. Ground-based columnar and vertically resolved aerosol optical properties are acquired through AERONET sun photometers and PollyXT lidar, while near-surface concentrations are taken from EMEP. Satellite-derived vertical dust and columnar aerosol optical properties are acquired through LIVAS (LIdar climatology of Vertical Aerosol Structure) and MIDAS (ModIs Dust AeroSol), respectively. Overall, in cases of either high or low aerosol loadings, the model predictive skill is improved when WRF-Chem simulations are initialised with the meteorological fields of Aeolus wind profiles assimilated by the IFS. The improvement varies in space and time, with the most significant impact observed during the autumn months in the study region. Comparison with observation datasets saw a remarkable improvement in columnar aerosol optical depths, vertically resolved dust mass concentrations and near-surface particulate concentrations in the assimilated run against the control run. Reductions in model biases, either positive or negative, and an increase in the correlation between simulated and observed values was achieved for October 2020.</p

First Ever Observations of Mineral Dust in Wintertime over Warsaw, Poland

The long-range transport of desert dust over the area of the temperate climate zone is associated with the influx of hot air masses due to the location of the sources of this aerosol in the tropical climate zone. Between 24–26 February 2021, such an aerosol outbreak took place and reached Central Europe. The mean temperature of +11.7 °C was recorded during the event. A comparison of this value to the 20-year (2000–2020) average February temperature for Warsaw (−0.2 °C) indicates the uniqueness of the meteorological conditions. It was the first wintertime inflow of Saharan dust over Warsaw, the presence of which was confirmed by lidar and sun-photometer measurements. The properties of the desert dust layers were obtained; the mean values of the particle depolarization for the fully developed mineral dust layer were 13 ± 3% and 22 ± 4% for 355 and 532 nm, respectively. The aerosol optical thickness was high with average values >0.36 for all wavelengths smaller than 500 nm. The three-modal, aerosol size distribution was dominated by coarse-mode particles, with a visible contribution of accumulation-mode particles. It suggests the possible presence of other aerosol types

Ambient air quality and human health in India

700 million Indians have used solid fuels in their homes for the last 30 years, contributing substantially to air pollutant emissions. The Indian economy and industrial, power generation, and transport sectors have grown considerably over the last decade, increasing emissions of air pollutants. These air pollutant emissions have caused present-day concentrations of ambient PM2.5 and O3 in India to be amongst the highest in the world. Exposure to this air pollution is the second leading risk factor in India, contributing one-quarter of the global disease burden attributable to air pollution exposure. Air pollutant emissions are predicted to grow extensively over the coming years in India. Despite the importance of air quality in India, it remains relatively understudied, and knowledge of the sources and processes causing air pollution is limited. This thesis aims to understand the contribution of different pollution sources to the attributable disease burden from ambient air pollution exposure in India and the effects of future air pollution control pathways. The attributable disease burden from ambient PM2.5 exposure in India is substantial, where large reductions in emissions will be required to reduce the health burden due to the non-linear exposure-response relationship. The attributable disease burden from ambient O3 exposure is larger than previously thought and is of similar magnitude to that from PM2.5 in the future. Key sources contributing to the present day disease burden from ambient PM2.5 and O3 exposure are the emissions from the residential combustion of solid fuels, land transport, and coal combustion in power plants. The attributable disease burden is estimated to increase in the future due to population ageing and growth. Stringent air pollution control pathways are required to provide critical public health benefits in India in a challenging environment. A key focus should be to reduce the combustion of solid fuels

Understanding Air Pollutants and Meteorology Interactions Using Chemical Transport Models

Air pollution is a worldwide threat to human health and ecosystems, especially in developing countries. After being emitted to the atmosphere, air pollutant concentrations are determined by chemical and physical processes including transport, transformation, and deposition, which are largely affected by meteorological variations. In turn, pollutants such as fine particulate matter (PM2.5) affect meteorology by impacting solar radiation and cloud condensation processes. Thus, it is important and necessary to understand the interactions between air pollutants and meteorology for better designing effective air pollution control strategies and forecasting weather. In this study, two chemical transport models (CTMs) are applied to understand the interactions between air pollutants and meteorology in different areas. One model is the Community Multi-scale Air Quality (CMAQ) model and the other is the Weather Research and Forecasting model with Chemistry (WRF/Chem). Four cases are studied, the first case studies the responses of ozone (O3) and PM2.5 concentrations to variations in meteorology in China from 2013 to 2015. It is found that emission reductions in 2014 and 2015 effectively reduced PM2.5 concentrations by 23.9 and 43.5 µg/m3, respectively, but was partially counteracted by unfavorable meteorology. Reduction of primary PM and gaseous precursors led to 13.4 and 16.5 ppb increase of daily maximum 8 h average (MDA8) concentrations in the summertime in 2014 and 2015 in comparison to 2013, which was likely caused by the increase of solar actinic flux due to PM reduction. The other case understands the uncertainties caused by meteorology in simulating summertime O3 from 2016 to 2018 over the Southeast United States. WRF/Chem showed good performance in O3 simulation over Southeast US, especially along the coastal areas. The O3 simulation is sensitive to the meteorology uncertainties. The ensemble was more reliable than any individual run in this simulation. The last two cases simulate the feedbacks of air pollutants on meteorological conditions and related changes in pollutant concentrations in the Sichuan Basin (SCB), China and Africa, respectively. Aerosol radiation decreased surface temperature by 1-2 ℃, wind speed (WS) by ~ 0.3 m/s, planetary boundary layer (PBL) height by 10-20 %, solar radiation (SR) by ~ 30 %, and precipitation by 0.02-0.2 mm, while increased relative humidity (RH) by up to 2-4 % in January, which resulted in up to 10 µg/m3 increase of PM2.5 in January and 2 ppb decrease of O3 in July in SCB. In the simulation of Africa, PM2.5 concentration was higher in January and lower in August while O3 showed no significant seasonal and distribution variance. Aerosol radiative effects reduced solar radiation at the ground by as much as 20 w/m2 in January and 40 w/m2 in August, lowering the temperature by 1 °C in January and 0.5 °C in August on average, decreased WS by ∼0.1 m/s, and reduced PBL height by up to 120 m in both months, while slightly increased RH (2-4%)