scholarly journals Status and future of Numerical Atmospheric Aerosol Prediction with a focus on data requirements

2018 ◽  
Author(s):  
Angela Benedetti ◽  
Jeffrey S. Reid ◽  
Alexander Baklanov ◽  
Sara Basart ◽  
Olivier Boucher ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Atmospheric Aerosol ◽  
Weather Prediction ◽  
Model Development ◽  
Optical Parameters ◽  
Climate Services ◽  
Near Surface ◽  
Particle Properties ◽  
Operational Models ◽  
Operational Activities

Abstract. Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centres due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, providers of climate services, and health professionals. The prediction of aerosol particle properties in Numerical Weather Prediction (NWP) models faces a number of challenges owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions. Errors in aerosol prediction concern all processes involved in the aerosol life cycle. These include errors on the source terms (for both anthropogenic and natural emissions), errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), as well as errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transformation and growth, hygroscopicity). The main goal of current research on aerosol forecast consists in prioritizing these errors and trying to reduce the most important ones through model development and data assimilation. Aerosol particle observations from satellite and ground-based platforms have been crucial to guide model development of the recent years, and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near-surface, and aircraft) and freely shared. This white paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centres. Some of the requirements are equally applicable to aerosol-climate research. However, the focus here is on the global operational prediction of aerosol properties such as mass concentrations and optical parameters. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of bin and bulk schemes with limited capability to simulate the size information. However the next generation of aerosol operational models will have the capability to predict both mass and number density which will provide a more complete description of the aerosols properties. A brief overview of the state-of-the-art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.

scholarly journals Status and future of numerical atmospheric aerosol prediction with a focus on data requirements

2018 ◽  
Vol 18 (14) ◽  
pp. 10615-10643 ◽  
Author(s):  
Angela Benedetti ◽  
Jeffrey S. Reid ◽  
Peter Knippertz ◽  
John H. Marsham ◽  
Francesca Di Giuseppe ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Atmospheric Aerosol ◽  
Weather Prediction ◽  
Model Development ◽  
Optical Parameters ◽  
Climate Services ◽  
Near Surface ◽  
Density Concentration ◽  
Operational Models ◽  
Operational Activities

Abstract. Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas–aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite- and ground-based platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centers. While some of the requirements are equally applicable to aerosol–climate, the focus here is on global operational prediction of aerosol properties such as mass concentrations and optical parameters. It is also recognized that the term “requirements” is loosely used here given the diversity in global aerosol observing systems and that utilized data are typically not from operational sources. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of “bin” and bulk schemes with limited capability of simulating the size information. However the next generation of aerosol operational models will output both mass and number density concentration to provide a more complete description of the aerosol population. A brief overview of the state of the art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.

scholarly journals Radiative forcing of the desert aerosol at Ouarzazate (Morocco)

2018 ◽  
Vol 37 ◽  
pp. 03004
Author(s):  
Abdelouahid Tahiri ◽  
Mohamed Diouri
Keyword(s):  
Optical Properties ◽  
Atmospheric Aerosol ◽  
Radiative Forcing ◽  
Cloud Formation ◽  
Optical Parameters ◽  
Aerosol Radiative Forcing ◽  
Daily Average ◽  
Definition Of ◽  
Aerosol Radiative

The atmospheric aerosol contributes to the definition of the climate with direct effect, the diffusion and absorption of solar and terrestrial radiations, and indirect, the cloud formation process where aerosols behave as condensation nuclei and alter the optical properties. Satellites and ground-based networks (solar photometers) allow the terrestrial aerosol observation and the determination of impact. Desert aerosol considered among the main types of tropospheric aerosols whose optical property uncertainties are still quite important. The analysis concerns the optical parameters recorded in 2015 at Ouarzazate solar photometric station (AERONET/PHOTONS network, http://aeronet.gsfc.nasa.gov/) close to Saharan zone. The daily average aerosol optical depthτaer at 0.5μm, are relatively high in summer and less degree in spring (from 0.01 to 1.82). Daily average of the Angstrom coefficients α vary between 0.01 and 1.55. The daily average of aerosol radiative forcing at the surface range between -150W/m2 and -10 W/m2 with peaks recorded in summer, characterized locally by large loads of desert aerosol in agreement with the advections of the Southeast of Morocco. Those recorded at the Top of the atmosphere show a variation from -74 W/m2 to +24 W/m2

scholarly journals On the Use of Rotary-Wing Aircraft to Sample Near-Surface Thermodynamic Fields: Results from Recent Field Campaigns

Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 10 ◽  
Author(s):  
Temple Lee ◽  
Michael Buban ◽  
Edward Dumas ◽  
C. Baker
Keyword(s):  
Weather Prediction ◽  
Chemical Properties ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Spatiotemporal Variability ◽  
Near Surface ◽  
Field Campaigns ◽  
High Level ◽  
Rotary Wing

Rotary-wing small unmanned aircraft systems (sUAS) are increasingly being used for sampling thermodynamic and chemical properties of the Earth’s atmospheric boundary layer (ABL) because of their ability to measure at high spatial and temporal resolutions. Therefore, they have the potential to be used for long-term quasi-continuous monitoring of the ABL, which is critical for improving ABL parameterizations and improving numerical weather prediction (NWP) models through data assimilation. Before rotary-wing aircraft can be used for these purposes, however, their performance and the sensors used therein must be adequately characterized. In the present study, we describe recent calibration and validation procedures for thermodynamic sensors used on two rotary-wing aircraft: A DJI S-1000 and MD4-1000. These evaluations indicated a high level of confidence in the on-board measurements. We then used these measurements to characterize the spatiotemporal variability of near-surface (up to 300-m AGL) temperature and moisture fields as a component of two recent field campaigns: The Verification of the Origins of Rotation in Tornadoes Experiment in the Southeast U.S. (VORTEX-SE) in Alabama, and the Land Atmosphere Feedback Experiment (LAFE) in northern Oklahoma.

scholarly journals High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

2020 ◽  
Author(s):  
Benjamin Fersch ◽  
Alfonso Senatore ◽  
Bianca Adler ◽  
Joël Arnault ◽  
Matthias Mauder ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Weather Prediction ◽  
Surface Model ◽  
Near Surface ◽  
Ground Heat Flux ◽  
The Impact ◽  
Fully Coupled ◽  
Regional Water

<p>The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. We examine the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assess the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the pre-Alpine Terrestrial Environmental Observatory (TERENO Pre-Alpine) for the Ammer (600 km²) and Rott (55 km²) river catchments in southern Germany, covering a five month period (Jun–Oct 2016).</p><p>The sensitivity of 7 land surface parameters is tested using the <em>Latin-Hypercube One-factor-At-a-Time</em> (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent <em>Parameter Estimation and Uncertainty Analysis software</em> (PEST).</p><p>The calibration of the offline WRF-Hydro leads to Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro shows only tiny alterations for radiation and precipitation but considerable changes for moisture- and energy fluxes. By comparison with TERENO Pre-Alpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.</p>

scholarly journals Wind plants can impact long-term local atmospheric conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicola Bodini ◽  
Julie K. Lundquist ◽  
Patrick Moriarty
Keyword(s):  
Wind Speed ◽  
Urban Areas ◽  
Weather Prediction ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Direct Observations ◽  
Stable Conditions ◽  
Weather And Climate ◽  
Central United States

AbstractLong-term weather and climate observatories can be affected by the changing environments in their vicinity, such as the growth of urban areas or changing vegetation. Wind plants can also impact local atmospheric conditions through their wakes, characterized by reduced wind speed and increased turbulence. We explore the extent to which the wind plants near an atmospheric measurement site in the central United States have affected their long-term measurements. Both direct observations and mesoscale numerical weather prediction simulations demonstrate how the wind plants induce a wind deficit aloft, especially in stable conditions, and a wind speed acceleration near the surface, which extend $$\sim 30$$ ∼ 30  km downwind of the wind plant. Turbulence kinetic energy is significantly enhanced within the wind plant wake in stable conditions, with near-surface observations seeing an increase of more than 30% a few kilometers downwind of the plants.

scholarly journals Aerosol particle characteristics measured in the United Arab Emirates and their response to mixing in the boundary layer

2021 ◽  
Author(s):  
Jutta Kesti ◽  
John Backman ◽  
Ewan James O'Connor ◽  
Anne Hirsikko ◽  
Eija Asmi ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Aerosol Particle ◽  
United Arab Emirates ◽  
Wind Direction ◽  
Aerosol Particles ◽  
Surface Wind ◽  
Number Concentration ◽  
Particle Properties ◽  
Boundary Layer Height

Abstract. Aerosol particles play an important in role in the microphysics of clouds and hence on their likelihood to precipitate. In the changing climate already dry areas such as the United Arab Emirates (UAE) are predicted to become even drier. Comprehensive observations of the daily and seasonal variation in aerosol particle properties in such locations are required reducing the uncertainty in such predictions. We analyse observations from a one-year measurement campaign at a background location in the United Arab Emirates to investigate the properties of aerosol particles in this region, study the impact of boundary layer mixing on background aerosol particle properties measured at the surface and study the temporal evolution of the aerosol particle cloud formation potential in the region. We used in-situ aerosol particle measurements to characterise the aerosol particle composition, size, number and cloud condensation nuclei (CCN) properties, in-situ SO2 measurements as an anthropogenic signature and a long-range scanning Doppler lidar to provide vertical profiles of the horizontal wind and turbulent properties to monitor the evolution of the boundary layer. Anthropogenic sulphate dominated the aerosol particle mass composition in this location. There was a clear diurnal cycle in the surface wind direction, which had a strong impact on aerosol particle total number concentration, SO2 concentration and black carbon mass concentration. Local sources were the predominant source of black carbon, as concentrations clearly depended on the presence of turbulent mixing, with much higher values during calm nights. The measured concentrations of SO2, instead, were highly dependent on the surface wind direction as well as on the depth of the boundary layer when entrainment from the advected elevated layers occurred. The wind direction at the surface or of the elevated layer suggests that the cities of Dubai, Abu Dhabi and other coastal conurbations were the remote sources of SO2. We observed new aerosol particle formation events almost every day (on four days out of five on average). Calm nights had the highest CCN number concentrations and lowest κ values and activation fractions. We did not observe any clear dependence of CCN number concentration and κ parameter on the height of the daytime boundary layer, whereas the activation fraction did show a slight increase with increasing boundary layer height, due to the change in the shape of the aerosol particle size distribution where the relative portion of larger aerosol particles increased with increasing boundary layer height. We believe that this indicates that size is more important than chemistry for aerosol particle CCN activation at this site. The combination of instrumentation used in this campaign enabled us to identify periods when anthropogenic pollution from remote sources that had been transported in elevated layers was present, and had been mixed down to the surface in the growing boundary layer.

scholarly journals Model of the process of extreme light scattering by atmospheric aerosol particle

2021 ◽  
Vol 64 (5) ◽  
pp. 376-383
Author(s):  
I.A. Potapova ◽  
A.P. Bobrovsky ◽  
N.V. Dyachenko ◽  
Yu.B. Rzhonsnitskaya ◽  
N.A. Sanotskaya ◽  
...  
Keyword(s):  
Light Scattering ◽  
Aerosol Particle ◽  
Atmospheric Aerosol

scholarly journals Effect of the uncertainty in meteorology on air quality model predictions

Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 625-646
Author(s):  
Zita Ferenczi ◽  
Emese Homolya ◽  
Krisztina Lázár ◽  
Anita Tóth
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Model System ◽  
Air Quality Model ◽  
Quality Model ◽  
Near Surface ◽  
The Impact

An operational air quality forecasting model system has been developed and provides daily forecasts of ozone, nitrogen oxides, and particulate matter for the area of Hungary and three big cites of the country (Budapest, Miskolc, and Pécs). The core of the model system is the CHIMERE off-line chemical transport model. The AROME numerical weather prediction model provides the gridded meteorological inputs for the chemical model calculations. The horizontal resolution of the AROME meteorological fields is consistent with the CHIMERE horizontal resolution. The individual forecasted concentrations for the following 2 days are displayed on a public website of the Hungarian Meteorological Service. It is essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input meteorological fields. The main aim of this research is to probe the response of an air quality model to its uncertain meteorological inputs. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. During the past decades, meteorological ensemble modeling has received extensive research and operational interest because of its ability to better characterize forecast uncertainty. One such ensemble forecast system is the one of the AROME model, which has an 11-member ensemble where each member is perturbed by initial and lateral boundary conditions. In this work we focus on wintertime particulate matter concentrations, since this pollutant is extremely sensitive to near-surface mixing processes. Selecting a number of extreme air pollution situations we will show what the impact of the meteorological uncertainty is on the simulated concentration fields using AROME ensemble members.

scholarly journals Evaluation of a Regional Reanalysis and ERA-Interim over East Asia Using In Situ Observations during 2013–14

2017 ◽  
Vol 56 (10) ◽  
pp. 2821-2844 ◽  
Author(s):  
Eun-Gyeong Yang ◽  
Hyun Mee Kim
Keyword(s):  
Relative Humidity ◽  
East Asia ◽  
Geopotential Height ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Surface Wind ◽  
Lower Troposphere ◽  
Near Surface ◽  
Skill Scores ◽  
Regional Reanalysis

AbstractIn this study, the East Asia Regional Reanalysis (EARR) is developed for the period 2013–14 and characteristics of the EARR are examined in comparison with ERA-Interim (ERA-I) reanalysis. The EARR is based on the Unified Model with 12-km horizontal resolution, which has been an operational numerical weather prediction model at the Korea Meteorological Administration since being adopted from the Met Office in 2011. Relative to the ERA-I, in terms of skill scores, the EARR performance for wind, temperature, relative humidity, and geopotential height improves except for mean sea level pressure, the lower-troposphere geopotential height, and the upper-air relative humidity. In a similar way, RMSEs of the EARR are smaller than those of ERA-I for wind, temperature, and relative humidity, except for the upper-air meridional wind and the upper-air relative humidity in January. With respect to the near-surface variables, the triple collocation analysis and the correlation coefficients confirm that EARR provides a much improved representation when compared with ERA-I. In addition, EARR reproduces the finescale features of near-surface variables in greater detail than ERA-I does, and the kinetic energy (KE) spectra of EARR agree more with the canonical atmospheric KE spectra than do the ERA-I KE spectra. On the basis of the fractions skill score, the near-surface wind of EARR is statistically significantly better simulated than that of ERA-I for all thresholds, except for the higher threshold at smaller spatial scales. Therefore, although special care needs to be taken when using the upper-air relative humidity from EARR, the near-surface variables of the EARR that were developed are found to be more accurate than those of ERA-I.

ACCOMPLISHMENTS OF NOAA’S AIRBORNE HURRICANE FIELD PROGRAM AND A BROADER FUTURE APPROACH TO FORECAST IMPROVEMENT

2021 ◽  
pp. 1-79
Author(s):  
Jonathan Zawislak ◽  
Robert F. Rogers ◽  
Sim D. Aberson ◽  
Ghassan J. Alaka ◽  
George Alvey ◽  
...  
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Integrated Approach ◽  
Environmental Modeling ◽  
Research Division ◽  
Forecast Models ◽  
Operational Models ◽  
National Hurricane Center ◽  
Operations Center ◽  
Aircraft Data

AbstractSince 2005, NOAA has conducted the annual Intensity Forecasting Experiment (IFEX), led by scientists from the Hurricane Research Division at NOAA’s Atlantic Oceanographic andMeteorological Laboratory. They partner with NOAA’s Aircraft Operations Center, who maintain and operate the WP-3D and G-IV Hurricane Hunter aircraft, and NCEP’s National Hurricane Center and Environmental Modeling Center, who task airborne missions to gather data used by forecasters for analysis and forecasting and for ingest into operational numerical weather prediction models. The goal of IFEX is to improve tropical cyclone (TC) forecasts using an integrated approach of analyzing observations from aircraft, initializing and evaluating forecast models with those observations, and developing new airborne instrumentation and observing strategies targeted at filling observing gaps and maximizing the data’s impact in model forecasts. This summary article not only highlights recent IFEX contributions towards improved TC understanding and prediction, but also reflects more broadly on the accomplishments of the program during the 16 years of its existence. It describes how IFEX addresses high-priority forecast challenges, summarizes recent collaborations, describes advancements in observing systems monitoring structure and intensity, as well as in assimilation of aircraft data into operational models, and emphasizes key advances in understanding of TC processes, particularly those that lead to rapid intensification. The article concludes by laying the foundation for the “next generation” of IFEX as it broadens its scope to all TC hazards, particularly rainfall, storm-surge inundation, and tornadoes, that have gained notoriety during the last few years after several devastating landfalling TCs.

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