Special Issue "Evaluation and Optimization of Atmospheric Numerical Models"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 30 June 2021.

Special Issue Editors

Dr. Ioannis Pytharoulis
E-Mail Website
Guest Editor
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: synoptic and dynamic meteorology; numerical weather prediction; atmospheric model evaluation; operational weather forecasting; land/sea–air interaction; extreme weather events; African Easterly Waves; Mediterranean tropical-like cyclones
Special Issues and Collections in MDPI journals
Dr. Petros Katsafados
E-Mail Website
Guest Editor
Department of Geography, Harokopio University of Athens, 16122 Athens, Greece
Interests: atmospheric dynamics; air-sea interaction; data assimilation; nowcasting
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The progress in atmospheric numerical models and the increase of computer power have led to a blooming of numerical weather prediction (NWP) and climate research, allowing for more effective protection from adverse meteorological and air-quality conditions, exploitation of renewable energy sources, planning of recreation/business activities and understanding of climate change effects. Despite these advances, the numerical models still present various errors associated to the numerical methods, the resolution, the physical parameterizations and the input data. There is room for further increase of the predictability by improving the modelling and data assimilation techniques and the various input data, as well as by employing higher resolution. The two-way coupling of atmospheric with hydrological, ocean, wave, dust and fire models has also exhibited a significant potential towards this goal.

The thorough understanding of the model errors can be achieved via the suitable evaluation of the different types of forecasts/simulations, exploiting the available observations and scientific knowledge. Τhe evaluation criteria may include the comparison against analytic theory, other independent numerical models or observations, the calculation of budgets and the performance of sensitivity experiments. Nowadays, the models are commonly evaluated against observations, through point-to-point, neighbourhood-based and object oriented methodologies.

The aim of this Special Issue is to comprise review and original theoretical and modelling studies on the evaluation and optimization of atmospheric numerical models.

Topics of interest include, but are not limited to, the following:

  • Development and evaluation of numerical techniques, diagnosis of data assimilation methods and physical parameterizations
  • Sensitivity experiments
  • Two-way coupling of atmospheric numerical models with hydrological, ocean, wave, dust and fire ones, aiming to improve the representation of the atmospheric processes
  • Atmospheric model evaluation - verification of model components and operational NWP products against in-situ measurements, remote sensing estimations, regional and global re-analysis of past observations

Prof. Ioannis Pytharoulis
Prof. Petros Katsafados
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Atmospheric Numerical Models
  • Model evaluation
  • Point-to-point, neighborhood-based, object oriented evaluation
  • Sensitivity experiments
  • Data assimilation
  • Physical parameterizations

Published Papers (4 papers)

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Research

Open AccessArticle
Investigation of Volcanic Emissions in the Mediterranean: “The Etna–Antikythera Connection”
Atmosphere 2021, 12(1), 40; https://doi.org/10.3390/atmos12010040 - 30 Dec 2020
Viewed by 593
Abstract
Between 30 May and 6 June 2019 a series of new flanks eruptions interested the south-east flanks of Mt. Etna, Italy, forming lava flows and explosive activity that was most intense during the first day of the eruption; as a result, volcanic particles [...] Read more.
Between 30 May and 6 June 2019 a series of new flanks eruptions interested the south-east flanks of Mt. Etna, Italy, forming lava flows and explosive activity that was most intense during the first day of the eruption; as a result, volcanic particles were dispersed towards Greece. Lidar measurements performed at the PANhellenic GEophysical observatory of Antikythera (PANGEA) of the National Observatory of Athens (NOA), in Greece, reveal the presence of particles of volcanic origin above the area the days following the eruption. FLEXible PARTicle dispersion model (FLEXPART) simulations and satellite-based SO2 observations from the TROPOspheric Monitoring Instrument onboard the Sentinel-5 Precursor (TROPOMI/S5P), confirm the volcanic plume transport from Etna towards PANGEA and possible mixing with co-existing desert dust particles. Lidar and modeled values are in agreement and the derived sulfate mass concentration is approximately 15 μg/m3. This is the first time that Etna volcanic products are monitored at Antikythera station, in Greece with implications for the investigation of their role in the Mediterranean weather and climate. Full article
(This article belongs to the Special Issue Evaluation and Optimization of Atmospheric Numerical Models)
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Open AccessArticle
Towards a Better Design of Convection-Allowing Ensembles for Precipitation Forecasts over Ensenada, Baja California, Mexico
Atmosphere 2020, 11(9), 973; https://doi.org/10.3390/atmos11090973 - 11 Sep 2020
Viewed by 595
Abstract
Convective ensembles promise to increase forecast accuracy while at the same time providing information on the probability of the forecast. A vast number of different methods of ensemble creation have been developed over time. Here, initial conditions and model error uncertainties are represented [...] Read more.
Convective ensembles promise to increase forecast accuracy while at the same time providing information on the probability of the forecast. A vast number of different methods of ensemble creation have been developed over time. Here, initial conditions and model error uncertainties are represented by a convective-allowing ensemble with more than 50 members. The results are analyzed using one case study with relatively high precipitation over Ensenada, Baja California, Mexico. The ensemble members are perturbed using random initial perturbations, breeding, and the Stochastic Kinetic Energy Backscatter parameterization (SKEBS) within the Weather Research and Forecasting (WRF) model. The aim is to improve the high-resolution ensemble design provided in a previous study for the same region by maximizing the spread of an ensemble with low member count. To this end, a comparative analysis of the members is performed using perturbation growth rates and information entropy. In addition, a comparative verification is performed using observations from one automatic meteorological station and satellite-derived precipitation data. It was found that the growth rates and the one-dimensional power spectral density of the initial perturbation fields are clustered depending on each member’s origin and the methods used to generate the breeding members. An inverse relationship was observed between these two variables, which can be useful for selecting appropriate initial condition perturbations. The dynamical injections of energy, introduced as perturbations to the numerical fields by the SKEBS method, were essential to maintain positive growth rates during the simulation period. Evaluation of the information entropy suggests that a selection of a set of members generated by the SKEBS method is best for increasing the ensemble spread while saving computer resources. Full article
(This article belongs to the Special Issue Evaluation and Optimization of Atmospheric Numerical Models)
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Open AccessArticle
A Lagrangian Advection Scheme for Solving Cloud Droplet Diffusion Growth
Atmosphere 2020, 11(6), 632; https://doi.org/10.3390/atmos11060632 - 15 Jun 2020
Cited by 1 | Viewed by 634
Abstract
Cloud drop diffusion growth is a fundamental microphysical process in warm clouds. In the present work, a new Lagrangian advection scheme (LAS) is proposed for solving this process. The LAS discretizes cloud drop size distribution (CDSD) with movable bins. Two types of prognostic [...] Read more.
Cloud drop diffusion growth is a fundamental microphysical process in warm clouds. In the present work, a new Lagrangian advection scheme (LAS) is proposed for solving this process. The LAS discretizes cloud drop size distribution (CDSD) with movable bins. Two types of prognostic variable, namely, bin radius and bin width, are included in the LAS. Bin radius is tracked by the well-known cloud drop diffusion growth equation, while bin width is solved by a derived equation. CDSD is then calculated with the information of bin radius, bin width, and prescribed droplet number concentration. The reliability of the new scheme is validated by the reference analytical solutions in a parcel cloud model. Artificial broadening of CDSD, understood as a by-product of numerical diffusion in advection algorithm, is strictly prohibited by the new scheme. The authors further coupled the LAS into a one-and-half dimensional (1.5D) Eulerian cloud model to evaluate its performance. An individual deep cumulus cloud studied in the Cooperative Convective Precipitation Experiment (CCOPE) campaign was simulated with the LAS-coupled 1.5D model and the original 1.5D model. Simulation results of CDSD and microphysical properties were compared with observational data. Improvements, namely, narrower CDSD and accurate reproduction of particle mean diameter, were achieved with the LAS-coupled 1.5D model. Full article
(This article belongs to the Special Issue Evaluation and Optimization of Atmospheric Numerical Models)
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Open AccessArticle
Improving WRF Typhoon Precipitation and Intensity Simulation Using a Surrogate-Based Automatic Parameter Optimization Method
Atmosphere 2020, 11(1), 89; https://doi.org/10.3390/atmos11010089 - 10 Jan 2020
Cited by 1 | Viewed by 998
Abstract
Typhoon precipitation and intensity forecasting plays an important role in disaster prevention and mitigation in the typhoon landfall area. However, the issue of improving forecast accuracy is very challenging. In this study, the Weather Research and Forecasting (WRF) model typhoon simulations on precipitation [...] Read more.
Typhoon precipitation and intensity forecasting plays an important role in disaster prevention and mitigation in the typhoon landfall area. However, the issue of improving forecast accuracy is very challenging. In this study, the Weather Research and Forecasting (WRF) model typhoon simulations on precipitation and central 10-m maximum wind speed (10-m wind) were improved using a systematic parameter optimization framework consisting of parameter screening and adaptive surrogate modeling-based optimization (ASMO) for screening sensitive parameters. Six of the 25 adjustable parameters from seven physics components of the WRF model were screened by the Multivariate Adaptive Regression Spline (MARS) parameter sensitivity analysis tool. Then the six parameters were optimized using the ASMO method, and after 178 runs, the 6-hourly precipitation, and 10-m wind simulations were finally improved by 6.83% and 13.64% respectively. The most significant improvements usually occurred with the maximum precipitation or the highest wind speed. Additional typhoon events from other years were simulated to validate that the WRF optimal parameters were reasonable. The results demonstrated that the improvements in 6-hourly precipitation and 10-m wind were 4.78% and 8.54% respectively. Overall, the ASMO optimization method is an effective and highly efficient way to improve typhoon precipitation and intensity simulation using a numerical weather prediction model. Full article
(This article belongs to the Special Issue Evaluation and Optimization of Atmospheric Numerical Models)
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