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Numerical Weather Prediction Models and Ensemble Prediction Systems

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A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (1 July 2024) | Viewed by 15213

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Dr. Petroula Louka

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Department of Mathematics and Natural Sciences, Hellenic Air Force Academy, Athens, Greece
Interests: NWP models; EPS; evaluation of NWPs and EPSs; aviation meteorology; effects of weather on aviation with emphasis on convective systems, icing, turbulence, dust transfer; study of convective systems with the use of NWPs, radar and satellite data; atmospheric boundary-layer meteorology
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Special Issue Information

Dear Colleagues,

Short- to medium-range weather forecasting is based both on high-resolution Numerical Weather Prediction (NWP) models that are able to accurately represent certain atmospheric processes, presenting the deterministic approach, as well as on the probabilistic Ensemble Prediction Systems (EPS) that provide information on the level of uncertainty in forecasts whose spread is obtained by perturbing both the initial conditions and also aspects of the physical processes within the model. Both require extensive research on the representation of physical processes, numerical methods, and data assimilation methodologies, while objective evaluation systems are necessary to assess their performance.

The aim of this Special Issue is to communicate advances in NWP models and EPS as state-of-the-art weather prediction tools that rely on the development of a seamless earth system modeling framework and make the best use of the model outputs in an objective way for both research and operational applications, such as in aviation, shipping, emergency warning systems, renewable energy, etc. Hence, this issue intends to collect contributions on new developments in data assimilation systems and integration of observing systems to support NWP models, improvements in model physics and parameterizations of subgrid-scale processes, and adoption of innovative computational grids and numerical methods leading to forecast skill enhancement as well as statistical approaches to evaluate their impact. In the case of EPS applications, the focus is on perturbation methods of near convection-permitting systems for developing members with a certain spread of different solutions, the range of which enables the assessment of the uncertainty in the probabilistic forecast and the confidence in the deterministic predictions. The study of high-impact weather events, their evolution, and analysis of dynamical and physical characteristics through NWP applications are also encouraged.

Dr. Petroula Louka
Guest Editor

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Keywords

model physics
model parameterizations
subgrid-scale processes
perturbation methods
EPS spread
data assimilation systems
model evaluation
high-impact weather events
NWP & EPS applications

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Published Papers (9 papers)

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Research

29 pages, 23715 KiB

Open AccessEditor’s ChoiceArticle

Forecasting In-Flight Icing over Greece: Insights from a Low-Pressure System Case Study

by Petroula Louka, Ioannis Samos and Flora Gofa

Atmosphere 2024, 15(8), 990; https://doi.org/10.3390/atmos15080990 - 17 Aug 2024

Viewed by 1151

Abstract

Forecasting in-flight icing conditions is crucial for aviation safety, particularly in regions with variable and complex meteorological configurations, such as Greece. Icing accretion onto the aircraft’s surfaces is influenced by the presence of supercooled water in subfreezing environments. This paper outlines a methodology of forecasting icing conditions, with the development of the Icing Potential Algorithm that takes into consideration the meteorological scenarios related to icing accretion, using state-of-the-art Numerical Weather Prediction model results, and forming a fuzzy logic tree based on different membership functions, applied for the first time over Greece. The synoptic situation of an organized low-pressure system passage, with occlusion, cold and warm fronts, over Greece that creates dynamically significant conditions for icing formation was investigated. The sensitivity of the algorithm was revealed upon the precipitation, cloud type and vertical velocity effects. It was shown that the greatest icing intensity is associated with single-layer ice and multi-layer clouds that are comprised of both ice and supercooled water, while convectivity and storm presence lead to also enhancing the icing formation. A qualitative evaluation of the results with satellite, radar and METAR observations was performed, indicating the general agreement of the method mainly with the ground-based observations. Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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13 pages, 3316 KiB

Open AccessArticle

Evaluation of the Forecasting Performance of Supercooled Clouds for the Weather Modification Model of the Cloud and Precipitation Explicit Forecasting System

by Jia Wang, Qin Mei, Haixia Mei, Jun Guo and Tongchang Liu

Atmosphere 2024, 15(8), 928; https://doi.org/10.3390/atmos15080928 - 3 Aug 2024

Viewed by 612

Abstract

Through the application of cloud top temperature data and the extraction of supercooled cloud information in cloud-type data from the next-generation Himawari-8 geostationary satellite with high spatial–temporal resolution, a quantitative evaluation of the forecasting performance of the weather modification model named the Cloud and Precipitation Explicit Forecasting System (CPEFS) was conducted. The evaluation, based on selected forecast cases from 8 days in September and October 2018 initialized at 00 and 12 UTC every day, focused especially on the forecasting performance in supercooled clouds (vertical integrated supercooled liquid water, VISL > 0), including the comprehensive spatial distribution of cloud top temperature (CTT) and 3 h precipitation over 0.1 mm (R3 > 0.1). The results indicated that the forecasting performance for VISL > 0 was relatively good, with the Threat Score (TS) ranging from 0.46 to 0.67. The forecasts initialized at 12 UTC slightly outperformed the forecasts initialized at 00 UTC. Additionally, the corresponding spatial Anomaly Correlation Coefficient (ACC) of CTT between forecasts and observations was 0.23, and the TS for R3 > 0.1 reached as high as 0.87. For a mix of cold and warm cloud systems, there was a correlation between the forecasting performance of VISL > 0 and CTT. The trends in the TS for VISL > 0 and the ACC of CTT aligned with the forecast lead-time. Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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29 pages, 17908 KiB

Open AccessEditor’s ChoiceArticle

Dust Transport from North Africa to the Middle East: Synoptic Patterns and Numerical Forecast

by Sara Karami, Dimitris G. Kaskaoutis, Ioannis Pytharoulis, Rafaella-Eleni P. Sotiropoulou and Efthimios Tagaris

Atmosphere 2024, 15(5), 531; https://doi.org/10.3390/atmos15050531 - 26 Apr 2024

Cited by 2 | Viewed by 1282

Abstract

Every year, large quantities of dust are transported from North Africa to the Americas, Europe, and West Asia. The purpose of this study is to analyze four intense and pervasive dust storms that entered the Middle East from Northern Africa. Satellite products, ground-based remote sensing measurements, reanalysis data, and the outputs of the Aire Limitée Adaptation dynamique Développement InterNational-Dust (ALADIN-Dust) and the ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON-ART) forecasting models were synergized. The dust storms originated from different source regions located in the north, northeastern, and central parts of the Sahara Desert. The transport height of the main dust plumes was about 3–5 km, triggered by the westerly zonal winds. The presence of a closed low over the Eastern Mediterranean and the penetration of a deep trough into North Africa at 500 hPa were the main synoptic circulation patterns favoring long-range dust transport during the four dust events. A comparison of aerosol optical depth (AOD) outputs from the two models with satellite data revealed that although both models forecasted dust transport from Africa to the Middle East, they considerably underestimated the AOD values, especially near the dust sources. The ICON-ART model performed slightly better than ALADIN in forecasting these dust storms, and for longer forecasting leading time, although the performance of both models decreased, the superiority of the ICON-ART model became more apparent. Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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40 pages, 23230 KiB

Open AccessEditor’s ChoiceArticle

Synoptic Analysis and Subseasonal Predictability of an Early Heatwave in the Eastern Mediterranean

by Dimitris Mitropoulos, Ioannis Pytharoulis, Prodromos Zanis and Christina Anagnostopoulou

Atmosphere 2024, 15(4), 442; https://doi.org/10.3390/atmos15040442 - 2 Apr 2024

Viewed by 1347

Abstract

Greece and the surrounding areas experienced an early warm spell with characteristics of a typical summer Mediterranean heatwave in mid-May 2020. The maximum 2 m temperature at Kalamata (southern Greece) reached 40 °C on 16 May and at Aydin (Turkey), it was 42.6 °C on 17 May. There was a 10-standard deviation positive temperature anomaly (relative to the 1975–2005 climatology) at 850 hPa, with a southwesterly flow and warm advection over Greece and western Turkey from 11 to 20 May. At 500 hPa, a ridge was located over the Eastern Mediterranean, resulting in subsidence. The aims of this study were (a) to investigate the prevailing synoptic conditions during this event in order to document its occurrence and (b) to assess whether this out-of-season heatwave was predictable on subseasonal timescales. The subseasonal predictability is not a well-researched scientific topic in the Eastern Mediterranean Sea. The ensemble global forecasts from six international meteorological centres (European Centre for Medium-Range Weather Forecasts—ECMWF, United Kingdom Met Office—UKMO, China Meteorological Administration—CMA, Korea Meteorological Administration—KMA, National Centers for Environmental Prediction—NCEP and Hydrometeorological Centre of Russia—HMCR) and limited area forecasts using the Weather Research and Forecasting model with the Advanced Research dynamic solver (WRF) forced by Climate Forecast System version 2 (CFSv.2; NCEP) forecasts were evaluated for lead times ranging from two to six weeks using statistical scores. WRF was integrated using two telescoping nests covering Europe, the Mediterranean basin and large part of the Atlantic Ocean, with a grid spacing of 25 km, and Greece–western Turkey at 5 km. The results showed that there were some accurate forecasts initiated two weeks before the event’s onset. There was no systematic benefit from the increase of the WRF model’s resolution from 25 km to 5 km for forecasting the 850 hPa temperature, but regarding the prediction of maximum air temperature near the surface, the high resolution (5 km) nest of WRF produced a marginally better performance than the coarser resolution domain (25 km). Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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19 pages, 10045 KiB

Open AccessArticle

Expected Changes in Heating and Cooling Degree Days over Greece in the near Future Based on Climate Scenarios Projections

by Athanasios Karagiannidis, Konstantinos Lagouvardos, Vassiliki Kotroni and Elisavet Galanaki

Atmosphere 2024, 15(4), 393; https://doi.org/10.3390/atmos15040393 - 22 Mar 2024

Cited by 1 | Viewed by 1387

Abstract

The change in heating and cooling needs of Greece in the near future due to the climate change is assessed in the present study. Global and regional climate models and two different representative concentration pathways (RCPs) are used to simulate the expected change in temperature. A widely used methodology of computation of heating degree days (HDDs) and cooling degree days (CDDs) is employed with a base temperature of 18 °C. In agreement with the expected temperature rise in the near future, an HDD decrease and CDD increase under both RCPs is also expected. The changes under RCP8.5 are stronger compared to those under RCP4.5. Differences related to topography are noted. The HDD decrease is stronger than CDD increase but the relative increase in CDDs is higher than the relative increase in HDDs. The highest absolute decreases in HDDs are expected for February and March while the highest absolute increases in CDDs are expected during the three summer months. Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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25 pages, 32622 KiB

Open AccessEditor’s ChoiceArticle

Integrating Ensemble Weather Predictions in a Hydrologic-Hydraulic Modelling System for Fine-Resolution Flood Forecasting: The Case of Skala Bridge at Evrotas River, Greece

by George Varlas, Anastasios Papadopoulos, George Papaioannou, Vassiliki Markogianni, Angelos Alamanos and Elias Dimitriou

Atmosphere 2024, 15(1), 120; https://doi.org/10.3390/atmos15010120 - 19 Jan 2024

Cited by 1 | Viewed by 2978

Abstract

Ensemble weather forecasting involves the integration of multiple simulations to improve the accuracy of predictions by introducing a probabilistic approach. It is difficult to accurately predict heavy rainfall events that cause flash floods and, thus, ensemble forecasting could be useful to reduce uncertainty in the forecast, thus improving emergency response. In this framework, this study presents the efforts to develop and assess a flash flood forecasting system that combines meteorological, hydrological, and hydraulic modeling, adopting an ensemble approach. The integration of ensemble weather forecasting and, subsequently, ensemble hydrological-hydraulic modeling can improve the accuracy of flash flood predictions, providing useful probabilistic information. The flash flood that occurred on 26 January 2023 in the Evrotas river basin (Greece) is used as a case study. The meteorological model, using 33 different initial and boundary condition datasets, simulated heavy rainfall, the hydrological model, using weather inputs, simulated discharge, and the hydraulic model, using discharge data, estimated water level at a bridge. The results show that the ensemble modeling system results in timely forecasts, while also providing valuable flooding probability information for 1 to 5 days prior, thus facilitating bridge flood warning. The continued refinement of such ensemble multi-model systems will further enhance the effectiveness of flash flood predictions and ultimately save lives and property. Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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24 pages, 12192 KiB

Open AccessEditor’s ChoiceArticle

Sensitivity of Simulated Conditions to Different Parameterization Choices Over Complex Terrain in Central Chile

by Jorge Arévalo, Julio C. Marín, Mailiu Díaz, Graciela Raga, Diana Pozo, Ana María Córdova and Darrel Baumgardner

Atmosphere 2024, 15(1), 10; https://doi.org/10.3390/atmos15010010 - 21 Dec 2023

Cited by 2 | Viewed by 1502

Abstract

This study evaluates the performance of fourteen high-resolution WRF runs with different combinations of parameterizations in simulating the atmospheric conditions over the complex terrain of central Chile during austral winter and spring. We focus on the validation of results for coastal, interior valleys, and mountainous areas independently, and also present an in-depth analysis of two synoptic-scale events that occurred during the study period: a frontal system and a cut-off low. The performance of the simulations decreases from the coast to higher altitudes, even though the differences are not very clear between the coast and interior valleys for 10 m wind speeds and precipitation. The simulated vertical profiles show a warmer and drier boundary layer and a cooler and moister free atmosphere than observed. The choice of the land-surface model has the largest positive impact on near-surface variables with the five-layer thermal diffusion scheme showing the smallest errors. Precipitation is more sensitive to the choice of cumulus parameterizations, with the simplified Arakawa–Schubert scheme generally providing the best performance for absolute errors. When examining the performance of the model simulating rain/no-rain events for different thresholds, also the cumulus parameterizations better represented the false alarm ratio (FAR) and the bias score (BS). However, the Morrison microphysics scheme resulted in the best critical success index (CSI), while the probability of detection (POD) was better in the simulation without analysis nudging. Overall, these results provide guidance to other researchers and help to identify the best WRF configuration for a specific research or operational goal. Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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23 pages, 12204 KiB

Open AccessArticle

Non-Parametric and Robust Sensitivity Analysis of the Weather Research and Forecast (WRF) Model in the Tropical Andes Region

by Jhon E. Hinestroza-Ramirez, Juan David Rengifo-Castro, Olga Lucia Quintero, Andrés Yarce Botero and Angela Maria Rendon-Perez

Atmosphere 2023, 14(4), 686; https://doi.org/10.3390/atmos14040686 - 6 Apr 2023

Cited by 4 | Viewed by 1872

Abstract

With the aim of understanding the impact of air pollution on human health and ecosystems in the tropical Andes region (TAR), we aim to couple the Weather Research and Forecasting Model (WRF) with the chemical transport models (CTM) Long-Term Ozone Simulation and European Operational Smog (LOTOS–EUROS), at high and regional resolutions, with and without assimilation. The factors set for WRF, are based on the optimized estimates of climate and weather in cities and urban heat islands in the TAR region. It is well known in the weather research and forecasting field, that the uncertainty of non-linear models is a major issue, thus making a sensitivity analysis essential. Consequently, this paper seeks to quantify the performance of the WRF model in the presence of disturbances to the initial conditions (IC), for an arbitrary set of state-space variables (pressure and temperature), simulating a disruption in the inputs of the model. To this aim, we considered three distributions over the error term: a normal standard distribution, a normal distribution, and an exponential distribution. We analyze the sensitivity of the outputs of the WRF model by employing non-parametric and robust statistical techniques, such as kernel distribution estimates, rank tests, and bootstrap. The results show that the WRF model is sensitive in time, space, and vertical levels to changes in the IC. Finally, we demonstrate that the error distribution of the output differs from the error distribution induced over the input data, especially for Gaussian distributions. Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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20 pages, 10931 KiB

Open AccessArticle

Scale-Dependent Verification of the OU MAP Convection Allowing Ensemble Initialized with Multi-Scale and Large-Scale Perturbations during the 2019 NOAA Hazardous Weather Testbed Spring Forecasting Experiment

by Aaron Johnson, Fan Han, Yongming Wang and Xuguang Wang

Atmosphere 2023, 14(2), 255; https://doi.org/10.3390/atmos14020255 - 28 Jan 2023

Cited by 2 | Viewed by 1509

Abstract

Given the large range of resolvable space and time scales in large-domain convection-allowing for ensemble forecasts, there is a need to better understand optimal initial-condition perturbation strategies to sample the forecast uncertainty across these space and time scales. This study investigates two initial-condition perturbation strategies for CONUS-domain ensemble forecasts that extend into the two-day forecast lead time using traditional and object-based verification methods. Initial conditions are perturbed either by downscaling perturbations from a coarser resolution ensemble (i.e., LARGE) or by adopting the analysis perturbations from a convective-scale, EnKF system (i.e., MULTI). It was found that MULTI had more ensemble spread than LARGE across all scales initially, while LARGE’s perturbation energy surpassed that of MULTI after 3 h and continued to maintain a surplus over MULTI for the rest of the 36h forecast period. Impacts on forecast bias were mixed, depending on the forecast lead time and forecast threshold. However, MULTI was found to be significantly more skillful than LARGE at early forecast hours for the meso-gamma and meso-beta scales (1–9h), which is a result of a larger and better-sampled ensemble spread at these scales. Despite having a smaller ensemble spread, MULTI was also significantly more skillful than LARGE on the meso-alpha scale during the 20–24h period due to a better spread-skill relation. MULTI’s performance on the meso-alpha scale was slightly worse than LARGE’s performance during the 6–12h period, as LARGE’s ensemble spread surpassed that of MULTI. The advantages of each method for different forecast aspects suggest that the optimal perturbation strategy may require a combination of both the MULTI and LARGE techniques for perturbing initial conditions in a large-domain, convection-allowing ensemble. Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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