Basic features of calculating field characteristics of meteorological quantities

2020 ◽  
Vol 04 (05) ◽  
pp. 49-52
Author(s):  
Sevda Nofal Gojayeva Gasimova ◽  
Keyword(s):  
Key Words ◽  
Prediction Models ◽  
Forecast Model ◽  
Numerical Prediction ◽  
Weather Forecasts ◽  
Basic Characteristics ◽  
Basic Features

The article analyzes the main characteristics of the field characteristics of meteorological quantities. One of the main priorities now facing aviation meteorology is to use numerical prediction models for the development of weather forecasts to ensure the regularity and reliability of modern meteorological flights. In this regard, the analysis of the basic characteristics of the field characteristics of meteorological quantities is practical. The use of numerical prediction models in the design of weather forecasts provides the basis for their reliability. Key words: weather pressure, weather temperature, weather humidity, forecast model

Forecasting of Tornadoes and Downbursts

2020 ◽  
Author(s):  
Djordje Romanic
Keyword(s):  
Chaos Theory ◽  
Prediction Models ◽  
Weather Prediction ◽  
Small Scale ◽  
Weather Forecasts ◽  
Wind Speeds ◽  
The Past ◽  
Extreme Wind ◽  
Extreme Wind Speeds ◽  
Numerical Weather Prediction Models

Tornadoes and downbursts cause extreme wind speeds that often present a threat to human safety, structures, and the environment. While the accuracy of weather forecasts has increased manifold over the past several decades, the current numerical weather prediction models are still not capable of explicitly resolving tornadoes and small-scale downbursts in their operational applications. This chapter describes some of the physical (e.g., tornadogenesis and downburst formation), mathematical (e.g., chaos theory), and computational (e.g., grid resolution) challenges that meteorologists currently face in tornado and downburst forecasting.

scholarly journals What Is the Predictability Limit of Midlatitude Weather?

2019 ◽  
Vol 76 (4) ◽  
pp. 1077-1091 ◽  
Author(s):  
Fuqing Zhang ◽  
Y. Qiang Sun ◽  
Linus Magnusson ◽  
Roberto Buizza ◽  
Shian-Jiann Lin ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Weather Prediction ◽  
Forecast Model ◽  
Small Scale ◽  
Lead Times ◽  
Winter Storms ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
Forecast Lead Time ◽  
Order Of Magnitude

Abstract Understanding the predictability limit of day-to-day weather phenomena such as midlatitude winter storms and summer monsoonal rainstorms is crucial to numerical weather prediction (NWP). This predictability limit is studied using unprecedented high-resolution global models with ensemble experiments of the European Centre for Medium-Range Weather Forecasts (ECMWF; 9-km operational model) and identical-twin experiments of the U.S. Next-Generation Global Prediction System (NGGPS; 3 km). Results suggest that the predictability limit for midlatitude weather may indeed exist and is intrinsic to the underlying dynamical system and instabilities even if the forecast model and the initial conditions are nearly perfect. Currently, a skillful forecast lead time of midlatitude instantaneous weather is around 10 days, which serves as the practical predictability limit. Reducing the current-day initial-condition uncertainty by an order of magnitude extends the deterministic forecast lead times of day-to-day weather by up to 5 days, with much less scope for improving prediction of small-scale phenomena like thunderstorms. Achieving this additional predictability limit can have enormous socioeconomic benefits but requires coordinated efforts by the entire community to design better numerical weather models, to improve observations, and to make better use of observations with advanced data assimilation and computing techniques.

scholarly journals Assessment of Radio Occultation Observations from the COSMIC-2 Mission with a Simplified Observing System Simulation Experiment Configuration

2017 ◽  
Vol 145 (9) ◽  
pp. 3581-3597 ◽  
Author(s):  
L. Cucurull ◽  
R. Li ◽  
T. R. Peevey
Keyword(s):  
Radio Occultation ◽  
Weather Forecasting ◽  
System Simulation ◽  
Weather Prediction ◽  
Forecast Model ◽  
Forecast Skill ◽  
Weather Forecasts ◽  
Global Coverage ◽  
Prediction Systems ◽  
Observing System Simulation Experiment

The mainstay of the global radio occultation (RO) system, the COSMIC constellation of six satellites launched in April 2006, is already past the end of its nominal lifetime and the number of soundings is rapidly declining because the constellation is degrading. For about the last decade, COSMIC profiles have been collected and their retrievals assimilated in numerical weather prediction systems to improve operational weather forecasts. The success of RO in increasing forecast skill and COSMIC’s aging constellation have motivated planning for the COSMIC-2 mission, a 12-satellite constellation to be deployed in two launches. The first six satellites (COSMIC-2A) are expected to be deployed in December 2017 in a low-inclination orbit for dense equatorial coverage, while the second six (COSMIC-2B) are expected to be launched later in a high-inclination orbit for global coverage. To evaluate the potential benefits from COSMIC-2, an earlier version of the NCEP’s operational forecast model and data assimilation system is used to conduct a series of observing system simulation experiments with simulated soundings from the COSMIC-2 mission. In agreement with earlier studies using real RO observations, the benefits from assimilating COSMIC-2 observations are found to be most significant in the Southern Hemisphere. No or very little gain in forecast skill is found by adding COSMIC-2A to COSMIC-2B, making the launch of COSMIC-2B more important for terrestrial global weather forecasting than that of COSMIC-2A. Furthermore, results suggest that further improvement in forecast skill might better be obtained with the addition of more RO observations with global coverage and other types of observations.

scholarly journals A Similarity-Based Implementation of the Schaake Shuffle

2016 ◽  
Vol 144 (5) ◽  
pp. 1909-1921 ◽  
Author(s):  
Roman Schefzik
Keyword(s):  
Prediction Models ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Similarity Criterion ◽  
Ensemble Prediction ◽  
Ensemble Forecasts ◽  
Weather Forecasts ◽  
Prediction Horizon ◽  
Prediction Systems ◽  
Specific Implementation

Contemporary weather forecasts are typically based on ensemble prediction systems, which consist of multiple runs of numerical weather prediction models that vary with respect to the initial conditions and/or the parameterization of the atmosphere. Ensemble forecasts are frequently biased and show dispersion errors and thus need to be statistically postprocessed. However, current postprocessing approaches are often univariate and apply to a single weather quantity at a single location and for a single prediction horizon only, thereby failing to account for potentially crucial dependence structures. Nonparametric multivariate postprocessing methods based on empirical copulas, such as ensemble copula coupling or the Schaake shuffle, can address this shortcoming. A specific implementation of the Schaake shuffle, called the SimSchaake approach, is introduced. The SimSchaake method aggregates univariately postprocessed ensemble forecasts using dependence patterns from past observations. Specifically, the observations are taken from historical dates at which the ensemble forecasts resembled the current ensemble prediction with respect to a specific similarity criterion. The SimSchaake ensemble outperforms all reference ensembles in an application to ensemble forecasts for 2-m temperature from the European Centre for Medium-Range Weather Forecasts.

scholarly journals Poleward Atmospheric Energy Transports and Their Variability as Evaluated from ECMWF Reanalysis Data

2012 ◽  
Vol 25 (2) ◽  
pp. 734-752 ◽  
Author(s):  
Michael Mayer ◽  
Leopold Haimberger
Keyword(s):  
Energy Budget ◽  
Energy Transport ◽  
Southern Oscillation ◽  
Forecast Model ◽  
Reanalysis Data ◽  
Energy Budgets ◽  
Global Energy ◽  
Weather Forecasts ◽  
Short Period ◽  
Global Energy Budget

Abstract The vertically integrated global energy budget is evaluated with a direct and an indirect method (both corrected for mass inconsistencies of the forecast model), mainly using the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis Interim (ERA-Interim) data. A new estimate for the net poleward total energy transport is given. Comparison to satellite-derived radiation data proves that ERA-Interim is better suited for investigation of interannual variations of the global energy budget than available satellite data since these either cover a relatively short period of time or are too inhomogeneous in time. While much improved compared to the 40-yr ECMWF Re-Analysis (ERA-40), regionally averaged energy budgets of ERA-Interim show that strong anomalies of forecasted vertical fluxes tend to be partly compensated by unrealistically large forecasted energy storage rates. Discrepancies between observed and forecasted monthly mean tendencies can be taken as rough measure for the uncertainties involved in the ERA-Interim energy budget. El Niño–Southern Oscillation (ENSO) is shown to have large impact on regional energy budgets, but strong compensation occurs between the western and eastern Pacific, leading to only small net variations of the total poleward energy transports (similar magnitude as the uncertainty of the computations). However, Hovmöller longitude–time plots of tropical energy exports show relatively strong slowly eastward-moving poleward transport anomalies in connection with ENSO. Verification of these findings using independent estimates still needs to be done.

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