Verification of JNWP-Unit Hurricane and Typhoon Forecasts for 19591

1961 ◽  
Vol 42 (4) ◽  
pp. 239-248 ◽  
Author(s):  
Lloyd W. Vanderman
Keyword(s):  
Sample Size ◽  
Tropical Cyclones ◽  
Northern Hemisphere ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Tropical Storms ◽  
Numerical Weather ◽  
One Year ◽  
Steering Current ◽  
Forecasting Techniques

During the 1959 season for tropical storms in the Northern Hemisphere, Joint Numerical Weather Prediction (JNWP) Unit computed operationally one or more forecast tracks for 11 hurricanes and tropical storms and 11 typhoons. The 500-mb barotropic forecast flow with the tropical vortex eliminated from the initial 500-mb analysis was employed as the steering current in obtaining these forecasts. A summary of 1959 forecasts and a table of verification of JNWP hurricane forecasts for the years 1956 through 1959 are presented. The improvement and deterioration in forecasts from one year to the next are discussed in terms of sample size, operational changes, and analysis and forecasting techniques specifically designed for forecasting trajectories of tropical cyclones.

scholarly journals Improvement in the Forecasting of Heavy Rainfall over South China in the DSAEF_LTP Model by Introducing the Intensity of the Tropical Cyclone

2020 ◽  
Vol 35 (5) ◽  
pp. 1967-1980
Author(s):  
Ding Chenchen ◽  
Fumin Ren ◽  
Yanan Liu ◽  
John L. McBride ◽  
Tian Feng
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
South China ◽  
Numerical Weather Prediction ◽  
Heavy Rainfall ◽  
Prediction Models ◽  
Weather Prediction ◽  
Numerical Weather ◽  
Landfalling Typhoon ◽  
Numerical Weather Prediction Models

AbstractThe intensity of the tropical cyclone has been introduced into the Dynamical-Statistical-Analog Ensemble Forecast (DSAEF) for Landfalling Typhoon (or tropical cyclone) Precipitation (DSAEF_LTP) model. Moreover, the accumulated precipitation prediction experiments have been conducted on 21 target tropical cyclones with daily precipitation ≥ 100 mm in South China from 2012 to 2016. The best forecasting scheme for the DSAEF_LTP model is identified, and the performance of the prediction is compared with three numerical weather prediction models (the European Centre for Medium-Range Weather Forecasts, the Global Forecast System, and T639). The forecasting ability of the DSAEF_LTP model for heavy rainfall (accumulated precipitation ≥ 250 and ≥100 mm) improves when the intensity of the tropical cyclone is introduced, giving some advantages over the three numerical weather prediction models. The selection of analog tropical cyclones with a maximum intensity (during precipitation over land) equaling to or higher than the initial intensity of the target tropical cyclone gives better forecasts. The prediction accuracy for accumulated precipitation is higher for tropical cyclones with higher intensity and higher observed precipitation, with in both cases positive linear correlations with the threat score.

Improving Numerical Weather Prediction-Based Near-Cloud Aviation Turbulence Forecasts by Diagnosing Convective Gravity Wave Breaking

2021 ◽  
Author(s):  
Soo-Hyun Kim ◽  
Hye-Yeong Chun ◽  
Dan-Bi Lee ◽  
Jung-Hoon Kim ◽  
Robert D. Sharman
Keyword(s):  
Gravity Wave ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Area Under The Curve ◽  
Wave Drag ◽  
Probability Of Detection ◽  
Numerical Weather ◽  
Air Turbulence ◽  
One Year ◽  
Nwp Model

AbstractBased on a convective gravity wave drag parameterization scheme in a Numerical Weather Prediction (NWP) model, previously proposed near-cloud turbulence (NCT) diagnostics for better detecting turbulence near convection are tested and evaluated by using global in situ flight data and outputs from operational global NWP model of the Korea Meteorological Administration for one year (from December 2016 to November 2017). For comparison, eleven widely used clear air turbulence (CAT) diagnostics currently used in operational NWP-based aviation turbulence forecasting systems are separately computed. For selected cases, NCT diagnostics predict more accurately localized turbulence events over convective regions with better intensity, which is clearly distinguished from the turbulence areas diagnosed by conventional CAT diagnostics that they mostly failed to forecast with broad areas and low magnitudes. Although overall performance of NCT diagnostics for whole one year is lower than conventional CAT diagnostics due to the fact that NCT diagnostics exclusively focus on the isolated NCT events, adding the NCT diagnostics to CAT diagnostics improves the performance of aviation turbulence forecasting. Especially in the summertime, performance in terms of an area under the curve (AUC) based on probability of detection statistics is the best (AUC = 0.837 with a 4% increase, compared to conventional CAT forecasts) when the mean of all CAT and NCT diagnostics is used, while performance in terms of root mean square error is the best when the maximum among combined CAT and single NCT diagnostic is used. This implies that including NCT diagnostics to currently used NWP-based aviation turbulence forecasting systems should be beneficial for safety of air travel.

One Year of Operational Numerical Weather Prediction, Part II *

1957 ◽  
Vol 38 (6) ◽  
pp. 315-328 ◽  
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Forecasting ◽  
Weather Prediction ◽  
Numerical Weather ◽  
Level Data ◽  
Analysis Center ◽  
Numerical Weather Forecasting ◽  
One Year ◽  
Near Future

This is the second of two brief reports on the activities and results of the Joint Numerical Weather Prediction Unit since May 1955, and is concerned primarily with the accuracy and characteristic errors of the numerical forecasts described in the previous report. The quality of the barotropic and 3-level forecasts has been measured by several statistical indices of error, and compared with that of the subjective forecasts issued by the National Weather Analysis Center. A breakdown of these statistics shows the dependence of forecasting accuracy on length of forecast period, level, data coverage, and proximity of lateral boundaries. Various sources of systematic error are discussed with reference to the JNWP Unit's efforts to isolate and remedy them. After almost a year of experimentation and operational numerical weather forecasting, it is concluded that the quality of the numerical 500 millibar forecasts is not significantly different from that of the best subjective forecasts prepared by methods in current use. Recent results indicate that a significant improvement can be expected in the near future. The numerical 1000 mb forecasts are worse, but recent changes of model show promise of matching the performance of subjective methods. Finally, the most glaring systematic errors of the present numerical forecasts have adequate explanation in existing theory, and can be (or have already been) corrected by generalization of the models.

scholarly journals Prediction of sea state under tropical cyclones in the UK Met Office operational global wave model

MAUSAM ◽  
2021 ◽  
Vol 48 (4) ◽  
pp. 621-628
Author(s):  
M.W. HOLT ◽  
J.C.R. HUNT
Keyword(s):  
Tropical Cyclone ◽  
Prediction Model ◽  
Tropical Cyclones ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Wave Model ◽  
Numerical Weather Prediction Model ◽  
Model Surface ◽  
Sea State ◽  
Numerical Weather

The United Kingdom Meteorological Office (UKMO) routinely runs a global operational numerical weather prediction model. Surface winds from this model are used by a spectral wave model to forecast sea state. A brief description is given of the formulation of the wave model, and two cases of Tropical Cyclones in the Bay of Bengal are examined using the archived data generated in real time by the operational wave model. These are Tropical Cyclone 3B, 14-15 June 1996 and Tropical Cyclone 07B, 4-6 November 1996.   At a resolution of 1.25° in longitude by 0.833° in latitude the numerical weather prediction model does not represent the dynamics of a tropical cyclone and the surface wind speeds are underestimated. Consequently, the extreme sea state generated by a Tropical Cyclone is not modelled. However, the wave model was able to generate a long period swell of over 3m height, which propagated away from the area of generation. Finally, work in progress to blend the operational numerical model surface winds with synthetically generated tropical cyclone surf winds, for use in the operational wave model, is outlined.    

Errors in Upper-Level Wind Forecasts

1957 ◽  
Vol 38 (9) ◽  
pp. 511-517
Author(s):  
Major Hugh W. Ellsaesser
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Numerical Weather ◽  
Standard Pressure ◽  
Upper Level ◽  
Forecasting Techniques

Errors in prognostic winds at standard pressure levels from 700 to 100 mb are investigated. Errors resulting from the use of conventional forecasting techniques (excluding Numerical Weather Prediction), persistence and climatology are compared and inherent errors due to operational techniques are discussed. Both published and manuscript data from American and British sources are used.

Sign in / Sign up

Export Citation Format

Share Document