Statistical Post-Processing of the Navy Nested Tropical Cyclone Model and the Operational Tropical Cyclone Model.

Abstract

A statistical technique proposed by Elsberry and Frill (1980) for adjusting dynamical tropical cyclone motion forecasts is extended to the Two-Way Interactive Nested Tropical Cyclone Model (NTCM) and the operational One-Way Interactive Tropical Cyclone Model (TCMO). The technique utilizes linear regression equations to reduce systemic errors. Backward extrapolation positions are presented as a less expensive, but inferior, alternative to the backward integration positions required by the original technique. A scheme is developed for applying the technique in storm-motion coordinates as well as zonal-meridional coordinates. Tests with 186 NTCM cases indicate moderate improvement in forecast errors by the zonal-meridional regression technique, and slight improvement by the storm-coordinate scheme. In TCMO tests with 212 cases, the zonal-meridional regression equations reduced the forecast errors, but the storm-coordinate equations did not. The technique failed to improve forecast errors in independent tests with NTCM 1981 data, presumably due to differences in error biases, which indicates a need for a larger sample size. Alternatively backward integration positions may be necessary to achieve consistent improvements from this statistical technique. The technique was able to improve 60h-72h forecast errors in TCMO 1981 cases. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1981
Accession Number
ADA114150

Entities

People

  • James E. Peak
  • Russell L. Elsberry

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Atmospheric Sciences
  • Cyclones
  • Databases
  • Earth Sciences
  • Extrapolation
  • Geography
  • Grids
  • Lisp Programming Language
  • Longitude
  • Meteorology
  • Models
  • Oceanography
  • Research Facilities
  • Right Angles
  • Schools
  • Standards
  • Tropical Cyclones

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers