Verification of Cloud Forecasts over the Eastern Pacific Using Passive Satellite Retrievals

Abstract

Operational cloud forecasts generated by the Coupled Ocean-Atmosphere Mesoscale Prediction System (COAMPS) were verified over the eastern Pacific Ocean. The study focused on the accuracy of cloud forecasts associated with extratropical cyclone and convective activity during the late winter and spring of 2007. The condensed total water (liquid and solid) path was used as a proxy for cloud cover to compare the forecasts with retrievals from the Geostationary Operational Environmental Satellites (GOES). Analyses of the GOES retrievals indicate that deep cloud systems were generally well represented during daylight hours. Thus, the bulk of the verification focused on the general aspects of quality and timing of these deep systems. Multiple statistics were collected, ranging from simple correlations and histograms to more sophisticated fuzzy and composite statistics. The results show that synoptic-scale systems were generally well predicted to at least two days, with the primary error being an overestimation of deep cloud occurrence. Smaller subsynopticscale systems were subject to spatial and timing biases in that a number of the forecasts were lagged by 3-6 h. Despite the bias, 60%-70% of the forecasts of the mesoscale phenomena displayed useful skill.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2009
Accession Number
ADA513417

Entities

People

  • Cristian Mitreschu
  • Jason E. Nachamkin
  • Jerome Schmidt

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Satellites
  • Atmospheres
  • Cloud Cover
  • Clouds
  • Composite Materials
  • Errors
  • False Alarms
  • Grids
  • High Performance Computing
  • High Resolution
  • Lead Time
  • Meteorology
  • Military Research
  • Oceans
  • Statistics
  • Verification

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Regression Analysis.

Technology Areas

  • Space