Author: Publisher:
ISBN:
Category : Numerical weather forecasting
Languages : en
Pages : 139
Book Description
Diagnosing Cloudiness from Global Numerical Weather Prediction Model Forecasts
Author: Publisher:
ISBN:
Category : Numerical weather forecasting
Languages : en
Pages : 139
Book Description
Diagnosing Cloudiness from Global Numerical Weather Prediction Model Forecasts
Author: Publisher:
ISBN:
Category : Numerical weather forecasting
Languages : en
Pages : 156
Book Description
Diagnosing Cloudiness from Global Numerical Weather Prediction
Author: Donald C. NorquistCloud Cover Predictions Diagnosed from Global Numerical Weather Prediction Model Forecasts
Author: Donald C. NorquistPublisher:
ISBN:
Category : Cloud forecasting
Languages : en
Pages : 154
Book Description
Environmental Research Papers
Author: Publisher:
ISBN:
Category : Environmental geology
Languages : en
Pages : 162
Book Description
Scientific and Technical Aerospace Reports
Author: Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 602
Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Conference on Numerical Weather Prediction
Author: Publisher:
ISBN:
Category : Numerical weather forecasting
Languages : en
Pages : 722
Book Description
Bulk Meteorological Parameters for Diagnosing Cloudiness in the Stochastic Cloud Forecast Model
Author: Publisher:
ISBN:
Category : Cloud forecasting
Languages : en
Pages : 59
Book Description
The three dimensional distribution of clouds is of great interest to the Air Force, and to the aviation community in general. The Stochastic Cloud Forecast Model (SCFM) is a novel, global cloud model currently operated at the Air Force Weather Agency (AFWA) which diagnoses cloud cover statistically using a minimal set of predictors from global numerical forecasts. Currently the four predictors are pressure, temperature, vertical velocity, and relative humidity. In this thesis, 330 sets of predictors are compared in the SCFM-R, a research version of the model programmed for this thesis. There are some differences in the SCFM and the SCFM-R that yield important information. It is found that the SCFM is very sensitive to how cloud cover in the boundary layer is diagnosed. An analysis of the diagnosis method used to initialize the model revealed a bias for over-diagnosing cloud at lower levels and under-diagnosing cloud at upper levels. Also, it is recommended that AFWA consider exchanging temperature for another predictor more related to moisture, such as cloud water, and that relative humidity is included as relative humidity to the fourth power. Other recommendations include improving the method for diagnosing cloud cover in the boundary layer and improving the model initial condition.
Cloud Cover Predictions Diagnosed from Global Numerical Weather Prediction Model Forecasts
Author: Donald C. NorquistPublisher:
ISBN:
Category : Cloud forecasting
Languages : en
Pages : 0
Book Description
Author: