scholarly journals A Diagram Depicting Forecast Skill and Predictability

1984 ◽  
Vol 65 (7) ◽  
pp. 701-703 ◽  
Author(s):  
Richard A. Anthes ◽  
David P. Baumhefner
Keyword(s):  
Numerical Weather Prediction ◽  
Numerical Models ◽  
Weather Prediction ◽  
Current Level ◽  
Forecast Skill ◽  
Numerical Weather ◽  
Prediction Systems ◽  
Atmospheric Phenomena

In operational numerical weather prediction systems, both observations and numerical models contribute to the skill of the forecast. A simple diagram representing the relative contributions of observations and models to the current level of forecast skill and to the ultimate predictability of atmospheric phenomena is interpreted in this note. The forecast skill of 500 mb heights and an estimate of the ultimate predictability of this variable are used in a quantitative illustration of the diagram.

scholarly journals Assessing the impact of Argo floats temperature measurements on the numerical weather prediction forecast skill

2019 ◽  
Vol 20 (2) ◽  
pp. 331 ◽  
Author(s):  
GEORGE VARLAS ◽  
PETROS KATSAFADOS ◽  
GERASIMOS KORRES ◽  
ANASTASIOS PAPADOPOULOS
Keyword(s):  
Boundary Conditions ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Lower Boundary ◽  
Forecast Skill ◽  
Temperature Measurements ◽  
Precipitation Forecast ◽  
Numerical Weather ◽  
Argo Floats ◽  
The Impact

The forecast skill of numerical weather prediction (NWP) models relies, among other factors such as the prediction itself and the assimilation scheme, on the accuracy of the observations utilized in the assimilation systems for the production of initial and boundary conditions. One of the most crucial parameters in weather forecasting is the sea surface temperature (SST). In the majority of NWP models, the initial and lower boundary conditions involve gridded (SST) analyses which consist of data obtained by buoys, ships and satellites. The main aim of this study is to integrate Argo temperature measurements in gridded SST analyses and to assess their impact on the forecast skill of a limited area atmospheric model. Argo floats are “state-of-the-art” oceanographic instruments producing high-quality temperature profiles for the ice-free ocean. In this study, Argo temperatures are incorporated into gridded SST fields without applying any smoothing method in order to directly assess the impact of Argo temperatures on numerical weather prediction. Their impact is assessed under intense weather cyclonic conditions at the Mediterranean Sea by performing two sensitivity simulations either incorporating or not Argo temperatures into gridded SST fields used in the generation of the initial and lower boundary conditions. The results indicate that the inclusion of Argo-measured near-surface temperatures in the lower boundary condition modifies the surface heat fluxes, thus affecting mean sea level pressure and precipitation. In particular, an overall improvement of the precipitation forecast skill up to 3% has been demonstrated. Moreover, the incorporation of Argo temperatures affects the simulated track and intensity of the cyclone over the Balkan Peninsula.

scholarly journals On the Effect of Model Parameters on Forecast Objects

2017 ◽  
Author(s):  
Caren Marzban ◽  
Corinne Jones ◽  
Ning Li ◽  
Scott Sandgathe
Keyword(s):  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Numerical Models ◽  
Weather Prediction ◽  
Clustering Algorithms ◽  
Numerical Weather Prediction Model ◽  
Model Parameters ◽  
Numerical Weather ◽  
The Impact ◽  
Mesoscale Numerical Weather Prediction

Abstract. Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature "map". However, the field for some quantities such as precipitation generally consists of spatially coherent and disconnected "objects". Certain features of these objects (e.g., number, size, and intensity) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on features of forecast objects. Although, in principle, the objects can be defined by any means, here they are identified via clustering algorithms. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

scholarly journals Processing and quality control with FY-3C/GNOS data used in numerical weather prediction applications

2018 ◽  
Author(s):  
Mi Liao ◽  
Sean Healy ◽  
Peng Zhang
Keyword(s):  
Quality Control ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
Noise Estimate ◽  
Ionosphere Model ◽  
Angle Space ◽  
Prediction Systems ◽  
L1 And L2

Abstract. The Chinese radio occultation sounder GNOS (Global Navigation Occultation Sounder) is on the FY-3C satellite, which was launched on September 23, 2013. Currently, GNOS data is transmitted via the Global Telecommunications System (GTS) providing 450–500 profiles per day for numerical weather prediction applications. This paper describes the processing for the GNOS profiles with large biases, related to L2 signal degradation. A new extrapolation procedure in bending angle space corrects the L2 bending angles, using a thin ionosphere model, and the fitting relationship between L1 and L2. We apply the approach to improve the L2 extrapolation of GNOS. The new method can effectively eliminate about 90 % of the large departures. In addition to the procedure for the L2 degradation, this paper also describes our quality control (QC) for FY-3C/GNOS. A noise estimate for the new L2 extrapolation can be used as a QC parameter to evaluate the performance of the extrapolation. Mean phase delays of L1 and L2 in the tangent height interval of 60 to 80 km are analysed and applied in the QC as well. A statistical comparison between GNOS and ECMWF (European Centre for Medium-Range Weather Forecasts) forecast data demonstrates that GNOS performs almost as well as GRAS, especially in the core region from around 10 to 35 km. The GNOS data with the new L2 extrapolation is suitable for assimilation into numerical weather prediction systems.

scholarly journals Precipitation forecast skill of numerical weather prediction models and radar nowcasts

2005 ◽  
Vol 32 (14) ◽  
pp. n/a-n/a ◽  
Author(s):  
Charles Lin ◽  
Slavko Vasić ◽  
Alamelu Kilambi ◽  
Barry Turner ◽  
Isztar Zawadzki
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Forecast Skill ◽  
Precipitation Forecast ◽  
Numerical Weather ◽  
Numerical Weather Prediction Models
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