Numerical Forecast System Research Articles

Eastern Mediterranean biogeochemical flux model – Simulations of the pelagic ecosystem

Abstract. During the second phase (2003–2006) of the Mediterranean ocean Forecasting System Project (MFS) named Toward Environmental Predictions (MFSTEP) one of the three major aims was the development of numerical forecasting systems. In this context a generic Biogeochemical Flux Model (BFM) was developed and coupled with hydrodynamic models already operating at basin scale as well as in regional areas. In the Eastern Mediterranean basin the BFM was coupled with the Aegean Levantine Eddy Resolving MOdel (ALERMO). The BFM is a generic highly complex model based on ERSEM and although a detailed description of the model and its components is beyond the scope of this work, a short overview of the main processes, laying emphasis on the parameter values used is presented. In addition the performance of the model is evaluated with some preliminary results being qualitatively compared against field observations. The model in its present form is rather promising and reproduces all important major features although there are some slight inefficiencies mostly related to primary and bacterial productivity rates.

A Local Ensemble Prediction System for Fog and Low Clouds: Construction, Bayesian Model Averaging Calibration, and Validation

Abstract At main international airports, air traffic safety and economic issues related to poor visibility conditions are crucial. Meteorologists face the challenge of supplying airport authorities with accurate forecasts of fog and cloud ceiling. These events are difficult to forecast because conditions evolve on short space and time scales during their life cycle. To obtain accurate forecasts of fog and low clouds, the Code de Brouillard à l’Echelle Locale (the local scale fog code)–Interactions between Soil, Biosphere, and Atmosphere (COBEL–ISBA) local numerical forecast system was implemented at Charles de Gaulle International Airport in Paris. However, even with dedicated observations and initialization, uncertainties remain in both initial conditions and mesoscale forcings. A local ensemble prediction system (LEPS) has been designed around the COBEL–ISBA numerical model and tested to assess the predictability of low visibility procedures events, defined as a visibility less than 600 m and/or a ceiling below 60 m. This work describes and evaluates a local ensemble strategy for the prediction of low visibility procedures. A Bayesian model averaging method has been applied to calibrate the ensemble. The study shows that the use of LEPS for specific local event prediction is well adapted and useful for low visibility prediction in the aeronautic context. Moreover, a wide range of users, especially those with low cost–loss ratios, can expect economic savings with the use of this probabilistic system.

Quality Assessment of the Cobel-Isba Numerical Forecast System of Fog and Low Clouds

Short-term forecasting of fog is a difficult issue which can have a large societal impact. Fog appears in the surface boundary layer and is driven by the interactions between land surface and the lower layers of the atmosphere. These interactions are still not well parameterized in current operational NWP models, and a new methodology based on local observations, an adaptive assimilation scheme and a local numerical model is tested. The proposed numerical forecast method of foggy conditions has been run during three years at Paris-CdG international airport. This test over a long-time period allows an in-depth evaluation of the forecast quality. This study demonstrates that detailed 1-D models, including detailed physical parameterizations and high vertical resolution, can reasonably represent the major features of the life cycle of fog (onset, development and dissipation) up to +6 h. The error on the forecast onset and burn-off time is typically 1 h. The major weakness of the methodology is related to the evolution of low clouds (stratus lowering). Even if the occurrence of fog is well forecasted, the value of the horizontal visibility is only crudely forecasted. Improvements in the microphysical parameterization and in the translation algorithm converting NWP prognostic variables into a corresponding horizontal visibility seems necessary to accurately forecast the value of the visibility.

Seasonal Sensitivity on COBEL-ISBA Local Forecast System for Fog and Low Clouds

Skillful low visibility forecasts are essential for air-traffic managers to effectively regulate traffic and to optimize air-traffic control at international airports. For this purpose, the COBEL-ISBA local numerical forecast system has been implemented at Paris CDG international airport. This local approach is robust owing to the assimilation of detailed local observations. However, even with dedicated observations and initialization, uncertainties remain in both initial conditions and mesoscale forcings. The goal of the research presented here is to address the sensitivity of COBEL-ISBA forecast to initial conditions and mesoscale forcings during the winter season 2002-2003. The main sources of uncertainty of COBEL-ISBA input parameters have been estimated and the evaluation of parameter uncertainty on the forecasts has been studied. A budget strategy is applied during the winter season to quantify COBEL-ISBA sensitivity. This study is the first step toward building a local ensemble prediction system based on COBEL-ISBA. The conclusions of this work point out the potential for COBEL-ISBA ensemble forecasting and quantify sources of uncertainty that lead to dispersion. Accurate prediction of fog and low clouds is one of the main issues related to improving air-traffic management and safety. At Paris Charles de Gaulle (CdG) international airport, adverse ceiling and visibility conditions (visibility under 600 m and ceiling below 60 m) lead to the application of Low Visibility Procedures (LVP). Under these conditions, the airport take-off/landing efficiency is reduced by a factor of 2, causing aircraft delays. In this context, accurate short-term forecasts of LVP conditions are considered to be a priority by airport authorities. Unfortunately, current operational Numerical Weather Prediction (NWP) models are not able to provide detailed information due to their lack of both vertical and horizontal resolutions with respect to the typical length scale of fog. However, owing to higher vertical resolution and more detailed physics than 3D

Implementation and evaluation of cloud analysis with WSR‐88D reflectivity data for GSI and WRF‐ARW

The cloud analysis procedure of the Advanced Regional Prediction System (ARPS) is implemented in a proposed operational numerical forecast system composed of the Grid‐point Statistical Interpolation (GSI) and the Advanced Research WRF (WRF‐ARW). The case of 23 May 2005 Central Plains storm cluster is used to assess the impact of the cloud analysis using reflectivity data from six operational WSR‐88D radars within the proposed operational configuration on 6‐h forecast of the storm cluster. The cloud analysis is shown to significantly reduce the spin‐up problem and improve the short‐range forecast for the storm cluster, even at the relatively coarse 9 km resolution.

Hurricane Juan (2003). Part II: Forecasting and Numerical Simulation

Abstract The landfall of Hurricane Juan (September 2003) in the Canadian Maritimes represents an ideal case in which to study the performance of operational forecasting of an intense, predominantly tropical feature entering the midlatitudes. A hybrid cyclone during its genesis phase, Juan underwent a tropical transition as it drifted slowly northward 1500 km from the east coast of the United States. Shortly after reaching its peak intensity as a category-2 hurricane, the storm accelerated rapidly northward and made landfall near Halifax, Nova Scotia, Canada, with maximum sustained winds of 44 m s−1. Although the forecasts and warnings produced by the U.S. National Hurricane Center and the Canadian Hurricane Centre were of high quality throughout Hurricane Juan’s life cycle, guidance from numerical weather prediction models became unreliable as the storm accelerated toward the coast. The short-range, near-surface forecasts from eight operational models during the crucial prelandfall portion of Juan’s track are investigated in this study. Despite continued improvements to operational numerical forecasting systems, it is shown that those systems not employing advanced tropical vortex initialization techniques were unable to provide forecasters with credible near-surface guidance in this case. A pair of regional forecasts, one successful and one from the failed model set, are compared in detail. Spurious asymmetries in the initial vortex of the deficient model are shown to hamper structural predictions and to cause nonnegligible track perturbations from the trajectory implied by the well-described deep-layer mean flow. The Canadian Mesoscale Compressible Community model is rerun with an improved representation of the hurricane’s vortex in the initial state. The hindcast produced following the tropical cyclone initialization contains reduced track, structure, and intensity errors compared with those generated by the model in real time. The enhanced initial intensity produces a direct improvement in the forecast storm strength throughout the period, and the symmetrization of the vortex eliminates the interactions that plague the operational system. The southeastward relocation of the implanted vortex to Juan’s observed location eliminates a significant northwestward track bias under the influence of a broad area of southerly steering flow. The study concludes that the initialization of Hurricane Juan’s structure and position adds value to numerical guidance even as the storm accelerates poleward at a latitude where the implantation of a quasi-symmetric vortex may not be generally valid.

A Numerical Forecasting System for the Prediction of Slippery Roads

Abstract A numerical forecasting system is presented for automatic prediction of slippery road conditions at road station sites in Denmark. The system is based on a road conditions model forced by input from an operational atmospheric limited area model. Synoptic information on cloud cover and observations of temperature and humidity from the road station sites are taken into account in a sophisticated initialization procedure involving flux corrections for individual locations. The system is run operationally at the Danish Meteorological Institute with promising results. Currently, new forecasts 5 h ahead are produced every hour for 200 road station sites. The potential of the model system is illustrated by model forecasts from two selected periods and operational results. Problems related to the accurate forecasting of road conditions are discussed.

Error Growth in a Large Numerical Forecast System

Internal and external z500 global total rms errors followed quadratic growth laws quite well in NMC Medium-Range Forecast (MRF) Model 0–10-day forecasts for 1988–93. Growth parameters and model and analysis errors for many winter were estimated using the quadratic rms error growth assumption. Both the MRF model error and analysis error have nearly halved during 1988–93. But at the same time the growth parameters have nearly doubled: smaller errors grow faster. Thus while the limit of deterministic predictability (rms error 71% of saturation) has been going up, the limit of dynamic predictability (rms error 97.5% of saturation) seems to be set at around 20 days in large horizontal scales, dropping to 6–7 days in small scales.

The wave forecast system of the “Deutscher Wetterdienst” and the “Bundesamt für Seeschiffahrt und hydrographie”: A verification using ERS-1 altimeter and scatterometer data

A new numerical wave forecast system, implemented on the computer of the “Deutscher Wetterdienst” (DWD), has provided operational wave forecasts since June 1992. The system consists of three modules, a deep water wave model for the North Atlantic and two shallow water wave models for the North European shelf area and the Baltic. The North Atlantic wave model is forced by the wind fields of the global atmospheric model T106, while the shallow water wave models are driven by wind forecasts of the “European model” of the DWD. A limited verification of the wave forecasts is based on comparisons with local buoy measurements. A thorough validation of the wave model results follows using “Fast Delivery Products” of the ERS-1 satellite for the one week period from 4th to 10th of January 1993. The ERS-1 products include windspeed and-direction derived by the scatterometer plus windspeed and significant waveheight recorded by the radar altimeter. In general the comparisons show a fairly good agreement between the altimeter waveheights and the wave model results. However, there are considerable deviations between the scatterometer wind directions and those computed by the atmospheric DWD-models in some cases, particularly in rather data sparse regions of the ocean. The measured windspeeds recorded by scatterometer and altimeter are usually smaller than the windspeeds computed by the atmospheric models. In conclusion, the comparisons between satellite and model data demonstrate that the new forecast system works properly and provides reliable data.

A Synoptic Comparison of SSM/I Winds with Output from an Operational Forecast System

Near-surface wind speed analyses from the Special Microwave/Imager (SSM/I) are compared with those from an operational numerical forecast system. Substantial agreement exists, especially over open ocean. Nevertheless, the use of both fields together should lead to a better understanding of the synoptic situation than the use of either field alone. The SSM/I winds give a superior representation of spatial variations of wind speeds. Also, the SSM/I information can he used to examine continental influences on marine wind speeds. Such mesoscale effects are not analyzed well by global numerical models. On the other hand, the output from the numerical forecast system provides wind direction, a parameter not available from the SSM/I. In addition, forecast system winds fill in information between satellite passes and in regions contaminated by precipitation.

A Diagnostic Study of the Impact of SEASAT Scatterometer Winds on Numerical Weather Prediction

With the launch of ERS-1, observations of the wind close to the sea surface are expected to become available in near real time. To assess the effect of this new form of meteorological data an operational numerical weather prediction, the impact of similar data, from the SEASAT-A scatterometer in 1978, has been studied in the numerical forecasting system of the U.K. Meteorological Office. Some modifications to the system were necessary before the SEASAT data were assimilated into the model. The geographical distribution of the differences between the analyses in a control run (without SEASAT data) and a parallel run (including SEASAT data) showed the largest values in the Southern Hemisphere and in association with some disturbances in the tropics. Studies have been made of the influence of some of the internal features of the assimilation scheme, especially the vertical cutoff in the data selection and the vertical correlation function. Changes to the model's divergence and vorticity have also been investigated. Overall, the inclusion of the SEASAT data appears to have slightly improved the model analyses. The differences between the two versions of the forecasts to 24 hours have been reviewed. Assessment is difficult because of the lack of corroborating data, but a beneficial effect has been found in the meridional wind, and a change in the ageostrophic flow has been detected.

An Interactive Analysis and Forecast System for Tropical Cyclone Motion

The design concept and operational trial of a fully interactive analysis and numerical forecast system for tropical-cyclone motion are described. The design concept emphasizes an interactive system in which forecasters can test various scenarios objectively, rather than having to subjectively decide between conflicting forecasts from standardized techniques. The system is designed for use on a personal computer, or workstation, located on the forecast bench. A choice of a Barnes or statistical interpolation scheme is provided to analyze raw or bogus observations at any atmospheric level or layer mean selected by the forecaster. The track forecast is then made by integration of a nondivergent barotropic model. An operational trial during the 1990 tropical-cyclone field experiments in the western north Pacific Ocean indicated that the system can be used very effectively in real time. A series of case-study examples is presented.

A model for the interpretation of verbal predictions

There is a marked gap between the demands on forecasting and the results that numerical forecasting techniques usually can provide. It is suggested that this gap can be closed by the implementation of experts' qualitative predictions into numerical forecasting systems. A formal analysis of these predictions can then be integrated into quantitative forecasts. In the framework of possibility theory, a model is developed which accounts for the verbal judgments in situations where predictions are made or knowledge is updated in the light of new information. The model translates verbal expressions into elastic constraints on a numerical scale. This numerical interpretation of qualitative judgments can then be implemented into numerical forecasting procedures. The applicability of this model was tested experimentally. The results indicate that the numerical predictions from the model agree well with the actual judgments and the evaluation behavior of the subjects. The applicability of this model is demonstrated in a study where bank clerks had to predict exchange rates. The analysis of qualitative judgments according to this model provided significantly more information than numerical predictions. A general framework for an interactive forecasting systems is suggested for further developments.

Tests on Some Programmed Numerical Wave Forecast Models

Abstract Numerical forecasting of wind-generated ocean waves by digital computer may be attempted using any of three fundamentally different ways of describing wave generation and decay: empirical significant wave, empirical spectral, and theoretical spectral. This paper describes four models, covering the three types, which have been programmed with a view to the adaptation of one or more into a numerical wave forecast system for the Australian region. Results from a simple test situation are presented, both for comparison purposes and as a check on the internal consistency of the model's generation and decay functions.