Search

There is an operational requirement to formulate an objective procedure to handle operational cyclone forecasting work in a more efficient and effective way. In this paper we propose a four-step statistical-dynamical scheme for the real time application in cyclone forecasting work. The four-step scheme consists of (a) Analysis of Genesis Potential Parameter (GPP), (b) Estimation of Maximum Potential Intensity (MPI), (c) 72 hours Intensity Prediction and (d) Prediction of decaying intensity after the landfall. In November 2007, a very severe cyclonic storm 'SIDR' formed over the Bay of Bengal and hit the Bangladesh coast. In this paper, a four-step procedure is demonstrated for real time forecasting this cyclone. The results show that the GPP analysis at early stages of development can strongly indicate that the cyclone »SIDR« had enough potential to reach its cyclone stage. The MPI of the cyclone based on the SST (Sea Surface Temperature) values along the cyclone track is estimated to be 146 knots. The observed maximum intensity of the cyclone is found to be 79 % of its MPI. The 72 hours intensity prediction based on 00 UTC on 12 November could reproduce the intensity value of 109 knots, an underestimation of 6 knots. The subsequent updated forecasts are found to be realistic and useful. The 6-hourly decaying intensity forecast after the landfall shows an underestimation of 10 knots at 12 hours forecast and a significant improvement is noticed with the incorporation of correction factor. The study has documented the potentiality of the procedure for operational application. [ABSTRACT FROM AUTHOR]

This paper is primarily devoted to general discussion of HRID (High resolution isentropic diagnosis) model developed by Glasnović (1983) and its vertical time cross-sections used operationally on direct output of forecasting model ALADIN (Aire Limitee Adaptation Dynamique et Development International). HRID is based on polynomial hydrostatic adjustment technique making use of reciprocal value of thermal stability parameter and its higher order derivatives. Since these relations are applied in local points of vertical interpolation, the problem is considered analytically, eliminating the finite difference approximation procedure in layers with different isentropic thicknesses. This paper presents a local 72 hourly ALADIN/HRID forecast for the city of Split, Croatia, at the eastern Adriatic coast, with detailed vertical atmospheric structure indicating the characteristic features of a frontal passage on 2 January 2007. [ABSTRACT FROM AUTHOR]

In this paper a Multi-Model Ensemble (MME) technique is experimented for improving day to day rainfall forecast over India in short to medium range time scale during summer monsoon of 2010. Four operational global Numerical Weather Prediction (NWP) models namely, ECMWF, JMA, NCEP GFS and UKMO available on real time basis at India meteorological Department (IMD), New Delhi are used simultaneously with appropriate weights to obtain the MME Technique. In this technique, weights for each NWP model at each grid point is assigned on the basis of the correlation coefficient (CC) between model forecasts and observed daily rainfall time series of south west monsoon (JJAS) season. Apart from MME, a simple ensemble mean (ENSM) forecast are also generated and experimented. The rainfall prediction skill of the weighted MME is examined against ENSM and member models. The inter-comparison reveals that the weighted MME is able to provide more accurate forecast of rainfall over Indian monsoon region by taking the strength of each constituent member model. It has been further found that the rainfall prediction skill of MME is higher as compared to ENSM and member models in the short range time scale. The rainfall prediction skill of weighted MME technique improved significantly over India. [ABSTRACT FROM AUTHOR]

India Meteorological Department (IMD) has been using a Limited Area Model (LAM) on operational basis for the forecast up to 48 hours with the first guess fields for objective analysis and lateral boundary conditions from the global spectral model (T-80) run of the National Center for Medium Range Weather Forecasting (NCMRWF), New Delhi. In this paper the model code has been modified and made more flexible, delinking it from the NCMRWF (T-80). This has allowed the use of initial and boundary conditions directly from the NCEP Global Forecast System (GFS) products available at the resolution of 1° × 1° lat./long. The main interest in this study is to improve the analysis and forecast in the short range time scale (up to 72 hours) by improving the model (LAM) resolution and using better Initial and boundary conditions from the NCEP GFS instead of the NCMRWF T-80 model. Simulation experiments are performed on wide variety of synoptic situations which occur very often over the Indian sub-continent. The performance evaluation in terms of qualitative comparison between the model simulated outputs against actual observations and the outputs of the operational model indicates that the modified version of the model is capable to provide a improved numerical guidance on the occurrence of heavy rainfall in the 48-72 hours forecast scale. [ABSTRACT FROM AUTHOR]

Accurate prediction of monsoon heavy rainfall events in the equatorial region has always been a challenge to weather forecasters. In this paper, forecast of a severe precipitation event that occurred over the eastern central coast of Peninsular Malaysia was attempted using the state-of-the-art Florida State University (FSU) Global and Regional Spectral Models. The sensitivity of parameterized convection in these models on precipitation forecast skill is studied using two different parameterization schemes for cumulus convection (the Relaxed Arakawa-Schubert scheme and the modified Kuo scheme). Low precipitation threshold of rainfall less than 2 mm day-1 was successfully predicted by both versions of the FSU model. However, the convection schemes lacked skill in predicting the correct placement of the area and amount for the high precipitation threshold greater than 40 mm day-1. Further evaluation of the predictive skills showed that the Relaxed Arakawa-Schubert scheme was a consistently better predictor of rainfall due to its low bias and lower root mean square errors (RMSEs) compared to the modified Kuo parameterization scheme. [ABSTRACT FROM AUTHOR]