Direct Model Output Research Articles

Groundwater recharge in Northrhine-Westfalia predicted by a statistical model for greenhouse gas scenarios

A statistical model that generates regional climate scenarios on the basis of observed time series is applied for precipitation calculations for Northrhine-Westfalia (NRW, Germany). The method consists of three steps and can be used for any climate station. In the first step, 30–50 years observed daily values of Tmax, Tmin, Tmean, spread between Tmin and Tmax and the duration of daylight are clustered by a non hierarchical cluster analysis. The resulting clusters are considered to be typical weather situations with respect to these five “relevant parameters”. Secondly, artificial time series for a future climate state are generated. The time series are designed to reproduce the observed statistical characteristics for the “relevant parameters”. Additionally, a transient increase of the mean temperature of 1.5 K / 50 years is prescribed, which is chosen as an estimate for temperature change by doubling the CO2. In step three every element of the generated time series can be assigned to one of the clusters estimated in step one. Thus it is possible to associate an observed day to each artificially generated situation. Other parameters like precipitation can then be taken from the observed day. In this way scenario temperature and precipitation values are produced for each of the 48 stations. Annual groundwater recharge is calculated from these values employing the Turc formula. Finally, a kriging interpolation estimates the distribution of groundwater recharge for the complete area. With the prescribed rise in mean temperature the statistical model simulates decreasing precipitation. Both effects contribute to a reduction of groundwater recharge. While in the mountainous parts of NRW the groundwater recharge change is small, in the planes a reduction of up to 30% of the current groundwater recharge is predicted. A comparison to direct model output from GCM integrations for a standard greenhouse gas scenario produces a similar reduction for that region.

An operational medium range local weather forecasting system developed in India

A forecasting system for objective medium range location specific forecasts of surface weather elements was evolved at the National Centre for Medium Range Weather Forecasting (NCMRWF). The basic information used for this is the output from a general circulation model (GCM). The two essential components of the system are statistical interpretation (SI) forecast and direct model output (DMO) forecast. These are explained in brief. The SI forecast is obtained by using dynamical-statistical methods like model output statistics (MOS) and the perfect prog method (PPM) in which prediction of upper air circulation from a GCM around the location of interest is used. The DMO forecast is obtained from the prediction of surface weather elements from the GCM. The procedure for preparation of final forecast by using these two components and prevailing synoptic conditions is also explained. This is essentially a man-machine-mix approach. Finally, an evaluation of the forecast skill for the 1996 monsoon and some of the future plans are presented. Copyright

An operational medium range local weather forecasting system developed in India

A forecasting system for objective medium range location specific forecasts of surface weather elements was evolved at the National Centre for Medium Range Weather Forecasting (NCMRWF). The basic information used for this is the output from a general circulation model (GCM). The two essential components of the system are statistical interpretation (SI) forecast and direct model output (DMO) forecast. These are explained in brief. The SI forecast is obtained by using dynamical-statistical methods like model output statistics (MOS) and the perfect prog method (PPM) in which prediction of upper air circulation from a GCM around the location of interest is used. The DMO forecast is obtained from the prediction of surface weather elements from the GCM. The procedure for preparation of final forecast by using these two components and prevailing synoptic conditions is also explained. This is essentially a man–machine-mix approach. Finally, an evaluation of the forecast skill for the 1996 monsoon and some of the future plans are presented. Copyright © 2000 Royal Meteorological Society

On the ‘state of the art’ in local weather forecasting

AbstractBased partly on more than 20 years of evaluating local weather forecasts in Germany, a comprehensive analysis of the verification results of synoptic, statistical and short‐ and medium‐range forecasts was carried out in order to obtain some insight into the present ‘state of the art’ in local weather forecasting. This ‘state’ is characterised by (a) striking improvements in skill, especially for the three‐to‐six‐day period; (b) an absence of significant progress in very‐short‐range forecasting, especially for aviation purposes and rare events; (c) an important role for statistical interpretation of medium‐range forecasting products; (d) an increasing importance of direct model output for some short‐range predictands; and, finally, (e) the urgent necessity to combine all the relevant forecast information m an optimum manner in real time.