Artificial Neural Networks (ANNs) that were originally proposed to model brain functions mathematically are now being used in many branches of research, including the atmospheric sciences. The main contribution of this paper is the development of ANN to identify the presence of thunderstorms (and their location) based on microwave measurements from all five AMSU-B frequencies and on surface observations over Iran (45–65°E, 25–45°N). From the surface observations, the position of each of the different meteorological events (thunderstorm, heavy rain, rain, light rain, snowfall and clear sky) is located in AMSU-B images. An area around this position with roughly the same brightness (visually) is selected. Then the brightness temperatures (TBs) of a few randomly selected pixels from this area are noted. In all, there were 560 pixel-points, over 20 passes of AMSU-B, in these selected areas. It is found that the thunderstorms are related to image features that are bright in all of the five-frequency images (i.e. have low TB), as expected.

The architecture of the neural network that was finally selected for identifying thunderstorm events (as against other reported events), after a series of trial and error for the best accuracy, was achieved using the four-layered Feed-Forward Artificial Neural Network (FFANN) with five nodes in input, two hidden layers with four nodes each, and one node in the output layer. In the ANN output, the thunderstorms clustered clearly away from other phenomena. ANN gave more correct thunderstorm recognition (96.7%), whereas the discriminant analysis gave 95.3% correct recognition without clear separation between the two classes.

The prediction of severe convection is a major forecasting problem in Australia during the summer months. In particular, severe convection in the Sydney basin frequently produces heavy rain or hail, flash flooding, and destructive winds. Convective activity is a forecasting challenge for the Sydney basin, mainly from October to April. Currently, there is a need for improved numerical model guidance to supplement the official probabilistic convective outlooks, issued by the operational forecasters. In this study we assess the performance of a very high resolution (2 km) numerical weather prediction (NWP) model in terms of how well it performed in providing guidance on heavy rainfall and hail, as well as other mesoscale features such as low level convergence lines. Two cases are described in which the operational forecasts were incorrect on both occasions. Non-severe thunderstorms were predicted on 1 December 2000 but severe convection occurred. Severe convection was predicted on 8 December 2000, but no convection was reported. In contrast, the numerical model performed well, accurately predicting severe convection on 1 December and no convection on 8 December. These results have encouraged a program aimed at providing an enhanced numerical modelling capability to the operational forecasters for the Sydney basin.

The ECMWF Ensemble Prediction System 2-metre temperature forecasts are affected by systematic errors due mainly to resolution inadequacies. Moreover, other errors sources are present: differences in height above sea level between the station and the corresponding grid point, boundary layer parameterisation, and description of the land surface. These errors are more marked in regions of complex orography. A recursive statistical procedure to adapt ECMWF EPS-2metre temperature fields to 58 meteorological stations on the Mediterranean island of Sardinia is presented. The correction has been made in three steps: (1) bias correction of systematic errors; (2) calibration to adapt the EPS temperature distribution to the station temperature distribution; and (3) doubling the ensemble size with the aim of taking into account the analysis errors. Two years of probabilistic forecasts of freezing are tested by Brier Score, reliability diagram, rank histogram and Brier Skill Score with respect to the climatological forecast. The score analysis shows much better performance in comparison with the climatological forecast and direct model output, for all forecast timse, even after the first step (bias correction). Further gains in skill are obtained by calibration and by doubling the ensemble size.

A method has been developed for retrieval of wind velocity profiles from satellite sounder radiances using a neural network technique. Each wind velocity represents a mean value for a layer approximately centred at that standard height or pressure level. The neural network input vector includes sounder radiances from the Geostationary Operational Environmental Satellite (GOES), plus ancillary information such as latitude and longitude. A set of ‘co-incident’ rawinsonde soundings provide the ‘truth’ data set. In the initial results root mean square errors for the standard levels from 850 to 300 hPa have about the same magnitude as those for current methods such as tracking of moisture features in GOES imagery. As with more traditional methods, the largest root mean square error occurs near the tropopause. Although the results to date appear highly promising, considerable further work is needed before we have an operationally capable technique.

An attempt has been made to forecast the all-India monsoon rainfall by using 30 years' pre-monsoon upper-air mean temperatures (recorded between 1959 and 1988) at stations over India. The importance of Nagpur temperatures at 850 and 700 hPa during the pre-monsoon season is discussed. Two sets of regression equations, one with April temperatures and the other with May temperatures, are fitted using the independent predictors. The equations are tested for a two-year period (1989-1990). The forecast values are found to be reasonably good.

Historical climate conditions were examined to determine whether climate information could improve decisions concerning the seasonal maintenance and operations of regional outdoor swimming pools in heavily urbanised northeastern Illinois. Key weather-sensitive issues defined for pool companies concern time periods for maintenance (including pool painting), weather limits to pools being open, and hot days which extend hours of pool operation. The specific conditions included the frequency of spring and fall painting periods (defined as dry conditions for two or more days with Tmax ≥18 °C (65 °F) and Tmin ≥ 4 °C (40 °F)); summer inclement weather days (days with precipitation ≥ 2.54 mm (0.10 inch) with not more than 2 consecutive hours of dry conditions during open swimming hours and/or Tmax ≤ 21 °C (70 °F)); and hot days (Tmax ≥ 32 °C (90 °F)) were examined.

Climatic records for the region going back 42 years revealed that there were nearly twice as many fall painting periods as those in the spring, indicating that greater emphasis should be placed on pool painting after the swimming season. The average number of inclement weather days was more than twice the number the company budgeted for at the beginning of each swimming season. Plans to extend swimming hours on hot days involves a risky decision since the number of hot days varies dramatically from year-to-year in the Chicago region. Studies showed that winter negative sea-surface temperature anomalies in the central Pacific were related to an above average number of spring painting periods. Also, a higher number of hot summer days occur following El Niño-classified winters. Results reveal that decision-makers in the swimming pool management industry can improve several management decisions by including climate information.

A cold-air comma cloud crossed southern Britain early on 18 February 1997 bringing strong gusts and convective precipitation. Development of the comma cloud occurred in association with a positive upper tropospheric potential vorticity (PV) anomaly. A mesoscale analysis of the comma cloud was carried out using special three-hourly soundings from UK radiosonde stations together with data from rainfall radar, satellite, NWP model output and a wind-profiling radar. The analysis reveals that the comma cloud tail was of ana-form whilst the polar cold front (behind which the comma cloud developed) was kata-form. Further analysis indicates that the polar cold ?w front and the comma cloud front were tending to become one entity at the surface and can thus be considered an example of a kata-cold front undergoing a partial transition to more of an ana-form locally in the region of an upper tropospheric positive PV anomaly.

Atmospheric pollution models are generally evaluated using measures of the difference between predicted and observed concentrations. These statistics can be inadequate as they tend to be sensitive to small errors in the timing of peak events that are generally of little consequence from a health point of view. This paper presents a technique for evaluating atmospheric carbon monoxide models based on the statistical properties of the uptake of carbon monoxide, rather than relying on traditional model evaluation measures. A simple semi-empirical atmospheric carbon monoxide model is used as an example to illustrate the approach.

The use of the SSM/I sea ice concentration data together with a sea surface temperature (SST) analysis in a numerical weather prediction (NWP) model is described. The ice concentration data provide a useful representation of the SST freezing-point isotherm while the SST field allows a quality control of the sea ice data. A land-sea mask, an orography field and a climatological SST field are also used to improve the analysis of surface temperature in some inland seas and lakes. A monthly mean sea ice concentration climatology has been created from 13 years of the ECMWF re-analysis ice concentration dataset which was also derived from satellite multi-channel microwave radiometer data. Data assimilation experiments have shown a small positive impact in the southern hemisphere model forecast scores when this new surface field is used in the NWP model.

A brief account is given of the case work undertaken as part of the Summer Study Week on ‘Extra-tropical Cyclones’ held in Reading during July 1996. It is shown that different approximate methods of assessing synoptic-scale vertical velocity can give widely differing results. Computation of the full quasi-geostrophically forced vertical velocity is recommended as a more informative procedure. Forecasts for the track of an explosively deepening north Atlantic cyclone are compared at different lead times. The comparison encompasses raw model forecasts and model forecasts adjusted by groups of case work participants. The groups achieved a large improvement over a model forecast at the 2-3 day lead time, but only marginal improvements thereafter. It is suggested that improved understanding of development mechanisms would enable the forecaster to appreciate better the range of possible outcomes in cyclogenetic situations.

A high pressure system between 20°S and 35°S, moving from east to west, passed over the Andes mountains on 27 and 28 February 1997. Some days earlier, on 20 February, another centre of anticyclonic vorticity had moved westward without crossing the Andes. These events developed during a South American Seesaw System (SASS) event that had been displaced southward from its climatological position.

This southward displacement of the local circulation pattern was accompanied by intense convective activity during the positive phase of the event, which favoured the development of strong storms in north and central Argentina. The unusual configuration of the motion field gave rise to atypically high temperatures in the mid-latitude Argentinian region.

Both anticyclonic systems reached the mountain barrier: one from the north and the other from the south. The analysis of the factors involved in this phenomenon reveals that the static stability in each system behaved differently near the mountain barrier. Advection of potential vorticity was responsible for the westward motion of the system, while the radiative processes influenced the production of cyclonic and anticyclonic potential vorticity which balanced out during each day.

The object of this study is to examine the possibility of developing a model that can determine road surface adjustment times to new conditions after weather changes. Situations where the weather changes from clear to overcast conditions are studied in order to produce a worst-case scenario. One hypothesis tested is that the decrease in road surface temperature (RST) differences between shaded and sun-exposed stations on clear days can be used to determine the reduction in RST difference on days with weather changes. A relationship that describes the variation in RST difference as a function of time of day and season is developed. For clear days a fourth-order polynomial can describe the relationship between RST differences and time of day. The coefficient in the polynomial depends on maximal solar elevation. Validation of the model for clear days showed that the deviation between modelled and measured values varied between 0.3 and 0.5 °C. It was also possible to use the clear day relationship to predict the decrease in RST differences for situations with weather changes, but during these situations the deviations between modelled and measured values were higher and also tended to show a positive bias.

A model to deduce cloudiness from automatic measurements of synoptic and road weather stations during winter nights is introduced. The (height-adjusted) cloud amount of each station can be determined from near-surface temperature measurements and precipitation information only. By using the difference between the air temperature at surface level and the air temperature 2 m above ground, a correlation coefficient is achieved of up to 0.91 between the calculated cloud amount and observations. The model is applied to a dense network in central Switzerland in order to obtain a two-dimensional cloud map by interpolation. With the help of a tracking algorithm, the displacement of cloud patterns is nowcasted. The procedure was tested using data from winter 2003–4. It works successfully with a forecast range up to about 90 minutes. The results are used to predict a change in surface temperature (in cases with changing cloudiness), and thus allow nowcasting of slippery roads or ground frost.

On 11–12 November 1987, a frontal system associated with an intense narrow cold frontal rainband was observed over the Channel between England and France. This case constitutes intensive observational period 2 (IOP2) of the FRONTS 87 experiment. It was an ideal example of upper-level and low-level jet coupling with substantial ascending motions and precipitation. The frontal system is analysed, in this paper, using the mesoscale non-hydrostatic model CSU/RAMS. The model uses a two-way interactive nested grid structure and full cloud microphysics parameterisation at various levels of complexity. The model results are compared with previous numerical investigations of this case as well as with observations obtained from the experimental network deployed during the campaign. The model succeeded in representing the frontal structure at meso- and convective scales, taking into account the large scale forcing; thus it is an important tool for the study of secondary cyclogenesis observed during the FASTEX campaign.

Large urban centres located within confining rugged or complex terrain can frequently experience episodes of high concentrations of lower atmospheric pollution. Metropolitan Phoenix, Arizona (United States), is a good example, as the general population is occasionally subjected to high levels of lower atmospheric ozone, carbon monoxide and suspended particulate matter. As a result of dramatic but continuous increase in population, the accompanying environmental stresses and the local atmospheric circulation that dominates the background flow, an accurate simulation of the mesoscale pollutant transport across Phoenix and similar urban areas is becoming increasingly important. This is particularly the case in an airshed, such as that of Phoenix, where the local atmospheric circulation is complicated by the complex terrain of the area.

Within the study presented here, a three-dimensional time-dependent mesoscale meteorological model (HOTMAC) is employed for simulation of lower-atmospheric flow in Phoenix, for both winter and summer case-study periods in 1998. The specific purpose of the work is to test the model's ability to replicate the atmospheric flow based on the actual observations of the lower-atmospheric wind profile and known physical principles. While a reasonable general agreement is found between the model-produced flow and the observed one, the simulation of near-surface wind direction produces a much less accurate representation of actual conditions, as does the simulation of wind speed over 1,000 metres above the surface. Using the wind and turbulence output from the mesoscale model, likely particle plume trajectories are simulated for the case-study periods using a puff dispersion model (RAPTAD). Overall, the results provide encouragement for the efforts towards accurately simulating the mesoscale transport of lower-atmospheric pollutants in environments of complex terrain.

The solar ultraviolet radiation (UV) flux density at the earth's surface depends on the incoming solar energy and the transmission properties of the atmosphere. UV radiation is strongly absorbed by ozone in the spectral range 200-310 nm, while the attenuation is increasingly weaker at longer wavelengths. Following the discovery of the Antarctic ozone hole in 1985, the risk of a possible UV increase at ground level, due to the observed stratospheric ozone depletion, has heightened the interest within the scientific community given the potentially harmful effects on terrestrial and aquatic ecosystems. Spectroradiometers, broad-band meters and dosimeters may be used for measurements of solar UV. In addition, radiation transfer models can be used to quantify UV irradiances at various times and locations, provided that the extraterrestrial solar radiation and the state of the atmosphere are known. Information about UV radiation at the earth's surface is given by the ultraviolet index ‘UVI’, which is defined as the effective integrated irradiance (280-400 nm) weighted by the erythemal action spectrum. The UV Index is widely used by many international weather services as an indicator of UV levels at the earth's surface providing public awareness of the effects of prolonged exposure to the sun's rays.

The aim of this paper is to present a device capable of estimating the UV Index. This device is a compact disc, used as a sundial, and is based on modelled UV irradiances derived from the STAR radiative transfer model (System for Transfer of Atmospheric Radiation). The device was tested in an urban setting under clear sky conditions.

Experimental model forecasts conditions every 10 kilometres

The National Weather Service (NWS) in the USA has begun testing a new experimental computer model that will assist forecasters to predict weather conditions across the western United States with more detail than ever before. The model, known as the Eta-10, allows forecasters to monitor the development of weather systems down to a 10-km grid.

The interaction between atmospheric and construction conditions and the exothermic, temperature-dependent hydration reactions of the concrete's binding components may produce adverse conditions in curing concrete, thereby reducing the quality of that concrete. Accurate model forecasts of concrete temperatures and moisture would help engineers determine an optimal time to pour, an optimal mix design, and/or optimal curing practices. Existing models of curing concrete bridge decks and road surface prediction models lack realistic boundary conditions. The concrete models contain unnecessarily detailed hydration heat generation mechanisms for a simplified field forecast model. In this paper, a new energy balance model (SLABS), which can be easily adapted to predict road surface conditions, is described and applied to predict the temperatures and moisture of curing concrete bridge decks made with New York State Department of Transportation's Class HP concrete. Highest concrete temperatures occurred at high air temperatures, humidities and initial concrete temperatures and at low cloud cover fractions and wind speeds. Peak concrete temperatures can exceed 60°C. To minimise concrete temperatures and temperature gradient magnitudes, concrete should be placed during the late afternoon or early evening. As a field forecast model for which the meteorological inputs are taken from NGM MOS forecasts, the outputs of SLABS include the peak concrete temperature (to within 2°C of the observed in one application), peak temperature gradient, evaporation rate at the time of placement and several warning messages indicating adverse field conditions.

Data from a VHF wind-profiling radar are being used as a teaching aid in the Department of Meteorology at the University of Reading. An example is given of data obtained during the passage of a train of baroclinic waves which shows how the radar, together with output from weather-forecast models, can vividly illustrate processes occurring over a range of scales.