Météo-France is preparing the implementation of a revised graphical summary of the synoptic situation. This graphical product has been developed since 1993 as, as far as possible, an extension of the existing framework published by WMO. Graphics remain the best way to convey rapidly a lot of information. However, the existing graphical language for meteorology has seldom changed over the years, while our dynamical understanding has improved. Its current use is in fact poorer than the one allowed by the WMO reference definition. In an attempt to overcome these drawbacks, a richer graphical language is proposed. Its goal is to show and, often, to explain areas of synoptic weather activity in the initial spirit of the Norwegian method, since it has been so successful in shaping modern operational meteorology. However, it takes into account the present understanding of cyclogenesis and large-scale dynamics: the actual and potential baroclinic interactions replace the polar front concept. Dynamical meteorology also provides rather precise guidance for structuring and preparing the summary. The proposed code is described and explained. Examples are shown, with most cases taken from the recent FASTEX (Fronts and Atlantic Storm-Track Experiment) project.

A multiscale study of a cold-air comma cloud that produced an area of heavy rain and locally severe weather has been undertaken by synthesising data from a research microwave Doppler radar and VHF and UHF Doppler wind profilers, along with routinely available radar-network, satellite, in situ and mesoscale-model data. The rain area was generated in the exit region of an upper-level jet characterised by laminated velocity perturbations. Some of the perturbations were attributable to inertia-gravity wave activity. The rain area itself is shown to have been composed of a well-organised set of mesoscale rainbands each being due to a mixture of upright and slantwise convection. The existence of the multiple rainbands may have been related to the multi-layered atmospheric structure upwind. Each of the rainbands had cold-frontal and warm-frontal portions, so as to form a series of mini warm sectors stacked along the axis of the comma cloud at roughly 70 km intervals. The multiple rainbands were accompanied by multiple fingers of overrunning low-θw air from part of a dry intrusion originating from just below a major tropopause fold. The fold contained an intense potential-vorticity maximum which appeared to be the focus of the overall system. The operational mesoscale version of the Met. Office's Unified Model, with its 12 km grid, is shown to have resolved many but not all of the key features of the rainbands. It is suggested that further improvements in very-short-range forecasting of important local detail could be achieved by further increasing its resolution and assimilating more mesoscale observational data.

We describe a method to remotely sense precipitation and classify its intensity over water, coasts and land surfaces. This method is intended to be used in an operational nowcasting environment. It is based on data obtained from the Advanced Microwave Sounding Unit (AMSU) onboard NOAA-15. Each observation is assigned a probability of belonging to four classes: precipitation-free, risk of precipitation, precipitation between 0.5 and 5 mm/h, and precipitation higher than 5 mm/h. Since the method is designed to work over different surface types, it relies mainly on the scattering signal of precipitation-sized ice particles received at high frequencies. For the calibration and validation of the method we use an eight-month dataset of combined weather radar and AMSU data obtained over the Baltic area. We compare results for the AMSU-B channels at 89 GHz and 150 GHz and find that the high frequency channel at 150 GHz allows for a much better discrimination of different types of precipitation than the 89 GHz channel. While precipitation-free areas, as well as heavily precipitating areas (> 5 mm/h), can be identified to high accuracy, the intermediate classes are more ambiguous. This stems from the ambiguity of the passive microwave observations as well as from the non-perfect matching of the different data sources and sub-optimal radar adjustment. In addition to a statistical assessment of the method's accuracy, we present case studies to demonstrate its capabilities to classify different types of precipitation and to work over highly structured, inhomogeneous surfaces.

The qualitative parameters describing present weather are particularly difficult to automate. The weather types which create most of these difficulties are known, but little attention has been given to investigating the reasons for disagreements between the primary reference, the professional observer and an automated instrument. This paper provides a method - multiple logistic regression - to compare the WMO present weather codes detected by a professional observer and an automated system. A new approach is introduced to explain the errors relative to the official weather variables. Many weather periods have been analysed, but here results are presented for a snow period with slight and very slight precipitation. The best predictive variables were the dew point temperature, wind direction, relative humidity and visibility. The catalyst for this study was the need for better quality control and for tools to enable the development and the manufacture of better instruments and systems to detect present weather.

This paper is concerned with meteorological processes that may have an influence on the occurrence of episodes of high pollution involving chimney plumes. It reviews meteorological mechanisms that could lead to or maintain high concentrations at distances beyond the range normally considered in dispersion models (distances greater than 30 km). Fundamental parameters of the atmospheric boundary layer are shown to largely determine short-range and long-range dispersion, but their values are usually not well known in specific cases. A simple estimate is provided of the magnitude of the maximum hourly average concentrations during a long-range fumigation episode from a tall stack.

This study compares the performance of different models used to assess the local wind near-surface conditions at an agricultural site in Scania, southern Sweden. The methods are: (a) the WASP model (Wind Analysis and Application Program), (b) separate linear regressions of the two wind vector components, (c) a regression model based on vector correlation, and (d) linear regression of scalar wind. Each method was tested with three different data sets over nine months: wind measurements from the nearby Sturup airport SYNOP station, 10 m surface wind and surface geostrophic wind produced by the operational Swedish Mesoscale Analysis system (Mesan). The wind climate estimations were compared with observed winds at the field site, with respect to mean wind speed, wind direction, wind speed frequency distribution and the relative frequency of winds above 6 m s−1. All models performed reasonably well with data from Sturup and Mesan surface wind, but gave less reliable results with the Mesan geostrophic data. The estimated frequency of winds above 6 m s−1 was in general lower than the observed frequency. Overall, best results were obtained with WASP in combination with measurements from Sturup.

Despite the potential importance for air pollution, the association between temperature inversions and vertical wind profiles has been paid scant attention. A preliminary statistical assessment is made, using message data from radiosonde soundings at a station in eastern England for the period 1976–1980, from the surface up to 700 mb. In spite of an expectation among many air pollution meteorologists that inversions and local wind maxima (or vertical wind shears) are ‘typically’ associated, no such typical association between inversions and significant wind levels was identified. This conclusion extended to nocturnal surface inversions and low level jets. This does not mean that there are not clear cases of association, but that either (a) the dataset does not discriminate the associations, and/or (b) the associations are not evident on a climatological, or statistical, basis.

In partnership with the Environment Agency, the Met Office has developed a short-period thunderstorm forecasting system based on a conceptual life-cycle model of convective cells. Although originally intended to provide forecasts of intense precipitation, the model provides a mechanism for predicting other forms of severe weather phenomena associated with thunderstorms. This paper investigates the possibility of using GANDOLF to generate a forecast of lightning risk. Model life-cycle stages are compared against observed lightning locations in order to derive a basis for forecasting risk, and this was then tested on data for three different events. The results from this initial investigation seem promising and suggest this type of approach can be effective.

The turbulent kinetic energy (TKE) in the atmospheric surface layer (ASL) gives a measure of the intensity of turbulence that could be altered or brought about by mechanical generation, by thermal generation, through vertical transport into or away, and through dissipation. TKE is mainly responsible for the transportation of pollutants suspended in the air. In this paper, TKE evolution in the ASL is studied for Kharagpur (22.20° N, 87.18° E) during the summer monsoon by making use of data from a 30 m micrometeorological tower set up as part of the Monsoon Trough Boundary Layer Experiment (MONTBLEX). Under steady state and homogeneous conditions the various terms in the TKE equation are studied for active and non-active phases of the monsoon in 1990. Their day-to-day variations and the budgets are studied at the 8 m and 15 m levels. The study reveals strong day-to-day variation and significant vertical variations within the ASL. Despite being a tropical station, the buoyancy term is much less than the contribution by mechanical generation ostensibly due to the monsoon. There are also differences between active and non-active phases of the monsoon. Mechanical generation by wind shear has been found to be the dominating production term, while dissipation dominates the magnitude of all other terms.

The optimum sowing dates for soybean cv. Gaurav were derived for Jabalpur, Raipur and Gwalior in the state of Madhya Pradesh in central India. Dates were derived based on two strategies: (a) probabilities of rainfall and temperature events using ClimProb, a PC based software package, and (b) the CROPGRO Soybean v3.0 crop growth simulation model. In Madhya Pradesh, the optimum sowing dates for multiple cropping, with the first crop as soybean under rainfed conditions, are between weeks 25 and 27, while the optimum sowing dates for rainfed mono-cropping are between weeks 28 and 29.