SUMMARYDynamical aspects of the life cycle of the winter storm 'Lothar' (24-26 December 1999) are investigated with the aid of the European Centre for Medium-Range Weather Forecasts analysis data and mesoscale model simulations. Neither of these datasets capture the full amplitude of the observed extreme pressure fall and surface wind speeds, but they do help identify a range of key dynamical and physical features that characterize the development of this unusual event. The analysis and interpretation is primarily based upon the evolution of the lower-and upper-level potential vorticity (PV) eld complemented by three-dimensional trajectory calculations.'Lothar' originated in the western Atlantic and travelled as a shallow low-level cyclone of moderate intensity towards Europe. This translation took place below and slightly to the south of a very intense upper-level jet and was accompanied by continuous and intense condensational heating that sustained a pronounced positive low-level PV anomaly (not unlike the concept of a 'diabatic Rossby wave'). No signi cant PV anomalies were evident at the tropopause level during this early phase of the life cycle. The surface cyclone intensi ed rapidly when the shallow cyclone approached the jet-stream axis. The circulation induced by the diabatically produced low-tropospheric PV anomaly on steeply sloping isentropic surfaces that transect the intense upper-level jet contributed signi cantly to the rapid formation of a narrow and deep tropopause fold. This stratospheric PV anomaly virtually merged with the diabatically produced ephemeral PV feature to form a vertically aligned tower of positive PV at the time of maximum storm intensity. A sensitivity study with a dry adiabatic hindcast simulation shows no PV-tower con guration (and only a very weak surface development) and con rms the primary importance of the cloud diabatic heating for the tropopause fold formation and the rapid 'bottom-up' intensi cation of 'Lothar'.A comparison of the anomalously high Atlantic sea surface temperatures in December 1999 with the watervapour source regions for the latent-heat release that accompanied the rapid intensi cation phase of 'Lothar' shows a close relationship. This is of importance when discussing the possible implications of climate variability and change on the development of North Atlantic winter storms.

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In semiarid mountainous regions such as central Asia, runoff from snowmelt often represents the dominant contribution to river flow and freshwater supply during the dry season. The estimation of snow accumulation during the preceding seasons then provides a key to seasonal runoff forecasting with lead times of a few months, and it requires appropriate coverage with surface precipitation and/or snow water equivalent observations. This study tests whether the lack of conventional precipitation and snow observations can be overcome by using model-based precipitation estimates from meteorological data assimilation systems. To this end, a detailed examination is undertaken of the ability of model-assimilated precipitation data to represent the interannual (year-to-year) variations of observed runoff in the Aral Sea basin in central Asia. Precipitation from the 15-yr Re-Analysis (ERA-15) of the European Centre for Medium-Range Weather Forecasts (ECMWF) for the period 1979-93 is compared against precipitation estimates derived from rain gauge networks, and against the observed natural runoff in the Syrdarya (166 400 km 2) and Amudarya (320 520 km 2) basins. It is demonstrated that the ERA-15 dataset is able-despite its low spatial resolution-to describe the seasonal cycle and the larger-scale geographical distribution of precipitation in central Asia. For the Syrdarya basin, it is found that December-April ERA-15 precipitation correlates well with observed May-September natural discharge. The correlation coefficient between the two time series amounts to r ϭ 0.92. It is also demonstrated that ERA-15 precipitation is a better predictor for subsequent runoff than rain gauge-based precipitation analyses, presumably because of the poor coverage with rain gauge stations. The high correlations suggest that a reliable seasonal runoff forecasting system can be constructed from the statistical relationship between model-assimilated precipitation and subsequent runoff. Cross-validation hindcasting techniques are used to confirm this conclusion. A real runoff forecasting system would, however, require using a real-time precipitation product from an operational data assimilation system. For the Amudarya basin, the correlation between precipitation and subsequent runoff is substantially lower, presumably because of a lower quality of ERA-15 precipitation estimates within the tropical weather system, and/or due to a lower quality of the withdrawal-corrected runoff figures.

[1] A novel algorithm is described for the assimilation of time-averaged observations. A demonstration of this algorithm in an ideal model using an ensemble Kalman filter technique suggests the potential for resolving dynamical features that have a characteristic time-scale longer than the averaging time of the observations. This technique may offer new perspectives in climate reconstruction and in the assimilation of integrated meteorological quantities such as accumulated precipitation. Citation: Dirren, S., and G. J.Hakim (2005), Toward the assimilation of time-averaged observations, Geophys. Res. Lett., 32, L04804,

[1] An alternative approach is set out for the study of the difference between the forecast and contemporaneous analysis fields of a weather prediction system. Illustrations and interpretations are proffered of this difference when viewed in terms of potential vorticity (PV) for both a case study analysis and a single winter's climatology. The results indicate that the approach provides a compact and insightful description of the difference field's dynamics.