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hPa Temperature (hpa + temperature)
Selected AbstractsTowards ice-core-based synoptic reconstructions of west antarctic climate with artificial neural networksINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 5 2005David B. Reusch Abstract Ice cores have, in recent decades, produced a wealth of palaeoclimatic insights over widely ranging temporal and spatial scales. Nonetheless, interpretation of ice-core-based climate proxies is still problematic due to a variety of issues unrelated to the quality of the ice-core data. Instead, many of these problems are related to our poor understanding of key transfer functions that link the atmosphere to the ice. This study uses two tools from the field of artificial neural networks (ANNs) to investigate the relationship between the atmosphere and surface records of climate in West Antarctica. The first, self-organizing maps (SOMs), provides an unsupervised classification of variables from the mid-troposphere (700 hPa temperature, geopotential height and specific humidity) into groups of similar synoptic patterns. An SOM-based climatology at annual resolution (to match ice-core data) has been developed for the period 1979,93 based on the European Centre for Medium-Range Weather Forecasts (ECMWF) 15-year reanalysis (ERA-15) dataset. This analysis produced a robust mapping of years to annual-average synoptic conditions as generalized atmospheric patterns or states. Feed-forward ANNs, our second ANN-based tool, were then used to upscale from surface data to the SOM-based classifications, thereby relating the surface sampling of the atmosphere to the large-scale circulation of the mid-troposphere. Two recorders of surface climate were used in this step: automatic weather stations (AWSs) and ice cores. Six AWS sites provided 15 years of near-surface temperature and pressure data. Four ice-core sites provided 40 years of annual accumulation and major ion chemistry. Although the ANN training methodology was properly designed and followed standard principles, limited training data and noise in the ice-core data reduced the effectiveness of the upscaling predictions. Despite these shortcomings, which might be expected to preclude successful analyses, we find that the combined techniques do allow ice-core reconstruction of annual-average synoptic conditions with some skill. We thus consider the ANN-based approach to upscaling to be a useful tool, but one that would benefit from additional training data. Copyright © 2005 Royal Meteorological Society. [source] Horizontal resolution impact on short- and long-range forecast errorTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 649 2010Roberto Buizza Abstract The impact of horizontal resolution increases from spectral truncation T95 to T799 on the error growth of ECMWF forecasts is analysed. Attention is focused on instantaneous, synoptic-scale features represented by the 500 and 1000 hPa geopotential height and the 850 hPa temperature. Error growth is investigated by applying a three-parameter model, and improvements in forecast skill are assessed by computing the time limits when fractions of the forecast-error asymptotic value are reached. Forecasts are assessed both in a realistic framework against T799 analyses, and in a perfect-model framework against T799 forecasts. A strong sensitivity to model resolution of the skill of instantaneous forecasts has been found in the short forecast range (say up to about forecast day 3). But sensitivity has shown to become weaker in the medium range (say around forecast day 7) and undetectable in the long forecast range. Considering the predictability of ECMWF operational, high-resolution T799 forecasts of the 500 hPa geopotential height verified in the realistic framework over the Northern Hemisphere (NH), the long-range time limit ,(95%) is 15.2 days, a value that is one day shorter than the limit computed in the perfect-model framework. Considering the 850 hPa temperature verified in the realistic framework, the time limit ,(95%) is 16.6 days for forecasts verified in the realistic framework over the NH (cold season), 14.1 days over the SH (warm season) and 20.6 days over the Tropics. Although past resolution increases have been providing continuously better forecasts especially in the short forecast range, this investigation suggests that in the future, although further increases in resolution are expected to improve the forecast skill in the short and medium forecast range, simple resolution increases without model improvements would bring only very limited improvements in the long forecast range. Copyright © 2010 Royal Meteorological Society [source] Factors governing the interannual variation and the long-term trend of the 850 hPa temperature over IsraelTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 647 2010H. Saaroni Abstract This study examines the ability of the interannual variability in the occurrence of synoptic types, intensity of large-scale circulations and global temperature to explain that of the 850 hPa temperature in Israel for the summer and the winter. The synoptic factor was represented by 19 types defined by Alpert et al(2004b). For the summer, the deep and the weak Persian Trough explained 35% of the interannual temperature variance. For the winter, the lows to the east and to the north explained 44% of the interannual temperature variance. Two additional factors were incorporated: large-scale circulations, the North Atlantic Oscillation for the summer and the Arctic Oscillation for the winter; and global radiative forcing, represented by the global temperature. Both of them were found to be significant, and the variance explained by all of them is 56% for the summer and 64% for the winter. In the summer the variation is dominated by warm and cool types whereas in the winter the cold systems dominate. The individual contribution of each factor to the long-term temperature trend was estimated. While the global radiative forcing contribution was positive and large in both seasons, the synoptic contribution was positive, four times larger in the summer. The large-scale contribution was negative, three times larger in the winter. The considerable warming in the summer results from a rapid increase in the occurrence of the weak Persian Trough, which is a warm type. The study approach may be useful for predicting future temperature regimes, based on predicted synoptic features in climatic models. Copyright © 2010 Royal Meteorological Society [source] Flow dependence of background errors and their vertical correlations for radiance-data assimilationTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 647 2010Reinhold Hess Abstract This article examines the dependence of background-error statistics on synoptic conditions and flow patterns. Error variances and vertical correlations of background temperatures as used for variational radiance-data assimilation are estimated for two different weather regimes over Europe using the NMC method. The results are validated with real observations, i.e. radiosonde data and microwave satellite radiances and generalised with half a year of global data from the ECMWF forecasting system, where weather conditions are distinguished using model fields of wind speed, mean sea level pressure, and relative vorticity. Strong winds, low pressure, and cyclonic flow generally induce larger background errors of 500 hPa temperature than calm winds, high pressure, and anticyclonic flow, and also broader temperature correlations in the vertical with other tropospheric levels. Copyright © 2010 Royal Meteorological Society [source] A probability and decision-model analysis of PROVOST seasonal multi-model ensemble integrationsTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 567 2000T. N. Palmer Abstract A probabilistic analysis is made of seasonal ensemble integrations from the PROVOST project (PRediction Of climate Variations On Seasonal to interannual Time-scales), with emphasis on the Brier score and related Murphy decomposition, and the relative operating characteristic. To illustrate the significance of these results to potential users, results from the analysis of the relative operating characteristic are input to a simple decision model. The decision-model analysis is used to define a user-specific objective measure of the economic value of seasonal forecasts. The analysis is made for two simple meteorological forecast conditions or ,events', E, based on 850 hPa temperature. The ensemble integrations result from integrating four different models over the period 1979,93. For each model a set of 9-member ensembles is generated by running from consecutive analyses. Results from the Brier skill score analysis taken over all northern hemisphere grid points indicate that, whilst the skill of individual-model ensembles is only marginally higher than a probabilistic forecast of climatological frequencies, the multi-model ensemble is substantially more skilful than climatology. Both reliability and resolution are better for the multi-model ensemble than for the individual-model ensembles. This improvement arises both from the use of different models in the ensemble, and from the enhanced ensemble size obtained by combining individual-model ensembles; the latter reason was found to be the more important. Brier skill scores are higher for years in which there were moderate or strong El Niño Southern Oscillation (ENSO) events. Over Europe, only the multi-model ensembles showed skill over climatology. Similar conclusions are reached from an analysis of the relative operating characteristic. Results from the decision-model analysis show that the economic value of seasonal forecasts is strongly dependent on the cost, C, to the user of taking precautionary action against E, in relation to the potential loss, L, if precautionary action is not taken and E occurs. However, based on the multi-model ensemble data, the economic value can be as much as 50% of the value of a hypothetical perfect deterministic forecast. For the hemisphere as a whole, value is enhanced by restriction to ENSO years. It is shown that there is potential economic value in seasonal forecasts for European users. However, the impact of ENSO on economic value over Europe is mixed; value is enhanced by El Niño only for some potential users with specific C/L. The techniques developed are applicable to complex E for arbitrary regions. Hence these techniques are proposed as the basis of an objective probabilistic and decision-model evaluation of operational seasonal ensemble forecasts. [source] | ||||||||||