ALBERT

Description: CO 2 is the strongest anthropogenic forcing agent for climate change since pre-industrial times. Like other greenhouse gases, CO 2 absorbs terrestrial surface radiation and causes emission from the atmosphere to space. As the surface is generally warmer than the atmosphere, the total long-wave emission to space is commonly less than the surface emission. However, this does not hold true for the high elevated areas of central Antarctica. For this region, the emission to space is higher than the surface emission; and the greenhouse effect of CO 2 is around zero or even negative, which has not been discussed so far. We investigated this in detail and show that for central Antarctica an increase in CO 2 concentration leads to an increased long-wave energy loss to space, which cools the Earth-atmosphere system. These findings for central Antarctica are in contrast to the general warming effect of increasing CO 2 .

Description: Viele Menschen trinken gerne und regelmäßig viel Kaffee und schätzen den koffeinhaltigen Wachmacher. Lebensmittelchemiker von der Technischen Universität Kaiserslautern haben jetzt herausgefunden, dass regelmäßiger Kaffeekonsum das Erbmolekül DNA offenbar vor Schäden schützt, die sonst durch Umwelteinflüsse, wie etwa UV-Licht, entstehen können. Kaffee verhindert die sogenannten DNA-Strangbrüche, die zum Zelltod oder zu Mutationen führen können.

Description: The role of atmospheric uncertainty for the assimilation and prediction of Arctic sea ice is explored by running the Massachusetts Institute of Technology general circulation model (MITgcm) in data assimilation and prediction mode for the summer 2010. The atmospheric ensemble forcing is taken from the UK Met Office (UKMO) system available through the TIGGE (THORPEX Interactive Grand Global Ensemble) database. The DA system is based on a local Singular Evolutive Interpolated Kalman (LSEIK) filter and Special Sensor Microwave Imager/Sounder (SSMIS) sea ice concentration operational products from the National Snow and Ice Data Center (NSIDC) are assimilated. Two kinds of experiments are carried out differing in the LSEIK configuration and forcing used: The first one uses a single deterministic control forcing and a forgetting factor necessary to inflate the ensemble spread in the DA phase; the second one uses 23 members from the UKMO atmospheric ensemble prediction system, thereby avoiding any additional ensemble inflation and making further tuning unnecessary. With both systems the model data misfit improves as expected, but the ensemble approach outperforms the deterministic filter. The ice concentration of 24 h forecasts is consistently closer to observations with the ensemble approach, because a larger and more realistic ensemble spread, representing model uncertainty, leads to a better adjustment. 15-day forecasts are also better with ensemble forcing than with deterministic forcing, both because of the larger spread and the better initial state in the ensemble forced system. The ensemble forcing can also improve poor initial states obtained with the deterministic control forcing, because the ensemble forcing introduces a larger spread that spans a larger range of model simulations. Ice thickness forecasts cannot be significantly improved with the ensemble forcing.

Description: The technique of relaxation of the tropical atmosphere towards an analysis in a month-season forecast model has previously been successfully exploited in a number of contexts. Here it is shown that when tropical relaxation is used to investigate the possible origin of the observed anomalies in June–July 2007, a simple dynamical model is able to reproduce the observed component of the pattern of anomalies given by an ensemble of ECMWF forecast runs. Following this result, the simple model is used for a range of experiments on time-scales of relaxation, variables and regions relaxed based on a control model run with equatorial heating in a zonal flow. A theory based on scale analysis for the large-scale tropics is used to interpret the results. Typical relationships between scales are determined from the basic equations, and for a specified diabatic heating a chain of deductions for determining the dependent variables is derived. Different critical time-scales are found for tropical relaxation of different dependent variables to be effective. Vorticity has the longest critical time-scale, typically 1.2 days. For temperature and divergence, the time-scales are 10 hours and 3 hours, respectively. However not all the tropical fields, in particular the vertical motion, are reproduced correctly by the model unless divergence is heavily damped. To obtain the correct extra-tropical fields, it is crucial to have the correct rotational flow in the subtropics to initiate the Rossby wave propagation from there. It is sufficient to relax vorticity or temperature on a time-scale comparable or less than their critical time-scales to obtain this. However if the divergent advection of vorticity is important in the Rossby Wave Source then strong relaxation of divergence is required to accurately represent the tropical forcing of Rossby waves. Copyright © 2012 Royal Meteorological Society

Description: The European summer 2003 is a prominent example for an extreme hot and dry season. The main mechanisms that contributed to the growth of the heat wave are still disputed and state-of-the-art climate models have difficulty to realistically simulate the extreme conditions. Here we analyse simulations using recent versions of the European Centre for Medium-Range Weather Forecasts seasonal ensemble forecasting system and present, for the first time, retrospective forecasts which simulate accurately not only the abnormal warmth but also the observed precipitation and mid-tropospheric circulation patterns. It is found that while the land surface hydrology plays a crucial role, the successful simulations also required revised formulations of the radiative and convective parameterizations. We conclude that the predictability of the event was less due to remote teleconnections effects and more due to in situ processes which helped maintain the dry surface anomalies occurring at the beginning of the summer.

Description: The aim of this study was to investigate the occurrence, diversity, and distribution of Phytophthora species in Protected Natural Areas (PNAs), including forest stands, rivers, and riparian ecosystems, in Sicily (Italy), and assessing correlations with natural vegetation and host plants. Fifteen forest stands and 14 rivers in 10 Sicilian PNAs were studied. Phytophthora isolations from soil and stream water were performed using leaf baitings. Isolates were identified using both morphological characters and sequence analysis of the internal transcribed spacer (ITS) region. A rich community of 20 Phytophthora species from eight phylogenetic clades, including three new Phytophthora taxa, was recovered (17 species in rhizosphere soil from forest stands and 12 species in rivers). New knowledge about the distribution, host associations, and ecology of several Phytophthora species was provided.

Description: Two methods that can be used to diagnose possible remote origins for forecast error are compared. The idea is artificially to suppress the development of forecast error in certain parts of the globe (e.g. the Tropics) during the course of the integration and to analyze the influence that this has on forecast skill in remote regions (e.g. the extratropics). The first, computationally relatively cheap, method involves relaxing the European Centre for Medium-Range Weather Forecasts (ECMWF) model towards analysis data during the forecast. The second, computationally much more expensive, method involves running the ECMWF 4D-Var data-assimilation system with assimilation of observations in certain regions only. The two methods are compared by studying the impact that forecast-error reduction in the Tropics and the East Asian–Western North Pacific (EAWNP) region has on medium-range forecast skill in remote regions. For both regions the two techniques yield similar results. Reduction of tropical forecast error leads to the improvement of medium-range forecast skill in the Northern Hemisphere extratropics, especially over the North Pacific and the North Atlantic. Forecast-error reduction in the EAWNP region is beneficial further downstream up to North America; the EAWNP region has little impact on medium-range forecast skill over the North Atlantic and Europe. Copyright © 2011 Royal Meteorological Society

Description: The technique of relaxation of the tropical atmosphere towards an analysis in a month-season forecast model has previously been successfully exploited in a number of contexts. Here it is shown that when tropical relaxation is used to investigate the possible origin of the observed anomalies in June–July 2007, a simple dynamical model is able to reproduce the observed component of the pattern of anomalies given by an ensemble of ECMWF forecast runs. Following this result, the simple model is used for a range of experiments on time-scales of relaxation, variables and regions relaxed based on a control model run with equatorial heating in a zonal flow. A theory based on scale analysis for the large-scale tropics is used to interpret the results. Typical relationships between scales are determined from the basic equations, and for a specified diabatic heating a chain of deductions for determining the dependent variables is derived. Different critical time-scales are found for tropical relaxation of different dependent variables to be effective. Vorticity has the longest critical time-scale, typically 1.2 days. For temperature and divergence, the time-scales are 10 hours and 3 hours, respectively. However not all the tropical fields, in particular the vertical motion, are reproduced correctly by the model unless divergence is heavily damped. To obtain the correct extra-tropical fields, it is crucial to have the correct rotational flow in the subtropics to initiate the Rossby wave propagation from there. It is sufficient to relax vorticity or temperature on a time-scale comparable or less than their critical time-scales to obtain this. However if the divergent advection of vorticity is important in the Rossby Wave Source then strong relaxation of divergence is required to accurately represent the tropical forcing of Rossby waves. Copyright © 2012 Royal Meteorological Society

Description: Ensemble experiments with a climate model are carried out in order to explore how incorporating a stochastic ice strength parameterization to account for model uncertainty affects estimates of potential sea ice predictability on time scales from days toseasons. The impact of this new parameterization depends strongly on the spatial scale, lead time and the hemisphere being considered: Whereas the representation of model uncertainty increases the ensemble spread of Arctic sea ice thickness predictionsgenerated by atmospheric initial perturbations up to about 4 weeks into the forecast, rather small changes are found for longer lead times as well as integrated quantities such as total sea ice area. The regions where initial condition uncertainty generates spread in sea ice thickness on sub-seasonal time scales (primarily along the ice edge) differ from that of the stochastic sea ice strength parameterization (along the coast lines and in the interior of the Arctic). For the Antarctic the influence of the stochastic sea ice strength parameterization is much weaker due to the predominance of thinner first year ice. These results suggest that sea ice data assimilation and prediction on sub-seasonal time scales could benefit from taking model uncertainty into account, especially in the Arctic.

Description: High-latitude climate change is expected to increase the demand for reliable weather and environmental forecasts in polar regions. In this study, a quantitative assessment of the skill of state-of-the-art global weather prediction systems in polar regions is given using data from the THORPEX Interactive Grand Global Ensemble (TIGGE) for the period 2006/07–2012/13. Forecast skill in the Arctic is comparable to that found in the Northern Hemisphere mid-latitudes. However, relative differences in the quality between different forecasting systems appear to be amplified in the Arctic. Furthermore, analysis uncertainty in the Arctic is more of an issue than it is in the mid-latitudes, especially when it comes to near-surface parameters over snow and ice covered surfaces. Using NOAA’s reforecast data set it is shown that the changes in forecast skill during the 7-year period considered here can largely be explained by flow-dependent error growth, especially for the more skilful forecasting systems. Finally, a direct comparison between the Arctic and Antarctic suggests that predictions of mid-topospheric flow in the former region are more skilful.