Extremes of Extra-tropical Storms and Drivers of Variability on Different Time Scales

NASA Astrophysics Data System (ADS)

Leckebusch, G. C.

2015-12-01

Extreme extra-tropical cyclones are highly complex dynamical systems with relevance not only for the meteorological and climatological conditions themselves, but also for impacts on different sectors of society and economy. In this presentation latest research results to severe cyclones and related wind fields from synoptic to multi-decadal and anthropogenic scales will be presented, including recent work to risk assessment of potential damages out of this natural hazard. Nevertheless, the focus is laid on the seasonal timescale and recent results to predictability and predictive skills out of different forecast suites will be discussed. In this context, three seasonal forecast suites, namely ECMWF System 3, ECMWF System 4 and Met Office HadGEM-GA3, are analysed regarding their ability to represent wintertime extra-tropical cyclone and wind storm events for the period 1992 until 2011. Two objective algorithms have been applied to 6 hourly MSLP data and 12 hourly wind speeds in 925hPa to detect cyclone and wind storm events, respectively. Results show that all model suites are able to simulate the climatological mean distribution of cyclones and wind storms. For wind storms, all model suites show positive skill in simulating the inter-annual variability over the sub-tropical Pacific. Results for the Atlantic region are more model dependent, with all models showing negative correlations over the western Atlantic. Over the eastern Atlantic/Western Europe only HadGEM-GA3 and ECMWF-S4 reveal significant positive correlations. However, it is found that results over this region are not robust in time for ECMWF-S4, as correlations drop if using 1982 until 2011 instead of 1992 until 2011. Factors of potential predictability will be discussed.

Diagnostic Comparison of Meteorological Analyses during the 2002 Antarctic Winter

NASA Technical Reports Server (NTRS)

Manney, Gloria L.; Allen, Douglas R.; Kruger, Kirstin; Naujokat, Barbara; Santee, Michelle L.; Sabutis, Joseph L.; Pawson, Steven; Swinbank, Richard; Randall, Cora E.; Simmons, Adrian J.;

Multi-model global assessment of subseasonal prediction skill of atmospheric rivers

NASA Astrophysics Data System (ADS)

Deflorio, M. J.

2017-12-01

Atmospheric rivers (ARs) are global phenomena that are characterized by long, narrow plumes of water vapor transport. They are most often observed in the midlatitudes near climatologically active storm track regions. Because of their frequent association with floods, landslides, and other hydrological impacts on society, there is significant incentive at the intersection of academic research, water management, and policymaking to understand the skill with which state-of-the-art operational weather models can predict ARs weeks-to-months in advance. We use the newly assembled Subseasonal-to-Seasonal (S2S) database, which includes extensive hindcast records of eleven operational weather models, to assess global prediction skill of atmospheric rivers on S2S timescales. We develop a metric to assess AR skill that is suitable for S2S timescales by counting the total number of AR days which occur over each model and observational grid cell during a 2-week time window. This "2-week AR occurrence" metric is suitable for S2S prediction skill assessment because it does not consider discrete hourly or daily AR objects, but rather a smoothed representation of AR occurrence over a longer period of time. Our results indicate that several of the S2S models, especially the ECMWF model, show useful prediction skill in the 2-week forecast window, with significant interannual variation in some regions. We also present results from an experimental forecast of S2S AR prediction skill using the ECMWF and NCEP models.

Stratospheric water vapour in the vicinity of the Arctic polar vortex

NASA Astrophysics Data System (ADS)

Maturilli, M.; Fierli, F.; Yushkov, V.; Lukyanov, A.; Khaykin, S.; Hauchecorne, A.

2006-07-01

The stratospheric water vapour mixing ratio inside, outside, and at the edge of the polar vortex has been accurately measured by the FLASH-B Lyman-Alpha hygrometer during the LAUTLOS campaign in Sodankylä, Finland, in January and February 2004. The retrieved H2O profiles reveal a detailed view on the Arctic lower stratospheric water vapour distribution, and provide a valuable dataset for the validation of model and satellite data. Analysing the measurements with the semi-lagrangian advection model MIMOSA, water vapour profiles typical for the polar vortex' interior and exterior have been identified, and laminae in the observed profiles have been correlated to filamentary structures in the potential vorticity field. Applying the validated MIMOSA transport scheme to specific humidity fields from operational ECMWF analyses, large discrepancies from the observed profiles arise. Although MIMOSA is able to reproduce weak water vapour filaments and improves the shape of the profiles compared to operational ECMWF analyses, both models reveal a dry bias of about 1 ppmv in the lower stratosphere above 400 K, accounting for a relative difference from the measurements in the order of 20%. The large dry bias in the analysis representation of stratospheric water vapour in the Arctic implies the need for future regular measurements of water vapour in the polar stratosphere to allow the validation and improvement of climate models.

Beyond Open Data: the importance of data standards and interoperability - Experiences from ECMWF's Open Data Week

NASA Astrophysics Data System (ADS)

Wagemann, Julia; Siemen, Stephan

2017-04-01

The European Centre for Medium-Range Weather Forecasts (ECMWF) has been providing an increasing amount of data to the public. One of the most widely used datasets include the global climate reanalyses (e.g. ERA-interim) and atmospheric composition data, which are available to the public free of charge. The centre is further operating, on behalf of the European Commission, two Copernicus Services, the Copernicus Atmosphere Monitoring Service (CAMS) and Climate Change Service (C3S), which are making up-to-date environmental information freely available for scientists, policy makers and businesses. However, to fully benefit from open data, large environmental datasets also have to be easily accessible in a standardised, machine-readable format. Traditional data centres, such as ECMWF, currently face challenges in providing interoperable standardised access to increasingly large and complex datasets for scientists and industry. Therefore, ECMWF put open data in the spotlight during a week of events in March 2017 exploring the potential of freely available weather- and climate-related data and to review technological solutions serving these data. Key events included a Workshop on Meteorological Operational Systems (MOS) and a two-day hackathon. The MOS workshop aimed at reviewing technologies and practices to ensure efficient (open) data processing and provision. The hackathon focused on exploring creative uses of open environmental data and to see how open data is beneficial for various industries. The presentation aims to give a review of the outcomes and conclusions of the Open Data Week at ECMWF. A specific focus will be set on the importance of data standards and web services to make open environmental data a success. The presentation overall examines the opportunities and challenges of open environmental data from a data provider's perspective.

Precipitable water and surface humidity over global oceans from special sensor microwave imager and European Center for Medium Range Weather Forecasts

NASA Technical Reports Server (NTRS)

Liu, W. T.; Tang, Wenqing; Wentz, Frank J.

1992-01-01

Global fields of precipitable water W from the special sensor microwave imager were compared with those from the European Center for Medium Range Weather Forecasts (ECMWF) model. They agree over most ocean areas; both data sets capture the two annual cycles examined and the interannual anomalies during an ENSO episode. They show significant differences in the dry air masses over the eastern tropical-subtropical oceans, particularly in the Southern Hemisphere. In these regions, comparisons with radiosonde data indicate that overestimation by the ECMWF model accounts for a large part of the differences. As a check on the W differences, surface-level specific humidity Q derived from W, using a statistical relation, was compared with Q from the ECMWF model. The differences in Q were found to be consistent with the differences in W, indirectly validating the Q-W relation. In both W and Q, SSMI was able to discern clearly the equatorial extension of the tongues of dry air in the eastern tropical ocean, while both ECMWF and climatological fields have reduced spatial gradients and weaker intensity.

Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

NASA Astrophysics Data System (ADS)

Subramanian, Aneesh C.; Palmer, Tim N.

2017-06-01

Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.