A Workshop on Polar Lows

European Polar Low Working Group This workshop summarized the current state of PL research in the Arctic and Antarctic. A couple of related projects are in the planning phase or already funded. The creation of a PL database for the Norwegian Sea in the frame of the Sea Surface Temperature and Altimeter Synergy (STARS) project (http://projects.met.no stars) will provide a valuable resource for future research and, potentially, predictability improvements. The maintenance of this database and the creation of similar databases for other polar areas including satellite and NWP data are highly recommended. There is also a need for free and timely access to satellite data, in particular to SAR data to fill the gap caused by the mission end of Envisat. With the increasing resolution of climate models, mesoscale processes such as polar MCs will have to be considered in international research programs such as the World Climate Research Programme (WCRP) Polar Climate Predictability Initiative and the World Weather Research Programme (WWRP) Polar Predictability Project

Wave Extremes in the North East Atlantic from Ensemble Forecasts

A method for estimating return values from ensembles of forecasts at advanced lead times is presented. Return values of significant wave height in the North-East Atlantic, the Norwegian Sea and the North Sea are computed from archived +240-h forecasts of the ECMWF ensemble prediction system (EPS) from 1999 to 2009. We make three assumptions: First, each forecast is representative of a six-hour interval and collectively the data set is then comparable to a time period of 226 years. Second, the model climate matches the observed distribution, which we confirm by comparing with buoy data. Third, the ensemble members are sufficiently uncorrelated to be considered independent realizations of the model climate. We find anomaly correlations of 0.20, but peak events (>P97) are entirely uncorrelated. By comparing return values from individual members with return values of subsamples of the data set we also find that the estimates follow the same distribution and appear unaffected by correlations in the ensemble. The annual mean and variance over the 11-year archived period exhibit no significant departures from stationarity compared with a recent reforecast, i.e., there is no spurious trend due to model upgrades. EPS yields significantly higher return values than ERA-40 and ERA-Interim and is in good agreement with the high-resolution hindcast NORA10, except in the lee of unresolved islands where EPS overestimates and in enclosed seas where it is biased low. Confidence intervals are half the width of those found for ERA-Interim due to the magnitude of the data set.Comment: 27 pp, 10 figures, J Climate (in press

Calibrating ensemble reliability whilst preserving spatial structure

Ensemble forecasts aim to improve decision-making by predicting a set of possible outcomes. Ideally, these would provide probabilities which are both sharp and reliable. In practice, the models, data assimilation and ensemble perturbation systems are all imperfect, leading to deficiencies in the predicted probabilities. This paper presents an ensemble post-processing scheme which directly targets local reliability, calibrating both climatology and ensemble dispersion in one coherent operation. It makes minimal assumptions about the underlying statistical distributions, aiming to extract as much information as possible from the original dynamic forecasts and support statistically awkward variables such as precipitation. The output is a set of ensemble members preserving the spatial, temporal and inter-variable structure from the raw forecasts, which should be beneficial to downstream applications such as hydrological models. The calibration is tested on three leading 15-d ensemble systems, and their aggregation into a simple multimodel ensemble. Results are presented for 12 h, 1° scale over Europe for a range of surface variables, including precipitation. The scheme is very effective at removing unreliability from the raw forecasts, whilst generally preserving or improving statistical resolution. In most cases, these benefits extend to the rarest events at each location within the 2-yr verification period. The reliability and resolution are generally equivalent or superior to those achieved using a Local Quantile-Quantile Transform, an established calibration method which generalises bias correction. The value of preserving spatial structure is demonstrated by the fact that 3×3 averages derived from grid-scale precipitation calibration perform almost as well as direct calibration at 3×3 scale, and much better than a similar test neglecting the spatial relationships. Some remaining issues are discussed regarding the finite size of the output ensemble, variables such as sea-level pressure which are very reliable to start with, and the best way to handle derived variables such as dewpoint depression

A high-resolution hindcast of wind and waves for The North Sea, The Norwegian Sea and The Barents Sea

A combined high-resolution atmospheric downscaling and wave hindcast based on the ERA-40 reanalysis covering the Norwegian Sea, the North Sea and the Barents Sea is presented. The period covered is from September 1957 to August 2002. The dynamic atmospheric downscaling is performed as a series of short prognostic runs initialized from a blend of ERA-40 and the previous prognostic run to preserve the fine-scale surface features from the high-resolution model while maintaining the large-scale synoptic field from ERA-40. The nested WAM wave model hindcast consists of a coarse 50 km model covering the North Atlantic forced with ERA-40 winds and a nested 10-11 km resolution model forced with downscaled winds. A comparison against in situ and satellite observations of wind and sea state reveals significant improvement in mean values and upper percentiles of wind vectors and the significant wave height over ERA-40. Improvement is also found in the mean wave period. ERA-40 is biased low in wind speed and significant wave height, a bias which is not reproduced by the downscaling. The atmospheric downscaling also reproduces polar lows, which can not be resolved by ERA-40, but the lows are too weak and short-lived as the downscaling is not capable of capturing their full life cycle.Comment: 34 pages, 12 figures, 6 table

MyWave project final report

Proyecto "MyWave: A pan-European concerted and integrated approach to operational wave modelling and forecasting – a complement to GMES MyOcean services" perteneciente al Séptimo Programa Marco (7PM), en el cual participó AEMET, entre otros organismosThe main goal of MyWave is to lay the foundation for a future Marine Core Service that includes ocean waves. The proposal has identified four target areas where concerted research is needed to establish a high quality GMES Marine Core Service for ocean waves: 1. Increase the use of earth observations by improving data processing algorithms and data assimilation systems, 2. Improve the physics in current wave models and provide a framework for coupled model systems (atmosphere/waves/ocean), 3. Establish a new standard for probabilistic wave forecasts based on ensemble methods, 4. Derive standard protocols for validation products.Funded under: FP7-SPAC