Massimo Bonavita

ERA-20C: An Atmospheric Reanalysis of the Twentieth Century

AbstractThe ECMWF twentieth century reanalysis (ERA-20C; 1900–2010) assimilates surface pressure and marine wind observations. The reanalysis is single-member, and the background errors are spatiotemporally varying, derived from an ensemble. The atmospheric general circulation model uses the same configuration as the control member of the ERA-20CM ensemble, forced by observationally based analyses of sea surface temperature, sea ice cover, atmospheric composition changes, and solar forcing. The resulting climate trend estimations resemble ERA-20CM for temperature and the water cycle. The ERA-20C water cycle features stable precipitation minus evaporation global averages and no spurious jumps or trends. The assimilation of observations adds realism on synoptic time scales as compared to ERA-20CM in regions that are sufficiently well observed. Comparing to nighttime ship observations, ERA-20C air temperatures are 1 K colder. Generally, the synoptic quality of the product and the agreement in terms of climat...

Characteristics of Occasional Poor Medium-Range Weather Forecasts for Europe

Medium-range weather prediction has become more skillful over recent decades, but forecast centers still suffer from occasional very poor forecasts, which are often referred to as “dropouts” or “busts.” This study focuses on European Centre for Medium-Range Weather Forecasts (ECMWF) day-6 forecasts for Europe. Although busts are defined by gross scores, bust composites reveal a coherent “Rex type” blocking situation, with a high over northern Europe and a low over the Mediterranean. Initial conditions for these busts also reveal a coherent flow, but this is located over North America and involves a trough over the Rockies, with high convective available potential energy (CAPE) to its east. This flow type occurs in spring and is often associated with a Rossby wave train that has crossed the Pacific. A composite on this initial flow type displays enhanced day-6 random forecast errors and some-what enhanced ensemble forecast spread, indicating reduced inherent predictability. Mesoscale convective systems, as...

EnKF and Hybrid Gain Ensemble Data Assimilation. Part I: EnKF Implementation

AbstractThe desire to do detailed comparisons between variational and more scalable ensemble-based data assimilation systems in a semioperational environment has led to the development of a state-of-the-art EnKF system at ECMWF. A broad description of the ECMWF EnKF is given in this paper, focusing on highlighting differences compared to standard EnKF practice. In particular, a discussion of the novel algorithm used to control imbalances between the mass and wind fields in the EnKF analysis is given. The scalability and computational properties of the EnKF are reviewed and the implementation choices adopted at ECMWF described. The sensitivity of the ECMWF EnKF to ensemble size, horizontal resolution, and representation of model errors is also discussed. A comparison with 4DVar will be found in Part II of this two-part study.

The Role of Satellite Data in the Forecasting of Hurricane Sandy

AbstractThe excellent forecasts made by ECMWF predicting the devastating landfall of Hurricane Sandy attracted a great deal of publicity and praise in the immediate aftermath of the event. The almost unprecedented and sudden “left hook” of the storm toward the coast of New Jersey was attributed to interactions with the large-scale atmospheric flow. This led to speculation that satellite observations may play an important role in the successful forecasting of this event. To investigate the role of satellite data a number of experiments have been performed at ECMWF where different satellite observations are deliberately withheld and forecasts of the hurricane rerun. Without observations from geostationary satellites the correct landfall of the storm is still reasonably well predicted albeit with a slight timing shift compared to the control forecast. On the other hand, without polar-orbiting satellites (which represent 90% of the volume of currently ingested observations) the ECMWF system would have given n...

EnKF and Hybrid Gain Ensemble Data Assimilation. Part II: EnKF and Hybrid Gain Results

AbstractThe desire to do detailed comparisons between variational and more scalable ensemble-based data assimilation systems in a semioperational environment has led to the development of a state-of-the-art EnKF system at ECMWF, which has been described in Part I of this two-part study. In this part the performance of the EnKF system is evaluated compared to a 4DVar of similar resolution. It is found that there is not a major difference between the forecast skill of the two systems. However, similarly to the operational hybrid 4DVar–EDA, a hybrid EnKF–variational system [which we refer to as the hybrid gain ensemble data assimilation (HG-EnDA)] is capable of significantly outperforming both component systems. The HG-EnDA has been implemented with relatively little effort following Penny’s recent study. Results of numerical experimentation comparing the HG-EnDA with the hybrid 4DVar–EDA used operationally at ECMWF are presented, together with diagnostic results, which help characterize the behavior of the ...

Improving the Assimilation of Scatterometer Wind Observations in Global NWP

This study aims at improving the assimilation of scatterometer wind observations in global Numerical Weather Prediction (NWP) model by refining the background quality control and optimizing the observation sampling strategy. To improve the background quality control, different Huber Norm distribution implementations are tested and compared against the current “Gaussian plus flat” distribution. Sensitivity experiments show that the usage of the Huber Norm distribution improves the analysis and forecasts. The benefit is mainly seen in the lower model levels in the tropics and extra-tropical Southern Hemisphere. The optimal wind sampling is investigated by testing several combinations of thinning scheme and observation error standard deviation. The impact is demonstrated with a large sample and illustrated by a case study. The case study shows the impact of different settings on the analysis and forecast of a tropical cyclone. A revised wind sampling setting, where four times more observations and a higher observation error than the current operational one are used, showed slightly positive impact on the European Centre for Medium-Range Weather Forecasts (ECMWF) global NWP analyses and forecasts.