When can we expect extremely high surface temperatures?

In the Essence project a 17-member ensemble simulation of climate change in response to the SRES A1b scenario has been carried out using the ECHAM5/MPI-OM climate model. The relatively large size of the ensemble makes it possible to accurately investigate changes in extreme values of climate variables. Here we focus on the annual-maximum 2m-temperature and fit a Generalized Extreme Value (GEV) distribution to the simulated values and investigate the development of the parameters of this distribution. Over most land areas both the location and the scale parameter increase. Consequently the 100-year return values increase faster than the average temperatures. A comparison of simulated 100-year return values for the present climate with observations (station data and reanalysis) shows that the ECHAM5/MPI-OM model, as well as other models, overestimates extreme temperature values. After correcting for this bias, it still shows values in excess of 50°C in Australia, India, the Middle East, North Africa, the Sahel and equatorial and subtropical South America at the end of the century.

Fatty acid composition of cooked chicken meat and chicken meat products as influenced by price range at retail

The primary objective was to determine fatty acid composition of skinless chicken breast and leg meat portions and chicken burgers and nuggets from the economy price range, standard price range (both conventional intensive rearing) and the organic range from four leading supermarkets. Few significant differences in the SFA, MUFA and PUFA composition of breast and leg meat portions were found among price ranges, and supermarket had no effect. No significant differences in fatty acid concentrations of economy and standard chicken burgers were found, whereas economy chicken nuggets had higher C16:1, C18:1 cis, C18:1 trans and C18:3 n-3 concentrations than had standard ones. Overall, processed chicken products had much higher fat contents and SFA than had whole meat. Long chain n-3 fatty acids had considerably lower concentrations in processed products than in whole meat. Overall there was no evidence that organic chicken breast or leg meat had a more favourable fatty acid composition than had meat from conventionally reared birds.

Climatology and variability in the ECHO coupled GCM

ECHO is a new global coupled ocean-atmosphere general circulation model (GCM), consisting of the Hamburg version of the European Centre atmospheric GCM (ECHAM) and the Hamburg Primitive Equation ocean GCM (HOPE). We performed a 20-year integration with ECHO. Climate drift is significant, but typical annual mean errors in sea surface temperature (SST) do not exceed 2° in the open oceans. Near the boundaries, however, SST errors are considerably larger. The coupled model simulates an irregular ENSO cycle in the tropical Pacific, with spatial patterns similar to those observed. The variability, however, is somewhat weaker relative to observations. ECHO also simulates significant interannual variability in mid-latitudes. Consistent with observations, variability over the North Pacific can be partly attributed to remote forcing from the tropics. In contrast, the interannual variability over the North Atlantic appears to be generated locally.

Balanced Ocean-Data Assimilation near the Equator

The question is addressed whether using unbalanced updates in ocean-data assimilation schemes for seasonal forecasting systems can result in a relatively poor simulation of zonal currents. An assimilation scheme, where temperature observations are used for updating only the density field, is compared to a scheme where updates of density field and zonal velocities are related by geostrophic balance. This is done for an equatorial linear shallow-water model. It is found that equatorial zonal velocities can be detoriated if velocity is not updated in the assimilation procedure. Adding balanced updates to the zonal velocity is shown to be a simple remedy for the shallow-water model. Next, optimal interpolation (OI) schemes with balanced updates of the zonal velocity are implemented in two ocean general circulation models. First tests indicate a beneficial impact on equatorial upper-ocean zonal currents.

Analysis Scheme in the Ensemble Kalman Filter

This paper discusses an important issue related to the implementation and interpretation of the analysis scheme in the ensemble Kalman filter . I t i s shown that the obser vations must be treated as random variables at the analysis steps. That is, one should add random perturbations with the correct statistics to the obser vations and generate an ensemble of obser vations that then is used in updating the ensemble of model states. T raditionally , this has not been done in previous applications of the ensemble Kalman filter and, as will be shown, this has resulted in an updated ensemble with a variance that is too low . This simple modification of the analysis scheme results in a completely consistent approach if the covariance of the ensemble of model states is interpreted as the prediction error covariance, and there are no further requirements on the ensemble Kalman filter method, except for the use of an ensemble of sufficient size. Thus, there is a unique correspondence between the error statistics from the ensemble Kalman filter and the standard Kalman filter approach