Evaluating the potential for statistical decadal predictions of sea surface temperatures with a perfect model approach

We explore the potential for making statistical decadal predictions of sea surface temperatures (SSTs) in a perfect model analysis, with a focus on the Atlantic basin. Various statistical methods (Lagged correlations, Linear Inverse Modelling and Constructed Analogue) are found to have significant skill in predicting the internal variability of Atlantic SSTs for up to a decade ahead in control integrations of two different global climate models (GCMs), namely HadCM3 and HadGEM1. Statistical methods which consider non-local information tend to perform best, but which is the most successful statistical method depends on the region considered, GCM data used and prediction lead time. However, the Constructed Analogue method tends to have the highest skill at longer lead times. Importantly, the regions of greatest prediction skill can be very different to regions identified as potentially predictable from variance explained arguments. This finding suggests that significant local decadal variability is not necessarily a prerequisite for skillful decadal predictions, and that the statistical methods are capturing some of the dynamics of low-frequency SST evolution. In particular, using data from HadGEM1, significant skill at lead times of 6–10 years is found in the tropical North Atlantic, a region with relatively little decadal variability compared to interannual variability. This skill appears to come from reconstructing the SSTs in the far north Atlantic, suggesting that the more northern latitudes are optimal for SST observations to improve predictions. We additionally explore whether adding sub-surface temperature data improves these decadal statistical predictions, and find that, again, it depends on the region, prediction lead time and GCM data used. Overall, we argue that the estimated prediction skill motivates the further development of statistical decadal predictions of SSTs as a benchmark for current and future GCM-based decadal climate predictions.

Evidence that ice forms primarily in supercooled liquid clouds at temperatures > -27C

Using 4 years of radar and lidar observations of layer clouds from the Chilbolton Observatory in the UK, we show that almost all (95%) ice particles formed at temperatures >-20°C appear to originate from supercooled liquid clouds. At colder temperatures, there is a monotonic decline in the fraction of liquid-topped ice clouds: 50% at -27°C, falling to zero at -37°C (where homogeneous freezing of water droplets occurs). This strongly suggests that deposition nucleation plays a relatively minor role in the initiation of ice in mid-level clouds. It also means that the initial growth of the ice particles occurs predominantly within a liquid cloud, a situation which promotes rapid production of precipitation via the Bergeron-Findeison mechanism.

π-dimerization of pleiadiene radical cations at low temperatures revealed by UV–vis spectroelectrochemistry and quantum theory

One-electron oxidation of the non-alternant polycyclic aromatic hydrocarbon pleiadiene and related cyclohepta[ c,d]pyrene and cyclohepta[c,d]fluoranthene in THF produces corresponding radical cations detectable in the temperature range of 293–263 K only on the subsecond time scale of cyclic voltammetry. Although the EPR-active red-coloured pleiadiene radical cation is stable according to the literature in concentrated sulfuric acid, spectroelectrochemical measurements reported in this study provide convincing evidence for its facile conversion into the green-coloured, formally closed shell and, hence, EPRsilent π-bound dimer dication stable in THF at 253 K. The unexpected formation of the thermally unstable dimeric product featuring a characteristic intense low-energy absorption band at 673 nm (1.84 eV; logεmax=4.0) is substantiated by ab initio calculations on the parent pleiadiene molecule and the PF6 − salts of the corresponding radical cation and dimer dication. The latter is stabilized with respect to the radical cation by 14.40 kcal mol−1 (DFT B3LYP) [37.64 kcal mol−1 (CASPT2/DFT B3LYP)]. An excellent match has been obtained between the experimental and TDDFT- calculated UV–vis spectra of the PF6 − salt of the pleiadiene dimer dication, considering solvent (THF) effects.

BbgIV is an important Bifidobacterium β-galactosidase for the synthesis of prebiotic galactooligosaccharides at high temperatures

The individual contribution of four β-galactosidases present in Bifidobacterium bifidum NCIMB 41171 towards galactooligosaccharides (GOS) synthesis was investigated. Although the β-galactosidase activity of the whole cells significantly decreased as a function of temperature (40 to 75 °C), GOS yield was at its maximum at 65 °C. Native-PAGE electrophoresis of the whole cells showed that the contribution of BbgIII and BbgIV towards GOS synthesis increased as the temperature increased. Moreover, BbgIII and BbgIV were found to be more temperature stable and to produce a higher GOS yield than BbgI and BbgII, when used in their free form. The GOS yield using BbgIV was 54.8 % (% of total carbohydrates) and 63.9 % (% lactose converted to GOS) at 65 °C from 43 % w/w lactose. It was shown that BbgIV is the most important β-galactosidase in B. bifidum NCIMB 41171 and can be used for GOS synthesis at elevated temperatures.

The basic ingredients of the North Atlantic Storm Track. Part II: Sea surface temperatures

The impact of North Atlantic SST patterns on the storm track is investigated using a hierarchy of GCM simulations using idealized (aquaplanet) and “semirealistic” boundary conditions in the atmospheric component (HadAM3) of the third climate configuration of the Met Office Unified Model (HadCM3). This framework enables the mechanisms determining the tropospheric response to North Atlantic SST patterns to be examined, both in isolation and in combination with continental-scale landmasses and orography. In isolation, a “Gulf Stream” SST pattern acts to strengthen the downstream storm track while a “North Atlantic Drift” SST pattern weakens it. These changes are consistent with changes in the extratropical SST gradient and near-surface baroclinicity, and each storm-track response is associated with a consistent change in the tropospheric jet structure. Locally enhanced near-surface horizontal wind convergence is found over the warm side of strengthened SST gradients associated with ascending air and increased precipitation, consistent with previous studies. When the combined SST pattern is introduced into the semirealistic framework (including the “North American” continent and the “Rocky Mountains”), the results suggest that the topographically generated southwest–northeast tilt in the North Atlantic storm track is enhanced. In particular, the Gulf Stream shifts the storm track south in the western Atlantic whereas the strong high-latitude SST gradient in the northeastern Atlantic enhances the storm track there.

Statistical decadal predictions for sea surface temperatures: a benchmark for dynamical GCM predictions

Accurate decadal climate predictions could be used to inform adaptation actions to a changing climate. The skill of such predictions from initialised dynamical global climate models (GCMs) may be assessed by comparing with predictions from statistical models which are based solely on historical observations. This paper presents two benchmark statistical models for predicting both the radiatively forced trend and internal variability of annual mean sea surface temperatures (SSTs) on a decadal timescale based on the gridded observation data set HadISST. For both statistical models, the trend related to radiative forcing is modelled using a linear regression of SST time series at each grid box on the time series of equivalent global mean atmospheric CO2 concentration. The residual internal variability is then modelled by (1) a first-order autoregressive model (AR1) and (2) a constructed analogue model (CA). From the verification of 46 retrospective forecasts with start years from 1960 to 2005, the correlation coefficient for anomaly forecasts using trend with AR1 is greater than 0.7 over parts of extra-tropical North Atlantic, the Indian Ocean and western Pacific. This is primarily related to the prediction of the forced trend. More importantly, both CA and AR1 give skillful predictions of the internal variability of SSTs in the subpolar gyre region over the far North Atlantic for lead time of 2 to 5 years, with correlation coefficients greater than 0.5. For the subpolar gyre and parts of the South Atlantic, CA is superior to AR1 for lead time of 6 to 9 years. These statistical forecasts are also compared with ensemble mean retrospective forecasts by DePreSys, an initialised GCM. DePreSys is found to outperform the statistical models over large parts of North Atlantic for lead times of 2 to 5 years and 6 to 9 years, however trend with AR1 is generally superior to DePreSys in the North Atlantic Current region, while trend with CA is superior to DePreSys in parts of South Atlantic for lead time of 6 to 9 years. These findings encourage further development of benchmark statistical decadal prediction models, and methods to combine different predictions.

Determination of Holocene cave temperatures from Kr and Xe concentrations in stalagmite fluid inclusions

From the concentrations of dissolved atmospheric noble gases in water, a so-called “noble gas temperature” (NGT) can be determined that corresponds to the temperature of the water when it was last in contact with the atmosphere. Here we demonstrate that the NGT concept is applicable to water inclusions in cave stalagmites, and yields NGTs that are in good agreement with the ambient air temperatures in the caves. We analysed samples from two Holocene and one undated stalagmite. The three stalagmites originate from three caves located in different climatic regions having modern mean annual air temperatures of 27 °C, 12 °C and 8 °C, respectively. In about half of the samples analysed Kr and Xe concentrations originated entirely from the two well-defined noble gas components air-saturated water and atmospheric air, which allowed NGTs to be determined successfully from Kr and Xe concentrations. One stalagmite seems to be particularly suitable for NGT determination, as almost all of its samples yielded the modern cave temperature. Notably, this stalagmite contains a high proportion of primary water inclusions, which seem to preserve the temperature-dependent signature well in their Kr and Xe concentrations. In future work on stalagmites detailed microscopic inspection of the fluid inclusions prior to noble gas analysis is therefore likely to be crucial in increasing the number of successful NGT determinations.

Describing seasonal variability in the distribution of daily effective temperatures for 1985-2009 compared to 1904-1984 for De Bilt, Holland

This paper proposes a method for describing the distribution of observed temperatures on any day of the year such that the distribution and summary statistics of interest derived from the distribution vary smoothly through the year. The method removes the noise inherent in calculating summary statistics directly from the data thus easing comparisons of distributions and summary statistics between different periods. The method is demonstrated using daily effective temperatures (DET) derived from observations of temperature and wind speed at De Bilt, Holland. Distributions and summary statistics are obtained from 1985 to 2009 and compared to the period 1904–1984. A two-stage process first obtains parameters of a theoretical probability distribution, in this case the generalized extreme value (GEV) distribution, which describes the distribution of DET on any day of the year. Second, linear models describe seasonal variation in the parameters. Model predictions provide parameters of the GEV distribution, and therefore summary statistics, that vary smoothly through the year. There is evidence of an increasing mean temperature, a decrease in the variability in temperatures mainly in the winter and more positive skew, more warm days, in the summer. In the winter, the 2% point, the value below which 2% of observations are expected to fall, has risen by 1.2 °C, in the summer the 98% point has risen by 0.8 °C. Medians have risen by 1.1 and 0.9 °C in winter and summer, respectively. The method can be used to describe distributions of future climate projections and other climate variables. Further extensions to the methodology are suggested.

Impact of anthropogenic heat emissions on London's temperatures

We investigate the role of the anthropogenic heat flux on the urban heat island of London. To do this, the time-varying anthropogenic heat flux is added to an urban surface-energy balance parametrization, the Met Office–Reading Urban Surface Exchange Scheme (MORUSES), implemented in a 1 km resolution version of the UK Met Office Unified Model. The anthropogenic heat flux is derived from energy-demand data for London and is specified on the model's 1 km grid; it includes variations on diurnal and seasonal time-scales. We contrast a spring case with a winter case, to illustrate the effects of the larger anthropogenic heat flux in winter and the different roles played by thermodynamics in the different seasons. The surface-energy balance channels the anthropogenic heat into heating the urban surface, which warms slowly because of the large heat capacity of the urban surface. About one third of this additional warming goes into increasing the outgoing long-wave radiation and only about two thirds goes into increasing the sensible heat flux that warms the atmosphere. The anthropogenic heat flux has a larger effect on screen-level temperatures in the winter case, partly because the anthropogenic flux is larger then and partly because the boundary layer is shallower in winter. For the specific winter case studied here, the anthropogenic heat flux maintains a well-mixed boundary layer through the whole night over London, whereas the surrounding rural boundary layer becomes strongly stably stratified. This finding is likely to have important implications for air quality in winter. On the whole, inclusion of the anthropogenic heat flux improves the comparison between model simulations and measurements of screen-level temperature slightly and indicates that the anthropogenic heat flux is beginning to be an important factor in the London urban heat island.

On increasing global temperatures: 75 years after Callendar

In 1938, Guy Stewart Callendar was the first to demonstrate that the Earth’s land surface was warming. Callendar also suggested that the production of carbon dioxide by the combustion of fossil fuels was responsible for much of this modern change in climate. This short note marks the 75th anniversary of Callendar’s landmark study and demonstrates that his global land temperature estimates agree remarkably well with more recent analyses.

Proteolysis of milk heated at high temperatures by native enzymes analysed by trinitrobenzene sulphonic acid (TNBS) method

Native enzymes play a significant role in proteolysis of milk during storage. This is significant for heat resistant native enzymes. Plasmin is one of the most heat resistant enzymes found in milk. It has been reported to survive several heat treatments, causing spoilage during storage. The aim of this study was to assess susceptibility of high temperature heated milk to proteolysis by native enzymes. The trinitrobenzene sulphonic acid (TNBS) method was used for this purpose. Raw milk was heated at 110, 120, 130,142°C for 2 s and 85°C for 15 s and milk processed at low temperature (85°C /15s) was selected to mimic pasteurisation. TNBS method confirmed that raw milk and milk processed at 85°C /15s were the most proteolysed, whereas treatment of milk at high temperatures (110, 120, 130 and 142°C for 2 s) inactivated the native enzymes. It may thus be concluded that high temperature processing positively affects proteolysis by lowering its susceptibility to spoilage during storage.