Effect of food models and low-temperature storage on the adhesion of Lactobacillus rhamnosus GG to Caco-2 cells

This study evaluated the effects of fat and sugar levels on the surface properties of Lactobacillus rhamnosus GG during storage in food model systems, simulating yogurt and ice cream, and related them with the ability of the bacterial cells to adhere to Caco-2 cells. Freeze-dried L. rhamnosus GG cells were added to the model food systems and stored for 7 days. The bacterial cells were analyzed for cell viability, hydrophobicity, ζ potential, and their ability to adhere to Caco-2 cells. The results indicated that the food type and its composition affected the surface and adhesion properties of the bacterial cells during storage, with yogurt being a better delivery vehicle than ice cream in terms of bacterial adhesion to Caco-2 cells. The most important factor influencing bacterial adhesion was the storage time rather than the levels of fats and sugars, indicating that conformational changes were taking place on the surface of the bacterial cells during storage.

Co-variation of temperature and precipitation in CMIP5 models and satellite observations

Current variability of precipitation (P) and its response to surface temperature (T) are analysed using coupled(CMIP5) and atmosphere-only (AMIP5) climate model simulations and compared with observational estimates. There is striking agreement between Global Precipitation Climatology Project (GPCP) observed and AMIP5 simulated P anomalies over land both globally and in the tropics suggesting that prescribed sea surface temperature and realistic radiative forcings are sufficient for simulating the interannual variability in continental P. Differences between the observed and simulated P variability over the ocean, originate primarily from the wet tropical regions, in particular the western Pacific, but are reduced slightly after 1995. All datasets show positive responses of P to T globally of around 2 %/K for simulations and 3-4 %/K in GPCP observations but model responses over the tropical oceans are around 3 times smaller than GPCP over the period 1988-2005. The observed anticorrelation between land and ocean P, linked with El Niño Southern Oscillation, is captured by the simulations. All data sets over the tropical ocean show a tendency for wet regions to become wetter and dry regions drier with warming. Over the wet region (75% precipitation percentile), the precipitation response is ~13-15%/K for GPCP and ~5%/K for models while trends in P are 2.4%/decade for GPCP, 0.6% /decade for CMIP5 and 0.9%/decade for AMIP5 suggesting that models are underestimating the precipitation responses or a deficiency exists in the satellite datasets.

Systematic winter sea-surface temperature biases in the northern Arabian Sea in HiGEM and the CMIP3 models

Analysis of 20th century simulations of the High resolution Global Environment Model (HiGEM) and the Third Coupled Model Intercomparison Project (CMIP3) models shows that most have a cold sea-surface temperature (SST) bias in the northern Arabian Sea during boreal winter. The association between Arabian Sea SST and the South Asian monsoon has been widely studied in observations and models, with winter cold biases known to be detrimental to rainfall simulation during the subsequent monsoon in coupled general circulation models (GCMs). However, the causes of these SST biases are not well understood. Indeed this is one of the first papers to address causes of the cold biases. The models show anomalously strong north-easterly winter monsoon winds and cold air temperatures in north-west India, Pakistan and beyond. This leads to the anomalous advection of cold, dry air over the Arabian Sea. The cold land region is also associated with an anomalously strong meridional surface temperature gradient during winter, contributing to the enhanced low-level convergence and excessive precipitation over the western equatorial Indian Ocean seen in many models.

Northern winter stratospheric temperature and ozone responses to ENSO inferred from an ensemble of Chemistry Climate Models

The connection between the El Ni˜no Southern Oscillation (ENSO) and the Northern polar stratosphere has been established from observations and atmospheric modeling. Here a systematic inter-comparison of the sensitivity of the modeled stratosphere to ENSO in Chemistry Climate Models (CCMs) is reported. This work uses results from a number of the CCMs included in the 2006 ozone assessment. In the lower stratosphere, the mean of all model simulations reports a warming of the polar vortex during strong ENSO events in February–March, consistent with but smaller than the estimate from satellite observations and ERA40 reanalysis. The anomalous warming is associated with an anomalous dynamical increase of column ozone north of 70� N that is accompanied by coherent column ozone decrease in the Tropics, in agreement with that deduced from the NIWA column ozone database, implying an increased residual circulation in the mean of all model simulations during ENSO. The spread in the model responses is partly due to the large internal stratospheric variability and it is shown that it crucially depends on the representation of the tropospheric ENSO teleconnection in the models.

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

Equator-to-pole temperature differences and the extra-tropical storm track responses of the CMIP5 climate models

This paper aims to understand the physical processes causing the large spread in the storm track projections of the CMIP5 climate models. In particular, the relationship between the climate change responses of the storm tracks, as measured by the 2–6 day mean sea level pressure variance, and the equator-to-pole temperature differences at upper- and lower-tropospheric levels is investigated. In the southern hemisphere the responses of the upper- and lower-tropospheric temperature differences are correlated across the models and as a result they share similar associations with the storm track responses. There are large regions in which the storm track responses are correlated with the temperature difference responses, and a simple linear regression model based on the temperature differences at either level captures the spatial pattern of the mean storm track response as well explaining between 30 and 60 % of the inter-model variance of the storm track responses. In the northern hemisphere the responses of the two temperature differences are not significantly correlated and their associations with the storm track responses are more complicated. In summer, the responses of the lower-tropospheric temperature differences dominate the inter-model spread of the storm track responses. In winter, the responses of the upper- and lower-temperature differences both play a role. The results suggest that there is potential to reduce the spread in storm track responses by constraining the relative magnitudes of the warming in the tropical and polar regions.

The dependence of radiative forcing and feedback on evolving patterns of surface temperature change in climate models

Experiments with CO2 instantaneously quadrupled and then held constant are used to show that the relationship between the global-mean net heat input to the climate system and the global-mean surface-air-temperature change is nonlinear in Coupled Model Intercomparison Project phase 5 (CMIP5) Atmosphere-Ocean General Circulation Models (AOGCMs). The nonlinearity is shown to arise from a change in strength of climate feedbacks driven by an evolving pattern of surface warming. In 23 out of the 27 AOGCMs examined the climate feedback parameter becomes significantly (95% confidence) less negative – i.e. the effective climate sensitivity increases – as time passes. Cloud feedback parameters show the largest changes. In the AOGCM-mean approximately 60% of the change in feedback parameter comes from the topics (30N-30S). An important region involved is the tropical Pacific where the surface warming intensifies in the east after a few decades. The dependence of climate feedbacks on an evolving pattern of surface warming is confirmed using the HadGEM2 and HadCM3 atmosphere GCMs (AGCMs). With monthly evolving sea-surface-temperatures and sea-ice prescribed from its AOGCM counterpart each AGCM reproduces the time-varying feedbacks, but when a fixed pattern of warming is prescribed the radiative response is linear with global temperature change or nearly so. We also demonstrate that the regression and fixed-SST methods for evaluating effective radiative forcing are in principle different, because rapid SST adjustment when CO2 is changed can produce a pattern of surface temperature change with zero global mean but non-zero change in net radiation at the top of the atmosphere (~ -0.5 Wm-2 in HadCM3).

Arctic amplification dominated by temperature feedbacks in contemporary climate models

Climate change is amplified in the Arctic region. Arctic amplification has been found in past warm1 and glacial2 periods, as well as in historical observations3, 4 and climate model experiments5, 6. Feedback effects associated with temperature, water vapour and clouds have been suggested to contribute to amplified warming in the Arctic, but the surface albedo feedback—the increase in surface absorption of solar radiation when snow and ice retreat—is often cited as the main contributor7, 8, 9, 10. However, Arctic amplification is also found in models without changes in snow and ice cover11, 12. Here we analyse climate model simulations from the Coupled Model Intercomparison Project Phase 5 archive to quantify the contributions of the various feedbacks. We find that in the simulations, the largest contribution to Arctic amplification comes from a temperature feedbacks: as the surface warms, more energy is radiated back to space in low latitudes, compared with the Arctic. This effect can be attributed to both the different vertical structure of the warming in high and low latitudes, and a smaller increase in emitted blackbody radiation per unit warming at colder temperatures. We find that the surface albedo feedback is the second main contributor to Arctic amplification and that other contributions are substantially smaller or even opposeArctic amplification.

Models agree on forced response pattern of precipitation and temperature extremes

Model projections of heavy precipitation and temperature extremes include large uncertainties. We demonstrate that the disagreement between individual simulations primarily arises from internal variability, whereas models agree remarkably well on the forced signal, the change in the absence of internal variability. Agreement is high on the spatial pattern of the forced heavy precipitation response showing an intensification over most land regions, in particular Eurasia and North America. The forced response of heavy precipitation is even more robust than that of annual mean precipitation. Likewise, models agree on the forced response pattern of hot extremes showing the greatest intensification over midlatitudinal land regions. Thus, confidence in the forced changes of temperature and precipitation extremes in response to a certain warming is high. Although in reality internal variability will be superimposed on that pattern, it is the forced response that determines the changes in temperature and precipitation extremes in a risk perspective.

Fast and slow responses of Southern Ocean sea surface temperature to SAM in coupled climate models

We investigate how sea surface temperatures (SSTs) around Antarctica respond to the Southern An- nular Mode (SAM) on multiple timescales. To that end we examine the relationship between SAM and SST within unperturbed preindustrial control simulations of coupled general circulation models (GCMs) included in the Climate Modeling Intercomparison Project phase 5 (CMIP5). We develop a technique to extract the re- sponse of the Southern Ocean SST (55◦S−70◦S) to a hypothetical step increase in the SAM index. We demonstrate that in many GCMs, the expected SST step re- sponse function is nonmonotonic in time. Following a shift to a positive SAM anomaly, an initial cooling regime can transition into surface warming around Antarctica. However, there are large differences across the CMIP5 ensemble. In some models the step response function never changes sign and cooling persists, while in other GCMs the SST anomaly crosses over from negative to positive values only three years after a step increase in the SAM. This intermodel diversity can be related to differences in the models’ climatological thermal ocean stratification in the region of seasonal sea ice around Antarctica. Exploiting this relationship, we use obser- vational data for the time-mean meridional and vertical temperature gradients to constrain the real Southern Ocean response to SAM on fast and slow timescales.

Mean surface temperature prediction models for broiler chickens-a study of sensible heat flow

Body surface temperature can be used to evaluate thermal equilibrium in animals. The bodies of broiler chickens, like those of all birds, are partially covered by feathers. Thus, the heat flow at the boundary layer between broilers' bodies and the environment differs between feathered and featherless areas. The aim of this investigation was to use linear regression models incorporating environmental parameters and age to predict the surface temperatures of the feathered and featherless areas of broiler chickens. The trial was conducted in a climate chamber, and 576 broilers were distributed in two groups. In the first trial, 288 broilers were monitored after exposure to comfortable or stressful conditions during a 6-week rearing period. Another 288 broilers were measured under the same conditions to test the predictive power of the models. Sensible heat flow was calculated, and for the regions covered by feathers, sensible heat flow was predicted based on the estimated surface temperatures. The surface temperatures of the feathered and featherless areas can be predicted based on air, black globe or operative temperatures. According to the sensible heat flow model, the broilers' ability to maintain thermal equilibrium by convection and radiation decreased during the rearing period. Sensible heat flow estimated based on estimated surface temperatures can be used to predict animal responses to comfortable and stressful conditions. © 2013 ISB.

How stable are 20th century calibration models? A high-resolution summer temperature reconstruction for the eastern Swiss Alps back to A.D. 1580 derived from proglacial varved sediments

We found a significant positive correlation between local summer air temperature (May-September) and the annual sediment mass accumulation rate (MAR) in Lake Silvaplana (46°N, 9°E, 1800 m a.s.l.) during the twentieth century (r = 0.69, p < 0.001 for decadal smoothed series). Sediment trap data (2001-2005) confirm this relation with exceptionally high particle yields during the hottest summer of the last 140 years in 2003. On this base we developed a decadal-scale summer temperature reconstruction back to AD 1580. Surprisingly, the comparison of our reconstruction with two other independent regional summer temperature reconstructions (based on tree-rings and documentary data) revealed a significant negative correlation for the pre-1900 data (ie, late ‘Little Ice Age’). This demonstrates that the correlation between MAR and summer temperature is not stable in time and the actualistic principle does not apply in this case. We suggest that different climatic regimes (modern/‘Little Ice Age’) lead to changing state conditions in the catchment and thus to considerably different sediment transport mechanisms. Therefore, we calibrated our MAR data with gridded early instrumental temperature series from AD 1760-1880 (r = -0.48, p < 0.01 for decadal smoothed series) to properly reconstruct the late LIA climatic conditions. We found exceptionally low temperatures between AD 1580 and 1610 (0.75°C below twentieth-century mean) and during the late Maunder Minimum from AD 1680 to 1710 (0.5°C below twentieth-century mean). In general, summer temperatures did not experience major negative departures from the twentieth-century mean during the late ‘Little Ice Age’. This compares well with the two existing independent regional reconstructions suggesting that the LIA in the Alps was mainly a phenomenon of the cold season.

Comparison of co-located independent ground-based middle atmospheric wind and temperature measurements with numerical weather prediction models

High-resolution, ground-based and independent observations including co-located wind radiometer, lidar stations, and infrasound instruments are used to evaluate the accuracy of general circulation models and data-constrained assimilation systems in the middle atmosphere at northern hemisphere midlatitudes. Systematic comparisons between observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses including the recent Integrated Forecast System cycles 38r1 and 38r2, the NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses, and the free-running climate Max Planck Institute–Earth System Model–Low Resolution (MPI-ESM-LR) are carried out in both temporal and spectral dom ains. We find that ECMWF and MERRA are broadly consistent with lidar and wind radiometer measurements up to ~40 km. For both temperature and horizontal wind components, deviations increase with altitude as the assimilated observations become sparser. Between 40 and 60 km altitude, the standard deviation of the mean difference exceeds 5 K for the temperature and 20 m/s for the zonal wind. The largest deviations are observed in winter when the variability from large-scale planetary waves dominates. Between lidar data and MPI-ESM-LR, there is an overall agreement in spectral amplitude down to 15–20 days. At shorter time scales, the variability is lacking in the model by ~10 dB. Infrasound observations indicate a general good agreement with ECWMF wind and temperature products. As such, this study demonstrates the potential of the infrastructure of the Atmospheric Dynamics Research Infrastructure in Europe project that integrates various measurements and provides a quantitative understanding of stratosphere-troposphere dynamical coupling for numerical weather prediction applications.

Age models and summer sea surface temperature and winter sea ice concentration for the EPILOG-LGM time slice in the Pacific Southern Ocean

Sea surface temperatures and sea-ice extent are the most critical variables to evaluate the Southern Ocean paleoceanographic evolution in relation to the development of the global carbon cycle, atmospheric CO2 variability and ocean-atmosphere circulation. In contrast to the Atlantic and the Indian sectors, the Pacific sector of the Southern Ocean has been insufficiently investigated so far. To cover this gap of information we present diatom-based estimates of summer sea surface temperature (SSST) and winter sea-ice concentration (WSI) from 17 sites in the polar South Pacific to study the Last Glacial Maximum (LGM) at the EPILOG time slice (19,000-23,000 cal. years BP). Applied statistical methods are the Imbrie and Kipp Method (IKM) and the Modern Analog Technique (MAT) to estimate temperature and sea-ice concentration, respectively. Our data display a distinct LGM east-west differentiation in SSST and WSI with steeper latitudinal temperature gradients and a winter sea-ice edge located consistently north of the Pacific-Antarctic Ridge in the Ross sea sector. In the eastern sector of our study area, which is governed by the Amundsen Abyssal Plain, the estimates yield weaker latitudinal SSST gradients together with a variable extended winter sea-ice field. In this sector, sea-ice extent may have reached sporadically the area of the present Subantarctic Front at its maximum LGM expansion. This pattern points to topographic forcing as major controller of the frontal system location and sea-ice extent in the western Pacific sector whereas atmospheric conditions like the Southern Annular Mode and the ENSO affected the oceanographic conditions in the eastern Pacific sector. Although it is difficult to depict the location and the physical nature of frontal systems separating the glacial Southern Ocean water masses into different zones, we found a distinct temperature gradient in latitudes straddled by the modern Southern Subtropical Front. Considering that the glacial temperatures north of this zone are similar to the modern, we suggest that this represents the Glacial Southern Subtropical Front (GSSTF), which delimits the zone of strongest glacial SSST cooling (>4K) to its North. The southern boundary of the zone of maximum cooling is close to the glacial 4°C isotherm. This isotherm, which is in the range of SSST at the modern Antarctic Polar Front (APF), represents a circum-Antarctic feature and marks the northern edge of the glacial Antarctic Circumpolar Current (ACC). We also assume that a glacial front was established at the northern average winter sea ice edge, comparable with the modern Southern Antarctic Circumpolar Current Front (SACCF). During the glacial, this front would be located in the area of the modern APF. The northward deflection of colder than modern surface waters along the South American continent leads to a significant cooling of the glacial Humboldt Current surface waters (4-8K), which affects the temperature regimes as far north as into tropical latitudes. The glacial reduction of ACC temperatures may also result in the significant cooling in the Atlantic and Indian Southern Ocean, thus may enhance thermal differentiation of the Southern Ocean and Antarctic continental cooling. Comparison with temperature and sea ice simulations for the last glacial based on numerical simulations show that the majority of modern models overestimate summer and winter sea ice cover and that there exists few models that reproduce our temperature data rather well.

Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.