Sensitivity of terrestrial precipitation trends to the structural evolution of sea surface temperatures

Pronounced intermodel differences in the projected response of land surface precipitation (LSP) to future anthropogenic forcing remain in the Coupled Model Intercomparison Project Phase 5 model integrations. A large fraction of the intermodel spread in projected LSP trends is demonstrated here to be associated with systematic differences in simulated sea surface temperature (SST) trends, especially the representation of changes in (i) the interhemispheric SST gradient and (ii) the tropical Pacific SSTs. By contrast, intermodel differences in global mean SST, representative of differing global climate sensitivities, exert limited systematic influence on LSP patterns. These results highlight the importance to regional terrestrial precipitation changes of properly simulating the spatial distribution of large-scale, remote changes as reflected in the SST response to increasing greenhouse gases. Moreover, they provide guidance regarding which region-specific precipitation projections may be potentially better constrained for use in climate change impact assessments.

Vegetation and environmental changes in Northern Anatolia between 134 and 119ka recorded in Black Sea sediments

This multiproxy study on SE Black Sea sediments provides the first detailed reconstruction of vegetation and environmental history of Northern Anatolia between 134 and 119 ka. Here, the glacial–interglacial transition is characterized by several short-lived alternating cold and warm events preceding a meltwater pulse (~ 130.4–131.7 ka). The latter is reconstructed as a cold arid period correlated to Heinrich event 11. The initial warming is evidenced at ~ 130.4 ka by increased primary productivity in the Black Sea, disappearance of ice-rafted detritus, and spreading of oaks in Anatolia. A Younger Dryas-type event is not identifiable. The Eemian vegetation succession corresponds to the main climatic phases in Europe: i) the Quercus–Juniperus phase (128.7–126.4 ka) indicates a dry continental climate; ii) the Ostrya–Corylus–Quercus–Carpinus phase (126.4–122.9 ka) suggests warm summers, mild winters, and high year-round precipitation; iii) the Fagus–Carpinus phase (122.9–119.5 ka) indicates cooling and high precipitation; and iv) increasing Pinus at ~ 121 ka marks the onset of cooler/drier conditions. Generally, pollen reconstructions suggest altitudinal/latitudinal migrations of vegetation belts in Northern Anatolia during the Eemian caused by increased transport of moisture. The evidence for the wide distribution of Fagus around the Black Sea contrasts with the European records and is likely related to climatic and genetic factors

Eemian and Holocene sea-surface conditions in the southern Black Sea: organic-walled dinoflagellate cyst record from core 22-GC3/3

In order to compare the sea-surface conditions in the Black Sea during the Holocene and Eemian, sapropelic parts of marine core 22-GC3 (42°13.53′N/36°29.55′E, 838 m water depth) were studied for organic-walled dinoflagellate cyst content. The record shows a change from freshwater/brackish assemblages (Pyxidinopsis psilata, Spiniferites cruciformis, and Caspidinium rugosum) to more marine assemblages (Lingulodinium machaerophorum and Spiniferites ramosus complex) during each interglacial, due to the inflow of saline Mediterranean water. The lacustrine–marine transitions in 22-GC3 occurred at ~ 8.3 cal kyr BP during the early Holocene and ~ 128 kyr BP during the early Eemian, slightly later compared to the onset of interglacial conditions on the adjacent land. Dinoflagellate cyst assemblages reveal higher sea-surface salinity (~ 28–30) (e.g. Spiniferites pachydermus, Bitectatodinium tepikiense, and Spiniferites mirabilis) around ~ 126.5–121 kyr BP in comparison to the Holocene (~ 15–20) as well as relatively high sea-surface temperature (e.g. Tuberculodinium vancampoae, S. pachydermus, and S. mirabilis) especially at ~ 127.6–125.3 kyr BP. Establishment of high sea-surface salinity during the Eemian correlates very well with reconstructed relatively high global sea-level and is explained as a combined effect of increased Mediterranean supply and high temperatures at the beginning of the last interglacial. The observed changes in the dinocyst record highlight the importance of nutrients for the composition of the Eemian and Holocene dinocyst assemblages.

Communicating uncertainties in sea surface temperature

A project on sea surface temperature is generating new climate data records from satellite observations. The data are independent of in situ observations and are harmonious across satellite sensors to maximize stability and have realistic, context-sensitive uncertainty estimates at all spatial and temporal scales. The project, part of the European Space Agency Climate Change Initiative (SST CCI), now seeks to establish a useful method for communicating uncertainty in sea surface temperatures. This goal was the impetus for a workshop held in November 2014 in Exeter in the United Kingdom, summarised in this article.

Separating the influence of projected changes in air temperature and wind on patterns of sea level change and ocean heat content

We present ocean model sensitivity experiments aimed at separating the influence of the projected changes in the “thermal” (near-surface air temperature) and “wind” (near-surface winds) forcing on the patterns of sea level and ocean heat content. In the North Atlantic, the distribution of sea level change is more due to the “thermal” forcing, whereas it is more due to the “wind” forcing in the North Pacific; in the Southern Ocean, the “thermal” and “wind” forcing have a comparable influence. In the ocean adjacent to Antarctica the “thermal” forcing leads to an inflow of warmer waters on the continental shelves, which is somewhat attenuated by the “wind” forcing. The structure of the vertically integrated heat uptake is set by different processes at low and high latitudes: at low latitudes it is dominated by the heat transport convergence, whereas at high latitudes it represents a small residual of changes in the surface flux and advection of heat. The structure of the horizontally integrated heat content tendency is set by the increase of downward heat flux by the mean circulation and comparable decrease of upward heat flux by the subgrid-scale processes; the upward eddy heat flux decreases and increases by almost the same magnitude in response to, respectively, the “thermal” and “wind” forcing. Regionally, the surface heat loss and deep convection weaken in the Labrador Sea, but intensify in the Greenland Sea in the region of sea ice retreat. The enhanced heat flux anomaly in the subpolar Atlantic is mainly caused by the “thermal” forcing.

Aspects of designing and evaluating seasonal-to-interannual Arctic sea-ice prediction systems

Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter-annual Arctic sea-ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictability of Arctic climate. We also examine key issues for ensemble system design, such as: measuring skill, the role of ensemble size and generation of ensemble members. When assessing the potential skill of a set of prediction experiments, using more than one metric is essential as different choices can significantly alter conclusions about the presence or lack of skill. We find that increasing both the number of hindcasts and ensemble size is important for reliably assessing the correlation and expected error in forecasts. For other metrics, such as dispersion, increasing ensemble size is most important. Probabilistic measures of skill can also provide useful information about the reliability of forecasts. In addition, various methods for generating the different ensemble members are tested. The range of techniques can produce surprisingly different ensemble spread characteristics. The lessons learnt should help inform the design of future operational prediction systems.