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The most recent glacial to interglacial transition constitutes a remarkable natural experiment for learning how Earth's climate responds to various forcings, including a rise in atmospheric CO2 This transition has left a direct thermal remnant in the polar ice sheets, where the exceptional purity and continual accumulation of ice permit analyses not possible in other settings. For Antarctica, the deglacial warming has previously been constrained only by the water isotopic composition in ice cores, without an absolute thermometric assessment of the isotopes' sensitivity to temperature. To overcome this limitation, we measured temperatures in a deep borehole and analyzed them together with ice-core data to reconstruct the surface temperature history of West Antarctica. The deglacial warming was [Formula: see text]C, approximately two to three times the global average, in agreement with theoretical expectations for Antarctic amplification of planetary temperature changes. Consistent with evidence from glacier retreat in Southern Hemisphere mountain ranges, the Antarctic warming was mostly completed by 15 kyBP, several millennia earlier than in the Northern Hemisphere. These results constrain the role of variable oceanic heat transport between hemispheres during deglaciation and quantitatively bound the direct influence of global climate forcings on Antarctic temperature. Although climate models perform well on average in this context, some recent syntheses of deglacial climate history have underestimated Antarctic warming and the models with lowest sensitivity can be discounted.

The basal thermal state of an ice sheet (frozen or thawed) is an important control upon its evolution, dynamics and response to external forcings. However, this state can only be observed directly within sparse boreholes or inferred conclusively from the presence of subglacial lakes. Here we synthesize spatially extensive inferences of the basal thermal state of the Greenland Ice Sheet to better constrain this state. Existing inferences include outputs from the eight thermomechanical ice-flow models included in the SeaRISE effort. New remote-sensing inferences of the basal thermal state are derived from Holocene radiostratigraphy, modern surface velocity and MODIS imagery. Both thermomechanical modeling and remote inferences generally agree that the Northeast Greenland Ice Stream and large portions of the southwestern ice-drainage systems are thawed at the bed, whereas the bed beneath the central ice divides, particularly their west-facing slopes, is frozen. Elsewhere, there is poor agreement regarding the basal thermal state. Both models and remote inferences rarely represent the borehole-observed basal thermal state accurately near NorthGRIP and DYE-3. This synthesis identifies a large portion of the Greenland Ice Sheet (about one third by area) where additional observations would most improve knowledge of its overall basal thermal state.

The flow of ice is temperature-dependent, but direct measurements of englacial temperature are sparse. The dielectric attenuation of radio waves through ice is also temperature-dependent, and radar sounding of ice sheets is sensitive to this attenuation. Here we estimate depth-averaged radar-attenuation rates within the Greenland Ice Sheet from airborne radar-sounding data and its associated radiostratigraphy. Using existing empirical relationships between temperature, chemistry, and radar attenuation, we then infer the depth-averaged englacial temperature. The dated radiostratigraphy permits a correction for the confounding effect of spatially varying ice chemistry. Where radar transects intersect boreholes, radar-inferred temperature is consistently higher than that measured directly. We attribute this discrepancy to the poorly recognized frequency dependence of the radar-attenuation rate and correct for this effect empirically, resulting in a robust relationship between radar-inferred and borehole-measured depth-averaged temperature. Radar-inferred englacial temperature is often lower than modern surface temperature and that of a steady state ice-sheet model, particularly in southern Greenland. This pattern suggests that past changes in surface boundary conditions (temperature and accumulation rate) affect the ice sheet's present temperature structure over a much larger area than previously recognized. This radar-inferred temperature structure provides a new constraint for thermomechanical models of the Greenland Ice Sheet.

The last glacial period exhibited abrupt Dansgaard-Oeschger climatic oscillations, evidence of which is preserved in a variety of Northern Hemisphere palaeoclimate archives. Ice cores show that Antarctica cooled during the warm phases of the Greenland Dansgaard-Oeschger cycle and vice versa, suggesting an interhemispheric redistribution of heat through a mechanism called the bipolar seesaw. Variations in the Atlantic meridional overturning circulation (AMOC) strength are thought to have been important, but much uncertainty remains regarding the dynamics and trigger of these abrupt events. Key information is contained in the relative phasing of hemispheric climate variations, yet the large, poorly constrained difference between gas age and ice age and the relatively low resolution of methane records from Antarctic ice cores have so far precluded methane-based synchronization at the required sub-centennial precision. Here we use a recently drilled high-accumulation Antarctic ice core to show that, on average, abrupt Greenland warming leads the corresponding Antarctic cooling onset by 218 ± 92 years (2σ) for Dansgaard-Oeschger events, including the Bølling event; Greenland cooling leads the corresponding onset of Antarctic warming by 208 ± 96 years. Our results demonstrate a north-to-south directionality of the abrupt climatic signal, which is propagated to the Southern Hemisphere high latitudes by oceanic rather than atmospheric processes. The similar interpolar phasing of warming and cooling transitions suggests that the transfer time of the climatic signal is independent of the AMOC background state. Our findings confirm a central role for ocean circulation in the bipolar seesaw and provide clear criteria for assessing hypotheses and model simulations of Dansgaard-Oeschger dynamics.

The cause of warming in the Southern Hemisphere during the most recent deglaciation remains a matter of debate. Hypotheses for a Northern Hemisphere trigger, through oceanic redistributions of heat, are based in part on the abrupt onset of warming seen in East Antarctic ice cores and dated to 18,000 years ago, which is several thousand years after high-latitude Northern Hemisphere summer insolation intensity began increasing from its minimum, approximately 24,000 years ago. An alternative explanation is that local solar insolation changes cause the Southern Hemisphere to warm independently. Here we present results from a new, annually resolved ice-core record from West Antarctica that reconciles these two views. The records show that 18,000 years ago snow accumulation in West Antarctica began increasing, coincident with increasing carbon dioxide concentrations, warming in East Antarctica and cooling in the Northern Hemisphere associated with an abrupt decrease in Atlantic meridional overturning circulation. However, significant warming in West Antarctica began at least 2,000 years earlier. Circum-Antarctic sea-ice decline, driven by increasing local insolation, is the likely cause of this warming. The marine-influenced West Antarctic records suggest a more active role for the Southern Ocean in the onset of deglaciation than is inferred from ice cores in the East Antarctic interior, which are largely isolated from sea-ice changes.

The diurnal temperature range (DTR) is an identifiable and sensitive indicator of the synchronicity of changes in diurnal temperature extrema, but capturing DTR dynamics is challenging for climate models. This study investigates the climatology, variability, and changes of DTR in recent models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The results show that the CMIP6 models underestimate DTR climatology relative to observations. Most individual models overestimate December-February variability, particularly at high latitudes of the Northern Hemisphere. The models show substantially different changes over land surfaces and do not fully capture the observed spatiotemporal evolution of DTR. Large intermodel differences seem to be controlled by daily minimum air temperature. In the Northern Hemisphere, precipitation and cloud longwave and shortwave radiative effects appear tomake important contributions to the intermodel discrepancies. Evaporative fraction is an important factor contributing to the intermodel differences in DTR during the summer in the Northern Hemisphere. In general, CMIP6 models have not improved their ability to simulate temporal DTR changes in a consistent way over the entire analysis period (1901-2005) relative to theirCMIP5 counterparts. For periods of rapidDTRdecline (e.g., 1951-80)CMIP6models are typically better than the CMIP5 versions at simulating DTR, whereas for other periods CMIP6 models underperform their CMIP5 counterparts. [ABSTRACT FROM AUTHOR]

Land surface air temperature is an essential climate variable for understanding rapid global environmental changes. Sparse network coverage prior to the 1950s is a significant source of uncertainty in global climate change evaluations. Recognizing the importance of spatial coverage, more stations are continually being added to global climate networks. A challenge is how to best use the information introduced by the new station observations to enhance our understanding and assessment of global climate states and changes, particularly for times prior to the mid‐20th century. In this study, Data INterpolating Empirical Orthogonal Functions (DINEOF) were used to reconstruct mean monthly air temperatures from the Global Historical Climatology Network‐monthly (GHCNm version 4) over the land surface from 1880 through 2017. The final reconstructed air temperature dataset covers about 95% of the global land surface area, improving the spatial coverage by ~80% during 1880–1900 and by 10%–20% since the 1950s. Validation tests show that the mean absolute error of the reconstructed data is less than 0.82°C. Comparison with the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model output shows that the reconstructed dataset substantially reduces the bias in global datasets caused by sparse station coverage, particularly before the 1950s. [ABSTRACT FROM AUTHOR]

The vulnerability of dryland surfaces to wind erosion depends importantly on the absence or the presence and character of surface roughness elements, such as plants, clasts, and topographic irregularities that diminish wind speed near the surface. A model for the friction velocity ratio has been developed to account for wind sheltering by many different types of co-existing roughness elements. Such conditions typify a monitored area in the central Mojave Desert, California, that experiences frequent sand movement and dust emission. Two additional models are used to convert the friction velocity ratio to the surface roughness length (zo) for momentum. To calculate roughness lengths from these models, measurements were made at 11 sites within the monitored area to characterize the surface roughness element. Measurements included (1) the number of roughness species (e.g., plants, small-scale topography, clasts), and their associated heights and widths, (2) spacing among species, and (3) vegetation porosity (a measurement of the spatial distribution of woody elements of a plant). Documented or estimated values of drag coefficients for different species were included in the modeling. At these sites, wind-speed profiles were measured during periods of neutral atmospheric stability using three 9-m towers with three or four calibrated anemometers on each. Modeled roughness lengths show a close correspondence (correlation coefficient, 0.84–0.86) to the aerodynamically determined values at the field sites.The geometric properties of the roughness elements in the model are amenable to measurement at much higher temporal and spatial resolutions using remote-sensing techniques than can be accomplished through laborious ground-based methods. A remote-sensing approach to acquire values of the modeled roughness length is particularly important for the development of linked surface/atmosphere wind-erosion models sensitive to climate variability and land-use changes in areas such as the southwestern United States, where surface roughness has large spatial and temporal variations. [Copyright &y& Elsevier]