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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.

Turbulent fluxes of heat, momentum, and humidity in the atmospheric boundary layer are pivotal to the evolution of geology, weather and climate, and the possibility of life. Here we extend recent advances in calculating these near‐surface turbulent fluxes in the Earth's atmospheric boundary layer to any terrestrial planetary body with an atmosphere. These improvements include: (a) incorporating Monin‐Obukhov similarity functions that encompass the entire range of atmospheric stability expected on terrestrial planetary bodies, (b) accounting for the additional shear associated with buoyant plumes under unstable conditions, (c) using surface renewal theory to calculate transfer rates within the interfacial layer adjacent to the surface, and (d) explicitly accounting for key humidity effects that become especially important when a volatile is more buoyant than the ambient gas (e.g., on Mars where H2O is lighter than CO2). We tested and validated our model using in situ data collected on Earth, Mars, and Titan under a wide range of atmospheric stability, pressure, and surface roughness conditions. The model shows up to 71% better agreement with measurements compared to methods commonly used on Mars for evaporation/sublimation. Compared to previous estimates for H2O ice on Mars, our model predicts up to 1.5–190x lower latent heat fluxes under stable atmospheric conditions (depending on the wind speed) and 1.78x higher latent heat fluxes under unstable conditions. Our results provide improved constraints on the stability of ice on Mars and will help determine whether ice can melt under present‐day conditions. Plain Language Summary: As air flows over a surface, the resulting turbulent eddies cause the air to mix. The intensity of turbulence generated dictates the rate at which energy is given to, or taken away from the surface. If there are volatiles such as liquid water at the surface, then the magnitude of the turbulent fluxes determines how long the volatiles will remain stable before evaporating or freezing. We applied recent advances made on Earth to develop a model for predicting turbulent fluxes and evaporation rates on any planetary body with an atmosphere. To check whether our simulations are accurate, we compared them with measurements made on Earth, Mars and Titan. We found that our simulations agreed up to 71% better with measurements compared to previously developed models used for Mars evaporation. Our simulations predict significantly higher or lower rates of evaporation when compared to previous estimates, depending on atmospheric conditions. These results provide improved constraints on the stability of ice on Mars and will help determine whether ice can melt under present‐day conditions. Key Points: We present an improved model to predict atmospheric turbulent fluxes and evaporation/sublimation rates on any terrestrial planetary bodyThe model shows up to 71% better agreement with measurements compared to methods commonly used on Mars for evaporation and sublimationOur results provide improved constraints on the stability of Martian ice and will help determine whether ice can melt on Mars at present [ABSTRACT FROM AUTHOR]

Here, we present a compilation of 85 ice temperature profiles from 79 boreholes from the Greenland Ice Sheet and peripheral ice caps, as well as local ice caps in the Canadian Arctic. Only 25 profiles (32 %) were previously available in open-access data repositories. The remaining 54 profiles (68 %) are being made digitally available here for the first time. These newly available profiles, which are associated with pre-2010 boreholes, have been submitted by community members or digitized from published graphics and/or data tables. All 85 profiles are now made available in both absolute (meters) and normalized (0 to 1 ice thickness) depth scales, and are accompanied by extensive metadata. This metadata includes a transparent description of data provenance. The ice temperature profiles span 70 years, with the earliest profile being from 1950 at Camp VI, West Greenland. To highlight the value of this database in evaluating ice flow simulations, we compare the ice temperature profiles from the Greenland Ice Sheet with an ice flow simulation by the Parallel Ice Sheet Model (PISM). We find a cold bias in modeled near-surface ice temperatures within the ablation area, a warm bias in modeled basal ice temperatures at inland cold-bedded sites, and an apparent underestimation of deformational heating in high-strain settings. These biases provide process-level insight on simulated ice temperatures. [ABSTRACT FROM AUTHOR]

Data on surface solar radiation are scarce in high‐latitude regions, and few studies have evaluated the performance of reanalysis products in estimating solar radiation in those regions. Here, an extensive solar radiation dataset is compiled from 98 stations across Alaska to evaluate 11 different surface solar radiation products (seven reanalysis and four observation‐derived). No product can capture all aspects of the ground‐based observations, and there is ample room for improvement; root mean square errors (RMSEs) of daily, monthly, and annual average comparisons of the products against observations are 38–65, 19–39, and 11–17 W⋅m−2, respectively. ERA5, MERRA2, and ERA‐Interim performed the best in Alaska. Daily records from all products show large RMSEs of 60–108 W⋅m−2 during May–July, equivalent to 30–55% of the observed solar radiation during this season. The sparseness of Alaskan observations, cloud cover, and algorithm issues may be potential sources of bias. [ABSTRACT FROM AUTHOR]

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]