Several decades of ice-penetrating radar surveys of the Greenland and Antarctic ice sheets have observed numerous widespread internal reflections. Analysis of this radiostratigraphy has produced valuable insights into ice sheet dynamics and motivates additional mapping of these reflections. Here we present a comprehensive deep radiostratigraphy of the Greenland Ice Sheet from airborne deep ice-penetrating radar data collected over Greenland by The University of Kansas between 1993 and 2013. To map this radiostratigraphy efficiently, we developed new techniques for predicting reflection slope from the phase recorded by coherent radars. When integrated along track, these slope fields predict the radiostratigraphy and simplify semiautomatic reflection tracing. Core-intersecting reflections were dated using synchronized depth-age relationships for six deep ice cores. Additional reflections were dated by matching reflections between transects and by extending reflection-inferred depth-age relationships using the local effective vertical strain rate. The oldest reflections, dating to the Eemian period, are found mostly in the northern part of the ice sheet. Within the onset regions of several fast-flowing outlet glaciers and ice streams, reflections typically do not conform to the bed topography. Disrupted radiostratigraphy is also observed in a region north of the Northeast Greenland Ice Stream that is not presently flowing rapidly. Dated reflections are used to generate a gridded age volume for most of the ice sheet and also to determine the depths of key climate transitions that were not observed directly. This radiostratigraphy provides a new constraint on the dynamics and history of the Greenland Ice Sheet.Key PointsPhase information predicts reflection slope and simplifies reflection tracingReflections can be dated away from ice cores using a simple ice flow modelRadiostratigraphy is often disrupted near the onset of fast ice flow

Recent studies examine the potential for large urban fires ignited in a hypothetical nuclear exchange of one hundred 15 kt weapons between India and Pakistan to alter the climate (e.g.,

A calibrated single-model ensemble (SME) derived from the NCAR Community Atmosphere Model, version 3.1, is used to test two hypothesized emergent constraints on cloud feedback and equilibrium climate sensitivity (ECS). The Fasullo and Trenberth relative humidity (RH) metric and the Sherwood et al. lower-tropospheric mixing (LTMI) metric are computed for the present-day climate of the SME, and the relationships between the metrics, ECS, and cloud and other climate feedbacks are examined. The tropical convergence zone relative humidity (RH M) and the parameterized lower-tropospheric mixing (LTMI S) are positively correlated to ECS, and each is associated with a different spatial pattern of tropical shortwave cloud feedback in the SME. However, neither of those metrics is linked to the type of cloud response hypothesized by its authors. The resolved lower-tropospheric mixing (LTMI D) is positively correlated to ECS for a subset of the SME having LTMI D over a threshold value. LTMI and the RH for the dry, descending branch of the Hadley cell (RH D) narrow and shift upward the posterior estimates of ECS in the SME, but the SME bias in RH D and concerns over poorly understood physical mechanisms suggest the narrowing could be spurious for both constraints. While calibrated SME results may not generalize to multimodel ensembles, they can enhance the process understanding of emergent constraints and serve as out-of-sample tests of robustness.

We find that part of the uncertainty in the amplitude and pattern of the modeled precipitation response to CO2 forcing traces to tropical condensation not directly involved with parameterized convection. The fraction of tropical rainfall associated with large-scale condensation can vary from a few percent to well over half depending on model details and parameter settings. In turn, because of the coupling between condensation and tropical circulation, the different ways model assumptions affect the large-scale rainfall fraction also affect the patterns of the response within individual models. In two single-model ensembles based on the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM), versions 3.1 and 5.3, we find strong correlations between the fraction of tropical large-scale rain and both climatological rainfall and circulation and the response to CO2 forcing. While the effects of an increasing tropical large-scale rain fraction are opposite in some ways in the two ensembles—for example, the Hadley circulation weakens with the large-scale rainfall fraction in the CAM3.1 ensemble while strengthening in the CAM5.3 ensemble—we can nonetheless understand these different effects in terms of the relationship between latent heating and circulation, and we propose explanations for each ensemble. We compare these results with data from phase 5 of the Coupled Model Intercomparison Project (CMIP5), for which some of the same patterns hold. Given the importance of this partitioning, there is a need for constraining this source of uncertainty using observations. However, since a “large-scale rainfall fraction” is a modeling construct, it is not clear how observations may be used to test various modeling assumptions determining this fraction.

We use a physical model to investigate how changes in subglacial hydrology affect ice motion of Antarctic ice streams. Ice streams are modelled using silicone polymer placed over a thin water layer to mimic ice flow dominated by basal sliding. The model ice-stream force balance is calculated and compared directly to the observed force balance of Whillans Ice Stream (WIS). Dynamic similarity between the model and WIS is achieved when their force balances are equivalent. The WIS force balance has evolved over time owing to increased basal resistance. We test two hypotheses: (1) the subglacial water distribution influences the ice-flow speed and thus the force balance; (2) shear margins are locations where transitions in water layer thickness occur. We find that the velocity and force balance are sensitive to pulsed water discharge events and changes in lubrication that result in sticky spots, and that model shear margins tend to overlie water lubrication boundaries. We conclude that local changes in basal lubrication near margins (possibly as a result of the presence of sticky spots or subglacial lakes) influence the stability of ice-stream margin position and may be responsible for large and rapid shifts in margin location.

No abstract

No abstract

Automated custom calibration for the Energy Exascale Earth System Model (E3SM) applies primarily to focal area 2: Predictive modeling through the use of AI techniques, and includes elements of focal area 3: Insight gleaned from complex data (both observed and simulated). Science ChallengeEarth System Models (ESM) contain uncertain parameters that cannot be uniquely determined by data or theory, and can affect model predictions. The current state-of-the-art is to precede each release of an ESM with an expert tuning, also known as calibration, that takes 6-12 months, requires a large supercomputer allocation, and is deterministic, i.e. a single choice for each uncertain parameter is set in the model code. A single deterministic tuning inevitably degrades some predictions and underestimates uncertainty for all predictions. Those looking to make decisions on, or answer science questions with, climate predictions will best be served by custom, probabilistic calibrations.