Evaluating historical simulations from global climate models (GCMs) remains an important exercise for better understanding future projections of climate change and variability in rapidly warming regions, such as the Arctic. As an alternative approach for comparing climate models and observations, we set up a machine learning classification task using a shallow artificial neural network (ANN). Specifically, we train an ANN on maps of annual mean near-surface temperature in the Arctic from a multi-model large ensemble archive in order to classify which GCM produced each temperature map. After training our ANN on data from the large ensembles, we input annual mean maps of Arctic temperature from observational reanalysis and sort the prediction output according to increasing values of the ANN’s confidence for each GCM class. To attempt to understand how the ANN is classifying each temperature map with a GCM, we leverage a feature attribution method from explainable artificial intelligence. By comparing composites from the attribution method for every GCM classification, we find that the ANN is learning regional temperature patterns in the Arctic that are unique to each GCM relative to the multi-model mean ensemble. In agreement with recent studies, we show that ANNs can be useful tools for extracting regional climate signals in GCMs and observations.

The ice stream geometry and large ice surface velocities at the onset region of the Northeast Greenland Ice Stream (NEGIS) are not yet well reproduced by ice sheet models. They are a significant source of uncertainty in present ice sheet projections towards their future contribution to sea-level rise. The quantification of basal sliding and a parametrisation of basal conditions remains a major gap. In this study, we assess the basal conditions of the onset region of the NEGIS in a systematic analysis of airborne ultra-wideband radar data. We evaluate basal roughness and basal return echoes in the context of the current ice stream geometry and ice surface velocity. We observe a change from a smooth to a rougher bed where the ice stream widens, and a distinct roughness anisotropy, indicating a preferred orientation of subglacial structures. In this region, we also find an apparent increase of the bed return power towards the centre of the ice stream, potentially indicating increased water content at the base. At the downstream part, we observe an increased bed return power throughout the entire width of the ice stream and outside its margins. Together with basal water routing pathways, this hints to two different zones in this part of NEGIS: the upstream region collecting water, reducing basal traction, and in the further downstream part the distribution of basal water underneath and beyond the shear margins. Our findings support the hypothesis that the NEGIS is strongly controlled by the subglacial water system in its onset region.

Dolomite (CaMg(CO3)2) forms in minor quantities in few modern environments yet comprises most of the Precambrian carbonate rock record. Precambrian dolomites are often fine-grained and fabric-retentive and are interpreted to have precipitated as primary cements or formed as early diagenetic replacements of CaCO3. Primary dolomite precipitation from seawater in depositional environments has not yet been described. Here, we use synchrotron radiation to produce a nanoscale-resolution crystal orientation map of one exquisitely preserved ooid deposited at the onset of the Shuram carbon isotope excursion at ~574 Ma. The crystal orientation map reveals small (~10 μm) acicular, radially-oriented crystals grouped into bundles of similarly-oriented crystals with varying optical properties. We interpret this dolomite formed via primary, spherulitic precipitation during ooid growth in shallow marine waters. This result provides additional evidence that the physicochemical properties of late Precambrian oceans promoted dolomite precipitation and supports a primary origin for the Shuram excursion.

Evidence based on sparse tree-ring data suggests a severe sustained drought occurred in the 2nd century CE that could have rivaled medieval period droughts in the Colorado River basin (Gangopadhyay et al. 2022). Most of these tree-ring data have been used in gridded drought reconstructions (Cook et al., 2010) which extend back to 1 CE over an area that includes the intermountain western US. However, the 2nd century drought has not been highlighted in prior studies given the sparseness of the data available for this time period. A new reconstruction of Colorado River flow based on these data documents a notably severe and sustained drought over much of the 2nd century (Gangopadhyay et al. 2022). While this reconstruction suggests that the drought exceeds the severity and duration of any drought in the past 2000 years, a complete assessment of the 2nd century drought is challenging due to the sparseness of data. In this poster presentation, we describe the tree-ring data available, along with other proxy data that provide evidence for the 2nd century drought and support its severity. In our conclusions, we discuss outstanding questions and thoughts for further work.

Model simulations of past climates are increasingly found to compare well with proxy data at a global scale, but regional discrepancies remain. A persistent issue in modeling past greenhouse climates has been the temperature difference between equatorial and (sub-)polar regions, which is typically much larger in simulations than proxy data suggest. Particularly in the Eocene, multiple temperature proxies suggest extreme warmth in the southwest Pacific Ocean, where model simulations consistently suggest temperate conditions. Here we present new global ocean model simulations at 0.1° horizontal resolution for the middle-late Eocene. The eddies in the high-resolution model affect poleward heat transport and local time-mean flow in critical regions compared to the non-eddying flow in the standard low-resolution simulations. As a result, the high-resolution simulations produce higher surface temperatures near Antarctica and lower surface temperatures near the equator compared to the low-resolution simulations, leading to better correspondence with proxy reconstructions. Crucially, the high-resolution simulations are also much more consistent with biogeographic patterns in endemic-Antarctic and low-latitude-derived plankton, and thus resolve the long-standing discrepancy of warm subpolar ocean temperatures and isolating polar gyre circulation. The results imply that strongly eddying model simulations are required to reconcile discrepancies between regional proxy data and models, and demonstrate the importance of accurate regional paleobathymetry for proxy-model comparisons.

The fastest projected rates of sea level rise appear in models which include “the marine ice cliff instability (MICI),” a hypothesized but mostly unobserved process defined by rapid, brittle failure of terminal ice cliffs that outpaces viscous relaxation and ice-shelf formation. The response of Crane Glacier to the Larsen B Ice Shelf collapse has been invoked as observational evidence of this process, but limited data coverage in space and time has limited our ability to meaningfully refine our understanding of cliff failure processes using that event. Updates to Crane’s subglacial topography show that much of its terminus retreat occurred in floating, not grounded ice, but its retreat, arrest, and regrowth over the last decade indicate brittle (not viscous) processes dominated during the 2 years following ice shelf collapse. If retreat occurred by cliff failure, maximum cliff heights would have been 111 m, consistent with process models that incorporate damaged ice.

As a consequence of a diminishing sea ice cover in the Arctic, activity is on the rise. The position of the sea ice edge, which is generally taken to define the extent of the ice cover, changes in response to dynamic and thermodynamic processes. Forecasts for sea ice expansion due to an advancing ice edge will provide information that can be of significance for operations in polar regions. However, the value of this information depends on the quality of the forecasts. Here, we present methods for examining the quality of forecasted sea ice expansion and the geographic location where the largest expansion are expected from the forecast results. The algorithm is simple to implement, and an examination of two years of model results and accompanying observations demonstrates the usefulness of the analysis.

El Niño-Southern Oscillation (ENSO) shows a large diversity of events that is modulated by climate variability and change. The representation of this diversity in climate models limits our ability to predict their impact on ecosystems and human livelihood. Here, we use multiple observational datasets to provide a probabilistic description of historical variations in event location and intensity, and to benchmark models, before examining future system trajectories. We find robust decadal variations in event intensities and locations in century-long observational datasets, which are associated with perturbations in equatorial wind-stress and thermocline depth, as well as extra-tropical anomalies in the North and South Pacific. Some climate models are capable of simulating such decadal variability in ENSO diversity, and the associated large-scale patterns. Projections of ENSO diversity in future climate change scenarios strongly depend on the magnitude of decadal variations, and the ability of climate models to reproduce them realistically over the 21st century.

An analysis of concurrent extreme events of continental precipitation and Integrated Water Vapour Transport (IVT) is crucial to our understanding of the role of the major global mechanisms of atmospheric moisture transport, including that of the landfalling Atmospheric Rivers (ARs) in extratropical regions. For this purpose, gridded data on CPC precipitation and ERA-5 IVT at a spatial resolution of 0.5 º were used, covering the period from Winter 1980/1981 to Autumn 2017. For each season, and for each point with more than 400 non-dry days, several copula models were fitted to model the joint distribution function of the two variables. At each of the analysed points, the best copula model was used to estimate the probability of a concurrent extreme. At the same time, within the sample of observed concurrent extremes, the proportion of days with landfalling ARs was calculated for the whole period and for two 15-year subperiods, one earlier period and one more recent (warmer) period. Three metrics based on copulas were used to analyse carefully the influence of IVT on extreme precipitation in the main regions of occurrence of AR landfall. The results show that the probability of occurrence of concurrent extremes is strongly conditioned by the dynamic component of the IVT, the wind. The occurrence of landfalling ARs accounts for most of the concurrent extreme days of IVT and continental precipitation, with percentages of concurrent extreme days close to 90% in some seasons in almost all the known regions of maximum occurrence of landfalling ARs, and with percentages greater than 75% downwind of AR landfall regions. This coincidence was lower in tropical regions, and in monsoonal areas in particular, with percentages of less than 50%. With a few exceptions, the role of landfalling ARs as drivers of concurrent extremes of IVT and continental precipitation tends to show a decrease in recent (warmer) periods. For almost all the landfalling AR regions with high or very high probabilities of achieving a concurrent extreme, there is a general trend towards a lower influence of IVT on extreme continental precipitation in recent (warmer) periods.

The Antarctic Ice Sheet (AIS) response to past warming consistent with the 1.5–2°C ‘safe limit’ of the United Nations Paris Agreement is currently not well known. Empirical evidence from the most recent comparable period, the Last Interglaciation, is sparse, and transient ice-sheet model simulations are few and inconsistent. Here we present new results from transiently-forced ice-sheet modelling experiments. We evaluate our results against near and far-field proxy reconstructions and find good agreement. Our simulations indicate that the AIS contributed approximately 4 m to global mean sea level, peaking at 126 ka BP, with ice lost primarily from the Amundsen but not Ross or Weddell Sea sectors. The AIS thinned in the area of the Wilkes Subglacial Basin but did not retreat. Continuing beyond present day our model predicts that the West Antarctic Ice Sheet may already be predisposed to collapse even in the absence of further environmental change.

Quantifying the anthropogenic fluxes of CO2 is important to understand the evolution of carbon sink capacities, on which the required strength of our mitigation efforts directly depends. For the historical period, the global carbon budget (GCB) can be compiled from observations and model simulations as is done annually in the Global Carbon Project’s (GCP) carbon budgets. However, the historical budget only considers a single realization of the Earth system and cannot account for internal climate variability. Understanding the distribution of internal climate variability is critical for predicting the future carbon budget terms and uncertainties. We present here a decomposition of the GCB for the historical period and the RCP4.5 scenario using single model large ensemble simulations from the Max Planck Institute Grand Ensemble (MPI-GE) to capture internal variability. We calculate uncertainty ranges for the natural sinks and anthropogenic emissions that arise from internal climate variability, and by using this distribution, we investigate the likelihood of historical fluxes with respect to plausible climate states. Our results show these likelihoods have substantial fluctuations due to internal variability, which are partially related to ENSO. We find that the largest internal variability in the MPI-GE stems from the natural land sink and its increasing carbon stocks over time. The allowable fossil fuel emissions consistent with 3°C warming may be between 9–18 PgCyr-1. The MPI-GE is generally consistent with GCP’s global budgets with the notable exception of land-use change emissions in recent decades, highlighting that human action is inconsistent with climate mitigation goals.

A Large Eddy Simulation (LES) model that simulates the aerosol lifecycle, including aerosol sources and sinks, was used to study the stratocumulus to cumulus transition (SCT). To initialize, force, and evaluate the LES, we used a combination of reanalysis, satellite, and aircraft data from the Cloud System Evolution in the Trades field campaign in summer 2015 over the Northeast Pacific. The simulations follow two Lagrangian trajectories from initially overcast stratocumulus to the tropical shallow cumulus region near Hawaii. The first trajectory is characterized by an initially clean, well-mixed stratocumulus-topped marine boundary layer (MBL), then continuous MBL deepening and precipitation onset followed by a clear SCT and a consistent reduction of aerosols that ultimately leads to an ultra-clean layer in the upper MBL. The second trajectory is characterized by an initially polluted and decoupled MBL, weak precipitation, and a late SCT. Overall, the LES simulates the general MBL features seen in observations. Sensitivity studies with different aerosol initial and boundary conditions reveal aerosol-induced changes in the transition, and albedo changes are decomposed into the Twomey effect and adjustments of cloud liquid water path and cloud fraction. Impacts on precipitation play a key role in the sensitivity to aerosols: for the first case, runs with enhanced aerosols exhibit distinct changes in microphysics and macrophysics such as enhanced cloud droplet number concentration, reduced precipitation, and delayed SCT. Cloud adjustments are dominant in this case. For the second case, enhancing aerosols does not affect cloud macrophysical properties significantly, and the Twomey effect dominates.

For decades, the Arctic has been warming at least twice as fast as the rest of the globe. As a first step towards quantifying parametric uncertainty in Arctic feedbacks, we perform a variance-based global sensitivity analysis (GSA) using a fully-coupled, ultra-low resolution (ULR) configuration of version 1 of the Department of Energy’s Energy Exascale Earth System Model (E3SMv1). The study randomly draws 139 realizations of ten model parameters spanning three E3SMv1 components (sea ice, atmosphere and ocean), which are used to generate 75 year long projections of future climate using a fixed pre-industrial forcing. We quantify the sensitivity of six Arctic-focused quantities of interest (QOIs) to these parameters using main effect, total effect and Sobol sensitivity indices computed with a Gaussian process emulator. A sensitivity index-based ranking of model parameters shows that the atmospheric parameters in the CLUBB (Cloud Layers Unified by Binormals) scheme have significant impact on sea ice status and the larger Arctic climate. We also use the Gaussian process emulator to predict the response of varying each variable when the impact of other parameters are averaged out. These results allow one to assess the non-linearity of a parameter’s impact on a QOI and investigate the presence of local minima encountered during the spin-up tuning process. Our study confirms the necessity of performing global analyses involving fully-coupled climate models, and motivates follow-on investigations in which the ULR model is compared rigorously to higher resolution configurations to confirm its viability as a lower-cost surrogate in fully-coupled climate uncertainty analyses.

A new algorithm is proposed for estimating time-evolving global forcing in climate models. The method is a further development of the work of Forster et al. (2013), taking into account the non-constancy of the global feedbacks. We assume that the non-constancy of this global feedback can be explained as a time-scale dependence, associated with linear temperature responses to the forcing on different time scales. With this method we obtain stronger forcing estimates than previously assumed for the representative concentration pathway experiments in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The reason for the higher future forcing is that the global feedback parameter is more negative at shorter time scales than at longer time scales, consistent with the equilibrium climate sensitivity increasing with equilibration time. Our definition of forcing provides a clean separation of forcing and response, and we find that linear temperature response functions estimated from experiments with abrupt quadrupling of CO$_2$ can be used to predict responses also for future scenarios. In particular, we demonstrate that for most models, the response to our new forcing estimate applied on the 21st century scenarios provides a global surface temperature up to year 2100 consistent with the output of coupled model versions of the respective model.

Survey evidence has indicated that a significant percentage of the population does not fully embrace the scientific consensus regarding climate change. This paper assesses whether the hourly temperature data support this denial. Specifically, this paper examines the relationship between hourly CO2 atmospheric concentration levels and temperature using hourly data from the NOAA-operated Barrow observatory in northern Alaska. At this observatory, the average annual temperature over the 2015-2020 period has been about 3.37 oC higher than in the 1985-1990 period. A time-series model to explain hourly temperature is formulated using the following explanatory variables: the hourly level of total downward solar irradiance, the hourly CO2 value lagged by one hour, proxies for the diurnal variation in temperature, proxies for the seasonal temperature variation, and proxies for possible non-anthropomorphic drivers of temperature. A time-series modeling specification is employed to capture the data’s heteroskedastic and autoregressive nature. The model is estimated using hourly data from 1 Jan 1985 through 31 Dec 2015. The results are consistent with the hypothesis that increases in CO2 concentration levels have nontrivial consequences for hourly temperature. The estimated annual contributions of factors exclusive of CO2 and downward total solar irradiance are very small. The model was evaluated using out-of-sample hourly data from 1 Jan 2016 through 31 Aug 2017. The model’s out-of-sample hourly temperature predictions are highly accurate, but this accuracy is significantly degraded if the estimated CO2 effects are ignored. In short, the results are consistent with the scientific consensus on climate change.

Moisture recycling via evapotranspiration (ET) is often invoked as a mechanism for the high deuterium excess signals observed in continental precipitation (dP). However, a global-scale analysis of precipitation monitoring station isotope data shows that metrics of ET contributions to precipitation (van der Ent et al., 2014) explain little dp variability on seasonal timescales. This occurs despite the fact that ET contributions increase by ~50% in continental locations such as the Eurasian interior from wet to dry seasons. To explain this apparent paradox, we hypothesize that the effects of ET on dP are dampened during dry seasons due to contributions from isotopically-evolved residual water storage that act to lower the d-excess of ET fluxes (dET), in combination with changes in transpiration fraction (T/ET). To test this hypothesis, we develop a parsimonious two-season (wet, dry) model for dET incorporating residual water storage and ET partitioning effects. We find that in environments with limited water storage, such as shallow-rooted grasslands, dry season dET is lower than wet season dET despite lower relative humidity. As global average ratios of annual water storage to precipitation are relatively low (Guntner et al., 2007), these dynamics may be widespread over continents. In environments where water storage is not limiting, such as groundwater-dependent ecosystems, dry season dET is still likely lower; however, this effect arises instead due to higher seasonal T/ET when energy-driven plant water use is enhanced and surface evaporation is relatively limited by water availability. Together, these analyses also indicate multiple mechanisms by which dET may be lower than dp during the same season, challenging the view that moisture recycling feedback increases the dp in continental interiors. This work demonstrates the potential complexity of seasonal dp dynamics and cautions against simple interpretations of dP as a process tracer for moisture recycling. References: Guntner et al., 2007. Water Resour. Res., 43, W05416. van der Ent et al., 2014. Earth Syst. Dynam., 5, 471–489.

The Early Turonian interval represents a unique confluence of climatic and oceanographic conditions including peak surface temperatures, high greenhouse-gas concentrations and maximum Phanerozoic sea level. The susceptibility of this climate mode to short-term forcings such as astronomically paced insolation remains poorly understood partly due to a limited time control and unknown phasing of astronomical cycles in this interval. Here we offer a refined astrochronology of the Early Turonian based on laterally consistent precession signals preserved in offshore strata of the Bohemian Cretaceous Basin (central Europe). Pristine amplitude modulation verified through interference patterns in depth-frequency plots provides a robust indication of ~100-kyr and 405-kyr eccentricity phases (maxima and minima) that are pinned to ammonite biozones and new carbon-isotope data from two cores. The Early Turonian is estimated as 885 ±46 thousand years (kyr) in duration, with the Cenomanian-Turonian boundary predating the nearest 405-kyr maximum by 81 ±32 kyr. The results support a possible link of the recovery from Oceanic Anoxic Event II to increasing magnitude of seasonal insolation extremes due to rising eccentricity on 405-kyr and million-year (Myr) time scales. Superimposed upon this trend are small-scale carbon-isotope anomalies the pacing of which passes from ~110 kyr, resembling short eccentricity, to ~170-kyr, possibly related to obliquity modulation. The loss of short-eccentricity pacing despite Myr-scale increase in eccentricity amplitudes suggests decoupling of the carbon-cycle perturbations from low-latitude seasonal insolation and involvement of mid- to high-latitude carbon reservoirs.

Optical televiewer borehole logging within a crevassed region of fast-moving Store Glacier, Greenland, revealed the presence of 35 high-angle planes that cut across the background primary stratification. These planes were composed of a bubble-free layer of refrozen ice, most of which hosted thin laminae of bubble-rich ‘last frozen’ ice, consistent with the planes being the traces of former open crevasses. Several such last-frozen laminae were observed in four traces, suggesting multiple episodes of crevasse reactivation. The frequency of crevasse traces generally decreased with depth, with the deepest detectable trace being 265 m below the surface. This is consistent with the extent of the warmer-than-modelled englacial ice layer in the area, which extends from the surface to a depth of ~400 m. Crevasse trace orientation was strongly clustered around a dip of 63° and a strike that was offset by 71° from orthogonal to the local direction of principal extending strain. The traces’ antecedent crevasses were therefore interpreted to have originated upglacier, probably ~8 km distant involving mixed-mode (I and III) formation. We conclude that deep crevassing is pervasive across Store Glacier, and therefore also at all dynamically similar outlet glaciers. Once healed, their traces represent planes of weakness subject to reactivation during their subsequent advection through the glacier. Given their depth, it is highly likely that such traces - particularly those formed downglacier - survive surface ablation to reach the glacier terminus, where they may represent foci for fracture and iceberg calving.

The TRACMIP ensemble includes slab-ocean aquaplanet control simulations and experiments with a highly idealized narrow tropical continent (0-45ºW; 30ºS - 30ºN). We compare the two setups to contrast the characteristics of oceanic and continental rain bands and investigate monsoon development in GCMs with CMIP5-class dynamics and physics. Over land, the rainy season occurs close to the time of maximum insolation. Other than in its timing, the continental rain band remains in an ITCZ-like regime akin deep-tropical monsoons, with a smooth latitudinal transition, a poleward reach only slightly farther than the oceanic ITCZ’s (about 10º), and a constant width throughout the year. This confinement of the monsoon to the deep tropics is the result of a tight coupling between regional rainfall and circulation anomalies: ventilation of the lower troposphere by the anomalous meridional circulation is the main limiting mechanism, while ventilation by the mean westerly jet aloft is secondary. Comparison of two sub-sets of TRACMIP simulations indicates that a low heat capacity determines, to a first degree, both the timing and the strength of the regional solsticial circulation; this lends support to the choice of idealizing land as a thin slab ocean in much theoretical literature on monsoon dynamics. Yet, the timing and strength of the monsoon are modulated by the treatment of evaporation over land, especially when moisture and radiation can interact. This points to the need for a fuller exploration of land characteristics in the hierarchical modeling of the tropical rain bands.

By injecting SO2 into the stratosphere at four latitudes (30°, 15° N/S), it might be possible not only to reduce global mean surface temperature but also to minimize changes in the equator-to-pole and inter-hemispheric gradients of temperature, further reducing some of the impacts arising from climate change relative to equatorial injection. This can happen only if the aerosols are transported to higher latitudes by the stratospheric circulation, ensuring that a greater part of the solar radiation is reflected back to space at higher latitudes, compensating for the reduced sunlight. However, the stratospheric heating produced by these aerosols modifies the circulation and strengthens the stratospheric polar vortex which acts as a barrier to the transport of air toward the poles. We show how the heating results in a feedback where increasing injection rates lead to stronger high-latitudinal transport barriers. This implies a potential limitation in the high-latitude aerosol burden and subsequent cooling.

Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIA change, internal variability accounts for as much as 40-60% of the total uncertainty in the next decade, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for approximately 60-70% of the total uncertainty by mid-century and declines to 30% at the end of the 21st century during the summer months. For projections of wintertime Arctic SIA change, internal variability contributes as much as 50-60% of the total uncertainty in the next decade and impacts total uncertainty at longer lead times when compared to the summertime. Model structure contributes most of the remaining uncertainty with emissions scenario contributing little to the total uncertainty during the winter months. At regional scales, the contribution of internal variability can vary widely and strongly depends on the month and region. For wintertime SIA change in the GIN and Barents Seas, internal variability contributes approximately 60-70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate the need to improve the representation of internal variability of Arctic SIA in models, which is a significant source of uncertainty in future projections.

Estimates of changes in the frequency or height of contemporary extreme sea levels (ESLs) under various climate change scenarios are often used by climate and sea level scientists to help communicate the physical basis for societal concern regarding sea-level rise. Changes in ESLs (i.e., the hazard) are often represented using various metrics and indicators that, when anchored to salient impacts on human systems and the natural environment, provide useful information to policy makers, stakeholders, and the general public. While changes in hazards are often anchored to impacts at local scales, aggregate global summary metrics generally lack the context of local exposure and vulnerability that facilitates translating hazards into impacts. Contextualizing changes in hazards is also needed when communicating the timing of when projected ESL frequencies cross critical thresholds, such as the year in which ESLs higher than the design height benchmark of protective infrastructure (e.g., the 100-yr water level) are expected to occur within the lifetime of that infrastructure. We present specific examples demonstrating the need for such contextualization using a simple flood exposure model, local sea-level rise projections, and population exposure estimates for 414 global cities. We suggest regional and global climate assessment reports integrate global, regional, and local perspectives on coastal risk to address hazard, vulnerability and exposure simultaneously.

Through the PolarTREC program that pairs US educators with field researchers in polar regions, our team has been collaborating on K-12 and undergraduate curriculum development and outreach activities on Arctic amplification of climate change. We have created new lesson plans and activities focused on how organic carbon from thawing permafrost in the Arctic is turned into carbon dioxide, a greenhouse gas that amplifies climate change. This presentation will cover our collaboration to bring this knowledge and experience to high school science students through classroom activities and projects. The focus will be laboratory activities designed for the chemistry classroom: use of spectrophotometry to assess degree of photobleaching in organic samples and evaluation of data from high resolution mass spectrometry to characterize complex organic mixtures. We will also review lessons learned from our efforts to promote enthusiasm for polar science within the general public and discuss the benefits of the PolarTREC program to researchers, educators, students, and the public.

In calculating solar radiation, climate models make many simplifications, in part to reduce computational cost and enable climate modeling, and in part from lack of understanding of critical atmospheric information. Whether known errors or unknown errors, the community’s concern is how these could impact the modeled climate. The simplifications are well known and most have published studies evaluating them, but with individual studies it is difficult to compare. Here we collect a wide range of such simplifications in either radiative transfer modeling or atmospheric conditions and assess potential errors within a consistent framework on climate-relevant scales. We build benchmarking capability around a solar heating code (Solar-J) that doubles as a photolysis code for chemistry and can be readily adapted to consider other errors and uncertainties. The broad classes here include: use of broad wavelength bands to integrate over spectral features; scattering approximations that alter phase function and optical depths for clouds and gases; uncertainty in ice-cloud optics; treatment of fractional cloud cover including overlap; and variability of ocean surface albedo. We geographically map the errors in W m-2 using a full climate re-creation for January 2015 from a weather forecasting model. For many approximations assessed here, mean errors are ~2 W m-2 with greater latitudinal biases and are likely to affect a model’s ability to match the current climate state. Combining this work with previous studies, we make priority recommendations for fixing these simplifications based on both the magnitude of error and the ease or computational cost of the fix.