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Nicholas Siler
,
Gerard H. Roe
, and
Kyle C. Armour

Abstract

Recent studies have shown that the change in poleward energy transport under global warming is well approximated by downgradient transport of near-surface moist static energy (MSE) modulated by the spatial pattern of radiative forcing, feedbacks, and ocean heat uptake. Here we explore the implications of downgradient MSE transport for changes in the vertically integrated moisture flux and thus the zonal-mean pattern of evaporation minus precipitation (E − P). Using a conventional energy balance model that we have modified to represent the Hadley cell, we find that downgradient MSE transport implies changes in E − P that mirror those simulated by comprehensive global climate models (GCMs), including a poleward expansion of the subtropical belt where E > P, and a poleward shift in the extratropical minimum of E − P associated with the storm tracks. The surface energy budget imposes further constraints on E and P independently: E increases almost everywhere, with relatively little spatial variability, while P must increase in the deep tropics, decrease in the subtropics, and increase in middle and high latitudes. Variations in the spatial pattern of radiative forcing, feedbacks, and ocean heat uptake across GCMs modulate these basic features, accounting for much of the model spread in the zonal-mean response of E and P to climate change. Thus, the principle of downgradient energy transport appears to provide a simple explanation for the basic structure of hydrologic cycle changes in GCM simulations of global warming.

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Kevin J. Rennert
,
Gerard Roe
,
Jaakko Putkonen
, and
Cecilia M. Bitz

Abstract

Rain on snow (ROS) events are rare in most parts of the circumpolar Arctic, but have been shown to have great impact on soil surface temperatures and serve as triggers for avalanches in the midlatitudes, and they have been implicated in catastrophic die-offs of ungulates. The study of ROS is inherently challenging due to the difficulty of both measuring rain and snow in the Arctic and representing ROS events in numerical weather predictions and climate models. In this paper these challenges are addressed, and the occurrence of these events is characterized across the Arctic. Incidents of ROS in Canadian meteorological station data and in the 40-yr ECMWF Re-Analysis (ERA-40) are compared to evaluate the suitability of these datasets for characterizing ROS. The ERA-40 adequately represents the large-scale synoptic fields of ROS, but too often has a tendency toward drizzle. Using the ERA-40, a climatology of ROS events is created for thresholds that impact ungulate populations and permafrost. It is found that ROS events with the potential to harm ungulate mammals are widespread, but the large events required to impact permafrost are limited to the coastal margins of Beringia and the island of Svalbard. The synoptic conditions that led to ROS events on Banks Island in October of 2003, which killed an estimated 20 000 musk oxen, and on Svalbard, which led to significant permafrost warming in December of 1995, are examined. Compositing analyses are used to show the prevailing synoptic conditions that lead to ROS in four disparate parts of the Arctic. Analysis of ROS in the daily output of a fully coupled GCM under a future climate change scenario finds an increase in the frequency and areal extent of these events for many parts of the Arctic over the next 50 yr and that expanded regions of permafrost become vulnerable to ROS.

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Kyle C. Armour
,
Nicholas Siler
,
Aaron Donohoe
, and
Gerard H. Roe

Abstract

Meridional atmospheric heat transport (AHT) has been investigated through three broad perspectives: a dynamic perspective, linking AHT to the poleward flux of moist static energy (MSE) by atmospheric motions; an energetic perspective, linking AHT to energy input to the atmosphere by top-of-atmosphere radiation and surface heat fluxes; and a diffusive perspective, representing AHT in terms downgradient energy transport. It is shown here that the three perspectives provide complementary diagnostics of meridional AHT and its changes under greenhouse gas forcing. When combined, the energetic and diffusive perspectives offer prognostic insights: anomalous AHT is constrained to satisfy the net energetic demands of radiative forcing, radiative feedbacks, and ocean heat uptake; in turn, the meridional pattern of warming must adjust to produce those AHT changes, and does so approximately according to diffusion of anomalous MSE. The relationship between temperature and MSE exerts strong constraints on the warming pattern, favoring polar amplification. These conclusions are supported by use of a diffusive moist energy balance model (EBM) that accurately predicts zonal-mean warming and AHT changes within comprehensive general circulation models (GCMs). A dry diffusive EBM predicts similar AHT changes in order to satisfy the same energetic constraints, but does so through tropically amplified warming—at odds with the GCMs’ polar-amplified warming pattern. The results suggest that polar-amplified warming is a near-inevitable consequence of a moist, diffusive atmosphere’s response to greenhouse gas forcing. In this view, atmospheric circulations must act to satisfy net AHT as constrained by energetics.

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Xiaojuan Liu
,
David S. Battisti
, and
Gerard H. Roe

Abstract

The question “What determines the meridional heat transport (MHT)?” is explored by performing a series of rotation-rate experiments with an aquaplanet GCM coupled to a slab ocean. The change of meridional heat transport with rotation rate falls into two regimes: in a “slow rotating” regime (rotation rate < 1/2 modern rotation) MHT decreases with increasing rotation rate, whereas in a “fast rotating” regime (rotation rate ≥ 1/2 modern rotation) MHT is nearly invariant. The two-regime feature of MHT is primarily related to the reduction in tropical clouds and increase in tropical temperature that are associated with the narrowing and weakening of the Hadley cell with increasing rotation rate. In the slow-rotating regime, the Hadley cell contracts and weakens as rotation rate is increased; the resulting warming causes a local increase in outgoing longwave radiation (OLR), which consequently decreases MHT. In the fast-rotating regime, the Hadley cell continues to contract as rotation rate is increased, resulting in a decrease in tropical and subtropical clouds that increases the local absorbed shortwave radiation (ASR) by an amount that almost exactly compensates the local increases in OLR. In the fast-rotating regime, the model heat transport is approximately diffusive, with an effective eddy diffusivity that is consistent with eddy mixing-length theory. The effective eddy diffusivity decreases with increasing rotation rate. However, this decrease is nearly offset by a strong increase in the meridional gradient of moist static energy and hence results in a near-constancy of MHT. The results herein extend previous work on the MHT by highlighting that the spatial patterns of clouds and the factors that influence them are leading controls on MHT.

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John Erich Christian
,
Nicholas Siler
,
Michelle Koutnik
, and
Gerard Roe

Abstract

Glacier mass balance provides a direct indicator of a glacier’s relationship with local climate, but internally generated variability in atmospheric circulation adds a significant degree of noise to mass-balance time series, making it difficult to correctly identify and interpret trends. This study applies “dynamical adjustment” to seasonal mass-balance records to identify and remove the component of variance in these time series that is associated with large-scale circulation fluctuations (dynamical adjustment refers here to a statistical method and not a glacier’s dynamical response to climate). Mass-balance records are investigated for three glaciers: Wolverine and Gulkana in Alaska and South Cascade in Washington. North Pacific sea level pressure and sea surface temperature fields perform comparably as predictors, each explaining 50%–60% of variance in winter balance and 25%–35% in summer balance for South Cascade and Wolverine Glaciers. Gulkana Glacier, located farther inland, is less closely linked to North Pacific climate variability, with the predictors explaining roughly 30% of variance in winter and summer balance. To investigate the degree to which this variability affects trends, adjusted mass-balance time series are compared to those in the raw data, with common results for all three glaciers; winter balance trends are not significant initially and do not gain robust significance after adjustment despite the large amount of circulation-related variability. However, the raw summer balance data have statistically significant negative trends that remain after dynamical adjustment. This indicates that these trends of increasing ablation in recent decades are not due to circulation anomalies and are consistent with anthropogenic warming.

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Alison M. Anders
,
Gerard H. Roe
,
Dale R. Durran
, and
Justin R. Minder

Abstract

Persistent, 10-km-scale gradients in climatological precipitation tied to topography are documented with a finescale rain and snow gauge network in the Matheny Ridge area of the Olympic Mountains of Washington State. Precipitation totals are 50% higher on top of an ∼800-m-high ridge relative to valleys on either side, 10 km distant. Operational fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) runs on a 4-km grid produce similar precipitation patterns with enhanced precipitation over high topography for 6 water years.

The performance of the MM5 is compared to the gauge data for 3 wet seasons and for 10 large precipitation events. The cumulative MM5 precipitation forecasts for all seasons and for the sum of all 10 large events compare well with the precipitation measured by the gauges, although some of the individual events are significantly over- or underforecast. This suggests that the MM5 is reproducing the precipitation climatology in the vicinity of the gauges, but that errors for individual events may arise due to inaccurate specification of the incident flow.

A computationally simple model of orographic precipitation is shown to reproduce the major features of the event precipitation pattern on the windward side of the range. This simple model can be coupled to landscape evolution models to examine the impact of long-term spatial variability in precipitation on the evolution of topography over thousands to millions of years.

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James S. Risbey
,
Peter J. Lamb
,
Ron L. Miller
,
Michael C. Morgan
, and
Gerard H. Roe

Abstract

A set of regional climate scenarios is constructed for two study regions in North America using a combination of GCM output and synoptic–dynamical reasoning. The approach begins by describing the structure and components of a climate scenario and identifying the dynamical determinants of large-scale and regional climate. Expert judgement techniques are used to categorize the tendencies of these elements in response to increased greenhouse forcing in climate model studies. For many of the basic dynamical elements, tendencies are ambiguous, and changes in sign (magnitude, position) can usually be argued in either direction. A set of climate scenarios is produced for winter and summer, emphasizing the interrelationships among dynamical features, and adjusting GCM results on the basis of known deficiences in GCM simulations of the dynamical features. The scenarios are qualitative only, consistent with the level of precision afforded by the uncertainty in understanding of the dynamics, and in order to provide an outline of the reasoning and chain of contingencies on which the scenarios are based. The three winter scenarios outlined correspond roughly to a north–south displacement of the stationary wave pattern, to an increase in amplitude of the pattern, and to a shift in phase of the pattern. These scenarios illustrate that small changes in the dynamics can lead to large changes in regional climate in some regions, while other regions are apparently insensitive to some of the large changes in dynamics that can be plausibly hypothesized. The dynamics of summer regional climate changes are even more difficult to project, though thermodynamic considerations allow some more general conclusions to be reached in this season. Given present uncertainties it is difficult to constrain regional climate projections.

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Angeline G. Pendergrass
,
Gregory J. Hakim
,
David S. Battisti
, and
Gerard Roe

Abstract

A central issue for understanding past climates involves the use of sparse time-integrated data to recover the physical properties of the coupled climate system. This issue is explored in a simple model of the midlatitude climate system that has attributes consistent with the observed climate. A quasigeostrophic (QG) model thermally coupled to a slab ocean is used to approximate midlatitude coupled variability, and a variant of the ensemble Kalman filter is used to assimilate time-averaged observations. The dependence of reconstruction skill on coupling and thermal inertia is explored. Results from this model are compared with those for an even simpler two-variable linear stochastic model of midlatitude air–sea interaction, for which the assimilation problem can be solved semianalytically.

Results for the QG model show that skill decreases as the length of time over which observations are averaged increases in both the atmosphere and ocean when normalized against the time-averaged climatological variance. Skill in the ocean increases with slab depth, as expected from thermal inertia arguments, but skill in the atmosphere decreases. An explanation of this counterintuitive result derives from an analytical expression for the forecast error covariance in the two-variable stochastic model, which shows that the ratio of noise to total error increases with slab ocean depth. Essentially, noise becomes trapped in the atmosphere by a thermally stiffer ocean, which dominates the decrease in initial condition error owing to improved skill in the ocean.

Increasing coupling strength in the QG model yields higher skill in the atmosphere and lower skill in the ocean, as the atmosphere accesses the longer ocean memory and the ocean accesses more atmospheric high-frequency “noise.” The two-variable stochastic model fails to capture this effect, showing decreasing skill in both the atmosphere and ocean for increased coupling strength, due to an increase in the ratio of noise to the forecast error variance. Implications for the potential for data assimilation to improve climate reconstructions are discussed.

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Nathan J. Steiger
,
Gregory J. Hakim
,
Eric J. Steig
,
David S. Battisti
, and
Gerard H. Roe

Abstract

The efficacy of a novel ensemble data assimilation (DA) technique is examined in the climate field reconstruction (CFR) of surface temperature. A minimalistic, computationally inexpensive DA technique is employed that requires only a static ensemble of climatologically plausible states. Pseudoproxy experiments are performed with both general circulation model (GCM) and Twentieth Century Reanalysis (20CR) data by reconstructing surface temperature fields from a sparse network of noisy pseudoproxies. The DA approach is compared to a conventional CFR approach based on principal component analysis (PCA) for experiments on global domains. DA outperforms PCA in reconstructing global-mean temperature in all experiments and is more consistent across experiments, with a range of time series correlations of 0.69–0.94 compared to 0.19–0.87 for the PCA method. DA improvements are even more evident in spatial reconstruction skill, especially in sparsely sampled pseudoproxy regions and for 20CR experiments. It is hypothesized that DA improves spatial reconstructions because it relies on coherent, spatially local temperature patterns, which remain robust even when glacial states are used to reconstruct nonglacial states and vice versa. These local relationships, as utilized by DA, appear to be more robust than the orthogonal patterns of variability utilized by PCA. Comparing results for GCM and 20CR data indicates that pseudoproxy experiments that rely solely on GCM data may give a false impression of reconstruction skill.

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Nicholas Siler
,
Adriana Bailey
,
Gerard H. Roe
,
Christo Buizert
,
Bradley Markle
, and
David Noone

Abstract

The stable isotope ratios of oxygen and hydrogen in polar ice cores are known to record environmental change, and they have been widely used as a paleothermometer. Although it is known to be a simplification, the relationship is often explained by invoking a single condensation pathway with progressive distillation to the temperature at the location of the ice core. In reality, the physical factors are complicated, and recent studies have identified robust aspects of the hydrologic cycle’s response to climate change that could influence the isotope–temperature relationship. In this study, we introduce a new zonal-mean isotope model derived from radiative transfer theory and incorporate it into a recently developed moist energy balance climate model (MEBM), thus providing an internally consistent representation of the physical coupling between temperature, hydrology, and isotope ratios in the zonal-mean climate. The isotope model reproduces the observed pattern of meteoric δ 18O in the modern climate and allows us to evaluate the relative importance of different processes for the temporal correlation between δ 18O and temperature at high latitudes. We find that the positive temporal correlation in polar ice cores is predominantly a result of suppressed high-latitude evaporation with cooling, rather than local temperature changes. The same mechanism also explains the difference in the strength of the isotope–temperature relationship between Greenland and Antarctica.

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