Showing papers by "Clara Deser published in 2013"

The Atmospheric Response to Three Decades of Observed Arctic Sea Ice Loss

Abstract: Arctic sea ice is declining at an increasing rate with potentially important repercussions. To understand better the atmospheric changes that may have occurred in response to Arctic sea ice loss, this study presents results from atmospheric general circulation model (AGCM) experiments in which the only time-varying forcings prescribed were observed variations in Arctic sea ice and accompanying changes in Arctic sea surface temperatures from 1979 to 2009. Two independent AGCMs are utilized in order to assess the robustness of the response across different models. The results suggest that the atmospheric impacts of Arctic sea ice loss have been manifested most strongly within the maritime and coastal Arctic and in the lowermost atmosphere. Sea ice loss has driven increased energy transfer from the ocean to the atmosphere, enhanced warming and moistening of the lower troposphere, decreased the strength of the surface temperature inversion, and increased lower-tropospheric thickness; all of these chan...

A verification framework for interannual-to-decadal predictions experiments

Abstract: Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty.

The Continuum of Hydroclimate Variability in Western North America during the Last Millennium

Abstract: The distribution of climatic variance across the frequency spectrum has substantial importance for anticipating how climate will evolve in the future. Here power spectra and power laws (β) are estimated from instrumental, proxy, and climate model data to characterize the hydroclimate continuum in western North America (WNA). The significance of the estimates of spectral densities and β are tested against the null hypothesis that they reflect solely the effects of local (nonclimate) sources of autocorrelation at the monthly time scale. Although tree-ring-based hydroclimate reconstructions are generally consistent with this null hypothesis, values of β calculated from long moisture-sensitive chronologies (as opposed to reconstructions) and other types of hydroclimate proxies exceed null expectations. Therefore it may be argued that there is more low-frequency variability in hydroclimate than monthly autocorrelation alone can generate. Coupled model results archived as part of phase 5 of the Coupled ...

Characterizing decadal to centennial variability in the equatorial Pacific during the last millennium

Abstract: [1] The magnitude of sea surface temperature variability in the NINO3.4 region of the equatorial Pacific on decadal and longer timescales is assessed in observational data, state-of-the-art (Coupled Model Intercomparison Project 5) climate model simulations, and a new ensemble of paleoclimate reconstructions. On decadal to multidecadal timescales, variability in these records is consistent with the null hypothesis that it arises from “multivariate red noise” (a multivariate Ornstein-Uhlenbeck process) generated from a linear inverse model of tropical ocean-atmosphere dynamics. On centennial and longer timescales, both a last millennium simulation performed using the Community Climate System Model 4 (CCSM4) and the paleoclimate reconstructions have variability that is significantly stronger than the null hypothesis. However, the time series of the model and the reconstruction do not agree with each other. In the model, variability primarily reflects a thermodynamic response to reconstructed solar and volcanic activity, whereas in the reconstruction, variability arises from either internal climate processes, forced responses that differ from those in CCSM4, or nonclimatic proxy processes that are not yet understood. These findings imply that the response of the tropical Pacific to future forcings may be even more uncertain than portrayed by state-of-the-art models because there are potentially important sources of century-scale variability that these models do not simulate.

Uncertainty in future regional sea level rise due to internal climate variability

Abstract: [1] Sea level rise (SLR) is an inescapable consequence of increasing greenhouse gas concentrations, with potentially harmful effects on human populations in coastal and island regions. Observational evidence indicates that global sea level has risen in the 20th century, and climate models project an acceleration of this trend in the coming decades. Here we analyze rates of future SLR on regional scales in a 40-member ensemble of climate change projections with the Community Climate System Model Version 3. This unique ensemble allows us to assess uncertainty in the magnitude of 21st century SLR due to internal climate variability alone. We find that simulated regional SLR at mid-century can vary by a factor of 2 depending on location, with the North Atlantic and Pacific showing the greatest range. This uncertainty in regional SLR results primarily from internal variations in the wind-driven and buoyancy-driven ocean circulations.

The Atmospheric Response to Realistic Reduced Summer Arctic Sea Ice Anomalies

Abstract: The impact of reduced Arctic summer sea ice on the atmosphere is investigated by forcing an atmospheric general circulation model, the Community Climate Model (CCM 3.6), with observed sea ice conditions during 1995, a low-ice year. The 51 experiments, which spanned April to October of 1995, were initiated with different states from a control simulation. The 55-year control was integrated using a repeating climatological seasonal cycle of sea ice. The response was obtained from the mean difference between the experiment and control simulations. The strongest response was found during the month of August where the Arctic displays a weak local thermal response, with warmer surface air temperatures and lower sea level pressure (SLP). However, there is a significant remote response over the North Pacific characterized by an equivalent barotropic (anomalies are collocated with height and increase in magnitude) structure, with anomalous high SLP collocated with a ridge in the upper troposphere. The ice anomalies force an increase (decrease) in precipitation north of (along) the North Pacific storm track. A linear baroclinic model forced with the transient eddy vorticity fluxes, transient eddy heat fluxes, and diabatic heating separately demonstrated that transient eddy vorticity fluxes are key to maintaining the anomalous high over the North Pacific. The model's sensitivity to separately imposed ice anomalies in the Kara, Laptev-East Siberian, or Beaufort seas includes SLP, geopotential height, and precipitation changes that are similar to but weaker than the response to the full sea ice anomaly.

Uncertainty in Climate Change Projections of the Hadley Circulation: The Role of Internal Variability

Abstract: The uncertainty arising from internal climate variability in climate change projections of the Hadley circulation (HC) is presently unknown. In this paper it is quantified by analyzing a 40-member ensemble of integrations of the Community Climate System Model, version 3 (CCSM3), under the Special Report on Emissions Scenarios (SRES) A1B scenario over the period 2000‐60. An additional set of 100-yr-long timeslice integrations with the atmospheric component of the same model [Community Atmosphere Model, version 3.0 (CAM3)] is also analyzed. Focusing on simple metrics of the HC—its strength, width, and height—three key results emerge from the analysis of the CCSM3 ensemble. First, the projected weakening of the HC is almost entirely confined to the Northern Hemisphere, and is stronger in winter than in summer. Second, the projected widening of the HC occurs only in the winter season but in both hemispheres. Third, the projected rise of the tropical tropopause occurs in both hemispheres and in all seasons and is, by far, the most robust of the three metrics. This paper shows further that uncertainty in future trends of the HC width is largely controlled by extratropical variability, while those of HC strength and height are associated primarily with tropical dynamics. Comparison of the CCSM3 and CAM3 integrations reveals that ocean‐atmosphere coupling is the dominant source of uncertainty in future trends of HC strength and height and of the tropical mean meridional circulation in general. Finally, uncertainty in future trends of the hydrological cycle is largely captured by the uncertainty in future trends of the mean meridional circulation.

Climate Data Guide Spurs Discovery and Understanding

Abstract: Highly accurate and stable observations—beyond those provided by routine weather monitoring—are essential for understanding the behavior of the climate system, developing and validating Earth system models, and attributing extreme weather events and long-term trends to causes [National Research Council, 2012; Trenberth et al., 2013]. In parallel with an exploding volume of climate data, ready access to data in user-friendly formats is important to an expanding number and increasing diversity of individuals worldwide across public, private, and academic sectors [Overpeck et al., 2011].

Recent trends in Arctic sea ice and the evolving role of atmospheric circulation forcing, 1979—2007

Abstract: This study documents the evolving trends in Arctic sea ice extent and concentration during 1979―2007 and places them within the context of overlying changes in the atmospheric circulation. Results are based on 5-day running mean sea ice concentrations (SIC) from passive microwave measurements during January 1979 to October 2007. Arctic sea ice extent has retreated at all times of the year, with the largest declines (0.65 × 10 6 km 2 per decade, equivalent to 10% per decade in relative terms) from mid July to mid October. The pace of retreat has accelerated nearly threefold from the first half of the record to the second half, and the number of days with SIC less than 50% has increased by 19 since 1979. The spatial patterns of the SIC trends in the two halves of the record are distinctive, with regionally opposing trends in the first half and uniformly negative trends in the second half. In each season, these distinctive patterns correspond to the first two leading empirical orthogonal functions of SIC anomalies during 1979-2007. Atmospheric circulation trends and accompanying changes in wind-driven atmospheric thermal advection have contributed to thermodynamic forcing of the SIC trends in all seasons during the first half of the record and to those in fall and winter during the second half. Atmospheric circulation trends are weak over the record as a whole, suggesting that the long-term retreat of Arctic sea ice since 1979 in all seasons is due to factors other than wind-driven atmospheric thermal advection.

Changes in Variability Associated with Climate Change

Abstract: In this paper, we briefly discuss changes in large-scale oscillations such as the El Nino/Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the northern and southern annular modes (NAM and SAM), changes in the polar and tropical troposphere, and interactions between the stratosphere and troposphere in a changing climate. We consider both changes in variability as well as trends in the mean state. We conclude, that to fully understand how modes of variability will change in a changing climate, we need additional analysis of observations, both paleo and present day, and a solid fundamental understanding of mechanisms. Understanding of mechanisms necessarily requires use of models, ranging from simple to complex. Such models need to be fully coupled, between atmosphere and ocean, and need to include a fully resolved middle atmosphere as well.