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Zili Shen
,
Anmin Duan
,
Wen Zhou
,
Yuzhuo Peng
, and
Jinxiao Li

Abstract

Two large ensemble simulations are adopted to investigate the relative contribution of external forcing and internal variability to Arctic sea ice variability on different time scales since 1960 by correcting the response error of models to external forcing using observational datasets. Our study suggests that previous approaches might overestimate the real impact of internal variability on Arctic sea ice change especially on long time scales. Our results indicate that in both March and September, internal variability plays a dominant role on all time scales over the twentieth century, while the anthropogenic signal on sea ice change can be steadily and consistently detected on a time scale of more than 20 years after the 2000s. We also reveal that the dominant mode of internal variability in March shows consistency across different time scales. On the contrary, the pattern of internal variability in September is highly nonuniform over the Arctic and varies across different time scales, indicating that sea ice internal variability in September at different time scales is driven by different factors.

Open access
Free access
Veeshan Narinesingh
,
Huan Guo
,
Stephen T. Garner
, and
Yi Ming

Abstract

Coupled ocean and prescribed sea surface temperature (SST) experiments are performed to investigate the drivers of Northern Hemisphere (NH) midlatitude winter circulation and blocking changes in warmer climates. In coupled experiments, a historical simulation is compared to a simulation following an end of the 21st century SSP5-8.5 emissions scenario. The SSP5-8.5 simulation yields poleward shifted jets and an enhanced stationary wave pattern compared to the historical simulation. In terms of blocking, a reduction is found across North America and over the Pacific Ocean with suggestion of more blocking over parts of Eurasia. Separately, prescribed SST experiments are performed decomposing the SSP5-8.5 SST response into a uniform warming component plus a spatially dependent change in SST pattern. SSP5-8.5 changes in circulation are primarily driven by a uniform warming of SST. Uniform warming is also found to account for most of the SSP5-8.5 blocking reduction over North America and the Pacific Ocean, but not over Eurasia. El Niño like changes to the SST pattern also yield less blocking over the Pacific and North America. However, adding the responses of uniform and pattern experiments yields a non-linear overreduction of blocking compared to the SSP5-8.5 experiment. Regional analyses of block energetics suggest that much of the reductions in blocking in warming simulations are driven by decreased baroclinic conversion in some regions and enhanced dissipation from diabatic sources in others.

Open access
Alex J. Cannon
,
Dae-Il Jeong
, and
Ka-Hing Yau

Abstract

Global warming is expected to lead to increases in atmospheric moisture and intensify subhourly to hourly rainfall extremes. However, signal-to-noise ratios are low, especially at the local scale, making detection of changes in the observational record difficult. For Canada, previous studies based on short data records from 1965 to 2005 did not show conclusive evidence of increases in short-duration extreme rainfall. This study updates single-site and regional trend analyses of 5-min–24-h annual maximum rainfall in Canada using data from 1950 to 2021. Estimates of temporal trends are extended to also consider the association between rainfall intensity and dewpoint temperature, a measure of moisture availability. With longer records, evidence for increases in extreme rainfall at individual sites is stronger. Field significant increasing trends are found for the majority of durations, whereas before results were mixed and typically not statistically significant. Intensification is even more pronounced in single-site scaling of rainfall intensity with summer mean dewpoint temperature. Field significant positive scaling rates are detected for all durations. When data are pooled in space—irrespective of choice of regionalization—the results are even more clear. Notably, the strongest and most spatially homogeneous intensification of short-duration extreme rainfall is detected in subhourly to 2-h durations. When data are pooled across Canadian climate regions, field significant positive scaling is found in 72.7%–81.8% of regions for 5-min–2-h durations, with median scaling rates ranging from 5.3% to 9.4% °C−1. For durations ≥ 6 h, this falls to 27.3%–53% of regions, with scaling rates less than 4% °C−1.

Open access
Stephanie Hay
and
Paul J. Kushner

Abstract

The response to Antarctic sea ice loss within a coupled modeling framework is examined in comparison to the response to Arctic sea ice loss and within the context of general greenhouse warming. Sea ice loss responses are found to be linear (particularly in response to Antarctic or global sea ice loss) with respect to the degree of imposed perturbation and additive when perturbations are applied in hemispheres separately and concurrently. Globally, and in the tropical Pacific in particular, Antarctic sea ice loss plays a relatively larger role than Arctic sea ice loss in both the atmosphere and the ocean, within the parameters of our experiments. The pattern of response to Antarctic sea ice loss is also found to more closely resemble that of greenhouse warming, again particularly in the tropics. An extension to multiparameter pattern scaling is developed to include a scaling factor for Antarctic change in addition to those for tropical warming and Arctic sea ice loss. The decomposition is applied to the modeled response to Antarctic sea ice loss to break it down into component partial responses that scale with Antarctic, tropical, and Arctic changes. This reveals the aspects of the response that are directly related to Antarctic change, such as an equatorward intensification of tropical precipitation in the Northern Hemisphere, and those that are modified via the induced changes in the tropics and Arctic, such as Northern Hemisphere temperature change. With this, we hope to gain a deeper understanding of the role of each of these changes for the development of physical mechanisms of the response.

Open access
Free access
Clark Weaver
,
Dong L. Wu
,
P. K. Bhartia
,
Gordon Labow
,
David P. Haffner
,
Lauren Borgia
,
Laura McBride
, and
Ross Salawitch

Abstract

We construct a long-term record of top of atmosphere (TOA) shortwave (SW) albedo of clouds and aerosols from 340-nm radiances observed by NASA and NOAA satellite instruments from 1980 to 2013. We compare our SW cloud+aerosol albedo with simulated cloud albedo from both AMIP and historical CMIP6 simulations from 47 climate models. While most historical runs did not simulate our observed spatial pattern of the trends in albedo over the Pacific Ocean, four models qualitatively simulate our observed patterns. Those historical models and the AMIP models collectively estimate an equilibrium climate sensitivity (ECS) of ∼3.5°C, with an uncertainty from 2.7° to 5.1°C. Our ECS estimates are sensitive to the instrument calibration, which drives the wide range in ECS uncertainty. We use instrument calibrations that assume a neutral change in reflectivity over the Antarctic ice sheet. Our observations show increasing cloudiness over the eastern equatorial Pacific and off the coast of Peru as well as neutral cloud trends off the coast of Namibia and California. To produce our SW cloud+aerosol albedo, we first retrieve a black-sky cloud albedo (BCA) and empirically correct the sampling bias from diurnal variations. Then, we estimate the broadband proxy albedo using multiple nonlinear regression along with several years of CERES cloud albedo to obtain the regression coefficients. We validate our product against CERES data from the years not used in the regression. Zonal mean trends of our SW cloud+aerosol albedo show reasonable agreement with CERES as well as the Pathfinder Atmospheres–Extended (PATMOS-x) observational dataset.

Significance Statement

Equilibrium climate sensitivity is a measure of the rise in global temperature over hundreds of years after a doubling of atmospheric CO2 concentration. Current state-of-the-art climate models forecast a wide range of equilibrium climate sensitivities (1.5°–6°C), due mainly to how clouds, aerosols, and sea surface temperatures are simulated within these models. Using data from NASA and NOAA satellite instruments from 1980 to 2013, we first construct a dataset that describes how much sunlight has been reflected by clouds over the 34 years and then we compare this data record to output from 47 climate models. Based on these comparisons, we conclude the best estimate of equilibrium climate sensitivity is about 3.5°C, with an uncertainty range of 2.7°–5.1°C.

Open access
B. I. Moat
,
B. Sinha
,
D. I. Berry
,
S. S. Drijfhout
,
N. Fraser
,
L. Hermanson
,
D. C. Jones
,
S. A. Josey
,
B. King
,
C. Macintosh
,
A. Megann
,
M. Oltmanns
,
R. Sanders
, and
S. Williams

Abstract

We construct an upper ocean (0-1000m) North Atlantic heat budget (26°-67°N) for the period 1950-2020 using multiple observational datasets and an eddy-permitting global ocean model. On multidecadal timescales ocean heat transport convergence controls ocean heat content (OHC) tendency in most regions of the North Atlantic with little role for diffusive processes. In the subpolar North Atlantic (45°N-67°N) heat transport convergence is explained by geostrophic currents whereas ageostrophic currents make a significant contribution in the subtropics (26°N-45°N). The geostrophic contribution in all regions is dominated by anomalous advection across the time-mean temperature gradient although other processes make a significant contribution particularly in the subtropics. The timescale and spatial distribution of the anomalous geostrophic currents are consistent with a simple model of basin scale thermal Rossby waves propagating westwards/northwestwards in the subpolar gyre and multidecadal variations in regional OHC are explained by geostrophic currents periodically coming into alignment with the mean temperature gradient as the Rossby wave passes through. The global ocean model simulation shows that multidecadal variations in the Atlantic Meridional Overturning Circulation are synchronized with the ocean heat transport convergence consistent with modulation of the west-east pressure gradient by the propagating Rossby wave.

Open access
Free access
Elena Saggioro
,
Theodore G. Shepherd
, and
Jeff Knight

Abstract

Skillful prediction of the Southern Hemisphere (SH) eddy-driven jet is crucial for representation of mid-to-high-latitude SH climate variability. In the austral spring-to-summer months, the jet and the stratospheric polar vortex variabilities are strongly coupled. Since the vortex is more predictable and influenced by long-lead drivers 1 month or more ahead, the stratosphere is considered a promising pathway for improving forecasts in the region on subseasonal to seasonal (S2S) time scales. However, a quantification of this predictability has been lacking, as most modeling studies address only one of the several interacting drivers at a time, while statistical analyses quantify association but not skill. This methodological gap is addressed through a knowledge-driven probabilistic causal network approach, quantified with seasonal ensemble hindcast data. The approach enables to quantify the jet’s long-range predictability arising from known late-winter drivers, namely, El Niño–Southern Oscillation (ENSO), Indian Ocean dipole (IOD), upward wave activity flux, and polar night jet oscillation, mediated by the vortex variability in spring. Network-based predictions confirm the vortex as determinant for skillful jet predictions, both for the jet’s poleward shift in late spring and its equatorward shift in early summer. ENSO, IOD, late-winter wave activity flux, and polar night jet oscillation only provide moderate prediction skill to the vortex. This points to early spring submonthly variability as important for determining the vortex state leading up to its breakdown, creating a predictability bottleneck for the jet. The method developed here offers a new avenue to quantify the predictability provided by multiple, interacting drivers on S2S time scales.

Significance Statement

Predictions of the Southern Hemisphere midlatitude jet stream are crucial for skillful forecasts of the austral mid-to-high latitudes. Several oceanic and atmospheric phenomena could, if better represented in models, improve spring-to-summer jet predictions on subseasonal to seasonal time scales. However, the combined potential skill arising from the inclusion of such phenomena has not been quantified. This study does so by using a probabilistic causal network model, representing the connections between those drivers and the jet with conditional probabilities, trained on large sets of model data. The stratospheric polar vortex is confirmed as crucial predictor of jet variability but is itself hard to predict a month in advance due to submonthly variability, creating a predictability bottleneck for the jet.

Open access