Reduction of internal climate variability in surface temperature due to sea-ice loss since the mid-21st century

2017 ◽  
Vol 37 (15) ◽  
pp. 5211-5216
Author(s):  
Seung-Hwon Hyun ◽  
Sang-Wook Yeh ◽  
Jinho Yoon
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Surface Temperature ◽  
21St Century ◽  
Internal Climate Variability

scholarly journals Elusive drought: uncertainty in observed trends and short- and long-term CMIP5 projections

2012 ◽  
Vol 9 (12) ◽  
pp. 13773-13803 ◽  
Author(s):  
B. Orlowsky ◽  
S. I. Seneviratne
Keyword(s):  
South Africa ◽  
Soil Moisture ◽  
Climate Variability ◽  
Central America ◽  
21St Century ◽  
Economic Losses ◽  
Drought Risk ◽  
Dominant Source ◽  
Internal Climate Variability ◽  
The Mediterranean

Abstract. Recent years have seen a number of severe droughts in different regions around the world, causing agricultural and economic losses, famines and migration. Despite their devastating consequences, the Standardised Precipitation Index (SPI) of these events lies within the range of internal climate variability, which we estimate from simulations from the 5th phase of the Coupled Model Intercomparison Project (CMIP5). In terms of drought magnitude, regional trends of SPI over the last decades remain mostly inconclusive in observations and CMIP5 simulations, although Soil Moisture Anomalies (SMAs) in CMIP5 simulations hint at increased drought in a few regions (e.g. the Mediterranean, Central America/Mexico, the Amazon, North-East Brazil and South Africa). Also for the future, projections of meteorological (SPI) and agricultural (SMA) drought in CMIP5 display large uncertainties over all time frames, generally impeding trend detection. Analogue analyses of the frequencies rather than magnitudes of future drought display, however, more robust signal-to-noise ratios with detectable trends towards more frequent drought until the end of the 21st century in the Mediterranean, South Africa and Central America/Mexico. Other present-day hot spots are projected to become less drought-prone, or to display unsignificant changes in drought occurrence. A separation of different sources of uncertainty in drought projections reveals that for the near term, internal climate variability is the dominant source, while the formulation of Global Climate Models (GCMs) generally becomes the dominant source of uncertainty by the end of the 21st century, especially for agricultural (soil moisture) drought. In comparison, the uncertainty in Green-House Gas (GHG) concentrations scenarios is negligible for most regions. These findings stand in contrast to respective analyses for a heat wave indicator, for which GHG concentrations scenarios constitute the main source of uncertainty. Our results highlight the inherent difficulty of drought quantification and the uncertainty of drought projections. However, high uncertainty should not be equated with low drought risk, since potential scenarios include large drought increases in key agricultural and ecosystem regions.

Observed statistical connections overestimate the causal effects of Arctic sea-ice changes on midlatitude winter climate

2021 ◽  
pp. 1-46
Author(s):  
Russell Blackport ◽  
James A. Screen
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Surface Temperature ◽  
Kara Sea ◽  
Arctic Sea Ice ◽  
Causal Effects ◽  
Coupled Models ◽  
Stratospheric Polar Vortex ◽  
Winter Climate ◽  
Arctic Sea

AbstractDisentangling the contribution of changing Arctic sea ice to midlatitude winter climate variability remains challenging because of the large internal climate variability in midlatitudes, difficulties separating cause from effect, methodological differences, and uncertainty around whether models adequately simulate connections between Arctic sea ice and midlatitude climate. We use regression analysis to quantify the links between Arctic sea ice and midlatitude winter climate in observations and large initial-condition ensembles of multiple climate models, in both coupled configurations and so-called atmospheric model intercomparison project (AMIP) configurations, where observed sea ice and/or sea surface temperatures are prescribed. The coupled models capture the observed links in interannual variability between winter Barents-Kara sea ice and Eurasian surface temperature, and between winter Chukchi-Bering sea ice and North American surface temperature. The coupled models also capture the delayed connection between reduced November-December Barents-Kara sea ice, a weakened winter stratospheric polar vortex, and a shift towards the negative phase of the North Atlantic Oscillation in late winter, although this downward impact is weaker than observed. The strength and sign of the connections both vary considerably between individual 35-year-long ensemble members, highlighting the need for large ensembles to separate robust connections from internal variability. All the aforementioned links are either absent, or substantially weaker, in the AMIP experiments prescribed with only observed sea ice variability. We conclude that the causal effects of sea ice variability on midlatitude winter climate are much weaker than suggested by statistical associations, evident in observations and coupled models, because the statistics are inflated by the effects of atmospheric circulation variability on sea ice.

Role of the internal climate variability in the atmospheric response to a sudden summer Arctic sea ice loss

2021 ◽  
Author(s):  
Steve Delhaye ◽  
Thierry Fichefet ◽  
François Massonnet ◽  
David Docquier ◽  
Christopher Roberts ◽  
...  
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Signal To Noise Ratio ◽  
Horizontal Resolution ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
Signal To Noise ◽  
Internal Climate Variability ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

<p>The retreat of Arctic sea ice for the last four decades is a primary manifestation of the climate system response to increasing atmospheric greenhouse gas concentrations. This retreat is frequently considered as a possible driver of atmospheric circulation anomalies at mid-latitudes. However, the year-to-year evolution of the Arctic sea ice cover is also characterized by significant fluctuations attributed to internal climate variability. It is unclear how the atmosphere will respond to a near-total retreat of summer Arctic sea ice, a reality that might occur in the foreseeable future. This study uses sensitivity experiments  with higher and lower horizontal resolution configurations of three global coupled climate models to investigate the local and remote atmospheric responses to a reduction in Arctic sea ice cover during the preceding summer. Recognizing that these responses likely depend on the model itself and on its horizontal resolution, and that the model’s internally-generated climate variability may obscure the atmospheric response, we design a protocol to compare each source separately. After imposing a 15-month albedo perturbation resulting in a sudden summer Arctic sea ice loss, the remote mid-latitude climate response has a very low signal-to-noise ratio such that internal climate variability dominates the uncertainty of the response, regardless of the atmospheric variable. Indeed, more than 28, 165 and 210 members are needed to detect a robust response in surface air temperature, precipitation and sea level pressure to sea ice loss in Europe, respectively. Finally, we find that horizontal resolution plays a secondary role in the uncertainty of the atmospheric response to substantial perturbation of Arctic sea ice. These findings suggest that even with higher resolution model configurations, it is important to have large ensemble sizes to increase the signal to noise ratio for the mid-latitude atmospheric response to sea ice changes.</p>

Decadal modulation of global surface temperature by internal climate variability

2015 ◽  
Vol 5 (6) ◽  
pp. 555-559 ◽  
Author(s):  
Aiguo Dai ◽  
John C. Fyfe ◽  
Shang-Ping Xie ◽  
Xingang Dai
Keyword(s):  
Climate Variability ◽  
Surface Temperature ◽  
Internal Climate Variability ◽  
Global Surface Temperature ◽  
Decadal Modulation ◽  
Global Surface

scholarly journals Comparison of Low-Frequency Internal Climate Variability in CMIP5 Models and Observations

2017 ◽  
Vol 30 (12) ◽  
pp. 4763-4776 ◽  
Author(s):  
Anson H. Cheung ◽  
Michael E. Mann ◽  
Byron A. Steinman ◽  
Leela M. Frankcombe ◽  
Matthew H. England ◽  
...  
Keyword(s):  
Climate Variability ◽  
Surface Temperature ◽  
Time Scales ◽  
Linear Regression Analysis ◽  
Low Frequency ◽  
Semiempirical Method ◽  
Cmip5 Models ◽  
Instrumental Data ◽  
Internal Climate Variability ◽  
Instrumental Record

Low-frequency internal climate variability (ICV) plays an important role in modulating global surface temperature, regional climate, and climate extremes. However, it has not been completely characterized in the instrumental record and in the Coupled Model Intercomparison Project phase 5 (CMIP5) model ensemble. In this study, the surface temperature ICV of the North Pacific (NP), North Atlantic (NA), and Northern Hemisphere (NH) in the instrumental record and historical CMIP5 all-forcing simulations is isolated using a semiempirical method wherein the CMIP5 ensemble mean is applied as the external forcing signal and removed from each time series. Comparison of ICV signals derived from this semiempirical method as well as from analysis of ICV in CMIP5 preindustrial control runs reveals disagreement in the spatial pattern and amplitude between models and instrumental data on multidecadal time scales (>20 yr). Analysis of the amplitude of total variability and the ICV in the models and instrumental data indicates that the models underestimate ICV amplitude on low-frequency time scales (>20 yr in the NA; >40 yr in the NP), while agreement is found in the NH variability. A multiple linear regression analysis of ICV in the instrumental record shows that variability in the NP drives decadal-to-interdecadal variability in the NH, whereas the NA drives multidecadal variability in the NH. Analysis of the CMIP5 historical simulations does not reveal such a relationship, indicating model limitations in simulating ICV. These findings demonstrate the need to better characterize low-frequency ICV, which may help improve attribution and decadal prediction.

scholarly journals Consistently Estimating Internal Climate Variability from Climate Model Simulations

2017 ◽  
Vol 30 (23) ◽  
pp. 9555-9573 ◽  
Author(s):  
Dirk Olonscheck ◽  
Dirk Notz
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Arctic Sea Ice ◽  
New Method ◽  
Polar Regions ◽  
Internal Climate Variability ◽  
Ensemble Simulations

This paper introduces and applies a new method to consistently estimate internal climate variability for all models within a multimodel ensemble. The method regresses each model’s estimate of internal variability from the preindustrial control simulation on the variability derived from a model’s ensemble simulations, thus providing practical evidence of the quasi-ergodic assumption. The method allows one to test in a multimodel consensus view how the internal variability of a variable changes for different forcing scenarios. Applying the method to the CMIP5 model ensemble shows that the internal variability of global-mean surface air temperature remains largely unchanged for historical simulations and might decrease for future simulations with a large CO2 forcing. Regionally, the projected changes reveal likely increases in temperature variability in the tropics, subtropics, and polar regions, and extremely likely decreases in midlatitudes. Applying the method to sea ice volume and area shows that their respective internal variability likely or extremely likely decreases proportionally to their mean state, except for Arctic sea ice area, which shows no consistent change across models. For the evaluation of CMIP5 simulations of Arctic and Antarctic sea ice, the method confirms that internal variability can explain most of the models’ deviation from observed trends but often not the models’ deviation from the observed mean states. The new method benefits from a large number of models and long preindustrial control simulations, but it requires only a small number of ensemble simulations. The method allows for consistent consideration of internal variability in multimodel studies and thus fosters understanding of the role of internal variability in a changing climate.

scholarly journals The Recent Decline of the Arctic Summer Sea-Ice Cover in the Context of Internal Climate Variability

2008 ◽  
Vol 2 (1) ◽  
pp. 91-100 ◽  
Author(s):  
W. Dorn ◽  
K. Dethloff ◽  
A. Rinke ◽  
M. Kurgansky
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Interannual Variability ◽  
Arctic Basin ◽  
Ice Cover ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Internal Climate Variability ◽  
Arctic Summer

By means of a 21-year simulation of a coupled regional pan-Arctic atmosphere-ocean-ice model for the 1980's and 1990's and comparison of the model results with SSM/I satellite-derived sea-ice concentrations, the patterns of maximum amplitude of interannual variability of the Arctic summer sea-ice cover are revealed. They are shown to concentrate beyond an area enclosed by an isopleth of barotropic planetary potential vorticity that marks the edge of the cyclonic rim current around the deep inner Arctic basin. It is argued that the propagation of the interannual variability signal farther into the inner Arctic basin is hindered by the dynamic isolation of upper Arctic Ocean and the high summer cloudiness usually appearing in the central Arctic. The thinning of the Arctic sea-ice cover in recent years is likely to be jointly responsible for its exceptionally strong decrease in summer 2007 when sea-ice decline was favored by anomalously high atmospheric pressure over the western Arctic Ocean, which can be regarded as a typical feature for years with low sea-ice extent. In addition, unusually low cloud cover appeared in summer 2007, which led to substantial warming of the upper ocean. It is hypothesized that the coincidence of several favorable factors for low sea-ice extent is responsible for this extreme event. Owing to the important role of internal climate variability in the recent decline of sea ice, a temporal return to previous conditions or stabilization at the current level can not be excluded just as further decline.

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