scholarly journals Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community Atmosphere Model

2021 ◽  
Author(s):  
Siyu Zhao ◽  
Jiaying Zhang ◽  
Yi Deng ◽  
Na Wang
Keyword(s):  
Atlantic Multidecadal Oscillation ◽  
Daily Basis ◽  
Arctic Sea Ice ◽  
Radiative Processes ◽  
The Past ◽  
Community Atmosphere Model ◽  
Arctic Sea ◽  
Sst Warming ◽  
Concentration Changes ◽  
Atmosphere Model

Abstract The past four decades have seen an increase of terrestrial hot extremes during summer in the northern extratropics, accompanied by the Northern Hemisphere (NH) sea surface temperature (SST) warming (mainly over 10°–70°N, 0°–360°) and CO2 concentration rising. This study aims to understand possible causes for the increasing hot extremes, which are defined on a daily basis. We conduct a series of numerical experiments using the Community Atmosphere Model version 5 model for two periods, 1979–1995 and 2002–2018. The experiment by changing the CO2 concentration only with the climatological SST shows less increase of hot extremes days than that observed, whereas that by changing the NH SST (over 10°–70°N, 0°–360°) with constant CO2 concentration strengthens the hot extremes change over mid-latitudes. The experiment with both SST and CO2 concentration changes shows hot extremes change closer to the observation compared to the single-change experiments, as well as more similar simulations of atmospheric circulations and feedbacks from cloud and radiative processes. Also discussed are roles of natural variability (e.g., Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation) and other factors (e.g., Arctic sea ice and tropical SST).

Atmospheric impacts of an Arctic sea ice minimum as seen in the Community Atmosphere Model

2013 ◽  
Vol 34 (3) ◽  
pp. 766-779 ◽  
Author(s):  
Elizabeth N. Cassano ◽  
John J. Cassano ◽  
Matthew E. Higgins ◽  
Mark C. Serreze
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Community Atmosphere Model ◽  
Arctic Sea ◽  
Atmosphere Model

Assessment of the Regional Arctic System Model Intra-Annual Ensemble Predictions of Arctic Sea Ice

2020 ◽  
Author(s):  
Wieslaw Maslowski ◽  
Younjoo Lee ◽  
Anthony Craig ◽  
Mark Seefeldt ◽  
Robert Osinski ◽  
...  
Keyword(s):  
Sea Ice ◽  
Time Scales ◽  
Weather Prediction ◽  
Arctic Sea Ice ◽  
System Model ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Ensemble Forecasts ◽  
The Past ◽  
Arctic Sea

<p>The Regional Arctic System Model (RASM) has been developed and used to investigate the past to present evolution of the Arctic climate system and to address increasing demands for Arctic forecasts beyond synoptic time scales. RASM is a fully coupled ice-ocean-atmosphere-land hydrology model configured over the pan-Arctic domain with horizontal resolution of 50 km or 25 km for the atmosphere and land and 9.3 km or 2.4 km for the ocean and sea ice components. As a regional model, RASM requires boundary conditions along its lateral boundaries and in the upper atmosphere, which for simulations of the past to present are derived from global atmospheric reanalyses, such as the National Center for Environmental Predictions (NCEP) Coupled Forecast System version 2 and Reanalysis (CFSv2/CFSR). This dynamical downscaling approach allows comparison of RASM results with observations, in place and time, to diagnose and reduce model biases. This in turn allows a unique capability not available in global weather prediction and Earth system models to produce realistic and physically consistent initial conditions for prediction without data assimilation.</p><p>More recently, we have developed a new capability for an intra-annual (up to 6 months) ensemble prediction of the Arctic sea ice and climate using RASM forced with the routinely produced (every 6 hours) NCEP CFSv2 global 9-month forecasts. RASM intra-annual ensemble forecasts have been initialized on the 1<sup>st</sup> of each month starting in 2019 with forcing for each ensemble member derived from CSFv2 forecasts, 24-hr apart from the month preceding the initial forecast date.  Several key processes and feedbacks will be discussed with regard to their impact on model physics, the representation of initial state and ensemble prediction skill of Arctic sea ice variability at time scales from synoptic to decadal. The skill of RASM ensemble forecasts will be assessed against available satellite observations with reference to reanalysis as well as hindcast data using several metrics, including the standard deviation, root mean square difference, Taylor diagrams and integrated ice-edge error.</p>

scholarly journals How does sea ice influence δ<sup>18</sup>O of Arctic precipitation?

2016 ◽  
Author(s):  
Anne-Katrine Faber ◽  
Bo Møllesøe Vinther ◽  
Jesper Sjolte ◽  
Rasmus Anker Pedersen
Keyword(s):  
Sea Ice ◽  
Ice Cover ◽  
Research Community ◽  
Arctic Sea Ice ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Atmospheric Research ◽  
Community Atmosphere Model ◽  
Arctic Sea ◽  
Ice Concentration

Abstract. This study investigates how variations in Arctic sea ice cover influence δ18O of presentday Arctic precipitation. This is done using the model isoCAM3, an isotope-equipped version of the National Center for Atmospheric Research Community Atmosphere Model version 3. Four sensitivity experiments and one control simulation are performed with prescribed SSTs and sea ice. Each of 5 the four experiments simulates the atmospheric and isotopic response to Arctic oceanic conditions for selected years after the beginning of the satellite era in 1979. Results show that δ18O of precipitation is sensitive to local changes of sea ice concentration. Reduced sea ice extent yields more enriched isotope values while increased sea ice extent yields more depleted isotope values. The configuration of the sea ice cover is essential for the spatial distribution 10 of the simulated changes in δ18O. The experiments of this study show no changes of δ18O for central Greenland. However, this does not exclude that simulations based on other sea ice configurations might yield changes in Greenland δ18O.

Changes in Lake Area in the Inner Mongolian Plateau under Climate Change: The Role of the Atlantic Multidecadal Oscillation and Arctic Sea Ice

2020 ◽  
Vol 33 (4) ◽  
pp. 1335-1349
Author(s):  
Yong Liu ◽  
Huopo Chen ◽  
Guoqing Zhang ◽  
Jianqi Sun ◽  
Hua Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Summer Precipitation ◽  
Atlantic Multidecadal Oscillation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Lake Area ◽  
Mongolian Plateau ◽  
Arctic Sea

AbstractThe lake area in the Inner Mongolian Plateau (IMP) has experienced a rapid reduction in recent decades. Previous studies have highlighted the important role of intensive human activities in IMP lake shrinkage. However, this study found that climate change–induced summer precipitation variations can exert great influences on the IMP lake area variations. The results suggest that the decadal shift in the IMP summer precipitation may be the predominant contributor to lake shrinkage. Further analysis reveals that the Atlantic multidecadal oscillation (AMO) and Arctic sea ice concentration (SIC) play important roles in the IMP summer precipitation variations. The AMO seems to provide beneficial large-scale circulation fields for the decadal variations in the IMP summer precipitation, and the Arctic SIC decline is favorable for weakening the IMP summer precipitation intensity after the late 1990s. Evidence indicates that the vorticity advection related to the Arctic SIC decline can result in the generation of Rossby wave resources in the midlatitudes. Then, the strengthened wave resources become favorable for enhancing the stationary wave propagation across Eurasia and inducing cyclonic circulation over the Mongolia–Baikal regions, which might bring more rainfall northward and weaken the IMP summer precipitation intensity. Consequently, due to the decreased rainfall and gradual warming after the late 1990s, the lake area in the IMP has experienced a downward trend in recent years.

scholarly journals Constraining Uncertainties in CMIP5 Projections of September Arctic Sea Ice Extent with Observations

2020 ◽  
Vol 33 (4) ◽  
pp. 1487-1503 ◽  
Author(s):  
Daniel Senftleben ◽  
Axel Lauer ◽  
Alexey Karpechko
Keyword(s):  
Sea Ice ◽  
Model Uncertainty ◽  
Coupled Model ◽  
Internal Variability ◽  
Arctic Sea Ice ◽  
Mitigation Strategies ◽  
Sea Ice Extent ◽  
The Past ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

AbstractIn agreement with observations, Earth system models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulate a decline in September Arctic sea ice extent (SIE) over the past decades. However, the spread in their twenty-first-century SIE projections is large and the timing of the first ice-free Arctic summer ranges from 2020 to beyond 2100. The uncertainties arise from three sources (internal variability, model uncertainty, and scenario uncertainty), which are quantified in this study for projections of SIE. The goal is to narrow uncertainties by applying multiple diagnostic ensemble regression (MDER). MDER links future projections of sea ice extent to processes relevant to its simulation under present-day conditions using data covering the past 40 years. With this method, we can reduce model uncertainty in projections of SIE for the period 2020–44 by 30%–50% (0.8–1.3 million km2). Compared to the unweighted multimodel mean, the MDER-weighted mean projects an about 20% smaller SIE and an earlier near-disappearance of Arctic sea ice by more than a decade for a high–greenhouse gas scenario. We also show that two different methods estimating internal variability in SIE differ by 1 million km2. Regardless, the total uncertainties in the SIE projections remain large (up to 3.5 million km2, with irreducible internal variability contributing 30%) so that a precise time estimate of an ice-free Arctic proves impossible. We conclude that unweighted CMIP5 multimodel-mean projections of Arctic SIE are too optimistic and mitigation strategies to reduce Arctic warming need to be intensified.

Reconstructed changes in Arctic sea ice over the past 1,450 years

Nature ◽  
2011 ◽  
Vol 479 (7374) ◽  
pp. 509-512 ◽  
Author(s):  
Christophe Kinnard ◽  
Christian M. Zdanowicz ◽  
David A. Fisher ◽  
Elisabeth Isaksson ◽  
Anne de Vernal ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Past ◽  
Arctic Sea

scholarly journals A recent weakening of winter temperature association between Arctic and Asia

2022 ◽  
Author(s):  
Bingyi Wu ◽  
Zhenkun Li ◽  
Jennifer A. Francis ◽  
Shuoyi Ding
Keyword(s):  
Sea Ice ◽  
Phase Ii ◽  
Arctic Sea Ice ◽  
Winter Temperature ◽  
The Arctic ◽  
Arctic Warming ◽  
The Past ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss ◽  
Over Time

Abstract Arctic warming and its association with the mid-latitudes have been hot topic over the past two decades. Although many studies have explored these issues it is not clear that how their linkage has changed over time. The results show that winter low tropospheric temperatures in Asia experienced two phases over the past two decades. Phase I (2007/2008 to 2012/2013) was characterized by a warm Arctic and cold Eurasia, and phase II by a warm Arctic and warm Eurasia (2013/2014 to 2018/2019). A strengthened association in winter temperature between the Arctic and Asia occurred during phase I, followed by a weakened linkage during phase II. Simulation experiments forced by observed Arctic sea ice variability largely reproduce observed patterns, suggesting that Arctic sea ice loss contributes to phasic (or low-frequency) variations in winter atmosphere and make the Arctic-Asia temperature association fluctuate over time. The weakening of the Arctic-Asia linkage post-2012/2013 was associated with amplified and expanded Arctic warming. The corresponding anomalies in SLP resembled a positive phase North Atlantic Oscillation (NAO) during phase II. This study implies that the phasic warm Arctic-cold Eurasia and warm Arctic-warm Eurasia patterns would alternately happen in the context of Arctic sea ice loss, which increase the difficulty to correctly predict Asian winter temperature.

scholarly journals A fully coupled Arctic sea ice-ocean-atmosphere model (ArcIOAM v1.0) based on C-Coupler2: model description and preliminary results

2020 ◽  
Author(s):  
Shihe Ren ◽  
Xi Liang ◽  
Qizhen Sun ◽  
Hao Yu ◽  
L. Bruno Tremblay ◽  
...  
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Model Description ◽  
Preliminary Results ◽  
Comparison Results ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Atmosphere Model

Abstract. The implementation of a new Arctic regional coupled sea ice-ocean-atmosphere model (ArcIOAM) and its preliminary results in the year of 2012 are presented in this paper. A newly developed coupler, C-Coupler2 (the Community Coupler 2), is used to couple the Arctic sea ice-oceanic configuration of the MITgcm (Massachusetts Institute of Technology general circulation model) with the Arctic atmospheric configuration of the Polar WRF (Weather Research and Forecasting) model. ArcIOAM is demonstrated with focus on seasonal simulation of the Arctic sea ice and ocean state in the year of 2012. The results obtained by ArcIOAM, along with the experiment of one-way coupling strategy, are compared with available observational data and reanalysis products. From the comparison, results obtained from two experiments both realistically capture the sea ice and oceanic variables in the Arctic region over a 1-year simulation period. The two-way coupled model has better performance in terms of sea ice extent, concentration, thickness and SST, especially in summer. This indicates that sea ice-ocean-atmosphere interaction takes a crucial role in controlling Arctic summertime sea ice distribution. The coupled model and documentation are available at  https://doi.org/10.5281/zenodo.3742692 (last access: 9 June 2020), and the source code is maintained at  https://github.com/cdmpbp123/Coupled_Atm_Ice_Oce (last access: 7 April 2020).

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