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Yunhe Wang
,
Xiaojun Yuan
,
Haibo Bi
,
Yibin Ren
,
Yu Liang
,
Cuihua Li
, and
Xiaofeng Li

Abstract

The Arctic sea ice decline and associated change in maritime accessibility have created a pressing need for sea ice thickness (SIT) predictions. This study developed a linear Markov model for the seasonal prediction of model-assimilated SIT. It tested the performance of physically relevant predictors by a series of sensitivity tests. As measured by the anomaly correlation coefficient (ACC) and root-mean-square error (RMSE), the SIT prediction skill was evaluated in different Arctic regions and across all seasons. The results show that SIT prediction has better skill in the cold season than in the warm season. The model performs best in the Arctic basin up to 12 months in advance with ACCs of 0.7–0.8. Linear trend contributions to model skill increase with lead months. Although monthly SIT trends contribute largely to the model skill, the model remains skillful up to 2-month leads with ACCs of 0.6 for detrended SIT predictions in many Arctic regions. In addition, the Markov model’s skill generally outperforms an anomaly persistence forecast even after all trends were removed. It also shows that, apart from SIT itself, upper-ocean heat content (OHC) generally contributes more to SIT prediction skill than other variables. Sea ice concentration (SIC) is a relatively less sensitive predictor for SIT prediction skill than OHC. Moreover, the Markov model can capture the melt-to-growth season reemergence of SIT predictability and does not show a spring predictability barrier, which has previously been observed in regional dynamical model forecasts of September sea ice area, suggesting that the Markov model is an effective tool for SIT seasonal predictions.

Open access
Tiangang Yuan
,
Siyu Chen
,
Jianping Huang
,
Dongyou Wu
,
Hui Lu
,
Guolong Zhang
,
Xiaojun Ma
,
Ziqi Chen
,
Yuan Luo
, and
Xiaohui Ma

Abstract

The Weather Research and Forecasting Model coupled with chemistry (WRF-Chem) associated with in situ measurements and satellite retrievals was used to investigate the meridional transport of Taklimakan Desert (TD) dust, especially in summer. Both satellite observations and simulations reveal that TD dust particles accumulate over the Tibetan Plateau (TP) and the Tianshan Mountains in summer, resulting in higher dust concentration up to 85 μg m−3 here. The proportions of meridional transport of TD dust in summer increase up to 30% of the total output dust over the TD. Further, the impacts of thermal and dynamic forcing on the meridional transport of TD dust to the TP and Tianshan Mountains are investigated based on composite analysis and numerical modeling. It is found that the weakness of the westerly jet over East Asia significantly decreases the eastward transport of TD dust. More TD dust particles lifted to higher altitude reach up to 8 km induced by the enhanced sensible heating in summer. Under the influence of the northerly airflow over the TD regions, the TD dust particles are strengthened southward and transported to the northern slope of the TP through topographic forcing. Moreover, the cyclonic circulation raises dust particles to higher altitude over the TP. It can further intensify the TP heat source by direct radiative forcing of dust aerosols, which may have a positive feedback to the southward transport of TD dust. This research provides confidence for the investigation of the role of TP dust with regard to the radiation balance and hydrological cycle over East Asia.

Open access
Sharon Stammerjohn
,
Ted A. Scambos
,
Susheel Adusumilli
,
Sandra Barreira
,
Germar H. Bernhard
,
Deniz Bozkurt
,
Seth M. Bushinsky
,
Kyle R. Clem
,
Steve Colwell
,
Lawrence Coy
,
Jos De Laat
,
Marcel D. du Plessis
,
Ryan L. Fogt
,
Annie Foppert
,
Helen Amanda Fricker
,
Alex S. Gardner
,
Sarah T. Gille
,
Tessa Gorte
,
Bryan Johnson
,
Eric Keenan
,
Daemon Kennett
,
Linda M. Keller
,
Natalya A. Kramarova
,
Kaisa Lakkala
,
Matthew A. Lazzara
,
Jan T. M. Lenaerts
,
Jan L. Lieser
,
Zhi Li
,
Hongxing Liu
,
Craig S. Long
,
Michael MacFerrin
,
Michelle L. Maclennan
,
Robert A. Massom
,
David Mikolajczyk
,
Lynn Montgomery
,
Thomas L. Mote
,
Eric R. Nash
,
Paul A. Newman
,
Irina Petropavlovskikh
,
Michael Pitts
,
Phillip Reid
,
Steven R. Rintoul
,
Michelle L. Santee
,
Elizabeth H. Shadwick
,
Alessandro Silvano
,
Scott Stierle
,
Susan Strahan
,
Adrienne J. Sutton
,
Sebastiaan Swart
,
Veronica Tamsitt
,
Bronte Tilbrook
,
Lei Wang
,
Nancy L. Williams
, and
Xiaojun Yuan
Free access