The Arctic Sea Ice Thickness Change in CMIP6’s Historical Simulations

This study assesses sea ice thickness(SIT)from the historical run of the Coupled Model Inter-comparison Project Phase 6(CMIP6).The SIT reanalysis from the Pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS)product is chosen as the validation reference data.Results show that most models can adequately reproduce the climatological mean,seasonal cycle,and long-term trend of Arctic Ocean SIT during 1979-2014,but significant inter-model spread exists.Differences in simulated SIT patterns among the CMIP6 models may be related to model resolution and sea ice model components.By comparing the climatological mean and trend for SIT among all models,the Arctic SIT change in different seas during 1979-2014 is evaluated.Under the scenario of historical radiative forcing,the Arctic SIT will probably exponentially decay at-18%(10 yr)-1 and plausibly reach its minimum(equilibrium)of 0.47 m since the 2070s.

Wave hindcast under tropical cyclone conditions in the South China Sea:sensitivity to wind fields

Reliable wave information is critical for marine engineering.Numerical wave models are useful tools to obtain wave information with continuous spatiotemporal distributions.However,the accuracy of model results highly depends on the quality of wind forcing.In this study,we utilize observations from five buoys deployed in the northern South China Sea from August to September 2017.Notably,these buoys successfully recorded wind field and wave information during the passage of five tropical cyclones of different intensities without sustaining any damage.Based on these unique observations,we evaluated the quality of four widely used wind products,namely CFSv2,ERA5,CCMP,and ERAI.Our analysis showed that in the northern South China Sea,ERA5 performed best compared to buoy observations,especially in terms of maximum wind speed values at 10 m height(U10),extreme U10 occurrence time,and overall statistical indicators.CFSv2 tended to overestimate non-extreme U10 values.CCMP showed favorable statistical performance at only three of the five buoys,but underestimated extreme U10 values at all buoys.ERAI had the worst performance under both normal and tropical cyclone conditions.In terms of wave hindcast accuracy,ERA5 outperformed the other reanalysis products,with CFSv2 and CCMP following closely.ERAI showed poor performance especially in the upper significant wave heights.Furthermore,we found that the wave hindcasts did not improve with increasing spatiotemporal resolution,with spatial resolution up to 0.5°.These findings would help in improving wave hindcasts under extreme conditions.

Weather induced subtidal flows through multiple inlets of an arctic microtidal lagoon

Estuarine processes in the arctic lagoons are among the least studied but important subjects, especially considering the rapid warming of arctic water which may change the length of ice-free period in the summer. In this paper, wind-driven exchange flows in the micro-tidal Elson Lagoon of northern Alaska with multiple inlets of contrasting widths and depths are studied with in situ observations, statistical analysis, numerical experiments, a regression model on the basis of dynamics, and remote sensing data. Water velocity profiles were obtained from a bottom deployed acoustic Doppler current profiler(ADCP) in the northwestern Eluitkak Pass connecting the Beaufort Sea to the Elson Lagoon during a 4.9 day ice-free period in the summer of 2013. The subtidal flow is found correlated with wind(R^2 value ～96%). Frequently occurring east, northeast and north winds from the arctic atmospheric high-and low-pressure systems push water from the Beaufort Sea into the lagoon through the wide inlets on the eastern side of the lagoon, resulting in an outward flow against the wind at the narrow northwestern inlet. The counter-wind flow is a result of an uneven wind forcing acting through the asymmetric inlets and depth,an effect of "torque" or vorticity. Under northwest wind, the exchange flow at the northwestern inlet reverses its direction, with inward flows through the upwind northwestern inlet and outward flows through the downwind eastern inlets. A regression model is established based on the momentum equations and Taylor series expansions. The model is used to predict flows in July and August of 2015 and July of 2017, supported by available Landsat satellite images. About 73%–80% of the time the flows at Eluitkak Pass are out of Elson Lagoon for the summer of 2015 and 2017. Numerical experiments are conducted to corroborate the findings and illustrate the effects under various wind conditions. A quasi-steady state balance between wind force and surface pressure gradient is confirmed.