The sudden ocean warming and its potential influences on earlyfrozen landfast ice in the Prydz Bay, East Antarctica

The ocean conditions beneath the ice cover play a key role in understanding the sea ice mass balance in the polar regions.An integrated high-frequency ice-ocean observation system,including Acoustic Doppler Velocimeter,Conductivity-Temperature-Depth Sensor,and Sea Ice Mass Balance Array(SIMBA),was deployed in the landfast ice region close to the Chinese Zhongshan Station in Antarctica.A sudden ocean warming of 0.14℃(p<0.01)was observed beneath early-frozen landfast ice,from(−1.60±0.03)℃during April 16-19 to(−1.46±0.07)℃during April 20-23,2021,which is the only significant warming event in the nearly 8-month records.The sudden ocean warming brought a double rise in oceanic heat flux,from(21.7±11.1)W/m^(2) during April 16-19 to(44.8±21.3)W/m^(2) during April 20-23,2021,which shifted the original growth phase at the ice bottom,leading to a 2 cm melting,as shown from SIMBA and borehole observations.Simultaneously,the slowdown of ice bottom freezing decreased salt rejection,and the daily trend of observed ocean salinity changed from+0.02 d^(-1) during April 16-19,2021 to+0.003 d^(-1) during April 20-23,2021.The potential reasons are increased air temperature due to the transit cyclones and the weakened vertical ocean mixing due to the tide phase transformation from semi-diurnal to diurnal.The high-frequency observations within the ice-ocean boundary layer enhance the comprehensive investigation of the ocean’s influence on ice evolution at a daily scale.

Parameterization, sensitivity, and uncertainty of 1-D thermodynamic thin-ice thickness retrieval

Retrieval of Thin-Ice Thickness(TIT)using thermodynamic modeling is sensitive to the parameterization of the independent variables(coded in the model)and the uncertainty of the measured input variables.This article examines the deviation of the classical model’s TIT output when using different parameterization schemes and the sensitivity of the output to the ice thickness.Moreover,it estimates the uncertainty of the output in response to the uncertainties of the input variables.The parameterized independent variables include atmospheric longwave emissivity,air density,specific heat of air,latent heat of ice,conductivity of ice,snow depth,and snow conductivity.Measured input parameters include air temperature,ice surface temperature,and wind speed.Among the independent variables,the results show that the highest deviation is caused by adjusting the parameterization of snow conductivity and depth,followed ice conductivity.The sensitivity of the output TIT to ice thickness is highest when using parameterization of ice conductivity,atmospheric emissivity,and snow conductivity and depth.The retrieved TIT obtained using each parameterization scheme is validated using in situ measurements and satellite-retrieved data.From in situ measurements,the uncertainties of the measured air temperature and surface temperature are found to be high.The resulting uncertainties of TIT are evaluated using perturbations of the input data selected based on the probability distribution of the measurement error.The results show that the overall uncertainty of TIT to air temperature,surface temperature,and wind speed uncertainty is around 0.09 m,0.049 m,and−0.005 m,respectively.