A Preliminary Investigation of Arctic Sea Ice Negative Freeboard from in-situ Observations and Radar Altimetry

The negative freeboard of sea ice(i.e., the height of ice surface below sea level) with subsequent flooding is widespread in the Southern Ocean, as opposed to the Arctic, due to the relatively thicker ice and thinner snow. In this study, we used the observations of snow and ice thickness from 103 ice mass balance buoys(IMBs) and NASA Operation IceBridge Aircraft Missions to investigate the spatial distribution of negative freeboard of Arctic sea ice. The Result showed that seven IMBs recorded negative freeboards, which were sporadically located in the seas around Northeast Greenland, the Central Arctic Ocean, and the marginal areas of the Chukchi–Beaufort Sea. The observed maximum values of negative freeboard could reach-0.12 m in the seas around Northeast Greenland. The observations from IceBridge campaigns also revealed negative freeboard comparable to those of IMBs in the seas around North Greenland and the Beaufort Sea. We further investigated the large-scale distribution of negative freeboard using NASA CryoSat-2 radar altimeter data, and the result indicates that except for the negative freeboard areas observed by IMBs and IceBridge, there are negative freeboards in other marginal seas of the Arctic Ocean. However, the comparison of the satellite data with the IMB data and IceBridge data shows that the Cryosat-2 data generally overestimate the extent and magnitude of the negative freeboard in the Arctic.

Projection of future streamflow of the Hunza River Basin,Karakoram Range(Pakistan)using HBV hydrological model

Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.