College of Sciences
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Browsing College of Sciences by Author "Ackley, Stephen F."
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Item Assessing Scale Dependence on Local Sea Level Retrievals from Laser Altimetry Data over Sea Ice(2020-11-13) Tian, Liuxi; Xie, Hongjie; Ackley, Stephen F.; Mestas-Nuñez, Alberto M.The measurement of sea ice elevation above sea level or the "freeboard" depends upon an accurate retrieval of the local sea level. The local sea level has been previously retrieved from altimetry data alone by the lowest elevation method, where the percentage of the lowest elevations over a particular segment length scale was used. Here, we provide an evaluation of the scale dependence on these local sea level retrievals using data from NASA Operation IceBridge (OIB) which took place in the Ross Sea in 2013. This is a unique dataset of laser altimeter measurements over five tracks from the Airborne Topographic Mapper (ATM), with coincidently high-spatial resolution images from the Digital Mapping System (DMS), that allows for an independent sea level validation. The local sea level is first calculated by using the mean elevation of ATM L1B data over leads identified by using the corresponding DMS imagery. The resulting local sea level reference is then used as ground truth to validate the local sea levels retrieved from ATM L2 by using nine different percentages of the lowest elevation (0.1%, 0.5%, 1%, 1.5%, 2%, 2.5%, 3%, 3.5%, and 4%) at seven different segment length scales (1, 5, 10, 15, 20, 25, and 50 km) for each of the five ATM tracks. The closeness to the 1:1 line, R2 , and root mean square error (RMSE) is used to quantify the accuracy of the retrievals. It is found that all linear least square fits are statistically significant (p < 0.05) using an F test at every scale for all tested data. In general, the sea level retrievals are farther away from the 1:1 line when the segment length scale increases from 1 or 5 to 50 km. We find that the retrieval accuracy is affected more by the segment length scale than the percentage scale. Based on our results, most retrievals underestimate the local sea level; the longer the segment length (from 1 to 50 km) used, especially at small percentage scales, the larger the error tends to be. The best local sea level based on a higher R2 and smaller RMSE for all the tracks combined is retrieved by using 0.1–2% of the lowest elevations at the 1–5 km segment lengths.Item Ice Production in Ross Ice Shelf Polynyas during 2017–2018 from Sentinel–1 SAR Images(2020-05-07) Dai, Liyun; Xie, Hongjie; Ackley, Stephen F.; Mestas-Nuñez, Alberto M.High sea ice production (SIP) generates high-salinity water, thus, influencing the global thermohaline circulation. Estimation from passive microwave data and heat flux models have indicated that the Ross Ice Shelf polynya (RISP) may be the highest SIP region in the Southern Oceans. However, the coarse spatial resolution of passive microwave data limited the accuracy of these estimates. The Sentinel-1 Synthetic Aperture Radar dataset with high spatial and temporal resolution provides an unprecedented opportunity to more accurately distinguish both polynya area/extent and occurrence. In this study, the SIPs of RISP and McMurdo Sound polynya (MSP) from 1 March–30 November 2017 and 2018 are calculated based on Sentinel-1 SAR data (for area/extent) and AMSR2 data (for ice thickness). The results show that the wind-driven polynyas in these two years occurred from the middle of March to the middle of November, and the occurrence frequency in 2017 was 90, less than 114 in 2018. However, the annual mean cumulative SIP area and volume in 2017 were similar to (or slightly larger than) those in 2018. The average annual cumulative polynya area and ice volume of these two years were 1,040,213 km2 and 184 km3 for the RSIP, and 90,505 km2 and 16 km3 for the MSP, respectively. This annual cumulative SIP (volume) is only 1/3–2/3 of those obtained using the previous methods, implying that ice production in the Ross Sea might have been significantly overestimated in the past and deserves further investigations.Item Sea Ice Freeboard in the Ross Sea from Airborne Altimetry IcePod 2016–2017 and a Comparison with IceBridge 2013 and ICESat 2003–2008(2020-07-11) Tian, Liuxi; Xie, Hongjie; Ackley, Stephen F.; Tinto, Kirsty J.; Bell, Robin E.; Zappa, Christopher J.; Gao, Yongli; Mestas-Nuñez, Alberto M.As part of the Polynyas and Ice Production in the Ross Sea (PIPERS) project, the IcePod system onboard the LC-130 aircraft based at McMurdo Station was flown over the Ross Sea, Antarctica in November 2016 and 2017, with the purpose of repeating the same lines that NASA's Operation IceBridge (OIB) aircraft flew over in 2013. We resampled the lidar data into 70 m pixels (similar to the footprint size of OIB L2 and ICESat data) and took the mean of the lowest 2% elevation values of 25 km (50 km) length along a flight track as the local sea level of the central 25 km (50 km). Most of the IcePod data were over the same flight lines taken by OIB in 2013, so the total freeboard changes from 2013 to 2016 and 2017 were examined. Combining with the ICESat (2003–2008), we obtained a better picture of total freeboard and its interannual variability in the Ross Sea. The pattern of the sea ice distribution supports that new ice produced in coastal polynyas was transported northward by katabatic winds off the ice shelf. Compared to ICESat years, sea ice near the coast was thicker, while sea ice offshore was thinner in the more recent OIB/IcePod years. The results also showed that, in general, sea ice was thicker in 2017 compared to 2013 or 2016—0.02–0.55 m thicker in total freeboard.Item Weekly Mapping of Sea Ice Freeboard in the Ross Sea from ICESat-2(2021-08-19) Koo, YoungHyun; Xie, Hongjie; Kurtz, Nathan T.; Ackley, Stephen F.; Mestas-Nuñez, Alberto M.NASA's ICESat-2 has been providing sea ice freeboard measurements across the polar regions since October 2018. In spite of the outstanding spatial resolution and precision of ICESat-2, the spatial sparsity of the data can be a critical issue for sea ice monitoring. This study employs a geostatistical approach (i.e., ordinary kriging) to characterize the spatial autocorrelation of the ICESat-2 freeboard measurements (ATL10) to estimate weekly freeboard variations in 2019 for the entire Ross Sea area, including where ICESat-2 tracks are not directly available. Three variogram models (exponential, Gaussian, and spherical) are compared in this study. According to the cross-validation results, the kriging-estimated freeboards show correlation coefficients of 0.56–0.57, root mean square error (RMSE) of ~0.12 m, and mean absolute error (MAE) of ~0.07 m with the actual ATL10 freeboard measurements. In addition, the estimated errors of the kriging interpolation are low in autumn and high in winter to spring, and low in southern regions and high in northern regions of the Ross Sea. The effective ranges of the variograms are 5–10 km and the results from the three variogram models do not show significant differences with each other. The southwest (SW) sector of the Ross Sea shows low and consistent freeboard over the entire year because of the frequent opening of wide polynya areas generating new ice in this sector. However, the southeast (SE) sector shows large variations in freeboard, which demonstrates the advection of thick multiyear ice from the Amundsen Sea into the Ross Sea. Thus, this kriging-based interpolation of ICESat-2 freeboard can be used in the future to estimate accurate sea ice production over the Ross Sea by incorporating other remote sensing data.