Klaus P. Hochheim

An Update on the Ice Climatology of the Hudson Bay System

Abstract The objective of this paper is to examine the thermodynamic and dynamic forcing of sea ice within the Hudson Bay System, including Hudson Bay, Hudson Strait, and Foxe Basin. Changes in fall and spring sea ice extents (SIEs) are examined in relation to seasonal surface air temperatures (SATs) and winds, as are changes in freeze-up dates and breakup dates. The proportional leverage of the fall (lag1) and spring SATs and winds on ice is statistically examined per basin. Results show SATs have increased significantly since the mid-1990s and that increases in the fall are higher than the spring period. Fall SATs are highly related to fall SIEs (R2 = 0.79–0.82). For every 1 °C increase in SAT, SIE decreases by 14% (% of basin area) within the Hudson Bay System; a 1 °C increase delays freezeup by 0.7 to 0.9 weeks on average. Spring SIEs and breakup dates are shown to be highly correlated with fall (lag1) and spring SATs, and with U and V component winds. Proportionately, spring and fall SATs combined play a dominant role (70–80%) in SIE, and the remaining leverage is attributed to dynamic forcing (winds). The relative leverage of fall (lag1) SATs and surface winds are shown to be significant and vary by basin. The open water season has on average increased by 3.1 (±0.6) weeks in Hudson Bay, 4.9 (±0.8) weeks in Hudson Strait, and 3.5 (±0.9) weeks in Foxe Basin.

Changing Sea Ice Conditions in Hudson Bay, 1980–2005

We present an overview of changes in Hudson Bay sea ice in the context of thermodynamic forcing due to increased surface air temperatures and dynamic wind and current forcing mechanisms. Examined in particular is the correspondence between sea ice extent, surface air temperatures, and atmospheric indices during spring and fall from 1980 to 2005. Changes in the timing of freeze-up and break-up over the last several decades were significant. In the spring, temperature trends were consistently positive with temperature increases of 0.23°C/decade from 1950 to 2005. With increasing temperatures in the Hudson Bay region, sea ice concentrations and sea ice extents have decreased significantly as well. Warmer surface air temperatures have also shifted the mean freeze-up and break-up dates by 0.8–1.6 weeks in each of the seasons. Dynamic forcing of sea ice is further explored using the concept of relative vorticity, or the tendency for sea ice to rotate clockwise (or counterclockwise) within Hudson Bay in response to changes in atmospheric circulation. Surface air temperatures and hence ice extent showed cyclical patterns over the time period studied and appear to be driven by large scale atmospheric circulation patterns. This cyclical behaviour has been previously associated with various hemispheric indices including the North Atlantic Oscillation. The implications of changing ice conditions in Hudson Bay for marine mammal habitat are discussed.

Change and variability in sea ice during the 2007–2008 Canadian International Polar Year program

In this paper we describe sea ice change and variability during the Canadian International Polar Year (IPY) program and examine several regional and hemispheric causes of this change. In a companion paper (Barber et al., Climate Change2012) we present an overview of the consequences of this observed change and variability on ecosystem function, climatically relevant gas exchange, habitats of primary and apex predators, and impacts on northern peoples. Sea ice-themed research projects within the fourth IPY were designed to be among the most diverse international science programs. They greatly enhanced the exchange of Inuit knowledge and scientific ideas across nations and disciplines. This interdisciplinary and cultural exchange helped to explain and communicate the impacts of a transition of the Arctic Ocean and ecosystem to a seasonally ice-free state, the commensurate replacement of perennial with annual sea ice types and the causes and consequences of this globally significant metamorphosis. This paper presents a synthesis of scientific sea ice research and traditional knowledge results from Canadian-led IPY projects between 2007 and 2009. In particular, a summary of sea ice trends, basin-wide and regional, is presented in conjunction with Inuit knowledge of sea ice, gathered from communities in northern Canada. We focus on the recent observed changes in sea ice and discuss some of the causes of this change including atmospheric and oceanic forcing of both dynamic and thermodynamic forcing on the ice. Pertinent results include: 1) In the Amundsen Gulf, at the western end of the Northwest Passage, open water persists longer than normal and winter sea ice is thinner and more mobile. 2) Large areas of summer sea ice are becoming heavily decayed during summer and can be broken up by long-period waves being generated in the now extensive open water areas of the Chukchi Sea. 3) Cyclones play an important role in flaw leads—regions of open water between pack ice and land-fast ice. They delay the formation of new ice and the growth of multi-year ice. 4) Feedbacks involving the increased period of open water, long-period wave generation, increased open-ocean roughness, and the precipitation of autumn snow are all partially responsible for the observed reduction in multiyear sea ice. 5) The atmosphere is observed as remaining generally stable throughout the winter, preventing vertical entrainment of moisture above the surface.

STORM STUDIES IN THE ARCTIC (STAR)

The Storm Studies in the Arctic (STAR) network (2007–2010) conducted a major meteorological field project from 10 October–30 November 2007 and in February 2008, focused on southern Baffin Island, Nunavut, Canada—a region that experiences intense autumn and winter storms. The STAR research program is concerned with the documentation, better understanding, and improved prediction of meteorological and related hazards in the Arctic, including their modification by local topography and land–sea ice–ocean transitions, and their effect on local communities. To optimize the applicability of STAR network science, we are also communicating with the user community (northern communities and government sectors). STAR has obtained a variety of surface-based and unique research aircraft field measurements, high-resolution modeling products, and remote sensing measurements (including Cloudsat) as part of its science strategy and has the first arctic Cloudsat validation dataset. In total, 14 research flights were flown b...

Crop fraction estimation from casi hyperspectral data using linear spectral unmixing and vegetation indices

It is important to estimate vegetation fraction for forecasting regional weather and in precision agriculture for assessing crop performance during emergence and early growth phases. In this study, two approaches, linear spectral unmixing and vegetation indices, were reviewed and evaluated for the estimation of crop fraction from hyperspectral data. Compact Airborne Spectrographic Imager (casi) hyperspectral data were acquired three times in the 2001 growing season over four agricultural fields to monitor crop growth conditions and develop procedures for delineating major subunits for crop management. Crops planted in these fields included corn, soybean, and wheat. End-member spectra were extracted from casi data and used for linear spectral unmixing. Various vegetation indices, including the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), optimized soil-adjusted vegetation index (OSAVI), modified soil-adjusted vegetation index (MSAVI), transformed soil-adjusted vegetation index (TSAVI), and recently developed modified triangular vegetation index (MTVI2) and VI700 and VIgreen indices, were evaluated with casi data and with simulated spectra using coupled PROSPECT and SAILH models. All these indices were highly correlated with measured crop fractions. A comparison study based on simulated spectra showed that MTVI2 maintained adequate sensitivity up to a higher crop coverage. A high coefficient of determination (R2 = 0.90) and a low root mean square error (RMSE = 0.10) were obtained between measured and estimated crop fraction using MTVI2. The crop fraction derived from linear spectral unmixing was also highly correlated with the measured crop fraction (R2 = 0.94; RMSE = 0.08). However, determining end-member spectra in the linear spectral unmixing method remains a challenge. Using vegetation indices is a convenient method for crop fraction estimation with satisfactory accuracy.