Variability in glacier albedo and links to annual mass balance for the gardens of Eden and Allah, Southern Alps, New Zealand

• Main Authors: A. J. Dowson, P. Sirguey, N. J. Cullen
• Format: Article
• Language: English
• Published: Copernicus Publications 2020-10-01
• Series: The Cryosphere
• Online Access: https://tc.copernicus.org/articles/14/3425/2020/tc-14-3425-2020.pdf

<p>The gardens of Eden and Allah (GoEA) are two of New Zealand's largest ice fields. However, their remote location and protected conservation status have limited access and complicated monitoring and research efforts. To improve our understanding of the spatial and temporal changes in mass balance of these unique ice fields, observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors are used to monitor annual minimum glacier-wide albedo (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mover accent="true"><mi mathvariant="italic">α</mi><mo mathvariant="normal">¯</mo></mover><mi mathvariant="normal">yr</mi><mi mathvariant="normal">min</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="22pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="5b9644d0a10a742f5d1b5314053dbb19"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-3425-2020-ie00001.svg" width="22pt" height="17pt" src="tc-14-3425-2020-ie00001.png"/></svg:svg></span></span>) over the period 2000–2018. The <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M2" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mover accent="true"><mi mathvariant="italic">α</mi><mo mathvariant="normal">¯</mo></mover><mi mathvariant="normal">yr</mi><mi mathvariant="normal">min</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="22pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="e71f55b57f6b5740ca2812e509375d2b"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-3425-2020-ie00002.svg" width="22pt" height="17pt" src="tc-14-3425-2020-ie00002.png"/></svg:svg></span></span> for 12 individual glaciers ranges between 0.42 and 0.70 and can occur as early as mid-January and as late as the end of April. The evolution of the timing of <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mover accent="true"><mi mathvariant="italic">α</mi><mo mathvariant="normal">¯</mo></mover><mi mathvariant="normal">yr</mi><mi mathvariant="normal">min</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="22pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="74b1418ac1d40454afda1cb8e050fb72"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-3425-2020-ie00003.svg" width="22pt" height="17pt" src="tc-14-3425-2020-ie00003.png"/></svg:svg></span></span> indicates a shift to later in the summer over the 19-year period on 10 of the 12 glaciers. However, there is only a weak relationship between the delay in timing and the magnitude of <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M4" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mover accent="true"><mi mathvariant="italic">α</mi><mo mathvariant="normal">¯</mo></mover><mi mathvariant="normal">yr</mi><mi mathvariant="normal">min</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="22pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="c9044c72caa8cb285357105790a58158"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-3425-2020-ie00004.svg" width="22pt" height="17pt" src="tc-14-3425-2020-ie00004.png"/></svg:svg></span></span>, which implies that albedo is not necessarily lower if it is delayed. The largest negative departures in <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mover accent="true"><mi mathvariant="italic">α</mi><mo mathvariant="normal">¯</mo></mover><mi mathvariant="normal">yr</mi><mi mathvariant="normal">min</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="22pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="07e0dc1092b37793453cf3d82f29616e"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-3425-2020-ie00005.svg" width="22pt" height="17pt" src="tc-14-3425-2020-ie00005.png"/></svg:svg></span></span> (lower-than-average albedo) are consistent with high snowline altitudes (SLAs) relative to the long-term average as determined from the End of Summer Snowline (EOSS) survey, which has been the benchmark for monitoring glaciers in the Southern Alps for over 40 years. While the record of <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M6" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mover accent="true"><mi mathvariant="italic">α</mi><mo mathvariant="normal">¯</mo></mover><mi mathvariant="normal">yr</mi><mi mathvariant="normal">min</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="22pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="d88a968b71c96142c69d9b8aef70780c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-3425-2020-ie00006.svg" width="22pt" height="17pt" src="tc-14-3425-2020-ie00006.png"/></svg:svg></span></span> for Vertebrae Col 25, an index glacier of the EOSS survey and one of the GoEA glaciers, explains less than half of the variability observed in the corresponding EOSS SLA (<span class="inline-formula"><i>R</i>²=0.43</span>, <span class="inline-formula"><i>p</i>=0.003</span>), the relationship is stronger when compared to other GoEA glaciers. Angel Glacier has the strongest relationship with EOSS observations at Vertebrae Col 25, accounting for 69&thinsp;% of its variance (<span class="inline-formula"><i>p</i>&lt;0.001</span>). A key advantage in using the <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mover accent="true"><mi mathvariant="italic">α</mi><mo mathvariant="normal">¯</mo></mover><mi mathvariant="normal">yr</mi><mi mathvariant="normal">min</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="22pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="f8fd62372c4e30353ed5144b83dde2f2"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-3425-2020-ie00007.svg" width="22pt" height="17pt" src="tc-14-3425-2020-ie00007.png"/></svg:svg></span></span> approach is that it enables variability in the response of individual glaciers to be explored, revealing that topographic setting plays a key role in addition to the regional climate signal. The observed variability in individual glacier response at the scale of the GoEA contrasts with the high consistency of responses found by the EOSS record across the Southern Alps and challenges the suggestion that New Zealand glaciers behave as a unified climatic unit. MODIS imagery acquired from the Terra and Aqua platforms also provides insights about the spatial and temporal variability in clouds. The frequency of clouds in pixels west of the Main Divide is as high as 90&thinsp;% during summer months and reaches a minimum of 35&thinsp;% in some locations in winter. These complex cloud interactions deserve further attention as they are likely a contributing factor in controlling the spatial and temporal variability in glacier response observed in the GoEA.</p>