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The Greenland Ice Sheet has undergone rapid mass loss over the last four decades, primarily through solid and liquid discharge at marine‐terminating outlet glaciers. The acceleration of these glaciers is in part due to the increase in temperature of ocean water in contact with the glacier terminus. However, quantifying heat transport to the glacier through fjord circulation can be challenging due to iceberg abundance, which threatens instrument survival and fjord accessibility. Here we utilize iceberg movement to infer upper‐layer fjord circulation, as freely floating icebergs (i.e., outside the mélange region) behave as natural drifters. In the summers of 2014 and 2019, we deployed transmitting GPS units on a total of 13 icebergs in Ilulissat Icefjord, an iceberg‐rich and historically data‐poor fjord in west Greenland, to quantify circulation over the upper 0–250 m of the water column. We find that the direction of upper‐layer fjord circulation is strongly impacted by the timing of tributary meltwater runoff, while the speed of this circulation changes in concert with glacier behavior, which includes increases and decreases in glacier speed and meltwater runoff. During periods of increased meltwater runoff entering from tributary fjords, icebergs at these confluences deviated from their down‐fjord trajectory, even reversing up‐fjord, until the runoff pulse subsided days later. This study demonstrates the utility of iceberg monitoring to constrain upper‐layer fjord circulation, and highlights the importance of including tributary fjords in predictive models of heat transport and fjord circulation.

 

Satellites have provided high-resolution ( < 100 m) water color (i.e., remote sensing reflectance) and thermal emission imagery of aquatic environments since the early 1980s; however, global operational water quality products based on these data are not readily available (e.g., temperature, chlorophyll- a , turbidity, and suspended particle matter). Currently, because of the postprocessing required, only users with expressive experience can exploit these data, limiting their utility. Here, we provide paths (recipes) for the nonspecialist to access and derive water quality products, along with examples of applications, from sensors on board Landsat-5, Landsat-7, Landsat-8, Landsat-9, Sentinel-2A, and Sentinel-2B. We emphasize that the only assured metric for success in product derivation and the assigning of uncertainties to them is via validation with in situ data. We hope that this contribution will motivate nonspecialists to use publicly available high-resolution satellite data to study new processes and monitor a variety of novel environments that have received little attention to date. 

Abstract. Remote sensing data are a crucial tool for monitoring climatological changes and glacier response in areas inaccessible for in situ measurements. The Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product provides temperature data for remote glaciated areas where air temperature measurements from weather stations are sparse or absent, such as the St. Elias Mountains (Yukon, Canada). However, MODIS LSTs in the St. Elias Mountains have been found in prior studies to show an offset from available weather station measurements, the source of which is unknown. Here, we show that the MODIS offset likely results from the occurrence of near-surface temperature inversions rather than from the MODIS sensor’s large footprint size or from poorly constrained snow emissivity values used in LST calculations. We find that an offset in remote sensing temperatures is present not only in MODIS LST products but also in Advanced Spaceborne Thermal Emissions Radiometer (ASTER) and Landsat temperature products, both of which have a much smaller footprint (90–120 m) than MODIS (1 km). In all three datasets, the offset was most pronounced in the winter (mean offset >8 ∘C) and least pronounced in the spring and summer (mean offset <2 ∘C). We also find this enhanced seasonal offset in MODIS brightness temperatures, before the incorporation of snow surface emissivity into the LST calculation. Finally, we find the MODIS LST offset to be consistent in magnitude and seasonal distribution with modeled temperature inversions and to be most pronounced under conditions that facilitate near-surface inversions, namely low incoming solar radiation and wind speeds, at study sites Icefield Divide (60.68∘N, 139.78∘ W; 2,603 m a.s.l) and Eclipse Icefield (60.84∘ N, 139.84∘ W; 3017 m a.s.l.). Although these results do not preclude errors in the MODIS sensor or LST algorithm, they demonstrate that efforts to convert MODIS LSTs to an air temperature measurement should focus on understanding near-surface physical processes. In the absence of a conversion from surface to air temperature based on physical principles, we apply a statistical conversion, enabling the use of mean annual MODIS LSTs to qualitatively and quantitatively examine temperatures in the St. Elias Mountains and their relationship to melt and mass balance. 

Increasing freshwater input to the subpolar North Atlantic through iceberg melting can influence fjord‐scale to basin‐scale ocean circulation. However, the magnitude, timing, and distribution of this freshwater have been challenging to quantify due to minimal direct observations of subsurface iceberg geometry and melt rates. Here we present novel in situ methods capturing iceberg change at high‐temporal and ‐spatial resolution using four high‐precision GPS units deployed on two large icebergs (>500 m length). In combination with measurements of surface and subsurface geometry, we calculate iceberg melt rates between 0.10 and 0.27 m/d over the 9‐day survey. These melt rates are lower than those proposed in previous studies, likely due to using individual subsurface iceberg geometries in calculations. In combining these new measurements of iceberg geometry and melt rate with the broad spatial coverage of remote sensing, we can better predict the impact of increasing freshwater injection from the Greenland Ice Sheet.