The Impacts of a Subglacial Discharge Plume on Calving, Submarine Melting, and Mélange Mass Loss at Helheim Glacier, South East Greenland

Almost half of the Greenland ice sheet’s mass loss occurs through iceberg calving at marine terminating glaciers. The presence of buoyant subglacial discharge plumes at these marine termini are thought to increase mass loss both through submarine melting and by undercutting that consequently increases calving rates. Plume models are used to predict submarine melting and undercutting. However, there are few observations that allow these relationships to be tested. Here we use airborne lidar from the terminus of Helheim Glacier, SE Greenland to measure the bulge induced at the surface by the upwelling plume. We use these measurements to estimate plume discharge rates using a high‐resolution, three‐dimensional plume model. Multi‐year observations of the plume are compared to a record of calving from camera and icequake data. We find no evidence to suggest that the presence of a plume, determined by its visibility at the surface, increases the frequency of major calving events and also show that mass loss at the terminus driven directly by plume discharge is significantly less than mass loss from major calving events. The results suggest that the contribution of direct plume‐driven mass loss at deep marine‐terminating glaciers may be less than at shallower termini

Complementary water quality observations from high and medium resolution Sentinel sensors by aligning chlorophyll-a and turbidity algorithms

High resolution imaging spectrometers are prerequisite to address significant data gaps in inland optical water quality monitoring. In this work, we provide a data-driven alignment of chlorophyll-a and turbidity derived from the Sentinel-2 MultiSpectral Imager (MSI) with corresponding Sentinel-3 Ocean and Land Colour Instrument (OLCI) products. For chlorophyll-a retrieval, empirical ‘ocean colour’ blue-green band ratios and a near infra-red (NIR) band ratio algorithm, as well as a semi-analytical three-band NIR-red ratio algorithm, were included in the analysis. Six million co-registrations with MSI and OLCI spanning 24 lakes across five continents were analysed. Following atmospheric correction with POLYMER, the reflectance distributions of the red and NIR bands showed close similarity between the two sensors, whereas the distribution for blue and green bands was positively skewed in the MSI results compared to OLCI. Whilst it is not possible from this analysis to determine the accuracy of reflectance retrieved with either MSI or OLCI results, optimizing water quality algorithms for MSI against those previously derived for the Envisat Medium Resolution Imaging Spectrometer (MERIS) and its follow-on OLCI, supports the wider use of MSI for aquatic applications. Chlorophyll-a algorithms were thus tuned for MSI against concurrent OLCI observations, resulting in significant improvements against the original algorithm coefficients. The mean absolute difference (MAD) for the blue-green band ratio algorithm decreased from 1.95 mg m− 3 to 1.11 mg m− 3, whilst the correlation coefficient increased from 0.61 to 0.80. For the NIR-red band ratio algorithms improvements were modest, with the MAD decreasing from 4.68 to 4.64 mg m− 3 for the empirical red band ratio algorithm, and 3.73 to 3.67 for the semi-analytical 3-band algorithm. Three implementations of the turbidity algorithm showed improvement after tuning with the resulting distributions having reduced bias. The MAD reduced from 0.85 to 0.72, 1.22 to 1.10 and 1.93 to 1.55 FNU for the 665, 708 and 778 nm implementations respectively. However, several sources of uncertainty remain: adjacent land showed high divergence between the sensors, suggesting that high product uncertainty near land continues to be an issue for small water bodies, while it cannot be stated at this point whether MSI or OLCI results are differentially affected. The effect of spectrally wider bands of the MSI on algorithm sensitivity to chlorophyll-a and turbidity cannot be fully established without further availability of in situ optical measurements

Assessment of the environmental, ecosystem, and human activities in coastal Vietnam and Cambodia gathered from satelitte remote sensing

Within the ACCORD (Addressing Challenges of Coastal Communities through Ocean Research for Developing Economies) project, satellite Earth Observations are used for two purposes: 1. To describe basic environmental dynamics around two focus regions, Da Nang Bay in Vietnam and Kep Province in Cambodia. Two aspects of satellite data are examined for this purpose: first, sea surface temperature (SST),); second, water quality data, focussing on chlorophyll a and turbidity. 2. To assess the potential for mapping locations of aquaculture sites around Da Nang Bay, Vietnam, through exploitation of EO data. This second purpose utilises the sea surface radar backscattering coefficient. NOAA’s Pathfinder SST dataset derived from measurements made by AVHRR sensors was used here at 4 km resolution. This dataset offers a long time series, which has gone through rigorous quality control and calibration, and as such is considered a climate-quality dataset. The seasonal cycle as well as the long term dynamics for SST can be observed, showing the monsoon dynamics of the region. No trend in warming over the past two decades is observable from these data. Water quality measurements were investigated using a number of EO-derived products. These products cover different spatial and temporal scales. The first is the ESA Ocean Colour Climate Change Initiative (OC-CCI) – Chlorophyll a dataset. This has a 1 km resolution and is mainly optimised for the open ocean through to moderately turbid coastal waters; the most turbid coastal waters around Da Nang and Kep are frequently masked in this dataset. Larger scale regional seasonality and long term changes in chlorophyll levels are assessed. There is no clear trend through time over the wider regions, however clear spatial dynamics can be observed. The relationship between chlorophyll a and SST over the past two decades was also investigated. Higher levels of chlorophyll a occurred near the coasts at certain times of year, predominantly corresponding to seasonal changes in temperature and increases in river flow during monsoon periods. The coastal and nearshore water quality around Da Nang and Kep was assessed using datasets processed with PML’s Calimnos processor, which includes a blend of algorithms designed for very turbid water and prioritises higher spatial resolution over having the longest time series. The 300 m dataset were derived from Envisat MERIS and Sentinel 3 OLCI, which provide a medium-term time series, although there is a four year gap between the missions so a continuous dataset is not available. These data offer the best balance of resolution and algorithm performance for coastal remote sensing at present. The 60 m water quality dataset was derived from Sentinel 2 MSI, which has been operating since 2015 and hence is a shorter time series. However, the 60 m dataset is especially useful for resolving smaller features, as is demonstrated by highlighting small eddy features and river outflows around both Da Nang bay and Kep. The method for detecting and mapping aquaculture structures, such as finfish cages, shellfish farms and floating houses using freely available Sentinel-1A SAR sensor data was successfully applied to Da Nang bay and nearby rivers. 11 aquaculture sites were identified in the bay and in the rivers, confirmed by comparing with high resolution Google Map satellite images. Comparing static maps across different years shows that this method can be used to monitor temporal changes in detected aquaculture sites

Quantifying decadal stability of lake reflectance and chlorophyll-a from medium-resolution ocean color sensors

Multi-decadal time-series of Lake Water-Leaving Reflectance (LWLR), part of the Lakes Essential Climate Variable, have typically been interrupted for the 2012–2016 period due to lack of an ocean color sensor with ca�pabilities equivalent to MERIS (2002− 2012) and OLCI (2016 - present). Here we assess, for the first time, the suitability of MODIS/Aqua to estimate LWLR and the derived concentration of chlorophyll-a (Chla) at the global scale across optically complex water types, in an effort to fill these information gaps for climate studies. We first compare the normalized water-leaving reflectance (Rw) derived from two atmospheric correction algorithms (POLYMER and L2gen) against in situ observations. POLYMER shows superior performance, considering the agreement with in situ measurements and the number of valid outputs. An extensive assessment of nine Chla algorithms is then performed on POLYMER-corrected Rw from MODIS observations. The algorithms are tested both in original parameterizations and following calibration against in situ measurements of Chla. We find that the performance of algorithms parameterized per Optical Water Type (OWT) allows considerable improvement of the global Chla retrieval capability. Using 3 years of overlapping observations between MODIS/Aqua and MERIS (2009–2011) and OLCI (2017–2019), respectively, MODIS-derived reflectance and Chla products showed a reasonable degree of long-term stability in 48 inland water bodies. These water bodies, therefore, mark the candidates to study long-term environmental change

Modelling environmental influences on calving at Helheim Glacier in eastern Greenland

Calving is an important mass-loss process for many glaciers worldwide, and has been assumed to respond to a variety of environmental influences. We present a grounded, flowline tidewater glacier model using a physically-based calving mechanism, applied to Helheim Glacier, eastern Greenland. By qualitatively examining both modelled size and frequency of calving events, and the subsequent dynamic response, the model is found to realistically reproduce key aspects of observed calving behaviour. Experiments explore four environmental variables which have been suggested to affect calving rates: water depth in crevasses, basal water pressure, undercutting of the calving face by submarine melt and backstress from ice mélange. Of the four variables, only crevasse water depth and basal water pressure were found to have a significant effect on terminus behaviour when applied at a realistic magnitude. These results are in contrast to previous modelling studies, which have suggested that ocean temperatures could strongly influence the calving front. The results raise the possibility that Greenland outlet glaciers could respond to the recent trend of increased surface melt observed in Greenland more strongly than previously thought, as surface ablation can strongly affect water depth in crevasses and water pressure at the glacier bed

A High-Resolution Sensor Network for Monitoring Glacier Dynamics

This paper provides an overview of a wide area wireless sensor network that was deployed on the calving front of the Helheim Glacier in Greenland during the summer of 2013. The purpose of the network was to measure the flow rate of the glacier using accurate satellite positioning data. The challenge in this extreme environment was to collect data in real time at the calving edge of the glacier. This was achieved using a solar powered 2.4-GHz Zigbee wireless sensor network operated in a novel hybrid cellular/mesh access architecture consisting of ice nodes communicating with base stations placed on the rock adjacent to the glacier. This highly challenging transmission environment created substantial signal outage conditions, which were successfully mitigated by a radio network diversity scheme. The network development and measurement campaign were highly successful yielding significant results on glacial dynamics associated with climate change

Spatial structure of in situ reflectance in coastal and inland waters: implications for satellite validation

Validation of satellite-derived aquatic reflectance involves relating meter-scale in situ observations to satellite pixels with typical spatial resolution ∼ 10–100 m within a temporal “match-up window” of an overpass. Due to sub-pixel variation these discrepancies in measurement scale are a source of uncertainty in the validation result. Additionally, validation protocols and statistics do not normally account for spatial autocorrelation when pairing in situ data from moving platforms with satellite pixels. Here, using high-frequency autonomous mobile radiometers deployed on ships, we characterize the spatial structure of in situ Rrs in inland and coastal waters (Lake Balaton, Western English Channel, Tagus Estuary). Using variogram analysis, we partition Rrs variability into spatial and intrinsic (non-spatial) components. We then demonstrate the capacity of mobile radiometers to spatially sample in situ Rrs within a temporal window broadly representative of satellite validation and provide spatial statistics to aid satellite validation practice. At a length scale typical of a medium resolution sensor (300 m) between 5% and 35% (median values across spectral bands and deployments) of the variation in in situ Rrs was due to spatial separation. This result illustrates the extent to which mobile radiometers can reduce validation uncertainty due to spatial discrepancy via sub-pixel sampling. The length scale at which in situ Rrs became spatially decorrelated ranged from ∼ 100–1,000 m. This information serves as a guideline for selection of spatially independent in situ Rrs when matching with a satellite image, emphasizing the need for either downsampling or using modified statistics when selecting data to validate high resolution sensors (sub 100 m pixel size)

Consistency between Satellite Ocean Colour Products under High Coloured Dissolved Organic Matter Absorption in the Baltic Sea

Ocean colour (OC) remote sensing is an important tool for monitoring phytoplankton in the global ocean. In optically complex waters such as the Baltic Sea, relatively efficient light absorption by substances other than phytoplankton increases product uncertainty. Sentinel-3 OLCI-A, Suomi-NPP VIIRS and MODIS-Aqua OC radiometric products were assessed using Baltic Sea in situ remote sensing reflectance

Retrieval of Chlorophyll-a concentration and associated product uncertainty in optically diverse lakes and reservoirs

Satellite product uncertainty estimates are critical for the further development and evaluation of remote sensing algorithms, as well as for the user community (e.g., modelers, climate scientists, and decision-makers). Optical remote sensing of water quality is affected by significant uncertainties stemming from correction for atmospheric effects as well as a lack of algorithms that can be universally applied to waterbodies spanning several orders of magnitude in non-covarying substance concentrations. We developed a method to produce estimates of Chlorophyll-a (Chla) satellite product uncertainty on a pixel-by-pixel basis within an Optical Water Type (OWT) classification scheme. This scheme helps to dynamically select the most appropriate algorithms for each satellite pixel, whereas the associated uncertainty informs downstream use of the data (e.g., for trend detection or modeling) as well as the future direction of algorithm research. Observations of Chla were related to 13 previously established OWT classes based on their corresponding water-leaving reflectance (Rw), each class corresponding to specific bio-optical characteristics. Uncertainty models corresponding to specific algorithm - OWT combinations for Chla were then expressed as a function of OWT class membership score. Embedding these uncertainty models into a fuzzy OWT classification approach for satellite imagery allows Chla and associated product uncertainty to be estimated without a priori knowledge of the biogeochemical characteristics of a water body. Following blending of Chla algorithm results according to per-pixel fuzzy OWT membership, Chla retrieval shows a generally robust response over a wide range of class memberships, indicating a wide application range (ranging from 0.01 to 362.5 mg/m3). Low OWT membership scores and high product uncertainty identify conditions where optical water types need further exploration, and where biogeochemical satellite retrieval algorithms require further improvement. The procedure is demonstrated here for the Medium Resolution Imaging Spectrometer (MERIS) but could be repeated for other sensors, atmospheric correction methods and optical water quality variables