Study region: Selenga River Delta (SRD), Russia.
Study focus: How is water occurrence changing in the SRD, and what are the hydroclimatic drivers behind these changes? The presence of water on the surface in river deltas is governed by land use, geomorphology, and the flux of water to and from the Delta. We trained an accurate image classification of the Landsat satellite imagery during the last 33 years to quantify surface water occurrence and its changes in the SRD. After comparing our estimations with global-scale data sets, we determined the hydrological drivers of these changes.
New hydrological insights for the region: We find mild decreases in water occurrence in 51% of the SRD's surface area from 1987-2002 to 2003-2020. Water occurrence in the most affected areas decreased by 20% and in the most water-gaining areas increased by 10%. We find a significant relationship between water occurrence and runoff (R-2 = 0.56) that does not exist between water occurrence and suspended sediment concentration (SSC), Lake Baikal's water level, and potential evapotranspiration. The time series of water occurrence follows the peaks in the runoff but not its long-term trend. However, the extremes in SSC do not influence surface water occurrence (R-2 < 0.1), although their long-term trends are similar. Contrary to expected, we find that the Delta has a relatively stable long-term water availability for the time being.
Lakes are important sources of freshwater for human activities and provide critical ecosystem services. However, despite having approximately 100,000 lakes, Sweden has limited continuous gauged water level data. Although satellite radar altimetry has emerged as a popular alternative to measure water levels in inland water bodies, it is yet to be exploited to understand large-scale changes in inland water bodies in Sweden. Here, we quantify the changes in water levels of 144 lakes using satellite altimetry data and in-situ gauged measurements and examine the effects of flow regulation and hydroclimatic variability. Data from multiple altimetry missions, including ERS-2, ENVISAT, JASON-1,2,3, SARAL, and Sentinel-3A/B, are employed to estimate the variability and yearly and seasonal trends of water levels in two periods, 1995-2022 and 2013-2022. Our study finds that water levels significantly increased in 52% of the lakes during 1995-2022. The increasing trends primarily occurred in northern Sweden and are potentially attributed to earlier snowmelt. On the other hand, 43% of the lakes exhibited a significant decreasing trend, which was mostly concentrated in Southern Sweden. Dividing the set of lakes into regulated and unregulated groups shows how lake regulation in Sweden can partly explain the spatial patterns of water levels and their variability. This study highlights the need to continuously monitor lake water levels for adaptation strategies in the face of climate change and understand the downstream effects of water regulatory schemes.
It is essential to track lake water level fluctuations, however, the number of conventional gauging stations is declining worldwide due to impractical installation and maintenance procedures. Satellite altimetry is a substitute for traditional gauges. Nevertheless, altimetry sensors cannot identify small lakes owing to poor spatial coverage. Their application is limited to lakes falling exactly below the path of the altimeter. Differential Interferometric Synthetic Aperture Radar (D-InSAR) is commonly used to track land deformation and water surface changes, with the latter being comparatively limited and focused mainly on wetlands. We here explore the potential of D-InSAR to track water level changes in two Swedish lakes, focusing on the shoreline in search of potential double-bounce backscattering and analyzing pixel phase changes and coherence. We use Sentinel-1A and Sentinel-1B data from 2019, generate six-day interferograms, and exclude those when corresponding to in-situ water level changes exceeding one phase cycle. We find that D-InSAR is sensitive to minor water level changes, obtaining Lin's correlations of up to 0.63 and 0.89 (RMSE = 9 & 4 mm, respectively). These results evidence the potential of future L-band SAR missions with larger wavelengths, such as NISAR, to track water level changes in lakes and aid water tracking missions such as the SWOT.
Lakes are valuable water resources that support aquatic and terrestrial ecosystems and supply fresh water for the agricultural, industrial, and urban sectors worldwide. Although water levels should be tracked to monitor these services, conventional gauging is unfeasible in most lakes. This study explores the potential, advantages, and limitations of using Differential Interferometric Synthetic Aperture Radar (D-InSAR) to estimate small water level changes in lakes (i.e., less than the full cycle of the SAR signal) and overall long-term direction of change. We validated the method across the shores of 30 Swedish lakes with gauged observations during 2019. We used Sentinel-1A/B images with a six-day temporal separation to construct consecutive interferograms and accumulated the phase changes in pixels of high coherence to build time series of water levels. We find that the accumulated phase change replicates the magnitude of water levels in seven lakes in Southern Sweden, where water level changes seldom exceed a complete SAR phase (i.e., 1.8 cm in the vertical direction), evident from the Concordance Correlation Coefficients (0.30 < CCC < 0.55). Furthermore, D-InSAR can estimate the long-term direction of water level change (i.e., increase or decrease) in all 30 lakes. We elaborate on the possible explanation for this last finding. The novel methodology could be used to validate future altimetry missions such as SWOT in lakes worldwide and can be improved with upcoming SAR missions with longer wavelengths.
Lakes are valuable water resources that support aquatic and terrestrial ecosystems and supply fresh water for the agricultural, industrial, and urban sectors worldwide. Although water levels should be tracked to monitor these services, conventional gauging is unfeasible in most lakes. This study applies Differential Interferometric Synthetic Aperture Radar (D-InSAR) to estimate small water level changes, less than 2 cm, in Swedish lakes over 6-day intervals. We validated the method across the shores of 30 Swedish lakes with gauged observations in 2019. We used Sentinel-1A/B images with a 6-day temporal separation to construct consecutive interferograms and accumulated the phase changes in pixels of high coherence to build a time series of water levels. We find that the accumulated phase change obtained by D-InSAR replicates the magnitude of water levels in seven lakes in Southern Sweden, where water levels change slowly, less than 2 cm per 6-day period, as validated by in-situ gauges. In addition, this study demonstrates the application of D-InSAR to estimate the long-term direction of water level change (i.e., increase or decrease) in all 30 lakes. This work reveals the utility of high temporal resolution water level observations in support of other satellite water level instruments such as conventional altimeters and the recently launched Surface Water and Ocean Topography Mission.
Abstract Calibration and validation of glacier mass balance models typically rely on mass balance data derived from measurements at individual points, often along altitudinal gradients, thus neglecting
much of the spatial variability of mass balance. Remote sensing data can provide useful additional spatially distributed information, e.g. on surface conditions such as bare ice area, firn cover extent, or snow. We developed a semi-automated procedure to derive glacier-facies maps from Landsat satellite images, and applied it to Engabreen, an outlet glacier from the Svartisen ice cap in northern Norway. These maps, discriminating between firn, snow and ice surfaces, are then used as a reference for mass balance modelling. Facies information shows a general agreement with the available few field observations and results obtained by distributed mass balance modelling. We conclude that Earth Observation products provide a powerful, although as yet poorly exploited tool, for calibration and validation of distributed mass balance models.
In this paper the potential for inferring shallow firn depth from polarimetric SAR (PolSAR) data at L- and C-band is investigated. Using ALOS PALSAR and Radarsat-2 SAR imagery, and field data including Ground Penetrating Radar profiles and shallow cores, we investigate the spatial distribution of backscatter and decompose backscatter using polarimetric methods to analyse how polarimetric scattering is affected by firn depth near the firn line. The investigation is aimed at a more refined delineation of glacier firn lines and a better understanding of scattering from firn, superimposed ice and the bare ice facies. We found that PolSAR can be used to infer shallow firn thicknesses up to depths of at least 2 m water equivalent (m w.e.) and that old and contemporary firn surfaces can be differentiated using PolSAR. Contrary to many previous investigations the importance of surface scattering in the firn area is also emphasised in the scattering decompositions. Volume scattering was found to have a secondary or tertiary importance. This has important implications for the analysis of backscatter using semi-empirical models.The effect of snow depth on backscatter in pro-glacial a sub-Arctic forest and its potential for improving forest mapping is also discussed. Snow depth data were acquired by manual probing and snowpit measurements. In addition forest stand densities were assessed in situ and NDVI and tasseled cap transformations were made in optical remote sensing data (SPOT-4) to parameterise the forest. Scatterer decomposition and pedestal height products were found to be related to snowpack depth. It was not possible to separate the influences of snow cover and forest structure due to the partial dependence of the former on the latter. Nevertheless it can be concluded that PolSAR improves our ability to map the forest margins of low density, sub-Arctic forests. Our findings have implications for the implementation of algorithms for the exploitation of future SAR missions including Sentinel-1.
The conflict in Darfur, Western Sudan, is frequently represented in the media as a dispute over access to resources by competing communities. Environmental degradation is often cited as either a causal or a contributory factor to the outbreak of the conflict and its prolongation. In this paper, Normalized Difference Vegetation Index (NDVI) data are used as a measure of 'eco-scarcity' to assess the notion that the outbreak of conflict was the result of competition for resources between communities. It is shown that there is no evidence in the vegetation mapping for a worsening of the ecological situation in Western and Northern Darfur states around the outbreak of the conflict. On the contrary, the years prior to the outbreak of the conflict experienced better than average vegetation growth in the context of the past 25 years.
The firn line, like other glacier facies, is mapped operationally as part of glacier monitoring activities for glaciological and climate studies. Synthetic aperture radar (SAR) images are commonly used to determine the firn line in dry snow imagery. The radiometric response of retreating firn has not previously been investigated. Rather, it has been assumed that firn line mapping is only useful where large scale advances or retreats of the lower limit of continuous firn have occurred. In this paper the radiometric signal of retreating firn on an icecap in north Norway is analyzed using multi-temporal SAR imagery. Using comparisons with firn well above the firn line and field investigations of the firn properties, backscattering mechanisms are inferred. It is found that retreating firn has a distinctive radiometric signal that can be used to identify the inception and progression of firn down-wasting prior to and during firn line retreat.
Here we use in situ observations to identify spatio-temporal variations of snow particle size in 89 GHz AMSR-E passive microwave satellite imagery. We have correlated high temporal resolution data daily AMSR-E with reference to high spatial resolution Envisat ASAR images to a validation dataset of snow particle size acquired during the Japanese Swedish Antarctic Expedition (JASE) 2007/2008. We have found strong correlations between the 89 GHz AMSR-E data and two different size parameters: particle length and estimated Specific Surface Area (SSA). These correlations have been used to model the grain size variations over the entire region of interest. The daily AMSR-E data have been used to study the evolution of the snowpack over time revealing a seasonal metamorphosis of snow particles at the coast that is largely absent on the polar plateau. Furthermore, the AMSR-E data may exhibit effects from the passing of coastal weather systems on 3-6 day cycles. These effects penetrate to the polar plateau and may represent the drainage of cold air from the plateau drawn-down by passing coastal weather systems.
Mangroves are important habitats that face a range of threats, natural and anthropogenic. Synthetic aperture radar (SAR) images from 1994 to 2010 have been used to identify systematic changes in mangrove forest vegetation in the Rufiji Delta, Tanzania. The mangrove forest is a Forest Reserve and is protected from large scale exploitation, though there are settlements within the reserve. A dataset of five L-band SAR images spanning a 16-year time period was processed to identify spatio-temporal changes in mangrove forest extent and composition. SAR signatures are related to changes in water budget. The image data show minor expansion in cultivated land along the margins of established communities in the delta. Thinning of mangroves is detected on higher ground whilst along creeks and river channels SAR backscatter indicates an increase in biomass. Sea level height is found to exert a stronger influence on backscatter than minor differences in seasonality. Despite inaccuracies in older SAR images SAR time series are shown to provide valuable data on the spatio-temporal dynamics of East African mangrove forests.
The mangroves of the Rufiji Delta are an important habitat and resource. The mangrove forest reserve is home to an indigenous population and has been under pressure from an influx of migrants from the landward side of the delta. Timely and effective forest management is needed to preserve the delta and mangrove forest. Here, we investigate the potential of polarimetric target decomposition for mangrove forest monitoring and analysis. Using three ALOS PALSAR images, we show that L-band polarimetry is capable of mapping mangrove dynamics and is sensitive to stand structure and the hydro-geomorphology of stands. Entropy-alpha-anisotropy and incoherent target decompositions provided valuable measures of scattering behavior related to forest structure. Little difference was found between Yamaguchi and Arii decompositions, despite the conceptual differences between these models. Using these models, we were able to differentiate the scattering behavior of the four main species found in the delta, though classification was impractical due to the lack of pure stands. Scattering differences related to season were attributed primarily to differences in ground moisture or inundation. This is the first time mangrove species have been identified by their scattering behavior in L-band polarimetric data. These results suggest higher resolution L-band quad-polarized imagery, such as from PALSAR-2, may be a powerful tool for mangrove species mapping.
C-band SAR observations show that backscatter varies significantly across small scales (tens of kilometers) in western Dronning Maud Land. Generally, backscatter was found to diminish with altitude reflecting lower accumulation and reduced ice inclusions in the firn of the percolation zone at higher elevations. Reference to (incomplete) mass balance data suggests an anticorrelation between backscatter and net balance, although more data are needed to confirm the trend. Even within the percolation zone, areas of low backscatter (<-12 dB) exist. These are uncorrelated with altitude above sea level. Using a Rayleigh backscatter model, we show that backscatter over such regions may represent differences in grain sizes. The application of a buried-layers model did not accurately estimate backscatter from these regions. We suggest that these regions occupy exposed positions subject to increased wind sublimation which, in turn, results in smaller grain sizes in the firn and therefore reduced backscatter. The Radarsat Antarctica Mapping Mission SAR mosaic indicates such regions occur in Coates Land, near the edge of the Antarctic Plateau, and on exposed promontories elsewhere in East Antarctica. More information regarding the structure of the firn and the mass balance of the region is needed before we can definitively explain controls on backscatter and understand the climatology of the low backscatter zones.
Climate change is not only about changes in means of climatic variables such as temperature, precipitation and wind, but also their extreme values which are of critical importance to human society and ecosystems. To inspire the Swedish climate research community and to promote assessments of international research on past and future changes in extreme weather events against the global climate change background, the Earth Science Class of the Royal Swedish Academy of Sciences organized a workshop entitled 'Extreme weather events in a warming world' in 2019. This article summarizes and synthesizes the key points from the presentations and discussions of the workshop on changes in floods, droughts, heat waves, as well as on tropical cyclones and extratropical storms. In addition to reviewing past achievements in these research fields and identifying research gaps with a focus on Sweden, future challenges and opportunities for the Swedish climate research community are highlighted.
To better understand the spatio-temporal variability of the glaciological environment in Dronning Maud Land (DML), East Antarctica, a 2800-km-long Japanese-Swedish traverse was carried out. The route includes ice divides between two ice-coring sites at Dome Fuji and EPICA DML. We determined the surface mass balance (SMB) averaged over various time scales in the late Holocene based on studies of snow pits and firn cores, in addition to radar data. We find that the large-scale distribution of the SMB depends on the surface elevation and continentality, and that the SMB differs between the windward and leeward sides of ice divides for strong-wind events. We suggest that the SMB is highly influenced by interactions between the large-scale surface topography of ice divides and the wind field of strong-wind events that are often associated with high-precipitation events. Local variations in the SMB are governed by the local surface topography, which is influenced by the bedrock topography. In the eastern part of DML, the accumulation rate in the second half of the 20th century is found to be higher by similar to 15% than averages over longer periods of 722 a or 7.9 ka before AD 2008. A similar increasing trend has been reported for many inland plateau sites in Antarctica with the exception of several sites on the leeward side of the ice divides.
We have developed a digital image processing method for snow particle size and shape analysis suitable for quick and reliable analysis in the eld. Snow particle size is an important parameter strongly aecting snow cover albedo from seasonally snow covered areas and ice sheets. It is also important in remote sensing analysis because it influences the reflectance and scattering properties of the snow. Alternatively traditional methods based on visual inspection of samples can be used but they do not yield quantitative data. Our method provides an additional alternative to both simpler and more complex methods by providinga tool that limits the subjective eect of the visual analysis and provides a quantitativeparticle size distribution. The method involves image analysis software and field efficient instrumentation in order to develop a complete process-chain easily implemented under field conditions. The results from the analysis are a two dimensional analysis of particle size, shape and distributions for each sample. The developed method improves snow particle analysis being quantitative, reproducible and applicable for dierent types of eld sites.
Snow particle size is an important parameter strongly affecting snow cover broadband albedo from seasonally snow covered areas and ice sheets. It is also important in remote sensing analyses because it influences the reflectance and scattering properties of the snow. We have developed a digital image processing method for the capture and analysis of data of snow particle size and shape. The method is suitable for quick and reliable data capture in the field. Traditional methods based on visual inspection of samples have been used but do not yield quantitative data. Our method provides an alternative to both simpler and more complex methods by providing a tool that limits the subjective effect of the visual analysis and provides a quantitative particle size distribution. The method involves image analysis software and field efficient instrumentation in order to develop a complete process-chain easily implemented under field conditions. The output from the analysis is a two-dimensional analysis of particle size, shape, and distributions for each sample. The results of the segmentation process were validated against manual delineation of snow particles. The developed method improves snow particle analysis because it is quantitative, reproducible, and applicable for different types of field sites.
Snow grain size is an important parameter for determining albedo of the ice sheets and for calibration of optical and microwave remote sensing scattering processes. Snow grain size is a function of the local climate determined by moisture content, air and snow temperature, their gradients within the snow and firn, and wind patterns. Furthermore, it is an indicator on snow metamorphism. We have developed The Digital Grain Size Properties method (DGSP-method) using object oriented image analysis of very high resolution snow grain size images. Commonly used methods are based on visual interpretation, which is a subjective method providing only mean grain size does not retrieve size distribution within each sample.
This is a first attempt to validate satellite information by the in situ measurements from JASE (Japanese Swedish Antarctic Expedition) 2007/2008 using digital image processing. The DSGP-method is based on in-field photography of snow and pixel-based object oriented image analysis. The results show shows decreasing grain size towards the centre of Antarctica and larger grains in the coastal areas. The data used to validate is three different products based on two different types of optic satellite sensors; MERIS (Medium Resolution Imaging Spectrometer) and MODIS (Moderate Resolution Imaging Spectroradiometer). A first validation captures a cluster relation between grain size in the coastal and at the plateau and optical satellite reflection.
Understanding spatial snow particle size variations are key to help interpretation of remotely sensed data of snow cover. In the case of Antarctica, remote sensing is the only viable option to estimate the surface mass balance of the ice sheet on continental scale. We have investigated snow particle size variability along a transect from the coast onto the polar plateau in Dronning Maud Land, Antarctica, to better understand the spatial and temporal variations in surface snow properties. Two daily samples were collected during a 55 day traverse to capture the regional variability. Local variability was assessed by sampling in grids at selected locations and the particle size and shape distributions for each site was analysed through digital image analysis, which has the benefit of yielding large quantities of reproducible quantitative data without the need for advanced laboratory analysis. The results provide an understanding of the complexity of snow particle size variability at different scales and show a variability range from 0.18–3.31 mm depending on the sample type (surface, grid or pit). We can verify relationships between grain size and both elevation and distance to the coast (moisture source) but have also identified regional seasonal changes, particularly on the lower elevations of the polar plateau. Our data provide possibilities to quantitatively assess the optical properties of the surface snow for remote sensing. The details of the spatial and temporal variations observed in our data provides a basis for further studies of the complex and coupled processes affecting snow particle size and the interpretation of remote sensing of snow covered areas.
In this study, snow particle size variability was investigated along a transect in Dronning Maud Land from the coast to the polar plateau. The aim of the study was to better understand the spatial and temporal variations in surface snow properties. Samples were collected twice daily during a traverse in 2007-08 to capture regional variability. Local variability was assessed by sampling in 10 x 10m grids (5m spacing) at selected locations. The particle size and shape distributions for each site were analysed through digital image analysis. Snow particle size variability is complex at different scales, and shows an internal variability of 0.18-3.31 mm depending on the sample type (surface, grid or pit). Relationships were verified between particle size and both elevation and distance to the coast (moisture source). Regional seasonal changes were also identified, particularly on the lower elevations of the polar plateau. This dataset may be used to quantitatively analyse the optical properties of surface snow for remote sensing. The details of the spatial and temporal variations observed in our data provide a basis for further studies of the complex and coupled processes affecting snow particle size and the interpretation of remote sensing of snow covered areas.
Meltwater is stored in supra-glacial lakes on the Greenland Ice Sheet. Connections between the melt water, ice sheet dynamics and the extent of the surface hydrological system have been observed. This highlights the importance of being able to study the surface hydrology over large spatial scales with a high temporal resolution. In this study, we develop an adaptive classification method to identify and map these supra-glacial lakes using high temporal resolution satellite images from the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor. Surface reflectance images from 2007 are used to extract information about the lakes, their morphologies and their surroundings. Using a multiclass approach we can recognize lake types that have previously been difficult to classify, such as deep lakes, lakes within cryoconite areas and lakes with floating ice. Given significant increases in melting in recent years relative to the long term record the inclusion of deep lakes might prove particularly important.
Surface lakes on the Greenland Ice Sheet provide temporary storage for meltwater that influences both the surface and basal water fluxes. Thus, to understand the effects of variations in surface melt on ice sheet dynamics it is necessary to understand the surface hydrology. We have used satellite imagery, acquired at 5-day intervals, to map lake initiation and cessation on two sub-sections on the south west Greenland Ice Sheet over three melt seasons (2007–2009). We observe that lake initiation is closely tied to a threshold energy input of approximately 40 ± 18.5 positive-degree-days. This applies to all studied melt seasons, regardless of evolution and melting index anomalies. Lake longevity averages 24 days with little variation between different melt seasons. Our observed median lake area is larger than previously reported. Approximately 50% of all lakes have a life span of <10 d. Cessation of identified lakes is caused by two processes: drainage during the melt season (88% – 2007, 78% – 2008 and 88% – 2009) and freezeup at the end of the season (12% – 2007, 22% – 2008 and 12% – 2009). Inclusion of the energy needed for lake initiation and number of lakes that freeze up at the end of the season into supra-glacial lake models will add further insight into the hydrological system dynamics.
Melt water gathered in supra-glacial lakes on the Greenland ice sheet contributes to reduced basal friction by the input of water from the surface to the bed during the melt season. Supra-glacial lakes change on both annual and interannual timescales. The high temporal resolution and moderate spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) can be used to capture annual changes on the highly transient/fast-draining lakes. However, MODIS imagery lacks the ability to penetrate clouds. Using ENVISAT Synthetic Aperture Radar (SAR) winter images, we show that SAR images can be used to identify seasonal/inter-annual changes in the lake area. Furthermore, winter SAR images identify lakes obscured to optical data by ice and snow cover. However, the SAR imagery systematically failed to discriminate narrow lakes and lakes in corrugated topography. Thus, SAR images can be used as a complement to existing visible–near-infrared data but do not offer a viable replacement.
The stability of the ice sheets is affected by the ongoing climate change through changes in the meltwater budget and effects on ice sheet dynamics. Surface lakes on the Greenland Ice Sheet have attracted much attention, but assessing their number and size as well as the variability over time of these parameters is not straight-forward. We present a satellite image-based survey of the total lake area and number of supra-glacial lakes in a specific region on the western margin of the Greenland Ice Sheet. Optical images from two different sensors (Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat) and images from three different synthetic aperture radar (SAR) satellites (Radarsat, ERS and Envisat) from 2001, 2006 and 2007, were used in order to manually digitize the extent of supra-glacial lakes. The image spatial resolution ranges from high (Radarsat, ERS and Landsat) to moderate (Envisat and MODIS) where high resolution corresponds to 6.25 to 25 m, and a moderate resolution corresponds to 50 to 250 m. SAR imagery was tested as a supplement to the more commonly used optical data to fill gaps in the time series caused by frequent cloud cover. In total 709 individual lakes were studied. High resolution images were shown to be preferable in the beginning of the melt season, due to the smaller size of the lakes. In the middle of the melt season the resolution was of limited importance. Our work suggests that the use of a combination of active radar and optical images enables successful lake monitoring with high temporal and spatial resolution in both cloudy and clear weather conditions.
Supra-glacial lake form and store melt water during the ablation season every year on the Greenland Ice Sheet (GrIS). This melt water influences both the surface and basal water fluxes. Using an adaptive object-oriented classification approach supra-glacial lakes on the west GrIS are mapped in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) imagery 2001–2010. Lake size shape and distribution parameters are extracted for approximately 5-day intervals from the available cloud free imagery. Using temperature data measured within this region we correlate the lake parameters to melt proxies such ascumulative positive degree days (PDD). The analysis shows that simple parameters such as number of lakes and mean lake area, measures that have been used to describe the development of the surface hydrological system, are largely uncorrelated with melt proxies. Years with higher relative melt, expressed as negative surface mass balances and high PDDs, may exhibit long, predominantly mild melt seasons. Alternatively, a short but intense melt season may have occurred. Given the short duration of the time series, it is difficult to establish statistical relationships between parameters. However, parameters such as median lake size, reflectance and distance between lakes may provide valuable ancillary information to measures such as total lake area, median lake area and lake size distribution data.
Surface lakes on the Greenland Ice Sheet provide temporary storage for meltwater that influences both the surface and basal water fluxes. Thus, to understand the effects of variations in surface melt on ice sheet dynamics it is necessary to understand the surface hydrology. We have used satellite imagery, acquired at 5-day intervals, to map lake initiation and cessation on two sub-sections on the south west Greenland Ice Sheet over three melt seasons (2007-2009). We observe that lake initiation is closely tied to a threshold energy input of approximately 40 ± 18.5 positive-degree-days. This applies for all studied melt season, regardless of evolution and melt index anomalies. Lake longivity averages 24 days with little variation between different melt seasons. Our observed median lake area is larger than previously reported. Approximately 50% of all lakes have a life span of <10 days. Cessation of identified lakes is caused by two processes: drainage during the melt season (88% 2007, 78% 2008 and 88% 2009) and freeze-up at the end of the season (12% 2007, 22% 2008 and 12% 2009). Inclusion of energy needed for lake initiation and amount of freeze-up lakes into supra-glacial lake models will add further insight into the hydrological system dynamics.
The Randolph Glacier Inventory (RGI) is a globally complete collection of digital outlines of glaciers, excluding the ice sheets, developed to meet the needs of the Fifth Assessment of the Intergovernmental Panel on Climate Change for estimates of past and future mass balance. The RGI was created with limited resources in a short period. Priority was given to completeness of coverage, but a limited, uniform set of attributes is attached to each of the similar to 198 000 glaciers in its latest version, 3.2. Satellite imagery from 1999-2010 provided most of the outlines. Their total extent is estimated as 726 800 +/- 34 000 km(2). The uncertainty, about +/- 5%, is derived from careful single-glacier and basin-scale uncertainty estimates and comparisons with inventories that were not sources for the RGI. The main contributors to uncertainty are probably misinterpretation of seasonal snow cover and debris cover. These errors appear not to be normally distributed, and quantifying them reliably is an unsolved problem. Combined with digital elevation models, the RGI glacier outlines yield hypsometries that can be combined with atmospheric data or model outputs for analysis of the impacts of climatic change on glaciers. The RGI has already proved its value in the generation of significantly improved aggregate estimates of glacier mass changes and total volume, and thus actual and potential contributions to sea-level rise.
This chapter compiles and assesses information on recent and current change within the terrestrial cryosphere of the Baltic Sea drainage basin. Findings are based on long-term observations. Snow cover extent (SCE), duration and amount have shown a widespread decrease although there is large interannual and regional variation. Few data are available on changes in snow structural properties. There is no evidence for a recent change in the frequency or severity of snow-related extreme events. There has been a decrease in glacier coverage in Sweden and glacier ice thickness in inland Scandinavia. The European permafrost is warming, and there has been a northward retreat of the southern boundary of near-surface permafrost in European Russia.
The boreal winter 2019/2020 was very irregular in Europe. While there was very little snow in Central Europe, the opposite was the case in northern Fenno-Scandia, particularly in the Arctic. The snow cover was more persistent here and its rapid melting led to flooding in many places. Since the last severe spring floods occurred in the region in 2018, this raises the question of whether more frequent occurrences can be expected in the future. To assess the variability of snowmelt related flooding we used snow cover maps (derived from the DLR’s Global SnowPack MODIS snow product) and freely available data on runoff, precipitation, and air temperature in eight unregulated river catchment areas. A trend analysis (Mann-Kendall test) was carried out to assess the development of the parameters, and the interdependencies of the parameters were examined with a correlation analysis. Finally, a simple snowmelt runoff model was tested for its applicability to this region. We noticed an extraordinary variability in the duration of snow cover. If this extends well into spring, rapid air temperature increases leads to enhanced thawing. According to the last flood years 2005, 2010, 2018, and 2020, we were able to differentiate between four synoptic flood types based on their special hydrometeorological and snow situation and simulate them with the snowmelt runoff model (SRM).
Methods to quantify the dynamics of thermokarst lake margins in subarctic permafrost peatlands have been examined using historical aerial photographs and QuickBird imagery from the Hudson Bay Lowlands in west-central Canada, spanning a time period of 52 years (1954-2006). The goal of this study was to develop a method for detection of metre-scale changes in thermokarst lake extent using a time series of high resolution imagery. The method should be applicable to a variety of lake forms, transferable to other locations and sufficiently robust as to support different data types. Semi-automatic remote sensing techniques such as unsupervised and supervised classification and texture and high-pass filtering were tested, evaluated and rejected. According to an experiment of manual digitalization of shorelines by multiple operators the relative uncertainty for lakes surrounded by peat plateau was ±1.5 m. The uncertainty was reduced to ±0.6 m when binary encoding of transects perpendicular to the shoreline was used to refine the manual delineation. This proved to be the most accurate method to detect small-scale changes in lake extent. An increased understanding and quantification of thermokarst dynamics in permafrost peatlands is important for predicting future scenarios of greenhouse gas emissions from these ecosystems under changing climatic conditions and our method supports such goals.
Societal dependence on, and commercial and scientific exploitation of Earth-Oriented remote sensing from satellites is growing at an exponential rate. The comprehensive EU Copernicus programme provides a major contribution to the global effort, but even so, to achieve the necessary global and temporal coverage requires synergistic cooperation and associated interoperability of the Worlds sensors. For a user to exploit Earth Observation (EO) data there must exist confidence in data characteristics, quality and reliable delivery. Although long-term data records for climate may be the most demanding in nature, generation of analysis-ready operational data sets for applications, as diverse as food security to pollution monitoring, all require the user to have some quantitative level of confidence in the data and derived information. A long-term Calibration/Validation (Cal/Val) vision necessitates clear ownership and long-term funding. Delineating the roles of the European Commission (EC), space agencies and member states in long-term Cal/Val would provide clarity. It is clear that the space agencies have the responsibility to meet the mission requirement of their spaceborne instruments but long-term validation is often entrusted to interested parties bringing their own resources to the task. Furthermore, there is a critical need for Fiducial Reference Measurements (FRMs), acquired in operational mode, and comprehensive in coverage both spatially and temporally, to assure that the satellite product accuracies are met. This paper discusses the current status, gaps and challenges regarding long-term Cal/Val of EO satellites and recommends the creation of a European coordinating entity for satellite product calibration and validation. The proposed entity would be an integrative organization coordinating the European Cal/Val activities in partnership with the member states and the space agencies and working together with existing data providers to secure access to satellite and in-situ data of traceable FRM standards.