Analysis of climate change impacts on lake ice phenology in Canada using the historical satellite data record

Variability and trends in lake ice dynamics (i.e. lake ice phenology) are related to climate conditions. Climate influences the timing of lake ice melt and freeze onset, ice duration, and lake thermal dynamics that feedback to the climate system initiating further change. Phenology records acquired in a consistent manner and over long time periods are required to better understand variability and change in climate conditions and how changes impact lake processes. In this study, we present a new technique for extracting lake ice phenology events from historical satellite records acquired by the series of Advanced Very High Resolution Radiometer (AVHRR) sensors. The technique was used to extend existing in-situ measurements for 36 Canadian lakes and to develop records for 6 lakes in Canada's far north. Comparison of phenology events obtained from the AVHRR record and in-situ measurements show strong agreement (20 lakes, 180 cases) suggesting, with high confidence especially in the case of break-up dates, the use of these data as a complement to ground observations. Trend analysis performed using the combined in-situ and AVHRR record ∼ 1950-2004 shows earlier break-up (average — 0.18 days/year) and later freeze-up (average 0.12 days/year) for the majority of lakes analyzed. Less confidence is given to freeze-up date results due to lower sun elevation during this period making extraction more difficult. Trends for the 20 year record in the far north showed earlier break-up (average 0.99 days/year) and later freeze-up (average 0.76 days/year). The established lake ice phenology database from the historical AVHRR image archive for the period from 1985 to 2004 will to a certain degree fill data gaps in the Canadian in-situ observation network. Furthermore, the presented extraction procedure is not sensor specific and will enable continual data update using all available satellite data provided from sensors such as NOAA/AVHRR, MetOp/AVHRR, MODIS, MERIS and SPOT/VGT.     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

Changes in the wetland vegetation growth patterns in large lakes on the Yangtze Plain

In this study, the vegetation emergence times (VET), an important phenological characteristics, were obtained for 25 large lakes on the Yangtze Plain between 2001 and 2014. This was carried out by extracting the normalized difference vegetation index (NDVI) time series from the moderate-resolution imaging spectroradiometer (MODIS) data using a decision tree method. This is the first comprehensive documentation of the changes in temporal and spatial distribution in wetland vegetation phenology for large lakes on the Yangtze Plain. The results showed that considerable changes in the VET occurred in 25 wetland ecosystems in the Yangtze Plain. Specifically, 76% of the lakes showed delayed trends in the VET, and 32% of them were statistically significant (p < 0.05). In contrast, 24% of the lakes displayed advanced trends in the VET and 17% of them were statistically significant (p < 0.05) over the past 14 years. An analysis of the driving factors of VET revealed that a VET change was more sensitive to temperature and sunshine duration than to precipitation for most of the lakes. The temperature in 1–2 months before VET had great effect on the vegetation growth, while such a pattern was not evident for sunshine duration for 5 months before VET. Furthermore, the amounts of chemical fertilizers used in nearby farmlands have also played an important role in the vegetation growth for some of the lakes. This record of change in vegetation phenology provides critical information for wetland ecosystem monitoring in the Yangtze Plain.     

A new method to generate a high-resolution global distribution map of lake chlorophyll

A new method was developed, evaluated, and applied to generate a global dataset of growing-season chlorophyll-a (chl) concentrations in 2011 for freshwater lakes. Chl observations from freshwater lakes are valuable for estimating lake productivity as well as assessing the role that these lakes play in carbon budgets. The standard 4 km NASA OceanColor L3 chlorophyll concentration products generated from MODIS and MERIS sensor data are not sufficiently representative of global chl values because these can only resolve larger lakes, which generally have lower chl concentrations than lakes of smaller surface area. Our new methodology utilizes the 300 m-resolution MERIS full-resolution full-swath (FRS) global dataset as input and does not rely on the land mask used to generate standard NASA products, which masks many lakes that are otherwise resolvable in MERIS imagery. The new method produced chl concentration values for 78,938 and 1,074 lakes in the northern and southern hemispheres, respectively. The mean chl for lakes visible in the MERIS composite was 19.2 ± 19.2, the median was 13.3, and the interquartile range was 3.90–28.6 mg m^?3. The accuracy of the MERIS-derived values was assessed by comparison with temporally near-coincident and globally distributed in situ measurements from the literature (n = 185, RMSE = 9.39, R² = 0.72). This represents the first global-scale dataset of satellite-derived chl estimates for medium to large lakes.     

Statistical characterization of the sea ice extent during different winter scenarios in the Gulf of Riga (Baltic Sea) using optical remote-sensing imagery

This study focuses on the statistical characterization of ice conditions (extent, sea ice occurrence probability (SIOP), and length of ice season) in the Gulf of Riga, Baltic Sea, using remote-sensing data. The optical remote-sensing data with 250 m resolution acquired by a Moderate Resolution Imaging Spectroradiometer (MODIS) during 2002–2011 were used for statistical characterization of sea ice. A method based on bimodal histogram analysis of remote-sensing reflectance data was developed to discriminate ice from water. In general, ice extent information obtained from MODIS data agrees with the official ice chart data (synthetic aperture radar (SAR) and in situ measurements) and multi-sensor product containing data from microwave and infrared instruments (R² >0.83). However, in case of severe winters and extremely mild winters there are differences in the dates when maximum ice extent is registered. MODIS data can be used for detailed analysis of ice extent in specific basins of Baltic Sea. Depending on the year, the ice season length in the Gulf of Riga ranged from 68 to 146 days, and the maximum ice extent varied greatly from 329 to 15,350 km². SIOP and number of ice days increased significantly in areas where the depth is less than 15 m. Based on negative-degree days and ice cover characteristics (SIOP and ice season length), three winter scenarios were defined: severe (2003, 2006, 2010, and 2011), medium (2004 and 2005), and mild (2007, 2008, and 2009).     

Hazard assessment of glacial lake outburst floods in Southeast Tibet based on RS and GIS technologies

Glacial lakes are widely distributed across glaciated mountainous regions such as Southeast Tibet (ST). As a result of climate change, glacial lakes have expanded continually in ST over recent five decades, and ST is seriously suffering from glacial lake outburst floods (GLOFs). Hence, glacial lake investigations and hazard assessments of GLOFs are very necessary to perform and are of great practical significance for this area. The region running from Ranwu to Tongmai (RTR) in ST was selected as a study area. To assess hazard degrees of GLOFs, nine factors (F1–F9) were selected from glacial characteristics: the scale of glacial lakes, meteorological conditions, moraine dam parameters and downstream gullies. Average monthly (May to September) land surface temperatures (LSTs), temperature change rates, and average annual precipitation levels were first calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) LST product and Tropical Rainfall Measuring Mission (TRMM) precipitation data. Then, glacial lake areas, downstream gully slopes, distances to glacial lakes, upper glacier areas, average gradients of upper glaciers, and terminal moraine dam widths were obtained based on Thematic Mapper (TM) and Operational Land Imager (OLI) images and Digital Elevation Model (DEM) data. Finally, the fuzzy comprehensive assessment (FCA) method was used to assess hazard degrees of GLOFs in the study area. According to the results, 135 glacial lakes existed during the study periods, five new glacial lakes formed due to lake collapse and snow and ice melt, and one disappeared due to GLOFs. The number of glacial lakes in the area increased from 130 in 1986 to 134 in 2015, and the total area of glacial lakes increased from 832.77 ha in 1986 to 850.51 ha in 2015 due to lake expansion and GLOFs. Of the 134 glacial lakes present in 2015, 10 are identified as high hazardous lakes, eight are identified as medium hazardous lakes, two are considered low hazardous lakes, and 114 are considered extremely low hazardous lakes. The results illustrate hazard levels of GLOFs in ST, which can help guide future hazard prevention in the area.     

Airborne freeboard measurements of sea ice and lake ice at the Sea of Okhotsk coast in 1993-95 by a laser altimeter

An airborne laser altimeter using a Nd:YAG laser was constructed to measure surface profiles of sea ice and frozen lakes. The measurements were conducted to develop a technique for estimating the ice amount of the sea ice in the Sea of Okhotsk off the northern shore of Hokkaido Island, Japan. Distributions of freeboards, mean elevations and ice concentrations were investigated from the data observed in 1993-95. Distribution functions of the ice freeboard changed considerably depending on ice concentrations in contrast with the decreasing function for the sea ice in the Arctic Ocean. The mean ice freeboard, however, correlated very well with the ice concentration, which is very important for estimating total ice amounts in regions of drifting ice. The surface roughness of a frozen lake was also observed and analysed.     

Mapping inland lake water quality across the Lower Peninsula of Michigan using Landsat TM imagery

The number, size, and distribution of inland freshwater lakes present a challenge for traditional water-quality assessment due to the time, cost, and logistical constraints of field sampling and laboratory analyses. To overcome this challenge, Landsat imagery has been used as an effective tool to assess basic water-quality indicators, such as Secchi depth (SD), over a large region or to map more advanced lake attributes, such as cyanobacteria, for a single waterbody. The overarching objective of this research application was to evaluate Landsat Thematic Mapper (TM) for mapping nine water-quality metrics over a large region and to identify hot spots of potential risk. The second objective was to evaluate the addition of landscape pattern metrics to test potential improvements in mapping lake attributes and to understand drivers of lake water quality in this region. Field-level in situ water-quality measurements were collected across diverse lakes (n = 42) within the Lower Peninsula of Michigan. A multicriteria statistical approach was executed to map lake water quality that considered variable importance, model complexity, and uncertainty. Overall, band ratio radiance models performed well (R² = 0.65–0.81) for mapping SD, chlorophyll-a, green biovolume, total phosphorus (TP), and total nitrogen (TN) with weaker (R² = 0.37) ability to map total suspended solids (TSS) and cyanobacteria levels. In this application, Landsat TM and pattern metrics showed poor ability to accurately map non-purgable organic carbon (NPOC) and diatom biovolume, likely due to a combination of gaps in temporal overpass and field sampling and lack of signal sensitivity within broad spectral channels of Landsat TM. The composition and configuration of croplands, urban, and wetland patches across the landscape were found to be moderate predictors of lake water quality that can complement lake remote-sensing data. Of the 4071 lakes, over 4 ha in the Lower Peninsula, approximately two-thirds, were identified as mesotrophic (n = 2715). This application highlights how an operational tool might support lake decision-making or assessment protocols to identify hot spots of potential risk.     

Classification of freshwater ice conditions on the Alaskan Arctic Coastal Plain using ground penetrating radar and TerraSAR-X satellite data

Arctic freshwater ecosystems have responded rapidly to climatic changes over the last half century. Lakes and rivers are experiencing a thinning of the seasonal ice cover, which may increase potential over-wintering freshwater habitat, winter water supply for industrial withdrawal, and permafrost degradation. Here, we combined the use of ground penetrating radar (GPR) and high-resolution (HR) spotlight TerraSAR-X (TSX) satellite data (1.25 m resolution) to identify and characterize floating ice and grounded ice conditions in lakes, ponds, beaded stream pools, and an alluvial river channel. Classified ice conditions from the GPR and the TSX data showed excellent agreement: 90.6% for a predominantly floating ice lake, 99.7% for a grounded ice lake, 79.0% for a beaded stream course, and 92.1% for the alluvial river channel. A GIS-based analysis of 890 surface water features larger than 0.01 ha showed that 42% of the total surface water area potentially provided over-wintering habitat during the 2012/2013 winter. Lakes accounted for 89% of this area, whereas the alluvial river channel accounted for 10% and ponds and beaded stream pools each accounted for <1%. Identification of smaller landscape features such as beaded stream pools may be important because of their distribution and role in connecting other water bodies on the landscape. These findings advance techniques for detecting and knowledge associated with potential winter habitat distribution for fish and invertebrates at the local scale in a region of the Arctic with increasing stressors related to climate and land use change.