scholarly journals Remote Sensing of Lake Ice Phenology across a Range of Lakes Sizes, ME, USA

2019 ◽  
Vol 11 (14) ◽  
pp. 1718 ◽  
Author(s):  
Shuai Zhang ◽  
Tamlin M. Pavelsky

Remote sensing of ice phenology for small lakes is hindered by a lack of satellite observations with both high temporal and spatial resolutions. By merging multi-source satellite data over individual lakes, we present a new algorithm that successfully estimates ice freeze and thaw timing for lakes with surface areas as small as 0.13 km2 and obtains consistent results across a range of lake sizes. We have developed an approach for classifying ice pixels based on the red reflectance band of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, with a threshold calibrated against ice fraction from Landsat Fmask over each lake. Using a filter derived from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) surface air temperature product, we removed outliers in the time series of lake ice fraction. The time series of lake ice fraction was then applied to identify lake ice breakup and freezeup dates. Validation results from over 296 lakes in Maine indicate that the satellite-based lake ice timing detection algorithm perform well, with mean absolute error (MAE) of 5.54 days for breakup dates and 7.31 days for freezeup dates. This algorithm can be applied to lakes worldwide, including the nearly two million lakes with surface area between 0.1 and 1 km2.

2018 ◽  
Vol 10 (10) ◽  
pp. 1641 ◽  
Author(s):  
Justin Murfitt ◽  
Laura Brown ◽  
Stephen Howell

Lake ice is an important component in understanding the local climate as changes in temperature have an impact on the timing of key ice phenology events. In recent years, there has been a decline in the in-situ monitoring of lake ice events in Canada and microwave remote sensing imagery from synthetic aperture radar (SAR) is more widely used due to the high spatial resolution and response of backscatter to the freezing and melting of the ice surface. RADARSAT-2 imagery was used to develop a threshold-based method for determining lake ice events for mid-latitude lakes in Central Ontario from 2008 to 2017. Estimated lake ice phenology events are validated with ground-based observations and are compared against the Moderate Resolution Imaging Spectroradiometer (MODIS band 2). The threshold-based method was found to accurately identify 12 out of 17 freeze events and 13 out of 17 melt events from 2015–2017 when compared to ground-based observations. Mean absolute errors for freeze events ranged from 2.5 to 10.0 days when compared to MODIS imagery while the mean absolute error for water clear of ice (WCI) ranged from 1.5 to 7.1 days. The method is important for the study of mid-latitude lake ice due to its unique success in detecting multiple freeze and melting events throughout the ice season.


2021 ◽  
Author(s):  
Abhay Prakash ◽  
Saeed Aminjafari ◽  
Nina Kirchner ◽  
Tarmo Virtanen ◽  
Jan Weckström ◽  
...  

<p>Lake Tarfala is a small (~0.5 km<sup>2</sup>) glacier-proximal lake in the Kebnekaise Mountains in Northern Sweden, located at an altitude of 1162 meters above sea level, and close to Tarfala Research Station run by Stockholm University. Only very limited direct monitoring of lake ice phenology using ground observations is available so far, and, long polar nights and often persistent cloud cover at such altitude limit the use of optical remote sensing. However, active microwave radar signals illuminate the target and penetrate through the cloud cover allowing to monitor the lake independent of weather or time of day. In this study, we opt for the Level-1 GRD (Ground Range Detected) and SLC (Single Look Complex) products from the twin Sentinel-1 satellites which provide a coverage of Lake Tarfala at a very high spatial and temporal resolution. We aim to make use of a total of 60 scenes (June 2020 - May 2021) to create the backscatter and coherence time series. Further, we aim to associate the variation in intensity seen in the backscatter time series to the backscattering potential of the medium. It has been shown [1] that an increase in intensity is observed when transitioning from ice-free waters to the initial freeze-up (ice-on) stage. Around ice-on, the intensity would, however, be comparatively low as the ice cover would be very thin and not yet fully developed. The availability of in-situ high-resolution time-lapse imagery and air temperature data from a pilot project carried out during the fall of 2020 [2] will be exploited to assist in the detection of the initial ice formation and freeze-up. Over the course of winter, ice will continue to thicken and a subsequent increase in backscatter intensity is expected until it reaches a saturation point where it stabilises, until the onset of melt in the subsequent spring/summer, when finally, the detection of ice-off (water free of ice) can be characterised by low backscatter values. Furthermore, loss of interferometric coherence upon the onset of melt will aid the backscatter time series when it fails to show a clear signal. We expect to track and provide a complete timeline of the different ice-phenology stages, namely the onset of freezing and the date of complete ice-on, the ice-thickening, the onset of surface melt and the date of complete ice-off. We expect that this study will provide a basis for Arctic lake ice monitoring for various applications such as management of winter water resources, understanding the seasonal and inter-annual land-atmosphere greenhouse gases and energy flux exchanges and biological productivity.</p><p>References:</p><p>1. Morris, K., Jeffries, M.O., Weeks, W.F. Ice processes and growth history on Arctic and sub-Arctic lakes using ERS-1 SAR data. Polar Rec. 1995, 31, 115-128.</p><p><br>2. Weckström, J., Korhola, A. Kirchner, N., Virtanen, T., Schenk, F., Granebeck, A., Prakash, A. “Lake Thermal and Mixing Dynamics under Changing Climate” and “Towards a multi-approach detection and classification of ice phenology at Lake Tarfala”. Pilot projects funded by Arctic Avenue (a spearhead research project between the University of Helsinki and Stockholm University).</p>


2021 ◽  
Author(s):  
Yubao Qiu ◽  
Xingxing Wang ◽  
Matti Leppäranta ◽  
Bin Cheng ◽  
Yixiao Zhang

<p>Lake-ice phenology is an essential indicator of climate change impact for different regions (Livingstone, 1997; Duguay, 2010), which helps understand the regional characters of synchrony and asynchrony. The observation of lake ice phenology includes ground observation and remote sensing inversion. Although some lakes have been observed for hundreds of years, due to the limitations of the observation station and the experience of the observers, ground observations cannot obtain the lake ice phenology of the entire lake. Remote sensing has been used for the past 40 years, in particular, has provided data covering the high mountain and high latitude regions, where the environment is harsh and ground observations are lacking. Remote sensing also provides a unified data source and monitoring standard, and the possibility of monitoring changes in lake ice in different regions and making comparisons between them. The existing remote sensing retrieval products mainly cover North America and Europe, and data for Eurasia is lacking (Crétaux et al., 2020).</p><p>Based on the passive microwave, the lake ice phenology of 522 lakes in the northern hemisphere during 1978-2020 was obtained, including Freeze-Up Start (FUS), Freeze-Up End (FUE), Break-Up Start (BUS), Break-Up End (BUE), and Ice Cover Duration (ICD). The ICD is the duration from the FUS to the BUE, which can directly reflect the ice cover condition. At latitudes north of 60°N, the average of ICD is approximately 8-9 months in North America and 5-6 months in Eurasia. Limited by the spatial resolution of the passive microwave, lake ice monitoring is mainly in Northern Europe. Therefore, the average of ICD over Eurasia is shorter, while the ICD is more than 6 months for most lakes in Russia. After 2000, the ICD has shown a shrinking trend, except northeastern North America (southeast of the Hudson Bay) and the northern Tibetan Plateau. The reasons for the extension of ice cover duration need to be analyzed with parameters, such as temperature, the lake area, and lake depth, in the two regions.</p>


2020 ◽  
Vol 12 (3) ◽  
pp. 382 ◽  
Author(s):  
Justin Murfitt ◽  
Claude R. Duguay

Lake ice is a dominant component of Canada’s landscape and can act as an indicator for how freshwater aquatic ecosystems are changing with warming climates. While lake ice monitoring through government networks has decreased in the last three decades, the increased availability of remote sensing images can help to provide consistent spatial and temporal coverage for areas with annual ice cover. Synthetic aperture radar (SAR) data are commonly used for lake ice monitoring, due to the acquisition of images in any condition (time of day or weather). Using Sentinel-1 A/B images, a high-density time series of SAR images was developed for Lake Hazen in Nunavut, Canada, from 2015–2018. These images were used to test two different methods of monitoring lake ice phenology: one method using the first difference between SAR images and another that applies the Otsu segmentation method. Ice phenology dates determined from the two methods were compared with visual interpretation of the Sentinel-1 images. Mean errors for the pixel comparison of the first difference method ranged 3–10 days for ice-on and ice-off, while average error values for the Otsu method ranged 2–10 days. Mean errors for comparisons of different sections of the lake ranged 0–15 days for the first difference method and 2–17 days for the Otsu method. This research demonstrates the value of temporally consistent image acquisition for improving the accuracy of lake ice monitoring.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Suhua Liu ◽  
Hongbo Su ◽  
Renhua Zhang ◽  
Jing Tian ◽  
Weizhen Wang

To estimate the surface air temperature by remote sensing, the advection-energy balance for the surface air temperature (ADEBAT) model is developed which assumes the surface air temperature is driven by the local driving force and the advective driving force. The local driving force produces a local surface air temperature whereas the advective driving force changes it by adding an exotic air temperature. An advection factorfis defined to measure the quantity of the exotic air brought by the advection. Since thefis determined by the advection, this paper improves it to a regional scale by using the Inverse Distance Weighting (IDW) method whereas the original ADEBAT model uses a constant offfor a block of area. Results retrieved by the improved ADEBAT (IADEBAT) model are evaluated and comparison was made with the in situ measurements, with anR2(correlation coefficient) of 0.77, an RMSE (Root Mean Square Error) of 0.31 K, and a MAE (Mean Absolute Error) of 0.24 K. The evaluation shows that the IADEBAT model has higher accuracy than the original ADEBAT model. Evaluations together with at-test of the MAD (Mean Absolute Deviation) reveal that the IADEBAT model has a significant improvement.


2021 ◽  
pp. 1-19
Author(s):  
Xingxing Wang ◽  
Yubao Qiu ◽  
Yixiao Zhang ◽  
Juha Lemmetyinen ◽  
Bin Cheng ◽  
...  

2019 ◽  
Vol 32 (9) ◽  
pp. 2553-2568 ◽  
Author(s):  
Yong Liu ◽  
Huopo Chen ◽  
Huijun Wang ◽  
Jianqi Sun ◽  
Hua Li ◽  
...  

Abstract Lake ice phenology, as an indicator for climate variability and change, exerts a great influence on regional climate and hydrometeorology. In this study, the changing characteristics of lake ice phenology at Lake Qinghai (LQH) are investigated using retrieved historical datasets during 1979–2016. The results show that the variation of the lake freeze-up date over LQH is characterized by a strong interannual variability. Further analysis has revealed that November sea ice concentration (SIC) variation in the Kara Sea can exert a great impact on the freeze-up date at LQH. During the low sea ice years, the open sea serves as a strong diabatic heating source, largely contributing to the enhanced Arctic Eliassen–Palmer flux, which then results in the deceleration of zonal wind in the middle and high latitudes. In addition to this, accompanied with the decreasing Kara SIC, the enhanced stationary Rossby wave flux propagating along the high-latitude regions may further exert remarkable influences in deepening the East Asian trough, which provides a favorable atmospheric circulation pattern for cold air intrusion from the Arctic and Siberian regions to mainland China. The decreased surface air temperature would thus advance the freezing date over LQH. Furthermore, the close relationship between atmospheric circulation anomalies and Kara SIC variations is validated by a large ensemble of simulations from the Community Earth System Model, and the atmospheric circulation patterns induced by the SIC anomalies are reproduced to some extent. Therefore, the November Kara Sea ice anomaly might be an important predictor for the variation in the freeze-up date at LQH.


Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1316
Author(s):  
Woubet G. Alemu ◽  
Michael C. Wimberly

Despite the sparse distribution of meteorological stations and issues with missing data, vector-borne disease studies in Ethiopia have been commonly conducted based on the relationships between these diseases and ground-based in situ measurements of climate variation. High temporal and spatial resolution satellite-based remote-sensing data is a potential alternative to address this problem. In this study, we evaluated the accuracy of daily gridded temperature and rainfall datasets obtained from satellite remote sensing or spatial interpolation of ground-based observations in relation to data from 22 meteorological stations in Amhara Region, Ethiopia, for 2003–2016. Famine Early Warning Systems Network (FEWS-Net) Land Data Assimilation System (FLDAS) interpolated temperature showed the lowest bias (mean error (ME) ≈ 1–3 °C), and error (mean absolute error (MAE) ≈ 1–3 °C), and the highest correlation with day-to-day variability of station temperature (COR ≈ 0.7–0.8). In contrast, temperature retrievals from the blended Advanced Microwave Scanning Radiometer on Earth Observing Satellite (AMSR-E) and Advanced Microwave Scanning Radiometer 2 (AMSR2) passive microwave and Moderate-resolution Imaging Spectroradiometer (MODIS) land-surface temperature data had higher bias and error. Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) rainfall showed the least bias and error (ME ≈ −0.2–0.2 mm, MAE ≈ 0.5–2 mm), and the best agreement (COR ≈ 0.8), with station rainfall data. In contrast FLDAS had the higher bias and error and the lowest agreement and Global Precipitation Mission/Tropical Rainfall Measurement Mission (GPM/TRMM) data were intermediate. This information can inform the selection of geospatial data products for use in climate and disease research and applications.


Author(s):  
Shuai Zhang ◽  
Tamlin M Pavelsky ◽  
Christopher D. Arp ◽  
Xiao Yang

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