Articles | Volume 23, issue 5
https://doi.org/10.5194/hess-23-2401-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-2401-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
17 May 2019
Review article |
| 17 May 2019
| 17 May 2019
The recent developments in cloud removal approaches of MODIS snow cover product
Xinghua Li
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Yinghong Jing
School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
Huanfeng Shen
CORRESPONDING AUTHOR
School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
Liangpei Zhang
State Key Laboratory of Information Engineering in Surveying, Mapping and
Remote Sensing, Wuhan University, Wuhan, China
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Earth Syst. Sci. Data, 14, 3137–3156, https://doi.org/10.5194/essd-14-3137-2022, https://doi.org/10.5194/essd-14-3137-2022, 2022
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Snow variation is a vital factor in global climate change. Satellite-based approaches are effective for large-scale environmental monitoring. Nevertheless, the high cloud fraction seriously impedes the remote-sensed investigation. Therefore, a recent 20-year cloud-free snow cover collection in China is generated for the first time. This collection can serve as a basic dataset for hydrological and climatic modeling to explore various critical environmental issues.
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Investigations in central and western China show that tree ring inverted latewood intensity expresses a strong positive relationship with growing-season temperatures, indicating exciting potential for regions south of 30° N that are traditionally not targeted for temperature reconstructions. Earlywood BI also shows good potential to reconstruct hydroclimate parameters in some humid areas and will enhance ring-width-based hydroclimate reconstructions in the future.
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The semi-empirical physical approach derives PM2.5 with strong physical significance. However, due to the complex optical characteristic, the physical parameters are difficult to express accurately. Thus, combining the atmospheric physical mechanism and machine learning, we propose an optimized model. It creatively embeds the random forest model into the physical PM2.5 remote sensing approach to simulate a physical parameter. Our method shows great optimized performance in the validations.
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Earth Syst. Sci. Data, 14, 3137–3156, https://doi.org/10.5194/essd-14-3137-2022, https://doi.org/10.5194/essd-14-3137-2022, 2022
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Y. Tao, W. Huang, W. Gan, and H. Shen
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Related subject area
Subject: Snow and Ice | Techniques and Approaches: Remote Sensing and GIS
Detecting snowfall events over the Arctic using optical and microwave satellite measurements
Extending the utility of space-borne snow water equivalent observations over vegetated areas with data assimilation
Assimilation of airborne gamma observations provides utility for snow estimation in forested environments
Characterizing 4 decades of accelerated glacial mass loss in the west Nyainqentanglha Range of the Tibetan Plateau
Estimating spatiotemporally continuous snow water equivalent from intermittent satellite observations: an evaluation using synthetic data
Development and validation of a new MODIS snow-cover-extent product over China
Processes governing snow ablation in alpine terrain – detailed measurements from the Canadian Rockies
Evaluation of MODIS and VIIRS cloud-gap-filled snow-cover products for production of an Earth science data record
Characterising spatio-temporal variability in seasonal snow cover at a regional scale from MODIS data: the Clutha Catchment, New Zealand
Icelandic snow cover characteristics derived from a gap-filled MODIS daily snow cover product
Now you see it, now you don't: a case study of ephemeral snowpacks and soil moisture response in the Great Basin, USA
Assessment of a multiresolution snow reanalysis framework: a multidecadal reanalysis case over the upper Yampa River basin, Colorado
Snow cover dynamics in Andean watersheds of Chile (32.0–39.5° S) during the years 2000–2016
A new remote hazard and risk assessment framework for glacial lakes in the Nepal Himalaya
A snow cover climatology for the Pyrenees from MODIS snow products
Cloud obstruction and snow cover in Alpine areas from MODIS products
Application of MODIS snow cover products: wildfire impacts on snow and melt in the Sierra Nevada
LiDAR measurement of seasonal snow accumulation along an elevation gradient in the southern Sierra Nevada, California
Early 21st century snow cover state over the western river basins of the Indus River system
Validation of the operational MSG-SEVIRI snow cover product over Austria
Reducing cloud obscuration of MODIS snow cover area products by combining spatio-temporal techniques with a probability of snow approach
CREST-Snow Field Experiment: analysis of snowpack properties using multi-frequency microwave remote sensing data
Snow cover dynamics and hydrological regime of the Hunza River basin, Karakoram Range, Northern Pakistan
Responses of snowmelt runoff to climatic change in an inland river basin, Northwestern China, over the past 50 years
Assessing the application of a laser rangefinder for determining snow depth in inaccessible alpine terrain
Emmihenna Jääskeläinen, Kerttu Kouki, and Aku Riihelä
Hydrol. Earth Syst. Sci., 28, 3855–3870, https://doi.org/10.5194/hess-28-3855-2024, https://doi.org/10.5194/hess-28-3855-2024, 2024
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Snow cover is an important variable when studying the effect of climate change in the Arctic. Therefore, the correct detection of snowfall is important. In this study, we present methods to detect snowfall accurately using satellite observations. The snowfall event detection results of our limited area are encouraging. We find that further development could enable application over the whole Arctic, providing necessary information on precipitation occurrence over remote areas.
Justin M. Pflug, Melissa L. Wrzesien, Sujay V. Kumar, Eunsang Cho, Kristi R. Arsenault, Paul R. Houser, and Carrie M. Vuyovich
Hydrol. Earth Syst. Sci., 28, 631–648, https://doi.org/10.5194/hess-28-631-2024, https://doi.org/10.5194/hess-28-631-2024, 2024
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Estimates of 250 m of snow water equivalent in the western USA and Canada are improved by assimilating observations representative of a snow-focused satellite mission with a land surface model. Here, by including a gap-filling strategy, snow estimates could be improved in forested regions where remote sensing is challenging. This approach improved estimates of winter maximum snow water volume to within 4 %, on average, with persistent improvements to both spring snow and runoff in many regions.
Eunsang Cho, Yonghwan Kwon, Sujay V. Kumar, and Carrie M. Vuyovich
Hydrol. Earth Syst. Sci., 27, 4039–4056, https://doi.org/10.5194/hess-27-4039-2023, https://doi.org/10.5194/hess-27-4039-2023, 2023
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An airborne gamma-ray remote-sensing technique provides reliable snow water equivalent (SWE) in a forested area where remote-sensing techniques (e.g., passive microwave) typically have large uncertainties. Here, we explore the utility of assimilating the gamma snow data into a land surface model to improve the modeled SWE estimates in the northeastern US. Results provide new insights into utilizing the gamma SWE data for enhanced land surface model simulations in forested environments.
Shuhong Wang, Jintao Liu, Hamish D. Pritchard, Linghong Ke, Xiao Qiao, Jie Zhang, Weihua Xiao, and Yuyan Zhou
Hydrol. Earth Syst. Sci., 27, 933–952, https://doi.org/10.5194/hess-27-933-2023, https://doi.org/10.5194/hess-27-933-2023, 2023
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We assessed and compared the glacier areal retreat rate and surface thinning rate and the effects of topography, debris cover and proglacial lakes in the west Nyainqentanglha Range (WNT) during 1976–2000 and 2000–2020. Our study will help us to better understand the glacier change characteristics in the WNT on a long timescale and will serve as a reference for glacier changes in other regions on the Tibetan Plateau.
Xiaoyu Ma, Dongyue Li, Yiwen Fang, Steven A. Margulis, and Dennis P. Lettenmaier
Hydrol. Earth Syst. Sci., 27, 21–38, https://doi.org/10.5194/hess-27-21-2023, https://doi.org/10.5194/hess-27-21-2023, 2023
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We explore satellite retrievals of snow water equivalent (SWE) along hypothetical ground tracks that would allow estimation of SWE over an entire watershed. The retrieval of SWE from satellites has proved elusive, but there are now technological options that do so along essentially one-dimensional tracks. We use machine learning (ML) algorithms as the basis for a track-to-area (TTA) transformation and show that at least one is robust enough to estimate domain-wide SWE with high accuracy.
Xiaohua Hao, Guanghui Huang, Zhaojun Zheng, Xingliang Sun, Wenzheng Ji, Hongyu Zhao, Jian Wang, Hongyi Li, and Xiaoyan Wang
Hydrol. Earth Syst. Sci., 26, 1937–1952, https://doi.org/10.5194/hess-26-1937-2022, https://doi.org/10.5194/hess-26-1937-2022, 2022
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We develop and validate a new 20-year MODIS snow-cover-extent product over China, which is dedicated to addressing known problems of the standard snow products. As expected, the new product significantly outperforms the state-of-the-art MODIS C6.1 products; improvements are particularly clear in forests and for the daily cloud-free product. Our product has provided more reliable snow knowledge over China and can be accessible freely https://dx.doi.org/10.11888/Snow.tpdc.271387.
Michael Schirmer and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 143–157, https://doi.org/10.5194/hess-24-143-2020, https://doi.org/10.5194/hess-24-143-2020, 2020
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The spatial distribution of snow water equivalent (SWE) and melt are important for hydrological applications in alpine terrain. We measured the spatial distribution of melt using a drone in very high resolution and could relate melt to topographic characteristics. Interestingly, melt and SWE were not related spatially, which influences the speed of areal melt out. We could explain this by melt varying over larger distances than SWE.
Dorothy K. Hall, George A. Riggs, Nicolo E. DiGirolamo, and Miguel O. Román
Hydrol. Earth Syst. Sci., 23, 5227–5241, https://doi.org/10.5194/hess-23-5227-2019, https://doi.org/10.5194/hess-23-5227-2019, 2019
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Global snow cover maps have been available since 2000 from the MODerate resolution Imaging Spectroradiometer (MODIS), and since 2000 and 2011 from the Suomi National Polar-orbiting Partnership (S-NPP) and the Visible Infrared Imaging Radiometer Suite (VIIRS), respectively. These products are used extensively in hydrological modeling and climate studies. New, daily cloud-gap-filled snow products are available from both MODIS and VIIRS, and are being used to develop an Earth science data record.
Todd A. N. Redpath, Pascal Sirguey, and Nicolas J. Cullen
Hydrol. Earth Syst. Sci., 23, 3189–3217, https://doi.org/10.5194/hess-23-3189-2019, https://doi.org/10.5194/hess-23-3189-2019, 2019
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Spatio-temporal variability of seasonal snow cover is characterised from 16 years of MODIS data for the Clutha Catchment, New Zealand. No trend was detected in snow-covered area. Spatial modes of variability reveal the role of anomalous winter airflow. The sensitivity of snow cover duration to temperature and precipitation variability is found to vary spatially across the catchment. These findings provide new insight into seasonal snow processes in New Zealand and guidance for modelling efforts.
Andri Gunnarsson, Sigurður M. Garðarsson, and Óli G. B. Sveinsson
Hydrol. Earth Syst. Sci., 23, 3021–3036, https://doi.org/10.5194/hess-23-3021-2019, https://doi.org/10.5194/hess-23-3021-2019, 2019
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In this study a gap-filled snow cover product for Iceland is developed using MODIS satellite data and validated with both in situ observations and alternative remote sensing data sources with good agreement. Information about snow cover extent, duration and changes over time is presented, indicating that snow cover extent has been increasing slightly for the past few years.
Rose Petersky and Adrian Harpold
Hydrol. Earth Syst. Sci., 22, 4891–4906, https://doi.org/10.5194/hess-22-4891-2018, https://doi.org/10.5194/hess-22-4891-2018, 2018
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Ephemeral snowpacks are snowpacks that persist for less than 2 months. We show that ephemeral snowpacks melt earlier and provide less soil water input in the spring. Elevation is strongly correlated with whether snowpacks are ephemeral or seasonal. Snowpacks were also more likely to be ephemeral on south-facing slopes than north-facing slopes at high elevations. In warm years, the Great Basin shifts to ephemerally dominant as rain becomes more prevalent at increasing elevations.
Elisabeth Baldo and Steven A. Margulis
Hydrol. Earth Syst. Sci., 22, 3575–3587, https://doi.org/10.5194/hess-22-3575-2018, https://doi.org/10.5194/hess-22-3575-2018, 2018
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Montane snowpacks are extremely complex to represent and usually require assimilating remote sensing images at very fine spatial resolutions, which is computationally expensive. Adapting the grid size of the terrain to its complexity was shown to cut runtime and storage needs by half while preserving the accuracy of ~ 100 m snow estimates. This novel approach will facilitate the large-scale implementation of high-resolution remote sensing data assimilation over snow-dominated montane ranges.
Alejandra Stehr and Mauricio Aguayo
Hydrol. Earth Syst. Sci., 21, 5111–5126, https://doi.org/10.5194/hess-21-5111-2017, https://doi.org/10.5194/hess-21-5111-2017, 2017
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In Chile there is a lack of hydrological data, which complicates the analysis of important hydrological processes. In this study we validate a remote sensing product, i.e. the MODIS snow product, in Chile using ground observations, obtaining good results. Then MODIS was use to evaluated snow cover dynamic during 2000–2016 at five watersheds in Chile. The analysis shows that there is a significant reduction in snow cover area in two watersheds located in the northern part of the study area.
David R. Rounce, Daene C. McKinney, Jonathan M. Lala, Alton C. Byers, and C. Scott Watson
Hydrol. Earth Syst. Sci., 20, 3455–3475, https://doi.org/10.5194/hess-20-3455-2016, https://doi.org/10.5194/hess-20-3455-2016, 2016
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Glacial lake outburst floods pose a significant threat to downstream communities and infrastructure as they rapidly unleash stored lake water. Nepal is home to many potentially dangerous glacial lakes, yet a holistic understanding of the hazards faced by these lakes is lacking. This study develops a framework using remotely sensed data to investigate the hazards and risks associated with each glacial lake and discusses how this assessment may help inform future management actions.
S. Gascoin, O. Hagolle, M. Huc, L. Jarlan, J.-F. Dejoux, C. Szczypta, R. Marti, and R. Sánchez
Hydrol. Earth Syst. Sci., 19, 2337–2351, https://doi.org/10.5194/hess-19-2337-2015, https://doi.org/10.5194/hess-19-2337-2015, 2015
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There is a good agreement between the MODIS snow products and observations from automatic stations and Landsat snow maps in the Pyrenees. The optimal thresholds for which a MODIS pixel is marked as snow-covered are 40mm in water equivalent and 150mm in snow depth.
We generate a gap-filled snow cover climatology for the Pyrenees. We compute the mean snow cover duration by elevation and aspect classes. We show anomalous snow patterns in 2012 and consequences on hydropower production.
P. Da Ronco and C. De Michele
Hydrol. Earth Syst. Sci., 18, 4579–4600, https://doi.org/10.5194/hess-18-4579-2014, https://doi.org/10.5194/hess-18-4579-2014, 2014
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The negative impacts of cloud obstruction in snow mapping from MODIS and a new reliable cloud removal procedure for the Italian Alps.
P. D. Micheletty, A. M. Kinoshita, and T. S. Hogue
Hydrol. Earth Syst. Sci., 18, 4601–4615, https://doi.org/10.5194/hess-18-4601-2014, https://doi.org/10.5194/hess-18-4601-2014, 2014
P. B. Kirchner, R. C. Bales, N. P. Molotch, J. Flanagan, and Q. Guo
Hydrol. Earth Syst. Sci., 18, 4261–4275, https://doi.org/10.5194/hess-18-4261-2014, https://doi.org/10.5194/hess-18-4261-2014, 2014
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In this study we present results from LiDAR snow depth measurements made over 53 sq km and a 1600 m elevation gradient. We found a lapse rate of 15 cm accumulated snow depth and 6 cm SWE per 100 m in elevation until 3300 m, where depth sharply decreased. Residuals from this trend revealed the role of aspect and highlighted the importance of solar radiation and wind for snow distribution. Lastly, we compared LiDAR SWE estimations with four model estimates of SWE and total precipitation.
S. Hasson, V. Lucarini, M. R. Khan, M. Petitta, T. Bolch, and G. Gioli
Hydrol. Earth Syst. Sci., 18, 4077–4100, https://doi.org/10.5194/hess-18-4077-2014, https://doi.org/10.5194/hess-18-4077-2014, 2014
S. Surer, J. Parajka, and Z. Akyurek
Hydrol. Earth Syst. Sci., 18, 763–774, https://doi.org/10.5194/hess-18-763-2014, https://doi.org/10.5194/hess-18-763-2014, 2014
V. López-Burgos, H. V. Gupta, and M. Clark
Hydrol. Earth Syst. Sci., 17, 1809–1823, https://doi.org/10.5194/hess-17-1809-2013, https://doi.org/10.5194/hess-17-1809-2013, 2013
T. Y. Lakhankar, J. Muñoz, P. Romanov, A. M. Powell, N. Y. Krakauer, W. B. Rossow, and R. M. Khanbilvardi
Hydrol. Earth Syst. Sci., 17, 783–793, https://doi.org/10.5194/hess-17-783-2013, https://doi.org/10.5194/hess-17-783-2013, 2013
A. A. Tahir, P. Chevallier, Y. Arnaud, and B. Ahmad
Hydrol. Earth Syst. Sci., 15, 2275–2290, https://doi.org/10.5194/hess-15-2275-2011, https://doi.org/10.5194/hess-15-2275-2011, 2011
J. Wang, H. Li, and X. Hao
Hydrol. Earth Syst. Sci., 14, 1979–1987, https://doi.org/10.5194/hess-14-1979-2010, https://doi.org/10.5194/hess-14-1979-2010, 2010
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Short summary
This paper is a review article on the cloud removal methods of MODIS snow cover products.
This paper is a review article on the cloud removal methods of MODIS snow cover products.
