A new Level 4 multi-sensor ice surface temperature product for the Greenland Ice Sheet

Karagali, Ioanna; Suhr, Magnus Barfod; Mottram, Ruth; Nielsen‐Englyst, Pia; Dybkjær, Gorm; Ghent, Darren; Høyer, Jacob L.

doi:10.5194/tc-16-3703-2022

Cited by 3 publications

(1 citation statement)

References 41 publications

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“…The main objective of the LST_cci project is to provide a long-term LST data record using data from different thermal sensors meeting the Global Climate Observing System (GCOS) threshold for LST accuracy and precision, i.e., 1 K (GCOS, 2016, 2022). LST_cci data have been widely used in different studies, e.g., surface urban heat island [6][7][8], estimation of ice sheet mass [9], stability of thermal remote sensors [10] or evapotranspiration analysis [11]. Thus, in order to ensure the high quality of LST_cci products, all of them are assessed in the project by the LST_cci Validation Team.…”

Section: Introductionmentioning

confidence: 99%

Retrieval Consistency between LST CCI Satellite Data Products over Europe and Africa

et al. 2023

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The assessment of satellite-derived land surface temperature (LST) data is essential to ensure their high quality for climate applications and research. This study intercompared seven LST products (i.e., ATSR_3, MODISA, MODIST, SLSTRA, SLSTRB, SEVIR2 and SEVIR4) of the European Space Agency’s (ESA) LST Climate Change Initiative (LST_cci) project, which are retrieved for polar and geostationary orbit satellites, and three operational LST products: NASA’s MODIS MOD11/MYD11 LST and ESA’s AATSR LST. All data were re-gridded on to a common spatial grid of 0.05° and matched for concurrent overpasses within 5 min. The matched data were analysed over Europe and Africa for monthly and seasonally aggregated median differences and studied for their dependence on land cover class and satellite viewing geometry. For most of the data sets, the results showed an overall agreement within ±2 K for median differences and robust standard deviation (RSD). A seasonal variation of median differences between polar and geostationary orbit sensor data was observed over Europe, which showed higher differences in summer and lower in winter. Over all land cover classes, NASA’s operational MODIS LST products were about 2 K colder than the LST_cci data sets. No seasonal differences were observed for the different land covers, but larger median differences between data sets were seen over bare soil land cover classes. Regarding the viewing geometry, an asymmetric increase of differences with respect to nadir view was observed for day-time data, which is mainly caused by shadow effects. For night-time data, these differences were symmetric and considerably smaller. Overall, despite the differences in the LST retrieval algorithms of the intercompared data sets, a good consistency between the LST_cci data sets was determined.

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Section: Introductionmentioning

confidence: 99%

Retrieval Consistency between LST CCI Satellite Data Products over Europe and Africa

et al. 2023

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Monthly variability of wind-induced upwelling and its impact on chlorophyll-a distribution in the Southern and Northern parts of the Indonesian Archipelago

Napitupulu

2024

Ocean Dynamics

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Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals

Raoult¹,

Charbit²,

Dumas³

et al. 2023

The Cryosphere

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Abstract. Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise modelled albedo over the entirety of the ice sheet. We optimise the parameters of the albedo scheme in the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) land surface model for 3 random years taken over the 2000–2017 period and validate over the remaining years. In particular, we want to improve the albedo at the edges of the ice sheet, since they correspond to ablation areas and show the greatest variations in runoff and surface mass balance. By giving a larger weight to points at the ice sheet's edge, we improve the model–data fit by reducing the root-mean-square deviation by over 25 % for the whole ice sheet for the summer months. This improvement is consistent for all years, even those not used in the calibration step. We also show the optimisation successfully improves the model–data fit at 87.5 % of in situ sites from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) network. We conclude by showing which additional model outputs are impacted by changes to the albedo parameters, encouraging future work using multiple data streams when optimising these parameters.

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A new Level 4 multi-sensor ice surface temperature product for the Greenland Ice Sheet

Cited by 3 publications

References 41 publications

Retrieval Consistency between LST CCI Satellite Data Products over Europe and Africa

Retrieval Consistency between LST CCI Satellite Data Products over Europe and Africa

Monthly variability of wind-induced upwelling and its impact on chlorophyll-a distribution in the Southern and Northern parts of the Indonesian Archipelago

Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals

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