The AVHRR Polar Pathfinder Climate Data Records

Key, Jeffrey R.; Wang, Xuanji; Liu, Yinghui; Dworak, Richard; Letterly, Aaron

doi:10.3390/rs8030167

Cited by 57 publications

(62 citation statements)

References 36 publications

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“…OTIM utilizes data from optical (visible, near-infrared, and thermal infrared) satellite instruments such as the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA) family of Polar-orbiting Operational Environmental Satellites (POES), and is incorporated in the AVHRR Polar Pathfinder-extended (APP-x) dataset that covers the period 1982 through the present [14]. This is a very different approach than those used with ICESat, Cryosat-2, IceBridge, and SMOS.…”

mentioning

confidence: 99%

Comparison of Arctic Sea Ice Thickness from Satellites, Aircraft, and PIOMAS Data

et al. 2016

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Abstract:In this study, six Arctic sea ice thickness products are compared: the AVHRR Polar Pathfinder-extended (APP-x), ICESat, CryoSat-2, SMOS, NASA IceBridge aircraft flights, and the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). The satellite products are based on three different retrieval methods: an energy budget approach, measurements of ice freeboard, and the relationship between passive microwave brightness temperatures and thin ice thickness.

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confidence: 99%

Comparison of Arctic Sea Ice Thickness from Satellites, Aircraft, and PIOMAS Data

et al. 2016

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“…The mean APP-x [19] albedos of the melted and surviving parcels in this study are shown in Figure 10. The albedos in the melted populations were lower than the surviving parcel population means, which led to greater energy input for equal radiative forcing at the surface in the melted population.…”

Section: Surface Albedosmentioning

confidence: 99%

“…Downwelling shortwave and longwave radiative fluxes were obtained from the APP-x dataset [19]. Mean downwelling shortwave radiative fluxes for melted and surviving parcels were very similar for all years in the study period (Figure 8).…”

Section: Downwelling Radiative Fluxesmentioning

confidence: 99%

“…Albedo is corrected for clouds, and is derived through the procedures described in [20]. Comparisons of APP-x albedos with SHEBA measurements yielded a bias of −0.05 and an RMSE of 0.1 [19]. Downwelling shortwave and longwave fluxes at the surface are computed using FluxNet: a neural network that was trained to simulate a radiative model [21] …”

Section: App-x Productsmentioning

confidence: 99%

“…Broadband albedo, downwelling shortwave, and downwelling longwave are obtained from the AVHRR Polar Pathfinder-Extended (APP-x) dataset [18,19]. The data are provided on a 25 km EASE-Grid that is re-gridded to a 12.5 km grid by splitting each 25 km grid cell into four equal-valued cells [13].…”

Section: App-x Productsmentioning

confidence: 99%

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Investigating Arctic Sea Ice Survivability in the Beaufort Sea

Tooth

Tschudi

2018

Remote Sensing

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Arctic sea ice extent has continued to decline in recent years, and the fractional coverage of multi-year sea ice has decreased significantly during this period. The Beaufort Sea region has been the site of much of the loss of multi-year sea ice, and it continues to play a large role in the extinction of ice during the melt season. We present an analysis of the influence of satellite-derived ice surface temperature, ice thickness, albedo, and downwelling longwave/shortwave radiation as well as latitude and airborne snow depth estimates on the change in sea ice concentration in the Beaufort Sea from 2009 to 2016 using a Lagrangian tracking database. Results from this analysis indicate that parcels that melt during summer in the Beaufort Sea reside at lower latitudes and have lower ice thickness at the beginning of the melt season in most cases. The influence of sea ice thickness and snow depth observed by IceBridge offers less conclusive results, with some years exhibiting higher thicknesses/depths for melted parcels. Parcels that melted along IceBridge tracks do exhibit lower latitudes and ice thicknesses, however, which indicates that earlier melt and breakup of ice may contribute to a greater likelihood of extinction of parcels in the summer.

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An intercomparison and validation of satellite‐based surface radiative energy flux estimates over the Arctic

et al. 2017

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Accurate determination of radiative energy fluxes over the Arctic is of crucial importance for understanding atmosphere‐surface interactions, melt and refreezing cycles of the snow and ice cover, and the role of the Arctic in the global energy budget. Satellite‐based estimates can provide comprehensive spatiotemporal coverage, but the accuracy and comparability of the existing data sets must be ascertained to facilitate their use. Here we compare radiative flux estimates from Clouds and the Earth's Radiant Energy System (CERES) Synoptic 1‐degree (SYN1deg)/Energy Balanced and Filled, Global Energy and Water Cycle Experiment (GEWEX) surface energy budget, and our own experimental FluxNet / Satellite Application Facility on Climate Monitoring cLoud, Albedo and RAdiation (CLARA) data against in situ observations over Arctic sea ice and the Greenland Ice Sheet during summer of 2007. In general, CERES SYN1deg flux estimates agree best with in situ measurements, although with two particular limitations: (1) over sea ice the upwelling shortwave flux in CERES SYN1deg appears to be underestimated because of an underestimated surface albedo and (2) the CERES SYN1deg upwelling longwave flux over sea ice saturates during midsummer. The Advanced Very High Resolution Radiometer‐based GEWEX and FluxNet‐CLARA flux estimates generally show a larger range in retrieval errors relative to CERES, with contrasting tendencies relative to each other. The largest source of retrieval error in the FluxNet‐CLARA downwelling shortwave flux is shown to be an overestimated cloud optical thickness. The results illustrate that satellite‐based flux estimates over the Arctic are not yet homogeneous and that further efforts are necessary to investigate the differences in the surface and cloud properties which lead to disagreements in flux retrievals.

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The AVHRR Polar Pathfinder Climate Data Records

Cited by 57 publications

References 36 publications

Comparison of Arctic Sea Ice Thickness from Satellites, Aircraft, and PIOMAS Data

Comparison of Arctic Sea Ice Thickness from Satellites, Aircraft, and PIOMAS Data

Investigating Arctic Sea Ice Survivability in the Beaufort Sea

An intercomparison and validation of satellite‐based surface radiative energy flux estimates over the Arctic

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