Best Practices in Crafting the Calibrated, Enhanced-Resolution Passive-Microwave EASE-Grid 2.0 Brightness Temperature Earth System Data Record

Brodzik, M. J.; Long, D.G.; Hardman, M.

doi:10.3390/rs10111793

Cited by 34 publications

(38 citation statements)

References 23 publications

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“…The ice melt over Greenland is inspected using the 25 km resolution AMSR‐E Brightness temperature (TB) product at 36 GHz horizontal polarization for the night path (around 0100 UTC) on board the AQUA satellite. These observations have 25x25 km spatial resolution and can be downloaded from the webpage of the National Snow and Ice Data Center (Brodzik et al, ).…”

Section: Data Sourcesmentioning

confidence: 99%

Polar Jet Associated Circulation Triggered a Saharan Cyclone and Derived the Poleward Transport of the African Dust Generated by the Cyclone

et al. 2018

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In this study, we identify a new mechanism by which dust aerosols travel over long distances across the eastern side of the North Atlantic Ocean toward the Arctic. The meandering polar jet was at the origin of both dust emission through cyclogenesis over Northwest Africa and poleward transport of the uplifted dust toward the Arctic, through cut-off circulation. The dust emission was associated with an intense

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Section: Data Sourcesmentioning

confidence: 99%

Polar Jet Associated Circulation Triggered a Saharan Cyclone and Derived the Poleward Transport of the African Dust Generated by the Cyclone

et al. 2018

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“…This data record is a temporally extensive consortium of images from multiple sensors and platforms. The spatial resolution of the 19 and 37 GHz Tb channels used in this study are improved from the original 25-km resolution Tb format through spatially enhanced interpolation of overlapping Tb antenna patterns and regridding at 6.25 km (19 GHz) and 3.125 km (37 GHz) resolution in a northern polar EASE-grid format using the scatterometer image reconstruction (SIR) technique [43].…”

Section: Passive Microwave Record 1988-2016mentioning

confidence: 99%

A Long-Term Passive Microwave Snowoff Record for the Alaska Region 1988–2016

et al. 2020

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Snowoff (SO) date—defined as the last day of observed seasonal snow cover—is an important governor of ecologic and hydrologic processes across Alaska and Arctic-Boreal landscapes; however, our understanding and capacity for the monitoring of spatial and temporal variability in the SO date is still lacking. In this study, we present a 6.25 km spatially gridded passive microwave (PMW) SO data record, complimenting current Alaskan SO records from Moderate Resolution Imaging Spectrometer (MODIS) and Landsat, but extending the SO record an additional 13 years. The PMW SO record was validated against in situ snow depth observations and showed favorable accuracy (0.66–0.92 mean correlations; 2–10 day mean absolute errors) for the major climate regions of Alaska. The PMW SO results were also within 10 days of finer spatial scale SO observational records, including Interactive Multisensor Snow and Ice Mapping System (IMS), MODIS, and Landsat, for a majority (75%) of Alaska. However, the PMW record showed a general SO delay at higher elevations and across the Alaska North Slope, and earlier SO in the Alaska interior and southwest regions relative to the other SO records. Overall, we assign an uncertainty +/−11 days to the PMW SO. The PMW SO record benefits from the near-daily temporal fidelity of underlying brightness temperature (Tb) observations and reveals a mean regional trend in earlier SO timing (−0.39 days yr−1), while significant (p < 0.1) SO trend areas encompassed 11% of the Alaska domain and ranged from −0.11 days yr−1 to −1.31 days yr−1 over the 29-year satellite record. The observed SO dates also showed anomalous early SO dates during markedly warm years. Our results clarify the pattern and rate of SO changes across Alaska, which are interactive with global warming and contributing to widespread permafrost degradation, changes in regional hydrology, ecosystems, and associated services. Our results also provide a robust means for SO monitoring from satellite PMW observations with similar precision as more traditional and finer scale observations.

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“…As observed brightness temperatures, we use Calibrated Passive Microwave Daily EASE-Grid 2.0 (CETB) brightness temperatures processed as part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program (Brodzik et al, 2016(Brodzik et al, , updated 2018. They are an improved, enhanced-resolution, gridded passive microwave Earth System Data Record (ESDR) for monitoring cryospheric and hydrologic time series from the measure-ment devices Scanning Multi-channel Microwave Radiometer (SMMR), Special Sensor Microwave Imager/Sounder (SSM/I-SSMIS), and Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR-E).…”

Section: Observation Datamentioning

confidence: 99%

The Arctic Ocean Observation Operator for 6.9 GHz (ARC3O) – Part 2: Development and evaluation

et al. 2020

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Abstract. The observational uncertainty in sea ice concentration estimates from remotely sensed passive microwave brightness temperatures is a challenge for reliable climate model evaluation and initialization. To address this challenge, we introduce a new tool: the Arctic Ocean Observation Operator (ARC3O). ARC3O allows us to simulate brightness temperatures at 6.9 GHz at vertical polarization from standard output of an Earth System Model. To evaluate sources of uncertainties when applying ARC3O, we compare brightness temperatures simulated by applying ARC3O on three assimilation runs of the MPI Earth System Model (MPI-ESM), assimilated with three different sea ice concentration products, with brightness temperatures measured by the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) from space. We find that the simulated and observed brightness temperatures differ up to 10 K in the period between October and June, depending on the region and the assimilation run. We show that these discrepancies between simulated and observed brightness temperature can be attributed mainly to the underlying observational uncertainty in sea ice concentration and, to a lesser extent, to the data assimilation process, rather than to biases in ARC3O itself. In summer, the discrepancies between simulated and observed brightness temperatures are larger than in winter and locally reach up to 20 K. This is caused by the very large observational uncertainty in summer sea ice concentration and the melt pond parametrization in MPI-ESM, which is not necessarily realistic. ARC3O is therefore capable of realistically translating the simulated Arctic Ocean climate state into one observable quantity for a more comprehensive climate model evaluation and initialization.

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Best Practices in Crafting the Calibrated, Enhanced-Resolution Passive-Microwave EASE-Grid 2.0 Brightness Temperature Earth System Data Record

Cited by 34 publications

References 23 publications

Polar Jet Associated Circulation Triggered a Saharan Cyclone and Derived the Poleward Transport of the African Dust Generated by the Cyclone

Polar Jet Associated Circulation Triggered a Saharan Cyclone and Derived the Poleward Transport of the African Dust Generated by the Cyclone

A Long-Term Passive Microwave Snowoff Record for the Alaska Region 1988–2016

The Arctic Ocean Observation Operator for 6.9 GHz (ARC3O) – Part 2: Development and evaluation

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