Towards a global land surface climate fiducial reference measurements network

Thorne, Peter; Diamond, Howard J.; Goodison, B.; Harrigan, Shaun; Hausfather, Zeke; Ingleby, N. Bruce; Jones, Phil; Lawrimore, J. H.; Lister, David; Merlone, A.; Oakley, Tim; Palecki, Michael A.; Peterson, Thomas C.; Podesta, Michael de; Tassone, Caterina; Venema, Victor; Willett, Kate M.

doi:10.1002/joc.5458

Cited by 32 publications

(24 citation statements)

References 53 publications

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“…A further challenge is to identify some shipboard observations to serve as "reference" stations similar to what is being done in the land-surface community (e.g., Thorne et al, 2018). Most likely, these would be research vessels, but they should adhere to the highest standard for quality assessment/control.…”

Section: Evaluating Data Qualitymentioning

confidence: 99%

Ship-Based Contributions to Global Ocean, Weather, and Climate Observing Systems

et al. 2019

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The role ships play in atmospheric, oceanic, and biogeochemical observations is described with a focus on measurements made near the ocean surface. Ships include merchant and research vessels; cruise liners and ferries; fishing vessels; coast guard, military, and other government-operated ships; yachts; and a growing fleet of automated surface vessels. The present capabilities of ships to measure essential climate/ocean variables and the requirements from a broad community to address operational, commercial, and scientific needs are described. The authors provide a vision to expand observations needed from ships to understand and forecast the exchanges across the ocean-atmosphere interface. The vision addresses (1) recruiting vessels to improve both spatial and temporal sampling, (2) conducting multivariate sampling on ships, (3) raising technology readiness levels of automated shipboard sensors and ship-to-shore data communications, (4) advancing quality evaluation of observations, and (5) developing a unified data management approach for observations and metadata that meet the needs of a diverse user community. Recommendations are made focusing on integrating private and autonomous vessels into the observing system, investing in sensor and communications technology development, developing an integrated data management structure that includes all types of ships, and moving toward a quality evaluation process that will result in a subset of ships being defined as mobile reference ships that will support climate studies. We envision a future where commercial, research,

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Section: Evaluating Data Qualitymentioning

confidence: 99%

Ship-Based Contributions to Global Ocean, Weather, and Climate Observing Systems

et al. 2019

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“…As the data sets have grown in recent years (through digitization and synthesis of previously separate data streams; Freeman et al, 2016;Rennie et al, 2014;Thorne et al, 2018), and efforts have been made to improve data homogenization, bias corrections, and interpolation schemes, the sophistication of the uncertainty models has also grown. Notably, with the introduction of the Hadley Centre sea surface temperature (SST) analysis HadSST3 (Kennedy et al, 2011a(Kennedy et al, , 2011b, Berkeley Earth (Rohde et al, 2013a), and the joint Hadley Centre and University of East Anglia's Climatic Research Unit Hadley Centre/Climatic Research Unit 4 (HadCRUT4; Morice et al, 2012), Monte Carlo methodologies have been applied to generate observational ensembles that quantify uncertainties more comprehensively than was previously possible.…”

Section: Introductionmentioning

confidence: 99%

Improvements in the GISTEMP Uncertainty Model

et al. 2019

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We outline a new and improved uncertainty analysis for the Goddard Institute for Space Studies Surface Temperature product version 4 (GISTEMP v4). Historical spatial variations in surface temperature anomalies are derived from historical weather station data and ocean data from ships, buoys, and other sensors. Uncertainties arise from measurement uncertainty, changes in spatial coverage of the station record, and systematic biases due to technology shifts and land cover changes. Previously published uncertainty estimates for GISTEMP included only the effect of incomplete station coverage. Here, we update this term using currently available spatial distributions of source data, state‐of‐the‐art reanalyses, and incorporate independently derived estimates for ocean data processing, station homogenization, and other structural biases. The resulting 95% uncertainties are near 0.05 °C in the global annual mean for the last 50 years and increase going back further in time reaching 0.15 °C in 1880. In addition, we quantify the benefits and inherent uncertainty due to the GISTEMP interpolation and averaging method. We use the total uncertainties to estimate the probability for each record year in the GISTEMP to actually be the true record year (to that date) and conclude with 87% likelihood that 2016 was indeed the hottest year of the instrumental period (so far).

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“…The satellite community are important users of in situmeasured surface ECVs (e.g., Belmonte Rivas et al, 2007;Stoffelen et al, 2015;Jackson and Wick, 2016;Kinzel et al, 2016;Berry et al, 2018;Liman et al, 2018;Thorne et al, 2018), and recommendations that aim to improve the quantity, quality, and consistency of in situ data will be of huge benefit for satellite calibration and evaluation.…”

Section: Satellitesmentioning

confidence: 99%

Observing Requirements for Long-Term Climate Records at the Ocean Surface

et al. 2019

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Frontiers in Marine Science | www.frontiersin.org July 2019 | Volume 6 | Article 441 Kent et al. Long-Term Surface Marine Recordsbiases and to improve methods of construction of CDRs. The requirements developed in this paper encompass specific actions involving a variety of stakeholders, including funding agencies, scientists, data managers, observing network operators, satellite agencies, and international co-ordination bodies.

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Towards a global land surface climate fiducial reference measurements network

Cited by 32 publications

References 53 publications

Ship-Based Contributions to Global Ocean, Weather, and Climate Observing Systems

Ship-Based Contributions to Global Ocean, Weather, and Climate Observing Systems

Improvements in the GISTEMP Uncertainty Model

Observing Requirements for Long-Term Climate Records at the Ocean Surface

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