Observations for Reanalyses

Brönnimann, Stefan; Allan, Rob; Atkinson, C. P.; Buizza, Roberto; Bulygina, Olga; Dahlgren, Per; Dee, Dick; Dunn, Robert; Gomes, Pedro T.; John, Viju O.; Jourdain, Sylvie; Haimberger, Leopold; Hersbach, Hans; Kennedy, John J.; Poli, Paul; Pulliainen, Jouni; Rayner, Nick; Saunders, Roger; Schulz, Jörg B.; Sterin, Alexander; Stickler, Alexander; Titchner, Holly A.; Valente, M. A.; Ventura, Clara; Wilkinson, Clive

doi:10.1175/bams-d-17-0229.1

Cited by 40 publications

(37 citation statements)

References 35 publications

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“…These documents include dedicated meteorological logbooks as well as common ships' logbooks, meteorological forms, whale catch books, day reports, ice reports, ice charts, and other relevant items. Types and frequency of observations will vary from one document to another but typically there is barometric pressure and air, temperature, wind direction and force, weather, cloud cover, SST, sea state and swell, sometimes salinity and biological observations, sea ice, and icebergs (Bronnimann et al, ). To tackle the unavoidable issue of the ever‐changing observational network, a whitelisting approach to data selection for reanalyses covering the whole twentieth century has been developed.…”

Section: Introductionmentioning

confidence: 99%

CERA‐20C: A Coupled Reanalysis of the Twentieth Century

Laloyaux

Boisséson

Balmaseda

et al. 2018

J Adv Model Earth Syst

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248

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CERA-20C is a coupled reanalysis of the twentieth century which aims to reconstruct the past weather and climate of the Earth system including the atmosphere, ocean, land, ocean waves, and sea ice. This reanalysis is based on the CERA coupled atmosphere-ocean assimilation system developed at ECMWF. CERA-20C provides a 10 member ensemble of reanalyses to account for errors in the observational record as well as model error. It benefited from the prior experience of the retrospective atmospheric analysis ERA-20C. The dynamical model and the data assimilation systems initially developed for NWP had been modified to take into account the evolution of the radiative forcing and the observing system. To limit the impact of changes in the observing system throughout the century, only conventional surface observations have been used in the atmosphere. CERA-20C improves the specification of the background and the observation errors, two key elements to ensure a consistent weighting of the uncertainties across geophysical variables, space, and time. The quality of CERA-20C has been evaluated against other centennial reanalyses and independent observations. Although CERA-20C inherits some limitations of ERA-20C to represent correctly the tropical cyclones in the first part of the century, it shows significant improvements in the troposphere, compared to ERA-20C and 20CRv2c (the twentieth century reanalysis produced by NOAA/CIRES). A preliminary study of the climate variability in CERA-20C has been carried out. CERA-20C improves on the representation of atmosphere-ocean heat fluxes and mean sea level pressure compared to previous uncoupled ocean and atmospheric historical reanalyses performed at ECMWF.

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Section: Introductionmentioning

confidence: 99%

CERA‐20C: A Coupled Reanalysis of the Twentieth Century

Laloyaux

Boisséson

Balmaseda

et al. 2018

J Adv Model Earth Syst

Self Cite

248

262

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“…This feature obviously strongly depends on the density of assimilated observations. Hence, this work also highlights the value of past observations for reanalyses (Brönnimann et al ., ).…”

Section: Discussionmentioning

confidence: 97%

A framework for high‐resolution meteorological surface reanalysis through offline data assimilation in an ensemble of downscaled reconstructions

Devers¹,

Vidal²,

Lauvernet³

et al. 2019

Quart J Royal Meteoro Soc

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The knowledge of historical French weather has recently been improved through the development of the Spatially COherent Probabilistic Extended (SCOPE) climate reconstructions. This high‐resolution ensemble daily reconstruction dataset of precipitation and temperature covers the period 1871–2012 and is derived through a statistical downscaling of the Twentieth Century Reanalysis. Historical surface observations – even though rather scarce and sparse – do exist from at least the beginning of the period considered, and this information does not currently feed SCOPE Climate. We propose to construct a new high‐resolution surface reanalysis over France – called FYRE Climate (French hYdrometeorological REanalysis Climate) – by assimilating daily temperature and precipitation observations into SCOPE Climate through an offline Ensemble Kalman Filter. The goal of the study is to test methodological choices for developing the future FYRE Climate surface reanalysis. The data assimilation scheme is evaluated over the 2009–2012 period with an increasing assimilated observation density reproducing historical densities. A consistent set of independent stations is retained for validation in terms of continuous ranked probability score, daily bias and daily correlation. Results highlight the importance of the localization as well as the Gaussian anamorphosis for precipitation. They show that: (a) the reanalysis has a lower uncertainty than the initial SCOPE Climate reconstructions, (b) its reliability is similar, and (c) the data assimilation allows reaching the performance of the reference Safran surface reanalysis over France, even for a density of observations as low as the one of 1950. These results thus pave the way for a full 140‐year high‐resolution precipitation and temperature surface reanalysis over France.

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“…As all ECVs produced by a reanalysis are the products of a single reanalysis system, the system validation (to enable traceable quality information) is necessary [74,91,92]. Models of the various elements can be as far as coupled or fully integrated, but there are still generally strong disconnections between the various Earth system elements in the assimilation.…”

Section: Traceability Of Earth System Reanalysismentioning

confidence: 99%

Towards a Traceable Climate Service: Assessment of Quality and Usability of Essential Climate Variables

Zeng

Barmpadimos³

et al. 2019

Remote Sensing

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Climate services are becoming the backbone to translate climate knowledge, data & information into climate-informed decision-making at all levels, from public administrations to business operators. It is essential to assess the technical and scientific quality of the provided climate data and information products, including their value to users, to establish the relation of trust between providers of climate data and information and various downstream users. The climate data and information products (i.e., from satellite, in-situ and reanalysis) shall be fully traceable, adequately documented and uncertainty quantified and can provide sufficient guidance for users to address their specific needs and feedbacks. This paper discusses details on how to apply the quality assurance framework to deliver timely assessments of the quality and usability of Essential Climate Variable (ECV) products. It identifies an overarching structure for the quality assessment of single product ECVs (i.e., consists of only one single variable), multi-product ECVs (i.e., more than one single parameter), thematic products (i.e., water, energy and carbon cycles), as well as the usability assessment. To support a traceable climate service, other than rigorously evaluating the technical and scientific quality of ECV products, which represent the upstream of climate services, how the uncertainty propagates into the resulting benefit (utility) for the users of the climate service needs to be detailed.

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Observations for Reanalyses

Cited by 40 publications

References 35 publications

CERA‐20C: A Coupled Reanalysis of the Twentieth Century

CERA‐20C: A Coupled Reanalysis of the Twentieth Century

A framework for high‐resolution meteorological surface reanalysis through offline data assimilation in an ensemble of downscaled reconstructions

Towards a Traceable Climate Service: Assessment of Quality and Usability of Essential Climate Variables

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