Join us at 12pm EDT for the first of three POS Panel Webinars this week. Today's talk is by Stefano Ciavatta (Plymouth Marine Lab) on "Ocean biogeochemical reanalysis: Current status and future perspectives". Link to join can be found @ usclivar.org/webinars

A great opportunity for discussing observation platforms, modeling strategies, data assimilation products, and UQ of all these products relevant to the rapidly changing Arctic. Looking forward to engagement and outcomes. Co-organized by our very own Patrick Heimbach.

Statistical Methods for the Physical Sciences (STAMPS@CMU) webinar on July 10 at 1:30 PM ET "Stochastic modeling of the ocean using drifters: The Lagrangian perspective" by Adam Sykulski (OceanUQ working group member). More details on how to join here: stat.cmu.edu/stamps/webinar…

Next Monday's Data Science Webinar: "Scalable Covariance Approximations for Environmental and Climate Data" with Matthias Katzfuss. Read the complete abstract 👉 usclivar.org/working-groups… CLIVAR Data Sciences

We're conducting a survey, please retweet. Reading an oceanographic paper you come across the sentence, with no other specification: “Our estimate of the mean of quantity X is 10 +/- 2”. What do you expect +/- 2 to represent?

Summer 2020 Variations: New research on climate variability and change using initial-condition Large Ensembles. Guest editors Clara Deser & Keith Rodgers. Read it ➡️ indd.adobe.com/view/20699135-… Corresponding webinar on September 8 @ 10am EDT ➡️ usclivar.org/webinars

An excellent webinar by our team member, Patrick Heimbach on ocean parameter and state estimation problem is now online on youtube.

A great thread summarizing a multi-institutional collaborative research lead by @NoraLoose (including our team member Patrick Heimbach) on using the Hessian UQ methods for designing observation systems.

Ocean Best Practices Workshop will be hosted virtually starting this Friday. Many of our WG members will be presenting at an exciting session on UQ in ocean obs, DA and modeling. More info in the newsletter here 👇Donata Giglio, Patrick Heimbach, Shane Elipot

Ocean metrics are critical for understanding Earth’s climate and hence reducing uncertainty on them is highly valuable. Read about an exciting new method to help reduce uncertainty in ocean properties measured using proxy observations.

Call for papers and special session proposals for the 2021 IEEE international workshop on #metrology for the Sea metrosea.org

Uncertainty Quantification of Ocean Parameterizations: Application to the K‐Profile‐Parameterization for Penetrative Convection agupubs.onlinelibrary.wiley.com/doi/10.1029/20…

An excellent international collaboration to further reduce uncertainty on a very important climate threat (ice sheet melt and sea-level rise).

Lots of great work on Uncertainty Quantification for the next-generation ocean and climate science and datasets funded by NOAA Climate.gov!

In oceanography, as in any scientific field, the goal is not to eliminate #uncertainty in #data, but instead to better quantify and clearly communicate its size and nature. First publication in AGU's Eos is out from our working group US CLIVAR eos.org/opinions/overc…

Join us today at #OSM22 for the first of one of our official sessions OD02 10:00AM ET "Advances in Data Science for Ocean Uncertainty Quantification" hosted by US CLIVAR OceanUQ members Donata Giglio Shane Elipot & MIkael Kuusela

Join us again today Monday at #OSM22 for sessions 2 (2:30pm ET) and 3 (3:30pm ET) of OD02 "Advances in Data Science for Ocean Uncertainty Quantification" hosted by Alison Gray (UW) and US CLIVAR OceanUQ members Donata Giglio Shane Elipot & Mikael Kuusela

New in #datasciencej:G.Peng,C.Lacagnina,R.Downs,Anette Ganske,H.Ramapriyan, I.Ivánová, L.Wyborn, D.Jones, L.Bastin,C.Shie,D.Moroni Title: Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets doi.org/10.5334/dsj-20…