A. Düsterhus
@aduesterhus
Followers
195
Following
759
Media
94
Statuses
943
Scientist with a personal view on Statistics in Geo- & Earth Science. Working on data science, sea-level and long-term prediction.
Copenhagen, Denmark
Joined November 2013
Join us this morning for seasonal to decadal predictions and its applications in 0.49/50 at #egu25
1
0
1
As Storm Éowyn approached Ireland, the Irish Marine Data Buoy Observation Network—managed by the Marine Institute & Met Éireann—recorded extraordinary ocean conditions. 📍 M3 Buoy (56km off the Cork coast): 🌊 Wave height: 20.15m - almost the length of a tennis court! 📍 M4
1
21
33
Abstract submission for #egu25 opened: CL 4.6: "Climate Predictions from Seasonal to Multi-Decadal Timescales and Their Applications" Submission Deadline: January 15, 2025 Financial Support Deadline: December 2, 2024 We look forward to see you in Vienna & online!
0
1
3
End of year look at paper projects (* = first author): published 2024: DD* in review: PL in write up: BG, KA, EA, NW, KP in work: HY*, ND + some on the horizon #researchlife
0
0
1
Abstract submission for #egu25 opened: CL 4.6: "Climate Predictions from Seasonal to Multi-Decadal Timescales and Their Applications" Submission Deadline: January 15, 2025 Financial Support Deadline: December 2, 2024 We look forward to see you in Vienna & online!
0
1
3
Always a nice day when PhD students graduate. Congratulations to @DiabateSamuel and @CatsObeirne
1
3
28
Uh, a round number. But honestly, as it is gs, many of them do anyway not count (but anyway thanks) and there are reasons why we repeat again and again that citations are not as important as some try to make them. Anyway, we all love a round number, don't we. 🎉
0
0
0
After all these years it is great to be back. Hello Liverpool!
0
0
0
The research was done together with Sebastian at @unihh supported by the project Coming decade funded by @BMBF_Bund Myself funded for this by #nckf at @dmidk and @a_ceathair funded by @MIFundingOffice 7/7
0
0
0
This study demonstrate that predictions of distributions are possible, but require creative approaches for the verification. It opens a new dimension and increases the temporal resolution to look at these predictions. 6/7
2
0
0
Main physical result: different seasons show different skills. Especially with involved ice processes the skill between hindcasts and historicals vary considerately. We use a quite normal distributed variable, so the results are in most cases close to a correlation analysis. 5/7
1
0
0
But as we cannot evaluate them by a single value like correlation, we do it by counting how often over a given time span one simulation wins against another. It is a different form of looking at verification and a hopefully much more accessible for communication purposes. 4/7
1
0
0
In this study we propose a strategy to evaluate full distributions relatively against each other. For this we employ the IQD to compare hindcasts, historicals and climatology vs. a reference (assimilation simulation). 3/7
1
0
0
Up to know, almost everybody predicts mean values over a given time span. While it is convenient to do, it is only part of the full story. Because distributions of a variable are not necessarily reflected by an average value. 2/7
1
0
0
New paper out on decadal predictions of full seasonal temperature distributions. https://t.co/SNukWNfplv 1/7
agupubs.onlinelibrary.wiley.com
Potential of decadal prediction of temperature distributions Variability in prediction skill vary regionally over seasons The North Atlantic offers an important area where temperature distributi...
1
0
1
Congratulations!!!
Congratulations to Catherine O'Beirne on her successful defence of her thesis: Application of tailored decadal predictions for Eastern North Atlantic Catherine was supervised by Dr Gerard McCarthy, with Dr Andre Duesterhus on the team before he moved on #phdlife #oceanography
0
2
7