Data is currently at
https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.csv
or
https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.txt
(or such updated location for this Gistemp v4 LOTI data)
January 2024 might show as 124 in hundredths of a degree C, this is +1.24C above the 1951-1980 base period. If it shows as 1.22 then it is in degrees i.e. 1.22C. Same logic/interpretation as this will be applied.
If the version or base period changes then I will consult with traders over what is best way for any such change to have least effect on betting positions or consider N/A if it is unclear what the sensible least effect resolution should be.
Numbers expected to be displayed to hundredth of a degree. The extra digit used here is to ensure understanding that +1.20C resolves to an exceed 1.195C option.
Resolves per first update seen by me or posted as long, as there is no reason to think data shown is in error. If there is reason to think there may be an error then resolution will be delayed at least 24 hours. Minor later update should not cause a need to re-resolve.
@gonnarekt Yeah the latest ensembles have shown a quite a bit of increase further out (still lot of uncertainty).
Given I've had two months in a row where the final number looks like it is going to be off by ~0.05C I need to come up with a better ERA5->GISTEMP model... I havent been able to improve much in the past tries, so I'll have to come up with something new.
@parhizj i use many statistics and dynamic models for corrections, my point is that near past corrections better than all time, also I try to predict water variance for ersst close to the end
@parhizj what do you think now? I have very big variance this month, not sure right now about good range, but i guess it should go somewhere 1.16-1.26. I can change my mind in one week.
@gonnarekt I forgot to do a run this morning and now my power is out again today, so I’ll let you know later if it comes back. I haven’t bet much in this market as I was planning on doing some work on it though to figure out how my ERA5->gistemp model could be so far off the last couple months, but with the recent correction I’m going to wait until we have the real final August data to see if the difference from my prediction drops to within a more reasonable amount before starting to bet heavily in these markets..
@gonnarekt Ok got power back half hour ago luckily.
1.134 is my center point prediction at the moment..
-- I just realized forgot to revise my own prediction error for June/July oh well... it shouldn't decrease too much but I need to rerun gistemp with the new strange stations list to get more decimal points for June/July to revise.... we'll see how it is tomorrow... (without the final upward adjustment its 1.120)
Rant about variance:
There are a lot of ways to calculate the probabilities and variance with this superensemble I came up with before the month ends, and I may have mentioned before but I lack enough data to come up with the skew/kurtosis parameters (ideally I would come up with hierarchical bayesian model or a score driven model if there were, but the global models get updated every few years and improve, so you cant just old GEFS and EPS data (>1-3 years); they also have different approaches for hindcasts but that is a method I don't use (which is what a normal regular regional/local weather forecast would probably do)).
So best I can do is use the ensemble itself for each day's temps and carefully calculate them over the remaining period in the month in the super ensemble and then adjust for any bias and variance over the remaining period in the month in the superensemble using own prediction error, which is what I've been doing for a couple months) ... but it turns out this method is far too underconfident by itself... I haven't had time yet to try to constrain the final model to end up with a tighter variance and more peaky distribution (one way that I have yet to finish would be to use simple time series data from simply the GISTEMP anomaly data alone to constrain it)...