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Yeah. That is interesting. My guess is that there was a larger than usual data upload into GHCN and ERSST this month. I know there are ongoing record digitization efforts so it's possible some newly digitized records got uploaded. I had to deal with this situation in 2020 as well. The 2016 value was hovering very near a 0.005 value causing near monthly rounding changes. That market was based on 2020 being higher than 2016 when rounded to 2 decimal places. So I had to track both 2016 and 2020 values down to 3 decimal places which required running a modified version of GISTEMP on my own machine. Fortunately like you say Kalshi is strictly defined as >= 1.03 regardless of what 2016 and 2020 are doing. One strategy I was thinking of was to cash out my position on the >= 1.03 contract and take my gains and instead try to play the new 1.05 - 1.07 contract. The 1.05 - 1.07 contract is undervalued according to my analysis. The problem is that there isn't a lot of market depth on that contract. A mere $99 will take it from $0.20 to $0.69 instantly. I show a fair value around $0.60. So that play isn't going to work right now. And I only show maybe another $0.10 gain on the >= 1.03 contract before it reaches fair value. I think the opportunities via Kalshi are limited right now. My initial impression of the Kalshi is meh. I don't think it has been correctly valuing the contracts. It seems to be very reactionary leading me to believe that there are very few participants using predictive tools. The other markets I've tracked in the past had more participants and more educated/sophisticated participants at that resulting in the market being a leading indicator instead of a lagging indicator like what Kalshi is. So be it I guess. It's easier to get an edge this way.

GISS published the June update for GISTEMP. It came in at 1.07 C. Here are the changes on this update cycle. Jan: 0.87 => 0.86 Feb: 0.98 => 0.97 Mar: 1.21 => 1.20 Apr: 1.00 => 1.00 May: 0.94 => 0.93 Here is my updated analysis. Jan: 0.86 ± 0.01 C (3m lagged ENSO -0.99) Feb: 0.97 ± 0.01 C (3m lagged ENSO -0.90) Mar: 1.20 ± 0.01 C (3m lagged ENSO -0.86) Apr: 1.00 ± 0.01 C (3m lagged ENSO -0.71) May: 0.93 ± 0.01 C (3m lagged ENSO -0.46) Jun: 1.07 ± 0.02 C (3m lagged ENSO -0.11) Jul: 1.11 ± 0.16 C (3m lagged ENSO +0.14) Aug: 1.05 ± 0.22 C (3m lagged ENSO +0.46) Sep: 1.09 ± 0.23 C (3m lagged ENSO +0.86) Oct: 1.15 ± 0.24 C (predicted 3m lagged ENSO +1.03) Nov: 1.17 ± 0.25 C (predicted 3m lagged ENSO +1.17) Dec: 1.17 ± 0.26 C (predicted 3m lagged ENSO +1.26) Jan - Jun average: 1.01 C Jul - Dec predicted average: 1.12 C 2023 Average: 1.062 ± 0.07 with 80% chance of >= 1.03 (new record) and 60% chance >= 1.05.

And keep in mind that the expectation was that sea ice in the SH would actually remain level or even increase through 2030 - 2060 before beginning to decline. So observing a decline so soon and so dramatically obviously raises eyebrows.

Berkeley Earth is now saying there is an 81% chance that 2023 will be the warmest in their dataset. https://berkeleyearth.org/june-2023-temperature-update/

Yes for GISTEMP on the 1951-1980 baseline. With more data that has been refined to 1.09 ± 0.06 C. Sent from my Pixel 5a using Tapatalk

Exactly. It's like how we use CDAS to track ENSO. It's not the best metric. But it's close enough to give us a pretty good idea of what ERSST is going to show. And since CDAS is near real-time it is still incredibly useful.

I was actually getting ready to respond to your question from this morning. I don't use CFSR for my own modeling because it's skill is subpar. Of the reanalysis datasets I generally use ERA5 and/or JRA55. That doesn't mean CFSR should be dismissed though. It's correlation with ERA and JRA is still very high. I use ERA5 a lot. In fact, it is one of my go-to sources for getting an early lead on what GISTEMP is going to report since it correlates at R^2 = 0.89. Note that Copernicus confirmed the new record via ERA5. And it's likely July 4th eclipsed that as well. ERA5 has a 2 day lag so we don't know for sure yet.

Nick Stokes just processed the June GHCN-M and ERSST files. I estimate the GISTEMP value for June at 1.09 ± 0.06 C.

There is a lot of a information coming out today. Sorry for the rapid posting. Anyway, the April CERES Earth Energy Imbalance came in at +1.81 W/m2. I realize the CERES EEI calculations have high uncertainty, but if the EEI truly is this high then there is more than enough warming in the pipeline to go well beyond 1.5 C.

Copernicus won't publish the official numbers from ERA5 for another couple days. However, based on Hausfather's twitter post we might expect GISTEMP to publish around 1.10 C for June. ERA5 correlates with GISTEMP at R^2 = 0.89. Note that the previous record was 0.92 C in 2022. It is all but guaranteed at this point that June 2023 will be a new record in the GISTEMP dataset as well.

For the first time in recorded history the global average temperature breached 17 C; at least according to CFSR anyway.

I was actually getting ready to post the GFS forecast as well. You scooped me. Anyway, yeah, July is already forecasted to start off quite warm. I noticed that there was a small blip down in the global SST last week. I wonder if that means excess heat is transferring from the ocean into the atmosphere now. As of this moment my June expectation is a tick up to 1.08 ± 0.10. Once the June data starts rolling in I can get that uncertainty envelop down to ± 0.06 prior to the GISTEMP update. By all indications June 2023 is going to be the warmest June on record.

BTW...the page is buried pretty well. But you can get the probability density function corrected forecast (bias corrected) for the CFS from the following link. It took me forever to find it a couple of weeks ago and Google isn't much help. https://www.cpc.ncep.noaa.gov/products/people/wwang/cfsv2fcst/CFSv2SST8210.html

And the bias corrected CFS forecast is even lower at maybe +1.4.

I cannot disagree. If I have understood the Brown & Caldeira method correctly they only make predictions based on the current state of the climate system. In other words they do not take into account the expectation of future ENSO (or other highly correlated climatic element) states. This may explain why I get higher odds of a new record. My model is simpler (more like a multiple regression that minimizes RMSE), but incorporates the future expectation of ENSO and to a lesser extent total solar irradiance (which I do find to be at least minimally correlated with global temperatures). Both of which can be predicted 6 months in advance with reasonable skill. And yes, your point about global SST is well taken. My expectation is that the atmosphere will catch up to the higher SSTs in the next couple of months. It may be interesting to note that my model does not use SST has an input right now. In that regard one might argue that even I may be underestimating the warming potential in the later half of the year, but I'm going to remain more guarded on that matter as I also think a reversion to the trend may also be on the horizon. Afterall highly deviant increases/decreases tend to reverse some eventually. BTW...my current June expectation for GISTEMP is 1.07 ± 0.10 C. To put that into perspective even taking the ~2.5% chance that it comes in -0.10 C below the expectation at 0.97 C it will still easily surpass the previous record of 0.92 C set all the back in 2022. That should raise some eyebrows.

Brown & Caldeira are now saying there is a 57% chance of new GISTEMP record.

Berkeley Earth says there is a 54% chance of new record in their dataset.

@GaWx I bet you're right. I've not been able to find any daily ERSST updates. And I can't disagree, I see a very high correlation between NCEP/NCAR vs ERSST in ENSO 3.4 region at R^2 = 0.98. So while they don't match exactly it is very close. I certainly wouldn't dismiss it.

Someone can correct me if I'm wrong but it is my understanding that CDAS, which stands for Climate Data Assimilation System, is actually the model core for the NCEP/NCAR reanalysis. Or at least that is what the NCEP/NCAR built upon. The NCEP/NCAR reanalysis is known to be subpar. But I don't think that is justification for dismissing it outright. I do wonder if it wouldn't be better for Levi Cowan to use a more accepted product like OISST or ERSST though.

Several months back I suggested that if the shenanigans kept up in the Antarctic then perhaps it might be time for a dedicated thread. The data collected by the IPCC suggested that sea ice extents may increase through 2030 at the very least. Yet here we are with record lows. Perhaps the time for a dedicated thread as come.

Here is my latest expectation for GISTEMP which includes the June IRI ENSO ensemble forecast. Jan: 0.87 ± 0.01 C (3m lagged ENSO -0.99) Feb: 0.98 ± 0.01 C (3m lagged ENSO -0.90) Mar: 1.21 ± 0.01 C (3m lagged ENSO -0.86) Apr: 1.00 ± 0.01 C (3m lagged ENSO -0.71) May: 0.94 ± 0.02 C (3m lagged ENSO -0.46) Jun: 1.05 ± 0.12 C (3m lagged ENSO -0.11) Jul: 1.03 ± 0.22 C (3m lagged ENSO +0.13) Aug: 1.06 ± 0.23 C (3m lagged ENSO +0.39) Sep: 1.10 ± 0.24 C Oct: 1.13 ± 0.25 C Nov: 1.16 ± 0.26 C Dec: 1.17 ± 0.26 C 2023 Average: 1.06 ± 0.08 with 75% chance of a new record (>= 1.03)

The June IRI ensemble suite just got published. The statistical+dynamical average peak jumped up 0.2 to 1.5 on this update. https://iri.columbia.edu/our-expertise/climate/forecasts/enso/current/?enso_tab=enso-sst_table IRI June Seasons (2023 – 2024) Model JJA JAS ASO SON OND NDJ DJF JFM FMA Dynamical 1.295 1.539 1.679 1.761 1.746 1.598 1.473 1.264 1.009 Statistical 0.749 0.785 0.825 0.840 0.846 0.812 0.734 0.579 0.415 All 1.120 1.298 1.406 1.466 1.403 1.248 1.125 0.899 0.670

The bias corrected CFS peak has come down about 0.5 in the last few weeks.

This is great. I've been looking for an updated volcanic aerosol dataset for awhile now. I had no idea this existed. They even have it in an easy csv file format and it goes through 2022. Anyway, it looks like H2O adds about 0.1 W/m2 to the imbalance. Like you said the AOD portion is fading rapidly though so if the H2O portion is long term like scientists are expecting then we should expect a net positive, albeit small, effect from Hunga Tonga soon. Somewhat interesting...my machine learning model said a 5 month lag with GISTEMP for this volcanic aerosol dataset was optimal. My model was showing a -0.05 C adder to start the year and wanes to -0.02 C by the end after I extrapolate out the AOD decay based on what happened with Pinatubo.

ERA has a pretty high correlation with the traditional datasets. It correlates with GISTEMP at R^2 = 0.89. It's the same as JRA. The previous record via JRA was +0.34 (1991-2020 baseline) in 2019. So far the 2023 June value is +0.61. JRA correlation with GISTEMP is R^2 = 0.89 https://climatlas.com/temperature/jra55_temperature.php Similarly with the GFS as well. The previous record via GFS was +0.55 (1981-2010 baseline) in 2019. So far in 2023 June value is 0.68. GFS correlation with GISTEMP is R^2 = 0.78 http://www.karstenhaustein.com/climate.php