Since the “Daily Updates”, “Monthly Trends”, “ENSO”, “MLMW”, and “Paleo Climate” pages are not open for comments, I have added this page for comments and discussions regarding those pages as well as for general blog-related comments and discussion.
Please note if you post here for the first time, your comment will automatically go into moderation for approval. Once your first comment has been approved, subsequent comments will post immediately.
Climate Concerns 
Your daily updates chart is remarkably the same as Ryan Maue’s chart he plots from the NCEP CFSR / CFSv2 data generated every 4 hours to feed the GFS / ECMWF and other weather models (WeatherBell – paywalled). I always thought this was the best to use since it can’t be homogenized or the weather models will be worse then they currently are.
Good work.
Ren, thanks, and yes the graphs I prepare from daily GFS/CFSR data posted by UM CCI are very similar to those compiled independently by Ryan Maue for WxBELL. I check the WxBELL graphs every day to make sure the UM CCI data are consistent. I agree that the reanalysis approach is probably the best for estimating regional and global surface temperatures and anomalies, although I am not certain the current methods are optimal. I especially like that it is available in near real-time to monitor global weather pattern changes.
This is the first time I’ve seen these charts. Do you know why the differ from the anomaly charts I often see i.e. , GISS, HADCUT, UAH, RSS. For example the 1998 spike isn’t as prominent.
Tony, the CFSR estimates are based on the same weather data used to initialize the global weather forecast models four times every day, which is a lot more data with much better spatial coverage than what goes into the GHCN-based estimates like those from GISS, NCEI, and HadCRUT. The CFSR estimates have actually compared better with the UAH and RSS satellite derived TLT estimates than the GHCN-based estimates.
It’s too bad the daily graphs on UM CCI GFS/CFSR with actual values over the 1981-2010 period have been discontinued. I liked them better than the graphs with values rounded to the nearest decimal value and 1979-2000 baseline. Easier to get a feeling of how temp is evolving.
Congrats for your fine site, and thank you for making the info available.
Javier, UM CCI recently began reporting the daily GFS-based global and zonal temperature anomaly estimates in tenths rather than hundredths as previously reported, beginning 2017 November 30. Consequently, the graphs I present here based on the UM CCI daily estimates must also be presented in tenths. For consistency and simplicity I also converted the older data to tenths and I am now presenting the data with the same 1979-2000 reference period used by UM CCI. To shift to the 1981-2010 reference period, the annual offset is -0.12C and monthly offsets range from -0.09C for June-August to -0.16C for November.
In reality, these GFS-based estimates are probably not accurate to even a tenth of a degree Celsius at best, so effectively some of the random “noise” has been eliminated. However, I have to admit I like to see the hundredths detail as well, but I am not willing at present to commit the much greater time expenditure to go and get the GFS and CFSR output from NCEP and prepare my own analyses. WxBELL used to have time series graphs of the daily CFSR global estimates on their public model output web page, but since Ryan Maue left, they have removed them (although they still are providing a month-to-date global map).
Thank you for your answer. Of course it doesn’t make sense that you put extra time to change the display.
Perhaps it is just me, but I am under the impression that whenever the data stops going the alarming way, displays are changed or discontinued so no fair comparison can be done. I have seen this happening with Arctic sea ice age, that they first changed the display and then stopped reporting altogether, and with the length of the Arctic melt season, once it stopped growing and started to shrink. I guess it gives them the chills to think about skeptics using their own graphs against them.
I like your graphs but, as nature does not do straight lines, putting straight lines through everything is simply muddying the water.
A smoothing curve is nice, which would suggest the cyclic nature of most of these. Why do people think that a downward part of a cycle and an upward part deserve a straight line? The slope of the line is clearly dependent on the time frame and thus is a waste of time and distracting from the picture.
higley7 I agree that trend lines are not likely to be an accurate predictor beyond about 10 to 20 percent of the time period for which there is data and thus are likely to be misleading for longer time periods for the reasons you cite. However, since they are commonly used to analyze what has happened over a measurement period I include them. I like running averages to eliminate seasonal effects seen in daily and monthly temperature data and for smoothing over longer periods like 5 years or more and have included these on some of the graphs.
A much needed site! I wonder when you can update Mauna Loa and Mt Washington info from end of 2017 to present day (or end of Feb)?
Thanks Ilkka. There is about a 1-month lag beyond the end of the month for availability of the data. I will probably update the MLMW graphs quarterly, so the next update would be in early May for data through March.
Understood. Thank you.
Waiting eagerly for the MLMW data Jan – March…
Ilkka, I have updated the MLMW monthly graphs through 2018 March and two had data for April which I also included.
Thank you. Will you update the “detailed views” as well? They still say “through 2017”.
Ilkka, I updated all of the graphs displaying monthly data. The remaining graphs display annual data and cannot be updated until all of the 2018 data are available early next year. I will provide another update of the monthly graphs in the early fall to show the summer data.
Ok, thanks.
Hi Bryan,
I have noticed some changes to the UM CFSR data over the past four months. To highlight them I took one of your figures from November 2017 and another from March 2018 and overlaid them. March 2018 data is in blue and green as you post it, while November 2017 data is grey and pink. The baseline was changed from 1981-2010 to 1979-2000. This change doesn’t make much sense as it is going from 30 years to just 22, and towards comparing with a more distant past. Also the vertical scale went from 1.6 °C to 2.2 °C compressing the changes. But I have adjusted the vertical scale so they both match in this figure:
What can be observed is that the data from 2016 was slightly changed and for example the minimum of 2016 in mid-June is now slightly lower, while the data of 2017 was changed upward quite significantly, so the cooling since February 2016 has been reduced by 21% from the November to the March data.
Do you know the reason of this rather drastic change? Why does it take place at a time the baseline, the scale, and the resolution were changed, so it is more difficult to spot? If we are to trust UM CFSR data it is necessary that it is not subjected to the type of arbitrary changes that have made other datasets unreliable, and that always appear to go in the direction of warming the present and cooling the past.
What is your opinion on this?
Javier
Javier, if you look at the first graph in the Daily Update page, it compares the UM CCI preliminary GFS estimates with the UM CCI final CFSR estimates. This is the only change to the UM CCI daily estimates that occurs. The 2014-2018 graph uses a combination of the CFSR estimates available plus the GFS estimates extending beyond that time. So when UM CCI reports new CFSR estimates, I replace the corresponding GFS estimates with CFSR estimates.
On the Daily Update page I also compare the UM CCI GFS month-to-date and recent monthly averages with the WeatherBELL CFSR estimates for the same periods (see the paragraph just below the first graph). I have found that usually the final UM CCI CFSR estimates are much closer to the WeatherBELL CFSR estimates than are the preliminary UM CCI GFS estimates. Thus the WeatherBELL CFSR versus UM CCI GFS differences are a good indicator of what to expect when the UM CCI CFSR estimates are released. For 2018 January, February, and March so far, the preliminary UM CCI GFS estimates are running about 0.1C above the WeatherBELL CFSR estimates. Consequently, I expect the final UM CCI CFSR estimates to drop by about that amount. You will be able to tell when this change occurs in the graphs when the red line for the UM CCI CFSR jumps forward, closer to the preliminary GFS line in blue, on the first graph in Daily Updates. You will also see a slight change in the 2014-2018 graphs for the affected period, if you compare graphs before and after this update.
Also, I just recently started calculating the global surface temperature anomaly from the hemispheric anomalies and retaining the result to the nearest 0.05C for graphing, which adds a bit more detail to the daily global changes on the graphs. Previously I had been graphing the UM CCI global estimates rounded to 0.1C as provided by UM CCI.
Thank you for the explanation, Bryan. It just looks like a 20% deviation from GFS to CFSR is a lot.
Javier, I calculated the difference between monthly averages of the daily estimates and below is the result in Kelvin (or Celsius) for final CFSR minus preliminary GFS for 2017:
+0.047 Jan
+0.068 Feb
+0.074 Mar
+0.087 Apr
+0.047 May
+0.102 Jun
+0.040 Jul
-0.053 Aug
-0.098 Sep
-0.105 Oct
-0.063 Nov
-0.032 Dec
As you can see, early in 2017 the estimates went up from GFS to CFSR, but since August have been going down from GFS to CFSR. Individual days can have larger swings. So far for 2018, it looks the the estimates will continue to drop from GFS to CFSR and possibly as much as about 0.1C for monthly averages, based on the UM CCI vs WeatherBELL comparisons. If they continue to decrease as expected, that will also cause the running 365 day average to show a larger drop than at present using the preliminary GFS estimates since 2018 January 1.
As near as I can tell, the preliminary UM CCI GFS estimates are actually forecasts for the current day based on the 0000 UTC model run at the beginning of the day and this may account for much of the differences.
Thank you Bryan, that explains a lot. I have also noticed that on the monthly chart UM has become an outlier, showing 0.2°C higher anomaly than the rest, which is a lot.
Hey Brian,
Appreciate these updates. The updates seem to no longer agree with the Climate Reanalyzer, while it seemed like they did before. The updates are running lower. What does this mean?
Thanks
Ned, the Climate Reanalyzer daily output is actually a forecast for the day based on the Global Forecast System (GFS) model output from the first run of the UTC day (0000 UTC). Recently I switched to directly using the NOAA Climate Forecast System Reanalysis (CFSR) Version 2 output instead of the Climate Reanalyzer for providing current daily and monthly temperature anomaly estimates, as described in the “Methodology” section under “Daily Updates”. The CFSR data that I use are based on reanalyses of the model input data associated with the 4 GFS model runs each day and do not include any forecast data. I back-loaded the CFSR daily data for all of 2018 so far and over the next few months will be back-loading the 2017 daily data at higher resolution than what was provided by Climate Reanalyzer.
There have always been discrepancies between the Climate Reanalyzer GFS-forecast based daily temperature anomaly estimates posted each day versus the CFSR daily estimates that are eventually posted on Climate Reanalyzer, often many months later. The CFSR daily estimates for 2018 have not yet been posted there and estimates for 2017 were only posted to the nearest tenth of a degree Celsius, which is very coarse resolution.
I still privately track the Climate Reanalyzer GFS-based temperature anomaly estimates and compare them to the CFSR estimates that I derive from the NOAA output. Recently, the GFS temperature forecasts have been running a bit to the high side, especially in the Northern Hemisphere and that appears to be why the CFSR temperature anomaly estimates are at present lower. You can see a graph of the GFS temperature performance for the 168-hour forecasts, as well as a graph of the model run initial temperatures plus the latest forecast here (referenced to 1981-2010 and adjusted to better match GISS results):
http://www.karstenhaustein.com/climate.php
Watching the Arctic influxes (h/t to Caleb’s blog ‘Sunrise’s Swansong’) on DMI maps etc., one sees swift uplift to space, of energy. I expect including the large latent heat release from snowing. Thus the c.2 trillion tonne increase of arctic ice in the last two years noted by tony Heller and others.. On Greenland especially, and also thicker seaice. Holder’s inequality should put the ‘broiling’ into perspective, which commenters generally fail to do. It is like the hot exhaust pipe which fails to affect the nearby petrol tank…..
This is great work..
Thanks for spending the time to compute and report..not looking like a record year for the NH Is it?
However NASA/NOAA may find a way..🤔👍
Thanks. The NH monthly GMSTA of 0.21C for both May and June was the lowest since that same level in April 2015. So even the NH temperature is showing signs of trending downward.
Looked but didn’t find your copyright policies. I’m a retired Electrical Engineer, BSEE Texas A&M, MSEE SMU. Spent 40 years helping develop intelligence, surveillance and reconnaissance systems for our country’s national defense. I retired in 2002 and am pursuing the arts (painting, drawing, etc.). Recently, I became annoyed by the mass of climate change misinformation being publicized and determined to do my own search and review of credible published climate reports. Hence, my question about your copyright policies. You have some consolidated plots that I have considered creating of published data, and I would appreciate having permission to copy them for possible use, with appropriate credits, in a future blog. I am not going to write or publish any reports.
Bill, I don’t claim copyright for my work on this blog and anyone is free to copy it. I do appreciate credit, however.
Hi,
on the ENSO page you have this text: “A similar pattern can be seen in comparing the University of Alabama at Huntsville (UAH) Temperature for the Lower Troposphere (TLT) change over 12 months versus the MEI as shown below.”
In the graph the UAH line does not match with the global UAH 6.0 graph here: http://www.drroyspencer.com/latest-global-temperatures/
This makes me think that the line (TLT) represents Tropical Lower Trophosphere and not global lower trophosphere. Perhaps this was the intention all along – to show Tropical Lower Trophosphere?
Regards
Ilkka
Ilkka, on the ENSO page I am graphing the 12-month change for the UAH TLT, which is the current month minus the same month a year ago. This approach detrends the data somewhat to make it easier to compare to the MEI which is a unit-less index. I have the actual UAH TLT monthly averages plotted in the first graph on the Monthly Trends page.
Ok,
the word “change” was there but I did not get its meaning. This might make the sentence and the graph easier to understand:
“A similar pattern can be seen in comparing the University of Alabama at Huntsville (UAH) Temperature for the Lower Troposphere (TLT) change over 12 months versus the MEI as shown below (12-month change for the UAH TLT is the current month minus the same month a year ago).”
Regards
Ilkka
I am a trained analyst who studies climate science for the mental challenge of it, attempting to apply formal analytical methods to current climate science- not an easy challenge. The charts created by oz4caster have been extremely helpful in this. I have one key question that I haven’t been able to answer which impacts the trend and statistical analysis I am currently conducting: when did the IPCC change the Anthropogenic impact starting point for CO2 warming from the 1950’s CO2 spike, to the “Post Industrial Revolution” goalpost of 1750? Is there a clear study that linked it to that, or did they simply quietly change the goalposts? According the NOAA human CO2 didn’t outpace natural CO2 and overpower CO2 sinks until the 1960’s, meaning the warming impact would have been negligible to non-existent prior to 1960. The world was in the LIA in 1750. Is there science behind this change, or did they move it just so they could claim every portion of a degree exiting the LIA was human caused? (And does that mean they would rather the world have stayed frozen? Last I checked the LIA killed more people than the black death.) If anyone can provide some insight into this it would be appreciated.
inkandtears, I’m not an expert on IPCC analyses and thus I am uncertain about their reasoning. However, from what I have read, I do suspect that much of their reasoning is more political than scientific. My understanding is that most of the CO2 from human activities began ramping up in the 1950’s and has continued to increase since then. I also understand that the effect of atmospheric CO2 in the current concentration range is logarithmic versus temperature and not linear. That’s why a doubling of CO2 is often used as a benchmark for associated temperature increase, which often also includes very speculative positive feedbacks that induce most of the projected warming.
There is certainly a lot of historical evidence of severe hardships related to cold weather during the Little Ice Age that cannot be ignored. It appears that colder conditions in the more distant future, as the earth’s climate cycles into the next glacial period, will be much more of a challenge for humanity than any small amounts of possible CO2 induced warming in coming decades. In fact, a little warming in the near future might help to delay the inevitable next glacial period during our current ice age that has lasted about 3 million years so far, with no signs of stopping. Our best temperature proxies indicate the glacial periods have been getting longer and colder over the last million years with declining CO2 levels over successive glacial maximums. If the glacial maximum CO2 levels decline much farther, there will be severe repercussions for plant life on the earth.
Thank you very much for your rapid reply. I came across your page because I found two of the charts I was comparing had entirely different values for the rise of CO2 prior to 1958. I was impressed because you were doing comparisons that I had envisioned, but didn’t have the data to complete (the overlap of the interglacial periods is both ingenious, and frightening, as it implies there is about a 75% chance, from historical records, that the earth is headed toward another ice age sooner than we would like.) The problem with their moving the goalpost is that the pre-1960’s warming is key to disproving anthropogenic warming based on CO2 concentrations- I suspect the IPCC knows this and thus has moved the goalpost to preempt such analysis. It is that analysis that I am sitting on right now and which, even when accounting for CO2’s logarithmic nature, proves the world warmed more rapidly before the spike in human CO2 than it did after. Instead of arguing that science, they can now claim every bit of warming from the LIA onward is caused by man, without a shred of evidence, but from what I have seen that is fine with them.
Looking forward to what the Daily Updates look like on your graph. I am expecting a severe drop tonight, June 13, judging from the drop in temperatures.
There have been some drops in temperature on some web sites associated with the NOAA switch from GFS to the new GFS-FV3 at 1200 UTC on June 12. However, this switch does not seem to have affected the NOAA Climate Data Assimilation System (CDAS) output that I use. Even so, the GFS-FV3 forecast is suggesting a drop in the global mean surface temperature over the next 7 days, so it will be interesting to see how far it drops.
it appears I was confused by what appeared to be a fairly sudden drop in the Climate Reanalyzer global anomaly of around a half a degree. being an amateur, there must be a reason for that I am not aware of.
Yes, Climate Reanalyzer is one of the web sites that uses the GFS and now the GFS-FV3 for calculating temperature anomalies, so there is now apparently a baseline offset because of a change in the modeled global temperature with the new GFS-FV3. It will be interesting to see what happens over the next few months. It’s likely that Climate Reanalyzer will make some adjustments before too long.
I have only recently found your site and find it a wonderful source of up to date information. I collect a lot of different climate data myself, just to keep me informed of the real climate situation.
I have noticed a change some months ago in the relative difference in the daily temperature between Climate Reanalyzer (University of Maine) and NCEP/NCAR data. NCEP used to be lower than C/R now it is well above,is this due to some baseline adjustment. I would be interested to here your comments.
Many thanks
Keith, I also follow the Climate Reanalyzer and it uses the NOAA GFS model for current data, which recently in June changed to the new GFS-FV3 version, a major change. In the past, the Climate Reanalyzer presentation of current data was adjusted to better match the CFSR/CDAS data based on historical comparisons, but as near as I can tell, a new adjustment has not yet been made and their temperature output has been running about 0.2C low compared to the CDAS since July 1. The old GFS versus CDAS adjustment varied seasonally and I would not be surprised if the new GFS-FV3 versus CDAS also shows a seasonal variation, but time will tell.
Thank you the explanation I thought it must be adjustment caused.
What I couldn’t understand is how the two sets of data this year are now slowly diverging, NCEP was consistently around 0.2c below University of Maine till January 2019 now it is approaching 0.2c above in August, that is an adjustment of 0.4c over the last 12 months, this has not happened in one adjustment but seemingly slowly over the last 6 months, this may be that seasonal adjustment you mentioned.
I note your reply to Boyd on a similar matter, as you say we shall wait and see.
Hello, I saw the post about Mauna Loa temperature trend. I was trying to find the data myself. I could not find. Can you give me some directions on where to find this data. Thank You.
Salma, the hourly NOAA ESRL meteorological data from Mauna Loa can be found here:
https://www.esrl.noaa.gov/gmd/dv/data/index.php?category=Meteorology&search=Mauna+Loa
The USCRN monthly data is here:
ftp://ftp.ncdc.noaa.gov/pub/data/uscrn/products/monthly01/CRNM0102-HI_Mauna_Loa_5_NNE.txt
The daily USHCN data can be viewed by month and saved as PDF here:
https://www.ncdc.noaa.gov/cdo-web/datasets/LCD/stations/WBAN:21514/detail
What a pleasure to read through your website. Your approach is a classic example of objectivity and accuracy.
I was particularly interested in your graph of the temperature profiles of the last 4 interglacial periods in relation to the current Holocene. Superimposition of the curves on a common timebase is a technique I haven’t encountered before(in relation to climate studies) and it gives a very quick visual comparison of the various eras.
When was that graph last updated? The terminal point on the present day curve seems to suggest that the temperature is no higher than modern normal which doesn’t chime well with assertions that there is a climate crisis.
What were your source data for that graph.
Thanks for your efforts
Richard, thanks for the compliments. When I first started this blog I was lax about citing sources. All of the paleoclimate proxy temperature data were obtained from the NOAA/NCDC Paleoclimatology Program:
http://www.ncdc.noaa.gov/data-access/paleoclimatology-data
The latest update I have is at the bottom of my Holocene Climate post, the last graph under the “Update through 2018” heading. I will be updating that graph to 2019 when the HadCRUT annual global surface air temperature average is available.
Thanks for confirming that. I had assumed it would be NOAA or similar i.e a credible open access source which can be confidently quoted and independently verified.
Yours is a valuable voice in the debate…keep going.
Hi,
“daily zonal temperature anomalies” shows Arctic zone as much as +7C.
For example UAH6 shows less than one degree anomaly. What is the correct figure?
Regards
Ilkka
Hi Ilkka,
There are a couple of major differences between the CDAS daily temperature anomaly output that I provide versus the Lower Tropospheric (LT) temperature anomaly output that is provided by UAH. First, the CDAS daily temperature anomaly estimates are for air at 2-meters above the ground surface, whereas the monthly UAH6 temperature anomaly estimates are for the entire lower troposphere, a big difference. Second, the CDAS “daily zonal temperature anomalies” are daily temperature anomalies rather than monthly anomalies like those presented for UAH6, and thus subject to much more variation within a given month as compared to monthly temperature anomalies. In this regard, it is more appropriate to compare monthly temperature anomalies as I present in the “Monthly Trends”, which includes UAH6 in the global graph.
Thanks for the additional info…
Thanks…
I like the way that you address problems by looking for data so that your answers are based on facts and not just on opinions. You have found a useful hobby in retirement. The Carolina Bays are my retirement hobby. https://bit.ly/Carolina-Bays
Thanks Antonio. I have been following your videos about the Younger-Dryas Event for quite some time now. Very interesting work.
Dr. Oz,
Do you plan to update your reference period to 1991-2020 anytime soon?
I appreciate the work you put into this site.
John, I am not planning to change the reference periods any time soon. The reference period does not affect long-term trends in the graphs. It only effects the baseline offset. In general, going to a more recent baseline will decrease that offset when there has been an overall increase over many decades as we have seen.
I cant seem to get either of the 2 links below to work
“Daily archive
https://nomads.ncdc.noaa.gov/modeldata/cfsv2_analysis_pgbh/
Monthly archive
https://nomads.ncdc.noaa.gov/modeldata/cfsv2_analysis_monthlymeans_pgb/“
Richard, thanks for pointing out the broken links. NOAA closed their NOMADS server last year. The links below are for CFSV2 pressure level data. I will update the appropriate page.
Daily archive for 2021
https://www.ncei.noaa.gov/data/climate-forecast-system/access/operational-analysis/6-hourly-by-pressure/2021/
Monthly archive for 2021
https://www.ncei.noaa.gov/data/climate-forecast-system/access/operational-analysis/monthly-means-by-pressure/2021/
Thanks for your excellent data gathering and presentation and several interesting climate comments!
I check your daily updates every morning, but since October, it seems that the temepratures have been steadily biased towards higher anomalies than most other charts – including those based on the same climate analyzer data. For instance, Moyhu’s charges show gradually lower anomalies every month since October 2021 to February https://s3-us-west-1.amazonaws.com/www.moyhu.org/data/freq/days.png , while your data appear to go towards ever higher anomalies? In March, several days have been noted up to 1 degree celcius above baseline on your ‘daily updates’, which I cannnot find anything similar to in other charts. Could you say anything on how this discrepancy has come to happen?
Best regards; Tor Ole Klemsdal, Oslo
Tor, thanks for your comment. Yes, I have noticed the same high separation as well, but have not heard an explanation for it. It is especially noticeable on the monthly comparison graph – the first graph presented here:
Normally, the CDAS/CFSR surface air temperature anomaly estimates track closely to the very similar ERA5 estimates, but have separated high the last several months. In the past, there have been some problems in the CFSR data set that went on for months before being corrected. I suspect something similar is happening now, but time will tell.
Thank you for the quick response! Than we should probably see either a correction coming in due time, or that that the discrepancy will go away again when the underlying causes (presumably temporary) are no longer present.
Best regards; Tor
I second Tor’s acclaim as follower and have a question too: the ~0.2 K amplitude seasonality most clearly seen under Daily Updates, Fig. 4, with impact of orbital ellipticity and hemispheric differences already adjusted for, right? – what makes for this remaining NH-winter warming?
sofloc, my best guess on recent winter warming mainly in the Arctic region, is that it is related to ocean circulation patterns that are not affected much by the atmosphere. However, the ocean does have a big impact on the atmosphere and sea ice in the Arctic. There is some evidence that suggests periodic oscillations that vary in length, but may be in the 30-60 year range, where the Arctic becomes colder and then warmer during each oscillation. If true, we could possibly witness Arctic cooling within the next decade or two. Time will tell.
Hi,
I´ve had an exhange of messages with a person who relies on NASA/GISS/GISTEMP V4, which shows a rise in temperature of 1.0C between 1965 t0 2022. I´ve sent him NCAR DAILY R1, which shows a rise of about 0.6C in the same period and really no rise 2002-2022. He says that NCAR is “old fashioned” and haven´t been updated since 1995. Your comments on this?
P.S. Happy and successful year 2023!
Happy New Year to you and family too Ilkka,
The NCAR R1 is based on an old model that has not been updated since around 1995. However, I have read that it supposedly still uses the same data inputs for consistency over time. The model grid is coarse at 2.5 degrees latitude/longitude, but is comparable to some of the long-range climate models in that regard.
The GISS approach uses only surface temperature data, whereas the reanalysis approach, as in NCAR R1, uses a wide variety of ocean and full atmospheric measurements as model inputs. I prefer the reanalysis approach because of the more robust inputs and because it is more directly comparable to how the long-range climate models work.
In case you may not have noticed, I recently added the NCAR R1 output to the first graph in the Monthly Trends page, where it can be compared to the CFSR/CDAS as well as GISS and other models since 2014.
My science education team would like to use the graphs you include for annual average temperature data and running means on the “MLMW” page. How can we contact you to learn more about how you produced the graphs and if they are available for use in curriculum for high school students?
Lindsey, my work is not copyrighted and is free to use. All the data were compiled from USA National Oceanographic and Atmospheric Administration (NOAA) sources that can be found on the internet. I loaded the data into MS Excel workbooks to produce the graphs. Some of the daily data had to be loaded one month at a time to avoid paying charges, which was quite tedious. I will post the links I use when I make the next MLMW page update in February to add 2022 data.
Why is CFSR adjusted? What is used a “ground truth” to adjust to? I would think that the model initializations would be carefully constructed and dynamically balanced and any error would be minimal and randomly distributed.
Mary, I posted my reasoning for calculating an adjusted CFSR in my 2016 post here:
I’m not certain why the raw CFSR deviates so much from other indices at times. It does have some odd outlier stretches. The adjustment I made is somewhat crude, but does improve the comparison with other indices. However, I can’t rule out the possibility that CFSR is more accurate and all the others not as much for those outlier periods, but that’s not likely.
Is it possible to make the numbers underlying your Monthly Updates available in Excel or .csv? I understand Daily would be too tedious, but being able to see the numbers and format them to my liking would be amazing. Thanks!
Chris, I had not really thought about uploading data files to make them available, but I checked and found that WordPress does allow me to upload “documents”. I have a 6MB Excel file that has both daily and monthly data as well as the graphs that I post here. In the near future, I will try uploading it to “documents” and linking to the uploaded file from the Monthly Trends page. If this works, I will upload an updated file at the beginning of each month.
Thank you!
Hi there! I was following your ‘Daily Updates’ page on how you download and process the NOAA CDAS data used in the daily and monthly graphs. I’ve gotten stuck on the last bit where you explain the columns you have, specifically the 6th column with pre-calculated area weights for each of the 361 latitude zones based on a spherical earth and summing to 100 for the entire globe. So the question is, how did you get the area weight? Would really appreciate any help on this, thank you so much!
Denisa, thanks for your interest. Unfortunately I did this work back around 2016 and I cannot find the formula I used to calculate the weights for each latitude range. All I have now are the resulting numbers. I remember finding the formula on a website, but did not save a link.
Yeah Denisa, if you google it, you will find it. The areas from the top of the globe (90 degrees) down to the equator follow a sine curve formula, I believe. And then of course moving east to west around the globe 360 degrees, those areas will be the same.