July temperature up 0.1C

The global averaged surface temperature for July 2019 was 0.75C using my spherical triangulation method merging GHCNV3 with HadSST3. This is an increase of 0.13C since June.

Monthly temperatures updated for July

This is a large monthly rise but still in line with past monthly fluctuations. For the moment I am sticking with GHNC-V3/V3C. The annual temperature after 7 months is shown below. The 2019 value averaged over 7 months is 0.76C

Here is the spatial dependence for July.

Northern Hemisphere

Southern Hemisphere

Monthly variations are still quite large so one should not read too much into one month’s values. However it looks like 2019 will end up the second or third warmest year.

Note: If I use V4C instead then all past temperatures increase significantly. That is why I am hesitant to change to V4 until I understand why. I suspect it is because of a huge increase in recent stations without long term histories, so the normals are less affected than recent anomalies.

V4 annual results compared to V3, both combined with HadSST3.

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25 Responses to July temperature up 0.1C

  1. Snape says:

    What’s up with Climatereanalyzer? I’ve been monitoring the global, 2 meter temperature anomaly there for almost 3 years. It always matched pretty well with the major datasets. The past 2 months, though, have been the coolest I can remember. Obviously way off.

    Still cool even now:
    https://climatereanalyzer.org/wx/fcst/#gfs.arc-lea.t2anom

  2. Gerry McIsaac says:

    Can you do variance calculations with the spherical triangulation method

    • Clive Best says:

      Yes you could do the same as HADCRUT4 and generate an ensemble of 100 series randomly changing individual temperatures within errors.

      • Gerry McIsaac says:

        I was more interested in the variance of the temperature data for all the data for any specific time period. Have always wondered how a 0.1 C increase or decrease can be significant if the variance is not considered.

  3. MOTM says:

    I was hoping you would write a piece about the rapid sea level change between Interglacials? You have a interesting and unique way to analyze data and information.

    Ex:
    Global Climate and Sea Level Enduring Variability and Rapid Fluctuations over the past 150,000 years

    https://www.researchgate.net/publication/269687043_Global_Climate_and_Sea_Level_Enduring_Variability_and_Rapid_Fluctuations_Over_the_Past_150000_Years

  4. Dan Pangburn says:

    Measured water vapor exceeds by 64% that calculated from feedback from UAH temperatures (27% if from Had-CRUT4 temperatures) proving WV not CO2 drives average global temperature https://pbs.twimg.com/media/EHLxE8aUcAE2p5H?format=jpg&name=small

    • DP said: “Measured water vapor exceeds by 64% that calculated from feedback from UAH temperatures (27% if from Had-CRUT4 temperatures) proving WV not CO2 drives average global temperature”

      Close enough for engineering work. You don’t have a clue what the average temperature is in a region, nor how to average the temperature over a lapse rate range, etc. And then your inability to prove the direction of causality makes this a moot point anyways — e.g. if it is up by 64%, then does that mean a temperature rise is in the pipeline?

      Any scientist with an ounce of intuition will not buy what you are trying to sell.

      • Dan Pangburn says:

        Apparently you are unable to grasp that measured average global WV being greater than the amount determined by feedback proves causality. It does.

        The issue here is global not regional and I track the reporting of global average from several agencies. If I had a use for the average temperature over a lapse rate I would determine it, etc. You sound like someone mired in the minutia.

        “…exceeds by 64 %…” means the ratio of the trend for measured TPW to the trend for TPW calculated from the temperature increase is 1.64. The linked graph is for 27% so the ratio of trends is 1.27. The trend equations are displayed so you can verify. It has nothing to do with what is “in the pipeline”.

        I wonder how much wider the separation between GCM assessments and reality will need to get for you to realize that you must have missed something.

        • DP said:

          “You sound like someone mired in the minutia.”

          LOL. You are the one overfitting like a madman to get at a single scalar value. Just consider how much average temperature varies over the globe, and how much humidity varies over those same areas and you think you can boil this down to a meaningful result? Consider how well known it is that the northern latitudes contribute most to the warming signal, yet warming at polar temperatures won’t add much to water vapor content — this means your calibration is hosed.

          • Dan Pangburn says:

            It’s even worse than I thought. You are HOPELESSLY mired in the minutia and are unaware of it. Besides that, you have no clue as to what has been increasing the water vapor.

            I gave the link to a graph that shows that WV has been increasing faster than if determined from feedback as assumed in the GCMs. Do you even know how to make that assessment? Are you too stubborn to realize that this means that CO2 is not the driver and everything based on that false assumption is wrong?

          • Dan, LOL, you’re confirming Clausius-Clayperon to an engineering approximation. With the wild ENSO variations, which pump huge amounts of water vapor into the atmosphere in direct proportion to the upwelling heated ocean water, you’re delusional in being able to isolate any trend that isn’t approximated by AGW C-C.

          • Dan Pangburn says:

            Paul,
            Again you exhibit your lack of knowledge and willful blindness. Clapeyron was an engineer. The Clapeyron equation AKA the Clausius-Clapeyron equation precisely relates the volume change to the enthalpy change when a liquid changes into a vapor. Thermodynamics For Engineers, 1st ed., Doolittle. Others have approximated this to facilitate their work. I wonder if C-C is used correctly in the GCMs.

            Apparently you noticed that WV calculated from feedback closely follows the measured WV but failed to notice the difference in trends. The measured trend is 0.04272/0.03357 = 1.27 or 27% steeper than the calculated trend. I did the same thing using the UAH temperatures and the measured trend came out 64 % steeper.

            Because we only have 3 decades of data these factors will change, but any amount by which measured WV trend exceeds the WV trend calculated on the basis of average global temperature change demonstrates that WV leads and CO2 tags along behind temperature change.

            The explanation is quite simple. ENSO is a strong and rapid forcing on WV on the short term while the steadily increasing irrigation contributes to the trend.

          • “The measured trend is 0.04272/0.03357 = 1.27 or 27% steeper than the calculated trend.”

            This is in the noise given all the assumptions you are making.

          • Dan Pangburn says:

            PP,
            The trends account for the noise. The only assumption is that TPW is proportional to vapor pressure which is corroborated by the verification graph at http://www.remss.com/measurements/atmospheric-water-vapor/tpw-1-deg-product/

          • Vapor pressure experimentalists like myself are amused by your chart.

  5. Gerry McIsaac says:

    Dan
    Where are you getting your Water Vapor values from?

  6. Dan Pangburn says:

    Hitran calculates the relative absorb/emit intensity of water vapor molecules vs CO2 molecules. Comparison at zero altitude is shown at https://pbs.twimg.com/media/ECWhyyDUYAA1P89?format=jpg&name=medium . Comparison by the ratio of the summation of intensities (line lengths) for each wavenumber for each molecule species is 8.7/0.07 = 124. On average at ground level, WV molecules outnumber CO2 molecules by about 10,000/410 ? 24 to one. After accounting for molecule count, each WV molecule is still more than 124/24 ? 5 times more effective at absorb/emit of thermal radiation than a CO2 molecule.

    The relative effectiveness of the increases of WV and CO2 over the last 30 years is calculated as follows:
    CO2 increase in 3 decades, 1988 to 2018 = 407 – 348 = 59 ppmv

    Water vapor increase trend from NASA/RSS TPW data, is 0.04272/28.9 * 100 * 10 = 1.47 % per decade.

    Average global WV = 10,000 ppmv. WV increase in 3 decades = .0147 * 10,000 * 3 = 441 ppmv

    Therefore, WV has been 441/59 * 5 = 37+ times more effective at increasing ground level temperature than CO2.

    Above the tropopause WV molecules are reduced to about 32 ppmv because of the low temperature while CO2 molecules remain at 410 ppmv. Therefore, CO2 molecules outnumber WV molecules 410/32 ?12 to one. At higher altitudes the molecule spacing increases and more and more of outward directed radiation makes it all the way to space. The increased cooling by more CO2 well above the tropopause counters and apparently fully compensates for the tiny added warming from CO2 increase at ground level. The result being that Climate Sensitivity is not significantly different from zero.

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