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Plugging in the GFS wind field into the IKE calculator yields some gnarly looking values.

The COCORAHS station in St. Peters (just west of St. Louis) record 11.00" in 7 hours. The station is located 38.8 N, 90.6 W. According to the Precipitation Frequency Data Server this is easily a 1-in-1000 year event.

STL broke the calendar day rainfall record in only 6 hours. The previous record was 6.85" on August 20th, 1915. As of 7am STL had 7.97" today.

HadCET just updated. The highest daily mean in the Central England Temperature record dating back to 1772 just got SHATTERED. Here is the sequencing of the records of the highest daily mean. Date Highest Daily Mean 1772-08-10 22.5 1783-07-11 22.6 1808-07-13 24.5 1948-07-29 25.1 2019-07-25 25.3 2022-07-19 28.1 Here is the full 251 year list sorted in descending order on the highest daily mean for that year. Prior to 2022 the mean of this list was 21.0 C with a standard deviation of 1.6 C. 2022 is 4.4σ above the mean. Note that the distribution is right tailed so that 4.4σ figure may be a bit misleading. Year Highest Daily Mean 2022 28.1 2019 25.3 2020 25.2 1948 25.1 1995 24.8 2015 24.7 2006 24.6 1808 24.5 1976 24.5 1990 24.4 1852 24.0 1923 24.0 1818 23.9 1911 23.9 2003 23.9 1975 23.8 1825 23.7 2016 23.6 1943 23.4 2005 23.2 1868 23.1 1930 23.1 1942 23.0 1989 23.0 1947 22.9 2001 22.9 1826 22.8 1858 22.8 1932 22.8 2013 22.8 1817 22.7 1921 22.7 2018 22.7 1783 22.6 1983 22.6 1997 22.6 2009 22.6 1773 22.5 1830 22.5 1847 22.5 1952 22.5 1876 22.4 1878 22.4 1884 22.4 1901 22.4 1949 22.4 1950 22.4 1834 22.3 1873 22.3 1900 22.3 1906 22.3 1912 22.3 1926 22.3 1941 22.3 1957 22.3 2021 22.3 1793 22.2 1859 22.2 1925 22.2 1933 22.2 1996 22.2 1836 22.1 1856 22.1 1935 22.1 1955 22.1 1779 22.0 1814 22.0 1846 22.0 1872 22.0 1893 22.0 1953 22.0 1820 21.9 1842 21.9 1869 21.9 2011 21.9 1780 21.8 1790 21.8 1792 21.8 1819 21.8 1986 21.8 2017 21.8 1800 21.7 1881 21.7 1897 21.7 1936 21.7 1968 21.7 2004 21.7 1778 21.6 1844 21.6 1871 21.6 1898 21.6 1961 21.6 1970 21.6 1984 21.6 1999 21.6 1798 21.4 1870 21.4 1937 21.4 1969 21.4 2002 21.4 1850 21.3 1874 21.3 1917 21.3 1959 21.3 2000 21.3 1797 21.2 1807 21.2 1837 21.2 1885 21.2 1924 21.2 1982 21.2 2008 21.2 1775 21.1 1822 21.1 1824 21.1 1854 21.1 1944 21.1 2014 21.1 1804 21.0 1857 21.0 1914 21.0 1929 21.0 1945 21.0 1781 20.9 1828 20.9 1886 20.9 1934 20.9 1973 20.9 1987 20.9 1772 20.8 1803 20.8 1899 20.8 1938 20.8 1786 20.7 1795 20.7 1827 20.7 1835 20.7 1896 20.7 1980 20.7 1794 20.6 1904 20.6 1918 20.6 1939 20.6 1967 20.6 1810 20.5 1848 20.5 1866 20.5 1994 20.5 1998 20.5 1788 20.4 1843 20.4 1916 20.4 1960 20.4 1991 20.4 1992 20.4 2012 20.4 1776 20.3 1784 20.3 1838 20.3 1851 20.3 1855 20.3 1867 20.3 1940 20.3 1774 20.2 1801 20.2 1813 20.2 1831 20.2 1887 20.2 1782 20.1 1880 20.1 1894 20.1 1981 20.1 1985 20.1 1791 20.0 1833 20.0 1909 20.0 1958 20.0 2010 20.0 1787 19.9 1832 19.9 1865 19.9 1895 19.9 1902 19.9 1971 19.9 1977 19.9 1802 19.8 1821 19.8 1946 19.8 2007 19.8 1905 19.7 1796 19.6 1840 19.6 1845 19.6 1864 19.6 1877 19.6 1888 19.6 1903 19.6 1785 19.5 1806 19.5 1861 19.5 1863 19.5 1908 19.5 1919 19.5 1951 19.5 1966 19.5 1978 19.5 1979 19.5 1777 19.4 1922 19.4 1928 19.4 1964 19.4 1913 19.3 1927 19.3 1988 19.3 1993 19.3 1789 19.2 1823 19.2 1875 19.2 1915 19.2 1972 19.2 1963 19.1 1812 19.0 1829 19.0 1849 19.0 1805 18.9 1839 18.9 1883 18.9 1892 18.9 1841 18.8 1853 18.8 1910 18.8 1799 18.7 1889 18.7 1931 18.7 1956 18.7 1811 18.6 1891 18.6 1965 18.6 1974 18.6 1809 18.5 1816 18.5 1815 18.4 1879 18.4 1882 18.2 1920 18.2 1954 18.2 1907 18.1 1890 18.0 1962 18.0 1862 17.3 1860 17.2

Here is a reminder that the World Weather Attribution group is usually quick to publish their analysis of heatwaves. I would expect something within a month or so regarding this event. https://www.worldweatherattribution.org/analysis/heatwave/

UKMET is reporting 38.1 C at the official station in Santon Downham as the highest of the day for England. That's over there on the east side of England northeast of Cambridge. Very nearly an all time record already. Yesterday's 12Z GFS was forecasting 39 C max for this region. Yesterday's 12Z ECMWF was forecasting 36 C max for this region. Yesterday's 12Z UKMET was forecasting 34 C at 15Z for this region. Despite being biased a tad high GFS performed the best with its 2m T forecast. I'm thinking there is a decent chance we could see 40 C somewhere tomorrow. Today's 12Z GFS is forecasting 42 C.

Wales shattered their all time high. The previous record was 35.2 C on Aug. 2nd, 1990. The new record is now 37.1 C in Hawarden just south of Liverpool. 12Z GFS from yesterday forecasted 37C for this area. 12Z ECMWF from yesterday forecasted 35C for this area.

I saw that the GFS was the most aggressive with its 2m T product. I noticed that it has had a high bias with temperatures in the plains states this summer. I wonder if the same bias is in play here as well.

UKMET is now saying there is a 95% chance that the all time record will be broken.

Just to clarify...all models are showing 38C or higher. UKMET said the odds of > 38.7C were 80% on Friday. Based on more recent modeling I have not seen anything that would undermine that prediction. In fact, if anything, I think the 2m temperature products have actually amped up a bit since Friday. The all time record high appears to still be in play from what I'm seeing.

I just checked this morning's 12Z cycle. All 3 major global models (GFS, UKMET, ECMWF) have the UK maxing out at 38C or higher on Tuesday. The current all time high is 38.7C set on July 25th, 2019 at Cambridge.

The makes the irony of the Watts Up With That blog recently mocking a simulated forecast of 40C in 2050 beyond epic. https://wattsupwiththat.com/2022/06/28/forecast-for-22nd-june-2050/

St. Louis should break two records today. The low only got down to 83 and the high got up to 100. I believe that 83 low will become the highest daily minimum for the entire month of June.

6.6.2022 thru 6.10.2022 = 11.459e6 km^2 6.6.1980 thru 6.10.1980 = 11.490e6 km^2 Side note...6.6.1980, 6.8.1980, and 6.10.1980 are missing so the 11.490e6 km^2 value is actually the average of 6.7.1980 and 6.9.1980 only. If we use a simple linear interpolation to fill in the missing values the 5 day average becomes 11.499e6 km^2.

That graph is showing the trailing 5 day average which is different than the daily values. BTW...the graph has a quirk where the same date from different years is shifted visually if one of the years was a leap year such as 1980. If you look closely you'll see that June 10th, 1980 was 11.49e6 km^2 whereas June 10th, 2022 was 11.459e6 km^2. So even with the 5 day average 2022 was lower than 1980.

I see 11.813e6 km^2 for June 10th, 1980. Note that this is the simple linear interpolation of the June 9 and June 11 values of 11.665e6 and 11.961e6 km^2 respectively. The closest to 11.642e6 km^2 is 11.646e6 km^2 in 2019. Can you double check your source? I believe the 5.142e6 km^2 value you see is for April 10th, 2022 which is the 100th day of the year.

New record low extent for June 10th per NSIDC down in the Antarctic region. 11.642e6 km^2.

I just had a short conversation with someone on the WUWT blog who was trying to claim CMIP6 predictions were off by 4 standards of deviation from the UAH temperature. I had to point out that the UAH anomalies are baselined on the 1991-2020 period while the CMIP6 prediction he was looking at was on the 1880-1910 baseline. Furthermore his 5 month lead time prediction from Dec. 2021 was significantly worse than the CMIP6's 1709 month lead time prediction for the May 2022 anomaly. And I see these astonishingly bad contrarian predictions and misrepresentation of reputable predictions literally on a monthly basis.

The report has been finalized and is now officially available. There is a lot of information here. As I get time I'll try to post some of the most pertinent facts and figures. How much does net anthropogenic forcing contribute to net total forcing. 96% How much does CO2 contribute to the net anthropogenic forcing. 79% How much does CO2 contribute to the net total forcing. 76% This is table AIII.3 which summarizes the effective radiative forcing (ERF) in W/m2 of various contributing factors.

It appears that the ECMWF keeps a would-be Agatha as a closed low as it crosses from the Pacific into the Atlantic basin. When was the last time we had a named storm (TS or higher) cross basins in this manner? I know TD-11 crossed over and developed into a TS in 2010, but it only got named Hermine after it crossed. Note that I do see several Atlantic-to-Pacific crossovers, but few Pacific-to-Atlantic crossovers.

Just a quick post here. Using the same procedure as above I calculated the type A uncertainty on UAH and RSS satellite monthly anomalies at ±0.16 C. This is consistent with the type B evaluation from Christy et al. 2003 of ±0.20 C and the monte carlo evaluation by Mears et al. 2011 of 0.2 C. This compares to the surface station uncertainty of ±0.07. It might also be interesting to point out that Spencer & Christy 1992 first assessed the monthly uncertainty as ±0.01 C then later reevaluated it as ±0.20 C. Anyway the point is that the uncertainty on global average temperatures from satellites is significantly worse/higher than those from the surface station datasets.

I often hear that UAH is the most trustworthy and honest global average temperature dataset because they do not adjust the data. I thought it might be good to dedicate a post to the topic and debunk that myth right now. Fortunately I was able to track down a lot of the information from the US Climate Change Science Program's Temperature Trends in the Lower Atmosphere - Chapter 2 by Karl et al. 2006 which Dr. Christy was the lead author at least for that chapter. Year / Version / Effect / Description / Citation Adjustment 1: 1992 : A : unknown effect : simple bias correction : Spencer & Christy 1992 Adjustment 2: 1994 : B : -0.03 C/decade : linear diurnal drift : Christy et al. 1995 Adjustment 3: 1997 : C : +0.03 C/decade : removal of residual annual cycle related to hot target variations : Christy et al. 1998 Adjustment 4: 1998 : D : +0.10 C/decade : orbital decay : Christy et al. 2000 Adjustment 5: 1998 : D : -0.07 C/decade : removal of dependence on time variations of hot target temperature : Christy et al. 2000 Adjustment 6: 2003 : 5.0 : +0.008 C/decade : non-linear diurnal drift : Christy et al. 2003 Adjustment 7: 2004 : 5.1 : -0.004 C/decade : data criteria acceptance : Karl et al. 2006 Adjustment 8: 2005 : 5.2 : +0.035 C/decade : diurnal drift : Spencer et al. 2006 Adjustment 9: 2017 : 6.0 : -0.03 C/decade : new method : Spencer et al. 2017 [open] That is 0.307 C/decade worth of adjustments with a net of +0.039 C/decade.

For the second statistical test I will again focus on HadCRUT, GISTEMP, BEST, and ERA since these are all surface datasets that have full sphere converge. This test will compare the difference between monthly measurements of each dataset and the mean of all. The mean is considered to be the best expectation of the true value. The quantity we are calculating is Dx = Tx - Tavg where Dx is the difference between the temperature Tx of dataset x and the average temperature Tavg. The period of evaluation is 1979/01 to 2021/12 which covers 516 months. That means each dataset x has 516 measurements than be compared to the average. We will determine the uncertainty of Dx as 2*u(Dx) by calculating the standard deviation of Dx. Since it is common practice to report uncertainty at 95% confidence we will multiple by 2 for the 2-sigma range. Again, this a type A evaluation of uncertainty. For HadCRUT this value is 0.051 C, for Berkeley Earth it is 0.060 C, for GISTEMP it is 0.057 C, and for ERA it is 0.086 C. The average implied uncertainty is 0.065 C. I am a little surprised by ERA. It has the highest uncertainty wrt to the mean of the datasets analyzed. I'm surprised because ERA is considered to be among the best reanalysis datasets and incorporates not only orders of magnitude more observations than the other datasets but many different kinds of observations including surface, satellite, radiosonde, etc. It has a much longer tails on the distribution. So we've calculated average implied uncertainty 2u(D) as 0.065 C. But that is only the uncertainty of the difference wrt to the average. The average itself will have an uncertainty given by u(avg) = u(x) / sqrt(N). So u(Tavg) = u(D) / sqrt(N) = 0.0325 / sqrt(4) = 0.0163 C. So we have u(D) = 0.033 and u(Tavg) = 0.0163. We will apply the root sum square rule to find the final uncertainty u(T). It is u(T) = sqrt(u(D)^2 + u(Tavg)^2) = sqrt(0.033^2 + 0.0163^2) = 0.0368 C. And using the 2-sigma convention we have 2u(T) = 0.0368 * 2 = 0.074 C. That's our final answer. Method 1 above yields u = 0.075 C while method 2 here yields u = 0.074 C. This isn't much of a surprise that both methods give essentially the same result since they are both calculated from the same data.

There is no way 1.5 C is realistic anymore. Even at a modest sensitivity of 0.5 C per W/m2 that is 1.2 W/m2 * 0.5 C/W.m2 = 0.6 C of warming already queued up and in the pipeline to be added to the ~1.1 C of warming that has already occurred. And the evidence suggests the climate sensitivity in C per W/m2 may start low and increase as more tipping points are activated. A final 1 C per W/m2 or higher is very much in the realm of possibility still.