28-01-2021, 18:37 | #61 |
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Where is the electricity to come from to power these 'electric veh-he-cals'. Where are the materials going to come from to produce these cars in the first place? And are the factories that produce these cars powered by environmentally sound power sources? Questions we should be asking, but are not, because everything today is presented to us on a surface level. It's all about being seen doing the 'right thing', while not actually doing it.
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28-01-2021, 18:41 | #62 | |
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28-01-2021, 19:31 | #63 |
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Yes, what we really need to do is get rid of the idea of everyone owning a car, electric or not. Hopefully we'll head in that direction eventually, where possible.
It takes planning for the future and designing our cities and countryside better, which we're not exactly good at in Ireland. |
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28-01-2021, 21:10 | #64 | |
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28-01-2021, 23:00 | #65 |
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It was more that someone in our company ran the numbers and said "hang on a minute...!" It is enough to make our large multinational rethink its longterm strategy on a blanket removal of plastic.
Cue the normal accusations that it's these big multinationals who are the littering culprits. Yep, they're the ones who throw plastic bottles and Heineken six-pack rings in the rivers that lead to the ocean. Personal responsibility counts for nothing, it seems. |
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28-01-2021, 23:22 | #66 | |
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29-01-2021, 08:44 | #68 | |
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29-01-2021, 08:51 | #69 | |
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It’s now at about 413ppm and increasing each year. This is very basic stuff Danno Human CO2 emissions are above the planets ability to sequester it, and until we change that, global warming is going to get worse and worse |
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29-01-2021, 11:20 | #72 | |
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Here are the actual numbers from NASA relating to global average temperature Land-Ocean Temperature Index (C) -------------------------------- Year No_Smoothing Lowess(5) ---------------------------- 1880 -0.16 -0.08 1881 -0.07 -0.12 1882 -0.10 -0.16 1883 -0.16 -0.19 1884 -0.28 -0.23 1885 -0.32 -0.25 1886 -0.31 -0.26 1887 -0.35 -0.27 1888 -0.17 -0.26 1889 -0.10 -0.25 1890 -0.35 -0.25 1891 -0.22 -0.25 1892 -0.27 -0.26 1893 -0.31 -0.26 1894 -0.30 -0.23 1895 -0.22 -0.22 1896 -0.11 -0.20 1897 -0.11 -0.18 1898 -0.26 -0.16 1899 -0.17 -0.17 1900 -0.07 -0.19 1901 -0.15 -0.23 1902 -0.27 -0.25 1903 -0.36 -0.28 1904 -0.46 -0.30 1905 -0.26 -0.33 1906 -0.22 -0.35 1907 -0.38 -0.37 1908 -0.42 -0.39 1909 -0.48 -0.40 1910 -0.43 -0.41 1911 -0.43 -0.38 1912 -0.35 -0.34 1913 -0.34 -0.32 1914 -0.15 -0.30 1915 -0.13 -0.30 1916 -0.35 -0.29 1917 -0.45 -0.29 1918 -0.29 -0.29 1919 -0.27 -0.29 1920 -0.27 -0.27 1921 -0.18 -0.26 1922 -0.28 -0.25 1923 -0.26 -0.24 1924 -0.27 -0.23 1925 -0.22 -0.22 1926 -0.10 -0.22 1927 -0.21 -0.21 1928 -0.20 -0.19 1929 -0.36 -0.19 1930 -0.16 -0.19 1931 -0.09 -0.19 1932 -0.16 -0.18 1933 -0.29 -0.17 1934 -0.12 -0.16 1935 -0.20 -0.14 1936 -0.15 -0.11 1937 -0.03 -0.06 1938 0.00 -0.01 1939 -0.02 0.03 1940 0.13 0.06 1941 0.18 0.09 1942 0.07 0.11 1943 0.09 0.10 1944 0.20 0.07 1945 0.09 0.04 1946 -0.07 0.00 1947 -0.03 -0.04 1948 -0.11 -0.07 1949 -0.11 -0.08 1950 -0.17 -0.08 1951 -0.07 -0.07 1952 0.01 -0.07 1953 0.08 -0.07 1954 -0.13 -0.07 1955 -0.14 -0.06 1956 -0.19 -0.05 1957 0.05 -0.04 1958 0.06 -0.01 1959 0.03 0.01 1960 -0.03 0.03 1961 0.06 0.01 1962 0.03 -0.01 1963 0.05 -0.03 1964 -0.20 -0.04 1965 -0.11 -0.05 1966 -0.06 -0.06 1967 -0.02 -0.05 1968 -0.08 -0.03 1969 0.05 -0.02 1970 0.03 -0.00 1971 -0.08 0.00 1972 0.01 0.00 1973 0.16 -0.00 1974 -0.07 0.01 1975 -0.01 0.02 1976 -0.10 0.04 1977 0.18 0.07 1978 0.07 0.12 1979 0.16 0.16 1980 0.26 0.20 1981 0.32 0.21 1982 0.14 0.22 1983 0.31 0.21 1984 0.16 0.21 1985 0.12 0.22 1986 0.18 0.24 1987 0.32 0.27 1988 0.39 0.31 1989 0.27 0.33 1990 0.45 0.33 1991 0.41 0.33 1992 0.22 0.33 1993 0.23 0.33 1994 0.32 0.34 1995 0.45 0.37 1996 0.33 0.40 1997 0.46 0.42 1998 0.61 0.44 1999 0.38 0.47 2000 0.39 0.50 2001 0.54 0.52 2002 0.63 0.55 2003 0.62 0.59 2004 0.54 0.61 2005 0.68 0.62 2006 0.64 0.63 2007 0.67 0.64 2008 0.55 0.64 2009 0.66 0.65 2010 0.72 0.65 2011 0.61 0.67 2012 0.65 0.70 2013 0.68 0.74 2014 0.75 0.79 2015 0.90 0.83 2016 1.02 0.88 2017 0.93 0.92 2018 0.85 0.95 2019 0.99 0.98 2020 1.02 1.01 https://data.giss.nasa.gov/gistemp/g...Data/graph.txt The graph you used takes the mean of temperatures between 1986 and 2005 In the NASA data, that converts to 0.421, so this is the 0c anomaly on your graph According to Nasa's data the anomaly from 2012 onwards is year anomaly 1986-2005 2012 0.229 2013 0.259 2014 0.329 2015 0.479 2016 0.599 2017 0.509 2018 0.429 2019 0.569 2020 0.599 so you have plotted the wrong data on the graph from 2016 onwards I've corrected your graph and it shows a completely different picture now. The red dots on this are what you should have inputted It's very easy to 'prove' that climate change models and projections are wrong if you use the wrong figures in home made graphs This DIY 'science' where reputable papers in peer reviewed journals are 'debunked' with a back of the envelope calculation from someone who thinks they know more than the PHD climate scientists who wrote and reviewed the papers is a major cause of misinformation on this important topic. I see it all the time where people on blogs falsely manipulate data either through malice or incompetence, and then use this this to 'debunk' actual scientific findings |
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29-01-2021, 11:41 | #73 | |
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Secondly, if you plot the unsmoothed figure in the GISS link you gave you get the same as what I plotted. You plotted the LOWESS figure. Two different representations of the same data. |
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29-01-2021, 12:19 | #74 | |
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of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions. Addressing adequately the statistical nature of climate is computationally intensive and requires the application of new methods of model diagnosis, but such statistical information is essential. " The climate models are not weather forecasting machines, they do not accurately predict the exact state of the climate at any specified point in the future, and they do not try or pretend to do this What they do, is narrow down probabilities, they make projections of what the future is likely to be like given different scenarios None of the scenarios are predictions, they are scenarios that are aimed at measuring the impacts of different potential variables all of which are subject to change. If you do not understand what the models are, or what their purpose is, or how they are intended to be used, then you should refrain from making judgements on how effective they are. |
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29-01-2021, 12:32 | #75 | |
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How did they measure this? |
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