Lecture-TimeSeries: Global Warming / archived / read-only

 
  • Part of: Points on Climate Change
  • Outline
    • Aims:
    • • Present the empirical evidence
    • • Discuss other items (climate models) as required
    • Moderator: Leon.
    • Agenda:
      1. Introduction: start with list of economics issues from Malcolm's response to CSIRO.
    • And Malcolm's reply to Chief Scientist (5 mins)
      1. Show data on key variables to show what the datasets can do and to focus on:
    • (Subtly conveying understanding of data and variation and of filtering)
      • • Temperature
      • • CO2
      • • Temperature-CO2 relationship
      • • Climate measures - rain, storms, snow, droughts, floods (briefly to prove nothing unusual)
      • • Drivers of variation - solar, CO2, water vapour (briefly to prove nothing unusual)
      • (30 mins)
      1. Bill Johnston re data quality & BOM critique - GIGO (15 mins)
      1. Peter re GHCN (10 mins)
      1. Gavin Schmidt correspondence (Malcolm: 1 mins)
      1. Tony Heller’s two graphs showing NASA-GISS fiddling. Peter can show on computer (5 mins)
      1. Audience questions & take complex Q’s on notice and we’ll post answers on website. (20 mins)
      1. Conclusions about 3 core premises of CSIRO & Chief Scientist - show they're questionable and highlight specific errors. Critique the basic AGW premises. Sea Levels refer to Howard. CSIRO disclaimer (Peter to present) and "No danger" read CSIRO's response. (10 mins)
      1. Malcolm focus on Tim Flannery (rainfall graphs), Will Steffen, David Karoly connected with major international bodies pushing alarm with no evidence and benefitting personally. (5 mins)
      1. Howard Brady - sell his book (10 mins)
    • Total = 91 minutes, that’s 1.5 hours
      1. Open discussion. Available for answering questions and presenting graphs.
    • Other topics:
    • Climate models - if asked, Peter refer to Christy's graph and ask which is correct.
  • Introduction
    • Many people have uttered many statements on climate change. An easy way to back up a statement is to show some data behind it. Graphs are commonly used and those concerning climate change are often Time Series with years, months or days on the x axis. Graphs can be easily compared for potential correlation.
    • Graphs as pictures are not very versatile. Can't prune to common timescales. Some come as anomalies and some as measured values. Collecting the datasets underlying the graphs is a bit more trouble but opens up a lot more capability at finger tip control.
    • What is available? What is being plotted? Subject: Indicators; Indicators
  • Content
    • Where to start. Global Warming implies Temperature. so Indicator: Temperature
      • Satellites are shiny, modern and cover the whole globe. The lowest layer of the atmosphere measured is the Lower Troposphere, so Topic: Temp 30 Years
        • Looks like a lot of variation in the trends in various zones. Sort them
          • North polar zone warming the fastest, South polar zone is cooling. Atmospheric CO2 is almost the same at both poles on an annual scale, justifying the term "well mixed" gas, but the south pole has almost no seasonal variation in CO2. We come back to CO2 later.
          • Looking at the Global UAH-LT-Globe [new tab]
          • The big seasonal change is obvious. 1.5 to 2 degrees but this is the global average. The NH land heats more than the SH land. This graph is not showing what was actually measured. It is a monthly mean.There may be a further larger oscillation from day to day.
          • Seasonally Adjust reduces the monthly changes to more like +- 0.2 degrees.
          • The big 1998 El-Nino is visible,near the Nino 3-4 ticks at the top, The volcanic eruption (Pinatubo) is indicated at the bottom
          • Savitzky Golay Smoothing gives a nice clean graph by removing the cluttering noise, but one man's noise is another man's signal. This graph is not showing what actually happened.
          • What to make of that graph. It is obviously trending up. Overlay Poly Degree
          • Change Start Year: 1997 gives a different picture.
          • No one on earth experiences the Mean Global Temperature UAH-LT-AUST has more variation than UAH-LT-Globe but again no person experiences the Australian Monthly Mean Temperature. We can look at difference weather stations in Australia if time permits.
          • So unless you are a penguin or an Antarctic scientist you would probably conclude on the satellite record, that the earth is warming. For how long will this warming trend continue? Given that all previous warming trends have eventually ceased.
      • Going further back. Topics: Temp 200 Years Thermometers
        • These are Seasonally Adjusted. All have upward trends.
        • I choose to discard GISS Temp and NOAA Global Temp because of the activism of their senior officials. Index List Filter
        • Smooth with Savitzky Golay
        • Start Year: 1940 End Year: 1979 shows a 39 year pause
        • Ah 7000+ on land, few in ocean (70% of area) GHCN
        • Lat Long
        • Combine
        • NSW southern tablelands, trends mostly >>
        • Try the 4 major records.
          • All take a lot of data from the GHCN
            • Data is often adjusted by the country BoM before the GHCN gets it
            • GHCN adjusts it further
          • Lurching upwards but with pauses and slumps
          • GISS Temp highest trend. Run by Jim Hansen the activist
          • Unfortunately these are not independent, all based on GHCN 7000+ stations
        • GHCN
          • GHCN Australia
      • Going further back. Topics: Temp 1,000 Years TreeRings, Hockey sticks
      • Going further back. Topics: Temp 2,000 Years Tree rings and Ice cores
        • These are now based on Tree Rings, Ice Cores or other Reconstructions. Somewhat spread over the latitude zones but missing the South Temperate zone. All have downward trends. The sample intervals now extending beyond one year.
        • Comparison is easier with the Plot Function: Normalise to Means
      • Going further back. Topics: Temp 10,000 Years
        • These are all ocean water temperatures. All have slight long term downwards trends but some show sharp oscillations.
      • Going further back. Topics: Temp 1,000,000 Years
        • All Ice Cores with 30-200 year resolution.
        • General agreement of Arctic with Antarctic at long time scales. GISP2 has much more variation.
        • Start Year: -8000 No long term trends
    • What has atmospheric carbon dioxide concentration been doing?
      • The Scripps Institute runs a chain of precise flask stations up the Pacific Ocean in isolated areas. Topic: CO2 30 Years Scripps. All show almost identical seasonally adjusted trends.
      • Going back 200 years relies on GISS (which is probably Law Dome) and Beck's summary of 200,000 historical chemical measurements Topic: CO2 200Years
      • Going back 2000 years brings in Kouwenberg's stomatal method against Law Dome ice core. Topic: CO2 2000 Years
      • Further back 20,000 years to ice core EPICA Dome C, not much change, explain theories Search: epica-dome-c-co2
        • Some suggestions that ice cores underestimate CO2 levels and lose the extreme swings
      • Further back 400,000 years to Vostok Search: vostok
      • Geological time scale: Phanerozoic, Rothman: very different
      • Where is it coming from
        • Show long term
        • Show short term
        • Show by country
        • Variation in Land Sinks
          • Some suggest a strong temperature relationship
        • State change in 1940
        • GISS CO2 relies on Law Dome?
    • OLR
      • Compare plots
    • ModTRAN6
    • • Temperature-CO2 relationship
      • Short term Mauna Loa vs UAH LT, just depends on the zone
      • Mid term GISS CO2 vs BEST Global
      • Longer term Law dome CO2 and temp
      • Longer still EPICA Dome C vs GISP2 some correlation
      • Vostok Temp leads by 500 yrs
    • • Climate measures - rain, storms, snow, droughts, floods
      • Cyclone activity index
      • Polar Ice Extent
      • Snow coverage NH
      • Rainfall
    • • Drivers of variation - solar, CO2, water vapour
      • Sunspot number better than tsi
  • Conclusions
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