21st Century Global Temperature Trends

This analysis focuses on global temperature anomaly trends for our current 21st century so far, beginning in 2001, as we approach the first 15 years. The previous post covered trends over the entire satellite weather data era back to 1979.

As mentioned in my previous post, there are three main relatively independent sources of global surface temperature anomaly estimates available, derived from:  the Global Historical Climate Network (and sometimes including additional land stations) coupled with sea surface temperature measurements (GHCN), global weather forecast model input data, and satellite estimates of lower tropospheric temperatures.  There are multiple groups that compile and publish estimates from these sources, but for simplicity, estimates from four of these groups are presented here.  For the GHCN related estimates, this analysis uses the US National Center for Environmental Information (NCEI) estimates and the Berkeley Earth Surface Temperature (BEST) estimates.  These are compared to the satellite estimates from the University of Alabama Huntsville (UAH) and global forecast system (GFS) estimates provided by the University of Maine (UM) Climate Change Institute (CCI).

I compiled and graphed monthly global temperature anomaly estimates from each of these four groups for the period 2001 through September 2015 and calculated linear regression trends to indicate the overall change over this period. The UM CCI GFS estimates in Figure 1 show the lowest trend at -0.0014 degrees Celsius (C) per month over the period of nearly 15 years, which corresponds to -1.68C per century if maintained. The next lowest trend, shown in Figure 2, is +0.00005C per month from the UAH satellite estimates, which corresponds to +0.06C per century if maintained. The second highest trend is +0.0006C per month for the BEST GHCN estimates shown in Figure 3, which corresponds to +0.72C per century. The highest trend of 0.0009C per month is from the NCEI GHCN estimates shown in Figure 4 and corresponds to +1.08C per century if maintained.

Global temperature anomaly trend for 1979-2015 based on UM CCI GFS monthly estimates

Figure 1. Global temperature anomaly trend for 1979-2015 based on UM CCI GFS monthly estimates.

Global temperature anomaly trend for 1979-2015 based on UAH satellite monthly estimates

Figure 2. Global temperature anomaly trend for 1979-2015 based on UAH satellite monthly estimates.

Global temperature anomaly trend for 1979-2015 based on BEST GHCN monthly estimates

Figure 3. Global temperature anomaly trend for 1979-2015 based on BEST GHCN monthly estimates.

Global temperature anomaly trend for 1979-2015 based on NCEI GHCN monthly estimates

Figure 4. Global temperature anomaly trend for 1979-2015 based on NCEI GHCN monthly estimates.

The variation in these trends underscores the uncertainty in all of these approaches. I suspect that the satellite derived estimate of +0.06C per century is the best compromise among these estimates. I find it very interesting that the GFS derived estimate of -1.68C per century contrasts so greatly with the GHCN derived trends. This discrepancy provides further evidence that ongoing adjustments to the GHCN based estimates are pushing them farther away from reality. We have no way of knowing whether these trends will be maintained for a full century, but there is certainly no clear evidence of an upward trend so far this century despite continued rapid increases in carbon dioxide (CO2). The implication is that CO2 is not at all the driver for global temperature trends and does not warrant expensive efforts to control.

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2 responses to “21st Century Global Temperature Trends

  1. You are a bit confused on our data sources.
    second I spent about 6 months working with GFS on a daily basis comparing now casts to the actual data.

    in the end I had to dump GFS

    • Steven, I have not researched the inputs to BEST, but I do remember reading that it incorporated a lot more surface temperature measurements than GHCN alone. However, I suspect that it still does not incorporate as many measurements as go into the GFS. I am curious why you chose to dump GFS. Does that mean you believe the GFS is doing a poor job at initializing its weather model forecast runs?

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