Preliminary Climate Forecast System Reanalysis (CFSR) estimates of global surface temperature anomalies from the University of Maine Climate Change Institute (UM-CCI) are now available for 2015 and are described below. These estimates are based on the U.S. National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) model input prepared routinely four times each day to generate global weather forecasts.
The daily UM-CCI CFSR estimates of global surface temperature anomalies are graphed in Figure 1 and show a sudden upward shift in October that has continued through December. This jump may possibly be related to the peaking of the El Niño cycle as heat from the tropical Pacific is re-distributed around the globe by weather patterns. The UM-CCI estimates for November and December are preliminary and the raw output provided by UM-CCI have been adjusted using a linear regression formula based on raw versus final estimates during the period from July through October of 2015.
The monthly UM-CCI CFSR estimates of global temperature anomalies for 2014 through 2015 are graphed in Figure 2 along with similar CFSR estimates provided by WxBell (December is preliminary). This graph also includes the final monthly estimates through November from the U.S. National Center for Environment Information (NCEI) and from the University of Alabama at Huntsville (UAH) for comparison. The NCEI estimates are also for surface temperature anomalies based on land and ocean measurements, while the UAH estimates are for lower troposphere temperature anomalies derived from satellite measurements.
The preliminary UM-CCI CFSR 2015 annual estimate of global surface temperature anomaly is 0.278 degrees Celsius (C), referenced to the 1981-2010 climatological period, and compares closely to the 0.272C estimate from WxBell for 2015 through December 30. The annual UM-CCI CFSR estimates for 1979 through 2015 are graphed in Figure 3 along with the NCEI estimates for 1979 through 2014 (as posted in March 2015). The NCEI estimate for 2015 will likely be well above 0.4C, since the January through November average is already at 0.44C and will probably increase slightly when December is included. Consequently, the NCEI estimate for 2015 will likely be the highest global temperature anomaly since 1880, whereas the CFSR global temperature anomaly will only rank 5th highest since 1979.
The preliminary CFSR trend of the monthly global temperature anomaly estimates for the 21st Century so far (since 2001) is graphed in Figure 4. It still shows a downward trend despite the recent large upward spike in monthly anomalies for October through December of 2015. The trend is still -0.0011C per month which corresponds to -1.32C per century if maintained for another 85 years. The recent upward spike decreased the statistical confidence in the trend estimate as indicated by the coefficient of determination (R2) of 0.1454 as compared the R2=0.2335 for the trend 2001 through September 2015 before the spike occurred.
Considering the many uncertainties involved in trying to estimate global surface temperatures or temperature anomalies and associated trends, the overall confidence in this trend is low. As I have stated in previous posts, my best guesstimate of the overall uncertainty is about 0.3C to 0.5C for recent annual global temperature anomaly estimates. However, within the overall uncertainty, there does not appear to be any significant or alarming trend, either up or down that would warrant taking action to try to modify the earth’s climate at this time. In my view, government mandated efforts to reduce human carbon dioxide emissions are a huge waste of time and expenditure that will not likely have an impact on climate trends. And unfortunately, these efforts will likely cause much more harm than good for humanity. Hopefully people and governments will come to their senses before too much unnecessary harm is done.
For for the latest CFSR daily and monthly updates to key figures, see the Daily Updates and Monthly Trends pages accessible from the menu bar at the top of this page.
Happy new year everyone!
UM-CCI data source: Climate Reanalyzer