The magnitude of uncertainty in climate data that can blur the natural climate variability varies greatly with various factors that introduce biases. There are many factors that can impact the integrity of climate observations. Factors such as data assurance and quality control and maintenance are of great importance but are adequately covered under existing training curriculum of NWS TC. In the interest of containing this tutorial to the prescribed one hour session, we therefore focus our attention on the following:
Each factor is reviewed and then followed by recommended actions that can be taken to either minimize or document potential impacts.
Our goal in climate monitoring is to measure variability and change in natural environmental climate elements, not artificial ones such as those introduced by changing instruments, relocating stations, observing practices, etc.
Figure 5 illustrates our attempt to estimate of the relative importance of various factors that can impact the integrity of temperature observations. Other climate elements, such as precipitation (including snowfall), can also be similarly impacted.
As you review the chart, you see that artificially induced biases/discontinuities can be much greater in magnitude than the natural climate change/variability signals we desire to measure and track. If unaccounted for, artificial factors can totally overwhelm and blur the natural climate variability and change signals we so carefully strive to monitor and potentially mitigate.