Anthropogenic Fingerprint Detectable in Upper Tropospheric Ozone Trends Retrieved from Satellite.

Tropospheric ozone (O) is a strong greenhouse gas, particularly in the upper troposphere (UT). Limited observations point to a continuous increase in UT O in recent decades, but the attribution of UT O changes is complicated by large internal climate variability. We show that the anthropogenic signal ("fingerprint") in the patterns of UT O increases is distinguishable from the background noise of internal variability.

Exceptional stratospheric contribution to human fingerprints on atmospheric temperature.

In 1967, scientists used a simple climate model to predict that human-caused increases in atmospheric CO should warm Earth's troposphere and cool the stratosphere. This important signature of anthropogenic climate change has been documented in weather balloon and satellite temperature measurements extending from near-surface to the lower stratosphere. Stratospheric cooling has also been confirmed in the mid to upper stratosphere, a layer extending from roughly 25 to 50 km above the Earth's surface (S).

Internal variability and forcing influence model-satellite differences in the rate of tropical tropospheric warming.

Climate-model simulations exhibit approximately two times more tropical tropospheric warming than satellite observations since 1979. The causes of this difference are not fully understood and are poorly quantified. Here, we apply machine learning to relate the patterns of surface-temperature change to the forced and unforced components of tropical tropospheric warming.

Quantifying contributions of natural variability and anthropogenic forcings on increased fire weather risk over the western United States.

Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns.