The quasi-geostrophic height tendency equation is a prognostic equation that tells us how synoptic-scale systems are likely to evolve in time: strengthening/weakening of highs and lows #SJSU#METR171a#SynopticMeteorology
Pressure height falls and thus the development of lows (or the weakening of highs) are associated with positive vorticity advection by the geostrophic wind and/or increasing warm air advection with height or decreasing cold air advection with height by the geostrophic wind
Pressure height rises and thus the weakening of lows (or development of highs) are associated with negative vorticity advection by the geostrophic wind and increasing cold air advection with height or decreasing warm air advection with height by the geostrophic wind
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I have a piece out today in The Chronicle of Higher Education on how social and career incentives surrounding researchers cause a good portion of the full story on the climate problem to be left out of the high-impact literature. 🧵 chronicle.com/article/does-c…
I also recently gave a seminar for the Energy Policy and Climate Program at Johns Hopkins University (where I am a lecturer) that covers the same topic:
This piece stems from a frustration I feel about not being able to take the high-impact climate science literature at face value.
Even if temperatures return to the middle of the climate model projection envelope by the late 2020s, we still expect temperatures like those seen in 2023 to be commonplace in the 2030s...
Thus, any drastic change in weather at the regional level (like in the US) associated with this level of global warmth would be quite concerning when considering climate impacts over the coming decades.
On that front, The New York Times purported to connect the recent spike in global temperatures to a summer of unusually devastating weather in the US in a piece called Why Summers May Never Be the Same. The globe’s warmest months on record redefined summer for many Americans.
Last week, I described our paper on climate change and wildfires:
I am very proud of this research overall. But I want to talk about how molding research presentations for high-profile journals can reduce its usefulness & actually mislead the public.
I mentioned that this research looked at the effect of warming in isolation but that warming is just one of many important influences on wildfires with others being changes in human ignition patterns and changes in vegetation/fuels.
We have a paper out today in @Nature on the role that human-caused climate change is playing in changes in extreme wildfire behavior, at the daily timescale, in California.
Many previous studies have looked at the influence of climate change on wildfires in California, the US West, and around the world. However, most previous studies have focused on *conditions conducive* to wildfires rather than characteristics of wildfires themselves.
This is exemplified by the relevant statement in the latest Intergovernmental Panel on Climate Change (IPCC) report, which is an assertion about weather conditions conducive to wildfires.
I have a paper out today highlighting an error in the climate impacts literature that leads to major exaggerations of the influence of climate change on extreme weather impacts.
This error originated in the journal Nature, has been endorsed by the IPCC, and it undergirds some of the most attention-grabbing headlines assigning deaths and dollars to climate change. For example, the error provides the foundation for the following headlines:
“Climate crisis to blame for $67bn of Hurricane Harvey damage - study”.
When extreme precipitation or a drought occurs, it is often reflexively reported to have been “made worse,” “intensified,” or “driven” by climate change.
But could it have been made less intense by climate change?
How confident are we in the influence of increased greenhouse gasses on changes in extreme precipitation and droughts? It turns out, not very confident.
We use climate models to assess the influence of increased greenhouse gas concentrations on weather events.
There are dozens of models that differ slightly in their construction and, thus their output.
The *range* of output from models serves as a proxy for our uncertainty on how something like extreme precipitation or drought is changing under increased greenhouse gas concentrations