Historical Changes to Extreme Climate Events

One of the unique aspects of this climate “chapter” is that we are using historical data to reconstruct already observed climate changes in addition to the future projections. The historical data is just that: recorded temperature and precipitation from the recent past. These trends and patterns can help us to understand if and how climate has changed, is currently changing, and make informed interpretations of the future projections of these trends.

Credit: The beauty of Eastern Neck in Chesapeake Bay.

Credit: The beauty of Eastern Neck in Chesapeake Bay.

Of course, the historical data comes in many different “varieties.” For our climate assessment, we have been working with two types of data: gridded products which give regional trends (which are a spatially weighted averages of the near-shore Chesapeake Bay region), and individual weather stations (which give us an idea of spatial heterogeneity and/or homogeneity).

Today I will be showing a few of the regional historical trends using the HadEX2 gridded data product. These climate trends will be used by the CBNERR sites to create educational materials, update their exhibits, and be used in the next phase of this project (so stay tuned!).

Figure 2: The 110 year time series of teh Tropical Nights (TR) index with the 21-year rolling mean.

Figure 2: (left) The 110 year time series of the Tropical Nights (TR) index with a loess smoother and the stationary time series mean and (right) the 21-year rolling mean with the linear regression.

Tropical Nights

The Tropical Nights index is the annual count of days when the daily minimum temperature (Tmin) is greater than 68°F (20°C). Loosely speaking, it is an estimate of the amount of warm summer nights. Our regional analysis suggests that this count of warm nights has been increasing at a rate of 0.42 days per decade (Figure 2).

Why do we care?

So why does it matter that we are experiencing a greater number of warm summer nights each year? At the most basic level, this index predicts we may need to have our AC or fans on perhaps a few more nights to stay cool. But, it also suggests a few environmental concerns.

Hypoxia: The solubility of oxygen decreases with increasing temperatures (simple ideal gas law prediction). Likewise, in many aquatic critters, metabolism also increases with increasing temperatures, meaning a higher oxygen demand (Read more here). Thus, it is possible that more warm nights could exacerbate hypoxic conditions. (This could be fun to investigate more!)

Agriculture: A 2004 study by the Proceedings of the National Academy of Sciences showed that rice yields decreased by about 10% for every 1°C increase of Tmin during the growing season (Peng et al., 2004). The study also attributed reduced yields of maize, wheat, and soybeans also to increasing night time temperatures. While we cannot necessarily do anything about more warm nights, this data could help farmers in understanding how many crops they need to plant to meet their yield demands.

Figure 3:

Figure 3: (left) The 110 year time series of the R10mm index with a loess smoother and the stationary time series mean and (right) the 21-year rolling mean with the linear regression.


The R10mm index is the annual count of days when at least 10 mm (~ 0.4 inches) of precipitation fell. It is a measure of the amount of “wet days” we experience each year. From Figure 3, we can suggest that the count of wet days has increased at a wiggly rate of 0.21 days per decade since 1901.

Why do we care?
Rainy days can really affect my mood (and I’m sure many others). But it can also affect our economy by reducing tourism. An August 2013 article from a North Carolina newspaper wrote about this worry for Onslow County, NC. The 23 rainy days in August of that year caused many traveling beach-goers to cancel their plans, meaning they spent their money elsewhere.

Additionally, more rainy days means a higher potential for nuisance flooding. We’ve all experienced that scary time when you’re driving in the rain, and suddenly the road ahead of you is covered in standing water. You have to carefully assess: “Can I make it through this puddle or will I stall? What if I hydroplane?” These nuisance flooding events can also mean more frequent, and costly, road repairs. You can read more on precipitation trends here and here.)

Below is a table of all the observed rates of change for each extreme climate index. Let us know what other climate “stories” you’ve experienced from extreme events!

Table of the 21-year rolling mean slope's for each extreme

Table of the 21-year rolling mean slope’s for each extreme

Works Cited

Peng, Shaobing, et al. “Rice yields decline with higher night temperature from global warming.” Proceedings of the National Academy of Sciences of the United States of America 101.27 (2004): 9971-9975.


Kari Pohl

About Kari Pohl

I am a post-doctoral researcher at NOAA and the University of Maryland (Center for Environmental Science at Horn Point Laboratory). My work investigates how climate variability and extremes affect the diverse ecosystems in Chesapeake Bay. I received a Ph.D. in oceanography from the University of Rhode Island (2014) and received a B.S. in Environmental Science and a B.A. in Chemistry from Roger Williams University (2009). When I am not busy being a scientist, my hobbies include running, watching (and often yelling at) the Boston Bruins, and taking photos of my cat.
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