Insights & News

Climate Change: A New Inconsistency

28th November 2019

James Peacock… our Head Meteorologist

Takes a Look at The Intricate Realities of a Changing Climate in Weather Terms

Climate change is not uniform between places and seasons.

We assume warming is occurring, and as a trend, it is true that in the boreal summer (Jun-Aug), most of the world has seen a warming trend since the 1990s (Figure 1; left). Prominent examples include New York (+0.6°C per decade) and Moscow (+0.8°C per decade).

With this, the number of hot days is absolutely soaring (Figure 2), with significant implications for human health in both work and leisure.

However, this is not the case globally.

Though the exceptions are few… they’re essential in highly localised decision-making.

Considering Continents…

Seasonally Specific: Chilly Asia

Check out the Philippines, for example, which has trended down by an average of ~ 0.3°C per decade.

Boreal winter (Dec-Feb) also brings dramatic contrasts between locations: Across vast swathes of Eurasia warm Jun-Aug trends starkly oppose cool Dec-Feb trends (Figure 1; right). Increased heatwave risk in summer and increased perishing cold risk in winter – climate change wields a double-edged sword.

Spatially Specific: Macro-Scale Matters

In the US, there’s a strong warming trend in most of the western half, yet the eastern half has trended much cooler. This has big implications for the evolution of disruptive snow risk with climate change; a reducing tendency in Denver (Colorado), but an increasing one in Washington, D.C.

Figure 1: Maps showing the mean decadal trend in mean surface air temperatures (°C) since the 1990s.

Figure 1: Maps showing the mean decadal trend in mean surface air temperatures (°C) since the 1990s.

 

Figure 2: Graphs of decadal mean count of days with a maximum temperature of at least 30°C, for the period 1st Jun to 31st Aug, for New York, USA (left) and Moscow, Russia (right).

Figure 2: Graphs of decadal mean count of days with a maximum temperature of at least 30°C, for the period 1st Jun to 31st Aug, for New York, USA (left) and Moscow, Russia (right).

It’s Wetter and It’s Drier

The spatial and seasonal inconsistency of climate change applies to weather types other than temperature. Even looking all the way back to the 1950s, mean decadal trends tell different stories from one place to the next.

In Istanbul, Turkey, decadal rainfall means for the 1990s to 2010s have all been approx. 1.5 to 3.5 days higher than that of the 1980s (Figure 3).

Contrast that with Athens, Greece, where the 1980s saw a peak in dry runs that no decade since has come close to matching.

Figure 3: Graphs, for Istanbul, Turkey (left) and Athens, Greece right), of decadal mean maximum cumulative dry days for the period 1st Jun to 31st Aug. This is defined as the run of days with no single day reaching 1 mm and no three consecutive days reaching 0.25 mm.

Figure 3: Graphs, for Istanbul, Turkey (left) and Athens, Greece right), of decadal mean maximum cumulative dry days for the period 1st Jun to 31st Aug. This is defined as the run of days with no single day reaching 1 mm and no three consecutive days reaching 0.25 mm.

Drought Dread or Flood Fear?

There’s a strong connection to drought risk here. The probability of serious summer losses to damaging drought has increased in Istanbul. In Athens, less than 600 km to the southwest, it’s no more than it was in the 1960s.

In fact, flooding is now of far greater concern there. The decadal mean Jun-Aug rainfall for the 2010s is just over double the highest of the 1950s to 2000s.

Striking contrasts can be found from the United States to New Zealand, if you look hard enough and with the right tools. If you’re assessing for July events in Surat on the western coast of India, you’ll find that very wet days are increasing in frequency, raising the flash-flooding risk. If your July events are in Kolkata on the east coast, however, flash-flooding will be far from the most pressing climatic concern (Figure 4).

Figure 4: Graphs of decadal mean count of days with at least 20.0 mm of precipitation, for the period 1st Jun to 31st Aug, for Surat (left) and Kolkata (right), India.

Figure 4: Graphs of decadal mean count of days with at least 20.0 mm of precipitation, for the period 1st Jun to 31st Aug, for Surat (left) and Kolkata (right), India.

Hyperlocal is Hyper-Effective

With the seasonal and geospatial inconsistencies of climate change country and continent wide, generalisations introduce their own risk, in misjudging the climate trend for the specific location of your event or construction project (for example). In that instance, no amount of decision-making skill and purely raw data analysis is going to make the best call.

This is where MetSwift’s revolutionary, award-winning AI comes into its own. Hyperlocal risk information delivered in a few clicks!

 

James Peacock MSc

Head Meteorologist at MetSwift

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