From Tel Aviv University, another science press release with “could and may” qualifiers: Climate Change May Lead to Fewer — But More Violent — Thunderstorms
Number of flash floods and forest fires could increase with temperature, says TAU researcher
Researchers are working to identify exactly how a changing climate will impact specific elements of weather, such as clouds, rainfall, and lightning. A Tel Aviv University researcher has predicted that for every one degree Celsius of warming, there will be approximately a 10 percent increase in lightning activity.
This could have negative consequences in the form of flash floods, wild fires, or damage to power lines and other infrastructure, says Prof. Colin Price, Head of the Department of Geophysics, Atmospheric and Planetary Sciences at Tel Aviv University. In an ongoing project to determine the impact of climate change on the world’s lightning and thunderstorm patterns, he and his colleagues have run computer climate models and studied real-life examples of climate change, such as the El Nino cycle in Indonesia and Southeast Asia, to determine how changing weather conditions impact storms.
An increase in lightning activity will have particular impact in areas that become warmer and drier as global warming progresses, including the Mediterranean and the Southern United States, according to the 2007 United Nations report on climate change. This research has been reported in the Journal of Geophysical Research and Atmospheric Research, and has been presented at the International Conference on Lightning Protection.
From the computer screen to the real world
When running their state-of-the-art computer models, Prof. Price and his fellow researchers assess climate conditions in a variety of real environments. First, the models are run with current atmospheric conditions to see how accurately they are able to depict the frequency and severity of thunderstorms and lightning in today’s environment. Then, the researchers input changes to the model atmosphere, including the amount of carbon dioxide in the atmosphere (a major cause of global warming) to see how storms are impacted.
To test the lightning activity findings, Prof. Price compared their results with vastly differing real-world climates, such as dry Africa and the wet Amazon, and regions where climate change occurs naturally, such as Indonesia and Southeast Asia, where El Nino causes the air to become warmer and drier. The El Nino phenomenon is an optimal tool for measuring the impact of climate change on storms because the climate oscillates radically between years, while everything else in the environment remains constant.
“During El Nino years, which occur in the Pacific Ocean or Basin, Southeast Asia gets warmer and drier. There are fewer thunderstorms, but we found fifty percent more lightning activity,” says Prof. Price. Typically, he says,we would expect drier conditions to produce less lightning. However, researchers also found that while there were fewer thunderstorms, the ones that did occur were more intense.
Fire and flood warning
An increase in lightning and intense thunderstorms can have severe implications for the environment, says Prof. Price. More frequent and intense wildfires could result in parts of the US, such as the Rockies, in which many fires are started by lightning. A drier environment could also lead fires to spread more widely and quickly, making them more devastating than ever before. These fires would also release far more smoke into the air than before.
Researchers predict fewer but more intense rainstorms in other regions, a change that could result in flash-flooding, says Prof. Price. In Italy and Spain, heavier storms are already causing increased run-off to rivers and the sea, and a lack of water being retained in groundwater and lakes. The same is true in the Middle East, where small periods of intense rain are threatening already scarce water resources.
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I’m not sure why they think this is news, a nearly identical study was done back in 2007 and published in PNAS:
Changes in severe thunderstorm environment frequency during the 21st century caused by anthropogenically enhanced global radiative forcing
Robert J. Trapp , Noah S. Diffenbaugh, Harold E. Brooks, Michael E. Baldwin, Eric D. Robinson , and Jeremy S. Pal
Abstract
Severe thunderstorms comprise an extreme class of deep convective clouds and produce high-impact weather such as destructive surface winds, hail, and tornadoes. This study addresses the question of how severe thunderstorm frequency in the United States might change because of enhanced global radiative forcing associated with elevated greenhouse gas concentrations. We use global climate models and a high-resolution regional climate model to examine the larger-scale (or “environmental”) meteorological conditions that foster severe thunderstorm formation. Across this model suite, we find a net increase during the late 21st century in the number of days in which these severe thunderstorm environmental conditions (NDSEV) occur. Attributed primarily to increases in atmospheric water vapor within the planetary boundary layer, the largest increases in NDSEV are shown during the summer season, in proximity to the Gulf of Mexico and Atlantic coastal regions. For example, this analysis suggests a future increase in NDSEV of 100% or more in locations such as Atlanta, GA, and New York, NY. Any direct application of these results to the frequency of actual storms also must consider the storm initiation.
Full PDF here
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I find this most interesting:
Attributed primarily to increases in atmospheric water vapor within the planetary boundary layer, the largest increases in NDSEV are shown during the summer season, in proximity to the Gulf of Mexico and Atlantic coastal regions. For example, this analysis suggests a future increase in NDSEV of 100% or more in locations such as Atlanta, GA, and New York, NY. Any direct application of these results to the frequency of actual storms also must consider the storm initiation.
Yes, you must consider the storm initiation. The one thing the Tel Aviv researchers apparently have not taken into account in their GCM’s is urban evapotranspiration increases (due to irrigation), aerosols (dust and other cloud seeding nuclei from the urban area) and the role of UHI and boundary layer surface roughness in helping thunderstorm formation. Such factors have been shown to be a powerful convection assistant:
Urban Aerosol Impacts on Downwind Convective Storms
Susan C. van den Heever and William R. Cotton (2007 BAMS)
The impacts of urban-enhanced aerosol concentrations on convective storm development and precipitation over and downwind of St. Louis, Missouri, are investigated. This is achieved through the use of a cloud-resolving mesoscale model, in which sophisticated land use processes and aerosol microphysics are both incorporated. The results indicate that urban-forced convergence downwind of the city, rather than the presence of greater aerosol concentrations, determines whether storms actually develop in the downwind region. Once convection is initiated, urban-enhanced aerosols can exert a significant effect on the dynamics, microphysics, and precipitation produced by these storms. The model results indicate, however, that the response to urban-enhanced aerosol depends on the background concentrations of aerosols; a weaker response occurs with increasing background aerosol concentrations. The effects of aerosols influence the rate and amount of liquid water and ice produced within these storms, the accumulated surface precipitation, the strength and timing of the updrafts and downdrafts, the longevity of the updrafts, and the strength and influence of the cold pool. Complex, nonlinear relationships and feedbacks between the microphysics and storm dynamics exist, making it difficult to make definitive statements about the effects of urban-enhanced aerosols on downwind precipitation and convection. Because the impacts of urban aerosol on downwind storms decrease with increasing background aerosol concentrations, generalization of these results depends on the unique character of background aerosol for each urban area. For urban centers in coastal areas where background aerosol concentrations may be very low, it is speculated that urban aerosol can have very large influences on convective storm dynamics, microphysics, and precipitation.
and this one:
Simulation of St. Louis, Missouri, Land Use Impacts on Thunderstorms
Christopher M. Rozoff, William R. Cotton, and Jimmy O. Adegoke (JAM 2003)
A storm-resolving version of the Regional Atmospheric Modeling System is executed over St. Louis, Missouri, on 8 June 1999, along with sophisticated boundary conditions, to simulate the urban atmosphere and its role in deep, moist convection. In particular, surface-driven low-level convergence mechanisms are investigated. Sensitivity experiments show that the urban heat island (UHI) plays the largest role in initiating deep, moist convection downwind of the city. Surface convergence is enhanced on the leeward side of the city. Increased momentum drag over the city induces convergence on the windward side of the city, but this convergence is not strong enough to initiate storms. The nonlinear interaction of urban momentum drag and the UHI causes downwind convection to erupt later, because momentum drag over the city regulates the strength of the UHI. In all simulations including a UHI, precipitation totals are enhanced downwind of St. Louis. Topography around St. Louis also affects storm development. There is a large sensitivity of simulated urban-enhanced convection to the details of the urban surface model.
In 2000, Qing Lu Lin and Robert Bornstein, from San Jose State University, used data from meteorological stations set up during the 1996 Summer Olympics and discovered that the urban heat island in Atlanta created frequent thunderstorms. Using the National Weather Service’s newly installed local mesonet to collect data (setup for the purpose of aiding weather forecasts for Olympic athletic events), Lin and Bornstein found that five of nine days of precipitation over Atlanta were caused by the urban heat island effect.
Urban heat islands and summertime convective thunderstorms
in Atlanta: three case studies Lin and Bornstein 2000 (PDF)
Abstract
Data from both 27 sites in the Atlanta mesonet surface meteorological network and eight National Weather Service sites were analyzed for the period from 26 July to 3 August 1996. Analysis of the six precipitation events over the city during the period (each on a di!erent day) showed that its urban heat island (UHI) induced a convergence zone that initiated three of the storms at di!erent times of the day, i.e., 0630, 0845, and 1445 EDT. Previous analysis has shown that New York City (NYC) e!ects summer daytime thunderstorm formation and/or movement. That study found that during nearly calm regional flow conditions, the NYC UHI initiates convective activity. Moving thunderstorms, however, tended to bifurcate and to move around the city, due to its building barrier e!ect. The current Atlanta results thus agree with the NYC results with respect to thunderstorm initiation.
And then there’s this one: (from planning.org)
The urban heat island effect causes the warmer air (including its higher concentrations of moisture and pollutants) to rise more readily than cooler air over non-urban areas (Oke 1987). Consequently, moisture and pollutants are transported into higher levels of the urban atmosphere. Thus, the urban heat island creates a warmer, moister atmosphere over the city. Once lifted, the air will cool and, if enough moisture is available, clouds and precipitation may form.The increased number of cloud condensation nuclei (CCN) and ice forming nuclei (IN) from urban pollution further enhances urban precipitation.
See: http://www.atmosphere.mpg.de/enid/3rm.html and watch the animations.
It seems to me that local boundary layer conditions have a far greater impact on thunderstorms than a 0.8C per century background warming signal. Further, as cities tend to increase their area, the local effects on thunderstorm formation are likely to increase.
For example, this recent story thanks to Dr. Roger Pielke Sr.
One of the points worth noting is that there were fewer than 20 cities of 1 million or more a century ago, there are 450 today.
It seems that when they ignore important and significant mesoscale urban factors like these in favor of broader GCM models, the Tel Aviv researchers have a clear case of modeled confirmation bias on their hands.
After all, thunderstorms are local events, so shouldn’t they be looking for local factors too?
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How did aerodynamics get folded into modeling, that is never tested in real world conditions.
u.k. (us) says:
July 11, 2012 at 5:43 pm
How did aerodynamics get folded into modeling, that is never tested in real world conditions.
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It didn’t, it produced the F-15.
The nightmare of any enemy pilot, that might be forced to take-off.
davidmhoffer says:
July 11, 2012 at 12:00 pm
Steven Mosher;
rather than have a knee jerk response to “modelling” remember that we often use modelling when it is too dangerous to do the actual experiment. We model planes before we fly them.
>>>>>>>
NO MODEL CAN PREDICT THE BEHAVIOR OF THE HUMAN BODY!
This is one of the biggest problems in technical engineering – the inability to predict the real damages the human body will suffer. Even the most sophisticated dummies are not even CLOSE to our body. Let alone all these models.
As somebody already said: models are good tools to understand isolated processes, not to predict them.
And as good they may be, they are always bound by our knowledge and capability.
Just take a look at the weather forecasting – 3 days are the best we can have with reasonable prediction.
Climate? phhhh!
So they looked at “…regions where the climate changes naturally…”, as opposed to regions where it doesn’t?
Nice between the lines message – these exotic places we list have natural climate change, the stuff round your way is all the fault of mankind.
Mechanical modelling generally uses Finite Element Analysis (FEA) to refine models of mechanical components before real world testing is used to verify the model. The selection of the number of nodes to represent the component is obviously critical to the accuracy of the model: too few nodes and the model is not realistic and too many nodes results in unacceptable computational times or even complete failure of analysis.
So how to choose the optimal number of nodes? I am told by the experts that the method of producing confidence in the model outcome is to increase the number of nodes in successive computations until the results start to converge, and at the convergence point you can have a reasonable confidence that you have got it right.
Now I see the gridded system used in climate models to be equivalent to the nodal system used in FEA. The fundamental step that seems to be missing is that they are working essentially with static grid sizes. I have seen nothing that suggests that they are decreasing the grid size (equivalent to increasing the number of nodes) until they see evidence of convergence and hence have an indication that they may be close to an accurate simulation.
Can anyone with experience of designing climate models comment on how they assess the potential accuracy of gridded models
computer modelling …another name for “agenda”
like in politics. one can not argue or debate true believers. Darwinian logic says this would happen.
Thanks Anthony, that explains why every where around me, (Raleigh NC, Cary, Apex, Sanford, Siler City, Fayetteville, Chapel Hill…) gets thunderstorms in the summer but we do not. No cities for at least 15 miles in any direction.
I have repeatedly watched T-storms form, dissipate just before they get to us and then reform after they pass as they come up to the next city, VERY frustrating but at least now I know why.
Peter Plail says: July 12, 2012 at 5:45 am
“Can anyone with experience of designing climate models comment on how they assess the potential accuracy of gridded models”
Thanks for your comment Peter. I’m not a climate model but I’ve studied this subject (CAGW science) for almost 30 years.
Grid size is a “second-tier problem” for the modelers, imo.
A “first tier problem” of climate models is that they the models do not produce any credible results – for example, they consistently over-predict global temperatures, the “hot spot” they predict at altitude simply does not exist, and they fail to deal adequately with clouds.
The problem, in part, is that climate models are being used as political models rather than scientific models. The “climate sensitivity” (to CO2) input typically used in these models is about an order of magnitude (10x) too high, in order to support alarmist claims of catastrophic manmade global warming. I cannot estimate how much of the utter predictive failure of these models is due to actual model inadequacies, and how much is due to improper and excessive climate sensitivity input parameters.
Has anyone EVER seen results of a climate model run with climate sensitivity of ~0.3C – which is a value I estimated about a decade ago, based on real climate data?
I would be curious to see if such a model run actually demonstrated some predictive capability, when compared to actual satellite measurements available since 1979, AND also surface temperature measurements available for a few centuries (even though the surface temperature data has a definite warming bias of about 0.07C per decade (at least for recent decades, and perhaps much longer).
In the bigger picture, I doubt these climate models have ANY predictive skill, because their basic assumption is that atmospheric CO2 significantly drives temperature – whereas there is considerable evidence that points to the reverse – that temperature drives atmospheric CO2.
Peter Plail;
Now I see the gridded system used in climate models to be equivalent to the nodal system used in FEA.
>>>>>>>>>>>
I don’t. FEA is a way of breaking down a physical structure into elements so that you can understand how the structure will respond when subjected to various forces. (that’s an over simplification but good enough for this discussion). Modelling climate on the other hand requires an undertanding of radiative phyiscs, fluid dynamics, chemistry, and hald a dozen other disciplines all interacting with each other at the same time. FEA is tiddly winks by comparison.
Off topic: I can’t seem to access the Joanne Nova website. Is there something wrong with her website?
Allan MacRae says: July 12, 2012 at 7:52 am
Apologies for poor editing of my above post – anyway, you get the idea.
Researchers predict fewer but more intense rainstorms in other regions, a change that could result in flash-flooding, says Prof. Price. In Italy and Spain, heavier storms are already causing increased run-off to rivers and the sea, and a lack of water being retained in groundwater and lakes. The same is true in the Middle East, where small periods of intense rain are threatening already scarce water resources.
Do climate scientists never read previous generation’s work? Researchers years ago predicted that reducing the particle levels by cleaning up the atmosphere would result in rain being less frequent but more intense. It did not need any computer models to show it as there were physical tests that had already been done to prove the case. It really saddens me the way computer modeling has sunk to such the depths they have done in the climate science world as they could so easily have been used rather than abused. It is wrong to blame the tools for the ignorance of their users however.
Of course the increased run off into the rivers is nothing to do with the fashionable “Mediterranean” style garden and the increased building on the flood plains with the attendant drainage program.