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Climate Confusion and Clarity

Climate Confusion and Clarity

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Christelle Lagace-Babim, left, and Elise Lagace walk along Rue Jacques-Cartier Friday, after checking out their home in Gatineau, Que., as significant rainfall continues to cause flooding. (Justin Tang/Canadian Press)

A lot of verbage about global warming/climate change is worse than useless because the parties are using terms whose meaning is vague or equivocal, and thus no meaningful interaction occurs. Alarmists/activists claim climate change is real, man-made, and dangerous (Obama tweet). Skeptics/doubters respond that climate is always changing, has been both warmer and cooler in the past, long before humans did anything.

In addition, climate confusion causes statements like this one recently in the CBC: Gatineau flooding ‘tip of the iceberg,’ climate scientist warns

Swollen rivers and streams have threatened hundreds of homes in the Outaouais thanks to recent heavy rainfall — three times the normal amount since April 1.

University of Ottawa climate scientist Paul Beckwith says that’s due to a changing climate, and says we’re seeing its effects “on a day-to-day basis” in weather patterns.

Beckwith points to an increase in extreme weather events across North America as proof. “We’ve changed the chemistry of the atmosphere and the oceans with our greenhouse gases, so we’re seeing the consequences of this now,” he added. “It’s only the tip of the iceberg, so to speak.”

Such reports mislead people to think of the climate acting like some kind of agent causing the weather to change in ways unfavorable to us. That confuses the relation between climate and weather, as we shall see below.

What is “Weather”?

Fortunately in science things get defined not theoretically but by observations and measurements. In science, weather is defined as the behavior we measure on a daily basis. In fact today’s automated weather equipment monitors the weather constantly. Let us consider an operational definition of weather to be the variables for which data is reported into global databases.

Each National Weather Service has its own additional particulars they track, but the common global definition of weather can be seen in the defined elements from the ECA&D weather data dictionary (European Climate Assessment & Dataset)

Weather Measurement Elements

What is weather: Eight variables are measured globally–Sunshine, Sea Level Pressure, Humidity, Cloud cover, Wind, Precipitation, Snow Depth, Temperature. With multiple measures of some variables, weather datasets consist of 13 common elements.

Sunshine (SS) in units of 0.1 hour. Total daily SS plus measures of hours for intervals during the day.

Sea Level Pressure (PP) in units of 0.1hPa Daily average PP plus measures for specific times and parts of the day.

Humidity (HU) in units of 1% of relative humidity. Daily average HU plus measures for specific times and parts of the day.

Cloud Cover (CC) in oktas (0 being clear sky, 8 being completely overcast). Daily average CC plus measures for specific times and parts of the day.

Wind Direction (DD) in degrees azimuth for the wind source (that is, a southerly wind comes from 180 degrees.) Daily average DD plus measures for different times of day, and the direction of maximum gust.

Wind Speed (FG) in units of 0.1 m/s. Daily average FG plus measures for speeds at different times and parts of the day.

Wind Gust (FX) in units of 0.1m/s Daily average FX (24 hourly gusts) plus measures for maximums of different durations. (2 to 15 minutes).

Precipitation Amount (RR) in units of 0.1 mm. Daily total RR plus measures of amounts for intervals during the day.

Maximum Hourly Precipitation (MXR) in units of 0.1 mm. MXR for the dayplus measures of amounts for intervals during the day.

Snow Depth (SD) in units of 1 cm. Mean daily SD plus measures of depths for intervals during the day.

Mean Temperature (TG) in units of 0.1C. Daily TG plus measures of various ways of calculating TG.

Minimum Temperature (TN) in units of 0.1C. Daily TN plus measures for different times and parts of the day.

Maximum Temperature (TX) in units of 0.1C. Daily TX plus measures for different times and parts of the day.

What is “Climate”?

Change in Frequency of Frost Days in Europe in the Period 1976-2006

To sort out the confusion between “weather” and “climate”, we can also look at how climate is measured and thereby defined. From the same ECA&D source is a climate indices database which is termed Indices of Extremes’

There is one datafile for each index. Each datafile gives information for all available stations in the ECA&D database. The indices are aggregated over the year, the winter-half (ONDJFM), the summer-half (AMJJAS), winter (DJF), spring (MAM), summer (JJA), autumn (SON) and each of the calendar months.

There are 75 indices grouped into eleven categories corresponding with different aspects of climate change. Some categories come directly from weather elements, while others are derivations.

The 75 indices are statistics built upon weather data, adding patterns of interest to humans. For example, temperature is greatly emphasized by adding various concerns with heat and cold on top of temperature records. Also, a compound category focuses on temperature and precipitation combinations and their favorability to humans.

What is Climate: Categories and Indices

 

Note that climate is operationally defined as statistical patterns of weather data. Some indices are simply averages of daily weather over long term periods. By convention, a 30-year average is used to define a climate baseline for a location.

Other climate indices are based on value judgments according to human interests. For example, heat and cold include many examples like growing days, good tourism days, heating degree days. In fact, a feature of climate is the imposition of human expectations upon nature, other examples being the sunshine indices Mostly Sunny and Mostly Cloudy days.

Andrew John Herbertson, a British geographer and Professor at Oxford, wrote in a textbook from 1901:

By climate we mean the average weather as ascertained by many years’ observations. Climate also takes into account the extreme weather experienced during that period. Climate is what on an average we may expect, weather is what we actually get.

Mark Twain, who is often credited with that last sentence actually said:

Climate lasts all the time and weather only a few days.

The point is, weather consists of events occurring in real time, while climate is a statistical artifact. Weather is like a baseball player swinging in the batter’s box, climate is his batting average, RBIs, bases on balls, etc.

What is “Climate Change”

The usefulness of climate indices is suggested by the last category called compound, where temperature and precipitation patterns are combined. In fact those two factors are sufficient to define distinctive local climate zones..

Based on empirical observations, Köppen (1900) established a climate classification system which uses monthly temperature and precipitation to define boundaries of different climate types around the world. Since its inception, this system has been further developed (e.g. Köppen and Geiger, 1930; Stern et al., 2000) and widely used by geographers and climatologists around the world.

 

Köppen climate zones as they appear in the 21st Century.

As an example, consider how the island of Hawaii looks with its climate zones indicated:

Note: This image comes from an interactive tool and uses a different color scheme than the global map above.

Köppen and Climate Change

The focus is on differentiating vegetation regimes, which result primarily from variations in temperature and precipitation over the seasons of the year. Now we have an interesting study that considers shifts in Köppen climate zones over time in order to identify changes in climate as practical and local/regional realities.  The paper is: Using the Köppen classification to quantify climate variation and change: An example for 1901–2010 By Deliang Chen and Hans Weiteng Chen Department of Earth Sciences, University of Gothenburg, Sweden

Hans Chen has built an excellent interactive website (here): The purpose of this website is to share information about the Köppen climate classification, and provide data and high-resolution figures from the paper Chen and Chen, 2013:  For more details on Chen and Chen see the post: Data vs. Models 4: Climates Changing

Conclusion:

Chen and Chen provide a data-based definition of “climate change”. Climate zones are defined by past temperature and precipitation ranges observed by humans. The weather datasets and climate indices inform us whether or not the patterns in a place are moving outside the norm for that location. Climate change appears as a shift in zonal boundaries so that one place starts to resemble a neighboring zone with a different classification.  The table below shows the defined zones and thresholds.

Zones Zones Description Thresholds
A Tropical climates Tmin ≥ +18 °C
Af Tropical rain forest Pmin ≥ 60 mm
Am Tropical monsoon Pann ≥ 25(100 – Pmin) mm
As Tropical savannah with dry summer Pmin < 60 mm in summer
Aw Tropical savannah with dry winter Pmin < 60 mm in winter
B Dry climates Pann < 10 Pth
BW Desert (arid) Pann ≤ 5 Pth
BS Steppe (semi-arid) Pann > 5 Pth
C Mild temperate -3 °C < Tmin < +18 °C
Cs Mild temperate with dry summer Psmin < Pwmin, Pwmax > 3 Psmin, Psmin < 40 mm
Cw Mild temperate with dry winter Psmax > 10 Pwmin, Pwmin < Psmin
Cf Mild temperate, fully humid Not Cs or Cw
D Snow Tmin ≤ -3 °C
Ds Snow with dry summer Psmin < Pwmin, Pwmax > 3 Psmin, Psmin < 40 mm
Dw Snow with dry winter Psmax > 10 Pwmin, Pwmin < Psmin
Df Snow, fully humid Not Ds or Dw
E Polar Tmax < +10 °C
ET Tundra Tmax ≥ 0 °C
EF Frost Tmax < 0 °C

The Chen and Chen analysis shows that almost half of climates around the world will get a year of weather outside of their normal ranges. Getting a decade of abnormal weather is much rarer. True climate change would be a shift enduring over a 30 year period which has been observed in less than 10% of all climate zones.

Footnote:

This post was focused on the distinction between weather and climate, so extreme weather events were not discussed, since by definition such events are weather. Still the quote above shows that activists are working hard to attribute attention-grabbing events as proof of global warming/climate change.

Mike Hulme wrote a series of articles describing the effort to link extreme weather to climate change and said this:
In recent decades the meaning of climate change in popular western discourse has changed from being a descriptive index of a change in climate (as in ‘evidence that a climatic change has occurred’) to becoming an independent causative agent (as in ‘climate change caused this event to happen’). Rather than being a descriptive outcome of a chain of causal events affecting how weather is generated, climate change has been granted power to change worlds: political and social worlds as much as physical and ecological ones.

More at X-Weathermen are Back 

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May 6, 2017 at 05:45AM

China Fuels Coal Renaissance As Trump Weighs Global Warming Treaty

China Fuels Coal Renaissance As Trump Weighs Global Warming Treaty

via The Global Warming Policy Forum (GWPF)
http://www.thegwpf.com

China is generating more electricity than ever from coal-fired power plants and backing the construction of about one dozen coal plants in Pakistan over the next 15 years.

Chinese statistics show coal power generation hit a record 396.1 billion kilowatt hours (kWh) in March, which is nearly 8 percent above coal generation the previous year. That came after China generated a record-breaking 385.6 billion kWh in December 2016, Platts reported.

At the same time, China entered into a joint venture with Pakistan that is “expected to spend around $15 billion over the next 15 years to build close to a dozen coal power plants of varying sizes around the country,” Reuters reported.

Environmentalists have opposed the deal, but officials have said the new coal plants will use “supercritical” technology, which drastically cuts down on traditional pollutants and carbon dioxide emissions.

“The latest coal power plants (will) be as clean as gas-based power generation,” Pakistani minister Ahsan Iqbal told Reuters. “(They) require less coal per megawatt-hour, leading to lower emissions, including carbon dioxide and mercury, higher efficiency and lower fuel costs per megawatt.”

The coal plants are part of a $33 billion agreement between China and Pakistan to electrify the region, which Iqbal said is needed to “meet the country’s energy needs for several decades, for powering the country’s economic wheel, creating new jobs, and fighting spiking unemployment and poverty.”

Interestingly enough, this is pretty much exactly what China said it would do to fight global warming and cut emissions.

China pledged to “peak” total greenhouse gas emissions by 2030 or earlier while reducing its emissions to gross domestic product ratio. The Obama administration hailed the move as a coup, despite the fact that China promised to ramp up its coal use.

The news comes as President Donald Trump weighs pulling out of the Paris agreement on climate change, which former President Barack Obama joined in 2016.

Full story

via The Global Warming Policy Forum (GWPF) http://www.thegwpf.com

May 6, 2017 at 05:29AM

The Gentleman Snake

The Gentleman Snake

via The Deplorable Climate Science Blog
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More pictures from this morning.

The nice thing about Rattlesnakes is they let you know they are there, and that they aren’t happy about it.

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May 6, 2017 at 03:43AM

Link to climate forcing by the sun found by the SATIRE (Spectral And Total Irradiance REconstruction)

Link to climate forcing by the sun found by the SATIRE (Spectral And Total Irradiance REconstruction)

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Our resident solar physicist, Dr. Leif Svalgaard sends word of this paper:

​

Climate responses to SATIRE and SIM-based spectral solar forcing in a 3D atmosphere-ocean coupled GCM

Abstract

We apply two reconstructed spectral solar forcing scenarios, one SIM (Spectral Irradiance Monitor) based, the other the SATIRE (Spectral And Total Irradiance REconstruction) modeled, as inputs to the GISS (Goddard Institute for Space Studies) GCMAM (Global Climate Middle Atmosphere Model) to examine climate responses on decadal to centennial time scales, focusing on quantifying the difference of climate response between the two solar forcing scenarios. We run the GCMAM for about 400 years with present day trace gas and aerosol for the two solar forcing inputs. We find that the SIM-based solar forcing induces much larger long-term response and 11-year variation in global averaged stratospheric temperature and column ozone. We find significant decreasing trends of planetary albedo for both forcing scenarios in the 400-year model runs. However the mechanisms for the decrease are very different. For SATIRE solar forcing, the decreasing trend of planetary albedo is associated with changes in cloud cover. For SIM-based solar forcing, without significant change in cloud cover on centennial and longer time scales, the apparent decreasing trend of planetary albedo is mainly due to out-of-phase variation in shortwave radiative forcing proxy (downwelling flux for wavelength >330 nm) and total solar irradiance (TSI). From the Maunder Minimum to present, global averaged annual mean surface air temperature has a response of ~0.1 °C to SATIRE solar forcing compared to ~0.04 °C to SIM-based solar forcing. For 11-year solar cycle, the global surface air temperature response has 3-year lagged response to either forcing scenario. The global surface air 11-year temperature response to SATIRE forcing is about 0.12 °C, similar to recent multi-model estimates, and comparable to the observational-based evidence. However, the global surface air temperature response to 11-year SIM-based solar forcing is insignificant and inconsistent with observation-based evidence.

(a) Simulated global averaged annual mean temperature variations (thinner lines) for SATIRE spectral solar forcing and the responses extracted from the regression analysis of the modeled data (thicker lines) for different altitudes. Correlation coefficients between modeled variation and response from regression analysis are indicated. (b) Simulated global averaged annual mean temperature variations (thinner lines) for SIM-based spectral solar forcing and the responses extracted from the regression analysis of the modeled data (thicker lines) for different altitudes. Correlation coefficients between modeled variation and response from regression analysis are indicated.

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May 6, 2017 at 02:50AM