Archive for the ‘Agriculture’ Category

The terms ‘dangerous climate change’ and ‘climate sensitivity’; what do they mean and why are they so important in the climate change debate?

 

By David Holland

Dangerous Climate Change

A better way to put it may be (DAI) or dangerous anthropogenic interference with the climate system.

The word dangerous is an emotive word that has no definite meaning in relation to climate change. But risk of damage to social, economic and in particular ecological systems could give more understanding to the term.

The IPCC assessment gives 5 reasons for concern to guide policy makers.

  1. Risks to unique and threatened systems
  2. Risks of extreme weather events
  3. Distribution of impacts and vulnerabilities
  4. Aggregate impacts
  5. Risks of large-scale singularities.

The 2009 Copenhagen Climate congress, which held to the 2007 IPCC assessment, said that only society in general can give an opinion on the dangerousness of climate interference not science or any scientists.

Michael Mann:

“The Intergovernmental Panel on Climate Change (IPCC) is charged by the United Nations Environment Program to assess climate change risks in a way that informs, but, importantly, does not prescribe the government policies necessary to avoid DAI [dangerous anthropogenic interference with the climate system]. It is therefore not surprising that the IPCC stops short of defining what DAI actually is, let alone advocating policies designed to avoid it.”

— Michael Mann, in Defining dangerous anthropogenic interference (Proceedings of the National Academy of Science (PNAS), March 2009)
The UN Framework Convention on Climate Change defines dangerous as “adverse effects of climate change in its Article 1:

“Adverse effects of climate change” means changes in the physical environment or biota resulting from climate change, which have significant deleterious effects on the composition, resilience or productivity of natural and managed ecosystems or on the operation of socio-economic systems or on human health and welfare.

“Climate change” means a change of climate, which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods.

“Climate system” means the totality of the atmosphere, hydrosphere, biosphere and geosphere and their interactions.
Climate Sensitivity

Climate sensitivity is the sensitivity of the climate to CO2 concentration increases. The term equilibrium climate sensitivity or (ECS) is a change in the surface temperature due to a doubling of CO2 concentrations. It relates to what the temperature would be if the concentration of CO2 were to double from pre-industrial concentration. The best estimates under (AR5) is 1.5 degrees to 4.5 degrees increase in temperature for a doubling of CO2 levels. (IPCC 2013) Transient climate response (TCR) is simply the global warming temperature when CO2 doubles in the atmosphere by following a linear increase over a period of 70 years of CO2 forcing. (Nicholas Lewis, Judith A Curry ~ 2014, Climate Sensitivity Fact Sheet )

 Why are they important to the climate change debate?

Most people would understand what dangerous is in other contexts and now we need to explain what we mean in real terms. Climate change will change everything we do and affect our economy. Sensitivity of climate is simply related to how much warming will happen if we cannot reduce the green house gas emissions. It is the warming that is the part that is “dangerous” to our way of life, not so much the CO2 concentrations as part of the air that we breath.

The understanding that the climate and its sensitivity is a story that needs to be told and now is the time this sensitivity must be addressed before the climate responds to us by imposing its consequences on the things we do and the life we live.

 

References:

Climate Sensitivity Fact Sheet, Department of Environment, Australian Government, https://www.environment.gov.au/system/files/resources/d3a8654f-e1f1-4d3f-85a1-4c2d5f354047/files/factsheetclimatesensitivitycsiro-bureau.pdf, Accessed Sept.2016.

IPCC, Climate Change 2013, The Physical Science basis, Assessment Report No 5 (AR5) working Group 1: Near term Climate Change: Projections and Predictability, Chapter 11, Section The Water Cycle, Changes in Precipitation.

Lewis N, Curry J, (April 2016), Updated climate sensitivity estimates, Climate Etc., https://judithcurry.com/2016/04/25/updated-climate-sensitivity-estimates/, Accessed Sept. 2016.

Lewis Nicholas , Curry Judith A.,(~ 2014), The implications for climate sensitivity of AR5 forcing and heat uptake estimates, http://www.datascienceassn.org/sites/default/files/The%20Implications%20for%20Climate%20Sensitivity%20of%20AR5%20Forcing%20and%20Heat%20Uptake%20Estimates.pdf, Accessed Sept 2016

Michael Mann, in Defining dangerous anthropogenic interference (Proceedings of the National Academy of Science (PNAS), March 2009)

What are the most likely climate changes for Australia over the next 50 years or so.

By David Holland

In the latest IPCC assessment report 5 (AR5), entitled Southern Hemisphere extra-tropical circulation, it is suggested that because of the ozone layer hole recovering over the next few years due to better regulation of CFCs there will not be a southern shift to the Cyclone belt. This will mean that Sydney will likely not get tropical cycles in the next 50 years.

The section of the AR5 entitled, Changes in evaporation, evaporation minus precipitation, runoff, soil moisture, relative humidity and specific humidity, suggests that Australia in the southern hemisphere will have higher evaporation over oceans and less evaporation with more rainfall in coastal regions over the next 50 years.

The report shows that there will be more precipitation in higher latitudes and less in lower latitudes. However local condition around Sydney may influence weather such as anthropogenic aerosol emissions, which could bring a cooling and more precipitation. (IPCC, AR5 working Group 1)

As global average temperatures rise the wetter areas in Australia such as Sydney are expected to get wetter and dryer areas are expected to get dryer.

The El Niño southern oscillation and Indian Ocean Dipole will work with or against climate change in both Sydney and Perth respectively.

From data predicted from the AR5 document in section, Regional and seasonal patterns of surface warming, it is expected that there will be an intensification of energy transfer from the oceans to the land. This will increase coastal breeze wind speeds and intensify rain and storm events at a local scale.

This energy transfer will increasingly bring warmer nights and more humid conditions to coastal urban areas.

In the section of the report, Global mean surface air temperature it suggests that the 5% to 95% data from the multi-model mean would be 0.39 to 0.87 degrees increase in global average temperatures. This would confirm the increase in ocean temperatures and suggest that inland Australia would be effectively much hotter than today.

Chapter 5 of the Garnaut review outlines the future climate scenarios for Australia.

It suggests that a 1% increase in temperature will have a 15% reduction in stream flow. If this is the case then water may become more of a problem in the bush as global warming takes hold.

If there is a 10% drop in rainfall this would reduce stream flow by 35%. (Jones et al. 2001 cited in Garnaut CSIRO (2008)).

The report suggests there has been a trend of more bush fires and more intensive ones coupled with more hotter days. This is normally a recipe for drying out fuel for fires, which can be done on these extreme hot days within hours. Lucas et al. 2007 cited in Garnaut (2008) suggests that fire season will start earlier and finish later in the bush fire season.

A study of projected temperatures by Lucas et al. 2007 cited in Garnaut (2008) suggests that a 1 degree C increase in average global temperature will give 20 locations of catastrophic fire in Australia and reoccurring within 16 years. A 2.9 degree increase will give 22 locations, 19 of which are reoccurring within 8 years and three reoccurring within 3 years.

This type of fire regime may seem costly to land holders and insurance premiums will rise, but it will hit very hard on ecological systems and their recovery after a catastrophic fire. Then if the location is burnt on multiple occasions within the 7 to 10 year period a very great potential for species inhalation from that locality is highly likely.

Figure 5.3 of the report shows a prediction of 0.6 to 5.0 degrees between 2030 to 2100 for Sydney and Perth with the inland regions about a degree hotter.

The report indicates that seasonal variations could mask rain event intensity due to anthropogenic climate change. It suggests that rain event intensity will probably increase but overall average rainfall may remain the same.

Abbs et al. (2006) cited in Garnaut (2008) suggests that category 3-5 cyclones will increase in intensity by 60% by 2030 and 140% by 2070.

Although Garnaut recognizes the plight of other Asiatic countries and particularly Island atoll’s susceptibility to climate change induced sea level rise, he omits to say anything about Australia being impacted except by refugees from these places. (Garnaut (2008) Chapter 6)

Australia will be hit hard by rising sea levels and Garnaut suggests that there will be some higher floods and storm surges increases due to sea levels rising, no more than some adaptations to materials used in building will be necessary. (Garnaut (2008) Chapter 15)

Holland (2015), outlines that based on the IPCC fourth report the NSW State government in 2009 made councils review flood levels and ensure that no new development was made on at risk land. Sea Level rise is likely to affect coastal regions and development patterns over the next 50 years or so and impact of ecological systems such as salt marsh and wetland environments.
The type of Australia we will expect to see will be in the A2 scenario where the government has not found the courage to take the hard decisions and change the economy to a renewable energy and an environmentally protective economy. The big business mentality will probably prevail with fragmented prosperity and we will be going through a very tough time with mitigating anthropogenic climate change.

References:

Garnaut Ross, (2008),  The Garnaut review, Chapter 5, 6, 15, Projecting Australian climate change, CSIRO, http://www.garnautreview.org.au/pdf/Garnaut_Chapter5.pdf, Accessed Sept. 2016

Holland David, (2015), Planning for Sea Level Rise Risk in some Coastal Regions of Australia – A Market Approach, For Land Potentially Effected by Flood till the year 2100, originally drafted 2010, Habitat Town Planning Forum web page, https://habitattownplanningforum.files.wordpress.com/2015/04/planning-for-climate-change-the-risk-model-for-sea-level-rise-discussion-paper-3rd-edition-rev1-20151.pdf, cited September 2016

IPCC, Climate Change 2013, The Physical Science basis, AR5 working Group 1: Near term Climate Change: Projections and Predictability, Chapter 11, Section The Water Cycle, Changes in Precipitation.

 

 

 

Modelling Climate Change Uncertainties

By David Holland

Global climate models are used in the Independent Panel on Climate Change (IPCC) Assessment Report Four (AR4) and Assessment Report Five (AR5) to predict future climates.

How have the modellers resolved the uncertainties of climate change predictions?

This article is based on study related to Masters of Environmental Management (Natural Resources) undertaken by David Holland 2016

When entering the world of prediction we are looking into a crystal ball with many possibilities. With Climate change predictions, we may know the past, howbeit in less detail than would be desired, but the future is simply a guessing game.  Satellite technologies have produced data since the year 2000 with increased accuracy which has increased the hindsight data available to both AR4 and AR5. Increasingly data is becoming more refined and reflective of what is actually happening on the ground.

Wigley and Raper (2001) as cited in Meehl Gerald A.  (USA), Stocker Thomas F. (Switzerland), (2007) as part of IPCC AR4, states the main uncertainties are uncertainties in emissions, the climate sensitivity, the carbon cycle, ocean mixing and aerosol forcing.

But uncertainty in the future is about the best guess based on past experience. We do not know how much meetings like the Paris accord will change the governments of the world to react to the climate issues or how quickly they will react and as a result we simply do not know the volume of future GHG emission into the future.

Volcanologists can predict certain volcanic events but the prediction of where, and how big a volcanism events may be, and then how long an aerosol event may last is less certain. All we can say is that there is a likelihood of future volcanism.

We understand that the sun has a11-year cycles between sun spot activity by looking into the past but in the future things may change. As unlikely as it seems solar forcing could change.

But the most sensitive and possibly most uncertain is radiative forcing changes. This relates to the potential for changes in the concentrations of GHG’s in the atmosphere and the resultant heat retained in the atmosphere from solar radiation. There is a range of variables associated with this process. The feed back loop related to CO2 atmospheric /oceanic flux, the albedo effect reduction as ice caps melt and more ocean is exposed and how the ocean and atmospheric circulations will be affected by all this.

The first coupled models started their life in 1995 by the Climate Variability and Predictability Numerical Experimentation Group, which came out of the reconstituted World Climate Research Programme. They were call “Coupled Model Intercomparison Projects (CMIP)”. (Gerald A. Meehi, Curt Covey, Bryant McAvaney, Mojib Latif, and Ronald J. Stouffer, (Jan 2005) )

Coupled models are more advanced models, which incorporate complex software interactions of data relationships to produce output that mimics a natural system.

They are defined as a complex interaction of the various software components in the model. This interaction produces results that could be skewed by the addition of a spurious variables or a factor in the maths that may be erroneous. So inherently within the model there are at least two uncertainties, the weighting of the variables and the models complexity not fully understood as it attempts to mimic real natural systems.

As time went on several versions of this model emerged and with a variety of data sets being used to run on these models. CMIP3 was one of the better early models but it, as all the models had inaccuracies.

The various data sets from recorded data would produce a range of results from the coupled models and as a result any output from the model would have  uncertainty as to which results could be considered correct if at all any were correct.

Land use changes also have an impact of the future accuracy of a model. Land use change can change the dynamics of the complex interactions of GHGs, flux, radiative forcing within a system. If the model does not have this information then the change will not be reflected in the model output.

The CMIP5 model was able to used much less grainy data sets, which enabled CMIP5 to produce regional climate models (RCMs). But as these were on smaller scales some anomalies were observed on the edges of the regions that did not seem to match an adjacent regions boundary. As a result questions were raised as to what uncertainties needed to be addressed to correct these aberrations.

Clearly climate modelling is peppered with uncertainties, but the argument is that with better and more extensive data sets and the ground truthing of existing models, better models will be made in an attempt to reduce internal anomalies. But the fact remains that modelling is still attempting to predict an uncertain future.

Unfortunately there are a variety of data sets available to feed into the models and a range of models.

The next generation of models were used in the IPCC’ assessment report 4. These multi-model means were starting to be used because the various coupled models seemed to give both accurate and inaccurate correlations to the real natural system as recorded in the past. So if the model produced an accurate simulation on past data then it was reasoned likely that future predictions on simple climate model trends data would produce an accurate coupled data result for the future.

The fact was that coupled data results varied considerably using differed data sets and climate model versions. So it seemed to be logical that if the result were averaged, the results of the 5% to 95% results, (which gets rid of the eccentric data results), we will get from a lot of uncertain results a more certain result. This is an understanding of what a multi-model mean is. A mean of many results of a range of coupled models produced from a range of data sets and a range of assumptions of the future.

The interesting thing about this method is that each model has been set up differently with a range of parameters, some with higher GHG emissions for a future scenario, and some with lower emissions. The end result would be that if the majority of the uncertain future predictions now placed in the models were inaccurate, then the averaging out of the results of all the models would predict a wrong future for the earth.

The method starts with uncertainty as if it was a sows’ ear and suggests that it can make a silk purse by averaging the sows’ ears.

Maybe the analogy is too harsh. It is about the opinions of the model managers who input into the model their best guess of the future. If the manager feels that there will be a reduction of GHGs by a certain date and the majority of model managers believe that this will be the case then the mean of the models will trend that way.

So where does this leave us in predicting the future climate? It leaves us with a best guess solution based on the past’s data collection.

The way the IPCC have handled the uncertainty is by creating several scenarios of the future. These scenarios are based again on varies social and environmental predictions.

However in reality, the prediction that recent data has followed is in fact the highest or least safe prediction for the potential to return the climate to a normal state.

References:

MEEHL Gerald A. , COVEY Curt , MCAVANEY Bryant , LATIF Mojib , AND STOUFFER Ronald J. ,(Jan. 2005) Overview Of The Coupled Model Intercomparison Project, American meteorological society, meeting summaries, https://www.gfdl.noaa.gov/bibliography/related_files/gam0501.pdf, cited September 2016.

Meehl Gerald A.  (USA), Stocker Thomas F. (Switzerland), (2007), Global Climate Projections Coordinating Lead, IPCC assessment report 4, http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-chapter10.pdf, accessed September 2016.

REICHLER THOMAS , KIM JUNSU, (March 2008)How Well Do Coupled Models Simulate Today’s Climate?,   In Box – Insights and Innovations, , AMERICAN METEOROLOGICAL SOCIETY, Publ. NOAA, http://www.nssl.noaa.gov/users/brooks/public_html/feda/papers/ReichlerKimBAMS08.pdf

A warning to the NSW State government about the potential for climate change to affect the economy of rural towns reliant on agricultural income

 

by David Holland (Master Env. Mngt., B.A.S. Env. Planning)

I was alerted in recent news about cotton growers in Moree who have had good rains earlier in the year and were expecting a good crop of cotton this year. They were expecting 3.5 bales of cotton a hectare. To compare this with the top producers in 2012-13 this figure is well down on the 12 bales per hectare in this year and only 5 years ago at a time when the yield earned Australia in 2011 $3 billion from the trade. At the time, Australia was the 3rd largest exporter of cotton in the world and produced a high-quality product.

Due to recent hot weather in the Moree region and adjacent regions, estimates of the crop have dropped to 2 bales per hectare. This is possibly due to several factors but the hot day time temperatures would be one of the major factors in stressing the plant during the formation of the boll filling. This would often reduce the quality of the cotton and causes micronaire problems. Any temperatures above 35 degrees will shut down photosynthesis and effectively starve the plant.

During the summer of 2017 there have been a good many days above this temperature. But potentially more damaging to the cotton plant is high night time temperatures which continues the maintenance respiration of the plant through the night to keep it cool. This does not allow the plant to recover from the previous day further reduce the energy in the plant leading to underdeveloped fruit. (Holland, D, (2016) p. 12)

With a climate change scenario developing in NSW, the cotton industry which provides a large amount of Australia’s balance of trade, likely to be hard hit over the next few years, the State government should not only be aware of the issues related to the cotton industry, but start to be proactive to ensure that the industry can adapt to these new permanently changing climate conditions.

There are many rural towns that rely heavily on the profits from the cotton trade. If the cotton trade is damaged by the effects of climate change, then many of these rural towns will be financially effected. The State government and planners need to ensure that farmers and the industry finds ways to adapt so that towns reliant on this industry are not adversely affected economically by climate change in these regions.

I also heard a separate but related news item recently about the increased propensity of farmers taking out crop insurance. They are insuring against crop failures. In a climate change scenario in the cotton industry there will be a greater prevalence of farmers claiming insurance on crop failure and hoping against hope that the weather patterns will reverse and good crops will come again. This may happen for a time, but if a region is in the grip of climate change adverse to the crop in question a range of undesirable financial impacts are likely.

  1. Farmers will continue to farm as they have done and experience more failures.
  2. Farms that have no longer the right conditions for a crop will continue without considering new more viable locations to farm.
  3. Insurance premiums will continue to rise as more farmers call on the insurance to service their financial needs in the year of failed crop.
  4. At some point communities will be in a crisis where insurance is too high for the next year’s crop and crop failure is inevitable. This will potentially cause a town to decline in a fast and unexpected manner at some point.

The State government needs to consider the subject of farm insurance and the viability of the cotton industry in certain areas. If crop failure becomes the norm, then Australia will no longer have such an export bonanza through the cotton industry.

Reference:

Holland, D., (2016), The Cotton Growing Industry near Bourke NSW, A future with Climate Change, Habitat Association, WordPress web site, https://habitatassociation.files.wordpress.com/2016/12/cotton-bourke2.pdf, cited 2017.

 

Climate Change affecting the Cotton Industry in Bourke

As the effects of Climate Change intensify, more primary industries will be affected.

Cotton growing in Bourke may be on the margins but in 2016 is still viable.This paper outlines some important points about how climate change will affect established agricultural industries particularly in marginal and dryer areas on Australia.

The paper was written as part of a Master of Environmental Management study in climate change through Charles Sturt University in 2016.

To read the complete paper follow the link to:

How Climate Change will affect the Cotton Industry in Bourke

The Papers Author

David Holland, Master Environmental Management (Natural Resources), BAS Environmental Planning