Grey nomad lifestyle provides a model for living remotely


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Grey nomads are champions of a radical type of portable urbanism as they travel to far-flung places like Lake Ballard in Western Australia.
Image courtesy of Tourism Western Australia, Author provided

Timothy Moore, Monash University

Every other year, retired couple Jorg and Jan journey some 5,000 kilometres in their campervan from Port Fairy in southeastern Australia to Broome in the far northwest for a change of lifestyle and scenery. There they catch up with other couples from across the nation, who often converge on the beach for communal dinners. Jorg and Jan’s break lasts several weeks.

They are two of tens of thousands of retired adults travelling independently across the continent at any given time in search of adventure, warmer weather and camaraderie after a lifetime of hard work. These part-time nomadic adventurers, or grey nomads, have recast the image of Australia’s ageing population. Rather than being inert and conservative, or in need of care, these older Australians are champions of a radical type of urbanism: dwellings are mobile, infrastructure is portable or pluggable, social networks are sprawled, and adherents are on the move daily or weekly.




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Nomads driving along Meelup Beach Road near Dunsborough.
Image courtesy of Tourism Western Australia

Grey nomad is a term used to describe Australians over 55 years old who travel for an extended time – from weeks to months – and cover more than 300 kilometres in a day across semi-arid and coastal Australia. The term was popularised following the 1997 Australian documentary Grey Nomads, which captured the phenomenon of older travellers who made their homes wherever they parked.

What is the scale of grey nomadism?

Travellers, including grey nomads, contribute to a “roaming economy”: decentralised dwelling results in decentralised spending. The Western Australian government estimated in its Caravan and Camping Visitor Snapshot 2016 report that 1.54 million domestic visitors spent time in caravans or camping, contributing more than A$1 billion to the state economy.

According to the Campervan & Motorhome Club of Australia, RV drivers spend an average of $770 per week. And their value to a remote place extends beyond economic capital to human capital. Grey nomads often provide labour (such as gardening, house-sitting or their pre-retirement professional skills) in exchange for a place to park or for extra income.

Nomads relax at a caravan site in Esperance.
Image courtesy of Tourism Western
Australia

The availability of caravan parks, campsites and public parking reserves is essential to attract the grey nomad to regional towns. According to a 2012 report for Tourism WA, A Strategic Approach to Caravan & Camping Tourism in Western Australia, the state had a total of 37,369 campsites at 769 locations. In addition, remote private properties are becoming available through apps such as WikiCamps Australia.




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But while many nomads go off-grid, carrying their solar panels and generators, others are just looking for free reserves to park in. Beyond the site and its amenities – such as power, water, showers or flushing toilets – qualities such as “authenticity” are important to nomads, as highlighted by Mandy Pickering. Sites should feel remote rather than urban.

Will future generations be as fortunate?

The rise of the grey nomad over the past half-century has been made possible through the ability of ageing Australians to fund this retirement lifestyle. They might sell their houses (some may simply benefit from having secure accommodation), withdraw their superannuation or receive government benefits. Nomadism is a reward after a lifetime entangled in an economic and social system that keeps the individual tied to a stable workplace and place to live.

Aerial view of Osprey Campground near Ningaloo Reef.
Image courtesy of Tourism Western Australia

For future generations, the outlook in terms of grey nomadism being a viable retirement lifestyle is not especially bright. Home ownership is sliding out of reach for many younger people. And many are enmeshed in the gig economy, meaning they are not receiving employer superannuation contributions.




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Future generations may be so much in debt or living in such straitened circumstances that they cannot retire to a life of leisurely travel.

While grey nomadism might not be a sustainable model in the future, the lifestyle demonstrates how future generations of nomads – not necessarily grey – can live cheaply while populating regional centres for weeks or months, bringing economic and human capital to these remote places. These nomads will be able to work on their laptops in the public libraries, cafes, share houses and co-working spaces of country towns, accessing work remotely through cloud-based telecommunications.

They might not come in campervans but be dropped off in driverless vehicles; vacant campsites might become sites for small cabins. Or, as these nomads will be looking for temporary accommodation, spare rooms or entire houses might be made available. To find these dwellings, they might use apps that bring great efficiency to managing housing occupancy, enabling the “sharing” (renting) of unoccupied space for days, weeks or months.

Are regional towns ready to embrace these “emerging nomads” who are attracted by affordable living costs, network coverage, fast internet speeds, great weather, temporary housing options and unique regional identities, as the grey nomads were before them?

Grey nomads are recognised as a group that requires distributed infrastructures. They demonstrate a capacity for domesticity and urbanity without boundaries. The grey nomads are the precursor to a new generation that might not only want to travel, but need to in an economic environment that is not static or stable. And that will mean they can no longer afford to stay in one place.


This article was co-authored by Amelia Borg, a director of Sibling Architecture and a Masters of Business student at the University of Melbourne.

The Conversation is co-publishing articles with Future West (Australian Urbanism), produced by the University of Western Australia’s Faculty of Architecture, Landscape and Visual Arts. These articles look towards the future of urbanism, taking Perth and Western Australia as its reference point, with the latest series focusing on the regions. You can read other articles here.




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The Conversation


Timothy Moore, PhD Candidate, Melbourne School of Design, Monash University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Fires are increasing in warming world, but a new model could help us predict them


Ritaban Dutta, CSIRO

Over the past decade, the frequency of bushfires in Australia has increased. The Forest Fire Danger Index – which measures the frequency and severity of the weather most conducive to fire – has increased dramatically since the 1970s, and particularly in the 1990s and 2000s. This – along with a great deal of other evidence – indicates that a major change in the climate is looming.

In a study published today in Royal Society Open Science, we show that bushfire frequency has increased by 40% over the past five years.

This is part of our work to better predict bushfires using weather information. We developed a model that can predict bushfires over a week-long period with an accuracy of 91%. While we can’t yet use this to predict fires definitively, it is a big step forward in planning for and predicting fires.

There is an urgent need for scientific research that can contribute to Australia’s future bushfire preparedness. The knowledge gained from this research could help save lives and property, underpin effective building codes and help land-management decisions.

Fire forecasting gets smart

We wanted to find bushfire “hotspots” – places where a bushfire might happen in the future based on recent weather patterns. They don’t show that a bushfire will definitely happen, and similarly we need to be careful that people don’t assume a fire won’t happen if there is no hotspot.

To do this we developed a model that combined data on fires (from satellite images) with data on climate, including soil moisture, dry fuel load, wind speed, temperature and humidity.

We are using a machine learning approach to model future bushfire hotspots – in short, a form of artificial intelligence that allows the model to learn on its own. Our model used other forms of learning to produce maps of bushfire hotspots.

Map showing predicted hotspots (green) and real fires (purple). Red dots show fires not predicted by the model.
Ritaban Dutta

Predicting hotspots

We tested our model by looking at bushfires retrospectively. Our predictions achieved 91% global accuracy. The analysis also indicates that, on a week-by-week basis, the frequency of Australian bushfires, particularly during summer months, has increased by 40% over the past five years.

We conducted extensive research in Australian bushfire history, to make sure the data on the conditions and behaviour of 36 major fires were correct.

Two types of Australian vegetation are prone to fire: grasslands and forests. We found that our model could predict both.

Fighting fires

Although new technologies are being developed to manage the growing number of unplanned bushfires in Australia, we do not have, and are never likely to have, a way to avert natural fire disasters.

The recent history of Australian bushfires indicates that the most effective way to save lives is early planned evacuation, combined with timely advice and alerts to the people potentially at risk.

Early estimation of the likely frequency of future bushfires, and accurate hot-spot estimation of the locations most likely to be affected could provide great support to land managers, and assist in reducing the damage caused.

But as yet, our system exists only as a research model. Its impact and effectiveness could only be fully evaluated if a real system were implemented as a decision support tool for land managers and emergency services, to accurately forecast the most likely bushfire hot spots, at a detailed and fine-grained resolution and a timely scale.

The Conversation

Ritaban Dutta, Senior Research Scientist and Research Project Leader, Data61, CSIRO

This article was originally published on The Conversation. Read the original article.

Climate models too complicated? Here’s one that everyone can use


Dietmar Dommenget, Monash University

Most people have a fairly clear position on human-induced climate change, despite the vast majority of people not knowing much about the scientific basis of the climate models used to study it. That’s understandable – they are very complicated indeed and not accessible for everyone.

In one sense it doesn’t matter if climate models are only understood by climate modellers, as long as they can interpret their research findings for others to understand. But it does leave them open to the suggestion that their research is somehow “inferior” to that of scientists who don’t use models – despite the fact that models are used in every field of science, from economics to astrophysics.

The essence of science is to model our world, so it follows that understanding the underlying model is essential in understanding the predictions and its uncertainties.

Modelling the world

The state-of-the-art climate models on which groups such as the Intergovernmental Panel on Climate Change base their climate projections are developed from the models used in weather forecasting. Weather models primarily deal with questions such as “where does the wind blow from?” and “will it rain?”

These are essentially questions about how the atmosphere will circulate for the coming few days. This is why these kind of models are called “general circulation models” (GCMs). When extrapolating the climate, we essentially use longer-term forecasts of the same thing.

Today’s GCMs are probably the most complex and advanced scientific models ever created. But their complexity also makes them hard for the general public to understand, which in turn makes it less likely they will have faith in the models’ forecasts. To the general public (and even to other members of the climate research community) these GCMs are essentially black boxes – you put something in (such as increased CO₂ concentration) and you get a response out (warming temperatures).

These responses might be easier for the public to understand if we step back from the most complex models and instead use one that is easier to understand. There is no better way to learn than doing, so my lab has designed a climate model that people can try out for themselves.

A simpler climate model

A simpler approach of modelling the climate is often based on the first law of thermodynamics: the conservation of energy. It models how energy is going in or out of the system and by this it is modelling the energy balance of the surface of the earth. These models are called “Energy balance” models.

The new Monash Simple Climate Model (MSCM), which my research team developed, allows students and the public to use a real climate model to do their own climate simulations. It provides a simple model of the average global climate and its response to external factors such as changes in sunlight or CO₂ concentration.

The MSCM interface for experiments with the mean climate

The MSCM allows you to study the results of more than 2,000 different model experiments in an interactive way. You can take the climate apart, and see how it responds to different climate change scenarios. It also provides educational tutorials about the climate, climate models and climate change, and even some fun puzzles.

Virtual worlds

Experimental simulations are a key method in science. They allow you to address “what if?” questions that are not easily answered simply by observing the real world or by experimenting with it.

Using our model you can, for instance, address the question of what would happen if you took away all clouds. And how else are we to learn about clouds’ role in the climate system unless we see what happens when they’re not there?

Much as some people deride modelling as “not real science”, we only have one Earth and one climate, so we can’t do “real” experiments with it. By using models, we can test important questions such as what would happen if we double the concentration of CO₂ in the atmosphere. In fact this may not be the best example, as we are well on the way to doing this experiment in real life – although the models should hopefully warn us of the impacts in time for us to avoid the real thing.

Comparison of the temperature changes in two different IPCC future climate change scenarios simulated with the MSCM.

Speaking of the future, a publicly accessible climate model could also be used in schools, helping to equip future generations with a better understanding of our climate system. For a generation that will grow up in a fast-changing climate, this will educate the public about what’s in store, and might also inspire the next generation of scientific modellers – of the climate as well as in many other areas of science.

The Conversation

Dietmar Dommenget, Senior Lecturer, Climate Dynamics, Monash University

This article was originally published on The Conversation. Read the original article.