Want to know what climate change will do in your back yard? There’s a dataset for that

The 7-terabyte dataset, the largest of its kind, helps envision climate-change scenarios at scales as small as 1 kilometer; a new review validates and describes the dataset

International Center for Tropical Agriculture (CIAT)

IMAGE

A small bean farm in Colombia’s Darién region. Future climate scenarios can be modeled at the community scale thanks to a dataset created by the CGIAR research program on Climate Change, Agriculture and Food Security (CCAFS) and the International Center for Tropical Agriculture (CIAT).

Credit

Neil Palmer / International Center for Tropical Agriculture

What the global climate emergency has in store may vary from one back yard to the next, particularly in the tropics where microclimates, geography and land-use practices shift dramatically over small areas. This has major implications for adaptation strategies at local levels and requires trustworthy, high-resolution data on plausible future climate scenarios.

A dataset created by the International Center for Tropical Agriculture (CIAT) and colleagues is filling this niche. Primarily intended to help policymakers devise adaptation strategies for smallholder farmers around the world, the open-access dataset has been used in 350 research papers. Users in at least 186 countries have downloaded almost 400,000 files from the dataset since it went online in 2013.

A full description, review and validation of the dataset, including how it was built, was published January 20 in Scientific Data, an open-access publication by Nature for the description of scientifically valuable datasets.

“Climate models are complex representations of the earth system, but they aren’t perfect,” said Julian Ramirez-Villegas, the principal investigator of the project and a scientist with CIAT and the CGIAR Research Platform on Climate Change, Agriculture and Food Security (CCAFS). “These errors can have an impact on our agricultural models. Because these models help us make decisions, this can have dire consequences.”

While the data has primarily served agricultural research, it has also been used to map the potential global spread of Zika (a mosquito-borne disease), to plan investment strategies for international development, and to predict the ongoing decline of outdoor skating days in Canada due to warmer winters.

“The use and applicability of this data have been really extensive and topically quite broad,” said Ramirez-Villegas. “Of course, a large portion of the studies has been done on crops that are key to global food security and incomes such as rice, coffee, cocoa, maize, and others.”

Pinpointing climate impacts

Climate-change projections are typically available at coarse scales, ranging 70-400km. But models for the impact of climate change for many agricultural plant varieties require data at finer scales. The researchers used techniques to increase the spatial resolution (a process known as downscaling) and to correct errors (a process known as bias correction) to create high-resolution future climate data for 436 scenarios.

“This is a critical resource for modeling more realistically the future of crops and ecosystems,” said Carlos Navarro, the lead author of the study who is affiliated with CIAT and CCAFS.

For a given emissions pathway and future period, each scenario includes monthly information for average and extreme temperatures, rainfall, and 19 other related variables. The data are publicly available in the World Data Center for Climate and the CCAFS-Climate data portal.

“Through these scenarios, we can understand, for instance, how agricultural productivity might evolve if the world continues on the current greenhouse emissions trajectory,” said Navarro. “They also provide the data to model what types of adaptations would best counter any negative climate change effects.”

Global and regional models analyze climate conditions at a rougher scales and simplify natural processes, producing results that may deviate from realistic scenarios.

The dataset is CGIAR’s biggest Findable Accessible Interoperable Reusable (FAIR) database. It also underscores CGIAR’s role in big data for development, through its Platform for Big Data in Agriculture. The dataset is currently included in its Global Agriculture Research Data Innovation and Acceleration Network (GARDIAN).

The high-resolution scale of this data is useful for scientists, policymakers, NGOs and investors, as it can help them understand local climate change impacts and therefore make better bets on adaptation measures, which plans can specifically target watersheds, regions, municipalities or countries.

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In addition to the studies noted by Ramirez-Villegas above, other studies that have used the datasets include:

-Mapping global environmental suitability for Zika virus. The results showed that more than 2.17 billion people in the tropics and sub-tropics live in Zika-prone areas.

-A multi-year CCAFS study following more than 15,000 farmers across India who are testing new seed varieties to enhance smallholder resilience to climate change.

-The above study also noted how Concern Worldwide, an NGO that does long-term development work, has used the data to identify adaptation options and investment strategies in Chad and South Sudan.

-The datasets were used in numerous climate change-impact studies on crops in Africa, including cocoa in Ghana and Cote d’Ivoire, chickpea in East Africa, irrigated sugarcane in South Africa, and groundnuts in West Africa.

-In a show of the dataset’s broad research potential, a study in Canada showed how days of outdoor ice-skating are in decline there due to warming.

From EurekAlert!

33 thoughts on “Want to know what climate change will do in your back yard? There’s a dataset for that

  1. “…7-terabyte dataset…”

    Ha ha ha ha ha ha ha…get back to me when you are talking exabytes and more. I know the local state police databases that are in petabyte territory and growing, that’s just the SAN. NAS is even bigger! And it all has to be backed up and available 24×7!

    • No but it will tell you how many sign carrying safe zoners will break out in parades on college campuses and in metropolitan areas near you. That will give you a clear indicator on how the proportion of unsightly trash, odoriferous human excrement, and litter will vary.

  2. In related news, climate scientists at the Center for Counting of Climate Pinheads (CCCP), using their latest high resolution computer models, have ascertained the exact number of angels that can fit on the head of a pin. CCCP climate scientists have indeed confirmed that climate change is reducing pinhead size andthus throwing millions of angels out of work.

    • Not exactly throwing angels out of work, Joel. They will just have to find somewhere else to dance.

      They will become Pinhead Refugees.

  3. I live in Calgary. What will global warming do to my back yard? Less damage than the shade from the four storey condo going up next store and shading my house and garden.

    But more seriously, there are 7.7 billion people on the planet, and approx 7.5 billion of them live in places warmer than my yard. I think I will be able to adjust just fine.

    I am looking forward to no snow in June or September!

    • Your lawn will most likely be brown because of the growing Federal, State, County, Metropolitan, and City regulations on water usage.

  4. This is of course pure bull$hit. No GCM works at anything even close to 1 km resolution. And there is no computer that could handle a GCM that did so.

    Also to be valid this database must have ground data valid at 1 km resolution, and the data must be continuously updated as surface conditions (vegetation, moisture, buildings etc) changes.

    • Validation? Whatever it means, I would be more interested in the accuracy of its predictions. As it was online since 2013, we should be able to compare its predictions with reality, with homogenized reality, and with the Farmers Almanac.

      Can we still see what the data were in 2013, or is it continuously improved?

  5. Even assuming skillful GCMs, the variety of methods (statistical vs dynamic), and the assumptions required (bias correction, boundary condition, etc.) to downscale introduces a large uncertainty. This is rarely represented in the downscaling datasets published to date. Is anyone aware of a comparison of the various downscaled products for a single geography? I’ve done it informally in my work, and anecdotally see some agreement but a lot of difference, including sign of the signal, particularly for precipitation. It would be nice to see something more formal/systematic that follows the uncertainty through a decision analysis for policy development or project implementation.

  6. “Want to know what climate change will do in your back yard?”

    Not really. Just give me one crisis at a time to deal with or I’ll get my doomings all confused-
    https://www.msn.com/en-au/news/australia/new-study-reveals-south-australia-obesity-crisis/ar-BBZaHTj

    I suppose you can’t blame the poor folk if they’re perpetually told they’re going to starve with the climate dooming and there’ll be no meat to throw on the barbie. Survival of the fattest makes sense and they figure those stick insect vegans and the latte set will be off their backs early.

  7. From the article: “For a given emissions pathway”

    They ought to just throw RCP8.5 in the garbage where it belongs. It’s not even close to reality. All the scary CO2-calamity predictions use this unrealistic scenario.

  8. What the global climate emergency has in store may vary from one back yard to the next, …

    After reading that, I knew the rest of the article would not be worthwhile reading. My backyard has an assortment of grassy areas, hard-pack dirt areas, shady areas, sunny areas, weedy areas, frozen areas, and so on. This varies from day to day, hour to hour, month to month, year to year, and is slightly different from my neighbors’. I think they are trying to justify spending more money on their computer games.

      • Before my wife and I were married, she had a tomato garden in her parent’s back yard, running along a stockade fence. It had a south-westerly exposure. That fence sheltered the plants and reflected enough sun so that one year she was pulling tomatoes off until the first week of December! No small feat in northern NJ.

  9. This research tries to create an illusion of certainty for impacts of “climate change” on individual farmers. This may be an attempt to establish a foundation claims of current and future damage against fossil-fuel companies in foreign and international courts (see Donziger/Chevron). I would not be surprised if CIAT is shadow funded by the legal industry.

  10. “Concern Worldwide”

    Should change their name to Worrywart International, or Climate Hypochondriacs.

  11. I’ve been told repeatedly that at less than global scales, climate models are not accurate.
    However on the hectare scale, apparently they are close to perfect.

  12. “What the global climate emergency has in store may vary from one back yard to the next, particularly in the tropics where microclimates, geography and land-use practices shift dramatically over small areas.”

    This highlights one of the major problems with the current “global average temperature”.

    The current land temp record totally ignores the fact that microclimates exist and it is the sum of these microclimates that actually determine the climate. Instead they take the temperature reading for one station and “infill” it to encompass wide swaths of land, literally thousands and thousands of acres, up to and including significant parts of some continents. The size of their grids in the models are useless if the temperature value attributed to that grid comes from some other location that may bear no resemblance to the local grid.

    It’s why I’ve never understood how the “global” average temperature is said to be going up while major areas of land are actually cooling, e.g. the central and southeast continental US, parts of Siberia, and parts of South America. The number of cooling degree-days (calculated using the integration method) are going down over the past three years for many world-wide measurement stations meaning that maximum temperatures are probably coming down. This is true for various locations on all the continents.

    This doesn’t even consider the cooling provided to many micro-climates through the 13% greening of so much of the land area since 1980.

    I just plain don’t trust anything that is claimed to be “global”, especially with so much “in-filled” data.

  13. Cattle ranches have an abundant supply of this type of science lying about in the fields giving life to new vegetation.

  14. This report denies the IPCC claim that the system and processes are chaotic. Perhaps they discovered a semi-stable exclusion zone with a narrower than normal variance, in a virtual space, in the laboratory?

  15. Would you bet the farm based on this prediction? Better yet, would you bet all the farms in your country based on this prediction? Or would you let a political agenda-driven leader make the bet for you while they collect money from radical advocacy groups?

  16. Well, if the global climate model on which these data are based over-predicts the global average temperature rise by a factor of two, how far off will this model be for the average backyard?

    Since most backyards are in suburban areas, how does this database take into account the “urban heat island” effect of future buildings that haven’t been built yet? This would have far more impact on the future climate of a backyard than a little extra CO2 in the air!

    Another example: on the south side of my house, there is no snow within 10 feet of the wall, but there is six inches of snow along the north side, which is always shaded this time of year. Seventy years ago, my house did not exist, and the snow was probably evenly distributed over what is now my yard in winter.

    So this database might make all sorts of predictions for a plot of land that is now undeveloped, but if someone puts up a building there, there will be a milder climate on its south side and a colder climate on its north side, and the database could never predict that.

  17. From the article:

    What the global climate emergency? has in store may vary from one back yard to the next,

    Fixed.

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