Climate, using big data to save Venice and other cities

There energy crisis prompted the Italian government to postpone the turning on of the radiators in what was expected to be a difficult autumn. But in many cities the radiators were started even later than expected due to the abnormal heat. Unpredictable coincidence: the problem, as a Wired Riccardo Biancalani, project coordinator of the Food and agriculture organization (FAO), “is that agriculture cannot be”. We can adapt to climate change, but working times, types of crops and socio-economic system are marked by the rhythm of the seasons.

The philosopher Cosimo Accoto, author of several essays on the subject, states that we are passing from the society of archives to the society of oracles. Digital. That of long-term forecasting is one of the most promising areasat the crossroads between climate science and computer science. The challenge for entrepreneurs in the sector is to try to do better than governments and international organizations. It’s not just farmers who are interested. To look carefully (and pay) for reliable predictions are the large multinationals with assets located in dozens of different countries and latitudes, and oblige to defend them as much as possible; insurance companies, which pay out tens of billions in compensation every year; and, of course, the cities, which have to prepare in time.

What is Moses, which protected Venice from high water

The Mose dams have come into operation and have prevented high tides and bad weather from affecting Venice and the homes of its inhabitants

Changing scenarios

The role of data is central, but what really matters is the ability to analyze them. Londoner Cervest calls herself one climate intelligence company. “We deal with predict how the climate impacts assets, from plants to transport networks, to protect goods and people”, says John White, vice president responsible for partnerships. The clients are large multinational companies. The company is five years old and employs one hundred and ten people. Three (classical) outputs provided: the worst case scenario, the best one, and an intermediate one.

“To build them, we use a combination of statistics and climate sciencestarting from mostly public data – explains White -. What we do more than institutions like the IPCC (Intergovernmental panel on climate change, the United Nations body that deals with climate change, ed) is to employ a more refined model”. We ask: why trust you? “We cannot verify in advance the goodness of the answers we provide, but only the method we employ to find them – he claims- It’s about climate, not weather, and they are persistent factors determining its evolutions. We know what they are, although no one can say for sure what will happen in the future”. Difficult, risky bet. That doesn’t scare the British.

In the same vein is the Canadian Runwithit, which deals with disaster prediction with a particular declination and focus: cities. “Our clients are primarily Fortune 500 companies (ranking that collects the first US companies by turnover, ed)”, says Myrna Bittner, co-founder. “Then there is the energy sector, which is going through an unprecedented crisis”. But there are also public administrations and governments. “The difference is that to our models, we add a variable that is difficult to capture with traditional techniques modeling – he says – : people, even marginal segments”. Again, we ask how can you trust. “We don’t predict the future, but we give data and trends a character.” replies the manager. “The future cannot be predicted, but the best choices possible can be made. We make use of the best sources of information, we employ the work of thousands of experts”continues the entrepreneur. Runwithit produces reports and 3D models and uses mostly open data, she says. “But the magic happens when you go beyond that”. The company currently employs twenty-four people.