‘Top down’ climate data don’t serve growing cities

For climate data to be truly useful, scientists must work more closely with planners, says Sarah Opitz-Stapleton.

Urban environments are changing rapidly. People who live in cities are faced with risks and vulnerabilities that depend as much on socioeconomic factors, like access to health care, as they do on exposure to climate change and variability.

Many of the programmes designed to improve urban resilience to disasters and climate change try to incorporate data — such as estimates of summer temperatures by 2050 or number of frost-free springtime days by 2030 — as a key element in science-based decision making. Traditionally, scientists feed such data into impact models, expecting the results from these models to be used in risk reduction and adaptation programmes.

But, increasingly, scientists and development practitioners are calling into question such ‘top down’ efforts to use climate data for urban planning. This is partly because they do not account for rapidly changing conditions in cities or the multiple needs and capacities of different decision makers.

Needs and limits

There are many decision makers in a city with concerns about the impacts of climate change and weather hazards. These include government departments that maintain roads or issue building permits, NGOs and community groups trying to reduce vulnerability, and businesses and households taking autonomous actions in response to weather events.

Each of these groups has different needs and capacities for accessing, understanding and using climate information. Some may not know how to find the data or be in a position to engage with meteorological agencies. And they may not understand the data as presented.

Even the information itself may not be useful to them. Decision makers want to know how the weather or climate might affect their lives and operations, rather than that it may be 1.6-3 degrees warmer on average by 2080.

The limited usefulness of climate data is also partly down to the availability and quality of data in resource-poor countries. Monitoring capacity is part of the problem. Cities often lack enough weather stations and existing stations might be recently installed or not maintained regularly. Stations that only take measurements once or twice per day fail to capture brief extreme events, such as heavy rain contributing to flash floods.

It is the daily (or sub-daily) weather records taken for 30 years or more that describe a city’s ‘climate’, so short records make it difficult to detect trends and project into the future.

Making decisions without understanding the limitations of short-term records could be disastrous — particularly if they relate to building infrastructure such as flood defences that may not be robust or flexible against rapidly changing risks.

Evolving Urban Risks

The challenges of providing useful information are compounded by rapid changes in urban infrastructure and land use. In much of the developing world, basing decisions on impacts assessments becomes counterproductive because that method often relies on traditional climate statistics and limited data.

Climate scientists use statistics to describe extreme events, trends, and make projections into the future. For example, they might define an extreme rain event as one that exceeds the 90th or 95th percentile of a historical rainfall record.

But these statistical thresholds often do not match the thresholds at which a community might begin to experience harmful effects. This is because rapid development affects those thresholds.

Take Mehewa Ward in Gorakhpur, India, for example. Due to poor management of solid waste, limited drainage networks, and rapid construction which has reduced the area of green space, flooding can occur for rainfall at the 88th percentile of the city-average. If urban growth continues at the same pace without improved services, the rainfall threshold for flooding may be even lower in future.

Trying to estimate climate risk based on standard statistics alone, without taking into account local conditions such as land use and development, is simply not useful in dynamic urban situations.

A new model

So what can be done to overcome some of these challenges to make climate information more useful to urban resilience planning?

First and foremost, climate information providers such as national meteorological agencies need to work directly with decision makers. They need to understand their concerns, needs, and priorities;  and how they currently understand, use or ignore information, and why.

One way to do this is to embed information providers directly within government departments or NGOs and involve them in resilience projects from the beginning. Climate scientists would then better understand the city — its data gaps and limitations, as well as its changing conditions — and better describe the risks that are most relevant to local concerns.

An initiative to watch for its approach to this challenge is the Future Climate for Africa, but most existing adaptation programmes still rely on the traditional model.

Embedding providers within projects also treats the generation and communication of climate information as a circular, iterative and participatory learning process. In this way, climate information is driven by relationships in which communication evolves within the decision-making context.

Sarah Opitz-Stapleton is an independent research scientist based in Colorado, United States. She has worked as a climate information provider and advisor on adaptation programmes such as the Asian Cities Climate Change Resilience Network (ACCCRN), funded by the Rockefeller Foundation, and Adapting to Climate Change in China (ACCC), funded by the UK Department for International Development, the Swiss Agency for Development and Cooperation and the Chinese government. She can be contacted at [email protected]