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The Climate Damage Tracker (CDT) is an initiative based at 911½ñÈÕºÚÁÏ’s Grantham Institute. It develops and applies what is known as ‘impact attribution’ to rapidly estimate if - and by how much - climate change influenced the socio-economic impacts of an extreme weather event. At present, CDT uses methodologies that look at economic damage from tropical cyclones, and deaths resulting from heat events. 

Many of the methods that CDT applies have been peer-reviewed and those that haven’t are detailed clearly on the website. Rapid studies are published before peer review to provide analysis in the immediate aftermath of an event and some of them are then subsequently submitted for peer review.

We aim to study all tropical cyclones of Category 3 or higher intensity at landfall worldwide and major heatwaves in Europe.

Understanding the changing risk of tropical cyclones with climate change is difficult due to a scarcity of data. The IRIS Model - which is explained in more detail below - was developed to overcome this. The link between climate change and hotter, more frequent heatwaves is well established in the scientific literature. While attribution studies do sometimes show that climate change was not a causal factor, to date all the heatwaves and tropical cyclones CDT has analysed have shown that climate change worsened their likelihood and impacts.  

The models we use to estimate impacts from an extreme weather event are developed using available recent historical data. As such, they reflect the level of adaptation present at the time of the available data set.

Where our studies show that climate change worsened an event and its impacts, the findings help to build awareness of the costs associated with climate change and its role in extreme weather events. This information can help decision-makers plan for adapting to the changing climate, identify cost-benefits, inject urgency into conversations around emissions reductions, and inform conversations around Loss and Damage for climate vulnerable nations.

The Climate Damage Tracker is funded by the Grantham Foundation and the Quadrature Climate Foundation.

Understanding the changing risk of tropical cyclones with climate change is difficult due to a scarcity of data. There are less than 45 years of high-quality observations of global tropical cyclone intensity and tracks

To overcome this, the 911½ñÈÕºÚÁÏ College Storm Model (IRIS) has created a database of millions of synthetic tropical cyclone tracks globally. These tracks map the tropical cyclone from formation to landfall and describe how powerful the winds are at each stage of the tropical cyclone’s life. It estimates the maximum possible strength a tropical cyclone can reach under certain conditions. We can then adjust the environmental input to represent different conditions to simulate storm intensity in a pre-industrial world, today’s climate, and a warmer future.

This allows us to compare tropical cyclone risk across different scenarios and determine the likelihood of a given tropical cyclone wind speed impacting any location in the world.

The IRIS model is described in detail in (2024).

IRIS is a simulation based on physics and the global statistics of observations. We validate the global model against local observations.

We compare the same type of event in different climate scenarios. For example, we ask: how intense would a storm like this be in today’s climate, and how intense might it have been in a pre-industrial climate without human-caused warming?

By comparing the current conditions and a pre-industrial climate, we can isolate the "extra" intensity caused by climate change. This is then plugged into a damage function, a formula that translates wind speed into dollars lost, accounting for the current economic value and the current vulnerability.

The difference gives us an estimate of the damage attributable to climate change.

The relationship between wind speed and damage is not linear. A small increase in wind speed can translate into much more severe damage.

For many damage functions, below a certain wind speed, there is little or no damage expected, but once winds pass certain thresholds, damage can then rise very quickly. A modest increase in wind speeds on an already strong storm can therefore push a storm into a much more damaging range, putting more buildings and infrastructure at risk. 

Local context is also important. The same wind speed can cause very different levels of damage in different regions due to local factors like building quality and preparedness.

The models are statistical curves calculated using daily temperature and deaths. They show the risk of mortality at specific temperatures (). These curves account for age, seasonality, delayed effects, weekday patterns, and long-term trends.

Established hazard attribution methods compare today's climate with a climate without human-caused warming, using observations and models. First, the mortality model is run to gather the statistical curves. Then the mortality model is run twice more: once with actual temperatures, and once using the cooler temperatures that would have occurred in a world without climate change. The difference in the death toll between those two calculations is therefore attributed to the additional heat added by climate change. Other factors like seasonality, day-of-week patterns and age structure are built into the model.

The availability of open-access models in European cities provides us with the best data to make calculations. Cities also happen to be where most people live and urban heat effects make temperatures hotter than the surrounding countryside, driving more severe health impacts. Data from cities is also useful for policy-makers as most work on adaptation for heatwaves is focused on them.

Our studies show that people aged 65 and over make up the majority of estimated deaths. Risk concentrates in those with pre-existing heart, lung, kidney or neurological conditions, people on certain medications, and those with reduced mobility, because ageing bodies regulate temperature less effectively. Social factors matter too: people living alone, residents of poorly insulated housing without cooling, lower-income households, outdoor workers, pregnant women and infants are more vulnerable. Heat deaths are often recorded as heart or lung failure, which is why heatwaves are called silent killers.

Some countries in Europe provide official estimates of heat deaths (including the UK, Spain and Italy) using a method which differs from ours. All three look at ‘excess deaths’ that occur as ‘spikes’ beyond expected trends, similar to how deaths were measured during the COVID-19 pandemic. These estimates can be conservative as they don’t account for the warming climate, and the increasing ‘baseline’ of warm temperature deaths as a result. Our estimates try to capture the true impact of climate change.