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Physical climate risk management poses a significant data and methodological challenge for investors. Currently, there is no standard approach to understand, communicate or model these risks.

Impax continues to focus on developing and implementing its own approaches to physical climate risks through engagement with academia, companies and other investors, as well as through ongoing internal research. We recently explored an example of the latter with the help of Dr Nicola Ranger and Dr Mark Bernhofen, from the UK Centre for Greening Finance and Investment (CGFI) at the University of Oxford,1 as a step towards a consistent methodology on translating future climate changes into quantitative inputs for financial models.2

In general, public data alone is insufficient for this kind of analysis. We focus here on two specific industries where Impax has key insights on industry dynamics, asset locations and rebuild costs, which enabled an interesting and meaningful analysis.

Impax and the CGFI worked together on two case studies, focusing respectively on the semiconductor and data centre sectors. The purpose of the collaboration was to help Impax understand which assets might face heightened physical risks, and therefore loss or damage, and to demonstrate the usefulness and applicability of the CGFI’s Global Resilience Index Initiative (GRII) datasets within the investment community.

The focus of our collaboration

We assessed the exposure of 88 assets that belong to four companies (two semiconductor manufacturing companies and two data centre operators) to four separate climate hazards – tropical cyclones, river floods, coastal floods and heatwaves – in the Asia-Pacific (APAC) region.3 We were particularly focused on heatwaves for data centres, and flooding and cyclones for semiconductor manufacturing facilities.4

Our interest in the links between heatwaves and data centres was triggered by recent disruptive events such as persistent and extreme European heatwaves in the summer of 2022. One led to the temporary shutdown of a UK data centre, highlighting the vulnerability of data servers to extreme heat. Further, following a 2021 engagement with US companies, Impax was not confident in the plans of data centre operators or owners to mitigate their exposure, or improve their resilience, to physical climate risks in general. Understanding the exposure of data centre assets therefore became a key focus of this analysis, particularly given high average temperatures in the APAC region.

The motivation to assess the exposure of semiconductor makers to acute hazards such as cyclones and flooding was similar. During the global semiconductor chip shortage in 2021/22, the importance of this vital component was highlighted to capital markets. Some estimates place semiconductors as directly responsible for only 0.3% of US output, but they are an important input to products constituting 12% of US GDP.5 Taken with the geographic concentration of particular semiconductor companies in places like Taiwan, South Korea and China, a very damaging regional flooding or cyclone event would represent a potential systemic risk. The 2011 Thai floods were an example of such a disruption to a geographically concentrated supply chain.

Another reason to assess data centre and semiconductor manufacturing assets is their relative importance to their owners. The two semiconductor companies assessed have only 17 and seven major facilities respectively, for instance, despite large revenue bases. Additionally, their physical size and high cost make the relocation of exposed assets very difficult.

For the analysis, we evaluated the potential risk to each company by overlaying publicly disclosed physical asset locations with climate data from the GRII for each of the four climate hazards. The asset location data was retrieved from company websites and financial disclosures – an essential and often difficult-to-obtain input into the analysis. The data spanned both historical and future time periods (more information is available on the GRII website) and the future scenarios used are outlined below.6

HazardFuture scenarios used6Time points assessedNumber of models used
Flooding – coastalRCP4.5, RCP8.52030, 2050, 20801
Flooding – riversRCP4.5, RCP8.52030, 2050, 20805
HeatwavesRCP2.6, RCP6.0, RCP8.52030, 2050, 2080 4
Tropical cyclones SSP5 8.520504

These data points were used to calculate Average Annual Loss (AAL) for each of the assets across the above time periods and scenarios. AAL describes an expected loss per year due to either direct asset damage (in the case of flooding and cyclones) or revenue loss due to downtime (in the case of heatwaves). To calculate this, we also estimated asset values and annual revenue based on public disclosures and used or adjusted damage functions, as defined by various academic papers, to link the changing hazards to asset value impacts.7 Asset-level information was then aggregated to the company level in each case.

The charts below show some results of the analysis:

Chart illustrating annual revenue loss from heatwaves in 2050.
Chart illustrating annual losses by 2050 due to river and coastal flooding.

Conclusions from the research

Given that the analysis spans many decades and only some hazards have data points for 2030, the immediate materiality of implications for these companies is limited. However, the analysis illustrates the potential magnitude of future financial losses that may be incurred, relative to today, due to asset damage from climate events.

One conclusion is that we expect Semiconductor Company D’s assets to experience a greater change in flooding-related losses in the future than Company C. Beyond the factors of proximity to rivers and local topography, Company D also has fewer major assets and so is more vulnerable overall to the impact of any one of its assets being hit by floods.8

A second conclusion is that we expect heatwaves will lead to a dramatic increase in revenue loss. Of the two data centre operators analysed, Company A has a higher projected average annual revenue loss from heatwaves in 2050.

It is important to bear in mind that these figures express the average or expected annual loss: the real numbers may be higher and come sooner. To illustrate this, we grouped assets located in the same hydrological basin and summed their return period losses.9 Extreme losses (that one might expect once in a hundred years) for Semiconductor Company C were nearly ten times larger than the expected annual losses. These ‘extreme’ estimates are likely still an underestimate, as flood events can occur over much larger areas than the hydrological basins we considered. This point illustrates the importance of incorporating extremes in financial physical climate risk assessments. We are working closely with Oxford and the CGFI to develop approaches that explicitly do this.

These case studies serve as a proof of concept on the usefulness of GRII data and the application of a new methodology to assess future financial losses at the asset level. The research deepens our understanding of the risks facing data centres and semiconductor manufacturers, and could inform engagements with companies in these sectors to assess and compare their plans for adaptation and resilience to all four hazards.

This work represents another step towards our goal of comprehensive reporting on the expected financial value of physical climate risks. We look forward to our continued collaboration with Oxford on sector-specific research, with the aim of translating climate hazards into model-ready financial inputs. 

1 Impax has been a supporter of the UK Centre for Greening Finance and Investment since its inception, and Impax Founder and CEO, Ian Simm, is a member of the CGFI Advisory Council

2 We would like to thank Dr Nicola Ranger and Dr Mark Bernhofen for their collaboration. Dr Nicola Ranger is Executive Director at the Oxford Martin Programme on Systemic Resilience, and Programme Leader on Resilience and International Development at the Environmental Change Institute, University of Oxford. Dr Mark Bernhofen is a Research Associate in Climate Analytics and Scenarios at the Oxford Sustainable Finance Group, which is part of the Smith School of Enterprise and the Environment at the University of Oxford. Both are part of the UK Centre for Greening Finance Investment which brings together eight research institutions from across the UK to support financial institutions to integrate climate risks into decision making.

3 Our analysis looked at 24 semiconductor manufacturing and research facilities and 64 data centres

4 An exploration of water stress to these semiconductor manufacturing assets was also briefly explored, given the very-high water intensity of the fabrication process, but did not ultimately feature in this stage of the analysis due to data constraints. We would like to explore this aspect further in the future.

5 Goldman Sachs Economics Research, 21 April 2021: A Semi-Troubling Shortage

6 Representative Concentration Pathways (RCPs) describe a wide range of plausible future emissions scenarios and reflect different greenhouse gas concentrations in the atmosphere, relative to pre-industrial levels. Here is an explainer:—representative-concentration-pathways.pdf 

7 For our forward-looking analysis, we make the simplifying assumption that future annual revenue is equal to present annual revenue.

8 Future flood risk estimates in the APAC region are highly uncertain (some models don’t even agree on the sign of future change). Researching the drivers of this uncertainty and developing best-practice for communicating uncertainty is an ongoing topic at the CGFI.

9 We use the HydroBASINS Level 8 classification under the assumption that assets in a basin of this size are likely to experience the same flood event.

Nothing presented herein is intended to constitute investment advice and no investment decision should be made solely based on this information.  Nothing presented should be construed as a recommendation to purchase or sell a particular type of security or follow any investment technique or strategy.  Information presented herein reflects Impax Asset Management’s views at a particular time.  Such views are subject to change at any point and Impax Asset Management shall not be obligated to provide any notice.  Any forward-looking statements or forecasts are based on assumptions and actual results are expected to vary.  While Impax Asset Management has used reasonable efforts to obtain information from reliable sources, we make no representations or warranties as to the accuracy, reliability or completeness of third-party information presented herein.  No guarantee of investment performance is being provided and no inference to the contrary should be made.

Matthew Wright

Research Analyst

Matthew works in our Listed Equities team, covering companies across the water value chain. He is also a specialist in physical climate risk research and impact, as they apply to Impax’s investments.

Matthew previously worked as an analyst in both a management consulting firm and in his first role as a carbon data analyst for an investment data analytics company, formerly known as Engaged Tracking.

He graduated in 2019 from Imperial College London after gaining a master’s degree in Environmental Technology with a focus on environmental economics and policy. Matthew also has a bachelor’s degree in Geophysics from Imperial College London.

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