On November 4, MeteoSwiss published updated climate scenarios for Switzerland. The scenarios describe the expected changes in the climate in Switzerland under an increase in global warming by 1.5, 2 and 3 degrees respectively (Global Warming Level (GWL)) compared to the reference period 1991-2020. The timing if and when these GWLs are reached depends on the specific climate scenario considered.  

The climate scenarios for Switzerland are anchored in the global climate scenarios that have been included in the sixth and last assessment report of the Intergovernmental Panel on Climate Change (IPCC) from 2022. The three main global scenarios considered are a combination of a Shared Socio-Economic Pathway (SSP) and a Representative Concentration Pathway (RCP): 

• “SSP1-2.6” represents a combination of SSP1 and RCP2.6 ("2-degree path with net-zero target achieved by 2050") 

• “SSP2-4.5” represents a combination of SSP2 and RCP4.5 (“’Middle ground’ scenario following current and planned measures“) 

• “SSP5-8.5” represents a combination of SSP5 and RCP8.5 (“Fossil fuel path without climate protection“) 

The Figure above depicts the approach taken by MeteoSwiss to assess the consequences for Switzerland at specific GWLs: 

1. The top part of the Figure (“Global”) shows three global climate scenarios, each of which achieves the depicted GWL at a different point in time. 
2. MeteoSwiss has translated each of the global scenarios to specific scenarios for Switzerland (more than three in fact, but the picture only shows three). These scenarios are shown in the bottom part of the Figure (“Swiss”). It can be seen that the same GWL in the global scenarios corresponds to different warming levels for Switzerland. This leads to a range of possible warming levels in Switzerland for each GWL. 

In the next sections, the main expected changes in temperature and precipitation in Switzerland under the different GWLs are considered. Subsequently, the steps needed to use the information about the climate scenarios for a materiality assessment of climate risk are outlined. In addition, an overview is provided of the data that has been made available for the Swiss climate scenarios by MeteoSwiss, which can be used for such a materiality assessment. 

1. Changes in temperature 

MeteoSwiss estimates that by 2024, the average temperature in Switzerland already increased by 2.9°C compared to pre-industrial times (1871-1900). This is more than double the rise of 1.4°C in average global temperature. The larger rise in Switzerland is partially due to the fact that the temperature above land increases more quickly than above sea. 

With rising global warming, the number of hot days (>30°C) in Switzerland is expected to roughly triple in a 3-degree world (GWL3.0). The largest impact will be in urban areas, as depicted in the Figure on the right.  

In line with this, the average summer temperature as well as extreme temperatures (warmest day and night) will increase. 

Potential economic consequences: 

• Extreme heat during the day and a lack of cooling at night put strain on the body and affect health. In addition, physical and mental work is made more difficult during heatwaves, with dense urban development exacerbating this. This will affect productivity, lower economic output and may increase costs for cooling work environments. 

2. Changes in precipitation 

Yearly precipitation is not expected to change in Switzerland with global warming, but summers are expected to get drier and winters are expected to get wetter. Moreover, extreme precipitation (heavy rainfall, hail) is expected to increase in both frequency and intensity, as depicted in the Figure below. 

Source: Climate CH2025 – Brochure, MeteoSwiss (link) 

Drier summers lead to an increased risk of forest fires as well as increasing frequency and intensity of droughts, as depicted in the Figures below. 

Precipitation in winter will increasingly fall in the form of rain instead of snow as the zero-degree line increases.  

Potential economic consequences: 

• Sudden flash floods and hail can cause property damage and business interruptions. In addition, they can destroy agricultural crops. This will negatively affect economic output and decrease the value of properties in areas at risk. 

• Drought leads to yield losses in agriculture and increased risk of forest fires, causes water shortages in reservoirs and restricts water supply. In addition, drought can intensify and prolong heatwaves. This will negatively affect economic output 

• Thawing permafrost and melting glaciers can lead to unstable slopes, and the water cycle may be disrupted. This will affect industries that depend on water (e.g., for cooling). Decreasing snow will also affect winter tourism and associated industry sectors. 

3. Estimating financial impacts 

For the potential future changes in temperature and precipitation in Switzerland because of global warming, the possible economic consequences have been explored in the sections above. To what extent these are relevant for risk management of a financial institution will depend on the sectors and physical locations of their clients, counterparties and issuers of securities in which they invest.  

The general steps taken to perform a materiality assessment for individual clients, counterparties and issuers are: 

1. Identify transmission channels through which the impacts of global warming can negatively impact their business. 

2. Estimate the financial impact of individual transmission channels. 

• As historical data is not representative of what is likely to happen in the future under global warming, a common approach is to use scenario analysis.  

• FINMA explicitly expects financial institutions to employ scenario analysis when performing the materiality assessment for nature-related financial risks in its recent circular (link, see our Zanders blog for a summary).  

• The Swiss climate scenarios can form a basis for the scenario analysis. However, the climate impacts that have been made available by MeteoSwiss (see Section 4) need to be translated to a financial impact for clients, counterparties and issuers. The impact on both revenues (e.g., lower sales due to business disruptions or lower demand) and costs (e.g., higher costs due to damages or required additional investments) need to considered. 

• Mitigating measures such as insurance can be taken into account if they are deemed effective in the scenarios considered. 

3. Reflect the estimated financial impact in internal risk metrics, such as credit ratings, collateral values and the value-at-risk of investments. 

For companies that are active internationally, or which depend on international supply chains, the exposure of their supply chains and international markets to the impact of global warming also needs to be considered. 

4. Swiss climate scenario data 

With the publication of the Swiss climate scenarios, MeteoSwiss also makes available detailed scenario data. This data can be viewed through an interactive WebAtlas (link) for combinations of: 

• Various temperature and precipitation indicators (listed in the document “Overview of CH2025 climate indicators” (link)) 

• Reference period (1991-2020) and three future Global Warming Levels (GWL1.5, GWL2.0 and GWL3.0) 

• Annual changes as well as seasonal changes (Winter, Spring, Sommer and Autumn) 

• Switzerland as a whole, each of five ‘biogeographic’ regions (Jura, Swiss Plateau, Pre-Alps, Alps, and South side of the Alps) as well as individual weather stations 

• Three climate scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) over time (2040-2060) (for mean temperature and precipitation only) 

The following detailed data can also be accessed directly: 

• Historical climate data (daily) at individual Swiss measurement stations since measurement started, covering 169 indicators related to temperature, humidity, precipitation, wind, sunshine, snow, air pressure, evaporation and radiation. (link) 
  • These data have been ‘homogenized’ for changes in measurement methods over time. 

• Scenario forecast data (daily) for different Global Warming Levels (GWL) under different Regional Climate Models (RMC) (link)(link) at 
  • Individual weather stations (DAILY_LOCAL) 
  • 1km×1km gridpoints in Switzerland (DAILY-GRIDDED) 

Climate variables included in the daily scenario forecasts are shown in the table below. 

How Zanders can help 

We have supported various banks with the assessment of the materiality of climate risks for their clients, counterparties and investment issuers. With our focus on risk and technology and our strength in applying quantitative approaches, we are particularly well equipped to substantiate a materiality assessment with scenario analysis and the use of data. If you want to learn more, do not hesitate to contact us. 

We’ve spoken to many banks recently, and the message is clear: developing and implementing a climate reverse stress testing (RST) framework will be a significant challenge, particularly as it is a completely new regulatory expectation for climate risk from the PRA. Most banks are already familiar with RST in the context of credit, market, and liquidity risks. But extending this practice to climate introduces a different level of complexity.  

Until now, climate quantitative analysis has centered on standard stress testing and scenario analysis, asking what could happen under different climate pathways. Reverse stress testing flips the question: what climate pathway could push your business model to the point of failure?

You may have already fallen into the trap of believing these common myths; if so, it’s time to rethink your position: 

• “Our institution is not exposed to climate risk.” The PRA is unlikely to accept this - climate risk is systemic. It manifests as transition risk (such as carbon taxes or shifts in consumer expectations) and physical risk (both acute climate events and chronic changes). These drivers affect almost every portfolio: credit exposures like commercial loans and mortgages, market positions in bonds and equities, and even operational resilience. Hence, it is highly likely that your institution is already exposed to climate risk factors, directly or indirectly. 

• “Rain alone could never cause us to fail.” This could be true if it weren’t for the fact that risks don’t occur in isolation. Rainfall, carbon prices, GDP slowdown, and interest rate rises can interact in complex and non-linear ways to push an institution towards failure. Although a single risk factor might need to reach an extreme tail event to cause failure, multiple risk factors acting together don’t need to be extreme to push a firm to the brink. Plausible domino effects can occur - for example, in a mortgage portfolio, heavier rainfall increases flood risk, lowering property values and weakening collateral. At the same time, a rise in carbon prices lifts household energy bills, cutting disposable income and pushing up default probabilities. Higher PDs, combined with weaker collateral driving LGDs higher, can accelerate capital erosion towards the failure point.

• “The failure points are so extreme, there’s no benefit in analyzing them.” A failure point doesn’t have to mean the bank has collapsed entirely. In practice, it could be something completely plausible, such as the CET1 falling below 11% or liquidity buffers dropping under regulatory requirements. These are thresholds that banks already monitor as part of business-as-usual.  

• “What’s the benefit of RST? We already run standard stress tests.” RST forces firms to confront and explore extreme, and yet plausible, critical scenarios they might otherwise avoid. It can uncover vulnerabilities that remain hidden in conventional stress testing. 

We recommend that you should prepare for the following key challenges: 

• Defining failure points: Deciding exactly what a failure would look like is not straightforward and is the first challenge. Most firms will base the breaking point on a regulatory capital measure such as CET1. From there, they need to identify the internal drivers (PD, LGD, credit spreads, liquidity buffers etc) that would cause it to erode. 

• Deriving transmission channels: The next critical step is mapping which climate variables (such as carbon price, rainfall, and temperature shocks) could realistically impact those internal drivers. For example, in mortgage portfolios, heavier rainfall could reduce property values and raise insurance costs, leading not only to higher LGDs but also higher PDs. 

• Developing supporting models: In many cases, deriving the relationships between the different drivers requires additional supporting models. For example, firms may need to develop models to measure and assess the relationship between rainfall and LGD/PD. 

• Quantification of the narrative: Over time, the PRA is likely to require qualitative insights to evolve into quantified relationships between climate drivers, bank risk factors, and failure points. It’s not just about establishing a link between rainfall or carbon prices and LGD/PD, but defining potential levels of the risk factors that could push the bank to failure.

• Embedding outcomes: RST results need to feed into firm-wide processes and systems, including governance, reporting, and ongoing monitoring. At this stage, RST stops being just a regulatory expectation and becomes a proactive tool for managing risk. 

At Zanders, we can support you in developing climate RST frameworks that are: 

• Proportionate: from plausible qualitative narratives to quantification models, aligned to your portfolio exposure to climate risk. 

• Scalable: solutions that evolve along with your firm’s climate risk journey. 

• Strategic: we guide you through achieving regulatory compliance while always keeping an eye on your long-term business objectives. 

How far are you with planning and self-assessment for climate RST at your firm? Our advice: don’t wait until the updated Supervisory Statement is published by the PRA to planning (or start putting in place a plan for) for a climate RST framework. Starting early will make the process smoother and ensure you are well-positioned and prepared when regulatory scrutiny will inevitably materialize. 

We would be delighted to share our insights and discuss how we can support your climate risk journey. Please reach out to the Zanders UK climate risk modeling team (Polly Wong, Nikolas Kontogiannis, Hardial Kalsi, Paolo Vareschi).