NGFS Climate Scenarios Q&A

No compound risks are not yet covered by the scenarios at this point in time. This limitation has also been noted by us, and we have drafted a note that covers the topic, and explains how this could be potentially incorporated in the future of climate scenarios here
Short-term NGFS climate scenarios are currently also in development, and those should cover the compound effect of physical risks already to some extent.

There is no specific point where this happens. Rather, every year that effective transition is delayed, the transition becomes more disorderly (if the same goal is to be achieved).

Low Demand is not a 'de-growth' scenario. Lower energy demand is achieved by changes in preferences that do not affect total demand (by assumption).

Physical risk damages are available on country-level (or sometimes region-level, depending on the exact variable you are looking for). The frequency of such hazards occurring is not covered.

It depends on the source of these price increases. If they are the result of fuel taxes, yes. If they are the results of geo-political turmoil, no.

The starting point in the data is a result of the underlying models. For simplicity, consider the year of release as starting year. Scenario modelling/results considered infromation until march 2023 for the november release last year.

Yes

Yes, the GDP impacts are provided by NiGEM, with different inputs per climate risk type. Transition considers fossil fuel consumption, carbon price and revenue, as well as useful energy from the IAMs as input to the NiGEM output. Chronic takes into account temperature pathways from the IAMs that flow into the damage function and then feed into NiGEM. Acute is based on seperate modelling per hazard, but underlying temperature pathways define the severity levels for each of them. Cyclones and floods cause capital asset damages, heatwaves cause decreases in labour productivity, and drought cause crop yield declines.
A detailed description can be found in the Technical Documentation.

GDP damages are a result of different scenario narratives implemented in the IAMs feeding into NiGEM. As such, GDP damages presented in slide 21 are the sum of transition impacts (from the green transition) and physical impacts (from climate change). Physical risk considers chronic risk (based on a damage function) and acute risk (which considers damages from four natural hazards being cyclones, floods, heatwaves, droughts.

IAM data is also provided in IAM-native regional clusters as well as in seperately downscaled country-level data. Those might be more applicable to your needs.

We provide an overview of variables in the documentation in the IIASA Scenario Explorer
(https://data.ene.iiasa.ac.at/ngfs/#/docs)
and in the EnTry Parameter Guide
(https://colab.research.google.com/drive/1me73vvS2rQCFeQ3q1Ohck3JMltG0hEGS?usp=sharing)
where you can find an overvieew of all variables per category with corresponding units.

You may observe the higher damages in Delayed Transition because you are looking at overall GDP damages, which are driven by both transition and physical damages. The Net Zero 2050 scenario keeps global waming to 1.5°C, whereas the Delayed Transition models a global temperature increase up to 2°C, which results in higher physical risk damages. In general, Net Zero 2050 shows higher transition GDP damages than Delayed transition due to the higher carbon pric, but the total damage in Delayed Transition may be higher due to elevated physical risks.

Macro-models are indeed callibrated on historic data. However, the baseline used in our NiGEM runs is callibrated on the SSP2 pathway, which projects a number of macro variables decades into the future.

The macro-model does not provide confidence intervals on its output. There are only a few variables in the NGFS scenarios that come with confidence intervals. The temperature pathway of each scenario is one of the few variables for which multiple percentiles are available (ranging from the 5th to 95th). Output of the chronic damage function is also available for these various temperature percentiles, as well as a low, median and high damage estimate. As such, a confidence interval can be constructed for the chronic damages. Transition risk and acute physical risk impacts do not come with this feature

They are based on the same scenarios (specifically the respective temperature pathways). But are modelled differently, i.e. damage function versus nature catastrophe modelling.

NGFS Scenarios are not forecasts, not a final product rather a common reference framework.
Users often lacking knowledge on underlying assumptions and differences across IAMs or regional granularity. They should be used as a starting point for institutions' own analyses. The scenario set should not be considered an exhaustive analysis on itself. More details can be found in the recently published guidance note: https://www.ngfs.net/en/ngfs-guidance-note-scenarios

Can be found here https://colab.research.google.com/drive/1IaWVYFIoyqOT6uFjumRsmv94fRNvE9Zu?usp=sharing#scrollTo=Qlf5BPI6_O6I

After the latest release we held a few data tutorial sessions, which we will likely repeat after this year's release.

A sectoral disagregation method is being developped, which will allow users to increase the sectoral granularity of the long-term scenarios. In addition, many more granular variables are foreseen to be part of the short-term scenarios, which will likely be published early 2025.

The proposed methodology will show a way to disaggregate the scenarios final energy series using main CPRS sectors to create sectoral GDP impacts by incorporating energy demand, prices as well as elasticities in an estimation with a CES production functions at sectoral level.

This is due to a modelling assumption on chronic physical risk. While transition impacts are quite well captured by the NGFS suite-of-models, we recognize that it is difficult to capture the full potential impact of climate physical risks. At higher warming levels, such as observed in the Current Policies scenario, damage estimates may vastly underestimate total losses due to great uncertainty about what could happen at such high warming levels. To account for this higher uncertainty, and in attempt not to underestimate losses, the choice was made to use a higher damage estimate for Current Policies (i.e., a higher percentile of the damage distribution) than for Orderly scenarios. This difference in modelling assumtions between the scenarios causes the small difference at the start of the time period.

Regional impacts always differ from the global levels. On regional/country level there are regions above and below the global estimation. We do not observe the described tendency.

They are intended to be published early 2025 but adjusted depending on development and review process

The exogenous inputs per model used to produce are in detail described in the technical documentation. In short, IAMs are mainly based on the IPCC SSP2 scenario, which then flow into the other models of th emodelling suite, primarily GDP and temperature pathways.

At the moment, the technical documentation is the most granular type of information publicly available. We have noted this, and will take it into consideration for future updates for the technical documentation.