News & media Beyond 2°C: Managing Agricultural Climate Risk
By Thiago Dalmédico Gil
On the coattails of New York Climate Week 2025 and in the run-up to COP30 in Brazil next month, climate resilience and agriculture belong at the centre of the public debate. The financial community must be in the room, not as observers, but as proactive actors, because financial feasibility is a prerequisite for scaling sustainable agricultural practices.
One of COP30’s six strategic themes is “Agriculture and Food Systems”, emphasising mitigation through regenerative practices, adaptation of small-scale farming, and food security in the face of climate volatility. Such volatility is already fundamentally disrupting global food chains: the Intergovernmental Panel on Climate Change (IPCC)’s Sixth Assessment Report[1] confirmed that drought-related yield losses have occurred in approximately 75% of the global harvested area, with combined heat and drought effects decreasing global average grain yields by more than 10%.
One may argue that climate effects are counterbalancing: a drought in Brazil may be offset by positive weather patterns in the USA, allowing soybean production losses in the South to be compensated by production increases in the North. However, this assumption is flawed because agricultural impacts are fundamentally asymmetric, as shown by existing research: a considerable increase in precipitation can boost corn crop volume by slightly above 1%, while a decrease of the same magnitude reduces corn production by more than 5%[2].
The United Nations Framework Convention on Climate Change (UNFCCC, which addresses global responses to climate change) focus on curbing asymmetric risks is precisely what led to the adoption of the well-known 2°C maximum temperature increase threshold. The 2°C threshold has been a guiding target to the industry for years and will guide COP30 negotiations on agricultural adaptation and food security. However, the origin of this target is often misunderstood. It did not emerge from a definitive scientific consensus but rather from economist William Nordhaus’s 1975 paper, “Can We Control Carbon Dioxide?”, in which he tentatively proposed it as a “think out loud” metric. Subsequent research, however, has provided robust scientific justifications, demonstrating that risks of large-scale extinctions and other catastrophic impacts increase substantially beyond this threshold. This aligns with concepts from catastrophe theory, a mathematical principle that describes how gradual changes in systems, such as nonlinear climate systems, occur. These systems may exhibit gradual change until a tipping point triggers an abrupt and irreversible shift.
The regulatory and financial world’s intense focus on the 2°C threshold often comes at the expense of preparing for “near-catastrophe” conditions. By fixating on a single, clear target, they risk overlooking the inherent opacity and asymmetry of the climate crisis, thereby underestimating the immediate financial risks to vulnerable sectors such as agriculture. Understanding these nonlinear risks is crucial for policymakers and investors alike, ensuring that decisions made are financially and ecologically resilient.
This is why, at Cordiant, we move beyond conventional risk management when it comes to weather. We believe precautionary measures are the only reliable way to mitigate climate risk, which is why we employ exhaustive modelling techniques to estimate the potential financial impact of extreme weather events on our investments.
We have developed a comprehensive toolkit to estimate the financial implications of events (such as a severe El Niño) on portfolio resilience. This toolkit encompasses a range of statistical techniques, including multivariate analysis and copulas, that model the probabilities and impacts of asymmetric weather events on agricultural volumes and prices. Additionally, it includes biogeochemical models that simulate vegetative growth and soil organic carbon under various climate conditions.
Here are some examples below.
Exercise 1: We use a dynamic copula[3] climate model that turns raw ERA5 weather data into investable risk signals. We aggregate monthly temperature, wind, and precipitation data to fit each series with time series models, capturing persistence/seasonality and linking their joint extremes using a t-copula. Thus, we can simulate thousands of multi-year paths. From these paths, we obtain season-aware probabilities and return periods for events such as hot-dry months, as well as expected shortfall magnitudes. While this exercise is useful, it is not sufficient. Because t-copulas are not fully robust to complex systems, we incorporate extra layers to simulate extreme events, as shown below.
Exercise 2: We utilise a weather-to-yield stress-testing model that links temperature, rainfall, and radiation to plant physiology (evapotranspiration and water stress) and subsequently to expected yield and unit revenues. We run scenarios, for example, +3 °C with 50% precipitation during fruit set, to estimate the downside yield and convert that into revenue-at-risk and DSCR/ICR impacts. Those outputs drive action: pre-fund irrigation, adjust LTV and amortisation to scenario-weighted cash flows, and size hedge overlays (parametric drought covers or partial futures collars) to cap the modelled P&L drawdown.
In a climate system characterised by nonlinearity and escalating instability, conventional risk models are dangerously inadequate. Our exhaustive, multi-layered modelling is not merely an analytical exercise; it is a fundamental precaution. By quantifying the asymmetric nature of weather shocks and simulating crisis-level scenarios, we transition from reactive assessment to proactive management, particularly since we acknowledge that models are imperfect and prone to failure. This rigorous, forward-looking approach enables us to make decisive interventions, such as adjusting loan terms or structuring hedges, that protect investments against the volatile reality of a warming world. It ensures resilience to long-term capital where traditional methods would fail.
As COP30 approaches, proactive financial strategies are not optional, they are essential to ensuring that the world’s agricultural systems can withstand nonlinear climate risks, protect food security, and support sustainable investment in a warming world.
[1] United Nations Development Programme. (2022, May 26). 8 key messages about climate risks to agrifood systems from the IPCC’s Sixth Assessment Report. UNDP Climate Change Adaptation. https://www.adaptation-undp.org/8-key-messages-about-climate-risks-agrifood-systems-ipccs-sixth-assessment-report
[2] Organisation for Economic Co-operation and Development. (2025). Global Drought Outlook: Trends, impacts and policies to adapt to a drier world. OECD Publishing. https://doi.org/10.1787/d492583a-en
[3] A copula is a statistical “glue” that links separate uncertainties, like temperature, wind, and rainfall, so we can model how they move together, especially in bad times. In our case, a t-copula lets us ask: “How often do hot and dry months coincide, and how severe are they when they do?” That joint-extreme view is what matters for agriculture: yield and cash-flow risk usually spike when multiple weather stresses hit simultaneously, not in isolation.