How climate analytics helps utilities prepare for rapid change
Rapid climate change is already bringing new challenges to utilities. These challenges directly and indirectly impact multiple dimensions of the utility business, whether it’s physical damage to infrastructure from extreme weather or changing customer behaviors in response to warming temperatures. Factor in the stress on operations and the pressure of regulatory reform (along with the fact that climate change is projected to accelerate through the century), and it becomes evident that planning for these challenges is more important than ever to the bottom line—and that utilities should be acting now.
But utility planning based on historical information alone misses the mark. We know tomorrow’s climate won’t be like yesterday’s, so historical observations aren’t a sufficient barometer for future risks. Also, how tomorrow’s climate will manifest is uncertain; while we can say with a good deal of certainty what the weather will be three days from now, it’s impossible to provide a similar forecast for decades into the future.
Given this uncertainty, how should utilities approach climate planning? Climate analytics can help.
Climate analytics makes climate science actionable for utilities
Climate science provides us with a quantitative understanding of how future climate change can impact utility systems. The primary tools for understanding future climate change are global climate models, which numerically simulate climate system processes in time and space to produce projections of future climate. To do so, climate models consider a range of potential climate futures to quantify uncertainty and explore a range of impacts. However, utilities need more to understand these impacts in relation to their system and operations and, in turn, plan for the future.
That’s where climate analytics comes in. Climate analytics provides an actionable view of future climate conditions that can be tailored to the sensitivities, specifications, and characteristics of a utility system.
For example, climate analytics helps utilities integrate temperature projections to improve load forecasting and better estimate system conditions. It also allows utilities to understand how destructive climate hazards—such as coastal storms, wildfires, and heat waves—may impact specific assets over the decades ahead before utilities put new infrastructure in the ground.
Evaluating utility risks in a climate of uncertainty
Uncertainty can be the enemy of utility planning. It presents countless headaches for utilities trying to protect assets while deciding where to invest resources. That uncertainty, however, is here to stay, so ICF uses tools and approaches that put climate analytics and information to work to help utilities make smart decisions and build resilience.
While utilities are familiar with historical observations and short-term weather forecasts, climate projections differ because they aim to understand long-term changes over years and decades. Climate projections also carry larger uncertainty than weather forecasts due to their long-term focus (and because each climate model simulation produces a slightly different projection).
But it turns out that, instead of aiming for an incomplete understanding of the future by using projections from a single model, a large ensemble of models provides a broad perspective on the range of potential future climate outcomes. Moving beyond the science, climate analytics evaluates these outcomes probabilistically and through the lens of the utility’s risk tolerance to understand uncertainty and quantify a fuller range of utility impacts.
For example, the center of a distribution of model results may show 3°F of future warming, but a more extreme (but still plausible) outcome could be 6°F of warming near the distribution tail. While less likely, 6°F of warming drives more dramatic risks.
ICF uses climate analytics to understand how this range of potential warming could impact specific assets and operations. For example, based on a utility’s customized load forecasting, 6°F of warming could spike energy demand and peak load beyond its current system capacity, driving commensurate investments to adapt to a warmer world. Ultimately, the distribution of probabilistic projections prepares utilities to weigh the likelihood and severity of potential climate impacts, and to align with stakeholder-defined risk tolerances.
In the same way we use an ensemble of climate models to gain a clearer view of future climate risks, the climate science community looks to multiple representations of future greenhouse gas emission concentrations. Time-dependent greenhouse gas concentrations called Representative Concentration Pathway scenarios (RCPs) consider different emissions evolutions over the coming century—and drive global climate model simulations.
At ICF, climate analysts use multiple RCPs to bracket what future greenhouse gas emissions could look like and, in turn, represent different rates of climate change in a utility’s service territory. It’s not a tidy equation with an exact answer, but using multiple RCPs provides a way to corral climate uncertainty so utilities can make smarter investments in infrastructure, operations, and planning.
Stress-test scenarios for rare and complex events
Utilities increasingly face challenges from low-probability and high-impact events, such as hurricanes, nor’easters, ice storms, extreme heat waves, and catastrophic wildfires. These events often contain randomness and occur on scales too small to be simulated by global climate models. But these very events are tipping points for utilities, carrying the greatest risk and often leading to the most significant organizational change.
That’s where stress-test scenarios come into play.
A stress-test scenario is an interactive process between climate scientists and utility stakeholders.
At ICF, we first ask a utility what types of extreme events could pose the most considerable impacts to its systems because of the way those systems have been planned and built. Perhaps a utility’s transmission lines are susceptible to icing, or its substations are vulnerable to storm surge, or its supply chains are at risk from catastrophic hurricanes. We then pair that information with the best available climate science to craft quantitative scenarios that capture difficult-to-model and rare extreme events, and then apply them to a utility’s territory to stress-test its systems.
Stress-test scenarios are revealing in that they push a utility to think past traditional adaptation and resilience measures. When you understand that a Category 4 hurricane is going to wipe out parts of your system, for example, you realize you need to tackle the problem with a combination of approaches. Maybe you’ll decide to make smaller investments in microgrids and resiliency hubs to power food stores and hospitals when that hurricane hits.
When you know there’s not a simple solution, you can think more creatively about the interconnections between your utility and the area you serve, finding ways to build resilience with a solid understanding of the potential risks and rewards.
Tackling challenges, opening opportunities
Utilities are on the front lines of direct and indirect climate impacts—and doing nothing is no longer an option.
We’ve put climate analytics to work for leading utilities by developing climate change vulnerability studies and partnering on planning initiatives that help them face an uncertain future with confidence. To learn more, read our article about building utility resilience in a rapidly changing climate and listen to our webinar with Con Edison.
With the help of climate analytics, you, too, can be prepared for whatever tomorrow may bring.
