How Climate Change Can Skew Solar Energy Production

At first glance, solar energy appears to be the most stable and predictable of all renewable sources. Unlike wind, which can die down without warning, or hydropower, which depends on fluctuating rainfall and reservoir levels, the sun’s daily rhythm seems constant. The sun rises and sets every day, and over decades scientists have accumulated detailed irradiance records that allow energy planners to estimate expected output with remarkable precision. These datasets have underpinned the rapid expansion of solar worldwide, supporting investment decisions, grid integration strategies, and forecasts of how much power will be available at any given time of year.

Yet this sense of certainty is being quietly undermined. Climate change is not altering the fundamental fact that the sun will rise tomorrow, but it is reshaping the conditions that determine how much of that sunlight actually reaches solar panels and how efficiently they convert it into electricity. Shifts in weather patterns, rising global temperatures, and the increased frequency of extreme events are distorting long-held assumptions, leaving solar production less reliable than the historical averages suggest.

The consequences are no longer theoretical. From heatwaves in Europe that reduce panel efficiency, to wildfire smoke in North America that blocks out sunlight for days, to shifting monsoon cycles in Asia that bring longer periods of cloud cover, the impact is already visible. What was once a straightforward calculation based on irradiance tables and seasonal patterns has become a moving target — forcing operators, researchers, and policymakers to rethink how we plan for and manage solar energy in a changing climate.

More extreme weather events

One of the clearest fingerprints of climate change is the rise in extreme and unpredictable weather. For solar energy, this trend introduces multiple challenges at once.

Storms that bring heavy rain or dense cloud cover reduce the amount of direct sunlight reaching photovoltaic panels, lowering electricity production sometimes by half or more. Where once these events were occasional interruptions, they are now becoming more frequent, stretching across seasons and regions where they used to be rare. Long periods of persistent cloudiness — sometimes linked to stalled weather systems — can depress solar output for weeks, undermining the stability of daily and monthly energy forecasts.

Beyond reduced irradiance, extreme weather can also cause physical damage. Hailstorms, increasingly intense in some areas, can shatter or pit panel surfaces, reducing efficiency or rendering them useless until replaced. High winds associated with tropical storms, hurricanes, or derechos pose structural risks, not only to panels themselves but also to mounting systems and inverters. When such damage occurs, output does not simply drop by a predictable percentage: it can collapse suddenly, leaving operators with an unexpected gap in supply.

These events also test the resilience of solar farms at a systemic level. Flooding can disrupt access roads and bury wiring, while lightning strikes can knock out inverters or grid connections. Even when panels remain intact, downtime for inspection and repair can take plants offline for days or weeks.

What makes these challenges particularly serious is that they are not evenly distributed. Regions that have invested heavily in solar — such as southern Europe, the American Southwest, or parts of India and China — are also places where climate models project increases in heatwaves, drought punctuated by violent storms, and shifts in precipitation patterns. This geographical overlap amplifies the risks, making extreme weather not a distant possibility but a present and growing operational concern.

Rising temperatures

While solar power thrives on sunlight, it does not thrive on heat. Photovoltaic (PV) panels are rated under “standard test conditions” — typically a cell temperature of 25°C — but in real-world operation their efficiency declines as the temperature rises. For crystalline silicon panels, which dominate the global market, each degree above 25°C reduces efficiency by about 0.4–0.5%. In practice, that means a panel operating on a rooftop at 40°C may produce 7–8% less electricity than expected under laboratory conditions.

Climate change is intensifying this problem. Heatwaves are growing more frequent, more severe, and longer in duration across much of the world. In southern Europe, for example, record-breaking temperatures above 45°C have become almost annual events. Under these conditions, panel surfaces can exceed 65°C, pushing performance losses into the double digits.

The timing of these losses compounds the challenge. Peak heat often coincides with peak electricity demand, as households and businesses run air conditioners at full capacity. Instead of solar production comfortably meeting daytime demand, grid operators may find themselves facing reduced supply just when the need for power is greatest. This mismatch can strain systems, increase reliance on fossil-fuel backup plants, and raise costs for consumers.

High ambient temperatures also stress the surrounding infrastructure. Inverters, transformers, and battery storage systems all operate less efficiently in the heat, and in some cases must shut down to prevent overheating. The cumulative effect is a systemic vulnerability: not only do individual panels lose efficiency, but entire solar installations and their supporting systems may be compromised.

Looking ahead, climate projections suggest that temperature-related performance losses will become a routine planning factor. Solar developers are already experimenting with adaptations, such as elevated mounting systems that allow airflow under panels, lighter-colored rooftops to reduce heat absorption, and new materials with lower temperature coefficients. Yet these measures add cost and complexity, underscoring how rising global temperatures are reshaping what was once considered one of the simplest forms of renewable generation.

Shifting seasonal patterns

Solar production has always followed the rhythm of the seasons: longer days and higher sun angles in summer, shorter days and weaker sunlight in winter. For decades, planners could rely on relatively stable seasonal cycles to forecast generation, build financial models, and size systems correctly. Climate change, however, is starting to erode these familiar patterns, introducing new uncertainties into what used to be predictable.

One major factor is the shifting behavior of cloud cover. In many regions, atmospheric circulation is changing in ways that alter when and where clouds form. Southern Europe, for example, is experiencing summers that are not only hotter but also hazier, with more frequent dust intrusions from the Sahara and prolonged cloud banks linked to altered jet stream dynamics. Meanwhile, some areas that once enjoyed reliably clear winters are seeing extended periods of fog or haze. These changes disrupt the seasonal expectations that underpinned decades of solar planning.

Precipitation cycles are also becoming less regular. Monsoon systems in Asia are arriving later, lasting longer, or delivering rainfall in fewer but more intense bursts. For solar farms designed around historical monsoon calendars, this means extended stretches of low output when power was once expected, followed by sudden recovery that can complicate grid management. Similarly, in regions like the American West, climate change is linked to long dry spells punctuated by intense storms — a pattern that makes solar production more erratic than the smooth bell-shaped curves predicted by older models.

The tilt in seasonal reliability does not just affect grid operators; it also impacts households and businesses. Solar owners accustomed to predictable monthly bills may now face unexpected dips in output at times of year when production was historically steady. For utility-scale operators, revenue streams tied to seasonal expectations can be disrupted, forcing a reevaluation of financial risk models.

In the long run, these shifting patterns highlight the limits of relying solely on past climate records for planning future solar production. Instead, forward-looking models that integrate climate projections will be necessary to understand how the “new seasons” of the 21st century will shape solar energy availability.

Air quality and aerosols

Even when the skies look clear to the human eye, solar panels may be receiving far less sunlight than expected. The culprit is often aerosols, tiny particles suspended in the atmosphere, including dust, smoke, soot, and industrial pollution. These particles scatter and absorb sunlight, reducing the amount of direct irradiance that reaches photovoltaic cells and altering the balance between direct and diffuse radiation.

Climate change is amplifying this challenge in several ways. Wildfires, fueled by hotter and drier conditions, are burning larger areas and for longer periods than in the past. The massive smoke plumes generated can blanket entire regions for days or weeks, cutting solar output by 30–50% in some cases. During the 2020 wildfires in California, for example, solar generation dropped dramatically even though skies were only partially obscured. Australia has experienced similar disruptions during its “Black Summer” fires, with smoke haze reducing solar farm output across multiple states.

Dust transport is another growing factor. Shifting wind patterns and expanding desertification are increasing the frequency of dust storms, especially in regions such as North Africa, the Middle East, and South Asia. These storms can darken skies across hundreds of kilometers, temporarily slashing solar yields. Even after the skies clear, deposited dust on panel surfaces can further reduce efficiency until cleaned, a costly and resource-intensive process in water-scarce regions.

Human activity contributes as well. In parts of the developing world where coal remains a primary fuel, aerosol pollution from power plants and industry already suppresses solar production. While a shift toward cleaner energy sources may improve air quality in the long run, in the short term climate-driven interactions between heat, stagnating air masses, and pollution can make haze events more frequent and persistent.

The unpredictability of aerosols makes them especially difficult to model. Unlike temperature or cloud cover, which can be forecast with increasing accuracy, aerosol events are often sudden and localized. For grid operators, this translates into unexpected dips in production, requiring quick adjustments to maintain stability. For solar investors, it adds another layer of uncertainty to long-term yield projections.

In short, the quality of the air above a solar farm is just as important as the amount of sunshine it receives, and in a warming world marked by more fires, more dust, and shifting pollution patterns, this invisible factor is becoming an increasingly visible risk.

The bigger picture

Taken individually, each of these factors — extreme weather, rising temperatures, shifting seasonal patterns, and aerosol disruptions — poses a serious challenge to solar energy. Together, they amount to a systemic shift in how reliable and predictable solar production can be in a changing climate. The core appeal of solar has always been its apparent certainty: the sun rises every day, and with long historical records, output seemed easier to forecast than wind or hydropower. Climate change is eroding that certainty.

This does not mean solar is becoming unviable, far from it. Solar remains one of the cleanest, cheapest, and most scalable sources of renewable power available. But the conditions under which it operates are evolving, and so too must our approach to planning and managing it. Relying solely on past irradiance records or assuming smooth seasonal cycles is no longer sufficient. Instead, operators, policymakers, and researchers will need to integrate climate projections, advanced weather modeling, and real-time monitoring into their planning frameworks.

Adaptation will take multiple forms. On the technical side, this includes developing panels with lower temperature sensitivity, integrating automated cleaning systems to manage dust, and designing mounting structures resilient to stronger winds and hail. On the systemic side, grid planners will need to account for sharper fluctuations, ensuring flexible backup capacity, energy storage, and stronger interconnections between regions. Hybrid renewable systems — where solar is combined with wind, hydro, or geothermal — will also play an increasingly important role in smoothing out volatility.

For households and communities, these changes underscore the value of resilience. Battery storage, smart home energy management, and cooperative grid models can help buffer against the dips caused by extreme weather or haze events. At the national and international level, coordinated climate action to reduce emissions remains the only long-term safeguard against ever-worsening disruptions.

In short, solar power is still central to the clean energy transition, but it is no longer the simple, predictable resource it once seemed. Climate change is rewriting the rules, and our energy systems must adapt accordingly if we are to build a future that is not only sustainable but also resilient.

One way forward is smarter forecasting. That’s where my Fusion Forecast comes in. Traditional methods — such as Global Tilted Irradiance (GTI) models — rely on physical simulations of sunlight under clear-sky and weather conditions. AI models, on the other hand, learn from historical correlations between weather data and actual solar production. Both have strengths and weaknesses: GTI is grounded in physics but rigid in extreme or unusual weather; AI adapts to local patterns but can overfit or drift when climate dynamics shift.

The Fusion Forecast combines the two. It runs both GTI and AI forecasts in parallel, then dynamically blends them using a weighting scheme that adapts based on recent accuracy. If, for example, the AI model is currently tracking actual production more closely than GTI, its influence increases; if GTI proves more stable during unusual events, the balance shifts back. A correction term ensures that residual biases are minimized over time.