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Volcanic Aerosols: A Threat to Solar Production that Historical Satellite Data Doesn’t See

March 22, 2024

Introduction

During a major volcanic eruption, powerful volcanoes may launch sulfur gas high into the stratosphere, where it can form long-lasting aerosols persisting on time scales from months to years. These clouds of aerosols then diffuse into a layer that can cover the globe. Studies have shown that this process can result in a severe reduction of surface solar irradiance and reduce clear sky irradiance by as much as 13 percent (Robock 2000), with significant implications for solar PV production [Robock 2000, Bluth 1992, Hay and Darby 1984]. 

Obviously, the threat of these months to years-long volcano-induced periods of low solar irradiance presents a major risk to solar investor profitability and regional power grid reliability. However, these risks aren’t typically considered when investors and planners calculate expected production variability from new (or existing) utility-scale solar sites–primarily because conventional risk assessment approaches rely on a limited sample of historical irradiance data that coincidentally corresponds to a time period (beginning in 1998) without any of the major volcanic events that have affected North America.

A Limited Historical Record of Irradiance Data 

Due to the dearth of high-quality ground station solar irradiation measurements, the solar industry has come to rely on remote sensing data from geostationary satellite missions. Irradiance data from geostationary satellites is available starting in 1998. The resulting tradeoff between data quality and data breadth caused by this exclusive reliance on satellite data for production risk assessment evinces itself as a major gap in understanding just how low solar production can be if and when the next planetary scale volcanic eruption occurs. 

To put volcanic eruption risks to solar production into context, we estimate (as shown below) that volcanic aerosols can produce annual solar irradiance deficits 5 standard deviations below the satellite record estimate. In other words, using data from 1998-2023 to estimate an annual solar irradiance probability distribution at a solar site (as is commonly done today), a major volcanic eruption could lead to a year of observed solar irradiance 5 standard deviations lower than the mean expected value. Naïvely, a 5-sigma deviation is extremely unlikely: for example, if we assumed that annual irradiance was normally distributed, a 5-sigma event should happen on average 1 in 3.5 million years.

Yet we know that these risks are much more common–two eruption events occurred between 1982 and 1991–meaning that deriving a measure of irradiance variability using only the 1998-forward satellite record probably underestimates volcano risk. The industry, in effect, may be prioritizing short timescale accuracy at the expense of long-term risk assessment.

El Chichón and Pinatubo

The last fifty years have seen two eruptions with large scale persistent impacts to irradiance. The eruption of El Chichón in 1982 accelerated roughly 7 million tons of sulfur dioxide to atmospheric heights of over 22 kilometers. The eruption of Mt. Pinatubo a mere 9 years later resulted in a 35 km high plume of 20 million tons of sulfur dioxide (Bluth et al. 1992). Both plumes became entrained in the atmosphere, reacted with water vapor, and spread out to form reflective bands of sulphuric acid aerosols that encircled the globe within roughly three weeks and persisted for up to 3 years after their respective eruptions.1

Although satellite data is not available before 1998, the Mauna Loa observatory in Hawaii captured the impact of these global aerosol blankets on solar irradiance through measurements of the apparent transmission of the atmosphere during hours with clear skies. The data, presented in Figure 1, shows clear sky irradiance dropping by more than 13% due to the impact of El Chichón in 1982 and 11% due to the impact of  Pinatubo in 1991.

Figure 1: Apparent transmission (an estimate of the fraction of solar irradiance that is able to pass through the atmosphere during clear hours) measured at Mauna Loa Observatory. Figure from the Global Monitoring Laboratory (https://gml.noaa.gov/grad/mloapt.html)

To understand how these reductions in irradiance impacted the solar resource in the US, we aggregated surface solar irradiance from the ERA52 dataset in the southwestern states (CA, UT, CO, NV, AZ, NM) from 1950-2023. We found that the 4 years with the lowest mean irradiance on record followed these eruptions. When compared to the period since 1998, the year following El Chichón had an irradiance deviation of -5.3 𝝈; the year following Pinatubo had an irradiance deviation of -3.8 𝝈.

10 Lowest Surface Solar Irradiance Years: ERA5 1950-2023 (Avg of CA, UT, CO, NV, AZ, NM)
Rank Year Mean Annual GHI (W/m2) Mean Annual GHI 1998-2023 (W/m2) 𝝈1998-2023 Notes
1 1983 221.5 234.9 -5.3 Year after El Chichón
2 1982 225.4 234.9 -3.8 El Chichón
3 1992 225.4 234.9 -3.8 Year after Pinatubo
4 1984 227.0 234.9 -3.3 2 years after El Chichón
5 1986 227.7 234.9 -2.9
6 1981 228.6 234.9 -2.5
7 1957 229.0 234.9 -2.3
8 1991 229.6 234.9 -2.1 Pinatubo
9 1987 229.9 234.9 -2.0
10 1998 230.3 234.9 -1.8
Table 1: 10 Years with the lowest mean annual GHI in the southwestern US during 1950-2023. 𝝈1998-2023 is the number of standard deviations removed from years in which satellite data is available (1998-2023). Years impacted by El Chichón are shaded in red, years impacted by Pinatubo are shaded in orange.

To visualize these years within the full ERA5 date range, Figure 2 plots the time series of regional annual average solar irradiance from 1950-2023. Again, we see that the years following El Chichón and Pinatubo are the lowest, appearing as outliers compared to the 1998-forward satellite record range (consistent with the 3+ sigma measurements above).

Figure 2: Mean annual global horizontal irradiance (GHI) averaged over the southwestern United States. Years with volcanic eruptions are indicated by vertical lines.

Data Challenges and Future Risk

As seen above, volcanic eruptions can be an enduring hazard to solar production in the United States. However, because historic eruptions are not captured by the satellite record, they are often not accounted for during due diligence or planning exercises. Moreover, as the solar PV industry has not existed at scale for long enough to have meaningful first hand experience with volcanic eruption related deficits, empirical or even anecdotal evidence of their effects is rare.   

Clearly, solar production risk assessments using only historical data since 1998 are not incorporating these relatively rare but impactful events. Yet the risk of the next major eruption over the next decade may be greater than the industry realizes. Estimates of major eruption frequency (Rougier et al. 2018, Sheldrake and Caricchi 2017, Pyle 1995), though imprecise, suggest that volcanoes at least as severe as Pinatubo and El Chichón may occur with a frequency of roughly 1 in 51 years (Sheldrake and Caricchi 2017)–corresponding to a 33% chance of occurrence during a 20 year solar project life cycle.

Sunairio Irradiance Simulations Reveal Long Tails Consistent with Volcanic Events

Overcoming the limitations of a small sample set when estimating risk is a key benefit of employing stochastic simulation methods. While grounded in high-quality satellite-based irradiance data, Sunairio’s stochastic climate simulations generate a wide range of realistic weather scenarios that can extrapolate beyond the limitations of a restricted date range, using statistical and machine learning methods to infer complex spatio-temporal relationships between weather variables, locations, and timepoints to create a broad data set from which to evaluate risk. Therefore, Sunairio’s simulations are both representative of local weather down to a few kilometers and useful for characterizing variability–including extreme events.

To demonstrate how Sunairio simulations can “see” weather risk beyond a limited historical record, we simulated 1,000 scenarios of hourly weather for 2024 at a location just outside of Albuquerque, New Mexico–using satellite-based irradiance data from 1998-2023. Figure 3 plots the annual average GHI of each of our simulations compared to two distributions from ERA5: the 1998-2023 period (satellite data period), and the full 1950-2023 period of record. 

In the left plot of Figure 3 we see that the Sunairio simulations show a left skew (risk of low solar irradiance) that notably isn’t present in the 1998-2023 ERA5 distribution–but is present in the right plot of historical data since 1950, overlapping with the occurrence of major volcano years. Sunairio simulations, in other words, replicate the true tail of the historic distribution (including years with volcanic activity) which isn’t seen in the limited satellite data period.

Figure 3: Mean Annual GHI over 1,000 Sunairio simulations compared to mean annual GHI distributions derived from ERA5 for A) 1998-2023 (left) and B) 1950-2023 (right). Years impacted by the eruptions of El Chichón and Pinatubo are indicated by hatches.

Conclusions

In this case study we showed that:

  1. Major volcanic eruptions such as El Chichón (1982) and Pinatubo (1991) can significantly reduce surface solar radiation by creating a planetary-scale band of sulphuric acid aerosols that persist in the atmosphere for years. The effect is well documented by Moana Loa station observations.

  2. Traditional solar PV production risk estimates do not incorporate the risk of volcanic events because they derive annual risk estimates using satellite-based irradiance data (which starts in 1998).

  3. The signatures of El Chichón and Pinatubo eruptions are apparent in ERA5 reanalysis data: the four lowest mean annual irradiance years (between 1950 and 2023) are either eruption years or years immediately following those eruptions.

  4. Using the 1998-2023 satellite data period as the basis for risk estimates, volcanic eruption years appear to be 3- to 5-sigma events (i.e. extraordinarily unlikely)–contradicting the research on volcanic eruption frequency.

  5. Sunairio’s simulations replicate low-irradiance years at a frequency consistent with the historic record and reanalysis estimates. Using Sunairio simulations of Albuquerque, NM for 2024, the likelihood of a year having mean annual GHI equivalent to the 1983 El Chichón year is roughly 2.3%.

Notes

  1. Not all eruptions disrupt the climate on a planetary scale. The eruption of Mt. St. Helens in 1980 and, more recently, the eruption of Hunga Tonga–Hunga Haʻapai in 2022 both produced large explosions but failed to propel large quantities of SO2 into the stratosphere. Therefore, although they had catastrophic impacts on surrounding areas, the plume of aerosols were able to settle to the earth within a few weeks. ↩︎
  2. Although ERA5 data is less accurate than satellite data, these errors are most extreme during cloudy conditions (Urraca 2018). Looking at states in the southwest (which have fewer cloudy hours) allows us to partially mitigate these errors. ↩︎

Citations

Bluth, G. J. S., et al. (1992) Global tracking of the SO2 clouds from the June 1991 Mount Pinatubo eruptions, Geophys. Res. Lett.

Hay, J. E. and Darby, R. (1984) El Chichón – influence on aerosol optical depth and direct, diffuse and total solar irradiances at Vancouver, B.C., Atmosphere-Ocean, 22:3, 354-368, DOI: 10.1080/07055900.1984.9649204

Pyle, D. M. (1995) Mass and Energy Budgets of explosive volcanic eruptions. Geophysical Research Letters; 22, 5 563-566.

Robock, A. (2000) Volcanic Eruptions and Climate. Reviews of Geophysics.

Rougier, J., et al. (2017) The global magnitude–frequency relationship for large explosive volcanic eruptions. Earth Planet. Sci. Lett.

Sheldrake T., and Caricchi L. (2017) Regional variability in the frequency and magnitude of large explosive volcanic eruptions. Geology; 45 (2): 111–114. doi: https://doi.org/10.1130/G38372.1

Urraca, R. et al. (2018) Evaluation of global horizontal irradiance estimates from ERA5 and COSMO-REA6 reanalyses using ground and satellite-based data. Solar Energy.

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