As the Earth rotates, each location on its surface is periodically exposed to incoming sunlight. For example, over London at the beginning of September, the intensity of incoming sunlight ranges from zero overnight, when the sun is below the horizon, to almost 1000 W m–2 at noon, when the sun is highest in the sky (Fig. 1).
Earth’s atmosphere and surface respond to this repeating daily cycle of incoming sunlight in ways that can change the amount of energy that is emitted or reflected back to space. For example, the increased amount of sunlight in the afternoon can heat up the surface and cause more thermal energy to be emitted to space. Meanwhile, the surface heating can also cause the air near the surface to warm up and rise to form clouds that will, in turn, reflect sunlight back to space. The resulting daily cycle of the top-of-atmosphere outgoing energy flows is therefore intricate and represents one of the most fundamental cycles of our weather and climate. It is essential that we can properly represent the physical processes controlling this daily variability to obtain accurate weather and climate forecasts. However, the daily variability in Earth’s outgoing energy flows is not currently well observed across the entire globe, and current weather and climate models can struggle to reproduce realistic daily variability, highlighting a lack of understanding.
To improve understanding, dominant patterns of the daily cycle in outgoing energy flows are extracted from Met Office model output using a mathematical technique known as “principal component analysis”.
The daily cycle of reflected sunlight is found to be dominated by the height of the sun in the sky, or the “solar zenith” angle, because the atmosphere and surface are more reflective when the sun is low in the sky. There is a lesser importance from low-level clouds over the ocean, known as “marine stratocumulus” clouds, which burn off during the afternoon, reducing the amount of reflected sunlight, and tall and thick clouds, known as “deep convective” clouds, which develop later in the afternoon over land and increase the amount of reflected sunlight. On the other hand, the daily cycle of emitted thermal energy is dominated by surface heating, which increases the emitted energy at noon, but also by deep convective clouds that have very high and cold tops, reducing the emitted energy later in the afternoon. These dominant processes controlling the daily cycle of Earth’s outgoing energy flows and their relative importance (summarised in Fig. 2) have not been revealed previously at the global scale.
The physical processes discussed above are consistent with the daily cycle in other relevant model variables such as the surface temperature and cloud amount, further supporting the findings. Interestingly, a time lag is identified in the response of the emitted thermal energy to cloud variations, which is thought to be related to changes in the humidity of the upper atmosphere once the clouds evaporate.
The new results highlight an important gap in the current observing system, which can be utilized to evaluate and improve deficiencies in weather and climate models.
Gristey, J. J., Chiu, J. C., Gurney, R. J., Morcrette, C. J., Hill, P. G., Russell, J. E., and Brindley, H. E.: Insights into the diurnal cycle of global Earth outgoing radiation using a numerical weather prediction model, Atmos. Chem. Phys., 18, 5129-5145, https://doi.org/10.5194/acp-18-5129-2018, 2018.
Gristey, J. J., J. C. Chiu, R. J. Gurney, S.-C. Han, and C. J. Morcrette (2017), Determination of global Earth outgoing radiation at high temporal resolution using a theoretical constellation of satellites, J. Geophys. Res. Atmos., 122, doi:10.1002/2016JD025514.
The surface of our planet has warmed at an unprecedented rate since the mid-19th century and there is no sign that the rate of warming is slowing down. The last three decades have all been successively warmer than any preceding decade since 1850, and 16 of the 17 warmest years on record have all occurred since 2001. The latest science now tells us that it is extremely likely that human influence has been the dominant cause of the observed warming1, mainly due to the release of carbon dioxide and other greenhouse gases into our atmosphere. These greenhouse gases trap heat energy that would otherwise escape to space, which disrupts the balance of energy flows at the top of the atmosphere (Fig. 1). The current value of the resulting energy imbalance is approximately 0.6 W m–2, which is more than 17 times larger than all of the energy consumed by humans2! In fact, observing the changes in these energy flows at the top of the atmosphere can help us to gauge how much the Earth is likely to warm in the future and, perhaps more importantly, observations with sufficient spatial coverage, frequency and accuracy can help us to understand the processes that are causing this warming.
Observations of energy flows at the top of the atmosphere have traditionally been made by large and expensive satellites that may be similar in size to a large car3, making it impractical to launch multiple satellites at once. Although such observations have led to many advancements in climate science, the fundamental sampling restrictions from a limited number of satellites makes it impossible to fully resolve the variability in the energy flows at the top of atmosphere. Only recently, due to advancements in small satellite technology and sensor miniaturisation, has a novel, viable and sustainable sampling strategy from a constellation of satellites become possible. Importantly, a constellation of small satellites (Fig. 2a), each the size of a shoe-box (Fig. 2b), could provide both the spatial coverage and frequency of sampling to properly resolve the top of atmosphere energy flows for the first time. Despite the promise of the constellation approach, its scientific potential for measuring energy flows at the top of the atmosphere has not been fully explored.
To explore this potential, several experiments have been performed that simulate measurements from the theoretical constellation of satellites shown in Fig 2a. The results show that just 1 hour of measurements can be used to reconstruct accurate global maps of reflected sunlight and emitted heat energy (Fig. 3). These maps are reconstructed using a series of mathematical functions known as “spherical harmonics”, which extract the information from overlapping samples to enhance the spatial resolution by around a factor of 6 when compared with individual measurement footprints. After producing these maps every hour during one day, the uncertainty in the global-average hourly energy flows is 0.16 ± 0.45 W m–2 for reflected sunlight and 0.13 ± 0.15 W m–2 for emitted heat energy. Observations with these uncertainties would be capable of determining the sign of the 0.6 W m–2 energy imbalance directly from space4, even at very short timescales.
Also investigated are potential issues that could restrict similar uncertainties being achieved in reality such as instrument calibration and a reduced number of satellites due to limited resources. Not surprisingly, the success of the approach will rely on calibration that ensures low systematic instrument biases, and on a sufficient number of satellites that ensures dense hourly sampling of the globe. Development and demonstration of miniaturised satellites and sensors is currently underway to ensure these criteria are met. Provided good calibration and sufficient satellites, this study demonstrates that the constellation concept would enable an unprecedented sampling capability and has a clear potential for improving observations of Earth’s energy flows.
This work was supported by the NERC SCENARIO DTP grant NE/L002566/1 and co-sponsored by the Met Office.
2 Total energy consumed by humans in 2014 was 13805 Mtoe = 160552.15 TWh. This is an average power consumption of 160552.15 TWh / 8760 hours in a year = 18.33 TW
Rate of energy imbalance per square metre at top of atmosphere is = 0.6 W m–2. Surface area of “top of atmosphere” at 80 km is 4 * pi * ((6371+80)*103 m)2 = 5.23*1014 m2. Rate of energy imbalance for entire Earth = 0.6 W m–2 * 5.23*1014 m2 = 3.14*1014 W = 314 TW
Multiples of energy consumed by humans = 314 TW / 18.33 TW = 17
3 The satellites currently carrying instruments that observe the top of atmosphere energy flows (eg. MeteoSat 8, Aqua) will typically also be hosting a suite of other instruments, which adds to the size of the satellite. However, even the individual instruments are still much larger that the satellite shown in Fig. 2b.
4 Currently, the single most accurate way to determine the top-of-atmosphere energy imbalance is to infer it from changes in ocean heat uptake. The reasoning is that the oceans contain over 90% of the heat capacity of the climate system, so it is assumed on multi-year time scales that excess energy accumulating at the top of the atmosphere goes into heating the oceans. The stated value of 0.6 W m–2 is calculated from a combination of ocean heat uptake and satellite observations.
Allan et al. (2014), Changes in global net radiative imbalance 1985–2012, Geophys. Res. Lett., 41, 5588–5597, doi:10.1002/2014GL060962.
Barnhart et al. (2009), Satellite miniaturization techniques for space sensor networks, Journal of Spacecraft and Rockets, 46(2), 469–472, doi:10.2514/1.41639.
Swartz et al. (2016), The Radiometer Assessment using Vertically Aligned Nanotubes (RAVAN) CubeSat Mission: A Pathfinder for a New Measurement of Earth’s Radiation Budget. Proceedings of the AIAA/USU Conference on Small Satellites, SSC16-XII-03