Richard Willoughby,
Summary
This article examines how Earth–Sun geometry and solar variability change top-of-atmosphere (ToA) sunlight by latitude and season, and how those changes can propagate through convection, clouds, and poleward heat transport to shape regional climate trends. Daily insolation calculated across latitudes over 1200 years is compared with satellite-era observations to assess whether the geographic pattern of observed changes is consistent with solar-forced changes in the climate system.
Poleward heat transport from the tropics is described and related to why ocean heat content (OHC) changes tend to concentrate in the main condensation and storm-track zones of each hemisphere. The intent is to connect latitudinal differences in solar forcing to differences in advection and heat storage.
A simple matrix of climate zones and seasons is then used as an organising framework for comparing year-to-year and century-scale changes in seasonal sunlight and relating those changes to observed shifts in temperature, clouds, and heat uptake.
Introduction
Throughout this article, solar electromagnetic radiation per unit area (solar flux) is expressed in W/m² and refers to top-of-atmosphere (ToA) daily-mean insolation. Over timescales longer than a day, ToA insolation at a given latitude and time of year is set by (i) Earth–Sun distance, (ii) solar declination (the Sun’s angular position relative to Earth’s equatorial plane), and (iii) solar output. These inputs are sufficient to compute ToA daily-mean insolation at any latitude for any day of the year. The sections that follow first quantify how insolation varies by latitude and time, then relate those patterns to reflection in the tropics, poleward heat transport, OHC, and mid-latitude temperature response.
NASA/JPL’s HORIZONS system provides precise ephemerides that can be used to calculate Sun–Earth distance and solar declination for any date, which are the key astronomical inputs used here to compute daily-mean ToA insolation by latitude. The cyclic change in solar constant uses the observed correlation between divergence of the Sun velocity from average and the solar activity.
Daily Average Solar Flux across Latitudes and Time
The charts in this section show how the maximum daily average flux has varied over time for selected latitudes. Chart 1 provides trends for the Northern Hemisphere (NH) while Chart 2 has trends for the Southern Hemisphere (SH).
For the selected latitudes in the NH, 45N has the highest maximum daily average near 474W/m² that has little change over the 1200 years plotted. By contrast, 10N has the lowest maximum daily average and shows a distinct inflection around 1200AD.
For the same selected latitudes in the SH, 75S exhibits the highest maximum daily average solar flux and has declined over the entire period from 538W/m² in 1000AD. 10S shows a barely visible minimum inflection point around 1200AD. 15S is almost flat trend while 30S and 45S have slight down trends.
Note that there is no symmetry between the NH and SH. The significant differences are better appreciated by expanding the scale for selected north and south latitudes. Chart 3 compares 45N and 45S.
Over the 1200 years, 45S declines almost 4W/m² from 502W/m² while 45N exhibits a shallow minimum of 473.8W/m² in 1640 while changing less than 1W/m² over the entire 1200 years. Also note that the scales have the same range but are offset by 25W/m². In the present era, the maximum daily average solar flux in the SH is considerably more intense than the solar flux in the NH.
The next step is to consider how much of this ToA insolation is actually absorbed by the ocean–atmosphere system versus rejected back to space, particularly in the tropics where convection and associated clouds strongly regulate surface temperature.
Rejected ToA Solar Flux
A significant portion of incoming ToA solar flux is not thermalised; it is reflected by clouds and by high-albedo surfaces (ice and snow). This is especially important in the tropics, where deep convection and associated cloud fields act as a strong regulator of sea-surface temperature (SST), which rarely sustains values much above ~30°C in the warmest regions. Chart 4 examines this regulation by plotting mean ocean surface temperature against available ToA solar flux across a 1°×1° global grid.
It is evident that the temperature falls with rising ToA solar flux above 425W/m². Chart 5 zooms in on the tropical ocean where solar flux is above 425W/m² showing all grid points as well as a line of best fit.
The temperature exhibits a declining value with increasing solar flux.
Chart 6 plots all-sky reflected shortwave flux against available ToA solar flux for a representative day (in week 5, 2026), matched to the SST snapshot used above.
The reflected solar flux remains near constant until the solar flux is above 375W/m² then reflection increases rapidly to a peak approaching 50% of the available solar before reducing somewhat.
Chart 7 combines the calculated average daily solar flux across latitudes and the atmospheric thermo-regulating process to arrive at an estimate of the potential heat rejected through short wave reflection in the tropics of the NH each year.
This annual estimate is an area average based on a threshold approach: for each hemisphere, shortwave “rejection” is counted only on days and at latitudes where daily-mean ToA flux exceeds an assumed convection/reflectance threshold of 425W/m². Here, the thresholds are guided by (i) warm-pool buoy observations (SST near 28–30°C where persistent convection is common) and (ii) typical tropical reflected shortwave values (often exceeding ~80 W/m² under convective cloud regimes). Latitudes poleward of 30° are excluded because these regions rarely sustain SSTs high enough for persistent cyclic deep convection.
Based on this estimate, the NH had its lowest heat rejection around 1600AD and is now on a slight increasing trend. By contrast, the trend for the SH shown in Chart 8 has been steadily downward since before 1000AD without an inflection observed in the NH.
Given tropical cyclones require an environment that is potentially unstable due to moist convection (i.e., able to support deep convection) to spin up (Gray, 1968; NOAA, n.d.), it is probable that cyclone activity in both hemispheres was higher in 1000AD than present (e.g., Mann, Woodruff, Donnelly, & Zhang, 2009). Observed records for the Australian region indicate a decline in total tropical cyclone numbers since the start of reliable satellite-era observations, with large modulation by ENSO (Nicholls, Landsea, & Gill, 1998; Dowdy, 2014).
Heat Transport Tropics to Poles
Convective towers that form over tropical warm pools are the primary engines of the global circulation. They create the latitudinal atmospheric pressure gradient in each hemisphere that transports heat from the tropics toward the poles. This heat transport has a temporal aspect as well as latitudinal due to greater annual variation in solar flux at higher latitudes. Chart 9 combines the latitudinal and temporal aspects by considering the difference between the maximum daily average at 15 degrees and the minimum at 45 degrees for both hemispheres.
It is apparent that the NH is in a strong upward trend after bottoming around 1300AD while the SH is declining after peaking around 1000AD, albeit SH has greater difference than the NH.
The CERES and ARGO projects have been providing high resolution ToA radiation and ocean heat (OHC) data for most of the 21st century. Chart 10 is based on CERES Net radiation data to show the cumulative picture of heat retained or lost across the latitudes for the past 21 years.
The tropics-to-pole heat transport calculated for the SH (4044 ZJ) is higher than the NH (3856 ZJ), and the SH has retained more (320 ZJ) compared with the NH (117 ZJ). This asymmetry is consistent with the SH receiving higher tropical insolation in the present era.
The ARGO ocean heat data is shown in Chart 11 also across latitudes.
The two hemispheres are quite different with the NH showing distinct peaks in the tropics and in the advection zone north of 30N. The SH has one high, distinct peak at 45S, in the middle of the high advection zone. Also the SH has retained more ocean heat than the NH.
Chart 12 compares (i) accumulated monthly net radiation (CERES) and (ii) December OHC (Argo/derived OHC product) for each hemisphere across the Argo era. Given the observing systems and accounting are consistent, multi-year changes in net radiation should broadly track multi-year changes in ocean heat uptake (recognising that heat can also be stored in the atmosphere, land, and cryosphere, and that timing lags are expected).
The NH series track closely, whereas the SH series diverge after 2015. The divergence is clearer in Chart 12A, which compares year-end (December) accumulations for both net radiation and OHC.
The divergence at the end of 2025 was 140ZJ.
The annual change in OHC for both hemispheres per Chart 13 exhibit opposite trends.
The annual change in the SH is approaching zero. While the change in the NH is continuing to accelerate. Allowing for substantial time lags, both these trends are consistent with the changes in solar forcing of advection.
Mid Latitude Temperature Response to Solar Forcing
It is evident that the solar flux is not changing symmetrically across the two hemispheres. It is also apparent that the thermal response of the two hemispheres is quite different. Charts 14 and 15 show the monthly temperature for the mid latitudes in the two hemispheres from 2000 to 2025. The data is from the Berkeley global gridded 2m air temperature database.
Both mid-latitude bands exhibit an upward trend over 2000–2025, but the NH warms faster than the SH over this interval. If recent trends persist, the NH mid-latitudes will become consistently warmer, on average, than the SH mid-latitudes from 2026.
Both temperature records are highly correlated to solar flux but the response of the SH is slower and only a fifth of the response of the NH. Chart 16 shows X-Y plots for monthly temperature against 30-day daily average solar flux with NH lagged 36 days and SH lagged 61 days.
Year-to-Year Changes in Solar Forcing
There are substantial changes in seasonal solar forcing from year-to-year. The changes in the tropics drive convection and have linkage to convective potential and cyclone activity. The thermo-regulation of the tropics limit the impact on temperature from solar forcing. Once ice forms on the surface at the poles, the thermal response to forcing is highly non-linear. By contrast, the mid latitudes show almost linear response to solar forcing per Chart 16 above. Accordingly, the variation in daily solar forcing in the mid latitudes from year-to-year gives insight into expected temperature change from year-to-year.
The following series of charts are selected samples to show how daily sunlight in one year varies relative to a chosen base year for 45N and 45S. The days are numbered from the September Equinox of the year prior to the year being considered and continue to near March Equinox of the following year. The vertical green line identifies the December Solstice, which occurs about a week before the start of the year being considered.
Year 2023 had the highest spring to summer solar flux in both hemispheres in recent history. The difference relative to 1944 is as much as 3W/m² on the days of greatest divergence.
Considering 2026 relative to 2023, the spring to summer sunlight in both hemispheres is down by as much as 2W/m². As a matter of fact, 2027 mid latitude insolation in both hemispheres is not much different to 2023.
The next year that will have almost identical mid-latitude sunlight to 2023 is 2052. Marginally closer to 2023 than 2027.
Discussion
This discussion summarises what the charts show and then evaluates whether the combined pattern—insolation changes, tropical reflection behaviour, and hemispheric differences in advection and heat uptake—forms a coherent explanation for the observed trends highlighted above.
Variation in insolation – The analysis extends far enough back to identify inflection points in the precession-driven evolution of seasonal and latitudinal insolation. The charts show clear hemispheric and latitudinal asymmetries: maxima and minima do not occur at the same times in the NH and SH, and different latitudes exhibit different long-term tendencies. For example, the maximum daily solar flux at 45N reaches a shallow minimum around 1640 AD and then rises slowly, whereas 45S peaks around ~1000 AD and then declines. Low latitudes (e.g., ~10N) show an inflection near ~1200 AD and then increase by several W/m² over subsequent centuries. In addition to these multi-century trends, the year-to-year changes in seasonal insolation shown in the later charts are large enough (order 1–3 W/m² at some times of year) to influence interannual variability in circulation and temperature where the system response is close to linear.
Heat rejected (shortwave reflection) – Charts 4–6 indicate a regime change in the tropical ocean once daily-mean ToA flux is high enough that SST approaches the warm-pool ceiling: convection becomes persistent and all-sky reflected shortwave increases rapidly with further increases in ToA flux. In this framework, additional ToA forcing above a threshold contributes more to reflection and circulation changes than to further SST increase. Applying the threshold method in Charts 7–8 yields a higher estimated shortwave “rejection” in the NH tropics than in the SH tropics in the present era, despite higher ToA flux in parts of the SH. If the thresholds are reasonable, changes in this rejected-energy term would be expected to correlate with changes in convective potential and therefore relevant to cyclone energy.
Net radiation and OHC mismatch – Earth’s energy imbalance cannot be measured directly; rather it is inferred from satellite radiation products and checked for consistency against changes in ocean heat uptake. In Charts 12–13 the NH net-radiation accumulation and NH OHC track closely, while the SH series diverge after about 2015, reaching an end‑2025 cumulative difference of ~140 ZJ. Interpreting such a mismatch requires considering a number of possibilities: it can arise from observing-system uncertainty, from timing/lag differences between hemispheres, and/or from heat being stored outside the 0–2000 m ocean layer used for OHC (e.g., deeper ocean, cryosphere, land, and atmosphere). The remainder of this discussion point therefore considers candidate terms and whether their magnitude is plausibly large enough to explain the observed divergence starting with Chart 17 and atmospheric energy accumulation.
The calculated atmospheric-moisture contribution of ~4.8 ZJ over the decade is only a small fraction of the ~140 ZJ divergence, so it cannot resolve the mismatch on its own. It is nonetheless noteworthy that the moisture increase peaks near ~10N, where the long‑term maximum daily solar flux has been rising the most
. The mid-latitude moisture maxima are also qualitatively consistent with enhanced poleward transport in both hemispheres.
Other possibilities for Net radiation rising faster than OHC in the SH include:
- Latent heat of ice melt in the SH but it is estimated at less than 1ZJ in the past decade.
- There are some glaciers in the SH that are expanding but the heat associated with this is less than 1ZJ.
- There has been an increase of biomass globally but, while the NH has gained significantly, the evidence does not support substantial increase in biomass in the SH including the oceans.
- There has been heat transfer from the SH to the NH but the OHC and Net radiation in the NH currently show close balance rather than a deficit requiring an increase in heat transfer from the SH.
- A potential source of error is that the basis for the 2005 to 2015 alignment was flawed due to the high thermal lags in the climate system. Essentially the system is never static; rather always changing as it must due to changing solar forcing.
Thermal response – In this framework, tropical SST responds weakly to additional ToA forcing once deep convection becomes persistent, because reflected shortwave and latent-heat export increase sharply. By contrast, the mid-latitudes in Charts 14–16 show an approximately linear relationship between monthly temperature and recent (30‑day) mean insolation, with lagged responses of ~36 days (NH) and ~61 days (SH) in the illustrative fits shown. The smaller SH amplitude and longer lag are consistent with a greater ocean fraction and larger effective heat capacity in the SH mid-latitudes.
Conclusions
The daily-maximum ToA insolation series show hemispheric asymmetry over the past millennium. In the present era, maximum daily insolation in the SH is higher than at the corresponding NH latitudes, but the long-term trends differ: several SH latitudes (e.g., 45S) have been declining since around ~1000 AD, whereas several NH mid-latitudes (e.g., 45N) have been slowly increasing since reaching a minimum around ~1640 AD. In the low latitudes, an inflection around ~1200 AD is followed by a gradual increase in maximum daily insolation.
Using the threshold method introduced in the “Rejected ToA Solar Flux” section, the analysis implies that long-term changes in the frequency and intensity of tropical convective cloud regimes modulates how much additional ToA forcing is reflected rather than absorbed. In this framing, a decline in the SH maximum daily insolation south of ~10S reduces convective “rejection” there, while the NH shows a smaller change but is now increasing from its minimum. Given convective potential is a prerequisite for cyclones, this is consistent with observed reduction in SH cyclone relative to earlier periods. The NH cyclone intensity being higher in 1000AD than present is consistent with more heat being rejected in that period.
In the satellite era, the mid-latitude temperature series used here show a strong, near-linear relationship to recent insolation when an appropriate lag is applied, consistent with a relatively direct radiative forcing response in these bands. The same mid-latitude temperatures are also influenced by changes in advection, which can shift the seasonal timing and the geographic distribution of warming. In this framework, changes in tropical insolation and convection affect poleward moisture and heat transport, which can amplify or dampen local radiative forcing responses depending on season and hemisphere.
Many climate models have persistent biases in tropical convection, clouds, and the representation of warm-pool processes, and these biases affect simulated trends in regions where SST is strongly regulated by convection (including parts of the tropical west Pacific). Chart 18 is presented here as an example of a regime where observed SST is constrained near the warm-pool ceiling, highlighting why correctly representing convective cloud feedbacks matters for attribution and projection.
This limitation means that projections for tropical warm-pool regions (and for circulation responses tied to those regions) should be interpreted cautiously, and model evaluation should emphasise observed constraints on convection, cloud reflectance, and heat export.
The long-term decline in maximum daily insolation at high southern latitudes is consistent with the presence of cooling trends in regions south of ~55S during the satellite era (Kang et al., 2023), and with documented multi-decadal cooling over parts of Antarctica such as the Antarctic Peninsula since the late 1990s (Turner et al., 2016).
Overall, the changing seasonal and latitudinal pattern of ToA insolation provides a coherent, physically motivated framework that is consistent with many of the hemispheric and regional asymmetries highlighted in this article (including differences in tropical reflection behaviour, poleward transport, and mid-latitude temperature response). On that basis, changes in solar intensity across latitudes and seasons are argued here to be a primary driver of the observed patterns and a useful guide for anticipating future regional trends. Broadly, the NH has strong upward temperature trends while the SH is cooling in the high latitudes that will eventually progress to the mid-latitudes as both maximum daily insolation and poleward advection decline.
The Author
Richard Willoughby is a retired electrical engineer having worked in the Australian mining and mineral processing industry for 30 years with roles in large scale operations, corporate R&D and mine development. A further ten years was spent in the global insurance industry as an engineering risk consultant where he developed an enduring interest in natural catastrophes and changing climate.
References and data sources
Datasets and tools used
- NASA Jet Propulsion Laboratory (JPL) Solar System Dynamics. HORIZONS System (online ephemeris and solar system data service). Documentation: HORIZONS System Manual, version 4.98d (21 Nov 2025). NASA/JPL-Caltech.
- NASA Langley Research Center. Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.x, monthly mean TOA flux products (Level 3b). Product description and data quality summaries available via CERES data portal.
- Loeb, N. G., Doelling, D. R., Kato, S., Su, W., Mlynczak, P. E., & Wilkins, J. C. (2024). Continuity in top-of-atmosphere Earth radiation budget observations. Journal of Climate, 37(23), 6093–6108.
- International Argo Program and national partners. Argo (global profiling float observations of temperature/salinity, upper 2000 m). General program documentation available via Argo data portals.
- NOAA National Centers for Environmental Information (NCEI). Global Ocean Heat Content Climate Data Record (CDR), 1955–present. Configuration Item ID: 01B-41. Dataset DOI: 10.7289/V53F4MVP.
- Riser, S. C., Freeland, H. J., Roemmich, D., et al. (2016). Fifteen years of ocean observations with the global Argo array. Nature Climate Change, 6, 145–153.
- Rohde, R. A., & Hausfather, Z. (2020). The Berkeley Earth land/ocean temperature record. Earth System Science Data, 12, 3469–3479.
- Berkeley Earth. Berkeley Earth temperature data: gridded and time-series products (land and land–ocean; includes gridded near-surface air temperature over land and sea surface temperature over oceans; see Berkeley Earth data portal for product notes and licensing).
Supporting scientific literature (selected)
- Ramanathan, V., & Collins, W. (1991). Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature, 351, 27–32.
- Fu, R., Del Genio, A. D., Rossow, W. B., & Liu, W. T. (1992). Cirrus-cloud thermostat for tropical sea surface temperatures tested using satellite data. Nature, 358, 394–397.
- Lau, K.-M., Sui, C.-H., Chou, M.-D., & Tao, W.-K. (1994). An inquiry into the cirrus-cloud thermostat effect for tropical sea surface temperature. Geophysical Research Letters, 21(12), 1157–1160.
- Tompkins, A. M. (2001). On the relationship between tropical convection and sea surface temperature. Journal of Climate, 14(5), 633–637.
- Sud, Y. C., Walker, G. K., & Lau, K.-M. (1999). Mechanisms regulating sea-surface temperatures and deep convection in the tropics. Geophysical Research Letters, 26(8), 1019–1022.
- Stephens, G. L., Shiro, K. A., Hakuba, M. Z., Takahashi, H., Pilewskie, J. A., Andrews, T., Stubenrauch, C. J., & Wu, L. (2024). Tropical deep convection, cloud feedbacks and climate sensitivity. Surveys in Geophysics, 45, 1903–1931.
- Johnson, G. C., Lyman, J. M., & Loeb, N. G. (2016). Improving estimates of Earth’s energy imbalance. Nature Climate Change, 6, 639–640.
- Loeb, N. G., Ham, S.-H., Allan, R. P., Thorsen, T. J., Meyssignac, B., Kato, S., Johnson, G. C., & Lyman, J. M. (2024). Observational assessment of changes in Earth’s energy imbalance since 2000. Surveys in Geophysics, 45, 1757–1783.
- Villalba-Pradas, A., & Tapiador, F. J. (2022). Empirical values and assumptions in the convection schemes of numerical models. Geoscientific Model Development, 15, 3447–3518.
- Martin, E. R., & Schumacher, C. (2012). The relationship between tropical warm pool precipitation, sea surface temperature, and large-scale vertical motion in IPCC AR4 models. Journal of the Atmospheric Sciences, 69(1), 185–194.
- Kim, H., Kang, S. M., Takahashi, K., Donohoe, A., & Pendergrass, A. G. (2021). Mechanisms of tropical precipitation biases in climate models. Climate Dynamics, 56, 17–27.
- Gray, W. M. (1968). Global view of the origin of tropical disturbances and storms. Monthly Weather Review, 96(10), 669–700.
- National Oceanic and Atmospheric Administration (NOAA). (n.d.). Tropical Cyclone Introduction (JetStream—Online School for Weather). NOAA.
- Nicholls, N., Landsea, C., & Gill, J. (1998). Recent trends in Australian region tropical cyclone activity. Meteorology and Atmospheric Physics, 65, 197–205.
- Dowdy, A. J. (2014). Long-term changes in Australian tropical cyclone numbers. Atmospheric Science Letters, 15, 292–298.
- Mann, M. E., Woodruff, J. D., Donnelly, J. P., & Zhang, Z. (2009). Atlantic hurricanes and climate over the past 1,500 years. Nature, 460, 880–883.
- Turner, J., Lu, H., White, I., King, J. C., Phillips, T., Hosking, J. S., Bracegirdle, T. J., Marshall, G. J., Mulvaney, R., & Deb, P. (2016). Absence of 21st century warming on Antarctic Peninsula consistent with natural variability. Nature, 535, 411–415.
- Kang, S. M., Yu, Y., Deser, C., Zhang, X., Kang, I.-S., Lee, S.-S., Rodgers, K. B., & Ceppi, P. (2023). Global impacts of recent Southern Ocean cooling. Proceedings of the National Academy of Sciences, 120(30), e2300881120.
