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.
Chart 18
The Commonwealth Scientific and Industrial Research Organisation (CSIRO)
GOOGLE AI says:
The tropical oceans rarely exceed surface temperatures of approximately 30°C–31°C (86°F–88°F)… the broad tropical ocean surface tends to cap itself around this temperature.
CSIRO’s model goes off the rails around 2050, so why should anyone give them the time of day?
Sort of like the sea level projections & acceleration from C-SLRG (UC Sea Level Research Group)
I have had a long-running dispute with CSIRO over this issue. The best I got back from them was that their ACCESS model is middle of the road. Their benchmark was the GISS model; not reality.
There are known knowns.
These are things we know that we know.
There are known unknowns.
That is to say, there are things that we know we don’t know.
But there are also unknown unknowns.
There are things we don’t know we don’t know.
Donald Rumsfeld
Rumsfeld didn’t continue with there are things that don’t add up.
Such as climate models that go off the rails
Claims that
warm water causes coral bleaching when world maps
show them living in the hottest oceans on the planet
there will be multi-meter sea level rise by 2100.
methane is a stronger greenhouse gas than CO2.
polar bears are going extinct.
the economy can run on wind mills & solar panels.
etc. It’s a long list.
Seems Rumsfeld was Kamala Harris before Kamala Harris.
Rumsfeld was bang on target, but it was the dimwits who ridiculed him because they couldn’t understand the sense he was making. And the press and media went along for the ride.
Rumsfeld was not a dimwit.
This is how Rumsfeld was portrayed by the lying, Leftwing media.
If you believe Rumsfeld was a dimwit, then you are a victim of Leftwing propaganda.
I think you need to read my comment again. I said Rumsfeld was on target, not a dimwit.
Sorry about that. I put my comment in the wrong place. I meant to post it under the name of the person who thinks Rumsfeld is a dimwit.
Yes, you left off the hamsters running in their exercise wheels to generate electricity for your reading lamp.
I believe it was Willis Eschenbach who some time ago assembled some scatter plots of sea surface temperature and found that 28C is the typical maximum temperature over the open ocean with a very few readings higher, up to 30C. The Red Sea and Persian Gulf can get up to 30 because they are mostly enclosed. I guess Google doesn’t read Willis much.
Thanks for that tidbit. Coral reef bleaching may be a thing, but common sense says that it’s not caused by warm water.
Carbon dioxide is innocent. It is the Sun, and variations in it, that cause short term and long term changes in climate.
Is that a fair summary?
Definitely my view based on the evidence.
Land based biomass may contribute a little as well by adding to the solar driven increase in precipitable water.
You really mean that the sun with a weight of 1.98841*10^30
we get 99.9% of our energy from is controlling our climate
and not 0.04% of co2?
Craziest thing I’ve ever heard.
Wait till I give you my views on religion. 🙂
Also, as can be seen at climate4you.com, cloud cover has declined about 3% over the past several decades.
No. The Sun and variations in it cause weather.
Climate is now defined as the 30 year average of weather.
Climate change is not presented or calculated correctly. It should compare 30 year averaged weather (not just temperature) against prior averages.
The planet may, repeat may, have achieved a 1.5 C increase since 1850, but the climate average for the past 30 years is much less.
The first climate datum would be the average from 1850 to 1880. Then annual averages (1851 to 1881, etc.). Then one can trend climate change. The problem is the data integrity issue, so it is pointless to spend the time doing the calculations, although it is a simple spreadsheet calculation, but the calculations cannot be done with anomalies, it must be done with measured temperatures in kelvin.
Likewise such a calculation assumes a single global temperature definition is valid, which it isn’t.
Climate is more than temperature, be it absolute or anomaly. Mid-range temperature is not even a proxy for climate temperature. It’s why agriculture science speaks of heat accumulation instead of mid-range temperature. Ag science tends to use extensive properties like degree-days instead of intensive properties like temperature. Climate science has a LONG way to go before it becomes a legitimate “science”.
4th line in my post:
(not just temperature)
That detail pushed aside, you are spot on.
Yes, the Köppen climate classifications are based on seasonal temperature and precipitation.
Correct. I did not I was ignoring everything except temperature to make the point of how climate change is mis-calculated.
Precipitation.
Sunlight
Cloud cover
Wind speed and divection
Humidity
Soil moisture
Flora (including food crops, trees, grass, etc.)
And, yes, temperature
I probably missed one or 2 but that list covers most of micro climate.
elevation, pressure, terrain (e.g. east or west side of a mountain), geography (e.g. coastal vs inland)
In-sol-ation. The output of the sun, as a nuclear fire, is overall stable over short and medium time periods. The changes in energy from the sun – think sitting close to the fire or across the room – arriving at earth changes when earth is closer to or farther away from the sun in its variable orbit.
Years ago, I read that the total irradiance from the Sun was remarkably stable, within parts per 100,000 or so.
What isn’t stable is the magnetic activity on the surface of the Sun and, with it, its affect on the Sun’s heliosphere and then directly on the heliosphere’s effect on cosmic ray intensity reaching our atmosphere.
This magnetic activity translates into no increase in total irradiance but and increase in the amount and type of cloud formation in the cloud chamber that our atmosphere is equivalent to.
So, if you can believe the theory, there is no direct relationship to solar irradiance but there is an inverse relationship between the Sun’s sunspot cycle with its 11-year cycle plus the longer-term maximum and Maunder-like minimum solar activity.
I grok that we tend to think in direct relationships but all signs point to our climate being inversely related to something else, that is, the varying intensity levels of the cosmic rays reaching our lower atmospheric envelope.
Correct.
There was a report I read a while back about the effects of the solar magnetic field shifting from solar north hemisphere to solar south hemisphere as seen on earth.
Treating the sun like a constant and the orbit as merely a mean is a fatal mistake.
Is it sufficient to consider just the total insolation? Does the makeup of that insolation in terms of wavelength vary from season to season and year to year? And if so what effect does that have? I don’t know but I’m sure somebody on this blog will have an answer.
There are changes in the spectrum of the insolation linked to solar activity. The solar “constant” can increase by up to 3W/m^2 during high activity. That is not enough on its own to give the increase in temperature observed during high activity so there could be other factors associated with the spectrum. Generally high activity is linked to the arc of the Sun’s orbit that can also alter the distance and declination.
Richard, from my past readings, the solar spectrum is shifted towards the short wavelengths, with increases in the SW component as high as 10%.
Measurements made in the early 1800s (Sir William Herschel) discovered that different color bands of visible light have different energies. He also identified invisible light (calorific rays) that we now know are near IR.
Specific energy for a “photon” aka quantum of energy in an EM field related to valence electron states is:
E = hf
E = energy
f = frequency
h = Planck’s constant.
So yes. The total spectrum counts, not just IR.
so true. frequency and intensity matter. so many seem to think we can just add it all up.
What is shown is the average energy weighting assigned to each photon for its equivalent color band. What is missing is the number of photons for each color (i.e. wavelength) for a specified cross section of an illuminating beam. That is, the function describing the shape of the spectrum is missing.
That leads to the rabbit hole of designating a photon as a particle.
No rest mass. No volume. And an infinite number of energies depending on the EM frequency.
A “climate scientist” calculated, according to Google AI, the photons from the sun arrive at the earth separated by something like 1.5 cm.
That has never been detected and we do have the means.
A photon is a quanta of energy. That doesn’t make it a particle. The concept of a photon as a particle is a crutch used in thinking about how an EM wave interacts with physical reality. But there isn’t anything about a photon that doesn’t also describe an EM wave; polarization/spin, transfer of momentum, no mass. Even the photon as a quanta of energy only describes how energy is exchanged, it doesn’t *require* a particle to be involved. It’s a mathematical construct to make other quantum mechanics math work.
You are speaking of needing to know the *energies* in and out of the system we know as Earth. Energies are measured in joules.
When was the last time you saw a radiative balance diagram based on joules in and out over an interval of time?
That has been a major complaint of mine, especially with those stupid flat earth energy imbalance graphics for years.
I once posted about it and got corrected “it’s flux that matters” or something to that effect.
We are totally in agreement.
Another major complaint is a column of air 10 km high has a N W/m^2 transport across the atmosphere? Phew.
Another is EM travels at c. Thermal in gas travels at an average of 1/2 speed of sound. Thermal in liquids slower and in solids slower still. Leaving the latencies out of the analysis is bogus.
Another is the surface reflected light goes out without interacting with the atmosphere, but the incoming with the same spectrum does. WUWT?
Oh…I didn’t realize you thought S/4 was flat Earth as well. So if 340 W.m-2 is flat Earth then what is the average TOA flux for a spherical Earth over one orbital cycle?
An exploration of alternatives is highly beneficial.
Wavelength most certainly has a place in the analysis.
The extraterrestrial solar spectral irradiance is remarkably stable, with the exception of very short wavelengths, below 450nm, especially UV below 400nm. These vary with solar activity and the sunspot cycles; when high the UV output increases and varies over short time spans (less than a day). The subject is complex, involving solar physics and atomic emission lines. Integrated over all wavelengths, the solar irradiance increases by several W/m2 between valleys and peaks of the sunspot cycle.
The effects of these on climate are unknown.
The effects of these on weather (not climate) are unknown because the use a mean orbit and average solar EM. In other words, those factors are ignored but the “climate science” establishments.
Exactamondo, “Averages R Us”.
Humor – a difficult concept.
— Lt. Saavik
The term “thermalized” is misapplied in the article. EM and thermal energy are not the same.
It is one of those Trans-Reality Activist lexicon definitions where a legitimate scientific term with a specific definition was hijacked and redefined using common/social context derived definition.
Ditto for “heat.”
Those nits aside, and one must use common language at times to better communicate the significant points, I applaud the balance of the analysis.
One point: CERES only measures orthogonal to the planet surface. Atmospheric optical depth is based on the wave front vector with the sun as the starting point. Therefore, what CERES is measuring is not the reflected solar EM on the nadir.
The atmosphere depth is based on spherical geometries and is shallowest at the equator (when the wavefront vector is orthogonal to the surface) and thickest at the poles.
Draw two concentric circles, then do the trigonometry.
The work and effort put into this analysis deserves respect. Well done.
That is certainly true for most imaging satellites that record nadir views. However, IIRC, Ceres does do oblique viewing, albeit orthogonal to the orbital line projected to the surface. That means it is rarely looking in the direction of the sun, thus mostly recording diffuse scattering, missing most specular reflections. Furthermore, for high angles of incidence, CERES bins the readings, taking the arithmetic mean in the reflections from the angular-bin, where it is in a very non-linear portion (>60 deg) of the reflectance curve.
As I have remarked before [ https://wattsupwiththat.com/2016/09/12/why-albedo-is-the-wrong-measure-of-reflectivity-for-modeling-climate/ ] CERES measurements are a lower-bound on reflectance, typically missing specular reflections that require a geometry that looks towards the sun for all measurements. That is, one needs to add the specular reflectance across a hemisphere to the diffuse BRDF [ https://en.wikipedia.org/wiki/Bidirectional_reflectance_distribution_function ].
I read your article and it was good.
Albedo. In radar, we can calculate the reflectance and absorption.
Materials sciences has measure the emissivity of many materials.
All of that is ignored by the “climate science.”
In addition, EM reflections on the surface (and I know you know this) is driven by the angle of incidence.
CERES is an exceptional tool. But it is limited, specifically in its acquisition angle. While it can “look around” it cannot acquire all that comes its way. If the acquisition angle is, for example, 45 degrees, anything outside that cone (pinnacle is the sensor) is missed.
You don’t do nuance, eh?
If we are going to talk science and engineering, is it too much to ask to use the correct terminology and definitons?
Or maybe just fall back on 1+1=2, how do you feel about that (aka new math)?
The non-constant ISR ToA swings 91 W/m^2 from perihelion to aphelion.
The non-constant albedo uncertainty is 23 W/m^2.
A personal request, Nicholas Schroeder.
Please stop using that flat earth graphic.
Rick, regarding “ToA Daily Average Solar Flux (W/m2)”: are these averages for daylight hours or for all 24 hours?
The Sun appears at the poles for 24 hours per day. So the average has to be taken over 24 hours. The South Pole currently gets the highest average daily solar but then it goes to zero at other times of the annual cycle.
For my daily calculations, the average is based on 30-minute intervals over 24 hours. Lots of geometry involved to determine the average.
Thanks, I can well imagine the complexity of the calculations.
Only one pole at a time gets the 24 hours and that is never at equinox.
The non-constant tilted axis ISR swings 700 W/m^2 from summer to winter.
That graphic is useful.
THIS is a very good point and a good way to explain what you are trying to say. I agree with Sparta, avoid Trenberth at all costs.
So are we back to accepting that averaging intensive properties is possible, useful, and meaningful again?
Only when in service of prejudgments.
Off to the Cal central coast early June, for the summer. I’ll leave the St. Louis area summers to you and yours. We do this regularly, but started in the winters of the (if I recall) early teens, after a brutally cold winter spell. Temp trends have moved us from winters to summers away for several years now.
It has NOTHING to do with prejudgements. It has to do with the understanding of systems and intensive properties.
Since intensive properties do not depend on the system size you cannot add them to find a physically meaningful mean value – you can’t find the temperature of a combined system.
All you get is statistical descriptor of the data – which is physically meaningless. There is no such thing as a global *average* temperature. The only thing you have is the mean of the data. And without the standard deviation of the data you can’t even judge the uncertainty of the calculated mean – and when was the last time you saw climate science discuss the standard deviations of the data used to calculate the “global average temperature”?
Who is “we”. And who is accepting that you can average intensive properties to get an “average” temperature of a combined system?
You *can* mathematically average the intensive properties of a collection of different systems. It gives you the mean of the COLLECTION data, it does *not* tell you anything about a combined system since combining systems with intensive properties does *not* produce a physical sum that can be divided to find an average intensive property.
The mean of a set of temperatures collected from different measuring stations in different locations is only a statistical descriptor of the collection. It is *NOT* an average temperature of the systems being measured.
It’s why the Global Average Temperature is a joke. It is nothing more than a statistical descriptor of the data – it is *NOT* a physically meaningful average temperature of the globe. It doesn’t matter if you have data spanning a day, month, year, or century – you can’t find a physically meaningful average temperature of the combined system called the “globe”.
The standard deviation of the data would give you more physically meaningful information than the mean. But climate science NEVER provides anything about the standard deviation of the data being analyzed – doing so would show the uncertainty of the statistical descriptor known as the mean. Knowing the 5-number statistical descriptors would be even better, the range of the data is a physically meaningful description of the widely different systems being looked at. The mean and mode values would give some indication of the physical skewness of the data in the collection.
Statistical description of the data.
I shall definitely add that to my lexicon.
It is the first time I have heard it phrased exactly that way.
Kudos!
Even the mean of extensive properties is only a statistical descriptor of the data unless the objects can be combined into a single system. Adding the masses of a piece of wood and a piece of granite doesn’t really give you a combined system with a total mass that can be averaged. The average length of the 2″x4″x8′ boards in a bin at the lumber yard is nice to know but there is no guarantee that any of the boards are actually, physically of that length. Why it is nice is that it makes it easy to charge you for 20 boards – just use the average length instead of measuring each one. Even the mean of those boards is not very useful if you don’t know their standard deviation. Would you buy 20 2″x4″x8′ boards if the standard deviation of the supply is 6″? Your stud wall is going to be pretty wavy on top.
Too many statisticians and computer programmers think of the mean as a physical quantity, a MEASUREMENT. It isn’t. It’s a statistical descriptor of the data. It may be useful in certain situations but it is *not* physical reality.
The ISR ToA elliptical orbit, tilted axis and albedo drive the terrestrial systems.
The imaginary non-existent CO2 GHG warming hallucination is noise in the data.
Please feel free to correct me. It seems you just expect us to just have faith in your JPL work.
Afaik, no one has seen the details of your JPL data/research that you’ve been using all these years as the basis for all your analyses, so totally accepting any of your results can only happen for me after you have supplied your code, methods, and results for that part first; or get it peer-reviewed.
Charts 1 & 2 beg the question, how does 45N/S and 75N/S get more TOA insolation than 15N/S?
Secondly, on your unlabelled charts after Chart 16, what reason can you give for these two periods being so opposite each other within a few years after 2023? What changed?
They are the maximum value in any annual cycle. In mid latitudes, the surface temperature is highly correlated and linear so the maximum and minimum values is all you need to know to determine how the temperature will change. Of course there are underlying trends depending on the trend in the maximum and minium.
Rick,
I may be on the wrong track here, but I believe that Bob was asking HOW can the TOA values for the higher latitudes occur, at those latitudes the surface is inclined and must surely be ‘seeing’ less sunlight.
I would like to see a plot of just a few years data, showing each line of latitude, say at 10 degree intervals from the SP to the NP. The incident energy should show a smooth change between the lines.
If the lines are not stacked in some recognition of the latitude, then why not ask, “is there something wrong with the data?” I would expect that due to the incident angle of the Sun that the line for the equator would be the most illuminated. Hence Bob’s question above.
Most of the curves are related to the maximum daily-mean sunlight for the nominated latitude. Not the daily peak sunlight.
In the present era, the South pole gets the highest daily mean sunlight. Mainly because it gets sunlight all day on some days of the year. It remains cold because it is a 2000m high block of ice with high reflectivity that the sun cannot melt.
There are web based calculators for determining daily mean sunlight like this one:
Computation of various insolation quantities for Earth
Or you can use geometric formulas that are based on declination, distance, solar constant and hour angle. The formula is not what I regard as trivial geometry but it is not difficult to apply using a computer.
This is maximum daily-mean insolation at 100-year interval for South Pole from 2000AD assuming constant solar constant of 1362W/m2:
0.000 559.209557
0.100 558.695920
0.200 558.168289
0.300 557.627205
0.400 557.073220
0.500 556.506897
As I demonstrate, temperature in the mid-latitudes is highly, linearly correlated to sunlight. So if you know the change in maximum sunlight from one year to next, you can predict if temperature is going to be higher or lower in the mid latitudes from one year to the next.
Polar and tropical regions do not have linear response. I go into detail how the tropics respond.
The year-to-year comparison charts are daily anomalies of one year relative to another. For example, 2026 relative to 2023 indicates higher daily mean sunlight autumn to winter in the SH and lower spring-summer sunlight. The reverse for the NH. So both hemispheres more moderate than 2023 from the perspective of warming and cooling. Another surprise here is that 2027 is not much different to 2023. So there should be a temperature bounce next year.
I think you missed the point I was raising.
Shouldn’t the insolation at latitude follow a Cos curve, with the maximum at the equator, (assume that the Earth is at an equinox to keep it simple).
If not….. why not?.
If you had the data from a stack of measuring points, all at the TOA, spaced above the lines of latitude, then the AVERAGE measure should all be a multiple of Cos(latitude).
This should be the case for ANY year at the equinox dates. Of course you can slide the curve around to suit the day of the year, following a 23 degree +/- factor added to the latitude value, (with the +/- varying over a year from one peak to the next). For simplification, let’s leave that out for the moment. Just look at an equinox date. Does the data reflect the cos(latitude) rule for the solar insolation values. If not…. then maybe the data has been through the hands of the CSIRO or similar.
I think you and Rick are talking past each other. Rick is talking about the length of the day. You are talking about the amount of heat actually absorbed over the length of the day. Because of the angle of incidence, the poles wouldn’t absorb much heat from the sun’s insolation – your cos(θ)dθ is the maximum that would be absorbed. Because of the reflectivity of the ice the absorbed heat is actually even smaller. Even if the pole was covered in asphalt, it wouldn’t absorb very much heat. Can asphalt freeze?
If I placed a 1kW solar array at the South Pole on a horizontal surface it would produce at close to half rating for 24 hours on the December solstice. Around 14kWh for the day.
Now if I tilted the panel to face the Sun, it will get most of the 1409W/m^2 available and produce maybe 30kWh for the day because it would be operating 30% above rated power for 24 hours.
The South Pole gets the highest daily-mean sunlight normal to the surface and 24 hours of the most intense sunlight aligned with the Sun.
All calculations are based on the so-called cosine formula that is explained here:
Insolation – The Climate Laboratory
The geometry is quite a bit more complex than you are suggesting. That is why I give the South Pole example.
You have a far too simplistic view of the geometry.
For 2026, the daily average sunlight over the whole year for given latitudes is:
75s 183.5
60S 232
45S 301.5
30S 358.5
15S 395.2
Eq 407.1
15N 394.9
30N 358
45N 300.7
60N 231.4
75N 182.4
As you can see, they are not sinusoidal.
I provided a link to the formula and also a link to a web based calculator where you can get daily average insolation at any latitude for any day of the year.
And I have only charted the maximum daily mean because it is this that drives the maximum temperature in the mid-latitudes. If the maximum sunlight is trending up then the maximum temperature will be trending up.
“Most of the curves are related to the maximum daily-mean sunlight for the nominated latitude. Not the daily peak sunlight.”
I think you mean “daily-mean sunlight interval“.
The transfer of heat, and therefore temperature, is not just a function of the length of the day but also the angle of incidence. The cos(θ)dθ factor describes how much of the sunlight is absorbed as heat. The poles may be lit for a long time but very little heat is actually absorbed. cos(pi/2) = 0.
It’s not just elevation and reflectivity that are determining factors. Although I would note that the amount of sunlight that is reflected is not just dependent on the reflecting material but also on the angle of incidence. Even if the pole was not ice covered there still wouldn’t be much heat absorbed meaning that surface temperature there would still be cold.
Just look at the sunlight on a calm lake near sunset.
Most of the light is reflected and if you look for more than a brief glance you can hurt your eyes.
Snow blindness.
The daily mean flux is normal to the surface. It is “flux”; meaning per unit area.
I am not doing area averages unless I am calculating energy or regional temperature.
The South Pole gets the highest daily mean flux normal to the surface. A 1kW solar array set horizontal would produce about 12kWh at the south pole on the December solstice – it gets 24 hours of sunlight. If I set the panels to track the sun, I would get around 24kWh in a day- maybe even more due to the lack of moisture in the atmosphere. The Sun at the ToA is above 1400W/m^2 on the December solstice. So aiming the panels at the Sun, I would get most of that and panels are rated at 1000W/m^2.
“The South Pole gets the highest daily mean flux normal to the surface.”
Please. The flux normal to the surface is what transfers heat energy. If the poles received the most heat energy on earth they would also reach the highest temperatures on the earth. There would be no ice at the poles.
The solar flux is a plane wave. It’s vector has the same direction every where. It is not normal to all dS elements on a spherical surface.
“So aiming the panels at the Sun”
Those panels would also be at an angle to the surface. You are trying to equate putting an artificial surface perpendicular to the flux direction with the actual surface also being perpendicular to the flux direction.
You have this wrong. There is actually ice in the tropics all the time as well. Himalayas for example. Kilimanjaro is very close to the Equator and has permanent ice.
The South Pole remains cold despite getting the highest daily mean sunlight because it is an ice block at about 2800m altitude and has many days without any sunlight. Also there is not much heat in the air at 2800m and the surface is relfective. But if I sat a solar panel flat on the surface it would receive a daily mean of 558W/m^2 on the summer solstice. So would produce around 56% of its rating over the entire 24 hour period in clear sky conditions. A 1kW array sitting horizontal on the surface would produce about 13kWh
All insolation calculations for the article are based on the intensity through a plane parallel with the surface. There is no surface albedo or reflection involved in the calculation because it is at the top of the atmosphere. The angle of incidence throughout the day reduces the intensity by the geometry at that point on the globe.
I produced this chart for an article a couple of years ago that looks at solar intensity across latitudes for different times of year:
image-88.png (950×477)
Yu will note is it similar to what Bob Weber found at CERES.
“All insolation calculations for the article are based on the intensity through a plane parallel with the surface. There is no surface albedo or reflection involved in the calculation because it is at the top of the atmosphere.”
The heat absorbed *at the surface* is dependent on the angle of incidence. You use the divergence theory to calculate how much gets absorbed.
The sun’s insolation at the top of the atmosphere is a plane wave. You are basically just saying that you assume that the surface at TOA is 100% transparent and all incident flux get transmitted through the surface. There is nothing wrong with that. But when that plane wave reaches an absorbing material, the only heat that can be absorbed is that part of the flux that is normal to the surface. Depending on the absorbtivity and reflectivity of the absorbing material, it may not even absorb all of the normal flux.
The normal to the surface of a sphere in a plane wave is based on cos(θ), the angle between the incident wave and the normal of the surfact.. If you haven’t accounted for that then your totals are not correct.
Conceptually this is no different than splitting gravity into a normal and parallel force on an inclined plane. Only the parallel force contributes acceleration down the plane and only the normal force contributes to friction force.
I have a feeling this is being accounted for somewhere in your calculations, I’m just not sure where.
You are thinking of detail that is all accounted for by sticking with the top of the atmosphere for the incoming solar EMR. I do not need to go into detail on how and where the sunlight gets absorbed or reflected.
The EMR is reacting in a myriad of ways with whatever it encounters as it passes through the atmosphere and into the ocean; or onto a leaf or a rooftop or side of a building; or desert sand. None of that matters because I can demonstrate that the thermal response for any location or an entire region in the mid latitudes is highly linear with the daily solar intensity..
It is not linear in the tropics as I have detailed and not much gets absorbed by any grounded snow at high altitude or high latitude..
Rick as they are maximum annual values I suspect you’ve gotten them from the CERES zonal solar raw data, instead of the area-weighted zonal values, ie, weighted by cos(lat).
The figures you mentioned to Eng_Ian, who is on the right track, were similar to the CERES solar raw data maximums. Area-weighting yields an entirely different picture.
No – I did not get them from CERES. I produced them using the method explained from first principles. I doubt you will find CERES data back to 1000AD.
I quite clearly explain that I am giving maximum daily mean ToA insolation at selected latitudes. There is no reason to area average them. If you stood at the South Pole around the December solstice on a clear day you would get more sunlight than anywhere else on the planet as the top chart shows.
I am not adding them so no need to area weight. I nominate the specific latitude for the data. My intention is to show how maximum daily insolation changes each year at various latitudes.
If I was producing seasonal energy for a region I would be area weighting the solar flux.
The calculation for rejected heat versus sunlight requires area weighting for the rejected heat because I am considering the reflected flux across 30 degrees of latitude.
Fundamentally the SH gets its dose of energy in 8 to 9 days less than the NH gets its similar dose. So sunlight in the SH is inevitably more intense than the NH. But the orbit has already begun the long road to reversal.
The objective in the article was to show how the maximum is changing over time at selected latitudes.
If you use the JPL data and formulas I linked to below you will be able to produce a chart similar to the top chart in your post.
“I doubt you will find CERES data back to 1000AD.”
What I found was your answers conform to what CERES raw data shows.
Who knows how you might have cobbled anything together.
“If you use the JPL data and formulas I linked to below you will be able to produce a chart similar to the top chart in your post.”
What am I, a mind-reader? Please demonstrate that you can do what you just suggested. Please reproduce the maximum curve from first principles.
BTW I am someone really big into first principles. Show us you’ve done it.
If you’re not willing to divulge your method you should quit now, really.
I see no practical use for using the maximum value when the important aspect is what amount of insolation hits the surface, ie, area-weighted.
“December solstice on a clear day you would get more sunlight than anywhere else on the planet as the top chart shows.”
Definitely daylight defined as the number of hours of sunlight.
However, EM wave intensity striking the surface is much less per m^2 due to angle of incidence and optical depth above the surface.
The point being, one needs to define sunlight in context.
Not at all. I did not want to pad the article with trivial detail.
I rely on JPL getting the orbital data correct. It is a trivial exercise to download the data using the Horizons web application. It is limited to 90,000 lines. I had to do 6 downloads to get 1200 years but I overlapped them to ensure they were continuous. I also set the calendar rather than have the step from changing calendar. There may be ways to get a single dump but then I would have to learn more about the application.
The daily solar calculation is based on 48 30-minute intervals using well known geometric relationships related to declination, distance, solar constant and hour angle. Google it. There are web tools to check if you have the formula correct.
The solar constant is adjusted up to 3W/m^2 from a base of 1361W/m^2 based on the divergence of the sun velocity from average velocity with a 2.4 year phase shift because the high solar activity occurs during periods of acceleration and deceleration. The range was calibrated to the TSI measured data from 2002 to 2019. The Sun velocity again came from JPL. There is proxy data for TSI based on solar spot counts or magnetic field but it is the changing Sun velocity that drive the activity. Scarfetta has done some work on this but I am the only one, as MS Copilot can assess, who has actually made a free body model of the spin and observed how Mercury pumps it. I have also now determined that it does not need oblation of the Sun for the external gravity field to pump the spin. I did not include this detail because the article may not get published on WUWT if it was. In any case the change is small but not trivial on yearly scale. Trivial over centuries though.
This may be trivial to you by now, but I am not privy to your exact method.
Who would you trust to replicate your findings using only what you just described?
“Google it. There are web tools to check if you have the formula correct.”
It’s really not anyone else’s responsibility to Google such an incomplete description. How would anyone know they or you have the right formula?
As it stands now you’re still relying on us having faith in your method sight unseen.
You really want to be spoon fed.
Are you able to use JPL:
Horizons System
I have attached a screen image of the observer table. I am only interested in the apparent declination and range so I limit the table to those values. If you go back past 1500 then you should select a calendar to avoid a date jump.
“You really want to be spoon fed.”
Yes I do when it comes to the foundation of your work. You should resist the temptation to make this about me. It is about whether you have anything or nothing, and no one can know with you hiding your exact methods.
I detail the foundation of the work. It is not that difficult. You even found a CERES chart that shows the same information for a single year. I just did those calculations for 1200 years..
It doesn’t matter whether your work is difficult or not, it is whether others can see that you have done it right or not.
I made those charts btw.
This page has details of the insolation at time of day and latitude given distance, declination and solar constant:
Insolation – The Climate Laboratory
To get a daily average, I divide the day into 48 30-minute intervals and take the average.
There is a reasonable amount of calculation involved. But that is what computers are used for. When setting up the formula, it pays to validate the result against other calculators like the imcce. I am not certain if they are using the JPL ephemerides.
You can check what you calculate with this web calculator:
Computation of various insolation quantities for Earth
I have a new compact computer that does the 430,300 days for 20 selected latitudes in 3800 seconds.
Stop deflecting back onto people asking questions; show us your work.
I have given you the formulas and references to get the orbit data. I pointed out my “work” is in very large data files that anyone with a decent computer and a willingness to do some calculations can easily replicate.
I cannot help if you are incapable of applying those geometric formulas to arrive at daily sunlight at any latitude.
I have even given you a link that allows you to use a web calculator to check your calculations.
Excuse me, you haven’t give me or anyone else your specific formulas.
No one knows if you aren’t just full of sh!t.
You have only given out a smattering of links and loads of innuendo, expecting people to assemble your work themselves.
Your attitude demonstrates defensiveness, defiance, and arrogance.
The burden of proof for your claims rests with you and only you.
I am using well known formulas for determining ToA sunlight at any point on the globe given declination, distance and solar constant.
You have confirmed my data with what you have been able to find on CERES for recent history.
It is not up to me to train you in applying basic formulas.
Insolation.
Perhaps due to spherical geometry the atmospheric optical depth is greater at higher latitudes than the equator.
My bad. I confused insolation with insulation. Apologies for multiple posts.
I can’t see any change in solar radiation in the graph during the Little Ice Age 1300 to 1850. Was there no decrease in solar radiation during the Little Ice Age?
Are there more unknown factors that affect the Earth’s climate?
Weaker solar wind states cause the negative North Atlantic Oscillation conditions that brings the cold weather to Europe. The coldest parts of the Dalton minimum for west Europe had dearth of aurora sightings.
“no auroras at all during the years 1797, 1798, 1802, 1807, 1809, 1810, 1811, 1813, 1815, 1816, 1823, and 1824”
https://svalgaard.leif.org/EOS/92RG01571.pdf
The maximum daily mean at 45N hit a shallow minimum in 1640. It varies about 0,5W/m^2 from year to year. Maximum up almost 1W/m^2 in 2023 compared with 1640.
My proxy for NH advection hit a sharp minimum around 1250. Based on what the SH is currently doing, there is a long lag between the advection solar forcing changing and the actual temperature in the higher latitudes.
The heat rejection in the NH bottomed in 1600. This would be the quietest period for convective potential and cyclones in the NH for the 1200 years examined. Cyclones transport heat poleward.
I have not gone through in detail looking at the years when the Thames froze but direct solar forcing, lower poleward advection and tropical convection all point to the period from 1600 to about 1750 being cool years.
The term LIA is misplaced as well because Earth has remained in the present ice age for millions of years now with Antarctica permanently covered in ice. Getting ice onto land is energy intensive so relies on warm ocean to get the moisture into the atmosphere. The NH ocean warming started around 1700.
The difference between solar minimum and solar maximum is 1-1.3 W/m^2.
The average temperature of the Earth is not affected by solar minimum and solar maximum. Could it be true that 1W/m^2 lower solar radiation created a Little Ice Age?
The difference in W/m^2 between the Little Ice Age and today is controversial.
Some researchers say that the Little Ice Age was 0.5 W/m^2 lower than today. While other researchers say that the Little Ice Age was 2.5-4.6 W/m^2 lower than today.
There were many UK warm-hot years 1650-1666, especially the early to mid 1650’s. The 1610’s and 1630’s also saw plenty of hot weather.
Is 10Be concentration in the perpetual ice the best way to reconstruct historical solar radiation?
10Be concentration in the perpetual ice shows a more variable solar radiation during 1354-1950.
https://www.sciencedirect.com/science/article/pii/S2666277921000058
An Antarctic view of Beryllium-10 and solar activity for the past
millennium
https://www.whoi.edu/cms/files/delaygue11cd_240604.pdf
The Spörer Minimum started around 1425, and no centennial solar minima are longer than 5 solar cycles, so it ended in the 1480’s. There was an additional unnamed centennial solar minimum from 1550 to the 1580’s.
Cold weather associated with the Maunder Minimum was largely between 1670 and 1705, the 1650’s to mid 1660’s was not low solar as far as the weather is concerned. I don’t see the point of using 10Be concentration records as evidence of it being cold, when it was actually warm to hot.
https://www.metoffice.gov.uk/hadobs/hadcet/legacy/data/cetml1659on.dat
Richard, you state in your article, “Note that there is no symmetry between the NH and SH.” To what do you attribute the asymmetry?
Fundamentally, geometry. A tilted, rotating, orbiting ball with varying distance to the Sun.
Without doing the sums, my intuitive thought was that all latitudes in the NH would have rising maxima and all latitudes in the SH have falling maxima. Biggest surprises were that the maximum at 10S has a rising trend and the higher latitudes in the NH have not yet hit lowest maxima.
Both hemispheres get very close to the same energy each year but the SH gets its dose in 8 or 9 days less than the NH. So solar intensity in the SH is higher than NH. The time difference is reducing. In about 4500 years both hemispheres will have the same intensity but by then a lot more of the NH will be covered in ice.
In terms of precession, the NH has only started to warm up however 2026 is probably the year that the average temperature in the mid-latitudes of the NH exceeds the mid-lat temp in the SH. Distribution of water makes a big difference.
Fundamentally, geometry. A tilted, rotating, orbiting ball with varying distance to the Sun.
Without doing the sums, my intuitive thought was that all latitudes in the NH would have rising maxima and all latitudes in the SH have falling maxima. Biggest surprises were that the maximum at 10S has a rising trend and the higher latitudes in the NH have not yet hit lowest maxima.
Both hemispheres get very close to the same energy each year but the SH gets its dose in 8 or 9 days less than the NH. So solar intensity in the SH is higher than NH. The time difference is reducing. In about 4500 years both hemispheres will have the same intensity but by then a lot more of the NH will be covered in ice.
In terms of precession, the NH has only started to warm up however 2026 is probably the year that the average temperature in the mid-latitudes of the NH exceeds the mid-lat temp in the SH. Distribution of water makes a big difference.
Thank you for the response. I had overlooked Kepler’s 2nd Law.
The oceans and the continents occupy different percentages of the surface, more land in north, much more ocean in south.
The distribution of the land alters the response in the hemispheres but the asymmetry in the insolation is orbit and geometry. The Sun presently spends between 8 and 9 days longer over the NH than the SH for the same amount of energy So SH gets more intense sunlight. But that more intense sunlight does not translate to higher temperature in the SH due to the proportion of ocean surface.
But the graphs (and quote) are for the top of the atmosphere, not the surface.
Bad AI generated thumbnail! I’ll disk sun next to full disk earth and Australia, on the back side, is still in daylight???
But you know it is AI generated like most of the article headers.
net radiation from surface is (obviously) different to that at TOA. From surface, nearly all the rises are from ocean. Only small pockets, like near Peru, are over land.
so much for manmade CO2 forcings.
WOW! This is an excellent topic and from my 5 min scan looks ‘reasonable’, or at least contains the right topics! Thank you. This will take a while to really digest the assumptions of your math, but from the short review looks to be well thought out.
I hope it adds some understanding regarding how solar insolation has and will change.
There are no assumptions involved on my part. I selected the aspects that I consider important for understanding how climate has and will change. Most of what is displayed regarding sunlight is based on orbital mechanics and Earth geometry. JPL provide the data for the orbital mechanics and I am happy that they have enough handle on the starting conditions to give a reasonable reflection of reality. In a previous article I went into more detail on the free body motion of the Sun and planets:
Changing Sunlight – Sun Movement and Spin – Watts Up With That?
My proxy for the solar constant, variation of the Sun velocity relative to its average velocity with a 2.4 year phase shift then calibrated to measured TSI from 2002 to 2019, has daily error but the monthly averages align quite well. In any case the range of the solar constant is 3W/m^2 from a base of 1361W/m^2 It is important with respect year-to-year changes but is basically noise from the perspective of precession of the orbit that can vary the peak more than 100W/m^2 for the same day of the year over a precession cycle when orbital eccentricity is high.
Rick’s JPL based system doesn’t conform to observations. The following set of charts show that his Chart 1 & 2 zonal trends at his selected latitudes are opposite trends from CERES TOA data.
Charts 1 & 2 are unweighted; CERES TOA data was area-weighted, showing the true zonal averages at the surface. The CERES data area-weighting does not affect the trends.
Now I have little confidence in what follows in this article after Charts 1 & 2, especially after Rick has impeded verification of any of his calculations by choosing not to disclose them.
A reconstructed graph with the years 1000-2200 compared to a graph with real values for the years 2000-2025?
The down trend and up trend are opposite in the CERES TOA flux graph for 25 years compared to Chart 1 and 2.
Does this show an incorrectly reconstructed graph?
And shows that the Northern Hemisphere is getting warmer due to decreasing solar radiation.
Why are you trending all sunlight at selected latitude for 25 years and comparing it to what I have done?
To compare with my data you should look at the maximum flux each year not the average each year. That gives 25 data points.
I clearly explain that I have determined the daily sunlight for 1200 years and then select the maximum for each year.
So to check the CERES data against my trend, you would need to look at much longer time frames and only take the maximum.
And as I have also explained, there is no point using area weighted when you are considering a flux at a particular latitude. A flux is already given per unit area. If you are at 30S and exposed to sunlight of 1000W/m^2 then you will be taking in the same solar energy as a location at 10S taking in 1000W/m^2.
“If you are at 30S and exposed to sunlight of 1000W/m^2 then you will be taking in the same solar energy as a location at 10S taking in 1000W/m^2.”
This is not a precise statement. Have you accounted for the cos(θ) angle of incidence in both cases? It is possible for 30S to be closer to the sun and to have an angle of incidence closer to 90deg than 10S so the max for each during the earth’s travel could be the same.
The values are taken normal to the horizontal plane. The angle changes through the entire day. I provided links to the formula that combines declination solar constant and distance to calculate the surface normal sunlight.
If I am at 10S and the solar flux normal to the surface is 1000W/m^2 and I have a 100W rated solar panel, I will get 100W.
The actual solar intensity at ToA might be 1400W/m^2 but some is absorbed/reflected by the atmosphere leaving say 1300W/m^2 at an angle of incidence of 50 degrees so effectively 1000W/m^2 normal to the horizontal panel and it produces 100W. Now tile the panel to normal to the rays and it will produce 130W/m^2.
Same situation could apply at 30S where the intensity normal to the surface is 1000W/m^2.
The attached chart is for all days at 45N. It does show a down trend over this short period.
This chart shows the annual peak solar at 45N. It also has a downtrend over this short period. But what you get from this is a good indicator of the warmer years when the peak sunlight is higher.
Can increasing peak sunlight create increasing temperatures on Earth even though average sunlight does not change?
Yes. This is how the Milankovitch cycles can modulate the timing the of the glacial cycles. The total amount of solar energy does not change much, but the temporal and spacial distribution of that energy does. It is the distribution of that energy that drives facets of the climate system (like the snow/ice ebb and flow) which in turn forces the climate system into a new state with a higher/lower average temperature.
In the tropics, increasing sunlight can lower the temperature slightly because the convective engine fires up and continues to cycle for as long as the sunlight exceeds 425W/m^2. Refer Charts 4 & 5.
In the mid-latitudes, the ToA solar and surface temperature are highly correlated for a given location or region. So increasing maximum daily mean sunlight will drive increasing maximum mean daily temperature.
In the high latitudes, the response is non-linear. At latitudes higher than 67 degrees, there is no sun for times of the year but temperature does not go to 0K. The South Pole gets the highest daily mean sunlight but a snow covered ice block at altitude of 2800m is not going to get much above 273K even on the sunniest day of the year for anywhere on the planet.