There are two foundational errors in climate science. The first is in the theories and estimates of the role of cloud in changing the planet’s dynamic energy balance. Low level marine cloud forms over cool ocean water and dissipates over warm. The Pacific Ocean is where sea surface temperature varies most. Sea surface temperature changes dramatically across the Pacific Ocean as a result of a shifting balance between cold, turbulent, nutrient rich and acidic water rising in the eastern Pacific and the suppression of upwelling of sub-surface currents by a warm surface layer.
Observation from ships over 60 years show changes in cloud cover in the Pacific over periods clearly associated with the well known modes of Pacific Ocean multi-decadal variability. A change to less cloud in the shift to a warm El Niño dominated Pacific decadal pattern in the late 1970’s and a change to more cloud following the shift to a La Niña dominated cool mode since 1998. Satellite data quantifies changes in outgoing shortwave and longwave radiative flux associated with cloud changes between 1984 and the late 1990’s.
This is what NASA/GISS says about the International Satellite Cloud Climatology Project data.
The "slow increase of global upwelling LW (infrared or heat) flux at TOA from the 1980's to the 1990's, which is found mostly in lower latitudes, is confirmed by the ERBS records.’
"The overall slow decrease of upwelling SW (visible light) flux from the mid-1980's until the end of the 1990's and subsequent increase from 2000 onwards appears to be caused, primarily, by changes in global cloud cover (although there is a small increase of cloud optical thickness after 2000) and is confirmed by the ERBS measurements."
Wong et al (2006) find that “comparison of decadal changes in ERB with existing satellite-based decadal radiation datasets shows very good agreement among ERBS Nonscanner WFOV Edition3_Rev1, HIRS Pathfinder OLR, and ISCCP FD datasets.” They estimate the 15 year 'stability uncertainty' of the radiative flux anomaly data (for all three datasets) at 0.3W/m2 to 0.4W/m2.
All global warming in the past 50 years, the period in which the IPPC say most warming occurred because of human greenhouse gas emissions, happened between 1977 and 1998. In the instrumental record, the trajectory of global surface temperature mirrors the Pacific Ocean states. Cool to the late 1970’s, warm to 1998 and cool since. Ocean sea surface temperature is negatively correlated to marine stratiform cloud. Multiple satellite data sources show that over most of the last warm Pacific period there was planetary cooling in the infrared band where greenhouse gases were expected to result in warming - and planetary warming as a result of less cloud reflecting less sunlight back into space. As a testable hypothesis, made by many before me, the current cool La Niña mode of the Pacific decadal pattern will lead to increased cloud cover and global cooling over another decade or three.
The other foundational error is in the assumption that weather is an ‘initial value problem’ and climate a ‘boundary value problem’. The distinction sees weather as ‘chaotic’ and climate as the ‘statistics of weather’. The new scientific consensus is that both weather and climate are chaotic. For example, the British Royal Society in their recent climate science summary discussed internal climate variability as a result of climate being an example of a chaotic system in theoretical physics. While this may seem to be a quibble on a minor point to many - it is in fact central to consideration of climate predictability and climate risk. In a chaotic climate – predictability and risk are two sides of a coin. Climate predictions can only be made in terms of probabilities and climate risk from anthropogenic greenhouse gas emissions is mathematically certain as a result of those same probabilities.
Abrupt and violent climate shifts have a long history on planet Earth - less extreme climate shifts occurred four times last century. Small changes, such as anthropogenic greenhouse gas emissions, can accumulate in chaotic systems until they precipitate a shift that is wildly out of proportion to the initial impetus. The scientific proof that climate is a chaotic system - and that this has effects in the modern era - is relatively new. I date it from a 2007 study by Professor Anastasios Tsonis and colleagues: ‘A new dynamical mechanism for major climate shifts’. A numerical network model was constructed for the study from 4 observed ocean and climate indices – the El Niño Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the North Atlantic Oscillation (NAO) and the Pacific Northwest Anomaly (PNA) - thus capturing most of the major modes of climate variability in the period 1900–2000. This network synchronized around 1909, the mid 1940’s and 1976/77 – after which the climate state shifted. A later study (Swanson and Tsonis 2009) found a similar shift in 1998/2001. They found that where a ‘synchronous state was followed by a steady increase in the coupling strength between the indices, the synchronous state was destroyed, after which a new climate state emerged. These shifts are associated with significant changes in global temperature trend and in ENSO variability.’ Amongst the implications of these studies is that these indices of climate are not independent but interact globally in a shifting climate. There are tremendous energies cascading through powerful systems.
The satellite data is discussed in some detail at below.
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