Oh dear, now we have three peer reviewed papers (Lindzen and Choi, Spencer and Braswell, and now Richard P. Allan) based on observations that show a net negative feedback for clouds, and a strong one at that. What will Trenberth and Dessler do next? Maybe the editor of Meteorological Applications can be persuaded to commit professional suicide and resign? The key paragraph from the new paper:

…the cloud radiative cooling effect through reflection of short wave radiation is found to dominate over the long wave heating effect, resulting in a net cooling of the climate system of −21 Wm−2.

After all the wailing and gnashing of teeth over the Spencer and Braswell paper in Remote Sensing, and the stunt pulled by its former editor who resigned saying the peer review process failed, another paper was published last week in the journal Meteorological Applications that agrees well with Spencer and Braswell.

This new paper by Richard P. Allan of the University of Reading discovers via a combination of satellite observations and models that the cooling effect of clouds far outweighs the long-wave or “greenhouse” warming effect. While Dessler and Trenberth (among others) claim clouds have an overall positive feedback warming effect upon climate due to the long-wave back-radiation, this new paper shows that clouds have a large net cooling effect by blocking incoming solar radiation and increasing radiative cooling outside the tropics. This is key, because since clouds offer a negative feedback as shown by this paper and Spencer and Braswell plus Lindzen and Choi, it throws a huge monkey wrench in climate model machinery that predict catastrophic levels of positive feedback enhanced global warming due to increased CO2.

The cooling effect is found to be -21 Watts per meter squared, more than 17 times the posited warming effect from a doubling of CO2 concentrations which is calculated to be ~ 1.2 Watts per meter squared. This -21 w/m2 figure from Richard P. Allan is in good agreement with Spencer and Braswell.

[While the -21wm2 and ~1.2 W/m2 values are correct, the comparison is wrong, and it is my mistake. The values are Top of Atmosphere and Surface, which aren’t the same. This prompts a new rule for me, I shall not publish any posts after midnight again (other than something scheduled previously during the day), because clearly I was too tired to recognize this mistake. I’ll add that I have emailed Dr. Allan regarding the question of feedback on hisfigure 7, and have not received a response. – Anthony]

Here’s the paper abstract, links to the full paper (which I located on the author’s website) follow.

Combining satellite data and models to estimate cloud radiative effect at the surface and in the atmosphere

Richard P. Allan

Abstract: Satellite measurements and numerical forecast model reanalysis data are used to compute an updated estimate of the cloud radiative effect on the global multi-annual mean radiative energy budget of the atmosphere and surface. The cloud radiative cooling effect through reflection of short wave radiation dominates over the long wave heating effect, resulting in a net cooling of the climate system of -21 Wm-2. The short wave radiative effect of cloud is primarily manifest as a reduction in the solar radiation absorbed at the surface of -53 Wm-2. Clouds impact long wave radiation by heating the moist tropical atmosphere (up to around 40 Wm-2 for global annual means) while enhancing the radiative cooling of the atmosphere over other regions, in particular higher latitudes and sub-tropical marine stratocumulus regimes. While clouds act to cool the climate system during the daytime, the cloud greenhouse effect heats the climate system at night. The influence of cloud radiative effect on determining cloud feedbacks and changes in the water cycle are discussed.

1. Introduction

Earth’s radiative energy balance (solar radiative energy absorbed and terrestrial radiation emitted to space) determines current patterns of weather and climate, the complexity of which is illuminated by satellite observations of the evolving distribution and diversity of cloud structures. Representing clouds and the physical processes responsible

for their formation and dissipation is vital in numerical weather and climate prediction, yet many approximations must be made in these detailed models of our atmosphere (e.g. Bony et al., 2006; Allan et al., 2007). Observations of cloud characteristics from satellite instruments and in situ or ground-based measurements are crucial for improving understanding of cloud processes and their impact on Earth’s radiative energy balance (Sohn, 1999; Jensen et al., 2008; Su et al., 2010). The energy exchanges associated with cloud formation and precipitation are also a key component of the global water cycle, of importance for climate change (Trenberth, 2011). In this paper, initially presented at a joint meeting of the Royal Meteorological Society and Institute of Physics on Clouds and Earth’s Radiation Balance (Barber, 2011), the utility of combining weather forecast model output with satellite data in estimating the radiative effect of cloud is highlighted. Using a combination of models and satellite data a simple question is addressed: how do clouds influence the radiative energy balance of the atmosphere and the surface.

As an example of the radiative impact of cloud, Figure 1 displays thermal infra-red and visible channel narrow-band images of the European region from the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on board the Meteosat-9 satellite (Schmetz et al., 2002).

In both images clouds appear bright: this denotes relatively low infra-red emission to space and relatively high reflection of visible sunlight to space. The hot, generally clear regions of northern Africa are also noticeable in both images since they are associated with substantial thermal emission to space (dark regions in the infra-red image) and high surface reflection from the desert surface (bright in the visible image). The brightest clouds in the thermal image correspond with (1) a trailing cold front extending from the coast of Norway, across Scotland and to the west of Ireland, (2) a developing low pressure system to the west of Iceland, and, (3) a low pressure system in the Mediterranean centred on Sardinia.

These are regions of ascending air with relatively high altitude, low temperature cloud tops which depress the thermal emission to space compared with surrounding regions. These features are also present in the visible image. However, many more cloud structures are also present. There is a prevalence of low altitude cloud over the oceans: this cloud contains large amounts of water droplets which are highly reflective (e.g. Stephens et al., 1978). The imagery captures the complex cellular structure of this cloud (e.g. Jensen et al., 2008) over the region surrounding the Canary Islands. These cloud types are thought to contribute strongly toward uncertainty in climate projections (Bony et al., 2006). While these clouds also strongly attenuate infra-red radiation, their impact on the thermal radiation escaping to space is modest since cloud-top temperatures are not dissimilar to the surface at night and so they do not contribute significantly to the strong natural greenhouse effect of the clear-sky atmosphere.

The altitude and optical thickness of cloud determines the overall radiative impact of cloud, a combination of the warming greenhouse effect and the surface-cooling solar

shading effect. Yet, probably an even stronger influence does not relate to the cloud itself. The time of day and time of year dictate the incident solar radiation and, therefore,

modulates the strength of the short wave reflection: clearly at night the solar influence of cloud is absent.

…

7. Conclusions

Exploiting satellite measurements and combining them with NWP models initialized through assimilation of available observations enables the effect of clouds on the Earth’s radiative energy balance at the surface and within the atmosphere to be quantified for the present day climate. Consistent with previous results (Ramanathan et al., 1989; Su et al., 2010), the cloud radiative cooling effect through reflection of short wave radiation is found

to dominate over the long wave heating effect, resulting in a net cooling of the climate system of −21 Wm−2.

The short wave radiative effect of cloud is primarily manifest as a reduction in the solar radiation absorbed at the surface of −53 Wm−2 for the global multi-annual mean. The magnitude of this effect is strongly modulated by the incoming solar radiation and the dominance of cloud short wave cooling over long wave greenhouse trapping is maximum around local noon (Nowicki and Merchant, 2004) while the cloud long wave heating effect dominates at night.

The long wave greenhouse effect of cloud measured at the top of the atmosphere is manifest primarily as a heating of the atmosphere in the moist tropics, consistent with calculations by Sohn (1999).

Over the marine stratocumulus regions and across higher latitudes the cloud-base emission to the surface becomes substantial and dominates over the reduced outgoing long wave radiation to space resulting in enhanced radiative cooling of the atmosphere and heating of the surface. The cloud radiative influence on the exchange of radiative fluxes between the atmosphere and the surface are intimately linked with the water cycle through radiativeconvective balance. While tropical, high-altitude clouds act to stabilize the atmospheric profile radiatively, clouds over polar regions tend to cool the atmosphere while heating the surface through enhanced atmospheric longwave radiative emission to the surface. In future work it would be informative to categorize these effects by cloud type further (e.g. Futyan et al., 2005) and compare with climate model simulations. These analyses are vital in constraining cloud feedback processes further and in linking to future changes in the water cycle (Stephens, 2005; Bony et al., 2006; John et al., 2009).

A particular challenge is the accurate quantification of surface radiative fluxes due to the sparse ground-based observing network (Roesch et al., 2011) and also monitoring current changes in cloud radiative effect in satellite data, reanalyses and models (Wielicki et al., 2002); combining meteorological reanalyses with satellite data and surface observations provide a vital methodology for meeting these challenges.

Abstract is here: http://onlinelibrary.wiley.com/doi/10.1002/met.285/abstract

Full paper is here: http://www.met.reading.ac.uk/~sgs02rpa/PAPERS/Allan11MA.pdf

UPDATE: Some people in comments including Dr. Roy Spencer, (and as I was writing this, Dr. Richard Allan) suggest that the paper isn’t about feedback (at least in the eyes of IPCC interpretations, but Spencer adds “it could be”). Thus I’ve removed the word from the headline to satisfy such complaints. My view is that clouds are both a feedback and a forcing. Others disagree. That’s an issue that will occupy us all for sometime I’m sure.

Regarding cloud feedbacks, here’s what I noted in the paper in section 6, near the end. Allan is referring to figure 7 which shows (a) net radiation and (b) net cloud radiative forcing:

Substantial negative anomalies in net radiative flux from ERA Interim are apparent in 1998 and 2010, both El Niño years, suggesting that the substantial re-organization of atmospheric and oceanic circulation systems act to remove energy from Earth during these periods.

You can clearly see the famous double peak in the 1998 El Niño, but it is inverted. To me that looks like a thermostat action, and not one with stuck electrical contacts, i.e. a negative feedback. I’ve also updated the text related to the incorrect comparison I made. – Anthony

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