The Coming Climate July 4 Update

Update July 4 below

When you see a graph like that below, it is obvious that an unusually strong El Nino just happened in our climate system. It resulted in higher global temperatures the last two years and so far in 2016. But that event is over now, and naturally we wonder what to expect in the months and years ahead.

cdas_v2_hemisphere_2016june2
For example some comments from a recent thread at WUWT (here) were intriguing:

It will be interesting to see what comes next. The major difference between the 1998 el nino and this one is that in 1998 the sun was increasing in solar activity, while this one solar activity is decreasing. (rishrac)

Nino3,4 and UAH LT dC Anomalies, and UAH LT Scaled *3 and Lagged 4 Months h/t Allan MacRae

And richard takes the long view of the situation:

While we all stare at the short-term ups and downs of the global temperatures, pay a little thought to the fact that the Earth’s orbit around the Sun causes snow in the winter and warmth during the summer, so it may be important?

Perihelion presently occurs around January 3, (Northern hemisphere winter, Southern summer) while aphelion is around July 4. Therefore, the southern hemisphere receives more solar radiation and is therefore warmer in summer and colder in winter (aphelion). The Northern hemisphere has cooler summers and milder winter (solar radiation-wise).

Also the northern hemispheres autumn and winter are slightly shorter than spring and summer, because the Earth is moving faster around the Sun in winter slower in summer.

This alone could account for “Global Warming” attributed to CO2, (which no doubt plays some part in it).

Over the next 10,000 years, northern hemisphere winters will become gradually longer and summers will become shorter, due to the change in the Earth’s Orbital Eccentricity.

Couple this with changes in the Earth’s tilt, which varies from 22.1 degrees to 24.5 degrees, (currently at 23.4 degrees). More tilt means more solar radiation gets to the poles (global warming) and less tilt means less radiation gets to the poles (global cooling). The last maximum tilt occurred in 8700 BC (Holocene maximum) and the next minimum tilt will happen in 11,800 AD (the advance of the ice sheets), precisely at the time of longer northern winters and shorter summers.

Orbital Climate Factors: E for eccentricity, T for tilt, and P for precession

Predicting the Future is Tough

Chiefio (E.M. Smith) has a good post (here) reminding us that statistical projections do not help us much in this case. Temperature series produced by our climate system have special qualities. The patterns are auto-correlated, meaning that tomorrow’s weather will be similar to today’s; the occurrence is not totally independent, like the flip of coin. IOW there is momentum in the climate characteristics, which can and do fluctuate over seasons, decades, centuries and more. Our attempts to use linear regressions to forecast are thwarted by temperature time series that do not follow a normal gaussian distribution, and are semi-chaotic and non-stationary.

Four Possibilities Forward From Today

From past experience, the next few years could logically follow one of four temperature scenarios:
1. The Plateau since 1998 continues.
2. The Warming prior to 1998 resumes.
3. A new Plateau begins with 2016 at a higher (step up) level.
4. A Cooling begins comparable to the years after 1940.

All of these have analogues in our recent climate observations. If this now finished El Nino triggers a regime change comparable to the 1998 event, then a step-up plateau can result. If warmists are right, and there is a release of pent-up heat in the system, then a warming trend would resume.

If this El Nino is not strong enough to shift the regime, then the Plateau could continue at the same level. Finally, it could be that several factors align to reverse the warming since the 1970’s, and bring a return to cooler 1950’s weather.

Those who see a quasi-60 year cycle in weather patterns note that it is about time for the PDO in the Pacific and the AMO in the Atlantic to be in cooler phases, along with a quiet sun, which went spotless last week. There are also those attending to orbital climate patterns, which gave us the Modern Warming Period and will eventually take it away.

 

Changes in climate due to earth’s orbit around the sun

Update July 4

In the previous thread is a chart from J. Martin displaying the effects of the changing tilt of earth’s axis.  As shown, the long term pattern is toward cooling.

J. Martin: Tilt (obliquity) has a 41k yr cycle and prior to the arrival of 100,000 year glaciations, the 41k year world dominated with short sharp glaciations every 41 thousand years. The 41k influence us still there. Javier has done a graph which overlays the obliquity cycle on top of a graph of the holocene which produces a perfect match. So it would seem that interstitial temperatures are largely governed by obliquity, but glaciation temperatures are governed by eccentricity with occasional disturbances from precession .

In addition, ren provides interesting links to studies showing SA (Sunspot numbers) correlating to Middle Ages Warm period and LIA, and a 2012 study forecasting the next 2 cycles.

shepherd etalfig1

Figure 1. Bottom plot: the summary component of the two PCs (solid curve) and the decaying component (dashed curves) for the “historical” data (cycles 21–23) and predicted data (cycles 24–26). The cycle lengths (about 11 yr) are marked with different colors.

Abstract: We can conclude with a sufficient degree of confidence that the solar activity in cycles 24–26 will be systematically decreasing because of the increasing phase shift between the two magnetic waves of the poloidal field leading to their full separation into opposite hemispheres in cycles 25 and 26. This separation is expected to result in the lack of their subsequent interaction in any of the hemispheres, possibly leading to a lackof noticeable sunspot activity on the solar surface lasting for a decade or two, similar to those recorded in the medieval period.

Again, to the extent that SSNs are a proxy for changes in heat content within the earth’s climate system, the graph is also indicating future cooling.

For an approach to quantifying climate effects from Solar Activity, as well as oceanic cycles, see:
Quantifying Natural Climate Change

Think Global Act Local, or Not

The slogan “Think Global, Act Local” began with multinational corporations realizing that national and regional markets around the world had distinct needs and preferences requiring accommodations. As the name implies it refers to the corporate strategy by which a global viewpoint is adopted in terms of formulating company vision, long-term aims and objectives and devising effective programs to achieve these aims and objectives, however, adaptations are made in each market according to the culture and specifications of any specific market.

Environmental activists took the notion on board during the first wave becoming aware of globalization. Early bearers of the catchphrase were for the most part supporters of an environmental movement that supported individual activism. The theory behind the saying was that in order to make large-scale global movements stick, the responsibility lay on individuals to carry out progressive practices – like environmental stewardship – in their own homes. The globe had become the new frame of reference for some far-thinking activists.

Clearly “climate change” activism operates in this mode. But as we shall see in this essay, the top-down, Global-Local approach to understanding climate and weather leads to distortions and misconceptions. In fact, climate science itself is best served by observing and establishing principles from the bottom up.

It turns out that the climate system is one of those things where averages do not tell very much, and can be misleading. For example:

Look at precipitation around the world

About 1 meter a year is the nominal average of all rain over all surfaces. Some places get up to 10 meters of rain (about 400 inches ) and others get near none. 47% of the earth is considered dryland, defined as anyplace where the rate of evaporation/transpiration exceeds the rate of precipitation. A desert is defined as a dryland with less than 25 cm of precipitation. In the image above, polar deserts are remarkably defined. It just does not have much hope of precipitation as there is little heat to move the water. More heat in, more water movement. Less heat in, less water movement.

Then there’s the seasonal patterns. The band of maximum rains moves with the sun: More north in June, more south in December. More sun, more heating, more rain. Movement in sync with the sun, little time delay. Equatorial max solar heat has max rains. Polar zones minimal heating, minimal precipitation. It’s a very tightly coupled system with low time lags.

Then Look at Temperatures

Average temperatures in F at sea level by longitude and latitude. Source: Lyndon State College Meteorology

Notice:

  • latitudinal change
  • N.H. – difference between land and ocean
  • U.S. west coast (upwelling and cold current) v.s. U.S. east coast (gulf stream)
  • influence of gulf stream in north Atlantic
  • highest temps are in the subtropical N.H. desert regions
  • west coast of S. America is cool while the east coast is warm, due to the ocean currents
  • much less variability in the zonal direction in the S. H.

And look at clouds and their radiative effects

The large opacity of cloud increases the optical depth of the atmosphere, introducing warming in the LW energy budget. This warming varies with cloud-top temperature and height. For SW radiation, the high reflectivity of cloud decreases the incoming solar flux, favoring reduced surface temperature. Cloud routinely covers about 50% of the Earth. It accounts for about half of the Earth’s albedo (eg, for ∼0.15). Source: Salby 2012 pg315

Globally averaged values of CLW and CSW are about 30 and −45 W m−2, respectively. Net cloud forcing is then −15 W m−2. It represents radiative cooling of the Earth-atmosphere system. This is four times as great as the additional warming of the Earth’s surface that would be introduced by a doubling of CO2.

But clearly during Northern winter (diagrams above), that net cooling occurs largely over the Southern Ocean around Antarctica.

What happens when you average all this diversity?

We have all seen graphs showing how climate models project unrealistic global mean temperatures higher than those measured by stations or satellites. But Dr. Salby in his textbook points to a more fundamental failing of the climate simulations.  By construction they balance global average energy budgets, but regional realities are grossly distorted.

From IPCC Working Group 1 AR4

Figure 8.4. Root-mean-square (RMS) model error, as a function of latitude, in simulation of (a) outgoing SW radiation reflected to space and (b) outgoing LW radiation. The RMS error is calculated over all longitudes and over all 12 months of a climatology formed from several years of data. . .The Earth Radiation Budget Experiment (ERBE; Barkstrom et al., 1989) observational estimates used here are for the period 1985 to 1989 from satellite-based radiometers, and the model results are for the same period in the 20th-century simulations in the MMD at PCMDI.

Symbolizing the local energy budget is net radiation (Fig. 1.34c), which represents the local imbalance between the SW and LW fluxes F0 and F ↑(0) in the TOA energy budget (8.82). Local values of those fluxes have been measured around the Earth by the three satellites of ERBE. The observed fluxes, averaged over time, have then been compared against coincident fluxes from climate simulations, likewise averaged. Figure 8.34 plots, for several GCMs, the rms error in simulated fluxes, which have been referenced against those observed by ERBE.

Values represent the regional error in the (time-mean) TOA energy budget. The error in reflected SW flux, Fs 4 − F0 in the global mean (8.82), is of order 20 Wm−2 (Fig. 8.34a). Such error prevails at most latitudes. Differences in error between models (an indication of intermodel discrepancies) are almost as large, 10–20 Wm−2. The picture is much the same for outgoing LW flux (Fig. 8.34b). For F ↑(0), the rms error is of order 10–15 Wm−2. It is larger for all models in the tropics, where the error exceeds 20 Wm−2. . .Consequently, the simulated change introduced by increased CO2 (2–4 Wm−2), even inclusive of feedback, is overshadowed by error in the simulated change of major absorbers.

By construction, GCMs achieve global-mean energy balance. How faithfully the energy budget is represented locally, however, is another matter. The local energy budget forces regional climate, along with the gamut of weather phenomena that derive from it. This driver of regional conditions is determined internally – through the simulation of local heat flux, water vapor, and cloud.  (My bold)

Conclusion

A common expression is: “The devil is in the details.” When it comes to climate, it is truer to say that we humans are bedeviled (thwarted) by nature’s details refusing to fit into our global generalities. The proper role of science is to investigate those details and revise our mental constructs.

“Global Climate” is an oxymoron.
(oxymoron: A figure of speech in which two words with opposing meanings are used together intentionally for effect; IOW a contradiction in terms. From the Greek: pointed foolishness).

Climates are plural, not global, as the Koppen system makes clear. There are hundreds of regional climate zones defined empirically by temperature and precipitation patterns. And the observational data shows those zones are highly stable; that is, fears of climate change rarely appear in any actual climates showing shifting boundaries. See post: Data vs. Models 4: Climates Changing

Thus, we are better advised to:

Think Local Climates,
Prepare Local Adaptations
for the range of future weather consequences.

Fearless Physics from Dr. Salby

 

“Fearless Felix” Baumgartner ascended to the stratosphere and stepped into the void from 24.2 miles above the Earth. His speed during the fall reached Mach 1.24, and the Austrian adventurer nailed the landing. October 14, 2012 Wired 

Introduction
Murry Salby is also totally committed to the atmosphere. He is a scientist with such deep and broad knowledge of atmospheric physics that he has written multiple textbooks on the subject. And yet he is not fearful for the future of our climate system, in contrast to many of his colleagues. By stepping away from “consensus” climate alarms, he has shown unusual courage by speaking plainly about the atmosphere and climate, despite attempts to silence him.

Dr. Salby’s latest textbook is entitled Physics of the Atmosphere and Climate (here). I got a copy and have been reading in it to understand where he comes down on various issues related to climate change. In particular I wanted to know what explains his divergence from IPCC climate scientists.
H/T to Kenneth Richard and No Tricks Zone

Synopsis

In reading the textbook, I find two main reasons why Salby is skeptical of AGW (anthropogenic global warming) alarm. This knowledgeable book is an antidote to myopic and lop-sided understandings of our climate system.

  1. CO2 Alarm is Myopic: Claiming CO2 causes dangerous global warming is too simplistic. CO2 is but one factor among many other forces and processes interacting to make weather and climate.

Myopia is a failure of perception by focusing on one near thing to the exclusion of the other realities present, thus missing the big picture. For example: “Not seeing the forest for the trees.”  AKA “tunnel vision.”

2. CO2 Alarm is Lopsided: CO2 forcing is too small to have the overblown effect claimed for it. Other factors are orders of magnitude larger than the potential of CO2 to influence the climate system.

 

Lop-sided refers to a failure in judging values, whereby someone lacking in sense of proportion, places great weight on a factor which actually has a minor influence compared to other forces. For example: “Making a mountain out of a mole hill.”

Overview

Salby’s textbook presents all of the physical complexity of the climate system in contrast to simplistic global warming theory. And he provides his sense of the Scales of the various processes, balancing any lopsided overemphasis on CO2 effects.

From the Preface:
Despite technological advances in observing the Earth-atmosphere system and in computing power, strides in predicting its evolution reliably – on climatic time scales and with regional detail – have been limited. The pace of progress reflects the interdisciplinary demands of the subject. Reliable simulation, adequate to reproduce the observed record of climate variation, requires a grasp of mechanisms from different disciplines and of how those mechanisms are interwoven in the Earth-atmosphere system.

What is today labeled climate science includes everything from archeology of the Earth to superficial statistics and a spate of social issues. Yet, many who embrace the label have little more than a veneer of insight into the physical processes that actually control the Earth-atmosphere system, let alone what is necessary to simulate its evolution reliably. Without such insight and its application to resolve major uncertainties, genuine progress is unlikely.

The atmosphere is the heart of the climate system, driven through interaction with the sun, continents, and ocean. It is the one component that is comprehensively observed. For this reason, the atmosphere is the central feature against which climate simulations must ultimately be validated.

The treatment focuses upon physical concepts, which are developed from first principles. It integrates five major themes:
1. Atmospheric Thermodynamics;
2. Hydrostatic Equilibrium and Stability;
3. Radiation, Cloud, and Aerosol;
4. Atmospheric Dynamics and the General Circulation;
5. Interaction with the Ocean and Stratosphere.

Lessons from Dr. Salby:  Essential Elements of a Balanced Climate Understanding

Below I show some of the written statements from the textbook to illustrate how his knowledge counteracts myopic and lopsided thinking.

Focusing on CO2 from burning fossil fuels is myopic: A multitude of natural sources drive atmospheric concentrations.

Plate 24 Estimated global carbon cycle, illustrating stores of carbon,
in GtC, and transfers in GtC/yr, where 1 GtC=109 tons of carbon.
Source: Design by Philippe Rekacewicz, UNEP/GRID-Arendal (11.07.10).

Pg.545-6
The storage of CO2 is illustrated in Fig. 17.11. Except for deep sedimentary rock, which is sequestered, most of the carbon is stored in the ocean. It accounts for some 40,000 gigatons (1012 kg) of carbon (GtC), in the form of dissolved CO2 and organic matter. Most resides in the deep ocean, where cold water supports the greatest observed concentrations. There, dissolved CO2 is controlled by the thermohaline circulation. Land and the adjoining biosphere account for only about 2000 GtC. The atmosphere contains less than 1000 GtC, concentrated in CO2. Hence, the store of carbon in the ocean is two orders of magnitude greater than the store in the atmosphere.

Equally significant are transfers of carbon into and out of the ocean. Of order 100 GtC/yr, they exceed those into and out of land. Together, emission from ocean and land sources (∼150 GtC/yr) is two orders of magnitude greater than CO2 emission from combustion of fossil fuel. These natural sources are offset by natural sinks, of comparable strength. However, because they are so much stronger, even a minor imbalance between natural sources and sinks can overshadow the anthropogenic component of CO2 emission (cf Secs 1.6.2, 8.7.1).

The values in Fig. 17.11 can be used to estimate the effective turnover time of atmospheric CO2. At an absorption rate of 100 GtC/yr, the ocean will absorb the atmospheric store of CO2 of 1000 GtC in about a decade. That absorption of CO2, which is concentrated in cold SST at polar latitudes, is nearly offset by emission of CO2 from warm SST at tropical latitudes. Warming of SST (by any mechanism) will increase the outgassing of CO2 while reducing its absorption. Owing to the magnitude of transfers with the ocean, even a minor increase of SST can lead to increased emission of CO2 that rivals other sources (Sec. 8.7.1). Further, if the increase of SST involves heat transfer with the deep ocean, the time for equilibrium to be reestablished would be centuries (Sec. 17.1.2).

Attributing rising temperatures to fossil fuels is lop-sided: Natural sinks respond to warming by releasing CO2 in far greater quantities.

Net emission rate of CO2, r˙ CO2 = d dt rCO2 (ppmv/yr), derived from the Mauna Loa record (Fig. 1.15), lowpass filtered to changes that occur on time scales longer than 2 years (solid). Superimposed is the satellite record of anomalous Global Mean Temperature (Fig. 1.39), lowpass filtered likewise and scaled by 0.225 (dashed). Trend in GMT over 1979–2009 (not included) is ∼0.125 K/decade.

Pg.65ff
Net emission of CO2 closely tracks the evolution of GMT. Achieving a correlation of 0.80, the variation of GMT accounts for most of the variance in CO2 emission.

Plotted in Fig. 1.43b is the rate of change in isotopic composition, d dt δ13C = ˙ δ13C (solid).12 Its mean is negative, consistent with the long-term decline of δ13C in ice cores (Fig. 1.14). However, like emission of CO2, differential emission of 13CO2 varies substantially from one year to the next. It too tracks the evolution of GMT – just out of phase. When GMT increases, emission of 13CO2 decreases and vice versa. The records achieve a correlation of −0.86. Hence the variation of GMT, which accounts for most of the variance in emission of CO2, also accounts for most of the variance in differential emission of 13CO2.

The out-of-phase relationship between rCO2 and δ13C in the instrumental record (Fig. 1.43) is the same one evidenced on longer time scales by ice cores (Fig. 1.14). The out-of-phase relationship in ice cores is regarded as a signature of anthropogenic emission, subject to uncertainties (Sec. 1.2.4). The out-of-phase relationship in the instrumental record, however, is clearly not anthropogenic. Swings of GMT following the eruption of Pinatubo and during the 1997–1998 El Nino were introduced through natural mechanisms (cf. Figs 1.27; 17.19, 17.20). Changes in Fig. 1.43 reveal that net emission of CO2, although 13C lean, is accelerated by increased surface temperature. Outgassing from ocean, which increases with temperature (Sec. 17.3), is consistent with the observed relationship – if the source region has anomalously low δ13C. So is the decomposition of organic matter derived from vegetation. Having δ13C comparable to that of fossil fuel, its decomposition is likewise accelerated by increased surface temperature.

Focusing on CO2 as the greenhouse gas of concern is both myopic and lop-sided: H20 makes 98% of the IR radiative activity in the atmosphere.

Pg. 47
The radiative-equilibrium surface temperature Ts is significantly warmer than that in the absence of an atmosphere.

The discrepancy between Ts and Te follows from the different ways the atmosphere processes SW and LW radiation. Although nearly transparent to SW radiation (wavelengths λ ∼ 0.5 μm), the atmosphere is almost opaque to LW radiation (λ ∼ 10 μm) that is re-emitted by the Earth’s surface. For this reason, SW radiation passes relatively freely to the Earth’s surface, where it can be absorbed. However, LW radiation emitted by the Earth’s surface is captured by the overlying air, chiefly by the major LW absorbers: water vapor and cloud. Energy absorbed in an atmospheric layer is reemitted, half upward and half back downward. The upwelling re-emitted radiation is absorbed again in overlying layers, which subsequently re-emit that energy in similar fashion. This process is repeated until LW energy is eventually radiated beyond all absorbing components of the atmosphere and rejected to space. By inhibiting the transfer of energy from the Earth’s surface, repeated absorption and emission by intermediate layers of the atmosphere traps LW energy, elevating surface temperature over what it would be in the absence of an atmosphere.

Pg. 247ff
The residual, +1.5 Wm−2, represents net warming. It is about 0.5% of the 327 Wm−2 of overall downwelling LW radiation that warms the Earth’s surface (Fig. 1.32). The vast majority of that warming is contributed by water vapor. Together with cloud, it accounts for 98% of the greenhouse effect. How water vapor has changed in relation to changes of the comparatively minor anthropogenic species (Fig. 8.30) is not known. The additional surface warming introduced by anthropogenic increases in greenhouse gases amounts to about 75% of that which would be introduced by a doubling of CO2. Arrhenius’ estimate of 5–6◦ K for the accompanying increase of surface temperature (Sec. 1.2.4) then translates into ∼4◦ K. Yet, the observed change of global-mean temperature since the mid nineteenth century is only about 1◦ K (Sec. 1.6.1). The discrepancy points to changes of the Earth-atmosphere system (notably, involving the major absorbers, water vapor and cloud) that develop in response to imposed perturbations, like anthropogenic emission of CO2.

Focusing on CO2 radiative activity is myopic: The tropospheric heat engine comprises many powerful heat transfer processes.

Cloud Forcing

Figure 9.40 Cloud radiative forcing during northern winter derived from ERBE measurements on board the satellites ERBS and NOAA-9 for the (a) LW energy budget, (b) SW energy budget, and (c) net radiative energy budget. Courtesy of D. Hartmann (U. Washington).

Pg. 318ff
A quantitative description of how cloud figures in the global energy budget is complicated by its dependence on microphysical properties and interactions with the surface. These complications are circumvented by comparing radiative fluxes at TOA under cloudy vs clear-sky conditions. Over a given region, the column-integrated radiative heating rate must equal the difference between the energy flux absorbed and that emitted to space.

The components of cloud forcing (9.53) can be evaluated directly from broadband fluxes of outgoing LW and SW radiation that are measured by satellite. Figure 9.40 shows time-averaged distributions of CSW , CLW , and C. Longwave forcing (Fig. 9.40a) is large in centers of deep convection over tropical Africa, South America, and the maritime continent, where CLW approaches 100 W m−2 (cf. Fig. 1.30b). Secondary maxima appear in the maritime ITCZ and in the North Pacific and North Atlantic storm tracks (Sec. 1.2.5). Shortwave forcing (Fig. 9.40b) is strong in the same regions, where CSW < −100 W m−2. Negative SW forcing is also strong over extensive marine stratocumulus in the eastern oceans and over the Southern Ocean, coincident with the storm track of the Southern Hemisphere. Inside the centers of deep tropical convection, SW and LW cloud forcing nearly cancel. They leave small values of C throughout the tropics (Fig. 9.40c). Negative CSW in the storm tracks and over marine stratocumulus then dominates positive CLW , especially over the Southern Ocean. It prevails in the global-mean cloud forcing. Globally averaged values of CLW and CSW are about 30 and −45 W m−2, respectively.

Net cloud forcing is then −15 W m−2. It represents radiative cooling of the Earth-atmosphere system. This is four times as great as the additional warming of the Earth’s surface that would be introduced by a doubling of CO2. Latent heat transfer to the atmosphere (Fig. 1.32) is 90 W m−2. It is an order of magnitude greater. Consequently, the direct radiative effect of increased CO2 would be overshadowed by even a small adjustment of convection (Sec. 8.7).

Trusting climate models driven by CO2 sensitivity is lop-sided: Natural climate factors are poorly quantified but are orders of magnitude larger than estimated CO2 effects.

Pg. 260
Global climate models are sophisticated extensions of the idealized models considered above. Treatments of climate properties in different GCMs are as varied as they are complex. For some properties, like cloud cover, ice, and vegetation, they must resort to empirical relationships or simply ad hoc parameterization. For others, the governing equations cannot even be defined. Together with the ocean simulation, these limitations introduce errors, which can be substantial. Along with discrepancies between GCMs, they leave in question how faithfully climate feedbacks are represented (see, e.g., Tsushima and Manabe, 2001; Lindzen and Choi, 2009).

fig-8-04-724x1024

The accuracy of GCMs is reflected in the skill with which they simulate the TOA energy budget: the driver of climate. By construction, GCMs achieve global-mean energy balance. How faithfully the energy budget is represented locally, however, is another matter. The local energy budget forces regional climate, along with the gamut of weather phenomena that derive from it. This driver of regional conditions is determined internally – through the simulation of local heat flux, water vapor, and cloud. Symbolizing the local energy budget is net radiation (Fig. 1.34c), which represents the local imbalance between the SW and LW fluxes F0 and F ↑(0) in the TOA energy budget (8.82). Local values of those fluxes have been measured around the Earth by the three satellites of ERBE. The observed fluxes, averaged over time, have then been compared against coincident fluxes from climate simulations, likewise averaged. Figure 8.34 plots, for several GCMs, the rms error in simulated fluxes, which have been referenced against those observed by ERBE.

Values represent the regional error in the (time-mean) TOA energy budget. The error in reflected SW flux, Fs 4 − F0 in the global mean (8.82), is of order 20 Wm−2 (Fig. 8.34a). Such error prevails at most latitudes. Differences in error between models (an indication of intermodel discrepancies) are almost as large, 10–20 Wm−2. The picture is much the same for outgoing LW flux (Fig. 8.34b). For F ↑(0), the rms error is of order 10–15 Wm−2. It is larger for all models in the tropics, where the error exceeds 20 Wm−2.

The significance of these discrepancies depends on application. Overall fluxes at TOA are controlled by water vapor and cloud (Fig. 1.32) – the major absorbers that account for the preponderance of downwelling LW flux to the Earth’s surface. Relative to those fluxes, the errors in Fig. 8.34 are manageable: Of order 10% for outgoing LW and 20% for reflected SW. Relative to minor absorbers, however, this is not the case. The entire contribution to the energy budget from CO2 is about 4 Wm−2. Errors in Fig. 8.34 are an order of magnitude greater. Consequently, the simulated change introduced by increased CO2 (2–4 Wm−2), even inclusive of feedback, is overshadowed by error in the simulated change of major absorbers.

Conclusion:

Pg. 262
Discrepancies between GCMs arise from inaccuracies in climate properties and from differences in how those properties are represented. Much of the discrepancy surrounds the representation of convection and its influence on water vapor and cloud, the absorbers that account for most of the downwelling LW flux to the Earth’s surface. The involvement of convection is strongly suggested by models of radiative-convective equilibrium. Those simulations are inherently sensitive to how convection and cloud are prescribed. Cloud is especially significant to radiative considerations because it sharply modifies the atmosphere’s scattering characteristics, which determine albedo, and its absorption characteristics, which determine optical depth.

Footnote:

Best wishes to Dr. Salby and much appreciation for telling it like it is.  May you also nail your landing as did Fearless Felix.

h/t malagabay

Historic Climate Change

Orbital Climate Factors: E for eccentricity, T for tilt, and P for precession

My recent post The Coming Climate included a description of the orbital factors inducing natural cycles of warming and cooling far larger than any possible effect from CO2.

Yesterday commenter Alberto Zaragoza Comendador took this further into a discussion of the uncertainties in paleoclimatology. He started by referring to a paper by Lindzen, which focused on only one of these dynamics: fluxes of equator-to-pole heat transport.

Lindzen et al. 1993 concluded:
The present note shows the importance of aspects of the forcing which lead to changes in meridional (i.e., tropics to higher latitudes) heat fluxes. These aspects are seasonal, and involve the distribution of heating; they do not necessarily involve changes in globally and/or annually averaged insolation. Thus, simple, commonly used notions of climate sensitivity as employed in Houghton et al. (1990) are not relevant. Indeed, the present mechanism can readily produce major changes in climate (including, as a by product, changes in the globally averaged temperature) in systems which are profoundly insensitive to a doubling of CO2. To assume (as was done in Hoffert and Covey 1992, for example) that major climate changes necessarily require high sensitivity to such changes in gross averaged forcing is clearly inappropriate.

The full text of comment by Comendador is below from Climate Etc. (here)

Alberto Zaragoza Comendador | June 11, 2016 at 3:19 pm |

Somebody mentioned Milankovitch which reminded me of other thing.

http://www-eaps.mit.edu/faculty/lindzen/171nocephf.pdf (Lindzen et al 1993)

Check out the last paragraph. It explains why every paleo estimate of sensitivity is hopeless: even if you knew the temperatures, which you don’t really but even if you did, you’d have no idea what caused them. Lindzen uses the example of equator-to-pole heat transport but there are many more things that can cause climate to change, and we mostly know nothing about how they affected climate in the past.

We have records of methane and CO2, but we don’t have records of cloud albedo, ozone, water vapor, vegetation… someone might quibble that we do have some records of vegetation and dust for example, but unlike CH4 and CO2 you cannot assume these dust or vegetation ‘levels’ applied globally.

(Hell, until recently the greening trend of the last half-century was in dispute, even though we can look at the world’s plants and trees with seven billion pairs of eyes plus a few billion cameras, including some mounted on satellites. To assume we can now estimate greening or browning trends from twenty thousand years ago is preposterous.)

And we have estimates of how much area was covered in ice, but we have no idea how much dust that ice was covered with, or if the radiative forcing one could expect from the ice was really ‘apples to apples’ (i.e. of the same efficacy) as that of CO2. Now we know that as sea ice recedes the Arctic gets cloudier so the overall effect is about 1/3 of what you would expect simply looking at the decline in ice; we have no idea if the same thing would happen upon the disappearance of an ice sheet because we have never observed such a thing. Until recently we thought Greenland was reflecting less sunlight because it was getting dustier; it then turned out that, rather, the satellites’ sensors were getting degraded.

We still have little idea how aerosols affect climate… yet some guys are trying to model the aerosols of the past. And they’re not even the same kind (today the main agent is sulphuric acid, before dust).

(It’s funny that the ‘forcing efficacy’ issue has been raised about instrumental studies, and not about paleo papers that would be devastated if efficacy really changed much between forcing agents. For example, only about 20% of the forcing in LGM reconstructions is CO2).

You cannot simply assume that whatever change in GHG concentration (or other ‘forcings’) took place at the time of these temperature changes was responsible for said changes. In fact, by excluding other factors (which you know nothing about) you will systematically overestimate sensitivity. That’s why paleo sensitivity disagrees with both energy budget and inter-annual (ERBE/CERES) estimates. It also explains in part why the range of sensitivity in paleo is so wide.

Admittedly this is also a strike against sensitivity estimates using the instrumental record, but less so – because we have observations that allow us to rule out a good many ‘natural’ causes of climate change. We know that in the last 150 years the AMOC hasn’t shut down and there hasn’t been a massive change in equator-to-pole heat transfer. We know that since 1980 the amount of cloud cover has remained more or less the same, within a 5% band; the warming trend since then would be very difficult to explain from changes in cloud cover alone. And so on.

Whenever one mentions natural climate change the response from a certain side is something like ‘the ocean cannot create heat’ or ‘the clouds cannot change by themselves’. While technically true these statements are meaningless and reveal at best ignorance and at worst deception. All climate changes will involve a radiative change at some point, but said radiative change (forcing, feedback, whatever you call it) does NOT have to originate from a radiative source. It can all start with a change in air currents, or ocean currents, or tree cover, or sea ice, or methane emissions from bacteria, or…

Asking ‘yeah but what caused the clouds to change?’ is like asking why are there planets.

The best example of non-radiative climate change is in fact Milankovitch cycles, which affect not the amount but the distribution of sunlight (well eccentricity changes the amount of sunlight, but precession and tilt don’t). Technically speaking, the forcing is zero; paleo estimates consider GHGs, ice sheets and vegetation/dust forcings but if one is strict they should be considered feedbacks. Sensitivity, calculated the way it’s done for observational estimates, would be infinite.

You can also see how simply switching one of these radiative ‘things’ from forcing to feedback, or viceversa, can allow a researcher to arrive at a radically different sensitivity number. It’s all meaningless.

The one advantage of the paleo method is that since there is enough time for the ocean to reach equilibrium you avoid that source of uncertainty. But that also means you cannot use it to estimate TCR.

Anyway, as time goes on the estimates of aerosol forcing and heat uptake will get better and better. The instrumental studies will arrive at a number, if not for what sensitivity ‘is’, at least for what it has been for the last 150 years. The paleos will never arrive at anything.

Conclusion:

Thanks Alberto for that summation.  It deserves wide appreciation

Geological Time Spiral

Geological Time Spirial

Wave Drowns CO2 Warming

Update May 13 below

This post presents key findings from the recently published paper:
Anthropogenic CO2 warming challenged by 60-year cycle (here) by
François Gervais
Department of Physics, Faculty of Sciences & Techniques, François Rabelais University, Parc de Grandmont, 37200 Tours, France

In the synopsis below, Gervais puts his study in context, followed by his conclusions.

The Global Warming Debate Rages

The impact on climate of the CO2 emitted by burning of fossil fuels is a long-standing debate illustrated by 1637 papers found in the Web of Science by crossing the keywords

“anthropogenic” AND “greenhouse OR CO2” AND “warming”

This is to be compared to more than 1350 peer-reviewed papers which express reservations about dangerous anthropogenic CO2 warming and/or insist on the natural variability of climate.

Signatures of 60-year Climate Wave

Time series of sea-level rise are fitted by a sinusoid of period ~ 60 years, confirming the cycle reported for the global mean temperature of the earth. This cycle appears in phase with the Atlantic Multidecadal Oscillation (AMO). The last maximum of the sinusoid coincides with the temperature plateau observed since the end of the 20th century. A 60-year climate cycle is confirmed in sea-level rise and global sea ice area, as well as in measured temperature series.

Onset of the Declining Phase

The four following indicators sign for the onset of the declining  phase of the 60-year cycle.

  1. The recent change of sign of global sea ice area anomaly which
    reveals an excess in Fig. 3, a sensitive indicator of climate, is unexpected
    from model projections (AR5, 2013).
  2. The AMO index indicates the onset of a declining phase.
  3. A negative temperature slope is measured from 2002 to 2015 independently by different satellites in the low troposphere by Remote Sensing System (RSS, 2015) and by UAH (Spencer et al., 2015) as shown in Fig. 4. The plot is voluntarily restricted to 13 years, viz. less than 1/4 of the 60 year-cycle, to evaluate the sign of the tangent to the sinusoid.
  4. A deceleration of the sea-level rise measured by satellite altimetry is also found since 2002 (Chen et al., 2014; Cazenave et al.,2014).

Rising Temperatures cause rising CO2

The correlation of yearly CO2 increase, therefore, appears not with MEI or SOI but with global mean temperature to which El Niño and La Niña contribute. This temperature/CO2 correlation may be tentatively explained, at least partly, by the solubility of CO2 into water which decreases with temperature, consistent with sea pH maps (Byrne et al., 2010). Warm temperature fluctuations favor CO2 release from the oceans which contain 60 times more CO2 than the atmosphere (AR5, 2013), whereas cooler fluctuations favor its oceanic Capture.

Summary: 60-year Wave Rules

Dangerous anthropogenic warming is questioned (i) upon recognition of the large amplitude of the natural 60–year cyclic component and (ii) upon revision downwards of the transient climate response consistent with latest tendencies shown in Fig. 1, here found to be at most 0.6 °C once the natural component has been removed, consistent with latest infrared studies (Harde, 2014). Anthropogenic warming well below the potentially dangerous range were reported in older and recent studies. On inspection of a risk of anthropogenic warming thus toned down, a change of paradigm which highlights a benefit for mankind related to the increase of plant feeding and crops yields by enhanced CO2 photosynthesis is suggested.

The whole paper is well worth the read, and is chock full of links to sources and references supporting his analysis.

Here is a recent Youtube video of Francois Gervais presenting his findings (with English translation)

Update May 13

In the comments below ren points to the declining NAO, with the implication that a cooling phase is underway in the North Atlantic SSTs.  The cold blob in the North Atlantic was subject of a post here and elsewhere, and Paul Homewood posts today on the increasing cold water, not only surface but coming from below.

Dr. Gerard McCarthy is a lead researcher on the RAPID array project measuring the AMO heat transport and provides a good context on their observations and the implications for the climate cooling in coming decades.

Our results show that ocean circulation responds to the first mode of Atlantic atmospheric forcing, the North Atlantic Oscillation, through circulation changes between the subtropical and subpolar gyres – the intergyre region. This a major influence on the wind patterns and the heat transferred between the atmosphere and ocean.

The observations that we do have of the Atlantic overturning circulation over the past ten years show that it is declining. As a result, we expect the AMO is moving to a negative (colder surfer waters) phase. This is consistent with observations of temperature in the North Atlantic.

https://www.weforum.org/agenda/2015/06/how-the-atlantics-cool-phase-will-change-the-worlds-weather/

 

Data vs. Models #4: Climates Changing

188767-004-6bde1150

Köppen climate zones as they appear in the 21st Century.

Every day there are reports like this:

An annual breach of 2 degrees could happen as soon as 2030, according to climate model simulations, although there’s always the chance that climate models are slightly underestimating or overestimating how close we are to that date. Writing with fellow meteorologist Jeff Masters for Weather Underground, Bob Henson said the current spike means “we are now hurtling at a frightening pace toward the globally agreed maximum of 2.0°C warming over pre-industrial levels.”

That abstract, mathematically averaged world, the subject of so much media space and alarm, has almost nothing to do with the world where any of us live. Because nothing on our planet moves in unison.

Start with the hemispheres:

Notice that the global temperature tracks with the seasons of the NH. The reason for this is simple. The NH has twice as much land as the Southern Hemisphere (SH). Oceans have greater heat capacity and do not change temperatures as much as land does. So every year when there is almost a 4 °C swing in the temperature of the Earth, it follows the seasons of the NH. This is especially interesting because the Earth gets the most energy from the sun in January right now. That is because of the orbit of the Earth. The perihelion is when the Earth is closest to the sun and that currently takes place in January.

Using round numbers, the Northern Hemisphere (NH) half of the total surface combines 20% land with 30% ocean, while the SH comprises 9% land with 41% ocean. With the oceans having huge heat capacities relative to the land, the NH has much more volatility in temperatures than does the SH. But more importantly, the trends in multi-decadal warming and cooling also differ.

Climates Are Found Down in the Weeds

The top-down global view needs to be supplemented with a bottom-up appreciation of the diversity of climates and their changes.

slide_4

 

The ancient Greeks were the first to classify climate zones. From their travels and sea-faring experiences, they called the equatorial regions Torrid, due to the heat and humidity. The mid-latitudes were considered Temperate, including their home Mediterranean Sea. Further North and South, they knew places were Frigid.

Based on empirical observations, Köppen (1900) established a climate classification system which uses monthly temperature and precipitation to define boundaries of different climate types around the world. Since its inception, this system has been further developed (e.g. Köppen and Geiger, 1930; Stern et al., 2000) and widely used by geographers and climatologists around the world.

Köppen and Climate Change

The focus is on differentiating vegetation regimes, which result primarily from variations in temperature and precipitation over the seasons of the year. Now we have an interesting study that considers shifts in Köppen climate zones over time in order to identify changes in climate as practical and local/regional realities.

The paper is: Using the Köppen classification to quantify climate variation and change: An example for 1901–2010
By Deliang Chen and Hans Weiteng Chen
Department of Earth Sciences, University of Gothenburg, Sweden

Hans Chen has built an excellent interactive website (here): The purpose of this website is to share information about the Köppen climate classification, and provide data and high-resolution figures from the paper Chen and Chen, 2013: Using the Köppen classification to quantify climate variation and change: An example for 1901–2010 (pdf)

The Köppen climate classification consists of five major groups and a number of sub-types under each major group, as listed in Table 1. While all the major groups except B are determined by temperature only, all the sub-types except the two sub-types under E are decided based on the combined criteria relating to seasonal temperature and precipitation. Therefore, the classification scheme as a whole represents different climate regimes of various temperature and precipitation combinations.

Main characteristics of the Köppen climate major groups and sub-types:

Major group  Sub-types
A: Tropical Tropical rain forest: Af
Tropical monsoon: Am
Tropical wet and dry savanna: Aw, As
B: Dry Desert (arid): BWh, BWk
Steppe (semi-arid): BSh, BSk
C: Mild temperate Mediterranean: Csa, Csb, Csc
Humid subtropical: Cfa, Cwa
Oceanic: Cfb, Cfc, Cwb, Cwc
D: Snow Humid: Dfa, Dwa, Dfb, Dwb, Dsa, Dsb
Subarctic: Dfc, Dwc, Dfd, Dwd, Dsc, Dsd
E: Polar Tundra: ET
Ice cap: EF

Temporal Changes in Climate Zones

This study used a global gridded dataset with monthly mean temperature and precipitation, covering 1901–2010, which was produced and documented by Kenji Matsuura and Cort J. Willmott from Department of Geography, University of Delaware. Station data were compiled from different sources, including Global Historical Climatology Network version 2 (GHCN2) and the Global Surface Summary of Day (GSOD).The data and associated documentations can be found at http://climate.geog.udel.edu/climate/html_pages/Global2011/

In the maps below, the Köppen classification was applied on temperature and precipitation averaged over shorter time scales, from interannual to decadal and 30 year. The 30 year averages were calculated with an overlap of 20 years between each sub-period, while the interannual and decadal averages did not have overlapping years. Black regions indicate areas where the major Köppen type has changed at least once during 1901–2010 for a given time scale. Thus, the black regions are likely to be sensitive to climate variations, while the colored regions identify spatially stable regions.

Chen_and_Chen_2013fig2ab

Chen_and_Chen_2013fig2c

 

Major group Time scales
Interannual (%) Interdecadal (%) 30-year (%)
A                45.5                    89.0                 94.2
B                45.1                    85.2                 91.8
C                35.3                    77.4                 87.3
D                30.0                    83.3                 91.0
E                78.2                    92.8                 96.2

The table and images show that most places have had at least one entire year with temperatures and/or precipitation atypical for that climate.  It is much more unusual for abnormal weather to persist for ten years running.  At 30-years and more the zones are quite stable, such that is there is little movement at the boundaries with neighboring zones.

Over time, there is variety in zonal changes, albeit within a small range of overall variation:

Chen and Chen Conclusions

By using a global gridded temperature and precipitation data over the period of 1901–2010, we reached the following conclusions:

  • Over the whole period (1901–2010), the mean climate distributions have a comparable pattern and portion with previous estimates. The five major groups A, B, C, D, E take up 19.4%, 28.4%, 14.6%, 22.1%, and 15.5% of the total land area on Earth respectively. Since the relative changes of the areas covered by the five major groups are all small on the 30 year time scale, the agreement indicates that the climate dataset used overall is of comparable quality with those used in other studies.
  • On the interannual, interdecadal, and 30 year time scales, the climate type for a given grid may shift from one type to another and the spatial stability decreases towards shorter time scales. While the spatially stable climate regions identified are useful for conservation and other purposes, the instable regions mark the transition zones which deserve special attention since they may have implications for ecosystems and dynamics of the climate system.
  • On the 30 year time scale, the dominating changes in the climate types over the whole period are that the arid regions occupied by group B (mainly type BWh) have expanded and the regions dominated by arctic climate (EF) have shrunk along with the global warming and regional precipitation changes.

Summary: The Myth of “Global” Climate Change

Climate is a term to describe a local or regional pattern of weather. There is a widely accepted system of classifying climates, based largely on distinctive seasonal variations in temperature and precipitation. Depending on how precisely you apply the criteria, there can be from 6 to 13 distinct zones just in South Africa, or 8 to 11 zones only in Hawaii.

Each climate over time experiences shifts toward warming or cooling, and wetter or drier periods. One example: Fully a third of US stations showed cooling since 1950 while the others warmed.  It is nonsense to average all of that and call it “Global Warming” because the net is slightly positive.  Only in the fevered imaginations of CO2 activists do all of these diverse places move together in a single march toward global warming.

N2 is IR-Active: This Changes Everything!

E.M. Smith (Chiefio) has new post (here) presenting the evidence showing how Nitrogen, the dominant gas in the atmosphere, also radiates in the infrared, and thus participates in the “greenhouse” effect.  This information was measured and reported as long ago as 1944, but the implications have been ignored in the recent obsession with CO2.

This Changes Everything.

Footnote:  The original discovery of this effect from Nitrogen (here) attributes the IR to N atoms present in the upper atmosphere.

 

Facets of Ice and Climate

gallopingcamel commented recently on Flap over Arctic Ice Rebound

“Short term variations to Arctic ice were not a big deal for me, but you piqued my interest so your blog has been added to my favorites.

To date, my interest has been the long term record based on ice cores:
https://diggingintheclay.wordpress.com/2013/05/04/the-dog-that-did-not-bark/

Do you have any comments to share?”

His linked post is a tightly reasoned analysis regarding CO2, temperatures and ice cores. I appreciate greatly his summary showing that present warming is much too low if CO2 has been causing warming all along. I’d not seen the contradiction put so succinctly.

His comment causes me to reflect on several facets of ice in relation to climate, and this is the point of this post.

The immediate facet: What do Sea Ice Extents tell us about climate change?

As Peter says, my blogging on Arctic Ice extents is quite immediate and is motivated mainly by my concern to get some factual perspectives out there as a possible antidote to feverish claims the media will promote. In that sense, this facet of ice is an immediate and socio-political one. The issue: should Arctic ice extent cause us to be alarmed about the climate? My blogs on Arctic Ice Rebound provide my conclusions, but this battle for public opinion has not yet been joined in earnest. In my post on sea ice factors I make the point that among many things affecting ice extents, CO2 is the least likely. And Antarctic ice extent is another story which I have left to others.

The Longer View: The Ice Core Story of CO2 and Surface Temperatures

I am convinced as Peter is that in the ice core record, changes in CO2 follow temperature changes and are more effect than cause. The natural CO2 sources and sinks are estimated with large error bands and their behavior is likely to be dynamic, that is, changing with changing climate conditions.

This blog is like a personal journal where I try to articulate realizations that form from my engagement in climate topics. It is idiosyncratic in that I often have a new discovery, quite exciting to me, but long understood by others unknown to me. For example, John Holtquist just linked to a webpage by John Daly where he said years ago most of everything I’ve learned about Arctic ice and more.

My journey this year was marked by discovering we live on planet water, not planet earth, and it led me to read much more oceanographic material which is categorized here as Oceans Make Climate. That led me to ice, and to some theories regarding longer-term Arctic cycles summarized here.

The Big Picture: The Sun and the Earth, From Hot House to Ice House

Peter’s post has a comment thread that gets into the larger arena of climate shifts involving ice-covered ages (most of earth’s history) and the more hospitable inter-glacial periods such as we have enjoyed for the last 11,500 years. I wrote a post on how I believe the ocean’s thermal flywheel is responsible for keeping our climate so stable most of the time, until it is overwhelmed by external forces, primarily astronomical in nature.

I have not wandered far into the sun-climate controversy, and my present understanding is probably best expressed here:
https://rclutz.wordpress.com/2015/09/16/the-climates-they-are-a-changing/