Bishop Hill The extraordinary climate effect of land-use change
Dec 15, 2015 Climate: Models Climate: sensitivity The latest attempt to conjure up a hypothesis as to why things are going to get much worse on the climate front has appeared in Nature Climate Change, with an author team including Gavin Schmidt and Kate Marvel.
The paper delves deeper into the idea of forcing efficacy, a concept that is explained as follows:
The concept of radiative forcing is used to compare the effects of different physical drivers on the Earth's energy budget. Two forcing agents that produce a similar radiative imbalance might be expected to initiate similar feedbacks and have the same global mean temperature response. However, there can be variations in the size and type of feedbacks engendered by a specific forcing, mainly due to geographical variations in the forcing magnitude. These variations can be characterized by an e fficacy that scales for the differences in temperature response. Forcings that project more strongly on the Northern Hemisphere, land or polar regions are systematically more effective at changing temperatures than an equivalent amount of CO2, whose forcing is more uniformly distributed throughout the globe. The converse is true for forcings localized in the Southern Hemisphere or ocean regions.
The authors run a series of climate model simulations, tweaking just one climate forcing at a time, and using the slopes of the resulting graphs of forcing change versus temperature change to estimate the efficacies for each forcing. They then plug the answers into an Otto-type estimate of climate sensitivity from observations. Their conclusions are of course scary, with TCR of 1.9°C and ECS of 3.0°C (compared to 1.3 and 1.9 respectively, for Otto et al).
Whether you find this persuasive or not depends of course on how convinced you are that the GISS climate model the authors used is a fair reflection of the real-world climate. With that in mind it's amusing to consider their estimates of the effect of land-use change on the climate.
If you look at the plot of forcing versus temperature - I show the the TCR one, but its the same story with the ECS one - you can see that all the lines pass through the origin. This makes sense: no change in forcing gives no change in temperature. But in fact there is an exception. Look closely at the the brown dots, the data points for land-use change. Although the authors haven't plotted the line - the points are very close together - you can see that if they did it wouldn't pass through zero. In other words a zero change of forcing is apparently able to produce a non-zero change in temperature.
;)
My point here is not that this will make a difference to their results - the effect of land-use change in their simulations is small anyway. But it does highlight the constant problem with computer simulations, namely that you can kid yourself that they are a reflection of reality, when in fact they are entirely unphysical.
Reader Comments (45)
It is good that they are willing to consider other forcings than CO2.
The fundamental(ist) assumption of climatology is that CO2 will dominate all other forcings in the near future.
It's good to see that this assumption is being challenged.
Bish: there was a Richard (somebodyorother) From Sustainable (farming?) on R4 Farming Today at around 5:50 this am (I was too tired to get his name etc) and he came out fighting against land-use numbers - and how they are being mis-used in the push to claim emissions from UK land use and livestock are greater than they are. He claimed that the land-use numbers came from a single study in Argentina which looked at deforestation for land-use change. The numbers were then extrapolated.
I think that this is the link to the programme.
Do we conclude that not only do we have a series of forcing factors, but now we have additional efficacy factors for each and every one of the forcings - which may themselves vary across hemispheres (and god knows what else)?
I suggest the numbers should then be scaled by the suffix numbers of the next COP (squared, if the numbers are to be circulated to George Monbiot).
My biggest concern would be that while CO2 forcing is more or less understood (and presumably so are other GHGs), the rest of forcings may well be a guess.
Aerosol forcing in AR4: -1.3w/m2
In AR5: -0.9w/m2
In Stevens 2015: -0.5 (actually -0.47)
You'd have been better off if, instead of using AR4 estimates, you had ignored aerosols altogether. Hell, even the AR5 estimate is barely better than giving them a value of 0. Oh, and the Stevens estimate actually falls OUTSIDE the AR4 confidence interval (even though the latter was ridiculously big, -0.5 to -2.2).
If estimates of aerosol forcing were such a fail, how can they have any certainty about more obscure stuff like land use and ozone?
And then you have this (page 39):
https://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter08_FINAL.pdf
The IPCC isn't even sure about the sign of stratospheric ozone forcing. Land use is supposed to be negative, but if you throw in black carbon on snow, which is also a change in land use after all, it's unclear. Come on...
The trouble in climate science is that it's so difficult to rule things out, to prove others wrong. It always COULD be the case that [insert catastrophe scenario]. As I've said a couple times, the 'manufacturing doubt' point is an accusation in a mirror: alarmists are the ones saying we don't know nothing so we gotta prepare for the worst, just in case. What's the point of adding all those variables if no one's got a clue about their value?
(Ironically, the reasoning for excluding natural albedo changes - mostly cloud changes - and non-volcanic aerosols from the list of forcings is that these cannot be quantified... but neither can other stuff that the IPCC does include)
I am sorry, but any “explanation” that includes the term “forcing” loses it, for me. The only “forcing” that is extant in the atmosphere is the incoming radiation, be it from the sun or cosmic rays; all else are just passive components of the atmosphere, the complex interactions with which the incoming energy might have a discernible effect, potentially creating variable atmospheric conditions. It is the internal interplay between these variable conditions, as well as the planet surface, that will then determine weather probabilities – it is with the interaction with the surface that change of land use might have an effect on local climate. Hopefully, this weather displays a pattern from which near-future weather may be determined. No “forcings” required – Dr Who’s “timey-wimey” explanation of his Tardis drive has greater credibility than “forcings”!
This peculiar concept of 'forcings' whereby what is largely an effect, i.e. radiation balance/imbalance at the top of the atmosphere, is taken as a cause, is a handy invention for computer programmers like Schmidt, who seems to have gone the full turnip with his modelling. It allows them the fantasy that they can 'incorporate' just about anything into their models. Can you give us an estimate of the warming/cooling effect of kitchen sinks at the top of the atmosphere? You can! Oh good, that's the model nearly complete surely. No need to have those horribly complicated sinks actually modelled - they are, after all, all over the place and of a bewildering mix of shapes and sizes. No, no, far too messy. We just add their 'forcing' to the list of 'forcings' we put at the top of our atmosphere before watching, and pampering, our model runs as they scurry around adjusting themselves to the new budget. We used just to keep an eye out for warming trends (to be captured) and cooling trends (to be censored), but now we also have a PR interest at least in trendless runs so we look out for them now in case we can strike gold.
But let us leave that torrid, phony virtual nonsense world behind. In our one, the climate system is far from being driven from above. It is dominated instead by the surface. That's where the incoming sunlight largely ends up. That's where the convections largely begin. That's where that other big banana of the thermodynamics, the water molecules start and finish from. The models look feeble and fatuous in the face of the complexities we find there. But we are only at the beginning of the age of satellite observations and massive data sets of observations, and we still have huge scope for learning more of ancient climates through various proxies. There is where more of our 'climate money' should go, leaving the turnips in their chosen field to get by on what they already have.
The authors run a series of climate model simulations...
Stopped right there.
Next.
Historical CO2 lags.temperature by about 6-800 years. And when temperature plunges CO2 continue to rise 6-800 years and vise versa. The political established UNFCCC and its claim of CAGW is the same as claiming that lung cancer causes smoking?
John Shade:
But, but, but ..their projections are 97% accurate in HINDSIGHT. It is future projections that are wrong all over the place.
No doubt there is a simple error in this pap too, just like:
http://www.sciencedirect.com/science/article/pii/S0304380015002008
"Corrigendum to “On a minimal model for estimating climate sensitivity..."
"The authors regret that Section 1.4 of our paper (Cawley et al., 2015) contains an error; the estimates of equilibrium climate sensitivity and transient climate sensitivity should have been divided, rather than multiplied by 1.145."
....We thank Mark Richardson for first bringing this error to our attention, and Nicholas Lewis for also raising this issue.
..........anyone who pretends that the models are not running too hot is just deluding themselves.
The only clear conclusion is that Gavin needs the work.
RR
Presumably it is those "complex interactions with which the incoming energy might have a discernible effect, potentially creating variable atmospheric conditions" which the Climateers call "forcings".
As you and Alberto and John Shade point out, in your different ways, this is all nonsense on stilts; most of it is guesswork and guesswork applied to models — even if they were more accurate than they are — renders the entire exercise meaningless.
Not to mention irrelevant since while Schmidt is distracting attention with more pseudo-scientific codswallop the eco-activists are still beavering away trying to shut down power stations and impoverish the lot of us.
I'm confused about why they need to produce any more scary papers or indeed, spend any money at all on agw research at all. Paris is over and they have an agreement, and they're next meeting in 2050 or something aren't they? Until then shut up!
Do computer modelled forcings go down the plug hole faster or slower in the Northern Hemisphere? Have the same computer models been run from the Southern Hemisphere to check?
Anthony has a post on an interesting Twitter exchange over at wuwt involving Gavin. http://wattsupwiththat.com/2015/12/14/gavins-admission-about-the-satellite-record-versus-the-surface-temperature-record/
The signs are all there.
The warnings get more hysterical as reality fails to follow the climate models.
Ever more feedback loops are invented to magnify a basic temperature change of nothing.
The way I see COP21 is that the various nations are setting up enough slack to backtrack effortlessly and realine their economies back to the real world.
And then there's grant money
Can I get a definition of "forcing?" It seems to be the climate scientists magic word. What it is ain't exactly clear. But it EXPLAINS EVERYTHING!
Gamecock, Global Warming Forcing is what just happened in Paris, without a shred of evidence, scientific, or otherwise.
GC
A forcing is merely a simplification that allows models to be small enough to actually solve in a decent amount of time. It replaces some poorly understood or easily fudged part of the climate system with an input value/table and inbuilt algorithm that relies on it. As noted above the only forcings in reality are the sun, seismic events and the odd asteroid strike while everything else is a feedback. Fossil fuel CO2 is made a forcing as it is an injection of CO2 that was long-sequestered. The only advantage of forcings is speed. The disadvantage is that many of these variables would have been dependent on each other but that nuance is lost. In practise this doesn't matter because CO2 injection and manmade aerosols dominate so that without these two forcings the temperature output would flatline in most models. Whether that makes any sense depends on your degree of scepticism about CO2 versus the sun as Earths climate driver.
Of course the uncertainties are so huge that any result is possible - even a new ice age. So any result obtained may seem useful to an outsider but as it comes with a slew of often baseless and pessimistic assumptions it's true error margins are so wide that any output is in reality just meaningless noise that reflects the bias of the operators. So the models became mathematical cloaks around biased guesswork stemming from circular logic. That many models seem to recreate the recent past despite the inputs being wildly different has been remarked upon as unusual by several researchers. This result can only be due to deliberate tuning^ of the system to match the 20th century climate, which in any other field would render the model unsuitable a priori for prediction* but somehow this obvious conclusion is not explored in the cloistered, self-affirming world of climate science.
*prediction meaning here merely a projection based on a given emissions scenario.
^don't believe any parrot who says tuning is not done: All they have done is mere semantic manipulation in order to fool themselves or others.
The only "forcing" I can see is the Thermaggedonists "forcing" their putrid bullshit down everyone's throat to keep the scam going and their comfy sinecures with gold plated pension pots inviolate.
I wouldn't trust Gavin Schmidt if he announced that December 25th was going to be Christmas Day.
Maybe, just maybe, they would be better off looking at the corrected model produced by Dr David Evans. They won't because it shows all their previous propaganda is just that - propaganda and hot air.
Martin Brumby, with Computer Adjustments, any day can be Christmas Day. In Climate Science, every day IS Christmas Day, as they take money from everybody, and never give anything back.
JamesG, thank you for the explanation, but climate forcings are whatever climate scientists want them to be, should they choose to accept them.
With all the extra CO2 (and other Greenhouse gases) produced on Christmas Day, it is amazing it is not the hottest day of the year (in the Northern Hemisphere)
I wonder whether there's a warming difference between the prairie grass that used to be on the Great Plains, compared to plowed fields and other winter/spring cropland... and if there's a difference between various crops, whether warming climate simulations consider those.
AnonyMoose, any difference will be positive due to the absence of flatulating buffalo/bison.
I am not sure about Elk numbers, but most Moose have migrated towards better internet access.
"it does highlight the constant problem with computer simulations, namely that you can kid yourself that they are a reflection of reality, when in fact they are entirely unphysical."
This sums up a consistent frustration I encounter with your commentary.
There seems to be little space in your world view for the possibility that an imperfect, distorted reflection of reality can none the less be useful for certain purposes. You seem to argue that either a theory is a perfect reflection of reality or it is "entirely unphysical".
I don't think this really has anything to do with computer models, climate science, or even science generally. It's just a feature of all our knowledge - in science or anywhere else in life - that it is an imperfect reflection of reality. (Leave aside arguments about religious revelation.)
Climate science may or may not be full of serious errors that make it effectively useless for the purposes to which it is put by environmentalists (although personally I think that the most important errors in green thinking are elsewhere). But arguments whose logic runs 'our knowledge is not perfect, and therefore it is useless' seem to me to be a kind of post-modern irrationalism, which won't help anyone.
The Dog That Is Not Barking.
For 18 months now NASA has had the ability to show global CO2 concentrations mapped directly via the OCO2 satellite program which began in 2009. Almost no images of the Demon Gas concentrations worldwide have been released. The two seen on the JPL site seem not to show "polluting" originating in the desired locations and computer simulated futures are featured. There is a lot more coverage devoted to land use and seasonal cycling.
The website language is often not in the present tense and there is a lot of speculation about vegetation absorption and uncertainty. Odd now that with a clear view of the major threat to humanity, interest seems to fade away.
Most unsettling.
"Measurement Approach
The OCO-2 mission will not, however, directly measure CO2 sources and sinks. Instead, sophisticated computer-based data assimilation models that use column averaged dry air CO2 mole fraction (Xco2) data will infer the location of these sources and sinks". http://www.jpl.nasa.gov/missions/orbiting-carbon-observatory-2-oco-2/
You do have a point, JK, and it is one that TheBigYinJames has addressed, in part, on a discussions thread. For most of us (assuming I can speak for more than just myself), while we can accept that models can help to give us an idea of what might or might not be involved, and possible futures based upon supposed situations, we find it difficult to accept that these models can be so reliable that countries – indeed, the entire world! – can base their economies, infrastructure and social structure on them. That is what gets the ire of so many raised, as well as the enormous costs, with no visible benefits to the vast majority, though massive benefits for the favoured few. While there may be more important errors in green thinking, there is none quite so capital-hungry or with such impetus to drive us towards a totally undemocratic One World Government.
I'd like to make it known that I ran my own "experiment" using a model. I ran repeated iterations, changing a single input each time. While the result did not produce any information regarding forcing efficacy or tempertures, it did show that the Seattle Seahawks will win the Superbowl, so long as Marshawn Lynch is able to return to action by the time the team reaches the playoffs.
Madden NFL Football works like a charm. Am now taking (imaginary) bets on the results of my model experiment, as we all know their output is irrefutable.
JK,
It's not the imperfection that's the problem. Read John Shade's comment above: puts clearly why the models are worthless.
Now my 2c.
It's the dishonesty (as in the famous Feynman's quote) that prevents progress and demands criticism. The excuse making and refusal to acknowledge ignorance are as anti-science as it gets. Really, don't "forcings" sound more like astrology than science?
Some of Feynman's observations on the Challenger disaster have relevance to the climate models. He was appalled that the shuttle's engines were developed as a whole. Rather than bottom-up testing individual components to weed out weakest links, NASA just built the whole thing, tested it to failure, and set the safe life to half/a third whatever of the failure time. Crazy.
Similarly the climate models combine a multitude of poorly understood components in arbitrary ways. Not surprisingly, they can fit the part of the elephant they've already seen -- they don't have much idea what the rest of it is going to look like. In the space shuttle sense, there hasn't been a model run yet that wasn't a failure.
A photon arriving from the sun adds energy. A photon from anywhere else is on its way to deep space and subtracts energy. Only a delay in the latter would lead to an increased energy level. Radiative forcing is not a delay. Radiative forcing is a delusion.
Andrew,
I haven't analysed the Marvel et al. data so I'm not sure of the reason for apparent deltaT>0 even for zero radiative forcing (i.e. deltaF=0). (Given the small forcing and small temperature response, the result is uncertain and affected by internal climate variability). But I don't suppose you have analysed their data either, so I'm surprised by your certainty in claiming the result is
Why have you not considered possible physical reasons before rushing to such judgement? Land use forcing, more so than most other forcings, can alter surface climate via altering surface fluxes of heat and moisture even without (or rather, in addition to) altering the top of atmosphere radiation balance. Radiative forcing is a metric only of the latter. For example, Betts et al. (2007) write:
which would give surface warming even for zero top of atmosphere forcing, in qualitative agreement with the Marvel et al. land use results that you claim are "entirely unphysical".
They have been tweaking their Models again, but have not as yet been able to tweak them so that they can represent reality. This could be a useful line for future research, ...representing Reality. On the other hand, they could just look at the corrected model produced by Dr David Evans.
Thanks Tim. I was going to make exactly that point, but found you beat me to it - and you saved me citing myself too ;)
Bishop Hill and others interested in the effects of land use change on climate (via radiative forcing and other influences, as you describe above) may also be interested in this review paper by Roger Pielke Snr, myself and others.
Unfortunately it's paywalled, but I'll be happy to send a copy to a few people if they drop me an email.
It is a fallacy to imagine we are talking about models that are just imperfect. Many models (or model input assumptions) are wonderful, some are good enough for policy and many are just plain inadequate.
As for the scientists integrity, the latest meme about the 'hottest than ever year' should tell you that even if all of the other previous made-up and disproven cack didn't. They are modern-day shamans pretending to discern meaning from the digital equivalent of chicken entrails. In times past they'd be the ones sacrificing virgins to make rain or burning witches and heretics.
Tim, Richard
The graph is of ΔF, not F. It seems to say that zero change in F can produce a change in T. Or am I missing something?
Strange physics can operate in the Southern Hemisphere, things that would upset the authors of this paper if they knew about them.
For example, here is a new paper with a plausible assertion that the effect of increased CO2 on atmospheric temperatures above the Antarctic land mass is one of COOLING. Negative ECS. There are more papers along the same lines.
http://onlinelibrary.wiley.com/doi/10.1002/2015GL066749/abstract
Andrew
yes, I know it is ΔF not F. My point is that ΔF is not a complete measure of the effect of an external forcing.
Here, the external forcing is land-use change. This affects the climate in a number of ways, only some of which are reflected in a change of the Earth's radiation balance at the top of the atmosphere (TOA, which is the only thing that ΔF is measuring in this case).
Converting forest to cropland or grassland will usually increase the surface albedo, reflecting more incoming solar radiation back to space and therefore causing ΔF<0 and subsequently global-mean surface cooling.
However, the conversion from forest to cropland also alters winds and turbulence in the atmospheric boundary layer, canopy interception and re-evaporation, and the depth to which vegetation can retrieve soil moisture and make it available for transpiration. These things alter the non-radiative (i.e. latent and sensible) transfer of heat from surface to atmosphere and can therefore change the surface temperature even if the TOA radiation balance doesn't change (i.e. ΔF=0).
If the total effect of land-use change forcing is proportional to the TOA radiation perturbation (ΔF), then the relationship between ΔT and ΔF would still pass through zero (though for the small changes considered in Marvel et al., internal variability could offset that as I noted before). However if the total effect isn't proportional to ΔF, then the ΔT,ΔF line won't pass through zero. There are no data points at ΔF=0 in the Marvel et al. land-use change forcing case, you are extrapolating a straight line that you fitted to their ΔT,ΔF data. If the total forcing effect isn't proportional to ΔF, the relationship won't be linear and therefore assuming linearity and extrapolating to ΔF=0 will give the incorrect result.
Marvel et al. concentrate on the different slopes of the ΔT,ΔF lines for different forcing types, expressed as the forcing efficacy. The variation in slopes is the most prominent feature across the different single-forcing simulations that they analyse. The fact that the ΔT,ΔF relationships are not all linear is a much less prominent feature, but does need to be considered especially for land-use change and especially when considering if the models are behaving in an "entirely unphysical" manner.
Tim
You say " Land use forcing, more so than most other forcings, can alter surface climate via altering surface fluxes of heat and moisture". You also point out that such changes can "give surface warming even for zero top of atmosphere forcing". In principle, I agree.
However, in that case I would expect the regression line still to pass through the origin of the delta_T vs delta_F plot; it would just have an infinite slope. To produce a Marvel-like result, small land use changes would have to change surface fluxes only, whilst larger ones modified forcing as well as surface fluxes. This seems to me to be difficult to account for. Almost all GCMs show linear responses to varying, moderate, perturbations.
Richard
Thanks for the offer to send the land use change review paper. For those who are interested, it is in fact available here: iclimate.org/dev/publications-protected/J111.pdf .
BTW Jose Duarte says he doesn't want to idntify as a Skeptic , cos he can't be in a group that calls Gavin a "fraud"
..commenters explained that they had more experienced in that than Jose.
I would use a softer tem myself.
Nic
good, you agree with my second comment above that some nonlinear behaviour in the surface fluxes (or maybe in the temperature response to the changes) is needed to get a Marvel-like result. So we're in agreement there.
You can get a Marvel-like result if, for example, albedo increases linearly as you convert greater areas of forest to cropland but the surface non-radiative fluxes change nonlinearly. Is this the case here? I don't know (it's not my area, I've not analysed their model data) -- the purpose of my initial comment was simply to caution that such behaviour is possible and should at least be considered before rushing to the judgement that it is entirely unphysical.
I tweeted a schematic here which might help. It is just hypothetical. Negative land use change is nominally conversion of forest to cropland. (a) shows my assumed linear change in TOA radiative forcing (via albedo change). (b) shows my assumed nonlinear change in surface fluxes, which I've chosen to saturate beyond small land use changes. (c) sum of TOA radiative and surface non-radiative effects. (d) temperature response to the sum of these effects (y-axis) against only TOA radiative forcing (x-axis). In (d), if you only have the red data points and fit a straight line, you won't pass through the origin.
So that's just a made-up example to illustrate behaviour that looks Marvel-like. Their actual model output is here, so this is your chance to explore nonlinear GCM response :-) Enjoy!
Tim,
The graph in your tweet shows a strange combined temperature change because you have forcing positively related to land use change, but surely it is normally negatively related since the albedo of cleared land is higher? That being the case, the graph line won't display any maxima or minima.
In any event, your graph still goes through the origin, as it must, since zero forcing implies zero land use change, which will produce zero temperature change. I don't see non-linearity as very likely here, but if it did occur that would be at high forcing levels, not low ones.
And, indeed, Marvel's results show a highly linear relationship between land use forcing and GMST change in all but the last three decades. But the line through those points (the first four of which have almost zero GMST change) crosses zero GMST change at a negative forcing level. This is a bit obscured by the use of huge filled circles in the Marvel paper; it is much clearer in the TCR graph originally shown by Gavin Schmidt, here: www.mpimet.mpg.de/fileadmin/atmosphaere/WCRP_Grand_Challenge_Workshop/Ringberg_2015/Talks/Schmidt_25032015.pdf (page 9)
There are a number of other very strange things in the paper, BTW.
Nic, I get the feeling we're talking at cross-purposes here and probably aren't disagreeing much. In my hypothetical schematic, I arbitrarily chose (as I stated) the x-axis direction for land-use change as being negative for conversion of forest to cropland. So moving in the negative direction does indeed give higher albedo for cleared land and consequently a negative forcing, as shown. I chose that orientation because it seemed to help with comparison to the Marvel et al graph which has historical land use forcing in the lower-left quadrant.
The combined temperature change is not "strange" because of this orientation. Feel free to flip the orientation of panels (a)-(c). The result is the same. The curves will still have maxima and minima. Panel (d) doesn't flip as that is ΔT vs ΔF_TOA.
Yes, the graph still goes through the origin, for the reasons you give. But if you just have the red data points in (d) and not the black line, you might think that the relationship misses the origin. That is the purpose of the simple schematic, to illustrate this possibility.
You seem confident that if any nonlinearity is present that it will be at high forcing levels. Perhaps. Remember though that this is a global aggregation of geographically-varying patterns of vegetation change and evaporation change. Not all regions have equal scope for surface warming via reduced evapotranspiration, so the result depends on where the early land-use changes are versus where the later land-use changes are. I think Richard Betts showed that deforestation in regions with frequent spring snow cover had a greater albedo effect than elsewhere, so again you could get nonlinearities in global forcing according to where and when land-use change takes place.
The "highly linear relationship" in Marvel's results is over such a narrow range of forcing that I don't see it as strong evidence for linearity over a wider range, such as a range that encompasses zero ΔF_TOA forcing, which the data they present doesn't include.
I can see it crosses ΔT=0 at ΔF_TOA<0, though it is indeed clearer in Gavin's presentation graph. That is the main issue that this post and comments are about, isn't it? My schematic was designed as an example of how this could arise while still also passing through ΔT=0, ΔF=0 by a combination of positive (evapotranspiration) and negative (albedo) forcing components whose ratio is not constant for all land-use changes.
Maybe there are other explanations for the apparent oddity of the land-use results. Do you have any, or do you suspect some data analysis/presentation issue?
One of the marvellous recent observations is that, within the bounds of experimental error, the albedo of the Northern and Southern hemispheres averaged over a year are identical. Such an observation makes a mockery of all the model calculations on which Schmidt and Marvel rely. Their toys HAVE to be able to reproduce reality - otherwise they are sweet fudges, good to eat but merely fattening.
"reduces the aerodynamic roughness of the landscape"
The top of a forest or woodland is a sea of very flexible treetops; with leaves in growth seasons, bare branches in other seasons. Only a few 'forest giants' reach far above the level of the woodland.
Chopping out a section of woodland introduces a sudden loss of continuity. Even when vast acreages are clearcut, ther are trees and stands of trees left; as seed trees, shade trees, or just plain unharvested trees.
Woodlands mature as trees seek to spread their limbs to catch sunlight, completely obscuring all but the most drastic surface land changes. Cutting woodlands in any terrain, and especially in rough terrain, exposes surface irregularities that are not evident at treetop level.
Wind blowing across woodland treetops flex the branches so that less irregularity is encountered by winds.
Aerodynamic roughness of the landscape is increased when woodland is harvested!
"decreases both the capture of precipitation"
Aye. Which is a major factor in subsequent flooding as the land is unable to absorb rainfall quickly enough.
" and the root extraction of soil moisture"
Keeping the land as bare ground are we?
Introducing several crops per year that have a rapid growth - maturity cycle introduces a substantial root moisture extraction process. Introducing irrigation or other crop watering methods greatly changes land moisture impacts.
"these changes tend to decrease evaporation"
Aren't you equating evaporation to transpiration?
"hence reduce the fluxes of moisture and latent heat from the surface to the atmosphere"
No. It reduces the consistency of moisture fluxes as streams that used to be fed by captured groundwater dry up.
Moisture fluxes increase from a consistent woodland moisture levels to a boom and bust cycle as rainfall determines maximum moisture flux, lack of rainfall brings about a minimum moisture flux and human irrigation methods introduce a sporadic seasonal moisture flux.
The latent heat fluxes increase.
"acts to increase the temperature near the surface"
Maybe.
What happened to humidity? Woodlands maintain a very high humidity level under their canopies. All that transpiration coupled with reduced wind movement in the forest's understory.
That greenhouse gas H2O? Reduced from 90%plus to whatever the local air mass has? That change, perhaps, has the greatest effect on temperature near the surface and the lapse rate.
Heat in an open area radiates away very quickly at night. Heat under a forest canopy lingers for quite awhile at night.
Travelling in the American Southwest, walking, a person can feel touches of cool moist air as they near a water source. Locales near streams in even slight declines are quite noticeably cooler than surrounding open land.
All of the irrigated plots of land where crops are grown are also cooler.
When driving across the desert areas, one can spot occupied, usually, houses and lands by the trees planted near the houses. Trees that require more water than open desert land provides. Just human wastes, sewage, car or equipment washing, animal cleanings, provides a lot of extra groundwater that keeps a larger amount of plant life alive; and the whole area just a couple of degrees cooler.
A favorite tree planted in a windbreak line are the 'Hybrid Poplars' that grow straight up very quickly. People living in snow belts learn very quickly to plant more than one windbreak row, as the first row has an effect of letting more snow to stick in the calmer area after the wind break.
Hybrid poplars quickly perish when no longer irrigated in dry areas. Lines of dead poplars are also easy to spot and identify places where people either just stopped watering their trees or they no longer live there.
A wind break is not a woodland. Cutting down woodlands introduces surface irregularities and wind breaks that were not there before. Moisture retention and daily humidity are greatly lessened, Albedo is increased. Lapse rate is decreased.