CORRECTION

Ferenc Miskolczi not Miklós Zágoni.

Thank you for providing the very helpful comments & links.

-
Clarification:
It is not the summer dip at Alert (northern Canada), but rather the winter dip (in dCO2/dt) that is of particular interest.

I have been digging around to try to figure it out. Anything I could offer at this stage would be premature — I will refrain from speculative comment at this time.

Insights from anyone presently more-knowledgeable are certainly welcome.

- – -
Regarding “daily” CO2 time series, there is a noteworthy mystery:

The data labeled “daily” at
http://scrippsco2.ucsd.edu/data/data.html
…are NOT daily.

Fortunately, Ferdinand has pointed out truly daily CO2 time series:
ftp://ftp.cmdl.noaa.gov/ccg/co2/in-situ/

I briefly became concerned that a lot of the data had been estimated (interpolated – possibly using untenable assumptions about annual structure) after noting the long & variable-length gaps in the Scripps “daily” [but not daily] data.

I am very thankful that Ferdinand has commented. However, I will be uneasy about all CO2 data until someone sheds some light on what is up with the Scripps website’s misleading “daily” links.

-
bill (16:46:57) “Despite the change in temperature between 1975 and 2008 the minimum has barely changed. And the slope switch occurs in a metter of a couple of weeks
I still find the speed of response amazing for such a massive system!”

I imagine you are speaking of the seasonal timing of the minimum. If so, keep in mind that at the latitude of Alert, there is basically only polar-night (winter) & polar-day (summer). Think about the very low angle of the sun as it circles the sky [staying above the horizon (aside from mountain-shadows)] in the “evening” of the polar-day (i.e. approaching Sept. 21).

If the change over from -ve co2 slope to +ve slope were to take many weeks I would agree that vegetation/Ice could be the cause but using your ref for hourly data I plotted this for Barrow:
http://img132.imageshack.us/img132/7442/barrowhourlyco2.jpg
http://img190.imageshack.us/img190/1068/co2x7.jpg

Despite the change in temperature between 1975 and 2008 the minimum has barely changed. And the slope switch occurs in a metter of a couple of weeks
I still find the speed of response amazing for such a massive system!

Vegetation will affect the CO2 in a continual way for many weeks as spring approaches from the south. By the time Barrow unfreezes it will be growing vigorously a few hundred km further south.

Both the start and end of the growing season and the ice breakup and reformation are quite rapid processes in the high north… Usually transformed from complely frozen sea to open sea (at least near the coast) and from snow covered frozen land to growing leafs and flowers within a few weeks…

The atmospheric mixing is relative fast: days to weeks at the same altitude, with some Noth-South gradient (and a steep gradient near the equator, caused by the ITCZ), weeks to months for different altitudes. But as plant growth and ocean absorption are rather continuous processes when the temperature is high enough and ice is melted, there will be a continuous difference between the places with (relative) huge vegetation growth and high absorption and the rest of the atmosphere.

The other way out is more difficult to understand, as once all is frozen, there is no real source of CO2, or there should still be a lot of bacterial life decomposing the organics on/in the (permafrost!) soils.

Alternative is that the fast changes come from elsewhere and are brought in by air circulation, where the change from polar highs in winter to more southernly air masses could be the cause…

That the dip is mainly from vegetation growth can be seen in the d13C changes: http://cdiac.ornl.gov/trends/co2/allison-csiro/graphics/alc_c13co2.jpg here for Alert (NW Territories, Canada)

Looking at the different graphs of CO2 and CO2C13 (=d13C) at the NOAA website, it seems that the behaviour of CO2 and d13C at Barrow and Hohenpeisenberg (Germany, 1,000 m) is practically the same, see: http://www.esrl.noaa.gov/gmd/ccgg/iadv/
It looks like that instream at Barrow of already mixed air from the south is the main cause of the variation…

Ferdinand Engelbeen (10:47:54) :

The daily data dip in CO2 is very sharp. It goes from negative to positive slope within a couple of weeks. The slope to max co2 is very similar to to min co2 in this dip.

Is this really possible from a biological process and sea ice? It’s acting as if a CO2 sink / source switch has been thrown. No AGW agenda on this point! I just would like to know how the mass of the atmosphere can react this quickly.

My guess is that there will be plenty of datasets & publications, including a good number focused on short timescales. Publicly-available text-format data-websites are (arguably) essential in a knowledge society. Although I’m confident shorter timescale datasets exist, I suspect you’re right that they will not be long-term and I anticipate tediously-inefficient bureaucratic access-hoops (in most/many cases).

The data of one-hour raw averages of 40 minutes of 10-second measurements (without any filtering) are available at:
ftp://ftp.cmdl.noaa.gov/ccg/co2/in-situ/
for four base stations, including Barrow, from the start year (1973 for Barrow) up to 2008…

A nice explanation of the procedures followed at Mauna Loa and other baseline stations is at:
http://www.esrl.noaa.gov/gmd/ccgg/about/co2_measurements.html

About the dip of Barrow and other far north stations: most of the time the ocean near Barrow is frozen. When the temperature increases, two main things happen: tundra grows as crazy and the ocean ice sheet disappears. The first can be seen in the increase of d13C level and both as a dip in the CO2 levels (the stil cold ocean absorbs a lot of CO2). The increase in winter is more difficult to explain, but CO2 may be transported in from other places.

Most baseline stations are in the Pacific at sea level and don’t show such a huge seasonal variability. But if you look at the variability of Schauinsland (Black Forest, southern Germany), at 1200 m when measured with sufficient wind speed and above the inversion layer, the seasonal variation is even larger than at Barrow:
http://cdiac.ornl.gov/trends/co2/graphics/schauinsland.gif
The Ferrell air moving cells may transport the CO2 levels polewards…

Hope this helped…

I have made a lot of comments on the origin of the CO2 rise in the past, including Dr. Spencer’s different attempts to look at nature as cause…

Again a new round, where Dr. Spencer used this simple model:

delta[CO2]/delta[t] = a*SST + b*Anthro

There are fundamental problems with this model:

The first one is that there is no time limit in the equation for a change in sea surface temperature. That is the same problem as with the previous discussion with Frank Lansner at this blog: if the sea surface temperature goes up, the model assumes that the increase of CO2 per year remains the same over time. That is certainly not the case, as a new equilibrium between ocean temperature and vegetation at one side and CO2 levels at the other side will be reached within a limited amount of time for the fast processes (ocean solubility and vegetation growth) and after longer times for the slow processes (ice sheet/vegetation area, -deep- ocean flows). The real formula should have a term related to the change in temperature, not the relative temperature, as the overall change in CO2 is related to the change in temperature…

The second fundamental problem is that the formula shows the short term relationship between dCO2 and dT, that is the variability around the trend, but that doesn’t need to have any relationship with the trend itself, if the trend is caused by something else than temperature. Temperature then is only causing the “noise” around the trend. And eventually a small part of the trend, if there is a temperature difference between the start and the end of the period of interest. On the other side, the emissions cause only a small part of the variability around the trend, as most of the variability is temperature related.

I have used an alternative “simple model”:

dCO2 = 3*dT + 0.55*emissions

where CO2 and emissions are in ppmv (1 ppmv CO2 = 2.1 GtC emissions) and 3*dT is the factor 3 ppmv/°C which fits for short term changes, up to 8 ppmv/°C for very long term temperature influence on CO2 levels (glacials – interglacials, MWP-LIA temperature change) and dT is the temperature difference between begin and end of the period…

If we plot that formula for the short term variability (dCO2/dt), then we see the following:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/egbn_trend.jpg
which is a reasonable fit to the variability around the trend.

Pieter Tans of NOAA, responsible for the CO2 data of several stations, including Mauna Loa, made a better fit by including precipitation, which influences plant growth (see the second halve of the pdf):
http://esrl.noaa.gov/gmd/co2conference/pdfs/tans.pdf

Some different view if we look at the trends themselves. Have a look at the trends of temperature and accumulated emissions vs. CO2 levels:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/temp_co2_acc_1900_2004.jpg
The CO2 levels until 1960 are from different ice cores (Law Dome, best resolution 8 years), after 1959 from Mauna Loa. As can be seen, even in cooling periods (1945-1975) the CO2 levels increase at about 55% ratio with the accumulated emissions…

Even more informative, the correlation trends 1900-2004 between accumulated emissions and atmosphere:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/acc_co2_1900_2004.jpg

Compare that to the temperature – CO2 correlation trend:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/temp_co2_1900_2004.jpg
where a large change in temperature has little influence on CO2 increase…

Main conclusion of this all: temperature has a fast (and slow) influence on CO2 levels, but that is limited to 3ppmv/°C for short term changes, up to 8 ppmv/°C for very long term changes. Thus while temperature is mainly responsible for the variability around the trend, the emissions are responsible for the bulk of the trend itself…

Worthy of note for albedo/cloud enthusiasts:
“[...] a decline in the coccolithophores may have secondary effects on climate change, by decreasing the earth’s albedo via their effects on oceanic cloud cover.”
Wikipedia – Ocean Acidificationhttp://en.wikipedia.org/wiki/Ocean_acidification
[a rather "alarmist" article - well worth assessing for political bias]

GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 15, No. 2, PAGES 507-516, JUNE 2001

Decreasing marine biogenic calcification: A negative feedback on rising atmospheric pCo2

Ingrid Zondervan, Richard E. Zeebe1, Björn Rost, and Ulf Riebesell
Alfred Wegener Institute for Polar and Marine Research Bremerhaven, Germany

Abstract. In laboratory experiments with the coccolithophore species Emiliania huxleyi and Gephyrocapsa oceanica, the ratio of particulate inorganic carbon (PIC) to particulate organic carbon (POC) production decreased with increasing CO2 concentration ([CO2]). This was due to both reduced PIC and enhanced POC production at elevated [CO2]. Carbon dioxide concentrations covered a range from a preindustrial level to a value predicted for 2100 according to a “business as usual” anthropogenic CO2 emission scenario. The laboratory results were used to employ a model in which the immediate effect of a decrease in global marine calcification relative to POC production on the potential capacity for oceanic CO2 uptake was simulated. Assuming that overall marine biogenic calcification shows a similar response as obtained for E. huxleyi or G. oceanica in the present study, the model reveals a negative feedback on increasing atmospheric CO2 concentrations owing to a decrease in the PIC/POC ratio

Paul Vaughan (23:00:02)

Because the effect of periodic small scale phytoplankton blooms on ocean ecosystems is unclear, more studies would be helpful. Phytoplankton have a complex effect on cloud formation via the release of substances such as dimethyl sulfide (DMS) that are converted to sulfate aerosols in the atmosphere, providing cloud condensation nuclei, or CCN. But the effect of small scale plankton blooms on overall DMS production is unknown.”

Variability of atmospheric dimethylsulphide over the southern Indian
Ocean due to changes in ultraviolet radiation

D. R. Kniveton,1 M. C. Todd,2 J. Sciare,3 and N. Mihalopoulos4
Received 13 January 2003; revised 16 May 2003; accepted 11 August 2003; published 10 October 2003.

[1] Dimethylsulphide (DMS) is a climatically important component of global
biogeochemical cycles, through its role in the sulphur cycle. Changes in ultraviolet
radiation (UV) exhibit both positive and negative forcings on the dynamics of production and turnover of DMS and its precursor dimethylsulphoniopropionate (DMSP). In this study we investigate the net forcing of UV on atmospheric DMS. The work is based on a 10-year record of observed DMS at Amsterdam Island in the southern Indian Ocean, and satellite-based retrievals of surface UVand photosynthetically active radiation (PAR).The results show an inverse relationship between UV radiation and atmospheric DMS associated with extreme changes (defined as the greatest 5%n daily UV, independent of changes in wind speed, sea surface temperature, and PAR.

Testing the relationship between the solar radiation dose and surface DMS
concentrations using high resolution in situ data
C. J. Miles, T. G. Bell, and T. M. Lenton 2009

Abstract
We tested the recently proposed, strong positive relationship between dimethylsulphide (DMS) concentrations and the solar radiation dose (SRD) received into the surface ocean. We utilised in situ daily data sampled concurrently with DMS concentrations 5 from the Atlantic Meridional Transect (AMT) programme for the component variables of the SRD; mixed layer depth (MLD), surface insolation (I0) and a light attenuation coefficient (k), to calculate SRDin situ. We find a significant correlation (_=0.53) but the slope of the relationship is approximately half that previously proposed. The correlation is improved (_=0.76) by replacing the in situ data with an estimated I0 (which assumes 10 a constant 50% removal of the top of atmosphere value; 0.5×TOA), a MLD climatology and a fixed value for k following a previously described methodology. Equally significant, but non-linear relationships are also found between DMS and both in situ MLD (_=0.73) and the estimated I0 (_=0.76) alone. The DMS data shows an interesting relationship to an approximated UV attenuation depth profile. Using a cloud adjusted, 15 satellite climatology of surface UVA irradiance to calculate a UV radiation dose (UVRD)provides an equivalent correlation (_=0.73) to DMS. With this data, MLD appears the dominant control upon DMS concentrations and remains a useful shorthand to prediction without fully resolving the biological processes involved. However, the implied
relationship between incident solar/ultraviolet radiation dose and sea surface DMS con20 centrations (modulated by MLD) is critical for closing a climate feedback loop.

Also recommend Paul Crutzen.

Crutzen PJ 2002. Analysis of the Gaia hypothesis as
a model for climate/biosphere interactions. GAIA
2/2002, 96–103.

Also an interesting article here

(PhysOrg.com) — Groundbreaking Victoria University research shows that ocean acidification may have no negative effect on tropical corals and local sea anemones – in fact it may improve photosynthesis.

http://www.physorg.com/news161877580.html

useful crash course:
http://www.ferdinand-engelbeen.be/klimaat/co2_measurements.html

“Because the effect of periodic small scale phytoplankton blooms on ocean ecosystems is unclear, more studies would be helpful. Phytoplankton have a complex effect on cloud formation via the release of substances such as dimethyl sulfide (DMS) that are converted to sulfate aerosols in the atmosphere, providing cloud condensation nuclei, or CCN. But the effect of small scale plankton blooms on overall DMS production is unknown.”

If one googles “carbon dioxide wiki”, one is led to:

Wikipedia – Carbon dioxide
http://en.wikipedia.org/wiki/Carbon_dioxide

Focusing further on CO2 “in the Earth’s atmosphere” within that article leads to:

Wikipedia – Carbon dioxide in the Earth’s atmosphere
http://en.wikipedia.org/wiki/Carbon_dioxide_in_the_Earth%27s_atmosphere

The caption of the first graph one sees there links to:

Wikipedia – Keeling Curve
http://en.wikipedia.org/wiki/Keeling_curve

If one digs around for a link to “data” on that page, one finds a link to CO2 data labeled:

“Globally averaged marine surface monthly mean data.”

…but the link actually leads to the Mauna Loa Observatory (elevation more than 3km) data:
ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_mm_mlo.txt

…and note that nowhere on that webpage can one find “mauna loa” — that clue is found elsewhere in the directory – by adjusting the url …which is also how one can find the “globally-averaged” data.

Maybe it was just a linking accident? – even if so, the error is well worth pointing out, particularly considering the insights (into spatial variation) that arose in this thread.

- – -
Worthy of note for albedo/cloud enthusiasts:
“[...] a decline in the coccolithophores may have secondary effects on climate change, by decreasing the earth’s albedo via their effects on oceanic cloud cover.”
Wikipedia – Ocean Acidification
http://en.wikipedia.org/wiki/Ocean_acidification
[a rather "alarmist" article - well worth assessing for political bias]

I would still like to know how sharp the NH dip is and what feature of the ecosystem can respond in such a rapid way!”

All you have to do to see the dip is difference the series (& then plot). [It is as simple as d(i+1) = CO2(i+1) - CO2(i). There are advantages to this approach (over making assumptions about annual structure, which will mess up attempts to go after subtle nuances).]

I too was hoping someone would share the “standard” 2-sentence overview of the Alert winter dip – to tide me over until I have time to venture into another massive branch of the research jungle.

I rarely (fully) trust any conclusions I see in any publication without performing analyses myself. Researchers have all sorts of formal training in (abstract, theoretical) statistics (including heavily-mathematical statistics, complete with loads of proofs & derivations), but the education system – which has other priorities – lacks focus on fundamental concepts, data analysis, and the application of sound judgement in data analysis.

My guess is that there will be plenty of datasets & publications, including a good number focused on short timescales. Publicly-available text-format data-websites are (arguably) essential in a knowledge society. Although I’m confident shorter timescale datasets exist, I suspect you’re right that they will not be long-term and I anticipate tediously-inefficient bureaucratic access-hoops (in most/many cases).

-
bill (19:12:15) “I admire your interest in these things.”

Likewise – & same regarding co-participants in the evolving confluence of science & democracy that occurs in these valuable forums.

I admire your interest in these things.
I think that CO2 is measured at a 2 weekly rate so you will find it difficult to find shorter period with long term records.

I would still like to know how sharp the NH dip is and what feature of the ecosystem can respond in such a rapid way!

bill

How much photosynthesis do you think happens at night (relative to during the day)? ..and in the polar regions during the polar-day versus during the polar-night (i.e. summer vs. winter)?

-
bill (15:36:33) “What is needed is a computer [...]“

Computers are certainly useful tools, but no computer is going to be able to substitute satisfactorily for sound human judgement in the foreseeable future.

-
bill (15:36:33) “You are looking at the minutiae, not at the important stuff [...] I am proposintg that the rate of change which Roy Spencer has plotted is not relevant neither to man nor beast [...] VERY true neither should the anti-AGW’s be allowed endanger the future.”

Do you think a boreal forest carbon-modeler would agree with your suggestion that we ignore seasonal variations?

I think you might seriously misunderstand my motivation (& the motivation of others).

My interest is in understanding nature, including nature’s nuances. As indicated above, prior to this thread I did not find CO2 to be a very interesting variable to study because all it shows (at annual resolution – & upon superficial inspection) in the modern 1958+ records is dull, monotone increase (which leaves little over which to puzzle).

I’m neither “anti-AGW” nor “pro-AGW”. I’m a student of nature [which includes humans], an advocate of careful analysis, and a proponent of balance.

-
bill (15:36:33) “So what effect are you proposing that the spatiotemporal variation will have on peoples views?”

The take-home message for the general public here might be something like this:

Thinking of CO2 equilibria-chain balances only in terms of a “global annual average” is far too simple.

–
Final comments:
No one (sensible) is trying to say CO2 is not increasing; (sensible) people are saying, “Let’s understand nature, including water.” I see no sensible reason for introducing biases about what spatiotemporal scales are worth understanding. We can draw no definitive conclusions until we understand the whole picture (if that’s even possible).

It is important to note here (for anyone following along) that the lags we are seeing in these data seem [far] more likely to be related to anti-phase than to delayed-response (although we cannot be absolutely certain based just on these data alone).

From what I can see there are 2 (main) cycles of differing amplitudes – & they are in anti-phase. This comes as no surprise, as this is what is seen in many other geophysical time series (on our north-south asymmetric Earth).

- – -
maksimovich (14:52:40) “[...] Ramanathan 2008 [...] “This implies that the cloud contribution to the planetary albedo due to feedbacks with natural and forced climate changes has not changed during the last 100 years” [...]“

Note the use of the word “implies”; this is another example of the flawed logic that many applied above (in this thread) in interpreting the 90/10 split in Dr. Spencer’s demonstrative-presentation. It stems from a deep misunderstanding of decomposition (& shared variance).