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Instrumental Record

NPP lift off

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The launch of the NASA/NOAA NPP satellite seems to have gone off without a hitch this morning which is great news. This satellite has instruments that are vital to continuing data streams that were pioneered on the aging TERRA (1999), AQUA (2002) and AURA (2004), satellites – including the CERES instrument for monitoring the Earth’s radiation budget, a microwave sounder to continue the AMSU data and a visible/IR camera to complement the work of MODIS.

We really need to apologise for the acronym soup though – it is an endemic disease in satellite discussions. Indeed, NPP is a recursive acronym, standing for NPOESS Preparatory Project, where NPOESS stands for the National Polar-Orbiting Operational Environmental Satellite System.

Another satellite mission we’ve mentioned here, Aquarius (launched in June), has recently released its first results on ocean salinity:




The patterns are not particularly surprising, there is higher salinity in the sub-tropical evaporative regions, lower salinity near the equator (because of the rain!), and particularly low salinity near big river outflows (the Amazon plume stands out clearly). However, as we noted earlier, the main interest is going to be in the variability.

Results from the NPP mission will take a while to come out and be cross-calibrated with the existing records, but given other recent disappointments (GLORY and OCO), this is a huge boost to the effort to monitor the Earth System.

Global warming and ocean heat content

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The connection between global warming and the changes in ocean heat content has long been a subject of discussion in climate science. This was explicitly discussed in Hansen et al, 1997 where they predicted that over the last few decades of the 20th Century, there should have been a significant increase in ocean heat content (OHC). Note that at the time, there had not been any observational estimate of that change (the first was in 2000 (Levitus et al, 2000)), giving yet another example of a successful climate model prediction. At RC, we have tracked the issue multiple times e.g. 2005, 2008 and 2010. Over the last few months, though, there have been a number of new papers on this connection that provide some interesting perspective on the issue which will certainly continue as the CMIP5 models start to get analysed.
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References

  1. S. Levitus, J.I. Antonov, T.P. Boyer, and C. Stephens, "Warming of the World Ocean", Science, vol. 287, pp. 2225-2229, 2000. http://dx.doi.org/10.1126/science.287.5461.2225

CRUTEM3 data release (except Poland)

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The entire CRUTEM3 database of station temperature measurements has just been released. This comes after a multi-year process to get permissions from individual National Weather Services to allow the passing on of data to third parties and from a ruling from the UK ICO. All the NWSs have now either agreed or not responded (except for Poland which specifically refused). Since the Polish data is a such a small fraction of the globe (and there are a few Polish stations in any case via RBSC or GCOS), this doesn’t make much difference to hemispheric means or regional climate. These permissions were obtained with help from the UK Met Office (who have also placed the station data on their website in a slightly different format) and whose FAQ is quite informative.

This dataset has occasionally come up in blogospheric discussions.

Reanalyses ‘R’ Us

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There is an interesting new wiki site, Reanalyses.org, that has been developed by a number of groups dedicated to documenting the various reanalysis products for atmosphere and ocean that are increasingly being made available.

For those that don’t know, a ‘reanalysis’ is a climate or weather model simulation of the past that includes data assimilation of historical observations. The observations can be very comprehensive (satellite, in situ, multiple variables) or relatively sparse (say, sea level pressure only), and the models themselves are quite varied. Generally these models are drawn from the weather forecasting community (at least for the atmospheric components) which explains the odd terminology. An ‘analysis’ from a weather forecasting model is the 6 hour (say) forecast from the time of observations. Weather forecasting groups realised a decade or so ago that the time series of their weather forecasts (the analyses) could not be used to track long term changes because their models had been updated many times over the decades. Thus the idea arose to ‘re-analyse’ the historical observations with a single consistent model. These sets of 6 hour forecasts using the data available at each point are then more consistent in time (and presumably more accurate) that the original analyses were.

The first two reanalysis projects (NCEP1 and ERA-40) were groundbreaking and allowed a lot of analysis of the historical climate (around 1958 or 1948 onwards) that had not been possible before. Essentially, the models are being used to interpolate between observations in a (hopefully) physically consistent manner providing a gridded and complete data set. However, there are noted problems with this approach that need to be borne in mind.

The most important issue is that the amount and quality of the assimilated data has changed enormously over time. Particularly in the pre-satellite era (around 1979), data is relatively sparse and reliant on networks of in-situ measurements. After 1979 the amount of data being brought in increases by orders of magnitude. It is also important to consider how even continuous measurement series have changed. For instance, the response time for sensors in radiosondes (that are used to track atmospheric profiles of temperature and humidity) has steadily improved which, if uncorrected for in the reanalyses, would lead to an erroneous drying in the upper troposphere that has nothing to do with any actual climate trend. In fact it is hard to correct for such problems in data coverage and accuracy, and so trend analysis in the reanalyses have to be treated very carefully (and sometimes avoided altogether).

A further problem is that different outputs from the reanalyses are differently constrained by observations. Where observations are plentiful and span the variability, the reanalysis field is close to what actually happened (for instance, horizontal components of the wind), but where the output field is only indirectly related to the assimilated observations (rainfall, cloudiness etc.), the changes and variability are much more of a product of the model.

The more modern products are substantially improved (NCEP-2, ERA-Interim, MERRA and others) over the first set, and new approaches are also being tried. The ‘20th Century Reanalysis‘ is a new product that only uses (plentiful) surface pressure measurements to constrain dynamics and although it uses less data than other products, it can go back much earlier (to the 19th Century) and still produce meaningful results. Other new products are the ocean reanalyses (ECCO for instance) that tries to take the same approach with ocean temperature and salinity measurements.

These products should definitely not be assumed to have the status of ‘real observations’, but they are very useful as long as people are careful to take the caveats seriously, and be clear about the structural uncertainties. Results that differ enormously across different reanalyses should be viewed with caution.

The new site includes some very promising descriptions on how to download and plot the data, and will hopefully soon be able to fill up the rest of pages. Some suggestions might be for a list of key papers discussing the results of these reanalyses and lists of issues found (so that others don’t waste their time). It’s a very promising start though.

Revisiting historical ocean surface temperatures

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Readers may recall discussions of a paper by Thompson et al (2008) back in May 2008. This paper demonstrated that there was very likely an artifact in the sea surface temperature (SST) collation by the Hadley Centre (HadSST2) around the end of the second world war and for a few years subsequently, related to the different ways ocean temperatures were taken by different fleets. At the time, we reported that this would certainly be taken into account in revisions of data set as more data was processed and better classifications of the various observational biases occurred. Well, that process has finally resulted in the publication of a new compilation, HadSST3.
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Rescuing data…

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Guest commentary by Vicky Slonosky

One of the lesser-known branches of climatology is historical climatology, the study of past climates from historical records of instrumental observations and weather descriptions, with “historical” often loosely taken to mean “pre-government-organized-meteorological or weather service” observations. In the last ten years or so, with the development of digital imaging, increased storage and processing capabilities of computers, it’s become possible to think about analyzing these past records on a daily basis. Snowstorms, hurricanes, cold snaps or heat waves all happen on daily scales, and daily information over the past 200 years or more let us learn more about them. All over the world, efforts (many unfunded) are going on to try to find and preserve these historical data from personal weather diaries, scientific observatories and naval records. This is often described as “data archeology and rescue”, which has a nice ring to it, and even manages to make going through dusty boxes in dustier basements and typing in the original (often handwritten) observations sound glamorous and exciting. It’s not a simple task though:

“All my attention for recent years has been directed to that branch of meteorology connected with ascertaining the mean temperature of Lower Canada. I had not made up my mind as to the fact of the climate having materially altered but was impressed generally with the belief that the climate had improved, or become warmer, as it had increased in population and cultivation … I resolved to make diligent search for such records as might be found in the Province, in order to answer this interesting question. The difficulty of this experience was even greater than I had anticipated. Few individuals had turned their attention to this (even now) infant science, at a period sufficiently removed to bear comparison with the present, and of those which I was fortunate enough to discover, many were unsuitable from the irregular manner in which they were kept … None but the most zealous meteorologist knows how very difficult it is to obtain observations in this science which can be depended upon.”

John Samuel McCord, acc. 0882, McCord Museum of Canadian History Archives, circa 1838.

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How easy it is to get fooled

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When you analyse your data, you usually assume that you know what the data really represent. Or do you? This has been a question that over time has marred studies on solar activity and climate, and more recently cosmic rays and clouds. And yet again, this issue pops up in two recent papers; One by Feulner (‘The Smithsonian solar constant data revisited‘) and another by Legras et al. (‘A critical look at solar-climate relationships from long temperature series.’). Both these papers show how easily it is to be fooled by your data if you don’t know what they really represent.

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Going to extremes

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There are two new papers in Nature this week that go right to the heart of the conversation about extreme events and their potential relationship to climate change. This is a complex issue, and one not well-suited to soundbite quotes and headlines, and so we’ll try and give a flavour of what the issues are and what new directions these new papers are pointing towards.
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West Antarctica: still warming

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The temperature reconstruction of O’Donnell et al. (2010) confirms that West Antarctica is warming — but underestimates the rate

Eric Steig

At the end of my post last month on the history of Antarctic science I noted that I had an initial, generally favorable opinion of the paper by O’Donnell et al. in the Journal of Climate. O’Donnell et al. is the peer-reviewed outcome of a series of blog posts started two years ago, mostly aimed at criticizing the 2009 paper in Nature, of which I was the lead author. As one would expect of a peer-reviewed paper, those obviously unsupportable claims found in the original blog posts are absent, and in my view O’Donnell et al. is a perfectly acceptable addition to the literature. O’Donnell et al. suggest several improvements to the methodology we used, most of which I agree with in principle. Unfortunately, their actual implementation by O’Donnell et al. leaves something to be desired, and yield a result that is in disagreement with independent evidence for the magnitude of warming, at least in West Antarctica.

In this post, I’ll summarize the key methodological changes suggested by O’Donnell et al., discuss how their results compare with our results, and the implications for our understanding of recent Antarctic climate change. I’ll then try to make sense of how O’Donnell et al. have apparently wound up with an erroneous result.
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