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2012 Updates to model-observation comparisons

Time for the 2012 updates!

As has become a habit (2009, 2010, 2011), here is a brief overview and update of some of the most discussed model/observation comparisons, updated to include 2012. I include comparisons of surface temperatures, sea ice and ocean heat content to the CMIP3 and Hansen et al (1988) simulations.
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Sea-level rise: Where we stand at the start of 2013 — Part 2

Filed under: — stefan @ 11 January 2013

This is Part 2 of my thoughts on the state of sea-level research. Here is Part 1.

Sea-level cycles?

A topic that keeps coming up in the literature is the discussion on a (roughly) 60-year cycle in sea level data; a nice recent paper on this is Chambers et al. in GRL (2012). One thing I like about this paper is its careful discussion of the sampling issue of the tide gauges, which means that variability in the tide gauges is not necessarily variability in the true global mean sea level (see Part 1 of this post). I want to add some thoughts on the interpretation of this variability. Consider this graph from my Response to Comments in Science (2007):


Fig. 1: Fifteen-year averages of the global mean temperature (blue, °C, GISS data) and rate of sea level rise (red, cm/year, Church&white data), both detrended.
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References

  1. D.P. Chambers, M.A. Merrifield, and R.S. Nerem, "Is there a 60-year oscillation in global mean sea level?", Geophysical Research Letters, vol. 39, pp. n/a-n/a, 2012. http://dx.doi.org/10.1029/2012GL052885
  2. S. Rahmstorf, "Response to Comments on "A Semi-Empirical Approach to Projecting Future Sea-Level Rise"", Science, vol. 317, pp. 1866d-1866d, 2007. http://dx.doi.org/10.1126/science.1141283

Sea-level rise: Where we stand at the start of 2013

Filed under: — stefan @ 9 January 2013

Progress has been made in recent years in understanding the observed past sea-level rise. As a result, process-based projections of future sea-level rise have become dramatically higher and are now closer to semi-empirical projections. However, process-based models still underestimate past sea-level rise, and they still project a smaller rise than semi-empirical models.

Sea-level projections were probably the most controversial aspect of the 4th IPCC report, published in 2007. As an author of the paleoclimate chapter, I was involved in some of the sea-level discussions during preparation of the report, but I was not part of the writing team for the projections. At the core of the controversy were the IPCC-projections which are based on process models (i.e. models that aim to simulate individual processes like thermal expansion or glacier melt). Many scientists felt that these models were not mature and understated the sea-level rise to be expected in future, and the IPCC report itself documented the fact that the models seriously underestimated past sea-level rise. (See our in-depth discussion published after the 4th IPCC report appeared.) That was confirmed again with the most recent data in Rahmstorf et al. 2012.
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References

  1. S. Rahmstorf, G. Foster, and A. Cazenave, "Comparing climate projections to observations up to 2011", Environ. Res. Lett., vol. 7, pp. 044035, 2012. http://dx.doi.org/10.1088/1748-9326/7/4/044035

A review of cosmic rays and climate: a cluttered story of little success

Filed under: — rasmus @ 25 December 2012

A number of blogs were excited after having leaked the second-order draft of IPCC document, which they interpreted as a “game-changing admission of enhanced solar forcing”.

However, little evidence remains for a link between galactic cosmic rays (GCR) and variations in Earth’s cloudiness. Laken et al. (2012) recently provided an extensive review of the study of the GCR and Earth’s climate, from the initial work by Ney (1959) to the latest findings from 2012.

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References

  1. B.A. Laken, E. Pallé, J. Čalogović, and E.M. Dunne, "A cosmic ray-climate link and cloud observations", J. Space Weather Space Clim., vol. 2, pp. A18, 2012. http://dx.doi.org/10.1051/swsc/2012018

Improving the Tropical Cyclone Climate Record

Filed under: — gavin @ 16 December 2012

Guest Commentary by Christopher Hennon (UNC Asheville)

Get involved in a new citizen science project at CycloneCenter.org.

The poor quality of the tropical cyclone (TC) data record provides severe constraints on the ability of climate scientists to: a) determine to what degree TCs have responded to shifts in climate, b) evaluate theories on how TCs will respond to climate change in the future. The root cause for the poor data is the severity of the TC conditions (e.g. high wind, rough seas) and the remoteness of these storms – the vast majority of which form and remain well away from most observing networks. Thus, most TCs are not observed directly and those that are (with buoys, aircraft reconnaissance, ships) are often not sampled sufficiently (see the IBTrACS, (Knapp et al., 2010)).

This leaves tropical cyclone forecasters, who are ultimately responsible for recording TC tracks and intensities (i.e. maximum wind speeds), with a challenging problem. Fortunately, there is a tool called the Dvorak Technique which allows forecasters to make a reasonable determination of the TC intensity by simply analyzing a single infrared or visible satellite image, which is almost always available Velden et al., 2006). The technique calls for the analyst to determine the center location of the system, the cloud pattern type, the degree of organization of the pattern, and the intensity trend. A maximum surface wind speed is determined after the application of a number of rules and constraints.

Hurricane Gay (1992)The Dvorak Technique has been used for many years at all global tropical cyclone forecast centers and has been shown in many cases to yield a good estimate of maximum TC wind speed, when applied properly (Knaff et al., 2010). However, there is a level of analyst subjectivity inherent in the procedure; the cloud patterns are not always clear, it is sometimes difficult to accurately determine the storm center and the rules and constraints have been interpreted and applied differently across agencies. This introduces heterogeneity in the global TC record since the Dvorak Technique is usually the only available tool for assessing the maximum wind speed.

There has been recent work to eliminate the human element in the Dvorak Technique by automating the procedure. The Advanced Dvorak Technique (ADT) uses objective storm center and cloud pattern schemes to remove the subjectivity (Olander and Velden, 2007). All other classification rules and constraints are then applied and combined with additional statistical information to produce automated intensity estimates. Although the ADT skill is comparable to experienced human Dvorak analysts, large errors can occur if the scene type is not identified properly.

A new crowd sourcing project, called Cyclone Center, embraces the human element by enabling the public to perform a simplified version of the Dvorak Technique to analyze historical global tropical cyclone (TC) intensities (Hennon, 2012). Cyclone Center’s primary goal is to resolve discrepancies in the recent global TC record arising principally from inconsistent development of tropical cyclone intensity data. The Cyclone Center technique standardizes the classification procedure by condensing the Dvorak Technique to a few simple questions that can be answered by global, nonprofessional users.

One of the main advantages of this approach is the inclusion of thousands of users, instead of the 1-3 who would normally classify a TC image. This allows the computation of measures of uncertainty in addition to a mean intensity. Nearly 300,000 images, encompassing all global TCs that formed from 1978-2009, will be classified 30 times each – a feat that would take a dedicated team of twenty Dvorak-trained experts about 12 years to complete. Citizen scientists have already performed over 100,000 classifications since the project launch in September. Once the project is complete, a new dataset of global TC tracks and intensities will be made available to the community to contribute to our efforts to provide the best possible TC data record.

Interested readers are encouraged to learn more about and participate in the project at the cyclonecenter.org website (there are some FAQ on the project blog). The CycloneCenter project is a collaboration between the Citizen Science Alliance, NOAA National Climatic Data Center (NCDC), University of North Carolina at Asheville, and the Cooperative Institute for Climate and Satellites (CICS) – North Carolina.

References

  1. K.R. Knapp, M.C. Kruk, D.H. Levinson, H.J. Diamond, and C.J. Neumann, "The International Best Track Archive for Climate Stewardship (IBTrACS)", Bulletin of the American Meteorological Society, vol. 91, pp. 363-376, 2010. http://dx.doi.org/10.1175/2009BAMS2755.1
  2. C. Velden, B. Harper, F. Wells, J.L. Beven, R. Zehr, T. Olander, M. Mayfield, C. Guard, M. Lander, R. Edson, L. Avila, A. Burton, M. Turk, A. Kikuchi, A. Christian, P. Caroff, and P. McCrone, "The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite-Based Method that Has Endured for over 30 Years", Bulletin of the American Meteorological Society, vol. 87, pp. 1195-1210, 2006. http://dx.doi.org/10.1175/BAMS-87-9-1195
  3. J.A. Knaff, D.P. Brown, J. Courtney, G.M. Gallina, and J.L. Beven, "An Evaluation of Dvorak Technique–Based Tropical Cyclone Intensity Estimates", Wea. Forecasting, vol. 25, pp. 1362-1379, 2010. http://dx.doi.org/10.1175/2010WAF2222375.1
  4. T.L. Olander, and C.S. Velden, "The Advanced Dvorak Technique: Continued Development of an Objective Scheme to Estimate Tropical Cyclone Intensity Using Geostationary Infrared Satellite Imagery", Wea. Forecasting, vol. 22, pp. 287-298, 2007. http://dx.doi.org/10.1175/WAF975.1
  5. C.C. Hennon, "Citizen scientists analyzing tropical cyclone intensities", Eos, Transactions American Geophysical Union, vol. 93, pp. 385, 2012. http://dx.doi.org/10.1029/2012EO400002

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