James Annan's old Home Page

This is not my current page - as of December 2013 I no longer work at JAMSTEC. Come and find me at blueskiesresearch.org.uk or email jdannan(at)blueskiesresearch.org.uk.

I'll leave this up for posterity and redirection purposes
(JAMSTEC may kill it at any time).

Contents

This page contains a brief introduction to my work and some recent publications. I can be emailed here (address weakly obscured).
 


My personal (non-work) homepage is mostly full of photos of Japan, and can be found here. I have a blog too.

 

Research in probabilistic climate prediction

I am a member of the Global Change Projection Research Programme at RIGC (formerly known as FRCGC, and before that FRSCG, as you might guess from the URL). I was (2010-13) mostly working on ways to use the CMIP3 multi-model ensemble. This seems to be a hot topic these days, the IPCC held an Expert Meeting early in 2010:
"The expert meeting will provide tentative best practices in selecting and combining results from multiple models for IPCC AR5; in short the beginning of a quantitative framework for analysis and assessment of the models. Specific aims of the meeting will be to maximize the robustness and policy relevance of the projections provided in the presence of model error, projection uncertainty, observational uncertainties and a heterogeneous set of models."
Unfortunately, it seems to me that much of what has been written about the multi-model ensemble is misleading, inadequate or plain wrong. I'm writing a series of papers through which I hope to correct some misunderstandings. The first of these was this one published in GRL at the start of 2010 (see also this follow-up), this one eventually got into J Climate and there is another GRL paper here. I think there's still a bit of work to do on this, especially on the topic of model independence (what do we even mean to call models independent?) and how/why to discard or downweight models from the ensemble.

Another major interest of mine is the use of paleoclimate simulations to assess and evaluate climate models. According to the climate models, we can expect our current climate to change substantially through the current century (and beyond, for as long as we keep on emitting large quantities of CO2). Paleoclimates provide the only opportunity to actually evaluate the models' ability to simulate substantially different climates to today's, through the comparison of these simulations with proxy data. The proxy data are limited and imprecise, and the most recent paleoclimate eras - for which data are most plentiful and reliable - were generally colder rather than warmer than the present, but such testing is surely better than nothing. For the most part, the models seem to do a mostly reasonable job, as far as we can tell - but with substantial regional problems, inasmuch as the proxy data can be trusted. I've recently analysed proxy data and models to generate a new reconstruction of temperature at the Last Glacial Maximum and used this result for another estimate of climate sensitivity here.

Previously, I mostly worked on the problem of parameter estimation in single-model ensembles and its specific relevance to climate prediction (but now I'm not so convinced that single model ensembles are a good idea). Some of my work has been in collaboration with the UK-based GENIE project, and the rest is mostly in collaboration with other researchers here at RIGC, also with NIES and CCSR. There are now several researchers here working on related topics forming the JUMP group.

Betting on Climate Change

I'm also interested in the use of prediction markets and ideas futures. Here's a page I wrote, based on a poster presentation I gave at the EGU in 2005. I've also had an article published on realclimate.org on the same topic. It's not clear yet where, if anywhere, it is going, but it's been interesting and instructive so far. I've co-authored various articles with some financial people - to be honest, this is almost all Daniel Bloch's work - which can be found on the SSRN site through this link. The main problem with getting anything meaningful established is the long time scale associated with climate-change related damage, especially sea level rise.

I obviously shouldn't omit to mention the loss of one bet with David Whitehouse from the pressure group Global Warming Policy Foundation. I was expecting the 1998 record (in the Hadley Centre analysis) to be beaten in the 4 years 2008-2011 inclusive, and according to HadCRUT3, this did not occur. Interestingly, but unknown to me at the time, they had been working on an improved version of their temperature analysis HadCRUT4, with improved data coverage. According to this new analysis, 2010 (and also 2005) actually was warmer than 1998.


Publications (almost all peer-reviewed, selected non-reviewed in italics)

2013

Set of 4 non-reviewed articles in PAGES Newsletter number 21(2):
(1) G.J. Hakim, J. Annan, S. Brę”nnimann, M. Crucifix, T. Edwards, H. Goosse, A. Paul, G. van der Schrier and M. Widmann Overview of data assimilation methods
(online here)
(2) S. Brę”nnimann, J. Franke, P. Breitenmoser, G. Hakim, H. Goosse, M. Widmann, M. Crucifix, G. Gebbie, J. Annan and G. van der Schrier Transient state estimation in paleoclimatology using data assimilation (online here)
(3) T.L. Edwards, J. Annan, M. Crucifix, G. Gebbie and A. Paul Best-of-both-worlds estimates for timeslices in the past (online here)
(4) J.D. Annan, M. Crucifix, T.L. Edwards and A. Paul Parameter estimation using paleo-data assimilation (online here)

G. A. Schmidt, J. D. Annan, P. J. Bartlein, B. I. Cook, E. Guilyardi, J. C. Hargreaves, S. P. Harrison, M. Kageyama, A. N. LeGrande, B. Konecky, S. Lovejoy, M. E. Mann, V. Masson-Delmotte, C. Risi, D. Thompson, A. Timmermann, L.-B. Tremblay, and P. Yiou. Using paleo-climate comparisons to constrain future projections in CMIP5. Climate of the Past Discussions (under review).

T. Yokohata, J. D. Annan, M. Collins, C. S. Jackson, H. Shiogama, M. Watanabe, S.  Emori, M. Yoshimori, M. Abe, M. J. Webb, and J. C. Hargreaves.
Reliability and importance of structural diversity of climate model ensembles. Climate Dynamics doi: 10.1007/s00382-013-1733-9, (here).

J. C. Hargreaves, J. D. Annan, R. Ohgaito, A. Paul, and A. Abe-Ouchi. Skill and reliability of climate model ensembles at the Last Glacial Maximum and mid-Holocene. Clim. Past, 9, 811-823, doi:10.5194/cp-9-811-2013 (on-line)

E. J. Stone, D. J. Lunt, J. D. Annan and J. C. Hargreaves.
Quantification of the Greenland ice sheet contribution to Last Interglacial sea level rise. Clim. Past, 9, 621-639, 2013 doi:10.5194/cp-9-621-2013 (on-line)

J. D. Annan and J. C. Hargreaves. A new global reconstruction of temperature changes at the Last Glacial Maximum, Clim. Past, 9, 367-376, doi:10.5194/cp-9-367-2013 (on-line)

2012

J. C. Hargreaves, J. D. Annan, M. Yoshimori and A. Abe-Ouchi. Can the Last Glacial Maximum constrain climate sensitivity? GRL 39 doi:10.1029/2012GL053872 (here)

J. J. Day,
J. C. Hargreaves, J. D. Annan and A. Abe-Ouchi. Sources of multi-decadal variability in Arctic sea ice extent. Environmental Research Letters 7 doi:10.1088/1748-9326/7/3/034011 (here).

H. Shiogama, M. Watanabe, M. Yoshimori, T. Yokohata, T. Ogura, J. D. Annan, J. C. Hargreaves, M. Abe, Y. Kamae, R. O°«ishi, R. Nobui, S. Emori, T. Nozawa, A. Abe-Ouchi and M Kimoto. Perturbed Physics Ensemble using the MIROC5 Coupled Atmosphere-Ocean GCM without Flux Corrections: Experimental Design and Results. Climate Dynamics, DOI: 10.1007/s00382-012-1441-x (here).

J. D. Annan and J. C. Hargreaves. Identification of climatic state with limited proxy data. Clim. Past 8 pp 1141-1151. (on-line).

K. Tachiiri, A. Ito, T. Hajima, J. C. Hargreaves, J. D. Annan, M. Kawamiya.
Nonlinearity of Land Carbon Sensitivities in Climate Change Simulations, Journal of the Meteorological Society of Japan, vol 90A, pp 259-274 (on-line)

L. Das, J. D. Annan, J. C. Hargreaves, S. Emori. Improvements over three generations of climate model simulations for eastern India. Clim. Res. (2012) vol. 51 (3) pp. 201-216. (on-line).

M. Watanabe, H. Shiogama, T. Yokohata, Y. Kamae, M. Yoshimori, T. Ogura, J. D. Annan, J. C. Hargreaves, S. Emori, and M. Kimoto. Using a Multi-Physics Ensemble for Exploring Diversity in Cloud-Shortwave Feedback in GCMs, J Clim vol. 25, issue 15, pp. 5416-5431 doi:10.1175/JCLI-D-11-00564.1 (here)

2011


J. D. Annan, J. C. Hargreaves and K. Tachiiri. On the observational assessment of climate model performance GRL vol 38, L24702, 2011 doi:10.1029/2011GL049812 (here)

T. Yokohata, J. D. Annan, M. Collins, C. S. Jackson, M. Tobis, M. J. Webb and J. C. Hargreaves. Reliability of multi-model and structurally different single-model ensembles, Climate Dynamics 39, p599-616. DOI 10.1007/s00382-011-1203-1 (here).

J. C. Hargreaves, A. Paul, R. Ohgaito, A. Abe-Ouchi, and J. D. Annan. Are paleoclimate model ensembles consistent with the MARGO data synthesis? Climate of the Past 7, 917–933, doi:10.5194/cp-7-917-2011 (here)

M. Yoshimori, J. C. Hargreaves, J. D. Annan, T. Yokohata and A. Abe-Ouchi. Dependency of Feedbacks on Forcing and Climate State in Physics Parameter Ensembles. Journal of Climate 24, 6440-6455 (here)

J. D. Annan and J. C. Hargreaves, Understanding the CMIP3 multi-model ensemble, Journal of Climate 24, 4529–4538. doi: 10.1175/2011JCLI3873.1 (here).

J. D. Annan and J. C. Hargreaves, Reply to Henriksson et al.'s comment on "Using multiple observationally-based constraints to estimate climate sensitivity" by Annan and Hargreaves (2010). Clim. Past, 7, 587-589, doi:10.5194/cp-7-587-2011 (on-line)

L. Das, J. D. Annan, J. C. Hargreaves and S. Emori, Centennial scale warming over Japan: are the rural stations really rural? Atmospheric Science Letters, DOI:10.1002/asl.350 (on-line)

J. D. Annan and J. C. Hargreaves, On the generation and interpretation of probabilistic estimates of climate sensitivity. Climatic Change Vol 104 Nos 3-4  DOI: 10.1007/s10584-009-9715-y (here it is).

2010

K. Tachiiri, J. C. Hargreaves, J. D. Annan, A. Oka, A. Abe-Ouchi and M. Kawamiya. Development of a system emulating the global carbon cycle in Earth system models, Geosci. Model Dev., 3, 365-376, 2010 (here)

J. D. Annan, Bayesian approaches to detection and attribution, Wiley Interdisciplinary Reviews: Climate Change DOI: 10.1002/wcc.47 (here)


G. Foster, J. D. Annan, P. D. Jones, M. E. Mann, B. Mullan, J. Renwick, J. Salinger, G. A. Schmidt, and K. E. Trenberth, Comment on °»Influence of the Southern Oscillation on tropospheric temperature°… by J. D. McLean, C. R. de Freitas, and R. M. Carter. JGR Atmospheres, Vol. 115, D09110, 2010 doi:10.1029/2009JD012960 (here) with no accompanying reply from McLean et al because their manuscript was judged to be unsuitable for JGR.

T. Yokohata, M. J. Webb, M. Collins, K. D. Williams, M. Yoshimori, J. C. Hargreaves, J. D. Annan, Structural similarities and differences in climate responses to CO2 increase between two perturbed physics ensembles. Journal of Climate 23(6) 1392-1410 (here).

J. D. Annan and J. C. Hargreaves, Efficient identification of ocean thermodynamics in a physical/biogeochemical ocean model with an iterative Importance Sampling method, Ocean Modelling 32 (3-4) 205-215 (here).

J. D. Annan and J. C. Hargreaves, Reliability of the CMIP3 ensemble, Geophys. Res. Lett., 37, L02703, doi:10.1029/2009GL041994 (on-line) and see also my blog.

2009

J. C. Hargreaves and J. D. Annan, The importance of paleoclimate modelling for improving predictions of future climate change, Clim. Past, 5,803-814 (on-line here)

M. Abe, H. Shiogama, J. C. Hargreaves, J. D. Annan, T. Nozawa and S. Emori, Correlation between Inter-model Similarities in Spatial Pattern for Present and Projected Future Mean Climate, SOLA, Vol.5, 133-136, doi:10.2151/sola.2009-034 (on-line)

J. C. Hargreaves and J. D. Annan, Comment on "Aerosol radiative forcing and climate sensitivity deduced from the Last Glacial Maximum to Holocene transition", by P. Chylek and U. Lohmann, Geophys. Res. Lett., 2008. Clim. Past, 5, 143-145, 2009 (on-line)

P. J. Michaels, P. C. Knappenberger, J. R. Christy, C. S. Herman, L. M. Liljegren, J. D. Annan. Assessing the consistency between short-term global temperature trends in observations and climate model projections. Rejected by GRL, but the main conclusion seems widely accepted now (Arxived).

2008

G. Foster, J. D. Annan, G. A. Schmidt and M. E. Mann, Comment on `Heat capacity, time constant and sensitivity of Earth's climate system' by S. Schwartz Vol. 113, D15102, doi:10.1029/2007JD009373 (on-line here), with some blog coverage here and here.

2007

F. W. M. Brown, R. A. Pielke and J. D. Annan, Is there agreement amongst climate scientists on the IPCC AR4 WG1? Unpublished.

J. C. Hargreaves, A. Abe-Ouchi, J. D. Annan. Linking glacial and future climates through an ensemble of GCM simulations. Climate of the Past, 3, 77-87 (on-line).

A. Ridgwell, J. C. Hargreaves, N. R. Edwards, J. D. Annan, T. M. Lenton, R. Marsh, A. Yool, A. Watson. Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling. Biogeosciences 4, 87-104 (their version).

J.D. Annan and J.C. Hargreaves, Efficient estimation and ensemble generation in climate modelling, Philosophical Transactions of the Royal Society A 365(1857). 2077-2088.

T. Lenton, Y. Aksenov, J.D. Annan, T. Cooper-Chadwick, S. Cox, N. Edwards, S. Goswami, J.C. Hargreaves, P. Harris, Z. Jiao, V. Livina, D. Lunt, R. Marsh, T. Payne, A. Price, A. Ridgwell, I. Rutt, J.G. Shepherd, P. Valdes, G. Williams, M. Williamson, A. Yool., A modular, scalable, Grid ENabled Integrated Earth system modelling (GENIE) framework: Effects of dynamical atmosphere and ocean resolution on bi-stability of the thermohaline circulation, Climate Dynamics DOI 10.1007/s00382-007-0254-9 (their version).

I. Andreu-Burillo, J. Holt, R. Proctor, J. D. Annan, I. D. James and D. Prandle. Assimilation of sea surface temperature in the POL Coastal Ocean Modelling System. Journal of Marine Systems 65, 1-4, 27-40 (their version).

S. L. Smith, B. E. Casareto, M. P. Niraula, Y. Suzuki, J. C. Hargreaves, J. D. Annan and Y. Yamanaka. Examining the regeneration of nitrogen by assimilating Data from Incubations into a Multi-Element Ecosystem Model. Journal of Marine Systems 64, 1-4, 135-152 (their version).

2006

J. D. Annan and J. C. Hargreaves. Using multiple observationally-based constraints to estimate climate sensitivity, Geophys. Res. Lett., 33, L06704, doi:10.1029/2005GL025259 (their on-line version). My commentary on this paper.

J. C. Hargreaves and J. D. Annan. Using ensemble prediction methods to examine regional climate variation under global warming scenarios. Ocean Modelling Vol 11 Nos 1-2 p174-192 (their on-line version). This was Ocean Modelling's most downloaded article (for 9 months to Jan 2006, but no longer)!

2005

J. D. Annan, J. C. Hargreaves, R. Ohgaito, A. Abe-Ouchi, S. Emori. Efficiently constraining climate sensitivity with paleoclimate simulations. SOLA Vol 1 pages 181-184.

J. D. Annan, D. J. Lunt, J. C. Hargreaves and P. J. Valdes. Parameter estimation in an atmospheric GCM using the Ensemble Kalman Filter. Nonlinear Processes in Geophysics 12 (3), pages 363-371 (their on-line version).

J. D. Annan. Parameter estimation using chaotic time series. Tellus A Vol 57 No 5 pp 709-714.

J. D. Annan, J. C. Hargreaves, N. R. Edwards and R. Marsh. Parameter estimation in an intermediate complexity Earth System Model using an ensemble Kalman filter. Ocean Modelling, Volume 8, Issues 1-2, Pages 135-154. (On-line version for subscribers - which is OM's 5th most downloaded article, April 2004-March 2005)

2004

J. D. Annan. Fundamental error in "Trends in serious head injuries..." Cook and Sheikh 2003. Injury Prevention Online. (Not related to my real job!)

J. C. Hargreaves, J. D. Annan, N. R. Edwards and R. Marsh. Climate forecasting using an intermediate complexity Earth System Model and the Ensemble Kalman Filter.  Climate Dynamics Vol 23 Nos 7-8, pp 745-760, DOI: 10.1007/s00382-004-0471-4.

J. D. Annan and J. C. Hargreaves. Efficient parameter estimation for a highly chaotic system. Tellus A, Vol 56 No 5, Pages 520-526 (On-line version).

J. D. Annan. On the orthogonality of Bred Vectors. Monthly Weather Review, Vol 132, No 3, pp 843-849.

2003

C. Huntingford, J. C. Hargreaves, T. M. Lenton and J. D. Annan. Extent of partial ice cover due to carbon cycle feedback in a zonal energy balance model. Hydrology and Earth System Science 7, pp213-219.

2002

J. C. Hargreaves and J. D. Annan. Assimilation of paleo-data in a simple Earth system model. Climate Dynamics Vol 19 Nos 5-6, pp371-381.

2001

J. K. Hargreaves, A. Ranta, J. D. Annan and J. C. Hargreaves,  The temporal fine structure of night-time spike events in auroral radio absorption, studied by a wavelet method. Journal of Geophysical Research, 106(A11):24621--24636.

J. D. Annan. Hindcasting coastal sea levels in Morecambe Bay. Estuarine, Coastal and Shelf Science Vol 53 Issue 4, pp459-466.

J. D. Annan. Modelling under uncertainty: Monte Carlo methods for temporally varying parameters. Ecological Modelling, 136(2--3):297--302.

2000

F. Chen and J. D. Annan. The influence of different turbulence closure schemes on modelling primary production in a 1D coupled physical-biological model. Journal of Marine Systems 26:259--288.

J. C. Hargreaves and J. D. Annan. Comments on ``Improvement of the Short-Fetch Behaviour in the Wave Ocean Model (WAM)''. Journal of Atmospheric and Oceanic Technology, 18(4):711--715.


1999

J. D. Annan. Reply to ``Comments on the paper: On repeated parameter sampling in Monte Carlo simulations''. Ecological Modelling 124:255--257.

J. C. Hargreaves and J. D. Annan. The impact of fierce weather on lazy modelling. In The wind-driven air-sea interface, M. Banner (Editor), ADFA Document Production Centre, Canberra, Australia, 125--132.

J. D. Annan and J. C. Hargreaves. Sea surface temperature assimilation for a three-dimensional baroclinic model of shelf seas. Continental Shelf Research, 19:1507--1520 (on-line).

J. D. Annan. Numerical methods for the solution of the turbulence energy equations in shelf seas. International Journal for Numerical Methods in Fluids, 29:193--206.

1997

J. D. Annan.  On repeated parameter sampling in Monte Carlo simulations. Ecological Modelling 97(1--2):111--115.

1996

J. C. Hargreaves, G. Gilmore and J. D. Annan. The influence of binary stars on Dwarf Spheroidal Galaxy kinematics. Monthly Notices of the Royal Astronomical Society 279(1):108--120.

1995

J. D. Annan. The complexities of the coefficients of the Tutte polynomial. Discrete Applied Maths 57:93-103.

1994

J. D. Annan. An approximation algorithm for counting the number of forests in dense graphs. Combinatorics, Probability and Computing 3:273-283.

J. D. Annan. The complexity of counting problems. D. Phil. Thesis, University of Oxford.





Last updated December 2013