Research and Publications


I’m interested in understanding how climate behaves on decadal to centennial timescales. My research focuses on paleoclimate, in particular the past 2,000 years (a.k.a the Common Era). I use paleoclimate reconstruction to understand the temporal evolution of temperature, and spatial patterns of the temperature field. The former puts the recent global warming in a broader context, and the latter lends insight into the understanding of dynamics of the climate system.


Paleoclimate reconstruction

Instrumental temperature records are only available for the past 150 years or so. In order to get a longer history of temperature, we turn to proxies and look at how they express climate signals. We treat proxies as observations of past climate, and with the help of statistical tools we extract climate information of the past. This process is called reconstruction, and has been widely used in geosciences across all timescales.

The crediblity of paleoclimate reconstructions largely depends on two aspects: proxy data being used and statistical methods being employed. How reliable is a climate reconstruction? To what extent can we trust the reconstructed climate? The answers are not simple. In fact, the shortness of instrumental data and scarcity of proxy data make it extremely challenging to assess how well a reconstruction can be. In my research, I use pseudoproxy experiments to isolate the methodological impact, and conduct proxy quality control experiment to evaluate the data impact. 

Data challenges: In a multi-proxy setting, different types of proxies are assembled in the same dataset. They differ in length, resolution, the degree of their sensitivity to temper- ature and they may respond to temperature of different seasons. Furthermore, the sparsity of proxy network adds an additional level of complexity to reconstructing past climate based on multi-proxies. All these reveal the challenge of conducting multi-proxy reconstructions, and the difficulty of isolating individual factors that contribute to reconstruction uncertainty.

Statistical challenge: From a statistical point of view, deriving CFRs is challenging because of the data’s high dimensionality: yearly instrumental temperature observations (T) are only available for the past ∼150 years, and the number of proxies (P) is on the order of several hundreds to thousands. In other words, there are very few degrees of freedom available to estimate the variables. Statistically speaking, it is a rank-deficiency problem, where covariance matrix (which quantifies relationships between proxies and temperature) is singular (non-invertible), and traditional regression methods are no longer applicable. 

We show that the choice of staistical method for reconstruction can drastically change reconstruction results. In particular, a reconstructed La Niña-like pattern during the transition from the Medieval Climate Anomaly (MCA) to the Little Ice Age (LIA) has been widely tied to medieval droughts in southwest North America. This pattern is now used as a key benchmark for global climate models (GCMs), which have yet to reproduce it. I tested the pattern's robustness by using four different CFR methods and two proxy networks. With the older network, the reconstructed patterns is highly method-dependent, with the La Niña-like pattern not reproduced by two of the CFR methodologies. With an updated proxy network (PAGES2k), a globally uniform MCA emerges with all methods, in agreement with simulations from the Paleoclimate Model Intercomparison Project Phase 3 (PMIP3) ensemble.



Wang, J., Emile-Geay, J., Guillot, D., Smerdon, J.E.: Evaluating climate field reconstruction techniques using improved emulations of real-world conditions. Clim. Past, 10, 1-19, 2014

Wang, J., Emile-Geay, J., Guillot, D., Mckay, N. P., Rajaratnam, B.: Fragility of reconstructed temperature patterns over the Common Era. Implications for model evaluation., in revision, Geophys. Res. Lett.

Wang, J., Emile-Geay, Mckay, N. P., J., Guillot, D., Vaccaro, A.D.: The climate continuum in a global multi-proxy temperature reconstruction spanning the Common Era, in prep 


Academic Presentations

4th Asia 2k Workshop, Kyoto, Japan, Talk, March 2015

  • Asia 2k in a broader context: A comparison between regional and global surface temperature reconstructions (invited).

AGU Fall Meeting, San Francisco, CA, Talk, December 2014 

4th International Workshop on Climate Informatics, Boulder, CO, Poster, Sept 2014 

COAA-SCC 2014 Annual Workshop, La Jolla, CA, Talk, Sept 2014 

  • Global temperature reconstructions of the Common Era (best presentation award).

3rd Asia 2k Workshop, Beijing, China, Talk, May 2014 

  • Fragility of estimated spatial temperature patterns in climate field reconstructions of the CE (invited).

EGU General Assembly, Vienna, Austria, Talk, April 2014 

Advances in CFR Workshop, Woods Hole, MA, Talk, April 2014 

  • Experimental temperature field reconstructions with the PAGES 2k network (invited).

AGU Fall Meeting, San Francisco, CA, Talk, December 2013 

7th Graduate Climate Conference, Woods Hole, MA, Poster, November 2013 

  • Temperature reconstructions of the CE: Impact of methods and source data (with travel award).

10th Urbino Summer School in Paleoclimatology, Urbino, Italy, Poster, July 2013 

  • A review of large-scale temperature reconstructions of the Common Era (with travel award).

12th International Meeting of Statistical Climatology, Jeju, Korea, Talk, June 2013 

  • Impacts of methodology and source data on large-scale temperature reconstructions.

PAGES 4th OSM and 2nd YSM, Goa, India, Poster, February 2013

  • A pseudoproxy evaluation of four climate field reconstruction methods using improved emulations of real-world conditions (with travel award).

AGU Fall Meeting, San Francisco, CA, Poster, December 2012 

AGU Fall Meeting, San Francisco, CA, Poster, December 2011 


  • Jianghao Wang
  • 3651 Trousdale Pkwy, ZHS 117
  • Los Angeles, CA, 90089