Chaos in climate change scenarios means chaos in climate change impact estimates?

I finished a first complete draft of the paper "Chaos in climate change impact estimates".


Why the 2011-2030 years averages of temperature anomaly in December, January, February are so different for the same General Circulation model that uses virtually identical emissions trajectories?

(Thanks to Paola Marson for generating these maps!)

What are the implications for the impacts literature?

Is it really possible to use high-resolution climate change scenarios to predict impacts at sub-regional level?

These are the questions that I address in this paper at the cross-road of climate science, economics and the impacts literature.


I copy the abstract below. The draft of the paper on GCM scenarios is ready and available here. A lot of maps and other Supplementary Material is available here.

Global Circulation Models incorporate chaotic dynamics to reflect real-world weather patterns. This implies that extremely small perturbations of the climate system may generate very different weather patterns. Here I show that the SRES climate change scenarios generated by the Coupled Model Intercomparison Project phase 3 (CMIP3) - ubiquitous in the impact literature - display strong chaotic dynamics at regional and sub-regional level, at least until 2065. Chaos is triggered by changes to historic forcing in the year 2000 to reflect different emissions trajectories. This suggests that large uncertainty exists on how to link local climate change and global forcing. Furthermore,  short- and mid-term differences in local climate change across different SRES emission scenarios reflect chaotic dynamics rather than different forcing patterns. I show that the "chaos" in the climate scenarios generates a "chaotic" relationship between exogenous forcing and local economic impacts. "Perturbed exogenous forcing" model ensemble would resolve this uncertainty.

Using Degree Days to Value Farmland?

We revisit the use of degree days to estimate land values in the United States using the rich NARR weather reanalysis. With temperature data at 3-hour time intervals since 1979 we compute degree days more precisely than in previous papers. We also review the agronomic literature to see if it appropriate or not to use degree days to predict plants' growth.



Using Degree Days to Value Farmland?

by Emanuele Massetti, Robert Mendelsohn and Shun Chonabayashi

Abstract: Farmland values have traditionally been valued using seasonal temperature and precipitation. A new strand of the literature argues that degree days over the growing season provide more accurate predictions of farmland value than seasonal temperature and that farmland values fall precipitously at 34⁰C. The paper shows that these hypotheses of the degree day literature fail when accurate measures of degree days are used.

The paper is available here. Supplementary material is available here.

EAERE Summer School 2014 on the Economics of Adaptation to Climate Change

Robert Mendelsohn and I will co-ordinate the 2014 EAERE Summer School. The Summer School is aimed at Ph.D. students that are already writing a thesis on the economics of adaptation to climate change and want to engage into a highly interactive exchange with experts in the field. Students will be asked to present an advanced version of their research work and will receive valuable feedback from fellow students and from the School professors. Students will also be assigned a tutor that will provide individual feedback during consultation time.

School co-ordinators: Emanuele MASSETTI and Robert MENDELSOHN

• Brian HURD
  Professor of Agricultural Economics and Agricultural Business
  New Mexico State University
  Topic: Water


• Emanuele MASSETTI (School co-coordinator)
  Senior Researcher
  Fondazione Eni Enrico Mattei - FEEM
  Topic: Adaptation in Agriculture


• Robert MENDELSOHN (School co-coordinator)
  Sterling Professor of Economics
  Yale University
  Topic: Introduction and tropical cyclones


• Richard S. J. TOL
  Professor of Economics
  University of Sussex
  Topic: Sea level rise and Integrated assessment modeling


• Brent SOHNGEN
  Professor of Economics
  Ohio State University
  Topic: Forestry and Ecosystems

from http://virgo.unive.it

A new presentation of "Chaos-in, Chaos-out" at the SISC conference in Lecce

On September 23 I gave a presentation of my paper "Chaos in, chaos out? The effect of chaos in GCM scenarios on estimates of climate change impacts" at the First SISC conference in Lecce.

The presentation is available here in pdf format.

I am making progress towards a final draft. This presentation has new estimates of climate change impacts, with regional detail and bootstrap confidence intervals. It clearly shows that the impact of noise in the climate change scenarios is statistically significant for many General Circulation Models.

A final draft will be ready soon.

Here I copy a figure that compares 2011-2030 temperature anomaly (w.r.t. 1961-1990) differences between the A2 and the A1B SRES scenarios at global level. Dark blue means that the area is much colder in the A2 scenario, and viceversa if the area is red. This figure shows how almost identical emission trajectories can lead to very different climate change scenarios at local level.

(as I am taking differences, degrees celsius and degrees kelvin are identical)