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)

High Resolution Climate Change Scenarios in IAMs: Chaos In, Chaos Out?

On July 9 I attended a workshop "Integrated Assessment of International Climate Change Policies" organized by Ifo in Munich.

I presented for the first time my work on climate change scenarios. Still very preliminary, but in progress.

The presentation is available here.

In brief:

GCMs incorporate deterministic chaos to reflect real-world chaotic dynamics of weather. This implies that small changes in external forcing can generate very different weather patterns, especially at local level. By using the Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset I show that small variations in Greenhouse Gas Emissions (GHG) and other forcing agents across the SRES scenarios generate substantial different climate scenarios in the US. By using a Ricardian model of climate change impacts on agriculture I show that the “noise” in the climate scenarios generates a “noisy” relationship between global GHG concentrations and local impacts. This implies that climate change scenarios from the CMIP3 dataset - used for the IPCC AR4 - should be used with caution. This problem might be limited by providing model ensemble runs that use same initial conditions but introduce small perturbations around the central exogenous forcing scenario.

Longer presentation of the degree days paper

On June 20 2013 I gave a longer presentation of the paper "How Does Temperature Affect Land Values in the US?" at FEEM in Venice.

We introduce degree hours that were not tested in the previous draft of the paper.

The presentation is available here. The paper is still a work in progress.

AERE meeting in Banff

On June 7 2013 I presented the ongoing work with Robert Mendelsohn and Shun Chonabayashi on the use of degree days to study how climate affects land values in the US at the AERE Summer meeting in Banff.

The presentation is available here.

The paper is still a work in progress and it may change. I copy the abstract here:

We test three functional forms that relate land values and temperatures in a Ricardian model of US agriculture for the East of the US: a quadratic relationship based on average seasonal temperature and precipitations, a non-linear relationship based on degree days and a flexible functional form in which average seasonal temperatures are interacted with dummies. Results obtained using growing season average temperature and degree days are not significantly different. We do not find evidence of a threshold if we include degree days above 34 °C. Cold degree days instead matter and should not be omitted. Models that use a quadratic specification of average temperatures perform better than models that use degree days. This is in line with the agronomic literature. Degree days should be used to estimate the duration of phenological events rather than yields. Estimates of uniform +2 °C and +4 °C warming indicate that warming is significantly harmful for agriculture in the East of the US. The use of a more flexible functional form reveals that the relationship between temperatures and land values is flatter than in the quadratic. Seasons, within and outside the growing season, significantly affect land values and allow separating beneficial and harmful effects of warming more effectively.

Back to FEEM after Post Doc at Yale

Back at FEEM for the third year of my Marie Curie Outgoing Fellowship after two wonderful years at Yale!

The impact of climate change on European Agriculture

A recent paper on the impact of climate change on EU agriculture just came out as FEEM WP.

We use for the first time the Ricardian method at a continental EU scale. Things get bad for Mediterranean countries


Steven Van Passel, Emanuele Massetti, Robert Mendelsohn. 2012. "A Ricardian Analysis of the Impact of Climate Change on European Agriculture." FEEM Note di Lavoro 2012.083, November 2012.

Abstract:

This research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. Data on climate, soil, geography and regional socio-economic characteristics were matched for 37 612 individual farms across the EU-15. Farmland values across Europe are sensitive to climate. Even with the adaptation captured by the Ricardian technique, farms in Southern Europe are predicted to suffer sizeable losses (8% -13% per degree Celsius) from warming. In contrast, agriculture in the rest of Europe is likely to see only mixed impacts. Increases (decreases) in rain will increase (decrease) average farm values by 3% per centiliter of precipitation. Aggregate impacts by 2100 vary depending on the climate model scenario from a loss of 8% in a mild scenario to a loss of 44% in a harsh scenario.

Green Perspectives: a special issue of Energy Economics

Open access available to the new paper on investments under climate policy: here.

The whole special issue on "green perspectives", edited by Brian Flannery and Richard Tol is open access.

Here is the table of content with links:

Foreward
Page S1
Brian Flannery

From “Green Growth” to sound policies: An overview Original Research Article
Pages S2-S6
Richard Schmalensee

Energy and technology lessons since Rio
Pages S7-S14
James Edmonds, Katherine Calvin, Leon Clarke, Page Kyle, Marshall Wise

Investments and public finance in a green, low carbon, economy
Pages S15-S28
Carlo Carraro, Alice Favero, Emanuele Massetti

Financing for climate change
Pages S29-S33
Richard N. Cooper

Clean energy: Revisiting the challenges of industrial policy
Pages S34-S42
Adele C. Morris, Pietro S. Nivola, Charles L. Schultze

The elusive and expensive green job
Pages S43-S52
Diana Furchtgott-Roth

The potential role of carbon labeling in a green economy
Pages S53-S63
Mark A. Cohen, Michael P. Vandenbergh

Reducing greenhouse gas emissions through operations and supply chain managementArticle
Pages S64-S74
Erica L. Plambeck

Greening Africa? Technologies, endowments and the latecomer effect
Pages S75-S84
Paul Collier, Anthony J. Venables

Green growth and the efficient use of natural resources
Pages S85-S93
John M. Reilly