Presentation at COP 19 in Warsaw

On Thursday, November 21, I did a quick stop in Warsaw for the FEEM-CMCC-University of Venice side event at COP 19.

I gave a presentation for the general public on the benefits of adaptation, with a focus on the benefit for public finances. The presentation is available here.

The panel included:

Dr. Corrado Clini
General Director of Sustainable Development, Climate and Energy Directorate, Italian Ministry of Environment, Land and See

Prof. Carlo Carraro
President, Ca' Foscari University of Venice
Vice Chair, IPCC Working Group III
Director, Climate Change and Sustainable Development Programme, Fondazione Eni Enrico Mattei

Dr. Nancy Saich
Advisor on Climate & Environment, Projects Directorate, European Investment Bank

Dr. Serena Pontoglio
Research Programme Officer, Climate change and natural hazards unit, DG Research & Innovation, European Commission

Dr. Richard Klein
Senior Research Fellow, Theme Leader "Reducing Climate Risk", Stockholm Environment Institute

Trade of Woody Biomass for Electricity Generation Under Climate Mitigation Policy

The paper on woody biomass trade is now published online by Resource and Energy Economics:

Favero, A. and E. Massetti. 2013. “Trade of Woody Biomass for Electricity Generation Under Climate Mitigation Policy.” Resource and Energy Economics, published online.

Here is the abstract:

Bio-energy with carbon capture and sequestration (BECCS) has the potential to be a key mitigation option, because it can generate electricity and absorb emissions at the same time. However, biomass is not distributed evenly across the globe and regions with a potentially high demand might be constrained by limited domestic supply. Therefore, climate mitigation policies might create the incentive to trade biomass internationally. This paper uses scenarios generated by the integrated assessment model WITCH to study trade of woody biomass from multiple perspectives: the volume of biomass traded, its value, the impact on other power generation technologies and on the efficiency of mitigation policy. The policy scenarios consist of three representative carbon tax policies (4.8 W/m2, 3.8 W/m2 and 3.2 W/m2 radiative forcing values in 2100) and a cap-and-trade scheme (3.8 W/m2 in 2100). Results show that the incentive to trade biomass is high: at least 50% of biomass consumed globally is traded internationally. Regions trade 13-69 EJ/yr of woody biomass in 2050 and 55-81 EJ/yr in 2100. In 2100 the value of biomass traded is equal to US$ 0.7-7.2 Trillion. Trade of woody biomass substantially increases the efficiency of the mitigation policy. In the tax scenarios, abatement increases by 120-323 Gt CO2 over the century. In the cap-and-trade scenario biomass trade reduces the price of emission allowances by 34% in 2100 and cumulative discounted policy costs by 14%.

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!