Francisco Estrada

A time-series analysis of the 20th century climate simulations produced for the IPCC's Fourth Assessment Report.

In this paper evidence of anthropogenic influence over the warming of the 20th century is presented and the debate regarding the time-series properties of global temperatures is addressed in depth. The 20th century global temperature simulations produced for the Intergovernmental Panel on Climate Change’s Fourth Assessment Report and a set of the radiative forcing series used to drive them are analyzed using modern econometric techniques. Results show that both temperatures and radiative forcing series share similar time-series properties and a common nonlinear secular movement. This long-term co-movement is characterized by the existence of time-ordered breaks in the slope of their trend functions. The evidence presented in this paper suggests that while natural forcing factors may help explain the warming of the first part of the century, anthropogenic forcing has been its main driver since the 1970’s. In terms of Article 2 of the United Nations Framework Convention on Climate Change, significant anthropogenic interference with the climate system has already occurred and the current climate models are capable of accurately simulating the response of the climate system, even if it consists in a rapid or abrupt change, to changes in external forcing factors. This paper presents a new methodological approach for conducting time-series based attribution studies.

The new national climate change documents of Mexico: what do the regional climate change scenarios represent?

This paper presents a review of the methodology applied for generating the regional climate change scenarios utilized in important National Documents of Mexico, such as the Fourth National Communication to the United Nations Framework Convention on Climate Change, the Fourth National Report to the Convention on Biological Diversity and The Economics of Climate Change in Mexico. It is shown that these regional climate change scenarios, which are one of the main inputs to support the assessments presented in these documents, are an example of the erroneous use of statistical downscaling techniques. The arguments presented here imply that the work based on such scenarios should be revised and therefore, these documents are inadequate for supporting national decision- making.

GOBERNANZA Y CALIDAD EN LA GESTIÓN PÚBLICA

Esta investigacion se enfoca al estudio de la incorporacion de la calidad en las funciones del gobierno y la gestion publica. Mediante el estudio de la literatura mas representativa, publicada en los ultimos quince anos, se analizan los cambios globales y sus efectos en las transformaciones del Estado, para proponer el enfoque de la nueva gobernanza. Con base en este marco general, se plantea la convergencia entre nueva gestion publica y calidad, a partir de la experiencia de reforma administrativa aplicada en los gobiernos latinoamericanos en las dos ultimas decadas. Finalmente, se revisan los aportes del modelo de gestion de calidad y la certificacion de servicios a traves de la aplicacion de las normas ISO 9000 y el analisis de procesos en las organizaciones publicas.

A methodology for the risk assessment of climate variability and change under uncertainty. A case study: coffee production in Veracruz, Mexico

Existing methods for the assessment of the potential impacts of climate change in productive activities and sectors are usually limited to point estimates that do not consider the inherent variability and uncertainty of climatic and socioeconomic variables. This is a major drawback given that only a limited and potentially misleading estimation of risk can be expected when ignoring such determinant factors. In this paper, a new methodology is introduced that is capable of integrating the agent’s beliefs and expert judgment into the assessment of the potential impacts of climate change in a quantitative manner by means of an objective procedure. The goal is to produce tailor-made information to assist decision-making under uncertainty in a way that is consistent with the current state of knowledge and the available subjective “expert” information. Time-charts of the evolution of different risk measures, that can be relevant for assisting decision-making and planning, can be constructed using this new methodology. This methodology is illustrated with a case study of coffee production in Mexico. Time-dependent probabilistic scenarios for coffee production and income, conditional on the agent’s beliefs and expert judgment, are developed for the average producer under uncertain future conditions. It is shown that variability in production and income, generated by introducing climate variability and uncertainty are important factors affecting decision-making and the assessment of economic viability that are frequently ignored. The concept of Value at Risk, commonly applied in financial risk management, is introduced as a means for estimating the maximum expected loss for a previously chosen confidence level. Results are tailor-made for agents that have incomplete information and different beliefs. In this case study, the costs of climate change for coffee production in Veracruz are estimated to have a present value representing from 3 to 14 times the current annual value of coffee production in the state.

Extracting and analyzing the warming trend in global and hemispheric temperatures

This paper offers an updated and extended attribution analysis based on recently published versions of temperature and forcing datasets. It shows that both temperature and radiative forcing variables can be best represented as trend stationary processes with structural changes occurring in the slope of their trend functions and that they share a common secular trend and common breaks, largely determined by the anthropogenic radiative forcing. The common nonlinear trend is isolated and further evidence on the possible causes of the current slowdown in warming is presented. Our analysis offers interesting results in relation to the recent literature. Changes in the anthropogenic forcings are directly responsible for the hiatus as in Estrada et al. (2013a), while natural factors such as the Atlantic Multidecadal Oscillation, the Interdecadal Pacific Oscillation and the Southern Annular Mode, as well as the new temperature adjustments in Karl et al. (2105) contribute to weaken the signal. In other words, natural variability and data adjustments do not explain in any way the hiatus, they simply mask its presence.

Global economic impacts of climate variability and change during the 20th century

Estimates of the global economic impacts of observed climate change during the 20th century obtained by applying five impact functions of different integrated assessment models (IAMs) are separated into their main natural and anthropogenic components. The estimates of the costs that can be attributed to natural variability factors and to the anthropogenic intervention with the climate system in general tend to show that: 1) during the first half of the century, the amplitude of the impacts associated with natural variability is considerably larger than that produced by anthropogenic factors and the effects of natural variability fluctuated between being negative and positive. These non-monotonic impacts are mostly determined by the low-frequency variability and the persistence of the climate system; 2) IAMs do not agree on the sign (nor on the magnitude) of the impacts of anthropogenic forcing but indicate that they steadily grew over the first part of the century, rapidly accelerated since the mid 1970s, and decelerated during the first decade of the 21st century. This deceleration is accentuated by the existence of interaction effects between natural variability and natural and anthropogenic forcing. The economic impacts of anthropogenic forcing range in the tenths of percentage of the world GDP by the end of the 20th century; 3) the impacts of natural forcing are about one order of magnitude lower than those associated with anthropogenic forcing and are dominated by the solar forcing; 4) the interaction effects between natural and anthropogenic factors can importantly modulate how impacts actually occur, at least for moderate increases in external forcing. Human activities became dominant drivers of the estimated economic impacts at the end of the 20th century, producing larger impacts than those of low-frequency natural variability. Some of the uses and limitations of IAMs are discussed.

Fuzzy Models: Easier to Understand and an Easier Way to Handle Uncertainties in Climate Change Research

Greenhouse gas emission scenarios (through 2100) developed by the Intergovernmental Panel on Climate Change when converted to concentrations and atmospheric temperatures through the use of climate models result in a wide range of concentrations and temperatures with a rather simple interpretation: the higher the emissions the higher the concentrations and temperatures. Therefore the uncertainty in the projected temperature due to the uncertainty in the emissions is large. Linguistic rules are obtained through the use of linear emission scenarios and the Magicc model. These rules describe the relations between the concentrations (input) and the temperature increase for the year 2100 (output) and are used to build a fuzzy model. Another model is presented that includes, as a second source of uncertainty in input, the climate sensitivity to explore its effects on the temperature. Models are attractive because their simplicity and capability to integrate the uncertainties to the input and the output.

Towards Impact Functions for Stochastic Climate Change

Most functions of economic impact assume that climate change is smooth. We here propose impact functions that have stochastic climate change as an input. These functions are identical in shape and have similar parameters as do deterministic impact functions. The mean stochastic impacts are thus similar to deterministic impacts. Welfare effects are larger, and the stochasticity premium is larger than the risk premium. Results suggest that stochasticity is more important for past impacts than for future impacts. This outcome is partly caused by an underestimation of natural variability in the 21st century climate projections.

Causality from long-lived radiative forcings to the climate trend: Causality from long-lived radiative forcing

In our study, we present a purely statistical observations‐based model‐free analysis that provides evidence about Granger causality (GC) from long‐lived radiative forcings (LLRFs) to the climate trend (CT). This relies on having locally ordered breaks in the slopes of the trend functions of LLRF and the CT, with the break for LLRF occurring before that of the CT and with the slope changes being of the same sign. The empirical evidence indicates that these conditions are satisfied empirically using standard global surface temperature series and an aggregate measure of LLRF (carbon dioxide, nitrous oxide, and chlorofluorocarbons). We also discuss why the presence of broken trends can lead one to conclude in favor of GC when using standard methods even if the noise function in LLRF is negligible.

Preface to the thematic issue on Climate, economics and statistics

Environmental problems are typically produced by the interactions of complex natural and human systems and can entail far-reaching and sometimes irreversible consequences. Their study is characterized by the existence of incomplete knowledge and high levels of uncertainty and, in some cases, ambiguousness in the definition of the problem itself and its boundaries. These so-called wicked problems openly challenge the traditional disciplinary approach commonly used in natural and social sciences and call for the development of interdisciplinary, integrated research, as well as for innovative methods and frameworks.