Updated Basis Knowledge of Climate Change Summarized from the First part of Thailand’s Second Assessment Report on Climate Change

Recent evidence and key issues on climate change in Thailand have been presented in the first part of Thailand’s Second Assessment Report on Climate Change (2nd TRAC). The report highlights key findings including 1) a significant country-wide warming of 1.30 oC over the past 48 years (1970-2017); b) significant changes in rainfall patterns at smaller spatial and finer temporal scales; c) significant changes in temperature and rainfall extreme events over the last four-five decades; d) a significant decrease in frequency of tropical cyclones entering Thailand; e) significant rise in sea level in the seas around Thailand at higher rates than the global average; and f) significant projected increases in temperature and rainfall in Thailand by 2100. The first part of the 2nd TARC provides a comprehensive and updated analysis of climate change impacts in Thailand that can be used as an authoritative reference for building understanding and awareness, as well as for designing adaptation and mitigation strategies. Moreover, it can serve as a repository for scientific information to support further research related to impact, adaptation and vulnerability to climate change. Regular assessment of national climate change impacts is essential to informing national policy and to allow policymakers to assess priorities and set meaningful targets in line with the country’s international obligations under the Climate Change Agreement

A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment

The aim of this work is to report on an activity carried out during the 2010 Recognized Environmental Picture experiment, held in the Ligurian Sea during summer 2010. The activity was the first at-sea test of the recently developed decision support system (DSS) for operation planning, which had previously been tested in an artificial experiment. The DSS assesses the impact of both environmental conditions (meteorological and oceanographic) and non-environmental conditions (such as traffic density maps) on people and assets involved in the operation and helps in deciding a course of action that allows safer operation. More precisely, the environmental variables (such as wind speed, current speed and significant wave height) taken as input by the DSS are the ones forecasted by a super-ensemble model, which fuses the forecasts provided by multiple forecasting centres. The uncertainties associated with the DSS's inputs (generally due to disagreement between forecasts) are propagated through the DSS's output by using the unscented transform. In this way, the system is not only able to provide a traffic light map (run/not run the operation), but also to specify the confidence level associated with each action. This feature was tested on a particular type of operation with underwater gliders: the glider surfacing for data transmission. It is also shown how the availability of a glider path prediction tool provides surfacing options along the predicted path. The applicability to different operations is demonstrated by applying the same system to support diver operations

Linking weather generators and crop models for assessment of climate forecast outcomes

Agricultural production responses to climate variability require salient information to support decisions. We coupled a new hybrid stochastic weather generator (combining parametric and nonparametric components) with a crop simulation model to assess yields and economic returns relevant to maize production in two contrasting regions (Pergamino and Pilar) of the Pampas of Argentina. The linked models were used to assess likely outcomes and production risks for seasonal forecasts of dry and wet climate. Forecasts involving even relatively small deviations from climatological probabilities of precipitation may have large impacts on agricultural outcomes. Furthermore, yield changes under alternative scenarios have a disproportionate effect on economic risks. Additionally, we show that regions receiving the same seasonal forecast may experience fairly different outcomes: a forecast of dry conditions did not change appreciably the expected distribution of economic margins in Pergamino (a climatically optimal location) but modified considerably economic expectations (and thus production risk) in Pilar (a more marginal location).Fil: Apipattanavis, Somkiat. State University Of Colorado Boulder; Estados UnidosFil: Bert, Federico Esteban. Universidad de Buenos Aires. Facultad de Agronomia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Podestá, Guillermo. University of Miami; Estados UnidosFil: Rajagopalan, Balaji. State University Of Colorado Boulder; Estados Unido

Decadal climate variability in the Argentine Pampas: regional impacts of plausible climate scenarios on agricultural systems

The Pampas of Argentina have shown some of the most consistently increasing trends in precipitation during the 20th century. The rainfall increase has partly contributed to a significant expansion of agricultural area, particularly in climatically marginal regions of the Pampas. However, it is unclear if current agricultural production systems, which evolved partly in response to enhanced climate conditions, may remain viable if (as entirely possible) climate reverts to a drier epoch. We assess the potential impacts of a plausible decreasing trend in precipitation on the economic sustainability of 2 contrasting agricultural systems in the Pampas: Pergamino, in the most productive subregion of the Pampas, and Pilar, in the northern, semi-arid margin of the region. Also, we explore the scope for adaptation to changing climate. In the case where there is no adaptation, if precipitation decreases, as is plausible, impacts may be quite different between locations: whereas in Pergamino crop economic returns would not change noticeably, the more marginal Pilar would experience a marked decrease in profits and an increase in production risks. However, potential negative impacts might be mitigated, in part, if farmers adapt their agronomic management using current available technology or know-how.Fil: Podestá, Guillermo. University of Miami; Estados UnidosFil: Bert, Federico Esteban. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; ArgentinaFil: Rajagopalan, B.. State University of Colorado at Boulder; Estados UnidosFil: Apipattanavis, S.. State University of Colorado at Boulder; Estados UnidosFil: Laciana, Carlos Ernesto. Columbia University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Weber, E.. State University of Pennsylvania; Estados UnidosFil: Easterling, W.. National Center for Atmospheric Research; Estados UnidosFil: Katz, R.. No especifíca;Fil: Letson, D.. University of Miami; Estados UnidosFil: Menendez, A.. Universidad de Buenos Aires; Argentin