scholarly journals Understanding the uncertainty cascaded in climate change projections for agricultural decision making

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 223-234
Author(s):  
A. P. RAMARAJ ◽  
V. GEETHALAKSHMI ◽  
K. BHUVANESWARI

Climate projections have confirmed the need to adapt to a changing climate, but have been less beneficial in guiding how to effectively adapt. The reason is the uncertainty cascade, from assumptions about future emissions of greenhouse gases to what that means for the climate to real decisions on a local scale. Each of the steps in the process contains uncertainty and these uncertainties from various levels of the assessment accumulate. This cascade of uncertainty should be critically analyzed to inform decision makers about the certain range of future changes. Most widely used approaches like Bayesian and Monte Carlo gives specific values of parameters and their confidence, yet for agricultural decision making the range of possible changes itself is required as such to understand impact at every point of these ranges. This paper addresses these issues and examines the uncertainties in climate projections at a local scale. In the study locations (Coimbatore and Thanjavur), irrespective of the models, scenarios and time slices, the maximum and minimum temperatures are projected to increase with seasonal variations. With certainty, the projected increase in maximum and minimum temperature over Coimbatore is 0.2 to 4.1 ºC and 0.3 to 5.3 ºC and over Thanjavur is 0.3 to             4.6 ºC and 0.2 to 5.2 ºC, respectively. Rainfall is projected to vary between a decrease of 15.0 to an increase of 73.1 percent for Coimbatore and a decrease of 15.3 to an increase of 80.7 per cent for Thanjavur during the 21st century. On comparing the monsoon seasons, southwest monsoon (SWM) is projected to have a higher increase in both maximum and minimum temperature than northeast monsoon (NEM) for both the study locations, similar to their current trends. Rainfall is projected to increase more in NEM than in SWM.  

2015 ◽  
Vol 28 (10) ◽  
pp. 4171-4184 ◽  
Author(s):  
R. Manzanas ◽  
S. Brands ◽  
D. San-Martín ◽  
A. Lucero ◽  
C. Limbo ◽  
...  

Abstract This work shows that local-scale climate projections obtained by means of statistical downscaling are sensitive to the choice of reanalysis used for calibration. To this aim, a generalized linear model (GLM) approach is applied to downscale daily precipitation in the Philippines. First, the GLMs are trained and tested separately with two distinct reanalyses (ERA-Interim and JRA-25) using a cross-validation scheme over the period 1981–2000. When the observed and downscaled time series are compared, the attained performance is found to be sensitive to the reanalysis considered if climate change signal–bearing variables (temperature and/or specific humidity) are included in the predictor field. Moreover, performance differences are shown to be in correspondence with the disagreement found between the raw predictors from the two reanalyses. Second, the regression coefficients calibrated either with ERA-Interim or JRA-25 are subsequently applied to the output of a global climate model (MPI-ECHAM5) in order to assess the sensitivity of local-scale climate change projections (up to 2100) to reanalysis choice. In this case, the differences detected in present climate conditions are considerably amplified, leading to “delta-change” estimates differing by up to 35% (on average for the entire country) depending on the reanalysis used for calibration. Therefore, reanalysis choice is an important contributor to the uncertainty of local-scale climate change projections and, consequently, should be treated with as much care as other better-known sources of uncertainty (e.g., the choice of the GCM and/or downscaling method). Implications of the results for the entire tropics, as well as for the model output statistics downscaling approach are also briefly discussed.


2020 ◽  
Vol 39 (3) ◽  
pp. 4041-4058
Author(s):  
Fang Liu ◽  
Xu Tan ◽  
Hui Yang ◽  
Hui Zhao

Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs.


2019 ◽  
Author(s):  
Suci Handayani Handayani ◽  
Hade Afriansyah

Decision making is one element of economic value, especially in the era of globalization, and if it is not acceptable in the decision making process, we will be left behind. According to Robins, (2003: 173), Salusu, (2000: 47), and Razik and Swanson, (1995: 476) say that decision making can be interpreted as a process of choosing a number of alternatives, how to act in accordance with concepts, or rules in solving problems to achieve individual or group goals that have been formulated using a number of specific techniques, approaches and methods and achieve optimal levels of acceptance.Decision making in organizations whether a decision is made for a person or group, the nature of the decision is often determined by rules, policies, prescribed, instructions that have been derived or practices that apply. To understand decision making within the organization it is useful to view decision making as part of the overall administrative process. In general, individuals tend to use simple strategies, even if in any complex matter, to get the desired solution, because the solution is limited by imperfect information, time and costs, limited thinking and psychological stress experienced by decision makers.


2015 ◽  
Vol 4 (1and2) ◽  
Author(s):  
Rajeev Dhingra ◽  
Preetvanti Singh

Decision problems are usually complex and involve evaluation of several conflicting criteria (parameters). Multi Criteria Decision Making (MCDM) is a promising field that considers the parallel influence of all criteria and aims at helping decision makers in expressing their preferences, over a set of predefined alternatives, on the basis of criteria (parameters) that are contradictory in nature. The Analytic Hierarchy Process (AHP) is a useful and widespread MCDM tool for solving such type of problems, as it allows the incorporation of conflicting objectives and decision makers preferences in the decision making. The AHP utilizes the concept of pair wise comparison to find the order of criteria (parameters) and alternatives. The comparison in a pairwise manner becomes quite tedious and complex for problems having eight alternatives or more, thereby, limiting the application of AHP. This paper presents a soft hierarchical process approach based on soft set decision making which eliminates the least promising candidate alternatives and selects the optimum(potential) ones that results in the significant reduction in the number of pairwise comparisons necessary for the selection of the best alternative using AHP, giving the approach a more realistic view. A supplier selection problem is used to illustrate the proposed approach.


Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 124
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Florentin Smarandache ◽  
...  

Some decision-making problems, i.e., multi-criteria decision analysis (MCDA) problems, require taking into account the attitudes of a large number of decision-makers and/or respondents. Therefore, an approach to the transformation of crisp ratings, collected from respondents, in grey interval numbers form based on the median of collected scores, i.e., ratings, is considered in this article. In this way, the simplicity of collecting respondents’ attitudes using crisp values, i.e., by applying some form of Likert scale, is combined with the advantages that can be achieved by using grey interval numbers. In this way, a grey extension of MCDA methods is obtained. The application of the proposed approach was considered in the example of evaluating the websites of tourism organizations by using several MCDA methods. Additionally, an analysis of the application of the proposed approach in the case of a large number of respondents, done in Python, is presented. The advantages of the proposed method, as well as its possible limitations, are summarized.


2021 ◽  
Vol 11 (4) ◽  
pp. 1660 ◽  
Author(s):  
Ivan Marović ◽  
Monika Perić ◽  
Tomaš Hanak

A way to minimize uncertainty and achieve the best possible project performance in construction project management can be achieved during the procurement process, which involves selecting an optimal contractor according to “the most economically advantageous tender.” As resources are limited, decision-makers are often pulled apart by conflicting demands coming from various stakeholders. The challenge of addressing them at the same time can be modelled as a multi-criteria decision-making problem. The aim of this paper is to show that the analytic hierarchy process (AHP) together with PROMETHEE could cope with such a problem. As a result of their synergy, a decision support concept for selecting the optimal contractor (DSC-CONT) is proposed that: (a) allows the incorporation of opposing stakeholders’ demands; (b) increases the transparency of decision-making and the consistency of the decision-making process; (c) enhances the legitimacy of the final outcome; and (d) is a scientific approach with great potential for application to similar decision-making problems where sustainable decisions are needed.


Author(s):  
Christian Hauser

AbstractIn recent years, trade-control laws and regulations such as embargoes and sanctions have gained importance. However, there is limited empirical research on the ways in which small- and medium-sized enterprises (SMEs) respond to such coercive economic measures. Building on the literature on organizational responses to external demands and behavioral ethics, this study addresses this issue to better understand how external pressures and managerial decision-making are associated with the scope of trade-control compliance programs. Based on a sample of 289 SMEs, the findings show that the organizational responses of SMEs reflect proportionate adjustments to regulatory pressures but only if decision-makers are well informed and aware of the prevailing rules and regulations. Conversely, uninformed decision-making leads to a disproportionate response resulting in an inadequately reduced scope of the compliance program. In addition, the results indicate that SMEs that are highly integrated into supply chains are susceptible to passing-the-buck behavior.


2005 ◽  
Vol 24 (4) ◽  
pp. 259-274
Author(s):  
Sameer Kumar ◽  
Thomas Ressler ◽  
Mark Ahrens

This article is an appeal to incorporate qualitative reasoning into quantitative topics and courses, especially those devoted to decision-making offered in colleges and universities. Students, many of whom join professional workforce, must become more systems thinkers and decision-makers than merely problem-solvers. This will entail discussion of systems thinking, not just reaching “the answer”. Managers will need to formally and forcefully discuss objectives and values at each stage of the problem-solving process – at the start, during the problem-solving stage, and at the interpretation of the results stage – in order to move from problem solving to decision-making. The authors suggest some methods for doing this, and provide examples of why doing so is so important for decision-makers in the modern world.


2021 ◽  
Vol 37 (1) ◽  
pp. 79-84
Author(s):  
John Pullinger

Statistics are the currency of debate and the basis for sound decisions. If they are misused the currency of debate is devalued and the basis for decision making is undermined. Without confidence in statistics, decision makers are flying blind when they make their choices and citizens are in the dark in seeking to hold those decision makers to account. Misuse of statistics undermines trust and by doing so it undermines democracy. This paper explores the safeguards available to protect against misuse of statistics. It describes the nature of the threats and how they are changing before assessing the responses. It concludes that there is unfinished business to be taken forward.


2021 ◽  
Vol 13 (2) ◽  
pp. 292
Author(s):  
Megan Seeley ◽  
Gregory P. Asner

As humans continue to alter Earth systems, conservationists look to remote sensing to monitor, inventory, and understand ecosystems and ecosystem processes at large spatial scales. Multispectral remote sensing data are commonly integrated into conservation decision-making frameworks, yet imaging spectroscopy, or hyperspectral remote sensing, is underutilized in conservation. The high spectral resolution of imaging spectrometers captures the chemistry of Earth surfaces, whereas multispectral satellites indirectly represent such surfaces through band ratios. Here, we present case studies wherein imaging spectroscopy was used to inform and improve conservation decision-making and discuss potential future applications. These case studies include a broad array of conservation areas, including forest, dryland, and marine ecosystems, as well as urban applications and methane monitoring. Imaging spectroscopy technology is rapidly developing, especially with regard to satellite-based spectrometers. Improving on and expanding existing applications of imaging spectroscopy to conservation, developing imaging spectroscopy data products for use by other researchers and decision-makers, and pioneering novel uses of imaging spectroscopy will greatly expand the toolset for conservation decision-makers.


Sign in / Sign up

Export Citation Format

Share Document