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IPCC_Managing Risks of Extreme Events.pdf - Climate Access

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Chapter 5<strong>Managing</strong> the <strong>Risks</strong> from <strong>Climate</strong> <strong>Extreme</strong>s at the Local LevelBox 5-2 | Successful Communication <strong>of</strong> LocalRisk-Based <strong>Climate</strong> InformationThe following questions have been identified as shaping thesuccessful communication <strong>of</strong> risk-based climate information(Ascher, 1978; Fischh<strong>of</strong>f, 1992; Pulwarty, 2003):• What do people know and believe about the risks beingposed?• What is the past experience/outcomes <strong>of</strong> informationuse?• Is the new information relevant for decisions in theparticular community?• Are the sources/providers <strong>of</strong> information credible to theintended user?• Are practitioners (e.g., farmers) receptive to theinformation and to research?• Is the information accessible to the decisionmaker?• Is the information compatible with existing decisionmodels (e.g., for farming practice)?• Does the community (or individuals in the community)have the capacity to use information?such as during droughts, act as mechanisms for risk communication andresponse actions (Dekens, 2007).Policies and actions affecting communications and advanced warninghave a major impact on the adaptive capacity and resilience <strong>of</strong>livelihoods. The collection and transmittal <strong>of</strong> weather- (and climate-)related information is <strong>of</strong>ten a governmental function and timelyissuance remains a key weakness in climate information systems,especially for communication passed on to communities from thenational early warning units (UNISDR, 2006). There are other localizedforms <strong>of</strong> communication that can be used rapidly, such as neighborhoodwatch systems (Lichterman, 2000). Some private communication methods,such as text messaging, Facebook, and Twitter, may reach affectedpopulations before government directives (Palen et al., 2007). However,some research shows that there has been too much reliance on one-waydevices for communication (such as the radio), which were felt to beinadequate for agricultural applications (for example, farmers are notable to ask further questions regarding the information provided)(Ziervogel, 2004). Within many rural communities, low bandwidth andpoor computing infrastructure pose serious constraints to risk-messagereceipt. Such gaps are evident in developed as well as lesser-developedregions.The degree <strong>of</strong> acceptability <strong>of</strong> information and trust in the providersdictates the context <strong>of</strong> communicating disaster and climate information(see Box 5-2). Pre-decisional processes (reception, attention, andcomprehension) influence the disaster message’s effectiveness (Lindelland Perry, 2004). Several studies have identified the characteristics <strong>of</strong>pre-decisional practices that lead to effective communication over thelong-term (Fischh<strong>of</strong>f, 1992; Cutter, 2001; Pulwarty, 2007). These include:1) understanding the goals, objectives, and constraints <strong>of</strong> communitiesin the target system; 2) mapping practical pathways to different outcomescarried out as joint problem definition and fact-finding strategiesamong research, extension, and farmer communities; 3) bringing thedelivery persons (e.g., extension personnel, research community, etc.) toan understanding <strong>of</strong> what has to be done to translate current informationinto usable information; 4) interacting with actual and potential usersto better understand informational needs, desired formats <strong>of</strong> information,and timeliness <strong>of</strong> delivery; 5) assessing impediments and opportunitiesto the flow <strong>of</strong> information including issues <strong>of</strong> credibility, legitimacy,compatibility (appropriate scale, content, match with existing practice),and acceptability; and 6) relying on existing stakeholders’ networks andorganizations to disseminate and assess climate information andforecasts.Much research has yet to be done regarding risk communication onclimate change. There has been little systematic investigation, forexample, on message effectiveness in prompting local action based ondiffering characteristics such as the precision <strong>of</strong> message dissemination,penetration into normal activities, message specificity, messagedistortion, rate <strong>of</strong> dissemination over time, receiver characteristics,sender requirements, and feedback (Lindell and Perry, 1992; NRC, 2006).Little research attention has been devoted to how information can bedistributed within a family, although the existing research does showthere are emotional, social, and structural barriers to such distribution(Norgaard, 2009).5.3.1.3. Warnings and Warning SystemsThe disaster research community has shown that warnings <strong>of</strong> impendinghazards need to be complemented by information on the risks actuallyposed by the hazards as well as the potential strategies and pathwaysto mitigate the damage in the particular context in which they arise(Drabek, 1999; UNISDR, 2006). Local-level early warnings based ontraditional knowledge (e.g., water turning a different color, windsshifting) are frequently used. The use <strong>of</strong> radios, megaphones, and cellphones are also used at the local level to warn.Effective early warning implies information interventions into anenvironment where vulnerability is assumed (Olson, 2000). This backdropis reinforced through significant lessons that have been identified fromthe use <strong>of</strong> seasonal climate forecasts over the past 15 years (Podestá etal., 2002; Pulwarty, 2007). It is now widely accepted that the existence<strong>of</strong> predictable climate variability and impacts are necessary but notsufficient to achieve effective use <strong>of</strong> climate information, includingseasonal forecasts. The practical obstacles to using information aboutfuture conditions at the local scale are diverse. They include: limitationsin modeling the climate system’s complexities (e.g., projections havingcoarse spatial and temporal resolution; limited predictability <strong>of</strong> somerelevant variables; and forecast skill characterization; see Chapter 3);procedural, institutional, and cognitive barriers in receiving or303

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