In many regions around the world, Regional Climate Outlook Forums (RCOFs) provide seasonal climate information and forecasts to decision-makers at regional and national levels. Despite having two decades of experience, the forums have not been systematically monitored or evaluated. To address this gap, and to better inform nascent and widespread efforts in climate services, the authors propose a process-oriented evaluation framework derived from literature on decision support and climate communication around the production and use of scientific information. The authors apply this framework to a case study of the Caribbean RCOF (CariCOF), where they have been engaged in a collaborative effort to integrate climate information and decision processes to enhance regional climate resilience. The authors’ examination of the CariCOF shows an evolution toward the use of more advanced and more diverse climate products, as well as greater awareness of user feedback. It also reveals shortfalls of the CariCOF, including a lack of diverse stakeholder participation, a need for better understanding of best practices to tailor information, undeveloped market research of climate products, insufficient experimentation and vetting of communication mechanisms, and the absence of a way to steward a diverse network of regional actors. The authors’ analysis also provides insight that allowed for improvements in the climate services framework to include mechanisms to respond to changing needs and conditions. The authors’ process-oriented framework can serve as a starting point for evaluating RCOFs and other organizations charged with the provision of climate services.
Author: Gerlak, Andrea K., Guido, Z., Vaughan, C., Rountree, V., Greene, C., Liverman, D., Trotman, A. R., Mahon, R., Cox, S.-A., Mason, S. J., Jacobs, K. L., Buizer, J. L., Meerbeeck, C. J. Van and Baethgen, W. E.
Published Date: 2018-02
Topic (s): social science
Publication Type: Journal
Download: Gerlak et al. 2018 Evaluation of Outlook Forums.pdf
Researchers funded by NOAA's International Research and Applications Project (IRAP) convened a workshop in San Juan, Puerto Rico on March 28-29, 2019, on building public health resilience to severe weather in a changing climate.
The purpose of the event was to identify opportunities for integrating weather and climate science into public health decision making, with a focus on Puerto Rico. A total of 29 participants attended the workshop, including representatives from civic organizations (e.g., Heart to Heart International), academia, federal and state agencies (e.g., NOAA/NWS, CDC, FEMA, EPA, PR Department of Public Health) and members of the interdisciplinary research team and their collaborators (University of Puerto Rico, University of Arizona, Tulane University, IRI, CIMH, University of Colorado).
Public health concerns influenced by weather and climate addressed by the workshop included respiratory diseases (e.g., asthma, COPD), heat stress-related diseases (e.g., cardiovascular disease), vector-borne diseases (e.g., dengue, Zika), and mental health. Stakeholders expressed a need for better access to tailored information for decision-making in public health and expressed a desire for disease surveillance and warning systems to be supported with climate information, for example, by establishing climate thresholds for disease transmission and outbreaks. Participants identified a suite of specific information needs that will be considered as candidates for the co-production of knowledge and decision support resources by the research team and their collaborators in the climate and public health communities. One example of an area being explored by the group is to augment, test, and/or provide feedback on existing heat-related tools developed in the medical community to support existing community efforts.
This activity represents one of six grants awarded by IRAP in FY 18 which are designed to inform planning and prevention focused on weather and climate-sensitive health risks to U.S. economic, development, scientific, and safety interests at home and abroad.
Author: Guido, Zack; Lichtveld M.; Wahid, F.A.; Sherman, M.; Duncan, B.; Henderson, J.; Mason, S.; Méndez-Lázaro, P.; Santos- Hernandez, J.; Allen, T.
Published Date: 2019-06
Topic (s): Public Health and Severe Weather
Publication Type: Workshop Report
Download: PuertoRico_WorkshopReport_20190328.pdf
This study explores the predictive skill of seasonal rainfall characteristics for the first rainy (and planting) season, May–June, in Central America. Statistical predictive models were built using a Model Output Statistics (MOS) technique based on canonical correlation analysis, in which variables that forecast with the Climate Forecast System version 2 (CFSv2) were used as candidate predictors for the observed total precipitation, frequency of rainy days and mean number of extremely dry and wet events in the season. CFSv2 initializations from February to April were explored. The CFSv2 variables used in the study consist of rainfall, as in a typical MOS technique, and a combination of low‐level winds and convective available potential energy (CAPE), a blend that has been previously shown to be a good predictor for convective activity. The highest predictive skill was found for the seasonal frequency of rainy days, followed by the mean frequency of dry events. In terms of candidate predictors, the zonal transport of CAPE (uCAPE) at 925 hPa offers higher skill across Central America than rainfall, which is attributed in part to the high model uncertainties associated with precipitation in the region. As expected, dynamical model predictors initialized in February provide lower skill than those initialized later. Nonetheless, the skill is comparable for March and April initializations. These results suggest that the National Meteorological and Hydrological Services in Central America, and the Central American Regional Climate Outlook Forum, can produce earlier more skilful forecasts for May–June rainfall characteristics than previously stated.
Author: Alfaro, Eric J.; Xandre Chourio. Angel G. Munoz, Simon J. Mason
Published Date: 2017-11
Topic (s): seasonal climate prediction; precipitation; statistical models; MOS predictive schemes; canonical correlation analysis
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This study examines the dynamics of late spring rainfall (the Early Rainy Season, ERS) in the Caribbean region, in hopes of identifying mechanistic‐based predictors for low‐frequency climate modulations of the system. The subtropical Caribbean rain‐belt develops in May as seasonal warming proceeds. By July, the rain‐belt retreats north apparently following the westerlies and their vigorous synoptic disturbances. Daily climatology data suggest a physical definition of the Caribbean ERS as mid‐May to mid‐late June. Based on an examination of daily loops for several seasons, we hypothesize that rainfall occurs quasi‐randomly throughout tongues of air with sufficiently high (above 45–50 mm) precipitable water (PW). These moist airmasses are brought north from the deep tropics by low‐level southerlies, and typically bent over into SW‐NE bands by latitudinal shear of the westerlies. The low‐level flow that transports PW tongues is partly induced by upper‐level synoptic disturbances in the westerlies, but also involves the gentle persistent flow around a geographically anchored Panama Low. While forced ascent is sometimes active ahead of these upper‐level troughs, convective and mesoscale processes can produce rain wherever PW is sufficient. In summary, we hypothesize that rainfall hinges largely on the Lagrangian statistics of moist air tongues. Comparison is drawn between the Caribbean rain‐belt and its East Asian counterpart (Meiyu‐Baiu), and other mechanisms and diagnostics from that literature are discussed. Statistical prediction exercises, based on mechanistically chosen predictors, could both test hypotheses and aid local agricultural interests in the region.
Author: Allen, Theodore L.; Brian E. Mapes
Published Date: 2017-06
Topic (s): Caribbean precipitation; Caribbean rain-belt; mid-summer drought; Caribbean early rainfall season; Caribbean; precipitation
In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary indicators of flooding at the seasonal timescale across sub-Saharan Africa. Given the sparsity of hydrological observations, we input bias-corrected reanalysis rainfall into the Global Flood Awareness System to identify seasonal indicators of floodiness. Results demonstrate that in some regions of western, central, and eastern Africa with typically wet climates, even a perfect tercile forecast of seasonal total rainfall would provide little to no indication of the seasonal likelihood of flooding. The number of extreme events within a season shows the highest correlations with floodiness consistently across regions. Otherwise, results vary across climate regimes: floodiness in arid regions in southern and eastern Africa shows the strongest correlations with seasonal average soil moisture and seasonal total rainfall. Floodiness in wetter climates of western and central Africa and Madagascar shows the strongest relationship with measures of the intensity of seasonal rainfall. Measures of rainfall patterns, such as the length of dry spells, are least related to seasonal floodiness across the continent. Ultimately, identifying the drivers of seasonal flooding can be used to improve forecast information for flood preparedness and to avoid misleading decision-makers.
Author: Coughlan de Perez, Erin; et. al.
Published Date: 2017-09
Topic (s): climate; flood forecasting; flood management; soil moisture; rainfall; emergency preparedness; floods; flooding; indicators; arid regions; arid environments; extreme values; rain; wet climates; disaster management; hydrology
The purpose of this mid-term review is to assess progress of the Global Framework for Climate Services (GFCS) implementation and the approaches and developments in the GFCS's evolution in order to measure the success of implemented activities and to provide guidance on improivements. Also, provide recommendations to inform implementation.
Author: Gerlak, A.; Z. Guido; C. Knudson
Published Date: 2017
Topic (s): climate services
Publication Type: Published report
Boundary organizations, knowledge networks, and information brokers have been suggested as mechanisms that help integrate information into decision-making and enhance interactions between the producers and users of climate information. While these mechanisms have been discussed in many studies in disparate fields of research, there has been little empirical research describing how they relate and support each other within studies on climate services. In this paper, two Caribbean Regional Climate Outlook Forums (CariCOFs) convened in 2014 are studied. CariCOFs facilitate the production of regional seasonal climate information and the dissemination of it to a diverse climate and socioeconomic region. Network analysis, key informant interviews, and small group discussions were used to answer two questions: 1) what are the barriers to using seasonal climate forecasts (SCFs) by CariCOF participants and 2) what are the iterative processes of information exchange that address these barriers? The barriers to using SCF include difficulty in demonstrating the value of the forecast to potential users, difficulty in interpreting and explaining the forecast to others, and challenges associated with the scientific language used in the information. To address these constraints, the convener of the CariCOF acts as a boundary organization by enabling interactions between participants representing diverse sectoral and geographic settings. This develops a network that helps build shared scientific understanding and knowledge about how different sectors experience climate risk. These interactions guide information brokering activities that help individuals communicate and translate climate information to facilitate understanding at local levels.
Journal: Weather, Climate, and Society: http://journals.ametsoc.org/doi/10.1175/WCAS-D-15-0076.1
Author: Guido, Zack. Valerie Rountree. Christina Greene. Andrea Gerlak. Adrian Trotman
Published Date: 2016-06
Topic (s): boundary organizations, knowledge networks
Access to climate information has the potential to build adaptive capacity, improve agricultural profitability, and help manage risks. To achieve these benefits, knowledge of the local context is needed to inform information development, delivery, and use. We examine coffee farming in the Jamaican Blue Mountains (BM) to understand farmer livelihoods, opportunities for climate knowledge to benefit coffee production, and the factors that impinge on farmers’ ability to use climate information. Our analysis draws on interviews and 12 focus groups involving 143 participants who largely cultivate small plots. BM farmers currently experience stresses related to climate, coffee leaf rust, and production costs that interrelate concurrently and with time lags. Under conditions that reduce income, BM farmers compensate by adjusting their use of inputs, which can increase their susceptibility to future climate and disease stresses. However, farmers can also decrease impacts of future stressors by more efficiently and effectively allocating their limited resources. In this sense, managing climate, like the other stresses, is an ongoing process. While we identify climate products that can help farmers manage climate risk, the local context presents barriers that argue for interactive climate services that go beyond conventional approaches of information production and delivery. We discuss how dialogs between farmers, extension personnel, and climate scientists can create a foundation from which use can emerge.
Author: Guido, Zack; Tim Finan; Kevon Rhiney; Malgosia Madajewicz; Valerie Rountree; Elizabeth Johnson; Gusland McCook
Published Date: 2018-03
Topic (s): climate services; coffee industry
The International Research and Applications Project (IRAP), Integrating Climate Information and Decision Processes for Regional Climate Resilience, advances research on adaptation and resilience to climate variability and change while also advancing the application of climate services. The project supports risk management through research-based improvements in design, development, and provision of climate information, particularly as they contribute to national and regional development goals.
NOAA is pleased to present the first IRAP report, entitled "Integrating Climate Information and Decision Processes for Regional Climate Resilience in the Caribbean". The report synthesizes a workshop held in Kingston, Jamaica, May 29-30, 2014, sponsored by NOAA and USAID, in collaboration with the Caribbean Institute for Meteorology and Hydrology.
Author: Guido, Zackry. James Buizer. Tim Finan. S Gavin. Andrea Gerlak. Lisa Goddard. Christina Greene. Richard Johnson. Diana Liverman. Simon Mason. Ángel Muñoz.
Published Date: 2014-05
Topic (s): climate information integration, regional resilience
Publication Type: Workshop report
Download: IRAP report _sm.pdf
This paper proposes a heat-wave definition for Bangladesh that could be used to trigger preparedness measures in a heat early warning system (HEWS) and explores the climate mechanisms associated with heat waves. A HEWS requires a definition of heat waves that is both related to human health outcomes and forecastable. No such definition has been developed for Bangladesh. Using a generalized additive regression model, a heat-wave definition is proposed that requires elevated minimum and maximum daily temperatures over the 95th percentile for 3 consecutive days, confirming the importance of nighttime conditions for health impacts. By this definition, death rates increase by about 20% during heat waves; this result can be used as an argument for public-health interventions to prevent heat-related deaths. Furthermore, predictability of these heat waves exists from weather to seasonal time scales, offering opportunities for a range of preparedness measures. Heat waves are associated with an absence of normal premonsoonal rainfall brought about by anomalously strong low-level westerly winds and weak southerlies, detectable up to approximately 10 days in advance. This circulation pattern occurs over a background of drier-than-normal conditions, with below-average soil moisture and precipitation throughout the heat-wave season from April to June. Low soil moisture increases the odds of heat-wave occurrence for 10–30 days, indicating that subseasonal forecasts of heat-wave risk may be possible by monitoring soil-moisture conditions.
Author: Nissan, Hannah; Katrin Burkart; Erin Coughlan de Perez; Maarten Van Aalst; Simon Mason
Published Date: 2017-10
Topic (s): climate prediction; seasonal forecasting; short-range prediction; emergency preparedness; policy
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Lisa Vaughan Program Manager, International Research and Applications Project (IRAP) P: 1 (301) 734-1277 F: 1 (301) 713-0518 E: lisa.vaughan@noaa.gov
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Americans’ health, security and economic wellbeing are tied to climate and weather. Every day, we see communities grappling with environmental challenges due to unusual or extreme events related to climate and weather.