Extreme weather events in Myanmar: data needs for more effective humanitarian action

Extreme weather events, such as floods and cyclones, have increased in number in recent years. At the same time, there is growing evidence that providing for anticipatory humanitarian action – rather than post-event action – can give the affected populations more dignity, security and time in dealing with the impact of these shocks. Such anticipatory action, however, requires accurate weather forecasts, as well as mechanisms to provide financial resources on an ongoing basis. David MacLeod, Evan Easton-Calabria, Erin Coughlan de Perez and Catalina Jaime present research findings that evaluate both these factors in the context of Myanmar, one of the countries most at risk in its region

Climate information for humanitarian agencies: some basic principles

Since 2005, the International Federation of Red Cross and Red Crescent Societies and the Red Cross Red Crescent Climate Centre have had an ongoing partnership with the International Research Institute for Climate and Society (IRI) to connect end-users with providers of climate information. This partnership has enabled and encouraged the uptake of climate information in the humanitarian sector. From the perspective of the climate service provider, attempts to address problems of salience, credibility and legitimacy have been made by adopting the following set of principles: prioritize immediate user needs; provide only information that is relevant to the user context; provide decision support; right-scale rather than down-scale; and maintain ownership and partnership in design. Examples are presented of how these principles have been applied, highlighting not only the need to improve forecasts and their presentation, but also to address obstacles to the practical use of climate information

Beyond the forecast: knowledge gaps to anticipate disasters in armed conflict areas with high forced displacement

Although conflict-affected populations are often exposed to and severely impacted by disasters, little is known about their perceptions and practices concerning early warning and early action (EWEA) or how EWEA strategies can protect communities affected by conflict- and climate-related disasters. This is particularly problematic as, due to the multiple challenges posed by conflict and compound crises in these contexts, early warnings of weather hazards do not often translate in early actions. This comprehensive literature review examined 384 peer reviewed papers produced between 2004 and 2022, focused on the 20 countries most affected by non-international armed conflict and exposed to climate hazards. This paper answers the question: what is the state of knowledge of EWEA for climate hazards in countries affected by armed conflict and high levels of forced displacement? Findings demonstrate that most research focuses on climate science rather than social science across six elements of the EWEA value chain: 1. hazards analysis, 2. understanding vulnerability and exposure, 3. warning communication and dissemination, 4. forecasting availability and monitoring, 5. early action planning, and 6. financing systems. In total, 75.65% of the research studies focused on hazard analysis, forecast availability, and monitoring. There has been a strong increase in academic research on EWEA in conflict-affected countries since 2004. However, we identify that most of this research has been in Ethiopia, Pakistan, and Nigeria which, although severely affected by conflict, also have a higher level of economic development and stability. In contrast, there is little research focused on EWEA in most of the remaining countries. Across all thematic areas, there is a lack of consideration of conflict dynamics in EWEA research. This paper contributes to evidence on the need to recognize people affected by conflict in disaster risk reduction, as called for in the Sendai Framework for Action midterm review, with the aim of enhancing EWEA investments to enable tailored approaches appropriate for conflict-affected states

Scalable and Sustainable: How to Build Anticipatory Capacity into Social Protection Systems

Climate shocks contribute to a significant share of the humanitarian burden, and are a key factor in increasing poverty and food insecurity. Social protection is increasingly recognised as an instrument to help build resilience to climate risks through long-term, large-scale national systems. However, most experiences to date have focused on social protection’s role for chronic needs, or at best, shock-response, rather than on anticipation and prevention. This article argues that social protection can support more effective resilience building at scale by integrating early action and preparedness. We propose a concrete solution, namely linking a Forecast-based Financing mechanism to a social protection system to enable anticipatory actions based on forecast triggers and guaranteed funding ahead of a shock. Such a system may enhance scalability, timeliness, predictability and adequacy of social protection benefits. Key considerations for success of this emerging approach include sound analysis of forecast, risks, cost and benefits, and ring-fenced funding

Defining and predicting heat waves in Bangladesh

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

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers

Should seasonal rainfall forecasts be used for flood preparedness?

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 drivers 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 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 West 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 avoid misleading decision-makers

Different types of drought under climate change or geoengineering: systematic review of societal implications

Climate change and solar geoengineering have different implications for drought. Climate change can “speed up” the hydrological cycle, but it causesgreater evapotranspiration than the historical climate because of higher temperatures. Solar geoengineering (stratospheric aerosol injection), on the other hand, tends to “slow down” the hydrological cycle while reducing potential evapotranspiration. There are two common definitions of drought that take this into account; rainfall-only (SPI) and potential-evapotranspiration (SPEI). In different regions of Africa, this can result in different versions of droughts for each scenario, with drier rainfall (SPI) droughts under geoengineering and drier potential-evapotranspiration (SPEI) droughts under climate change. However, the societal implications of these different types of drought are not clear. We present a systematic review of all papers comparing the relationship between real-world outcomes (streamflow, vegetation, and agricultural yields) with these two definitions of drought in Africa. We also correlate the two drought definitions (SPI and SPEI) with historical vegetation conditions across the continent. We find that potential-evapotranspiration-droughts (SPEI) tend to be more closely related with vegetation conditions, while rainfall-droughts (SPI) tend to be more closely related with streamflows across Africa. In many regions, adaptation plans are likely to be affected differently by these two drought types. In parts of East Africa and coastal West Africa, geoengineering could exacerbate both types of drought, which has implications for current investments in water infrastructure. The reverse is true in parts of Southern Africa. In the Sahel, sectors more sensitive to rainfall-drought (SPI), such as reservoir management, could see reduced water availability under solar geoengineering, while sectors more sensitive to potential-evapotranspiration-drought (SPEI), such as rainfed agriculture, could see increased water availability under solar geoengineering. Given that the implications of climate change and solar geoengineering futures are different in different regions and also for different sectors, we recommend that deliberations on solar geoengineering include the widest possible representation of stakeholders

Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin

Extreme flooding impacts millions of people that live within the Amazon floodplain. Global hydrological models (GHMs) are frequently used to assess and inform the management of flood risk, but knowledge on the skill of available models is required to inform their use and development. This paper presents an intercomparison of eight different GHMs freely available from collaborators of the Global Flood Partnership (GFP) for simulating floods in the Amazon basin. To gain insight into the strengths and shortcomings of each model, we assess their ability to reproduce daily and annual peak river flows against gauged observations at 75 hydrological stations over a 19-year period (1997–2015). As well as highlighting regional variability in the accuracy of simulated streamflow, these results indicate that (a) the meteorological input is the dominant control on the accuracy of both daily and annual maximum river flows, and (b) groundwater and routing calibration of Lisflood based on daily river flows has no impact on the ability to simulate flood peaks for the chosen river basin. These findings have important relevance for applications of large-scale hydrological models, including analysis of the impact of climate variability, assessment of the influence of long-term changes such as land-use and anthropogenic climate change, the assessment of flood likelihood, and for flood forecasting systems

Beyond El Niño: unsung climate modes drive African floods

The El Niño Southern Oscillation (ENSO) dominates the conversation about predictability of climate extremes and early warning and preparedness for floods and droughts, but in Africa other modes of climate variability are also known to influence rainfall anomalies. In this study, we compare the role of ENSO in driving flood hazard over sub-Saharan Africa with modes of climate variability in the Indian and Atlantic Oceans. This is achieved by applying flood frequency approaches to a hydrological reanalysis dataset and streamflow observations for different phases of the ENSO, Indian Ocean Dipole and Tropical South Atlantic climate modes. Our results highlight that Indian and Atlantic Ocean modes of climate variability are equally as important as ENSO for driving changes in the frequency of impactful floods across Africa. We propose that in many parts of Africa a larger consideration of these unsung climate modes could provide improved seasonal predictions of associated flood hazard and better inform adaptation to the changing climate