Natural Hazards and Impacts

pic
Global Drought Hazard Distribution (1980-2000); Source: SEDAC

Because adaptation assessments often originate from the need to understand and address changes in natural hazards and climate impact, we focus here on climate information requirements to better characterize the frequency and intensity of natural hazards. For example, an analysis of changes in the length of dry spells over a historical period for a particular region would enable understanding of the severity and extent of drought conditions. Of course, not all climate-related disasters are caused by climate change; for example, flooding may be due to changes in land cover, and the impact on society that makes it a “disaster” depends on the exposure of things that humans value (e.g. buildings, infrastructures, farms). However, understanding the role of climate change in exacerbating these impacts is vital for adaptation. Through the identification of climate analyses that help explain historical, current and future changes in natural hazards/climate impacts, stakeholders can focus their efforts on understanding a specified subset of climate information.

SEVERE DROUGHT

The greatest contributing climatic factor in the duration and spatial extent of severe drought is precipitation. Temperature,  human-induced land use change, agricultural practices, and soil quality and moisture can also contribute. Analysis of extremely low rainfall amounts over a historical time-period can demonstrate the anticipated duration of a drought event, while monitoring and forecasting of seasonal rainfall can provide an early drought warning, and projected changes in precipitation can show worsening or alleviating drought conditions over the course of the 21st century. Table 1.2 provides a summary of climate analyses that are needed to understand severe drought at various timescales.

Typical Variables Time Frame 
Historical ClimateMonitoring & EWSProjections
Number of consecutive days with high maximum temperature
Maximum temperature
Historical changes in maximum temperature
Maximum temperature thresholds
Duration of high temperature sequences (above a certain critical threshold)
High temperature sequence monitoring
Weather/extended weather forecast
Seasonal probabilistic temperature forecast
Downscaled projections of changes in maximum temperature: magnitude; duration
Probabilities of exceeding high temperature sequences

CHANGES IN RAINFALL PATTERNS AND GENERAL DROUGHT CONDITIONS

Changes in rainfall patterns (i.e. the spatial distribution of rainfall, its seasonal onset, and general drought conditions) can be understood through analysis of average precipitation. Since it is vital for the agricultural sector to know about changes in the onset of the rainy season and how much rainfall is expected, investigation of total annual and seasonal precipitation is necessary. Unlike severe drought, which involves analysis of extreme precipitation, understanding changes in rainfall patterns and general drought conditions requires analysis of changes in average precipitation. Deviations from average precipitation are referred to as anomalies and can be calculated for each year and/or season. Table 1.3 provides a summary of climate analyses that are needed to understand potential changes in rainfall patterns and general drought conditions at various timescales.

Typical Variables Time Frame 
Historical ClimateMonitoring & EWSProjections
Climate AnalysisHistorical changes in average seasonal or annual precipitation
Historical changes in average daily precipitation (i.e. dry spell duration)
Cumulative rainfall
Seasonal probabilistic rainfall forecast
Downscaled projections of changes in average seasonal or annual precipitation
Changes in the amplitude of variability

FLASH FLOODS

In contrast to severe drought, understanding flash floods requires analysis of extreme precipitation events. Rapid flooding of low-lying areas is often associated with heavy rain and severe storms. Soil moisture is also an important non-climatic influencer. Historical analysis of extreme high precipitation events can help to understand the probability of a rare flood event and the chances of one happening in the future. Flood early warning systems are essential for disaster preparedness and evacuation. Regional projections of extreme high precipitation events are needed since climate change might negatively affect the frequency and intensity of such events. Furthermore, hydrological, infrastructural, and adaptation planning processes require this type of information. Table 1.4 provides a summary of climate analyses that are needed to understand flash flood events at various timescales.

Typical Variables Time Frame 
Historical ClimateMonitoring & EWSProjections
Hourly or daily rainfall or rainfall intensitiesHistorical variability and trends in extreme high precipitation
Thresholds based on past events
Weather forecast
10-day climate Bulletin-Dekadal probabilistic rainfall forecast
Downscaled projections of extreme precipitation, using thresholds based on historical analysis

SEASONAL FLOODING

Most West African countries experience seasonal flooding during the rainy season, which can vary in intensity depending on the West African Monsoon and other large-scale convective processes. Seasonal rainfall is a natural phenomenon that occurs due the north-south movement of the Intertropical Convergence Zone (ITCZ). Predictors with the greatest correlation to seasonal flooding include total seasonal rainfall and seasonal rainfall intensity, defined as total precipitation divided by the number of rainy days (de Perez et al., 2017). Understanding such predictors has become increasingly important due to observed changes in the rainy season and increased flooding intensity in certain areas as a possible impact of climate change. Additionally, sea level rise is another important climate change impact that should be investigated locally since it may exacerbate seasonal flooding.

Typical Variables Time Frame 
Historical ClimateMonitoring & EWSProjections
Average daily precipitation
Consecutive number of rainy days
Historical changes in average precipitation and length of wet sequencesSeasonal probabilistic rainfall forecastDownscaled projections of changes in average precipitation and length of wet sequences
fig
Figure 2.3 Probability of occurrence of temperature conditions; an increase in the average temperature results in more “hot weather” and “record hot weather.” Source: CDC

EXTREME HEAT EVENTS

An extreme heat event refers to an extended period of time (several days or more) with unusually hot weather conditions that can potentially harm human health. Increases in average global temperature are projected to make heat events last longer and occur more frequently. Both average and extreme temperature can be analyzed to better understand extreme heat events at various time scales. As shown in figure 2.3, an increase in average future temperature results in more “hot weather”.
In addition to average temperature analysis, projections using GCMs and RCMs for number of days above a certain temperature threshold can also be made to specifically analyze changes extreme heat events. Temperature monitoring is needed for short-term forecasting and early warning in preparation for such extreme events. Although there is emphasis on rainfall early warning systems for agricultural purposes, temperature early warning systems are just as important for human health and survival. Table 6 provides a summary of climate analyses that are needed to understand extreme heat events at various timescales.

Typical variables Time Frame 
Historical climateMonitoring & EWSProjections
Cumulative rainfall amounts
Dry spells (number of days with rainfall below a certain amount)
Evapotranspiration
Historical variability and trends of cumulative rainfall
Historical length and distribution of dry spell lengths
Standardized Precipitation Index (SPI)
Length of current dry spell
Water satisfaction index (WRSI)
Seasonal rainfall forecast
Seasonal rainfall and temperature
Daily rainfall distribution
Daily maximal and minimal temperature
Changes in distribution of length of dry spells
Probability distribution of WRSI

DISEASE OUTBREAKS

Appropriate climate and weather conditions are necessary for the survival, reproduction, distribution, and transmission of disease pathogens, vectors, and hosts. Therefore, changes in climate or weather conditions impact the ability of infectious diseases to survive and proliferate. Particularly, excessive heat can increase mortality rates for some pathogens; rising temperatures can influence their reproduction and extrinsic incubation period; and extended periods of hot weather can raise the average temperature of water bodies and food environments, which may provide an agreeable environment for microorganism reproduction and algal blooms. With increased precipitation there is often an associated increase in fecal pathogens during the rainy season; droughts/low rainfall lead to slow river flows, causing a concentration of effluent water-borne pathogens. Humidity, sunshine, and wind also impact the survival, reproduction, distribution, and environment of disease pathogens and hosts (Wu et al., 2016). Due to the variety of climatic factors and interactions that influence disease outbreaks, it is difficult to model disease outbreaks. However, there are disease monitoring resources available, including the Malaria Early Warning System (MEWS), developed by the International Research Institute for Climate and Society (IRI) and National Malaria Control Program (NMCP).

« Best Practice
Resources »