Precipitation Products’ Inter–Comparison over East and Southern Africa 1983–2017

During recent decades East Africa (EA) and Southern Africa (SA) have experienced an intensification of hydrological hazards, such as floods and droughts, which have dramatically affected the population, making these areas two of the regions of the African continent most vulnerable to these hazards. Thus, precipitation monitoring and the evaluation of its variability have become fundamentally important actions through the analysis of long-term data records. In particular, satellite-based precipitation products are often used because they counterbalance the sparsity of the rain gauge networks which often characterize these areas. The aim of this work is to compare and contrast the capabilities of three daily satellite-based products in EA and SA from 1983 to 2017. The selected products are two daily rainfall datasets based on high-resolution thermal infrared observations, TAMSAT version 3 and CHIRPS, and a relatively new global product, MSWEP version 2.2, which merges satellite-based, rain gauge and re-analysis precipitation data. The datasets have been directly intercompared, avoiding the traditional rain gauge validation. This is done by means of pairwise comparison statistics at 0.25° spatial resolution and daily time scale to assess rain–detection and quantitative estimate capabilities. Monthly climatology and spatial distribution of seasonality are analyzed as well. The time evolution of the statistical indexes has been evaluated in order to analyze the stability of the rain detection and estimation performances. Considerable agreement among the precipitation products emerged from the analysis, in spite of the differences occurring in specific situations over complex terrain, such as mountainous and coastal regions and deserts. Moreover, the temporal evolution of the statistical indices has demonstrated that the agreement between the products improved over time, with more stable capabilities in identifying precipitating days and estimating daily precipitation starting in the second half of the 1990s.

Natural Disasters—Origins, Impacts, Management

Natural hazards are processes that serve as triggers for natural disasters. Natural hazards can be classified into six categories. Geophysical or geological hazards relate to movement in solid earth. Their examples include earthquakes and volcanic activity. Hydrological hazards relate to the movement of water and include floods, landslides, and wave action. Meteorological hazards are storms, extreme temperatures, and fog. Climatological hazards are increasingly related to climate change and include droughts and wildfires. Biological hazards are caused by exposure to living organisms and/or their toxic substances. The COVID-19 virus is an example of a biological hazard. Extraterrestrial hazards are caused by asteroids, meteoroids, and comets as they pass near earth or strike earth. In addition to local damage, they can change earth inter planetary conditions that can affect the Earth’s magnetosphere, ionosphere, and thermosphere. This entry presents an overview of origins, impacts, and management of natural disasters. It describes processes that have potential to cause natural disasters. It outlines a brief history of impacts of natural hazards on the human built environment and the common techniques adopted for natural disaster preparedness. It also lays out challenges in dealing with disasters caused by natural hazards and points to new directions in warding off the adverse impact of such disasters.

Analysis of meteorological parameters triggering rainfall- induced landslide: a review of 70 years in Valtellina

This paper presents an extended reanalysis of the rainfall-induced geo-hydrological events that have occurred in the last 70 years in the alpine area of the Lombardy region, Italy. The work is focused on the description of the major meteorological triggering factors that have caused diffuse episodes of shallow landslides and debris flow. The aim of this reanalysis was to try to evaluate their magnitude quantitatively. The triggering factors were studied following two approaches. The first one started from the conventional analysis of the rainfall intensity (I) and duration (D) considering local rain gauge data and applying the I–D threshold methodology integrated with an estimation of the events' return period. We then extended this analysis and proposed a new index for the magnitude assessment (magnitude index, MI) based on frequency–magnitude theory. The MI was defined considering both the return period and the spatial extent of each rainfall episode. The second approach is based on a regional-scale analysis of meteorological triggers. In particular, the strength of the extratropical cyclone (EC) structure associated with the precipitation events was assessed through the sea level pressure tendency (SLPT) meteorological index. The latter has been estimated from the Norwegian cyclone model (NCM) theory. Both indexes have shown an agreement in ranking the event's magnitude (R2=0.88), giving a similar interpretation of the severity that was also found to be in accordance with the information reported in historical databases. This back analysis of 70 years in Valtellina identifies the MI and the SLPT as good magnitude indicators of the event, confirming that a strong cause–effect relationship exists among the EC intensity and the local rainfall recorded on the ground. In respect of the conventional I–D threshold methodology, which is limited to a binary estimate of the likelihood of landslide occurrence, the evaluation of the MI and the SLPT indexes allows quantifying the magnitude of a rainfall episode capable of generating severe geo-hydrological hazards.

Climate change adaptation to extreme heat: A global systematic review of implemented action

Extreme heat events impact people and ecosystems across the globe, and they are becoming more frequent and intense in a warming climate. Responses to heat span sectors and geographic boundaries. Prior research has documented technologies or options that can be deployed to manage extreme heat and examples of how individuals, communities, governments, and other stakeholder groups are adapting to heat. However, a comprehensive understanding of the current state of implemented heat adaptations—where, why, how, and to what extent they are occurring—has not been established. Here, we combine data from the Global Adaptation Mapping Initiative with a heat-specific systematic review to analyze the global extent and diversity of documented heat adaptation actions (n = 301 peer-reviewed articles). Data from 98 countries suggest that documented heat adaptations fundamentally differ by geographic region and national income. In high-income, developed countries, heat is overwhelmingly treated as a health issue, particularly in urban areas. However, in low and middle income, developing countries, heat adaptations focus on agricultural and livelihood-based impacts, primarily considering heat as a compound hazard with drought and other hydrological hazards. 63% of the heat-adaptation articles feature individuals or communities autonomously adapting, highlighting how responses to date have largely consisted of coping strategies. The current global status of responses to intensifying extreme heat, largely autonomous and incremental yet widespread, establishes a foundation for informed decision making as heat impacts around the world continue to increase.

ENHANCING FORECAST-BASED DISASTER RESPONSE IN NEPAL

Implementation of humanitarian actions in advance of a disaster event is a new approach to enhance overall effectiveness of disaster responses. Early actions following forecasts and early warnings can significantly reduce disaster losses and the cost of disaster recovery. Evidence from pilot projects reveal potential to integrate forecast-based humanitarian actions into disaster preparedness planning. Building on advanced technologies, it has been possible to predict disaster risk of many meteorological and hydrological hazards like heavy rainfall, storm surges, flood, drought and cyclones. Nepal has developed communitycentered, end to end flood early warning systems, which have utilised different global and regional weather forecasting models. The models have the capability to provide weather and flood scenarios three days in advance. In this study, we carefully examine current practices and approaches to explore opportunities to use weather forecasts, flood alerts and warning to inform forecast-based humanitarian actions. Furthermore, we analysed existing policy provisions and legal mandates in Nepal to assess the availability of enabling environment needed for adopting forecast-based humanitarian actions. We also present our learning from piloting this approach to disaster preparedness planning in 19 selected districts of Nepal. Our findings suggest that adequate legal provisions and appropriate institutional mechanisms are essential to ensure effective implementation of forecastbased early actions. It is important and urgent to depart from traditional post-event relief approach to a risk-informed preventive decision-making. Technological limitations and operational gaps between agencies are major barriers to proactive actions. The challenges can be overcome through sufficient legal provisions, technical guidelines and protocols to clarify roles, responsibilities and accountabilities of the authorities.

A Real-Time Algorithm to Identify Convective Precipitation Adjacent to or within the Bright Band in the Radar Scan Domain

Hydrological hazards usually occur after heavy precipitation, especially during strong convection. Therefore, accurately identifying convective precipitation is very helpful for hydrological warning and forecasting. However, separating the convective, bright band (BB), and stratiform precipitation is found to be challenging when the convection is adjacent to or within the BB region. A new convection/BB/stratiform precipitation segregation algorithm is proposed in this study to resolve this challenging issue. This algorithm is applicable for a single radar volume scan data in native (polar) coordinates and consists of four processes: 1) check the freezing (0°C) level to roughly assess whether convection is occurring or not; 2) identify the convective cores through analyzing composite reflectivity (maximum reflectivity for a given range gate among all the sweeps), vertically integrated liquid water (VIL), VIL horizontal gradient, and reflectivity at the levels of 0°, −10°, and above −10°C; 3) delineate the whole convective region through the seeded region growing method by taking account of the microphysical differences between the BB and convective regions; and 4) delineate BB features in the stratiform region. The proposed algorithm utilizes the physical characteristics of different precipitation types for precisely segregating the convective, BB, and stratiform precipitation. This algorithm has been tested with radar data of different precipitation events and evaluated with three months of rain gauge data. The results show that the proposed algorithm performs consistently well for challenging precipitation events with the convection adjacent to or within a strong BB. Furthermore, the proposed algorithm could be used to improve the vertical profile of reflectivity (VPR) correction and reduce the overestimation of rainfall in the BB precipitation region.

Flood risk behaviors of United States riverine metropolitan areas are driven by local hydrology and shaped by race

Flooding risk results from complex interactions between hydrological hazards (e.g., riverine inundation during periods of heavy rainfall), exposure, vulnerability (e.g., the potential for structural damage or loss of life), and resilience (how well we recover, learn from, and adapt to past floods). Building on recent coupled conceptualizations of these complex interactions, we characterize human–flood interactions (collective memory and risk-enduring attitude) at a more comprehensive scale than has been attempted to date across 50 US metropolitan statistical areas with a sociohydrologic (SH) model calibrated with accessible local data (historical records of annual peak streamflow, flood insurance loss claims, active insurance policy records, and population density). A cluster analysis on calibrated SH model parameter sets for metropolitan areas identified two dominant behaviors: 1) “risk-enduring” cities with lower flooding defenses and longer memory of past flood loss events and 2) “risk-averse” cities with higher flooding defenses and reduced memory of past flooding. These divergent behaviors correlated with differences in local stream flashiness indices (i.e., the frequency and rapidity of daily changes in streamflow), maximum dam heights, and the proportion of White to non-White residents in US metropolitan areas. Risk-averse cities tended to exist within regions characterized by flashier streamflow conditions, larger dams, and larger proportions of White residents. Our research supports the development of SH models in urban metropolitan areas and the design of risk management strategies that consider both demographically heterogeneous populations, changing flood defenses, and temporal changes in community risk perceptions and tolerance.

The impact of atmospheric rivers on rainfall in New Zealand

This study quantifies the impact of atmospheric rivers (ARs) on rainfall in New Zealand. Using an automated AR detection algorithm, daily rainfall records from 654 rain gauges, and various atmospheric reanalysis datasets, we investigate the climatology of ARs, the characteristics of landfalling ARs, the contribution of ARs to annual and seasonal rainfall totals, and extreme rainfall events between 1979 and 2018 across the country. Results indicate that these filamentary synoptic features play an essential role in regional water resources and are responsible for many extreme rainfall events on the western side of mountainous areas and northern New Zealand. In these regions, depending on the season, 40–86% of the rainfall totals and 50–98% of extreme rainfall events are shown to be associated with ARs, with the largest contributions predominantly occurring during the austral summer. Furthermore, the median daily rainfall associated with ARs is 2–3 times than that associated with other storms. The results of this study extend the knowledge on the critical roles of ARs on hydrology and highlight the need for further investigation on the landfalling AR physical processes in relation to global circulation features and AR sources, and hydrological hazards caused by ARs in New Zealand.