Danger from Above - The Economic Impacts of Floods

The scientific evidence decisively attributes natural hazards’ increasing intensity and frequency to global warming. The Synthesis Report of the 6th IPCC Assessment Report, which has just been finalized in March 2023, states: In the near term, every region in the world is projected to face further increases in climate hazards (medium to high confidence, depending on region and hazard), increasing multiple risks to ecosystems and humans (very high confidence). These risks of climate hazards include heat-related human mortality, biodiversity loss, and the spread of diseases, to name a few. Concerning the hazards themselves, floods, landslides, and water availability have the potential to lead to severe consequences for people, infrastructure, and the economy. Their study is highly relevant because climate hazards constitute a causal channel through which anthropogenic climate change influences the economy. For instance, estimates of their social and economic costs provide evidence for setting the social cost of carbon emissions. Given the projections from the natural sciences, it is striking that the discipline of economics has made little effort to assess the economic impact of many hazards. This thesis comprises four papers investigating the economic impacts of floods from extreme rainfall in Central America and the Caribbean. Chapter One provides empirical evidence that a non-negligible part of hurricanes’ direct damages can be attributed to extreme rainfall. Chapter Two then shifts the focus from large-scale hurricanes to small-scale flash floods. It develops a statistical method to detect potential flash flood events from satellite rainfall data. In Chapters Three and Four, I then use this method to study the economic impacts of flash floods consistently across Central America and the Caribbean. Specifically, Chapter Three looks at the dynamics in night light activity following a flood, whereas Chapter Four analyzes the flood’s impact on establishments. In the first chapter of my thesis, co-authored with Eric Strobl and published in Natural Hazards, we revisit the common notion of modeling the impacts of hurricanes solely via their local wind speed. In recent years, some of the most destructive hurricanes, such as Morakot in Taiwan 2009, Harvey in Texas 2017, and Idai in Mozambique 2019, are characterized not by particularly strong wind but by a tremendous amount of rainfall. Relying on a model and a damage function that ignores rainfall and subsequent flooding is thus bound to yield biased results. Furthermore, there is a consensus that rainfall-heavy hurricanes will likely become more common with global warming (Grossmann and Morgan, 2011; Walsh et al., 2016; Knutson et al., 2019). A priori, it is not clear how to best assess the rainfall flood risk and relate it to damages. For instance, adequate rainfall measurements at a high spatial resolution during a hurricane are generally unavailable. To this end, we link remote sensing precipitation data to regional damage data for five hurricanes in Jamaica from 2001 to 2012. We find that the maximum rainfall intensity during a hurricane in a region is a significant determinant of economic damages, explaining much of the variation. Next, we use extreme value modeling of precipitation and combine the return periods with an estimated damage function and satellite-derived night light intensity to assess the local risk in monetary terms. This allows us to quantify the monetary risk for different horizons. For instance, the damage risk for a 20-year rainfall event in Jamaica is estimated to be at least 238 million USD, i.e., about 1.5% of Jamaica’s yearly GDP. In my second chapter, co-authored with Nekeisha Spencer and Eric Strobl, we set out to study the rainfall conditions that trigger floods, particularly flash floods. These are a type of highly localized flood that is directly caused by short but intense episodes of rainfall (Borga et al., 2007). Compared to river floods that require catchment-type hydrological modeling, they can occur almost anywhere given intense rainfall and are, as such, one of the most common natural hazards.¹ The Caribbean is especially at risk from flash floods since urbanization is often unregulated and soil degradation common such that excess rainfall can not run off quickly (Gencer, 2013; Pinos and Quesada-Rom´an, 2021). We set out to assess rainfall characteristics of previous flash flood events to create a classification method above what threshold a rainfall event likely causes a flash flood. For this, we gather information on all 93 confirmed flash floods in Jamaica from 2001 to 2018. We link these to remote sensing precipitation data, with which we further construct the location-specific yearly maximum rainfall events. By employing the copula method to create intensity-duration-frequency (IDF) curves, we model the intensity and duration of the annual maximum events separately and flexibly from their respective marginal distribution. The estimated Normal copula has Weibull and generalized extreme value (GEV) marginals for duration and intensity, respectively. The parametric IDF curve with an associated return period of 2¹⁄₆ years is then the optimal threshold for flash flood event classification. The simple nature of connecting the copula method for IDF curves with a classification for flash floods potentially opens up many applications in parametric insurance programs, regional risk mapping, and hazard warning systems. I then investigate the local dynamic economic response after a flash flood in the third chapter. The idea that a natural disaster influences economic performance and organization not only on impact but over time has entertained several empirical studies that try to estimate these. These include the study of tropical storms (Nordhaus, 2010; Strobl, 2012; Hsiang and Jina, 2014), earthquakes (Barone and Mocetti, 2014; Fabian, Lessmann, and Sofke, 2019), droughts (Barrios, Bertinelli, and Strobl, 2010; Hornbeck, 2012) and floods (Loayza et al., 2012; Kocornik-Mina et al., 2020). The studies on floods focus on large-scale disasters and reports in global databases that neglect localized flash flood events. Conceptually, a natural hazard causes destruction upon impact that might depress local economic activity, cause its re-location or spur innovation and growth in the future. Given the high frequency of extreme rainfall events in many developing countries, they could be a primary mechanism for how climate and environmental degradation impacts their economic development. I employ the method from Chapter Two to construct a high-resolution physically based indicator of flash flood occurrence for Central America and the Caribbean. With that, I estimate the local economic response to an event via changes in local night light emissions from satellite data. After accounting for tropical cyclone activity, flash floods have a delayed, short-term negative effect on economic activity. In countries with a low to medium human development index (HDI), the average effect can be up to −5.7%. Back-of-the-envelope calculations suggest that, due to their high frequency, flash floods in these countries cause GDP growth to fall by −0.84 percentage points. Countries with higher development appear to be only marginally affected. I also find evidence for negative spatial spillovers from floods in neighboring locations. In my fourth chapter, I shift my focus from the dynamic perspective to the economic agents. With a limited capacity to adapt to climate change, it is important to study the mechanisms through which climate change affects the economy to guide policymakers (Mendelsohn, 2012). In the case of flash floods, such mechanisms likely include local establishments as the main economic agents. I again use the method from Chapter Two and link the indicator of flash flood occurrence to the Worldbank Enterprise Surveys for Central America and the Caribbean. They uniquely provide a large number of consistent, geo-located surveys across the study region. After controlling for the location-specific extreme rainfall history, I find that a flash flood significantly decreases sales and the number of employees but increases capital productivity. The negative effects are driven by establishments for which financial market access is an obstacle, whereas the increased capital productivity occurs in establishments with sufficient financial market access. Flash floods similarly affect different industries, with the notable exception of the construction sector. The construction sector is not negatively affected in terms of output and employment. My results suggest that flash floods negatively impact firms and that their increase due to global warming will likely influence economic activity. Improving financial market access appears to be an effective adaptation strategy to increase establishments’ resilience. ¹For instance, according to the Centre for Research on the Epidemiology of Disasters (CRED) Emergency Events Database (EM-DAT), the number of affected people in 2022 by flash floods (0.9 M) is significantly more than river floods (0.1 M) or forest fires (0.03 M)

Commonwealth Center for Recurrent Flooding Resiliency: An Update

October 17th, 2016 Update to Joint Subcommittee on Coastal Flooding. PDF of powerpoint presentation

The 2011 Thailand flood: climate causes and return periods

Thailand is one of the wealthiest and most developed countries in southeast Asia. However, its tropical location and the influence of seasonal monsoon rains and local topography make it prone to floods. The floods in 2011 were especially severe, causing estimated losses of US $30 billion (economic; Swiss Re, 2012) and US$12 billion (insured; Swiss Re, 2012). The insured loss ranks easily as the highest-ever worldwide from a freshwater flood disaster (Swiss Re, 2012). The primary reason for the floods was record rainfall: over Thailand as a whole, annual rainfall in 2011 was the highest in the country’s 61-year precipitation record (Thai Meteoro logical Department, 2011). In this article we first review the nature, impacts and historical ranking of the 2011 Thailand floods. We then examine the 2011 rainfall totals and anomalies across Thailand and use these with other data to discuss the climate causes for the exceptional rainfall. We then estimate the rainfall return period for this flooding event and compare this with satellite-derived return periods for the 2011 river flow. Finally, we bring together the different estimated return periods to provide a firmer assessment of how likely it is that a flood of the magnitude of 2011 will happen again

Rain Attenuation Modelling and Mitigation in The Tropics: Brief Review

This paper is a brief review of Rain AttenuationModelling and Mitigation in the Tropics. The fast depleting availability of the lower frequency bands like the Ku-band as a result of congestion by commercial satellite operations coupled with severe rain attenuations experienced at higher frequency bands (Ka and Q/V), particularly in the tropical regions which was caused by higher rainfall rates and bigger raindrop size, amongst others; it was pertinent that deliberate effforts be geared towards research along this direction. This became even more critical owing to a dearth database along the slant path in the tropical regions for use in rain propagation studies at microwave frequencies, especially at millimeter wave bands (where most signal depolarization and fading takes place). The results presented in this work are valuable for design and planning of the satellite link, particularly in the tropical regions.DAH, ITU-R and SAM model simulations along the slant-path were investigated using local rainfall data at 0.01% of the time, while making use of TRMM data from NigComSat-1 satellite to obtain the measured data for Lagos. Terrestrial attenuation data for 0.01% of the time for UTM were obtained from the UTM wireless communication center (WCC). The attenuation data were thereafter transformed to slant path using transformation technique proposed for Ku band byA. Y. Abdulrahman. Theattenuation exceeded for other percentages of the average year was obtained using statistical interpolation extrapolation method.It was observed that the proposed model predicts creditably well for the ka down link frequency band, by producing the best performance when compared with SAM, DAH and ITU-R models.DOI:http://dx.doi.org/10.11591/ijece.v2i6.122

Weekly synoptic analyses 5-, 2-, and 0.4- millibar surfaces for 1966

Meteorological rocketsonde and high level rawinsonde synoptic data analysi

Effects of Vertical Wind Shear on Intensity and Rainfall Asymmetries of Strong Tropical Storm Bilis (2006)

Abstract The effects of environmental vertical wind shear (VWS) on the intensity and rainfall asymmetries in Tropical Storm (TS) Bilis (2006) have been analyzed based on the TRMM/TMI estimated surface rainfall data, the QuikSCAT wind fields, 850-hPa and 200-hPa winds of the NCEP/NCAR reanalysis, the precipitation data at 5-minute intervals from automatic weather stations over mainland China, and the best track data of TS Bilis. The results show that the simultaneous and 6h-lagged correlation coefficients between VWS and storm intensity (the minimum central sea level pressure) are 0.59145 and 0.57438 (P<0.01), respectively. The averaged VWS was found to be about 11 m s -1 and thus suppressed the intensification of Bilis. Distribution of precipitation in Bilis was highly asymmetric. The azimuthally averaged rainfall rate in the partial eyewall, however, was smaller than that in a major outer rainband. As the storm intensified, the major rainband showed an unusual outward propagation. The VWS had a great impact on the asymmetric distribution of precipitation. Consistent with previous modeling studies, heavy rainfall generally occurred downshear to downshear-left of the VWS vector both near and outside the eyewall, showing a strong wavenumber-one asymmetry, which was amplified as the VWS increased

Feasibility of beneficial hurricane modification by carbon dust seeding

April 1973.Includes bibliographical references.Sponsored by NOAA N-22-65-73(G)

Central Florida Future, Vol. 38 No. 07, September 8, 2005

Car accident proves fatal for UCF student and two passengers; Underage beware! Police aim to curb illegal consumption; Ophelia nagging Florida\u27s coast: Winds increasing but tropical storm heading out to sea; Engineers taking students for a free ride: Automotive club to hold \u27UCF Day\u27 with hopes of gaining recruits.https://stars.library.ucf.edu/centralfloridafuture/2846/thumbnail.jp

The incidence of extreme climatic rainfall in Thailand

Extreme climatic rainfall, defined as extreme rainfall over monthly to annual timescales with a return period of 10 years or more, is common in Thailand due to its location and climate. Flooding from persistent heavy rainfall causes much of the insured and economic losses from natural hazards in the country. Despite this, there is little detailed historical information regarding the incidence of extreme climatic rainfall in Thailand. In this study I aimed to quantify the incidence of extreme climatic rainfall in Thailand, primarily through return period analysis. I used gridded (1901–2012) rainfall data to produce distribution-fitted return period curves with uncertainties, and then derived a catalogue of return period maps for Thailand. Extreme climatic precipitation events were identified for further study, including the 2011 flood, which caused the highest ever insured loss (US$12 billion) from a freshwater flood disaster worldwide. For each event, I examined the nature, impacts, rainfall totals and anomalies, and climate causes. Return period analysis assessed the likelihood of re-occurrence of each event. The extreme climatic rainfall return periods varied depending on length of dataset and the fitted distribution used. Various estimates suggest a precipitation return period of 79 (August), 385 (June–August) and 164 years (annual) for 1942, 1995 and 2011 respectively. Analysis found that the El Niño Southern Oscillation (ENSO) was the primary driver of interannual rainfall variability in Thailand. Rainfall during a La Niña phase was, on average, 8.7% higher than during an El Niño phase. This difference increased when the ENSO event persisted in the same phase for multiple years; rainfall was 14.4% higher during multi-year La Niña events than during multi-year El Niño events. These findings are of particular importance to the insurance and risk management industry, and the methodology is easily transferable for use in other Southeast Asian countries

A socio-economic environmental baseline summary for the south Atlantic region between Cape Hatteras, North Carolina and Cape Canaveral, Florida Volume II : Climatology

The geographic area covered in this report extends from Cape Hatteras, North Carolina, on the north, to Cape Canaveral, Florida, to the·south. Included within this area are portions of the coastal areas of South Carolina and Georgia. All or portions of thirty coastal counties are included within the study area. Estuaries in this area tend to be partially mixed due to relatively low runoff per mile of coast. The proximity of the Gulf Stream to the continental shelf and the low runoff combine to cause the salinity of the coastal water to be somewhat higher than that of the coastal water north of Cape Hatteras. Surface isotherms parallel the coast and temperatures generally increase seaward. Maximum horizontal gradients and minimum vertical gradients of temperature are usually found during winter