Pub Date : 2024-06-03DOI: 10.1038/s44304-024-00011-0
Roger Pielke Jr
For more than two decades, the U.S. National Oceanic and Atmospheric Administration (NOAA) has published a count of weather-related disasters in the United States that it estimates have exceeded one billion dollars (inflation adjusted) in each calendar year starting in 1980. The dataset is widely cited and applied in research, assessment and invoked to justify policy in federal agencies, Congress and by the U.S. President. This paper performs an evaluation of the dataset under criteria of procedure and substance defined under NOAA’s Information Quality and Scientific Integrity policies. The evaluation finds that the “billion dollar disaster” dataset falls short of meeting these criteria. Thus, public claims promoted by NOAA associated with the dataset and its significance are flawed and at times misleading. Specifically, NOAA incorrectly claims that for some types of extreme weather, the dataset demonstrates detection and attribution of changes on climate timescales. Similarly flawed are NOAA’s claims that increasing annual counts of billion dollar disasters are in part a consequence of human caused climate change. NOAA’s claims to have achieved detection and attribution are not supported by any scientific analysis that it has performed. Given the importance and influence of the dataset in science and policy, NOAA should act quickly to address this scientific integrity shortfall.
{"title":"Scientific integrity and U.S. “Billion Dollar Disasters”","authors":"Roger Pielke Jr","doi":"10.1038/s44304-024-00011-0","DOIUrl":"10.1038/s44304-024-00011-0","url":null,"abstract":"For more than two decades, the U.S. National Oceanic and Atmospheric Administration (NOAA) has published a count of weather-related disasters in the United States that it estimates have exceeded one billion dollars (inflation adjusted) in each calendar year starting in 1980. The dataset is widely cited and applied in research, assessment and invoked to justify policy in federal agencies, Congress and by the U.S. President. This paper performs an evaluation of the dataset under criteria of procedure and substance defined under NOAA’s Information Quality and Scientific Integrity policies. The evaluation finds that the “billion dollar disaster” dataset falls short of meeting these criteria. Thus, public claims promoted by NOAA associated with the dataset and its significance are flawed and at times misleading. Specifically, NOAA incorrectly claims that for some types of extreme weather, the dataset demonstrates detection and attribution of changes on climate timescales. Similarly flawed are NOAA’s claims that increasing annual counts of billion dollar disasters are in part a consequence of human caused climate change. NOAA’s claims to have achieved detection and attribution are not supported by any scientific analysis that it has performed. Given the importance and influence of the dataset in science and policy, NOAA should act quickly to address this scientific integrity shortfall.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00011-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141246197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The impact of tropical cyclones (TCs) has intensified with continued global warming and socio-economic development. Quantifying the TC economic exposure is a core element of economic risk assessment for TCs. The centroid of annual economic exposure to TCs in China shifted northward at a rate of 19.71 km per year from 2006 to 2020, where changes in the TC tracks contributed a northward shift of 11.22 km per year and changes in GDP distribution contributed a northward shift of 7.75 km per year. The northward shift of TC economic exposure centroid is more than twice as sensitive to the shift of GDP distribution as to that of TC tracks. The phenomenon of the northward shift in TC economic exposure is particularly evident in the subtropical zone in China. Further northward shift of TC exposure could potentially cause higher socio-economic losses in places underprepared for TC hazards. Our result provides references for TC disaster mitigation and preparedness in China.
{"title":"Recent northward shift of tropical cyclone economic risk in China","authors":"Lianjie Qin, Laiyin Zhu, Xinli Liao, Chenna Meng, Qinmei Han, Zixuan Li, Shifei Shen, Wei Xu, Jianguo Chen","doi":"10.1038/s44304-024-00008-9","DOIUrl":"10.1038/s44304-024-00008-9","url":null,"abstract":"The impact of tropical cyclones (TCs) has intensified with continued global warming and socio-economic development. Quantifying the TC economic exposure is a core element of economic risk assessment for TCs. The centroid of annual economic exposure to TCs in China shifted northward at a rate of 19.71 km per year from 2006 to 2020, where changes in the TC tracks contributed a northward shift of 11.22 km per year and changes in GDP distribution contributed a northward shift of 7.75 km per year. The northward shift of TC economic exposure centroid is more than twice as sensitive to the shift of GDP distribution as to that of TC tracks. The phenomenon of the northward shift in TC economic exposure is particularly evident in the subtropical zone in China. Further northward shift of TC exposure could potentially cause higher socio-economic losses in places underprepared for TC hazards. Our result provides references for TC disaster mitigation and preparedness in China.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00008-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141182310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1038/s44304-024-00006-x
Katsuichiro Goda, Raffaele De Risi
A new time-dependent probabilistic tsunami risk model is developed to facilitate the long-term risk management strategies for coastal communities. The model incorporates the time-dependency of earthquake occurrence and considers numerous heterogeneous slip distributions via a stochastic source modeling approach. Tidal level effects are examined by considering different baseline sea levels. The model is applied to Tofino, British Columbia, Canada within the Cascadia subduction zone. High-resolution topography and high-quality exposure data are utilized to accurately evaluate tsunami damage and economic loss to buildings. The results are tsunami loss curves accounting for different elapsed times since the last major event. The evolutionary aspects of Tofino’s time-dependent tsunami risk profiles show that the current tsunami risk is lower than the tsunami risk based on the conventional time-independent Poisson occurrence model. In contrast, the future tsunami risk in 2100 will exceed the time-independent tsunami risk estimate.
{"title":"Time-dependent probabilistic tsunami risk assessment: application to Tofino, British Columbia, Canada, subjected to Cascadia subduction earthquakes","authors":"Katsuichiro Goda, Raffaele De Risi","doi":"10.1038/s44304-024-00006-x","DOIUrl":"10.1038/s44304-024-00006-x","url":null,"abstract":"A new time-dependent probabilistic tsunami risk model is developed to facilitate the long-term risk management strategies for coastal communities. The model incorporates the time-dependency of earthquake occurrence and considers numerous heterogeneous slip distributions via a stochastic source modeling approach. Tidal level effects are examined by considering different baseline sea levels. The model is applied to Tofino, British Columbia, Canada within the Cascadia subduction zone. High-resolution topography and high-quality exposure data are utilized to accurately evaluate tsunami damage and economic loss to buildings. The results are tsunami loss curves accounting for different elapsed times since the last major event. The evolutionary aspects of Tofino’s time-dependent tsunami risk profiles show that the current tsunami risk is lower than the tsunami risk based on the conventional time-independent Poisson occurrence model. In contrast, the future tsunami risk in 2100 will exceed the time-independent tsunami risk estimate.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00006-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140844999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-02DOI: 10.1038/s44304-024-00004-z
Md Adilur Rahim, Ayat Al Assi, Rubayet Bin Mostafiz, Carol J. Friedland
The flood depth in a structure is a key factor in flood loss models, influencing the estimation of building and contents losses, as well as overall flood risk. Recent studies have emphasized the importance of determining the damage initiation point (DIP) of depth-damage functions, where the flood damage is assumed to initiate with respect to the first-floor height of the building. Here we investigate the effects of DIP selection on the flood risk assessment of buildings located in Special Flood Hazard Areas. We characterize flood using the Gumbel extreme value distribution’s location (μ) and scale (α) parameters. Results reveal that average annual flood loss (AAL) values do not depend on μ, but instead follow an exponential decay pattern with α when damage initiates below the first-floor height of a building (i.e., negative DIP). A linear increasing pattern of the AAL with α is achieved by changing the DIP to the first-floor height (i.e., DIP = 0). The study also demonstrates that negative DIPs have larger associated AAL, thus contributing substantially to the overall AAL, compared to positive DIPs. The study underscores the significance of proper DIP selection in flood risk assessment.
{"title":"Effects of damage initiation points of depth-damage function on flood risk assessment","authors":"Md Adilur Rahim, Ayat Al Assi, Rubayet Bin Mostafiz, Carol J. Friedland","doi":"10.1038/s44304-024-00004-z","DOIUrl":"10.1038/s44304-024-00004-z","url":null,"abstract":"The flood depth in a structure is a key factor in flood loss models, influencing the estimation of building and contents losses, as well as overall flood risk. Recent studies have emphasized the importance of determining the damage initiation point (DIP) of depth-damage functions, where the flood damage is assumed to initiate with respect to the first-floor height of the building. Here we investigate the effects of DIP selection on the flood risk assessment of buildings located in Special Flood Hazard Areas. We characterize flood using the Gumbel extreme value distribution’s location (μ) and scale (α) parameters. Results reveal that average annual flood loss (AAL) values do not depend on μ, but instead follow an exponential decay pattern with α when damage initiates below the first-floor height of a building (i.e., negative DIP). A linear increasing pattern of the AAL with α is achieved by changing the DIP to the first-floor height (i.e., DIP = 0). The study also demonstrates that negative DIPs have larger associated AAL, thus contributing substantially to the overall AAL, compared to positive DIPs. The study underscores the significance of proper DIP selection in flood risk assessment.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00004-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140819059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-04DOI: 10.1038/s44304-024-00005-y
Ji-Eun Byun, Sang-ri Yi
Multiple authorities have introduced an anti-price-gouging law to prevent sellers from raising prices higher than what is considered reasonable. Effectiveness of the law has been heatedly debated in various disciplines such as economics, ethics and politics. In this article, we investigate its effectiveness by developing a model that simulates a post-earthquake situation and apply the model to San Francisco, CA, USA. The model accounts for various competing forces, i.e. post-disaster increase in production cost and demands, assets damage, donation and hoarding. Thereby, it returns multiple decision metrics, i.e. unfulfilled needs in basic goods, repair periods and well-being loss caused by insufficient supplies and increased prices. The result shows that the optimal level of a price cap depends on a decision metric and local conditions. This indicates that the problem does not have a single optimal decision, but rather a compromise needs to be made between conflicting decision metrics. Generalising this observation, we propose a narrative numeric (NN) method as a new social discourse method. The objective of the NN method does not lie in concluding the most truthful argument, but rather in identifying a decision scenario that yields an agreeable compromise to (hopefully) all stakeholder groups.
{"title":"Anti-price-gouging law is neither good nor bad in itself: a proposal of narrative numeric method for transdisciplinary social discourses","authors":"Ji-Eun Byun, Sang-ri Yi","doi":"10.1038/s44304-024-00005-y","DOIUrl":"10.1038/s44304-024-00005-y","url":null,"abstract":"Multiple authorities have introduced an anti-price-gouging law to prevent sellers from raising prices higher than what is considered reasonable. Effectiveness of the law has been heatedly debated in various disciplines such as economics, ethics and politics. In this article, we investigate its effectiveness by developing a model that simulates a post-earthquake situation and apply the model to San Francisco, CA, USA. The model accounts for various competing forces, i.e. post-disaster increase in production cost and demands, assets damage, donation and hoarding. Thereby, it returns multiple decision metrics, i.e. unfulfilled needs in basic goods, repair periods and well-being loss caused by insufficient supplies and increased prices. The result shows that the optimal level of a price cap depends on a decision metric and local conditions. This indicates that the problem does not have a single optimal decision, but rather a compromise needs to be made between conflicting decision metrics. Generalising this observation, we propose a narrative numeric (NN) method as a new social discourse method. The objective of the NN method does not lie in concluding the most truthful argument, but rather in identifying a decision scenario that yields an agreeable compromise to (hopefully) all stakeholder groups.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00005-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140345845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A catastrophic Mw7.8 earthquake hit southeast Turkey and northwest Syria on February 6th, 2023, leading to more than 44 k deaths and 160 k building collapses. The interpretation of earthquake-triggered building damage is usually subjective, labor intensive, and limited by accessibility to the sites and the availability of instant, high-resolution images. Here we propose a multi-class damage detection (MCDD) model enlightened by artificial intelligence to synergize four variables, i.e., amplitude dispersion index (ADI) and damage proxy (DP) map derived from Synthetic Aperture Radar (SAR) images, the change of the normalized difference built-up index (NDBI) derived from optical remote sensing images, as well as peak ground acceleration (PGA). This approach allows us to characterize damage on a large, tectonic scale and a small, individual-building scale. The integration of multiple variables in classifying damage levels into no damage, slight damage, and serious damage (including partial or complete collapses) excels the traditional practice of solely use of DP by 11.25% in performance. Our proposed approach can quantitatively and automatically sort out different building damage levels from publicly available satellite observations, which helps prioritize the rescue mission in response to emergent disasters.
{"title":"Intelligent assessment of building damage of 2023 Turkey-Syria Earthquake by multiple remote sensing approaches","authors":"Xiao Yu, Xie Hu, Yuqi Song, Susu Xu, Xuechun Li, Xiaodong Song, Xuanmei Fan, Fang Wang","doi":"10.1038/s44304-024-00003-0","DOIUrl":"10.1038/s44304-024-00003-0","url":null,"abstract":"A catastrophic Mw7.8 earthquake hit southeast Turkey and northwest Syria on February 6th, 2023, leading to more than 44 k deaths and 160 k building collapses. The interpretation of earthquake-triggered building damage is usually subjective, labor intensive, and limited by accessibility to the sites and the availability of instant, high-resolution images. Here we propose a multi-class damage detection (MCDD) model enlightened by artificial intelligence to synergize four variables, i.e., amplitude dispersion index (ADI) and damage proxy (DP) map derived from Synthetic Aperture Radar (SAR) images, the change of the normalized difference built-up index (NDBI) derived from optical remote sensing images, as well as peak ground acceleration (PGA). This approach allows us to characterize damage on a large, tectonic scale and a small, individual-building scale. The integration of multiple variables in classifying damage levels into no damage, slight damage, and serious damage (including partial or complete collapses) excels the traditional practice of solely use of DP by 11.25% in performance. Our proposed approach can quantitatively and automatically sort out different building damage levels from publicly available satellite observations, which helps prioritize the rescue mission in response to emergent disasters.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00003-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-28DOI: 10.1038/s44304-024-00001-2
Ziqiang Han, Guochun Wu
Limited studies investigated the reasons for not adopting specific preparedness actions. This paper addresses this gap using national survey data from China. Seven disaster preparedness actions are used to measure preparedness behaviors, including “preparing food and water at home,” “paying attention to disaster-related information,” “making emergency plans,” “being aware of nearest shelters,” “being aware of building codes,” “participating in exercises or drills,” and “volunteering for emergencies.” The primary reasons for not adopting are “lack of awareness,” “not knowing where to buy or reach resources,” and “perceiving the action as unnecessary.” Other less chosen reasons ranking from high to low are the “financial cost,” “need for special knowledge,” “lack of time,” “need for collaboration with others,” “human energy consuming,” and “not feeling responsible.” Trust in government, relocation due to disasters, living in urban areas, and higher socioeconomic status are positively correlated with higher probabilities of adopting all seven preparedness activities. These findings emphasize the importance of community outreach by emergency management professionals to increase public awareness of disaster preparedness.
{"title":"Why do people not prepare for disasters? A national survey from China","authors":"Ziqiang Han, Guochun Wu","doi":"10.1038/s44304-024-00001-2","DOIUrl":"10.1038/s44304-024-00001-2","url":null,"abstract":"Limited studies investigated the reasons for not adopting specific preparedness actions. This paper addresses this gap using national survey data from China. Seven disaster preparedness actions are used to measure preparedness behaviors, including “preparing food and water at home,” “paying attention to disaster-related information,” “making emergency plans,” “being aware of nearest shelters,” “being aware of building codes,” “participating in exercises or drills,” and “volunteering for emergencies.” The primary reasons for not adopting are “lack of awareness,” “not knowing where to buy or reach resources,” and “perceiving the action as unnecessary.” Other less chosen reasons ranking from high to low are the “financial cost,” “need for special knowledge,” “lack of time,” “need for collaboration with others,” “human energy consuming,” and “not feeling responsible.” Trust in government, relocation due to disasters, living in urban areas, and higher socioeconomic status are positively correlated with higher probabilities of adopting all seven preparedness activities. These findings emphasize the importance of community outreach by emergency management professionals to increase public awareness of disaster preparedness.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00001-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139987507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-28DOI: 10.1038/s44304-024-00002-1
Abolfazl Hojjat Ansari, Alfonso Mejia, Raj Cibin
Inland levees can amplify flood risk in unprotected communities by altering floodwater levels away from their location. While these nonlocal effects of levees, which we term flood teleconnections, have been studied for specific river segments, their impact on flood risks along a river network remains underexplored. By combining data-driven, hydrodynamic, and economic models, we quantify the magnitude, spatial distribution, and economic damages associated with flood teleconnections for a large river network system with extensive levees. We find that due to levees, the 100-year flood inundation extent grows by 25% of the total levee-protected area regionally, and the flood inundation depth increases by up to 2 m at specific locations. Levees also increase the vulnerability of unprotected, marginalized communities to flooding. Our results demonstrate that flood teleconnections are spatially widespread, involve unaccounted costs, and can lead to flood inequities. These findings will be critical to climate adaptation efforts in flood-prone regions.
{"title":"Flood teleconnections from levees undermine disaster resilience","authors":"Abolfazl Hojjat Ansari, Alfonso Mejia, Raj Cibin","doi":"10.1038/s44304-024-00002-1","DOIUrl":"10.1038/s44304-024-00002-1","url":null,"abstract":"Inland levees can amplify flood risk in unprotected communities by altering floodwater levels away from their location. While these nonlocal effects of levees, which we term flood teleconnections, have been studied for specific river segments, their impact on flood risks along a river network remains underexplored. By combining data-driven, hydrodynamic, and economic models, we quantify the magnitude, spatial distribution, and economic damages associated with flood teleconnections for a large river network system with extensive levees. We find that due to levees, the 100-year flood inundation extent grows by 25% of the total levee-protected area regionally, and the flood inundation depth increases by up to 2 m at specific locations. Levees also increase the vulnerability of unprotected, marginalized communities to flooding. Our results demonstrate that flood teleconnections are spatially widespread, involve unaccounted costs, and can lead to flood inequities. These findings will be critical to climate adaptation efforts in flood-prone regions.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00002-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139987500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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