Developing a Global Method for Normalizing Economic Loss from Natural Disasters

Alstadt, Brian Baird; Hanson, Anthony; Nijhuis, A.P.

doi:10.1061/(asce)nh.1527-6996.0000522

Cited by 3 publications

(5 citation statements)

References 23 publications

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“…Other, more sophisticated and granular approaches to the normalization of U.S. weather and climate related disaster losses robustly confirm the aggregate downward trend in losses, once population growth and wealth are properly accounted 6,[18][19][20][21][22] . Hurricane, flood and tornado losses have all decreased as a proportion of GDP on climate time scales, and as these are responsible for the majority of direct losses, so too have aggregate disaster losses.…”

Section: Presentation and Substancementioning

confidence: 74%

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Scientific integrity and U.S. “Billion Dollar Disasters”

Pielke

2024

npj Nat. Hazards

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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.

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Section: Presentation and Substancementioning

confidence: 74%

“…A common approach to disaster normalization adjusts historical losses based on GDP, as a proxy for increasing population and wealth [14][15][16][17][18] . Figure . 3 shows loss per disaster in the NOAA 2023 dataset as a percentage of US GDP (https://fred.stlouisfed.org/series/RGDPNAUSA666NRUG).…”

Section: Presentation and Substancementioning

confidence: 99%

Scientific integrity and U.S. “Billion Dollar Disasters”

Pielke

2024

npj Nat. Hazards

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“…A common approach to disaster normalization adjusts historical losses based on GDP, as a proxy for increasing population and wealth. 33,34,35,36,37 Figure 3 shows loss per disaster in the NOAA 2023 dataset as a percentage of US GDP. 38 According to a simple linear trend, losses per disaster are down by about 80% since 1980, as a proportion of GDP.…”

Section: Presentation and Substancementioning

confidence: 99%

“…Other, more sophisticated and granular approaches to the normalization of U.S. weather and climate related disaster losses robustly confirm the aggregate downward trend in losses, once population growth and wealth are properly accounted. 20,37,39,40,41,42 Hurricane, flood and tornado losses have all decreased as a proportion of GDP on climate time scales, and as these are responsible for the majority of direct losses, so too have aggregate disaster losses.…”

Section: Presentation and Substancementioning

confidence: 99%

Scientific Integrity and U.S. “Billion Dollar Disasters”

Pielke

2024

Preprint

View full text Add to dashboard Cite

For more than two decades, the U.S. National Oceanic and Atmospheric Administration (NOAA) has popularized 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 comprehensively short of meeting these criteria. Thus, public claims promoted by NOAA associated with the dataset and its significance are flawed and 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.

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“…Following Alstadt et al (2022), Hoeppe (2016) and Neumayer and Barthel. (2011), to further prove the relationship between climate risk and corporate green innovation, we use the proportion of economic losses of climate risk to current GDP as an alternative measure of climate risk to test the robustness of the empirical results.…”

Section: Alternative Measurement Of the Explanatory Variablementioning

confidence: 99%

How does climate risk matter for corporate green innovation? Empirical evidence from heavy-polluting listed companies in China

Ling

Gao

2023

Front. Energy Res.

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Chinese heavy-polluting companies have been facing enormous challenges in responding to climate risk and energy transformation. This paper uses panel regression model and investigates the impact of climate risk on corporate green innovation in Chinese heavy-polluting listed companies from 2011 to 2020. The empirical results show that climate risk adversely affects green innovation in heavy-polluting companies, and this effect persists throughout a series of robustness and endogeneity tests. Climate risk may affect corporate green innovation through decreasing R&D investment, lowing resource allocation efficiency and increasing company risk. Climate risk has a greater negative impact on mid-western, state-owned and large-size heavy-polluting companies, but can be mitigated by the development of green finance, digital finance and marketization. These findings may help heavy-polluting companies fully utilize existing resources, policies, and channels for green innovation and mitigate climate risks.

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Developing a Global Method for Normalizing Economic Loss from Natural Disasters

Cited by 3 publications

References 23 publications

Scientific integrity and U.S. “Billion Dollar Disasters”

Scientific integrity and U.S. “Billion Dollar Disasters”

Scientific Integrity and U.S. “Billion Dollar Disasters”

How does climate risk matter for corporate green innovation? Empirical evidence from heavy-polluting listed companies in China

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