Potential National Income Loss: Difference between revisions

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'''The dataset is explained in details here:''' https://drive.google.com/file/d/1jhCuZr-1bdh3AafpuxNPIMKIbEQKCH-z/view?usp=drive_link
'''Access the complete dataset here:''' https://drive.google.com/file/d/1glmwSUu2u_q4XLOXL7eMxuCQxsAxWMHA/view?usp=drive_link
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'''Access the complete dataset here:''' https://drive.google.com/file/d/14eseGYDiRcC5vmV3gFRR_zb0QlIH0bJz/view?usp=drive_link
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Revision as of 08:47, 11 December 2023

The term "Potential National Income Loss from Chronic Climate Damages" refers to an estimation or projection of the economic impact a country might face due to persistent or ongoing climate-related damages over a certain period.

This metric attempts to quantify the potential economic loss a nation could experience as a result of the long-term effects of climate change, including:

1. Chronic Climate Damages: These damages encompass various adverse effects caused by climate change over an extended period. This can include but is not limited to:

- Sea-level rise impacting coastal areas.
- Increased frequency and severity of extreme weather events (such as storms, floods, droughts, and heatwaves).
- Loss of agricultural productivity due to changes in temperature, rainfall patterns, and soil moisture.
- Negative impacts on infrastructure, health, ecosystems, and livelihoods.

2. National Income Loss: It refers to the reduction in a country's overall income or economic output due to the chronic damages caused by climate change. This loss can result from decreased productivity in sectors like agriculture, increased costs associated with recovery and adaptation measures, reduced tourism revenues, and other economic consequences stemming from climate-related impacts.

Estimating potential national income loss from chronic climate damages involves complex modeling and analysis of various factors affected by climate change. It's used as a projection to highlight the potential economic risks and encourage policymakers, governments, and stakeholders to take proactive measures to mitigate climate change impacts, adapt to changing conditions, and invest in resilience strategies to minimize economic losses.

National Income Loss Dataset

This dataset serves as a critical resource for understanding the threats to biodiversity, highlighting species at risk of extinction, and guiding conservation efforts worldwide. It enables researchers, conservationists, policymakers, and the general public to access and analyze data crucial for prioritizing conservation actions, identifying regions of high biodiversity significance, and tracking changes in species' statuses over time.

This dataset appears to contain projections or simulated data related to climate change impacts, specifically assessing potential damages or effects on the United States under different scenarios and percentiles. Here's an explanation of the columns:

Country: The country being analyzed or evaluated, which in this case is the United States.

Model: It likely refers to the climate model or simulation tool used to generate these projections.

Scenario: This column specifies the scenario being considered. For example, "Below 2°C," indicates scenarios where efforts are made to limit global warming to below a 2-degree Celsius increase compared to pre-industrial levels.

Damage: This could represent the level or extent of damage or impact being assessed. It's categorized as "High" or "Median," likely representing different severity levels or estimates of damages.

Percentile: This column indicates different percentiles, probably representing different levels of certainty or probability associated with the projected damages. The values 5, 50, and 95 typically correspond to low, median, and high percentiles in a statistical context.

Years (2020-2100): These columns contain the projected or simulated data for the years 2020 through 2100. The numerical values seem to represent the estimated damages or impacts under the specified scenario, model, damage level, and percentile for each year.

Plot showing prediction in Losses due to climate risks from 2020 to 2100

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Access the complete dataset here: https://drive.google.com/file/d/1glmwSUu2u_q4XLOXL7eMxuCQxsAxWMHA/view?usp=drive_link