Anthropogenic aerosols mask increases in US rainfall by greenhouse gases – Nature Communications

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Report on Human-Induced Changes to Rainfall and the Role of Sustainable Development Goals (SDGs)

Abstract

A comprehensive understanding of human-induced changes to rainfall is essential for water resource management and infrastructure design. However, at regional scales, existing detection and attribution studies are rarely able to conclusively identify human influence on precipitation. This report demonstrates that anthropogenic aerosol and greenhouse gas (GHG) emissions are the primary drivers of precipitation change over the United States. GHG emissions increase mean and extreme precipitation across all seasons, while global aerosol emissions decrease precipitation on a decadal scale. Local aerosol emissions offset GHG increases in winter and spring but enhance rainfall during summer and fall. The conflicting literature on historical precipitation trends can be explained by offsetting aerosol and greenhouse gas signals. Individual climate models reproduce observed changes but cannot confidently determine whether a given anthropogenic agent has increased or decreased rainfall.

Introduction

Daily accumulated precipitation, including extreme events, is a crucial part of the global water cycle. Precipitation is particularly important considering decreases in natural water storage, including snowpack, glaciers, and groundwater. A comprehensive understanding of precipitation change is critical to human systems, including agriculture, water resource management, and infrastructure design. Such knowledge can underpin mitigation policies and adaptation in response to changing risks of natural hazards such as flooding and droughts within a nonstationary global climate.

While anthropogenic influence has been identified for many aspects of the Earth system, robust conclusions regarding human influence on regional precipitation remain difficult to obtain. Existing studies primarily address changes at the global scale, zonal land-averages, or continental-scale averages. Large-scale statements about anthropogenic influence on precipitation are useful but do not provide the information needed to understand local climate change. Attempts to attribute local-scale precipitation trends have proven largely inconclusive even over the continental United States (CONUS) where there are well-documented century-length trends in seasonal mean and extreme precipitation.

Methods

1. Analysis of GHCN in situ records: Utilized measurements from approximately 2500 high-quality weather stations with records dating back to 1900.
2. Comparison with optimal fingerprinting methods: Implemented a two-way regression analysis with single-forcing greenhouse gas-only and anthropogenic aerosol-only experiments.
3. Summarizing the GHCN analysis: Converted statistical attribution coefficients to an effect on precipitation for interpretability and cross-comparison.

Results

• Spatial scales of attribution: fast versus slow response: Detected changes in regional precipitation using a D&A framework across various spatial scales.
• Grid-box attribution for precipitation change: Explored statistical attribution coefficients for GHG, AER-glob, and AER-local forcing at small spatial scales.
• GHG signal emergence masked by aerosols: Assessed anthropogenic influence as a function of time and evaluated the overall trajectories of precipitation change over the last century.

Discussion

The combination of large observational uncertainty, model uncertainty, and internal variability has made it difficult for traditional D&A methods to obtain conclusive statements regarding human influence on regional precipitation change. This study explicitly quantified the composition of forced precipitation changes over the United States by developing and implementing methods that use model simulations offline from observational analysis and simultaneously account for multiple anthropogenic agents. The results provide Granger-causal statements that will serve as a foundation for more traditional Pearl-causal D&A studies.

Our conclusions underscore the importance of considering both century-length records and multiple anthropogenic forcing agents when calculating observed trends and conducting regional D&A analyses. Understanding the relative contributions of individual forcing agents, particularly GHG forcing, is highly useful for characterizing different scenarios of future projections.

Sustainable Development Goals (SDGs)

• SDG 6: Clean Water and Sanitation: Understanding changes in precipitation is critical for managing water resources and ensuring access to clean water.
• SDG 13: Climate Action: Identifying human influences on climate helps in formulating effective climate action policies.
• SDG 15: Life on Land: Changes in precipitation patterns affect ecosystems and biodiversity, necessitating informed conservation strategies.

Data Availability

All global climate data analyzed in this study are available in the Earth System Grid Federation repository. The in situ precipitation records supporting this article are based on publicly available measurements from the National Centers for Environmental Information.

Code Availability

All data analysis was conducted using open-source programming languages and software (R and Python). The primary results utilize functionality from the climextRemes and convoSPAT software packages for R.

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Sustainable Development Goals (SDGs) Analysis

1. Which SDGs are addressed or connected to the issues highlighted in the article?

1. SDG 6: Clean Water and Sanitation
2. SDG 13: Climate Action

2. What specific targets under those SDGs can be identified based on the article’s content?

1. SDG 6: Clean Water and Sanitation
   • Target 6.4: By 2030, substantially increase water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater to address water scarcity and substantially reduce the number of people suffering from water scarcity.
2. SDG 13: Climate Action
   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries.
   • Target 13.2: Integrate climate change measures into national policies, strategies, and planning.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

1. SDG 6: Clean Water and Sanitation
   • Indicator 6.4.1: Change in water-use efficiency over time.
   • Indicator 6.4.2: Level of water stress: freshwater withdrawal as a proportion of available freshwater resources.
2. SDG 13: Climate Action
   • Indicator 13.1.1: Number of deaths, missing persons, and directly affected persons attributed to disasters per 100,000 population.
   • Indicator 13.2.1: Number of countries that have communicated the establishment or operationalization of an integrated policy/strategy/plan which increases their ability to adapt to the adverse impacts of climate change, and foster climate resilience and low greenhouse gas emissions development in a manner that does not threaten food production (including a national adaptation plan, nationally determined contribution, national communication, biennial update report or other).

4. Findings from Analyzing the Article

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Fuente: nature.com

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