Climate Change Attribution Using Empirical Decomposition of Climatic Data (1206.5845v1)

Abstract: The climate change attribution problem is addressed using empirical decomposition. Cycles in solar motion and activity of 60 and 20 years were used to develop an empirical model of Earth temperature variations. The model was fit to the Hadley global temperature data up to 1950 (time period before anthropogenic emissions became the dominant forcing mechanism), and then extrapolated from 1951 to 2009. After subtraction of the model, the residuals showed an approximate linear upward trend after 1942. Herein we assume that the residual upward warming observed during the second half of the 20th century has been mostly induced by a worldwide rapid increase of anthropogenic emissions, urbanization and land use change. The warming observed before 1942 is relatively small and it is assumed to have been mostly naturally induced by a climatic recovery since the Little Ice Age of the 17th century and the Dalton Minimum at the beginning of the 19th century. The resulting full natural plus anthropogenic model fits the entire 160 year record very well. Residual analysis does not provide any evidence for a substantial cooling effect due to sulfate aerosols from 1940 to 1970. The cooling observed during that period may be due to a natural 60-year cycle, which is visible in the global temperature since 1850 and has been observed also in numerous multisecular climatic records. New solar activity proxy models are developed that suggest a mechanism for both the 60-year climate cycle and a portion of the long-term warming trend. Our results suggest that because current models underestimate the strength of natural multidecadal cycles in the temperature records, the anthropogenic contribution to climate change since 1970 should be around half of that previously claimed by the IPCC [2007]. A 21st Century forecast suggests that climate may warm less than 1^{\circ}C by 2100.

An Empirical Approach to Climate Change Attribution

The paper by Loehle and Scafetta (2011), titled Climate Change Attribution Using Empirical Decomposition of Climatic Data, presents a paper focusing on the dissection of Earth’s climate data to address the problem of climate change attribution. By leveraging empirical decomposition, the authors aim to distinguish natural climatic cycles from anthropogenic warming trends within historical temperature records.

The analysis posits that solar activity, manifesting in cycles around 60 and 20 years, plays a notable role in influencing Earth's temperature fluctuations over time. The empirical model suggested by Loehle and Scafetta fits the historical temperature data up to 1950, a period predating substantial anthropogenic influence from greenhouse emissions, and extends this model to assess subsequent years. Key findings indicate an approximate linear upward trend in residuals post-1942, largely attributed to anthropogenic factors such as emissions, urbanization, and land-use changes.

This work challenges prevailing models endorsed by the Intergovernmental Panel on Climate Change (IPCC), which assign high percentages of post-1970 warming to human activities. It highlights the possibility of an understatement of natural cycles in these assessments, suggesting that the anthropogenic contribution could be nearly half of what is typically postulated.

Key Insights and Quantitative Findings

• Empirical Model Fit: The decomposition analysis utilizing solar cycles effectively captures the multidecadal oscillations observed in global temperature records. This results in a model with closer alignment to historical data compared to conventional climate models.
• Residual Analysis: The post-1950 warming trend, when filtered for natural cycles, exhibits a linear increase consistent with anthropogenic influences. Between 1970 and 2000, natural cycles account for approximately 60% of observed warming, underscoring their significance.
• Future Projections: Forecasting climate based on the model suggests a modest rise, less than 1°C by the year 2100, which contradicts the more severe projections by IPCC marked by significant anthropogenic warming trends.

Implications for Climate Science

The implications of this paper are substantial and merit careful consideration within climate research and policymaking contexts:

• Reevaluation of Climate Models: The findings suggest that climate models should incorporate stronger natural cycle influences, potentially leading to revised understandings of climate sensitivity and projections.
• Future Research Directions: Exploring solar activity's influence on climate, especially through improved proxies for total solar irradiance (TSI), could offer refined insights into multidecadal climate variability.
• Policy Decisions: A potential reduction in estimated anthropogenic impacts could influence global climate policy, leading to revised targets and strategies in emissions reduction and climate risk management.

Loehle and Scafetta's work indicates the necessity of a balanced approach in climate change attribution, where natural cycles are accounted for alongside anthropogenic factors. As climate science evolves, such empirical methodologies hold promise in demystifying the various contributing components to global temperature changes, fostering more accurate climate projections and informed policy-making.