从人为和自然因素的角度检测和归因北半球地表变暖(1850–2018):数据不足的挑战

IF 3 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Climate Pub Date : 2023-08-28 DOI:10.3390/cli11090179
W. Soon, R. Connolly, M. Connolly, S. Akasofu, S. Baliunas, J. Berglund, A. Bianchini, W. Briggs, C. J. Butler, R. Cionco, M. Crok, A. Elias, V. M. Fedorov, F. Gervais, H. Harde, G. Henry, D. Hoyt, O. Humlum, D. Legates, A. Lupo, S. Maruyama, Patrick D. Moore, M. Ogurtsov, C. ÓhAiseadha, Marcos J. Oliveira, S. Park, S. Qiu, G. Quinn, N. Scafetta, J. Solheim, Jim Steele, L. Szarka, Hiroshi L. Tanaka, M. Taylor, F. Vahrenholt, V. V. Velasco Herrera, Weijia Zhang
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引用次数: 4

摘要

对北半球陆地表面温度(1850–2018)进行了统计分析,试图确定自19世纪中期以来观测到的变暖的主要驱动因素。考虑了两种不同的温度估计——一种是农村和城市的混合(与目前的大多数估计几乎完全一致),另一种是仅农村的估计。农村和城市的混合表明,自1850年以来,长期变暖0.89°C/世纪,而农村仅表明0.55°C/年。这与一种普遍的假设相矛盾,即当前基于温度计的全球温度指数相对不受城市变暖偏差的影响。根据政府间气候变化专门委员会(IPCC)最近的第六次评估报告(AR6)所采用的方法,考虑了三个主要的气候驱动因素:两种自然强迫(太阳和火山)和IPCC AR6建议的“所有人为强迫的组合”时间序列。火山时间序列是IPCC AR6建议的时间序列。对比了两个替代的太阳强迫数据集。一个是IPCC AR6推荐的太阳总辐射量(TSI)时间序列。另一个TSI时间序列显然被IPCC AR6忽略了。研究发现,改变温度估计和/或太阳强迫数据集的选择,会导致对观测到的变暖的主要驱动因素得出截然不同的结论。我们的分析重点是全球表面温度的北半球陆地分量,因为这是数据最丰富的分量。研究表明,更广泛的全球变暖检测和归因问题仍然面临重大挑战:(1)城市化偏差仍然是全球陆地温度数据的一个重大问题;(2) 仍然不清楚文献中的许多TSI时间序列中的哪一个(如果有的话)是对过去TSI的准确估计;(3) 科学界还无法自信地确定1850年以来的变暖主要是人为的、主要是自然的还是某种组合。提出了如何解决这些科学挑战的建议。
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The Detection and Attribution of Northern Hemisphere Land Surface Warming (1850–2018) in Terms of Human and Natural Factors: Challenges of Inadequate Data
A statistical analysis was applied to Northern Hemisphere land surface temperatures (1850–2018) to try to identify the main drivers of the observed warming since the mid-19th century. Two different temperature estimates were considered—a rural and urban blend (that matches almost exactly with most current estimates) and a rural-only estimate. The rural and urban blend indicates a long-term warming of 0.89 °C/century since 1850, while the rural-only indicates 0.55 °C/century. This contradicts a common assumption that current thermometer-based global temperature indices are relatively unaffected by urban warming biases. Three main climatic drivers were considered, following the approaches adopted by the Intergovernmental Panel on Climate Change (IPCC)’s recent 6th Assessment Report (AR6): two natural forcings (solar and volcanic) and the composite “all anthropogenic forcings combined” time series recommended by IPCC AR6. The volcanic time series was that recommended by IPCC AR6. Two alternative solar forcing datasets were contrasted. One was the Total Solar Irradiance (TSI) time series that was recommended by IPCC AR6. The other TSI time series was apparently overlooked by IPCC AR6. It was found that altering the temperature estimate and/or the choice of solar forcing dataset resulted in very different conclusions as to the primary drivers of the observed warming. Our analysis focused on the Northern Hemispheric land component of global surface temperatures since this is the most data-rich component. It reveals that important challenges remain for the broader detection and attribution problem of global warming: (1) urbanization bias remains a substantial problem for the global land temperature data; (2) it is still unclear which (if any) of the many TSI time series in the literature are accurate estimates of past TSI; (3) the scientific community is not yet in a position to confidently establish whether the warming since 1850 is mostly human-caused, mostly natural, or some combination. Suggestions for how these scientific challenges might be resolved are offered.
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来源期刊
Climate
Climate Earth and Planetary Sciences-Atmospheric Science
CiteScore
5.50
自引率
5.40%
发文量
172
审稿时长
11 weeks
期刊介绍: Climate is an independent, international and multi-disciplinary open access journal focusing on climate processes of the earth, covering all scales and involving modelling and observation methods. The scope of Climate includes: Global climate Regional climate Urban climate Multiscale climate Polar climate Tropical climate Climate downscaling Climate process and sensitivity studies Climate dynamics Climate variability (Interseasonal, interannual to decadal) Feedbacks between local, regional, and global climate change Anthropogenic climate change Climate and monsoon Cloud and precipitation predictions Past, present, and projected climate change Hydroclimate.
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