Detectable anthropogenic changes in daily-scale circulations driving summer rainfall shifts over eastern China

Wetting in the south while drying in the north during the last few decades constitutes the well-known ‘southern flood–northern drought’ (SFND) precipitation pattern over eastern China. The fingerprint of anthropogenic influence on this dipole pattern of regional precipitation trends has not been confirmed, especially for forced changes in relevant dynamics at the synoptic scale. Using a process-based approach involving model experiments both with and without anthropogenic inputs, it is demonstrated that the occurrences of daily circulation patterns (CPs) governing precipitation over eastern China during 1961–2013 have been altered by human influence. Due to anthropogenic forcing, CPs favoring SFND have become more likely to occur at the expense of CPs unfavorable to SFND. Regression analysis shows that changes recorded in the occurrence of CPs from the factual simulations could explain a large part of the precipitation trends over eastern China. CP frequencies driven by purely natural forcing do not reproduce this dipole pattern nor the inferred magnitude of precipitation trends over eastern China. These results suggest that human influence has played a critical role in shaping the contrasting north–south precipitation trends

Anthropogenic influences on extremely persistent seasonal precipitation in Southern China during May–June 2022

Precipitation in southern China during April–June 2022 was the highest since 1961. Anthropogenic forcing has reduced the probability of 2022-like Rx30day precipitation by about 45% based on CMIP6 simulations

Event attribution of Parnaíba River floods in Northeastern Brazil

The climate modeling techniques of event attribution enable systematic assessments of the extent that anthropogenic climate change may be altering the probability or magnitude of extreme events. In the consecutive years of 2018, 2019, and 2020, rainfalls caused repeated flooding impacts in the lower Parnaíba River in Northeastern Brazil. We studied the effect that alterations in precipitation resulting from human influences on the climate had on the likelihood of flooding using two ensembles of the HadGEM3-GA6 atmospheric model: one driven by both natural and anthropogenic forcings; and the other driven only by natural atmospheric forcings, with anthropogenic changes removed from sea surface temperatures and sea ice patterns. We performed hydrological modeling to base our assessments on the peak annual streamflow. The change in the likelihood of flooding was expressed in terms of the ratio between probabilities of threshold exceedance estimated for each model ensemble. With uncertainty estimates at the 90% confidence level, the median (5% 95%) probability ratio at the threshold for flooding impacts in the historical period (1982–2013) was 1.12 (0.97 1.26), pointing to a marginal contribution of anthropogenic emissions by about 12%. For the 2018, 2019, and 2020 events, the median (5% 95%) probability ratios at the threshold for flooding impacts were higher at 1.25 (1.07 1.46), 1.27 (1.12 1.445), and 1.37 (1.19 1.59), respectively; indicating that precipitation change driven by anthropogenic emissions has contributed to the increase of likelihood of these events by about 30%. However, there are other intricate hydrometeorological and anthropogenic processes undergoing long-term changes that affect the flood hazard in the lower Parnaíba River. Trend and flood frequency analyses performed on observations showed a nonsignificant long-term reduction of annual peak flow, likely due to decreasing precipitation from natural climate variability and increasing evapotranspiration and flow regulation

Anthropogenic influence on 2019 May-June extremely low precipitation in southwestern China

Anthropogenic forcing has likely increased the likelihood of the May–June 2019 severe low precipitation event in southwestern China by approximately 6 (1.4) times based on the HADGEM3-GA6 (CMIP6) simulations

Anthropogenic influences on heavy precipitation during the 2019 extremely wet rainy season in Southern China

Anthropogenic forcings have reduced the likelihood of heavy precipitation in southern China like the 2019 March-July event by about 60

Anthropogenic Influences on 2019 July Precipitation Extremes Over the Mid–Lower Reaches of the Yangtze River

Understanding the driving factors for precipitation extremes matters for adaptation and mitigation measures against the changing hydrometeorological hazards in Yangtze River basin, a habitable area that provides water resources for domestic, farming, and industrial needs. However, the region is naturally subject to major floods linked to monsoonal heavy precipitation during May–September. This study aims to quantify anthropogenic influences on the changing risk of 2-week-long precipitation extremes such as the July 2019 extreme cases, as well as events of shorter durations, over the middle and lower reaches of Yangtze River basin (MLYRB). Precipitation extremes with different durations ranging from 1-day to 14-days maximum precipitation accumulations are investigated. Gridded daily precipitations based on nearly 2,400 meteorological stations across China are used to define maximum accumulated precipitation extremes over the MLYRB in July during 1961–2019. Attribution analysis is conducted by using the Met Office HadGEM3-GA6 modeling system, which comprises two sets of 525-member ensembles for 2019. One is forced with observed sea-surface temperatures (SSTs), sea-ice and all forcings, and the other is forced with preindustrialized SSTs and natural forcings only. The risk ratio between the exceedance probabilities estimated from all-forcing and natural-forcing simulations is calculated to quantify the anthropogenic contribution to the changing risks of the July 2019–like precipitation extremes. The results reveal that anthropogenic warming has reduced the likelihood of 2019-like 14-days heavy precipitation over the mid–lower reaches of the Yangtze River by 20%, but increased that of 2-days extremes by 30%

A cross-national mixed-method study of reality pedagogy

This mixed-methods cross-national study investigated the effectiveness of reality pedagogy (an approach in which teachers become part of students’ activities, practices and rituals) in terms of changes in student perceptions of their learning environment and attitudes towards science. A questionnaire was administered to 142 students in grades 8–10 in the Bronx, New York City and Dresden, Germany. The questionnaire combines learning environment scales from the Constructivist Learning Environment Survey and the What Is Happening In this Class? Questionnaire with attitude scales from the Test of Science-Related Attitudes. Student interviews were used to support questionnaire findings. Quantitative data analyses revealed that reality pedagogy had a greater impact on students in the Bronx than in Dresden, with qualitative data clarifying differences in how reality pedagogy was enacted in each geographic area. Overall, our findings add to the body of evidence concerning the effectiveness of reality pedagogy as an approach to teaching and learning science across a variety of contexts. © 2016 Springer Science+Business Media Dordrech

Anthropogenic influences on the persistent night-time heat wave in summer 2018 over North-East China

Persistent night-time heat waves like the event of summer 2018 in Northeast China are extremely rare (about a one-in-a-500-year event) in the natural world, but now have become about a one-in-60-year event with anthropogenic warming

Was the extended rainy winter of 2018/2019 over the Middle and Lower reaches of the Yangtze River driven by anthropogenic forcing?

Anthropogenic forcing reduced the probability of rainfall amount in the extended rainy winter of 2018/19 over the middle and lower reaches of the Yangtze River, China, by ~19%, but exerted no influence on the excessive rainy days, based on HadGEM3-GA6-N216 ensembles. Instead the natural variability played a large and important role in this event

Attributing human influence on July 2017 Chinese heatwave: the influence of sea-surface temperatures

On 21st-25thJuly 2017 a record breaking heatwave occurred in Central Eastern China affecting nearly half of the national population and causing severe impacts on public health, agriculture and infrastructure. Here, we compare attribution results from two UK Met Office Hadley Centre models, HadGEM3-GA6 and weather@home (HadAM3P driving 50km HadRM3P). Within HadGEM3-GA6 July 2017-like heatwaves were unequaled in the ensemble representing the world without human influences. Such heatwaves became approximately a 1 in 50 year event and increased by a factor of 4.8 (5-95% range of 3.1 to 8.0) in weather@home as a result of human activity. Considering the risk ratio (RR) for the full range of return periods shows a discrepancy at all return times between the two model results. Within weather@home a range of different counterfactual Sea Surface Temperature (SST) patterns were used whereas HadGEM3-GA6 used a single estimate. The global mean difference in SST (between factual and counterfactual simulations) is shown to be related to the Generalised Extreme Value (GEV) location parameter and consequently the RR, especially for return periods less than 50 years. It is suggested that a suitable range of SST patterns are used for future attribution studies to ensure that this source of uncertainty is represented within the simulations and subsequent attribution results. It is shown that the risk change between factual and counterfactual simulations is not purely a simple shift in the distribution (i.e. change in GEV location parameter). For return periods greater than 50 years the GEV shape parameter is found to strongly influence the RR determined with the GEV scale parameter affecting only the most severe events