Influence Of Anthropogenic Forcing Research Articles

A comparative analysis of the attribution of extreme summer precipitation in south and north parts of the East China monsoon region—with the year 2020 as an example

AbstractIn summer 2020, several watersheds in China monsoon region experienced historically unusually heavy precipitation. The flooding associated with these heavy precipitation events led to devastating impacts on human life, infrastructure, agriculture and economy. Using historical climate simulations from the HadGEM3‐GA6 and CMIP6 models under influences of natural and/or anthropogenic forcings, we conducted a comparative study on the attribution of extremely heavy precipitation events in summer 2020 in the mid‐lower reaches of the Yangtze River and the mid‐lower reaches of the Yellow River‐Hai River Basin which locates respectively in the south and north parts of the East China monsoon region. The potential contributions of anthropogenic forcings to monthly‐scale extreme precipitation and daily maximum precipitation (RX1day) were examined. The results suggest that human activities have decreased the probability of month‐scale extreme precipitation events in the south part of the East China monsoon region. For RX1day extreme precipitation events, anthropogenic factors have increased their probability in both regions. However, the influence of anthropogenic forcings on month‐scale extreme precipitation events in the north part of the East China monsoon region is not robust among the two attribution systems. Further analyses indicated that anthropogenic aerosols (AER) make both month‐scale extreme precipitation events and extreme RX1day less likely to occur in summer 2020, and greenhouse gases (GHG) increase the likelihood of both. GHG influences on Rx1day overwhelm AER influences, leading to an increase of the probability of Rx1day similar to the 2020 events in both regions. In contrast, the decrease in the probability of month‐scale precipitation in the south part of the East China monsoon region is predominantly due to aerosol forcing. The model projections show that the likelihood of both monthly and daily extreme precipitation events in both regions will increase in the future. Accordingly, the recurrence period of extreme precipitation events will be shortened by the end of the 21st century, which is more significant under the high‐emission scenario.

Intensified Likelihood of Concurrent Warm and Dry Months Attributed to Anthropogenic Climate Change

AbstractDetection and attribution studies generally examine individual climate variables such as temperature and precipitation. Thus, we lack a strong understanding of climate change impacts on correlated climate extremes and compound events, which have become more common in recent years. Here we present a monthly‐scale compound warm and dry attribution study, examining CMIP6 climate models with and without the influence of anthropogenic forcing. We show that most regions have experienced large increases in concurrent warm and dry months in historical simulations with human emissions, while no coherent change has occurred in historical natural‐only simulations without human emissions. At the global scale, the likelihood of compound warm‐dry months has increased 2.7 times due to anthropogenic emissions. With this multivariate perspective, we highlight that anthropogenic emissions have not only impacted individual extremes but also compound extremes. Due to amplified risks from multivariate extremes, our results can provide important insights on the risks of associated climate impacts.

Quantifying the Human Influence on the Intensity of Extreme 1- and 5-Day Precipitation Amounts at Global, Continental, and Regional Scales

Abstract This study provides a comprehensive analysis of the human contribution to the observed intensification of precipitation extremes at different spatial scales. We consider the annual maxima of the logarithm of 1-day (Rx1day) and 5-day (Rx5day) precipitation amounts for 1950–2014 over the global land area, four continents, and several regions, and compare observed changes with expected responses to external forcings as simulated by CanESM2 in a large-ensemble experiment and by multiple models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). We use a novel detection and attribution analysis method that is applied directly to station data in the areas considered without prior processing such as gridding, spatial or temporal dimension reduction, or transformation to unitless indices and uses climate models only to obtain estimates of the space–time pattern of extreme precipitation response to external forcing. The influence of anthropogenic forcings on extreme precipitation is detected over the global land area, three continental regions (the western Northern Hemisphere, western Eurasia, and eastern Eurasia), and many smaller IPCC regions, including central North America, East Asia, east-central Asia, eastern Europe, eastern North America, northern Europe, and western Siberia for Rx1day, and central North America, eastern Europe, eastern North America, northern Europe, the Russian Arctic region, and western Siberia for Rx5day. Consistent results are obtained using forcing response estimates from either CanESM2 or CMIP6. Anthropogenic influence is estimated to have substantially decreased the approximate waiting time between extreme annual maximum events in regions where anthropogenic influence has been detected, which has important implications for infrastructure design and climate change adaptation policy. Significance Statement All previous detection and attribution studies of observed changes in extreme precipitation (i) use station data that has been heavily processed via gridding, transformation, and spatial and temporal averaging or other dimension reduction approaches, as well as using climate models to estimate the responses to external forcing, and (ii) also use models to estimate the unforced natural variability of extreme precipitation. Both aspects reduce user confidence in detection and attribution results. This study uses station data directly and avoids difficult to verify model-based estimates of the unforced variability of precipitation extremes. Results confirm findings from previous studies, and extend them to a number of subcontinental regions, thus substantially increasing confidence in detection and attribution findings precipitation.

Recent decreases in domestic energy consumption in the United Kingdom attributed to human influence on the climate

AbstractDomestic energy consumption in the United Kingdom depends on both meteorological and socio‐economic factors. The former are dominated by the effect of temperature during the colder months of the year, with the energy demand increasing as the temperature decreases. Warming of the UK climate under the influence of anthropogenic forcings is therefore expected to lead to a reduction in domestic energy consumption. Here, we present an end‐to‐end attribution study that investigates whether the anthropogenic effect on consumption is already evident in the United Kingdom. We analyse data of gas and electricity use in UK households during 2008–2019 and use a simple linear model to express the temperature dependence. Uncertainties in the resulting transfer functions are derived with a recent methodology, originally introduced for downscaling purposes, but adapted here for use in impact studies. The transfer functions are applied to temperature data from simulations with and without the effect of human influence on the climate, generated by 11 state‐of‐the‐art climate models. We thus assess the anthropogenic impact on energy consumption during the reference period by comparing it with what it might have been in a climate without anthropogenic climate change, but at the same level of adaptation. We find that without human influence on the climate, UK households would consume on average about 1,400 kWh more per year, which would increase the annual energy bills by about 70 GBP. Our attribution assessment provides useful evidence of an impact that has already emerged, which can help inform UK's adaptation plans as the climate continues to warm.

Human Influence on the Increasing Drought Risk Over Southeast Asian Monsoon Region

AbstractSoutheast Asian monsoon region is regularly stricken by drought, but less attention is paid due to its slow‐onset and less visual impact. This study investigated the observed drought changes over Southeast Asian monsoon region and impacts of anthropogenic forcing using the Coupled Model Intercomparison Project Phase 6 models. We revealed an increasing drought risk for 1951–2018 due to more frequent and wide‐spread droughts. The influence of anthropogenic forcing is successfully detected, which has increased the likelihood of the extreme droughts in historical simulation by reducing precipitation and enhancing evapotranspiration. The time of emergence of anthropogenic forcing in extreme drought occurrence and affected area occurs around the 1960s. The future projected severe and extreme drought risks are still beyond natural only forced changes under all scenarios. Our findings demonstrate a robust impact of anthropogenic forcing on drought risk over Southeast Asia, and highlight the importance of future pathway choice.

Detecting human influence on the temperature changes in Central Asia

The ecosystem and societal development in arid Central Asia are highly vulnerable to climate change. During the past five decades, significant warming occurs in Central Asia, but whether the influence of anthropogenic forcing is detectable remains unclear. Therefore, we employ the optimal fingerprinting method to address the question in this study. The observed annual mean temperature (°C) over Central Asia significantly increases by 1.33 from 1961 to 2005, which mainly concentrates in summer (0.90), autumn (1.22), and winter (2.48). The influence of anthropogenic forcing, particularly the greenhouse gases (GHG) forcing, on both the annual and seasonal significant warming trends are robustly detected. GHG increases the annual, summer, autumn, and winter mean temperature (°C) by 1.25 (0.52–2.00), 1.11 (0.32–1.92), 1.11 (0.40–1.83), and 2.50 (0.91–4.34), respectively. Attribution results demonstrate an underestimation (overestimation) of CMIP5 models in simulating the annual and winter (summer and autumn) historical warming trend in Central Asia, implying a potential bias of the future temperature projections reported in IPCC AR5. Thus, we adjust the projections based on the attributed scaling factors, showing that the projected annual, summer, autumn, and winter mean temperature would significantly increase at a rate (°C decade−1) of 0.32 (0.16–0.49), 0.20 (0.06–0.35), 0.24 (0.10–0.38) and 0.58 (0.24–0.93) under RCP4.5, while 0.74 (0.36–1.12), 0.48 (0.14–0.84), 0.58 (0.25–0.91), and 1.25 (0.53–2.02) under RCP8.5, respectively, demonstrating large annual variation. To the end of twenty-first century, the annual (winter) mean temperature (°C) over Central Asia would increase by 7.00 (11.75) under RCP8.5, 0.85 (5.17) higher than the unadjusted results.

Simulation of Daily Extreme Precipitation over the United States in the CMIP5 30-Yr Decadal Prediction Experiment

AbstractThe CMIP5 decadal hindcast (“Hindcast”) and prediction (“Predict”) experiment simulations from 11 models were analyzed for the United States with respect to two metrics of extreme precipitation: the 10-yr return level of daily precipitation, derived from the annual maximum series of daily precipitation, and the total precipitation exceeding the 99.5th percentile of daily precipitation. Both Hindcast simulations and observations generally show increases for the 1981–2010 historical period. The multimodel-mean Hindcast trends are statistically significant for all regions while the observed trends are statistically significant for the Northeast, Southeast, and Midwest regions. An analysis of CMIP5 simulations driven by historical natural (“HistoricalNat”) forcings shows that the Hindcast trends are generally within the 5th–95th-percentile range of HistoricalNat trends, but those outside that range are heavily skewed toward exceedances of the 95th-percentile threshold. Future projections for 2006–35 indicate increases in all regions with respect to 1981–2010. While there is good qualitative agreement between the observations and Hindcast simulations regarding the direction of recent trends, the multimodel-mean trends are similar for all regions, while there is considerable regional variability in observed trends. Furthermore, the HistoricalNat simulations suggest that observed historical trends are a combination of natural variability and anthropogenic forcing. Thus, the influence of anthropogenic forcing on the magnitude of near-term future changes could be temporarily masked by natural variability. However, continued observed increases in extreme precipitation in the first decade (2006–15) of the “future” period partially confirm the Predict results, suggesting that incorporation of increases in planning would appear prudent.

Weakening of annual temperature cycle over the Tibetan Plateau since the 1870s

The annual cycle of extra-tropical surface air temperature is an important component of the Earth’s climate system. Over the past decades, a reduced amplitude of this mode has been observed in some regions. Although attributed to anthropogenic forcing, it remains unclear when dampening of the annual cycle started. Here we use a residual series of tree-ring width and maximum latewood density from the Tibetan Plateau >4,000 m asl to reconstruct changes in temperature seasonality over the past three centuries. The new proxy evidence suggests that the onset of a decrease in summer-to-winter temperature difference over the Tibetan Plateau occurred in the 1870s. Our results imply that the influence of anthropogenic forcing on temperature seasonality might have started in the late nineteenth century, and that future human influence may further contribute to a weakening of the annual temperature cycle, with subsequent effects on ecosystem functioning and productivity.

Causal Influence of Anthropogenic Forcings on the Argentinian Heat Wave of December 2013

Fil: Hannart, Alexis. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmosfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmosfera; Argentina

Attributing northern high-latitude precipitation change over the period 1966–2005 to human influence

Using an optimal fingerprinting method and improved observations, we compare observed and CMIP5 model simulated annual, cold season and warm season (semi-annual) precipitation over northern high-latitude (north of 50°N) land over 1966–2005. We find that the multi-model simulated responses to the effect of anthropogenic forcing or the effect of anthropogenic and natural forcing combined are consistent with observed changes. We also find that the influence of anthropogenic forcing may be separately detected from that of natural forcings, though the effect of natural forcing cannot be robustly detected. This study confirms our early finding that anthropogenic influence in high-latitude precipitation is detectable. However, in contrast with the previous study, the evidence now indicates that the models do not underestimated observed changes. The difference in the latter aspect is most likely due to improvement in the spatial–temporal coverage of the data used in this study, as well as the details of data processing procedures.

Depth‐specific responses of a chironomid assemblage to contrasting anthropogenic pressures: a palaeolimnological perspective from the last 150 years

Summary The specific effects of three types of anthropogenic forcing (nutrient concentrations, climate change and fisheries management practices) on the benthic invertebrate community over the last 150 years in a re‐oligotrophicated large, deep subalpine lake were investigated using chironomid remains. The structural changes in the chironomid assemblages in different habitats were assessed based on sub‐fossil remains retrieved from sediment cores sampled along a depth gradient (30, 56 and 65 m) and analysed at a high temporal resolution (2–5 years). Until the 1940s, the chironomid assemblages were strongly depth specific and were characterised by oxyphilous taxa at all studied depths. Subsequently, the assemblages drifted towards domination by common hypoxia‐tolerant taxa. The scores of the first axis of principal component analyses for each studied depth were used as a proxy for community structure, and the influence of anthropogenic forcings on axis scores was assessed using general additive models. The temporal variability of the contribution of each covariate to our model estimates allowed their specific effects to be clarified. The sensitivity of the chironomid assemblages to the considered forcings was depth dependent. Profundal chironomid assemblages (65 m) responded mainly to nutrient enrichment, whereas assemblages at shallower depths (56 and 30 m) were mainly affected by top‐down effects of the fish community on the pelagic food web, triggering increasing losses of organic matter from the pelagic to the benthic zone. Since the late 1980s, increased air temperatures have probably been responsible for changes in assemblages at all sampled depths, potentially through their effect on the strength and duration of thermal stratification, possibly coupled with changes in mixing efficiency during winter. Our results highlight linkages between the pelagic and benthic food webs and identify possible temporal substitutions among anthropogenic forcings that successively drive the chironomid assemblages. These findings provide additional evidence of the multiple environmental controls structuring chironomid assemblages and highlight the associated difficulties in predicting chironomid assemblage trajectories following mitigation efforts.

Tropical Pacific spatial trend patterns in observed sea level: internal variability and/or anthropogenic signature?

Abstract. In this study we focus on the sea level trend pattern observed by satellite altimetry in the tropical Pacific over the 1993–2009 time span (i.e. 17 yr). Our objective is to investigate whether this 17-yr-long trend pattern was different before the altimetry era, what was its spatio-temporal variability and what have been its main drivers. We try to discriminate the respective roles of the internal variability of the climate system and of external forcing factors, in particular anthropogenic emissions (greenhouse gases and aerosols). On the basis of a 2-D past sea level reconstruction over 1950–2009 (based on a combination of observations and ocean modelling) and multi-century control runs (i.e. with constant, preindustrial external forcing) from eight coupled climate models, we have investigated how the observed 17-yr sea level trend pattern evolved during the last decades and centuries, and try to estimate the characteristic time scales of its variability. For that purpose, we have computed sea level trend patterns over successive 17-yr windows (i.e. the length of the altimetry record), both for the 60-yr long reconstructed sea level and the model runs. We find that the 2-D sea level reconstruction shows spatial trend patterns similar to the one observed during the altimetry era. The pattern appears to have fluctuated with time with a characteristic time scale of the order of 25–30 yr. The same behaviour is found in multi-centennial control runs of the coupled climate models. A similar analysis is performed with 20th century coupled climate model runs with complete external forcing (i.e. solar plus volcanic variability and changes in anthropogenic forcing). Results suggest that in the tropical Pacific, sea level trend fluctuations are dominated by the internal variability of the ocean–atmosphere coupled system. While our analysis cannot rule out any influence of anthropogenic forcing, it concludes that the latter effect in that particular region is stillhardly detectable.

Investigating the Influence of Anthropogenic Forcing on Observed Mean and Extreme Sea Level Pressure Trends over the Mediterranean Region

We investigate whether the observed mean sea level pressure (SLP) trends over the Mediterranean region in the period from 1975 to 2004 are significantly consistent with what 17 models projected as response of SLP to anthropogenic forcing (greenhouse gases and sulphate aerosols, GS). Obtained results indicate that the observed trends in mean SLP cannot be explained by natural (internal) variability. Externally forced changes are detectable in all seasons, except spring. The large-scale component (spatial mean) of the GS signal is detectable in all the 17 models in winter and in 12 of the 17 models in summer. However, the small-scale component (spatial anomalies about the spatial mean) of GS signal is only detectable in winter within 11 of the 17 models. We also show that GS signal has a detectable influence on observed decreasing (increasing) tendency in the frequencies of extremely low (high) SLP days in winter and that these changes cannot be explained by internal climate variability. While the detection of GS forcing is robust in winter and summer, there are striking inconsistencies in autumn, where analysis points to the presence of an external forcing, which is not GS forcing.

Anthropogenic Influence on Long Return Period Daily Temperature Extremes at Regional Scales

Abstract Observed 1961–2000 annual extreme temperatures, namely annual maximum daily maximum (TXx) and minimum (TNx) temperatures and annual minimum daily maximum (TXn) and minimum (TNn) temperatures, are compared with those from climate simulations of multiple model ensembles with historical anthropogenic (ANT) forcing and with combined anthropogenic and natural external forcings (ALL) at both global and regional scales using a technique that allows changes in long return period extreme temperatures to be inferred. Generalized extreme value (GEV) distributions are fitted to the observed extreme temperatures using a time-evolving pattern of location parameters obtained from model-simulated extreme temperatures under ANT or ALL forcing. Evaluation of the parameters of the fitted GEV distributions shows that both ANT and ALL influence can be detected in TNx, TNn, TXn, and TXx at the global scale over the land areas for which there are observations, and also regionally over many large land areas, with detection in more regions in TNx. Therefore, it is concluded that the influence of anthropogenic forcing has had a detectable influence on extreme temperatures that have impacts on human society and natural systems at global and regional scales. External influence is estimated to have resulted in large changes in the likelihood of extreme annual maximum and minimum daily temperatures. Globally, waiting times for extreme annual minimum daily minimum and daily maximum temperature events that were expected to recur once every 20 yr in the 1960s are now estimated to exceed 35 and 30 yr, respectively. In contrast, waiting times for circa 1960s 20-yr extremes of annual maximum daily minimum and daily maximum temperatures are estimated to have decreased to fewer than 10 and 15 yr, respectively.

Observed Strengthening of the Zonal Sea Surface Temperature Gradient across the Equatorial Pacific Ocean*

Abstract Decadal variations of very small amplitude [∼0.3°C in sea surface temperature (SST)] in the tropical Pacific Ocean, the genesis region of the interannual El Niño–Southern Oscillation (ENSO) phenomenon, have been shown to have powerful impacts on global climate. Future projections from different climate models do not agree on how this critical feature will change under the influence of anthropogenic forcing. A number of attempts have been made to resolve this issue by examining observed trends from the 1880s to the present, a period of rising atmospheric concentrations of greenhouse gases. A recent attempt concluded that the three major datasets disagreed on the trend in the equatorial gradient of SST. Using a corrected version of one of these datasets, and extending the analysis to the seasonal cycle, it is shown here that all agree that the equatorial Pacific zonal SST gradient has strengthened from 1880 to 2005 during the boreal fall when this gradient is normally strongest. This result appears to favor a theory for future changes based on ocean dynamics over one based on atmospheric energy considerations. Both theories incorporate the expectation, based on ENSO theory, that the zonal sea level pressure (SLP) gradient in the tropical Pacific is coupled to SST and should therefore strengthen along with the SST gradient. While the SLP gradient has not strengthened, it is found that it appears to have weakened only during boreal spring, consistent with the SST seasonal trends. Most of the coupled models included in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report underestimate the strengthening SST gradient in boreal fall, and show almost no change in the SLP gradient in any season. The observational analyses herein suggest that both theories are at work but with relative strengths that vary seasonally, and that the two theories need not be inconsistent with each other.

On the influence of anthropogenic forcings on changes in the stratospheric mean age

A common feature of stratospheric simulations of the past or future is an increase in tropical upwelling and a decrease in mean age. Possible causes of these changes include (1) increases in tropical sea surface temperatures (SSTs) driven by increases in well‐mixed greenhouse gases (WMGHGs), (2) the direct radiative effect of increases in WMGHGs, and (3) changes in ozone. Here we examine a suite of simulations from the Goddard Earth Observing System chemistry‐climate model (GEOS CCM) to isolate the relative role of these three factors. Our analysis indicates that all three factors cause changes in the mean age, but the relative impact of each factor depends on the time period analyzed. Over the past 30–40 years ozone depletion is the major factor causing the decrease in mean age, with negligible changes due to direct radiative impact of WMGHGs. However, ozone is predicted to recover back to 1970 levels during the next 50–60 years, and this causes an increase in the mean age, whereas the continued increase in SSTs from increased levels of WMGHGs and the direct radiative impact of WMGHGs will still cause a decrease in the mean age. The net impact of these factors will still result in a decreasing mean age although the rate will be smaller than that of the past. The decreases in mean age are primarily caused by increases in upwelling in the tropical lower stratosphere. The increased upwelling from both increased tropical SSTs and polar ozone loss appears to be related to changes in zonal winds and increases in wave activity propagating into the stratosphere. The different contributions of changes in SSTs, WMGHGs, and ozone to the circulation of the stratosphere may help explain the large spread in the rate of change of tropical upwelling seen in previous studies.