scholarly journals Detection of Human Influence on Precipitation Extremes in Asia

2020 ◽  
Vol 33 (12) ◽  
pp. 5293-5304 ◽  
Author(s):  
Siyan Dong ◽  
Ying Sun ◽  
Chao Li
Keyword(s):  
High Latitude ◽  
Extreme Precipitation ◽  
Signal Analysis ◽  
Coupled Model ◽  
Internal Variability ◽  
Precipitation Extremes ◽  
Anthropogenic Influence ◽  
Significance Level ◽  
External Forcings ◽  
Extreme Indices

AbstractThis paper examines the possible influence of external forcings on observed changes in precipitation extremes in the mid-to-high latitudes of Asia during 1958–2012 and attempts to identify particular extreme precipitation indices on which there are better chances to detect the influence of external forcings. We compare a recently compiled dataset of observed extreme indices with those from phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations using an optimal fingerprinting method. We consider six indices that characterize different aspects of extreme precipitation, including annual maximum amount of precipitation falling in 1 day (Rx1day) or 5 days (Rx5day), the total amount of precipitation from the top 5% or top 1% daily amount on wet days, and the fraction of the annual total precipitation from these events. For single-signal analysis, the fingerprints of external forcings including anthropogenic agents are robustly detected in most studied extreme indices over all Asia and for midlatitude Asia but not for high-latitude Asia. For two-signal analysis, anthropogenic influence is detectable in these indices over Asia at 5% or slightly less than 5% significance level, whereas natural influence is not detectable. In high-latitude Asia, anthropogenic influence is detected only in a fractional index, representing a stark contrast to the midlatitude and full Asia results. We find relatively smaller internal variability and thus higher signal-to-noise ratio in the fractional indices when compared with the other ones. Our results point to the need for studying precipitation extreme indices that are less affected by internal variability while still representing the relevant nature of precipitation extremes to improve the possibility of detecting a forced signal if one is present in the data.

Forced modulations of Sahel rainfall at decadal timescale over the 20th Century.

2021 ◽  
Author(s):  
Cassien Diabe Ndiaye ◽  
Juliette Mignot ◽  
Elsa Mohino
Keyword(s):  
North Atlantic Ocean ◽  
Coupled Model ◽  
Internal Variability ◽  
Boreal Summer ◽  
Semiarid Region ◽  
Rainfall Regime ◽  
Anthropogenic Aerosols ◽  
Coupled Models ◽  
External Forcings ◽  
Sahel Precipitation

<p>The semiarid region of the Sahel was marked during the 20<sup>th</sup> Century by significant modulations of its rainfall regime. Part of these modulations has been associated with the internal variability of the climate system, mediated by changes in oceanic sea surface temperature (SST). We show here that the external forcings, and in particular anthropogenic aerosols, might have played a role more important than previously thought in setting these variations. The study is based on the recent simulations performed for CMIP6 with the IPSL-CM6A-LR coupled model. As in most coupled models, the maximum precipitation is limited to the southern Sahel during boreal summer in the IPSL-CM6A-LR model. A novel definition of the Sahel precipitation region is proposed in order to take this bias into account. Our results show that external forcings induce decadal modulations of Sahel precipitation that correlate significantly at 0.6 with the observed precipitations and that the anthropogenic aerosols explain more than 70% of these modulations. These results confirm recent results of CMIP6 highlighting an important role of aerosol forcing for the decadal climate in and around the North Atlantic ocean.</p>

scholarly journals Forced and Unforced Decadal Behavior of the Interhemispheric SST Contrast during the Instrumental Period (1881–2012): Contextualizing the Late 1960s–Early 1970s Shift

2020 ◽  
Vol 33 (9) ◽  
pp. 3487-3509 ◽  
Author(s):  
Andrew R. Friedman ◽  
Gabriele C. Hegerl ◽  
Andrew P. Schurer ◽  
Shih-Yu Lee ◽  
Wenwen Kong ◽  
...  
Keyword(s):  
Coupled Model ◽  
Internal Variability ◽  
Forced Response ◽  
Meridional Overturning Circulation ◽  
Large Magnitude ◽  
Sst Cooling ◽  
Sst Variability ◽  
External Forcings ◽  
Sst Warming ◽  
Instrumental Period

AbstractThe sea surface temperature (SST) contrast between the Northern Hemisphere (NH) and Southern Hemisphere (SH) influences the location of the intertropical convergence zone (ITCZ) and the intensity of the monsoon systems. This study examines the contributions of external forcing and unforced internal variability to the interhemispheric SST contrast in HadSST3 and ERSSTv5 observations, and 10 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) from 1881 to 2012. Using multimodel mean fingerprints, a significant influence of anthropogenic, but not natural, forcing is detected in the interhemispheric SST contrast, with the observed response larger than that of the model mean in ERSSTv5. The forced response consists of asymmetric NH–SH SST cooling from the mid-twentieth century to around 1980, followed by opposite NH–SH SST warming. The remaining best-estimate residual or unforced component is marked by NH–SH SST maxima in the 1930s and mid-1960s, and a rapid NH–SH SST decrease around 1970. Examination of decadal shifts in the observed interhemispheric SST contrast highlights the shift around 1970 as the most prominent from 1881 to 2012. Both NH and SH SST variability contributed to the shift, which appears not to be attributable to external forcings. Most models examined fail to capture such large-magnitude shifts in their control simulations, although some models with high interhemispheric SST variability are able to produce them. Large-magnitude shifts produced by the control simulations feature disparate spatial SST patterns, some of which are consistent with changes typically associated with the Atlantic meridional overturning circulation (AMOC).

scholarly journals Spatio-Temporal Variations in Precipitation Extremes in the Endorheic Hongjian Lake Basin in the Ordos Plateau, China

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1981 ◽  
Author(s):  
Kang Liang
Keyword(s):  
Extreme Precipitation ◽  
Temporal Variations ◽  
Precipitation Extremes ◽  
Lake Basin ◽  
Oscillation Phase ◽  
Ordos Plateau ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Spatio Temporal ◽  
Extreme Indices

Precipitation extremes have important implications for regional water resources and ecological environment in endorheic (landlocked) basins. The Hongjian Lake Basin (HJLB), as the representative inflow area in the Ordos Plateau in China, is suffering from water scarcity and an ecosystem crisis; however, previous studies have paid little attention to changes in precipitation extremes in the HJLB. In this study, we investigated the spatio-temporal variations of the core extreme precipitation indices (i.e., PRCTOT, R99p, Rx1day, Rx5day, SDII, R1, R10, CWD, and CDD) recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI), and analyzed the climatic dry–wet regime indicated by these extreme indices during 1960–2014 in the HJLB. The results show that the nine extreme indices had large differences in temporal and spatial variation characteristics. All the nine extreme precipitation indices showed a large fluctuation, both in the whole period and in the three detected different sub-periods, with variation magnitudes of 13%–52%. Most extreme indices had non-significant downward trends, while only the consecutive wet days (CWD) had a significant upward trend. The eight extreme wet indices increased from northwest to southeast, while the consecutive dry days (CDD) had the opposite change direction. Each index had a different trend with different spatial distribution locations and areas. The nine extreme indices revealed that the climate in the HJLB has become a drought since the early 1980s. This was specifically indicated by all four extreme precipitation quantity indices (PRCTOT, R99p, Rx1day, Rx5day) and the extreme intensity index (SDII) declining, as well as the number of heavy precipitation days (R10) decreasing. When the dry–wet variations was divided into the different sub-periods, the climatic dry–wet changes of each index demonstrated more inconsistency and complexity, but most indices in the first sub-period from 1960 to the late 1970s could be regarded as a wet high-oscillation phase, the second sub-period after the early 1980s was a relatively dry low-oscillation phase, and the third sub-period after the late 1990s or early 21st century was a dry medium-oscillation phase. It is worth noting that most extreme indices had an obvious positive linear trend in the third sub-period, which means that in the last 20 years, the precipitation extremes showed an increasing trend. This study could provide a certain scientific reference for regional climate change detection, water resources management, and disaster prevention in the HJLB and similar endorheic basins or inland arid regions.

scholarly journals Attribution of Extreme Precipitation with Updated Observations and CMIP6 Simulations

2021 ◽  
Vol 34 (3) ◽  
pp. 871-881
Author(s):  
Siyan Dong ◽  
Ying Sun ◽  
Chao Li ◽  
Xuebin Zhang ◽  
Seung-Ki Min ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Coupled Model ◽  
Historical Period ◽  
Anthropogenic Aerosols ◽  
Detection And Attribution ◽  
Attribution Analysis ◽  
Group I ◽  
Annual Total ◽  
Intercomparison Project ◽  
Extreme Indices

AbstractWhile the IPCC Fifth Assessment Working Group I report assessed observed changes in extreme precipitation on the basis of both absolute and percentile-based extreme indices, human influence on extreme precipitation has rarely been evaluated on the basis of percentile-based extreme indices. Here we conduct a formal detection and attribution analysis on changes in four percentile-based precipitation extreme indices. The indices include annual precipitation totals from days with precipitation exceeding the 99th and 95th percentiles of wet-day precipitation in 1961–90 (R99p and R95p) and their contributions to annual total precipitation (R99pTOT and R95pTOT). We compare these indices from a set of newly compiled observations during 1951–2014 with simulations from models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). We show that most land areas with observations experienced increases in these extreme indices with global warming during the historical period 1951–2014. The new CMIP6 models are able to reproduce these overall increases, although with considerable over- or underestimations in some regions. An optimal fingerprinting analysis reveals detectable anthropogenic signals in the observations of these indices averaged over the globe and over most continents. Furthermore, signals of greenhouse gases can be separately detected, taking other forcing into account, over the globe and over Asia in these indices except for R95p. In contrast, signals of anthropogenic aerosols and natural forcings cannot be detected in any of these indices at either global or continental scales.

Anthropogenic and Natural Contributions to the Lengthening of the Southern Hemisphere Summer Season

2020 ◽  
Vol 33 (24) ◽  
pp. 10539-10553
Author(s):  
Evan Weller ◽  
Bo-Joung Park ◽  
Seung-Ki Min
Keyword(s):  
Greenhouse Gas ◽  
Southern Hemisphere ◽  
Dominant Role ◽  
Coupled Model ◽  
Internal Variability ◽  
Southern Annular Mode ◽  
Summer Season ◽  
External Forcings ◽  
Regional Trends

AbstractThis study provides the first quantitative assessment of observed long-term changes in summer-season timing and length in the Southern Hemisphere (SH) and its subregions over the past 60 years, enabling a global completeness by complementing such characteristics previously reported for the Northern Hemisphere (NH). Using an objective algorithm that is based on temperature indices, relative measures of summer onset, withdrawal, and duration are determined at each land location over the period 1953–2012. Significant widespread summer-season lengthening, due to earlier onset and delayed withdrawal, has occurred across the SH, a longer period for extreme heat-wave events and wildfires to potentially occur. The asymmetric magnitude (onset vs withdrawal) in summer-season lengthening is slightly less over the SH than over the NH. Contributions of anthropogenic and natural factors to the observed trends in summer-season characteristics were investigated using phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel simulations integrated with observed external forcings [anthropogenic plus natural (ALL)], greenhouse gas forcing only (GHG), and natural forcing only [solar and volcanic activities (NAT)]. Overall, consistent with the NH, increased greenhouse gases were the main cause of observed changes in the SH, with negligible contribution from other external forcings. ALL and GHG simulations also reproduced a slight tendency for earlier summer onset to contribute more to summer lengthening. Proportions of observed regional trends in summer-season indices attributable to trends in long-term internal variability in the SH, namely, the interdecadal Pacific oscillation (IPO) and southern annular mode (SAM), suggests such variability can only explain up to ~12%, supporting the dominant role of greenhouse gas forcing.

scholarly journals Evaluation and Future Projection of Chinese Precipitation Extremes Using Large Ensemble High-Resolution Climate Simulations

2019 ◽  
Vol 32 (8) ◽  
pp. 2169-2183 ◽  
Author(s):  
Weili Duan ◽  
Naota Hanasaki ◽  
Hideo Shiogama ◽  
Yaning Chen ◽  
Shan Zou ◽  
...  
Keyword(s):  
High Resolution ◽  
General Circulation ◽  
Southern China ◽  
Coupled Model ◽  
Circulation Model ◽  
Internal Variability ◽  
Precipitation Extremes ◽  
Large Ensemble ◽  
Extreme Precipitation Events ◽  
The Difference

AbstractEvaluation of Chinese precipitation extremes is conducted based on large ensemble projections of the present climate and 4-K-warmer climates derived from a high-resolution atmospheric general circulation model. The model reproduced the overall trend and magnitude of total precipitation and extreme precipitation events for China reasonably well, revealing that this dataset can represent localized precipitation extremes. Precipitation extremes are more frequent and more severe in future projections under 4-K-warmer climates than in the representative concentration pathway 8.5 (RCP8.5) scenario of phase 5 of the Coupled Model Intercomparison Project (CMIP5). Our results show that using a large-ensemble simulation can improve the ability to estimate with high precision both the precipitation mean and the precipitation extremes compared with small numbers of simulations, and the averaged maximum yearly precipitation will be likely to increase by approximately 18% under a +4-K future in southern China compared with the past. Finally, uncertainty evaluation in future precipitation projections indicates that the component caused by the difference in six ΔSST patterns is more important in southern China compared with the component due to the atmospheric internal variability. All these results could provide valuable insights in simulating and predicting precipitation extremes in China.

scholarly journals Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 797 ◽  
Author(s):  
Asher Samuel Bhatti ◽  
Guojie Wang ◽  
Waheed Ullah ◽  
Safi Ullah ◽  
Daniel Fiifi Tawia Hagan ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Temporal Trend ◽  
Daily Precipitation ◽  
Heavy Precipitation ◽  
Precipitation Extremes ◽  
Study Region ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Extreme Indices

Assessing the long-term precipitation changes is of utmost importance for understanding the impact of climate change. This study investigated the variability of extreme precipitation events over Pakistan on the basis of daily precipitation data from 51 weather stations from 1980-2016. The non-parametric Mann–Kendall, Sen’s slope estimator, least squares method, and two-tailed simple t-test methods were used to assess the trend in eight precipitation extreme indices. These indices were wet days (R1 ≥1 mm), heavy precipitation days (R10 ≥ 10 mm), very heavy precipitation days (R20 ≥ 20 mm), severe precipitation (R50 ≥ 50 mm), very wet days (R95p) defining daily precipitation ≥ 95 percentile, extremely wet days (R99p) defining daily precipitation ≥ 99 percentile, annual total precipitation in wet days (PRCPTOT), and mean precipitation amount on wet days as simple daily intensity index (SDII). The study is unique in terms of using high stations’ density, extended temporal coverage, advanced statistical techniques, and additional extreme indices. Furthermore, this study is the first of its kind to detect abrupt changes in the temporal trend of precipitation extremes over Pakistan. The results showed that the spatial distribution of trends in different precipitation extreme indices over the study region increased as a whole; however, the monsoon and westerlies humid regions experienced a decreasing trend of extreme precipitation indices during the study period. The results of the sequential Mann–Kendall (SqMK) test showed that all precipitation extremes exhibited abrupt dynamic changes in temporal trend during the study period; however, the most frequent mutation points with increasing tendency were observed during 2011 and onward. The results further illustrated that the linear trend of all extreme indices showed an increasing tendency from 1980- 2016. Similarly, for elevation, most of the precipitation extremes showed an inverse relationship, suggesting a decrease of precipitation along the latitudinal extent of the country. The spatiotemporal variations in precipitation extremes give a possible indication of the ongoing phenomena of climate change and variability that modified the precipitation regime of Pakistan. On the basis of the current findings, the study recommends that future studies focus on underlying physical and natural drivers of precipitation variability over the study region.

scholarly journals Slow Modes of Global Temperature Variability and Their Impact on Climate Sensitivity Estimates

2021 ◽  
pp. 1-68
Author(s):  
Robert C. J. Wills ◽  
Kyle C. Armour ◽  
David S. Battisti ◽  
Cristian Proistosescu ◽  
Luke A. Parsons
Keyword(s):  
Climate Sensitivity ◽  
Energy Budget ◽  
High Latitude ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Coupled Model ◽  
Internal Variability ◽  
Minimal Impact ◽  
Radiative Feedback ◽  
The Impact

AbstractInternal climate variability confounds estimates of the climate response to forcing but offers an opportunity to examine the dynamics controlling Earth’s energy budget. This study analyzes the time-evolving impact of modes of low-frequency internal variability on global-mean surface temperature (GMST) and top-of-atmosphere (TOA) radiation in pre-industrial control simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6). The results show that the slow modes of variability with the largest impact on decadal GMST anomalies are focused in high-latitude ocean regions, where they have a minimal impact on global TOA radiation. When these regions warm, positive shortwave cloud and sea ice-albedo feedbacks largely cancel the negative feedback of outgoing longwave radiation, resulting in a weak net radiative feedback. As a consequence of the weak net radiative feedback, less energy is required to sustain these long-lived temperature anomalies. In contrast to these weakly radiating high-latitude modes, the El Niño-Southern Oscillation (ENSO) has a large impact on the global energy budget, such that it remains the dominant influence on global TOA radiation out to decadal and longer timescales, despite its primarily interannual timescale. These results show that on decadal and longer timescales, different processes control internal variability in GMST than control internal variability in global TOA radiation. The results are used to quantify the impact of low-frequency internal variability and ENSO on estimates of climate sensitivity from historical GMST and TOA-radiative-imbalance anomalies.

scholarly journals Quantifying the human influence on the intensity of extreme 1- and 5-day precipitation amounts at global, continental, and regional scales

2021 ◽  
pp. 1-51
Author(s):  
Qiaohong Sun ◽  
Francis Zwiers ◽  
Xuebin Zhang ◽  
Jun Yan
Keyword(s):  
North America ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Spatial Scales ◽  
Coupled Model ◽  
Anthropogenic Influence ◽  
Land Area ◽  
Temporal Dimension ◽  
Time Pattern ◽  
Global Land

AbstractThis 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 (western Northern Hemisphere, western Eurasia and eastern Eurasia), and many smaller IPCC regions, including C. North-America, E. Asia, E.C. Asia, E. Europe, E. North-America, N. Europe, and W. Siberia for Rx1day, and C. North-America, E. Europe, E. North-America, N. Europe, Russian-Arctic, and W. 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.

scholarly journals Climate Drift in the CMIP5 Models*

2013 ◽  
Vol 26 (21) ◽  
pp. 8597-8615 ◽  
Author(s):  
Alexander Sen Gupta ◽  
Nicolas C. Jourdain ◽  
Jaclyn N. Brown ◽  
Didier Monselesan
Keyword(s):  
Climate Models ◽  
Coupled Model ◽  
Deep Ocean ◽  
Internal Variability ◽  
Correction Method ◽  
Physical Models ◽  
Cmip5 Models ◽  
Steric Sea Level ◽  
Biogeochemical Models ◽  
The Difference

Abstract Climate models often exhibit spurious long-term changes independent of either internal variability or changes to external forcing. Such changes, referred to as model “drift,” may distort the estimate of forced change in transient climate simulations. The importance of drift is examined in comparison to historical trends over recent decades in the Coupled Model Intercomparison Project (CMIP). Comparison based on a selection of metrics suggests a significant overall reduction in the magnitude of drift from phase 3 of CMIP (CMIP3) to phase 5 of CMIP (CMIP5). The direction of both ocean and atmospheric drift is systematically biased in some models introducing statistically significant drift in globally averaged metrics. Nevertheless, for most models globally averaged drift remains weak compared to the associated forced trends and is often smaller than the difference between trends derived from different ensemble members or the error introduced by the aliasing of natural variability. An exception to this is metrics that include the deep ocean (e.g., steric sea level) where drift can dominate in forced simulations. In such circumstances drift must be corrected for using information from concurrent control experiments. Many CMIP5 models now include ocean biogeochemistry. Like physical models, biogeochemical models generally undergo long spinup integrations to minimize drift. Nevertheless, based on a limited subset of models, it is found that drift is an important consideration and must be accounted for. For properties or regions where drift is important, the drift correction method must be carefully considered. The use of a drift estimate based on the full control time series is recommended to minimize the contamination of the drift estimate by internal variability.

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