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Seung-Ki Min and Andreas Hense

Abstract

A Bayesian approach is applied to the observed regional and seasonal surface air temperature (SAT) changes using single-model ensembles (SMEs) with the ECHO-G model and multimodel ensembles (MMEs) of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) simulations. Bayesian decision classifies observations into the most probable scenario out of six available scenarios: control (CTL), natural forcing (N), anthropogenic forcing (ANTHRO), greenhouse gas (G), sulfate aerosols (S), and natural plus anthropogenic forcing (ALL). Space–time vectors of the detection variable are constructed for six continental regions (North America, South America, Asia, Africa, Australia, and Europe) by combining temporal components of SATs (expressed as Legendre coefficients) from two or three subregions of each continental region.

Bayesian decision results show that over most of the regions observed SATs are classified into ALL or ANTHRO scenarios for the whole twentieth century and its second half. Natural forcing and ALL scenarios are decided during the first half of the twentieth century, but only in the low-latitude region (Africa and South America), which might be related to response patterns to solar forcing. Overall seasonal decisions follow annual results, but there are notable seasonal dependences that differ between regions. A comparison of SME and MME results demonstrates that the Bayesian decisions for regional-scale SATs are largely robust to intermodel uncertainties as well as prior probability and temporal scales, as found in the global results.

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Seungmok Paik and Seung-Ki Min

Abstract

This study analyzes extreme temperature and precipitation responses over the global land to five explosive tropical volcanic eruptions that occurred since the 1880s, using CMIP5 multimodel simulations. Changes in annual extreme indices during posteruption years are examined using a composite analysis. First, a robust global decrease in extreme temperature is found, which is stronger than the internal variability ranges (estimated from random bootstrap sampling). Intermodel correlation analysis shows a close relationship between annual extreme and mean temperature responses to volcanic forcing, indicating a similar mechanism at work. The cooling responses exhibit strong intermodel correlation with a decrease in surface humidity, consistent with the Clausius–Clapeyron relation. Second, extreme and mean precipitation reductions are observed during posteruption years, especially in Northern and Southern Hemisphere summer monsoon regions, with good intermodel agreement. The precipitation decreases are also larger than the internal variability ranges and are dominated by the monsoon regions. Moisture budget analysis further reveals that most of the precipitation decrease over the monsoon regions is explained by evaporation decrease, as well as dynamic and thermodynamic contributions. Interestingly, the dynamic effect is found to have a large influence on intermodel spread in precipitation responses, with high intermodel correlation with mean and extreme precipitation changes. These model-based results are largely supported by an observational analysis based on the Hadley Centre Global Climate Extremes Index 2 (HadEX2) dataset for the recent three volcanic eruptions. Our results demonstrate that temperature and precipitation extremes significantly respond to volcanic eruptions, largely resembling mean climate responses, which have important implications for geoengineering based on solar radiation management.

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Seungmok Paik and Seung-Ki Min

Abstract

This study conducts a detection and attribution analysis of the observed changes in boreal spring snow-cover extent (SCE) for an extended period of 1925–2019 for early spring (March and April) and 1970–2019 for late spring (May and June) using updated observations and multimodel simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6). The observed and simulated SCE changes over the Northern Hemisphere (NH), Eurasia, and North America are compared using an optimal fingerprinting technique. Detection results indicate that anthropogenic influences are robustly detected in the observed SCE decrease over NH and the continental regions, in separation from natural forcing influences. In contrast to previous studies, anthropogenic response in the early spring SCE shows a consistent magnitude with observations, due to an extension of the time period to 2019. It is demonstrated for the first time that the greenhouse gas (GHG) influence is robustly detected in separation from anthropogenic aerosol and natural forcing influences, and that most of the observed spring SCE decrease is attributable to GHG influences. The observed SCE decline is also found to be closely associated with the surface warming over the corresponding extratropical lands. Our first quantification of GHG contribution to the observed SCE changes has important implications for reliable future projections of the SCE changes and its hydrological and ecological impacts.

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Seung-Ki Min and Andreas Hense

Abstract

A Bayesian approach is applied to the observed global surface air temperature (SAT) changes using multimodel ensembles (MMEs) of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) simulations and single-model ensembles (SMEs) with the ECHO-G coupled climate model. A Bayesian decision method is used as a tool for classifying observations into given scenarios (or hypotheses). The prior probability of the scenarios, which represents a degree of subjective belief in the scenarios, is changed into the posterior probability through the likelihood where observations enter, and the posterior is used as a decision function. In the identical prior case the Bayes factor (or likelihood ratio) becomes a decision function and provides observational evidence for each scenario against a predefined reference scenario. Four scenarios are used to explain observed SAT changes: “CTL” (control or no change), “Nat” (natural forcing induced change), “GHG” (greenhouse gas–induced change), and “All” (natural plus anthropogenic forcing–induced change). Observed and simulated global mean SATs are decomposed into temporal components of overall mean, linear trend, and decadal variabilities through Legendre series expansions, coefficients of which are used as detection variables. Parameters (means and covariance matrices) needed to define the four scenarios are estimated from SMEs or MMEs. Taking the CTL scenario as reference one, application results for global mean SAT changes for the whole twentieth century (1900–99) show “decisive” evidence (logarithm of Bayes factor >5) for the All scenario only. While “strong” evidence (log of Bayes factor >2.5) for both the Nat and All scenarios are found in SAT changes for the first half (1900–49), there is decisive evidence for the All scenario for SAT changes in the second half (1950–99), supporting previous results. It is demonstrated that the Bayesian decision results for global mean SATs are largely insensitive to both intermodel uncertainties and prior probabilities.

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Sang-Min Lee and Seung-Ki Min

Abstract

This study provides a first quantification of possible benefits of global warming mitigation through heat stress reduction over East Asia by comparing projection results between low-emission and high-emission scenarios, as well as between 1.5° and 2.0°C target temperature conditions. Future changes in summer heat stress over East Asia were examined based on the wet-bulb globe temperature (WBGT) using CMIP5 multimodel simulations. Changes in the intensity, frequency, and duration of heat stress were analyzed in terms of area fraction across RCP2.6, RCP4.5, and RCP8.5 scenarios and also between two selected model groups representing 1.5°- and 2.0°C-warmer worlds. Severe heat stress, exceeding the 50-yr return value of the present-day period, is expected to become very frequent, occurring every second year over the large part of East Asia by the 2040s, irrespective of RCP scenarios. The frequency of extreme daily heat stress events is predicted to increase in a similar speed of expansion, with signals emerging from the low latitudes. The WBGT signal emergence is found to be much faster than that of corresponding temperature alone due to the smaller variability in WBGT, supporting previous findings. The 1.5°C-warmer world would have about 20% reduction in areas experiencing severe heat stress over East Asia, compared to the 2.0°C-warmer world, with significant changes identified over the low latitudes. Further, compared to the transient world, the equilibrium world exhibits larger increases in heat stress over East Asia, likely due to the warmer ocean surface in the northwestern North Pacific. This suggests an important role of ocean warming patterns in the regional assessment of global warming mitigation.

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In-Hong Park and Seung-Ki Min

Abstract

On a subdaily time scale, the intensities of extreme precipitation are observed to increase with temperature at a rate exceeding water vapor constraints determined by the Clausius–Clapeyron (C-C) relationship. This so-called super C-C scaling has been suggested to occur as a result of 1) the statistical effect that involves the transition of precipitation types from stratiform to convective events and 2) the physical effect by which the convective process itself can overcome the thermodynamic limitation. This study examines these two mechanisms for the super C-C relationship using in situ observations in South Korea for a recent 35-yr period, focusing on the role of convective rainfall. Scaling results show that hourly extreme precipitation undergoes a transition from a C-C rate to a super C-C rate at around 20°C, supporting the statistical effect. The transition temperature observed in South Korea is, however, much higher than in European regions (12°C), which seems to be due to the climatologically lower frequency of convective events in South Korea than in Europe. Nevertheless, the threshold fraction of convective precipitation when the scaling transition starts to occur is found to very similar between two regions, around 0.2, indicating the important role of convective events in shaping the scaling. On the other hand, convective extreme precipitation alone exhibits a super C-C scaling, suggesting that the physical effect is also at work in South Korea. Also, the scaling shows a robust peaklike shape with maximum precipitation intensity near 24°C, which is closely linked with moisture limitation at high temperature, supporting the previous findings.

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Jonghun Kam, Seung-Ki Min, Piotr Wolski, and Jong-Seong Kug
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Seok-Woo Son, Seo-Yeon Kim, and Seung-Ki Min

Abstract

The Hadley cell (HC) change from paleoclimate to future climate is examined by comparing coupled model simulations archived for the Paleoclimate Modeling Intercomparison Project phase 3 (PMIP3) and phase 5 of the Coupled Model Intercomparison Project (CMIP5). Specifically, HC width and strength are evaluated using 100-yr equilibrium simulations for the Last Glacial Maximum (LGM), preindustrial (PI), and extended concentration pathway 4.5 (ECP4.5) conditions. Where available, ECP8.5 simulations are also examined to increase the sample size. All models show a systematic widening of the HC from the LGM to the PI and to the ECP4.5 and ECP8.5 simulations. Such widening, which is found in both hemispheres with more robust change in the Southern Hemisphere (SH) than in the Northern Hemisphere (NH), is significantly correlated with global-mean surface air temperature change and the associated static stability change in the subtropics. Based on the zero-crossing latitude of 500-hPa mass streamfunction, about 4.5° latitude widening of the HC results from global warming of 10°C. HC strength also exhibits a systematic weakening in the NH. However, in the SH, HC strength shows a rather minor change from LGM to ECP4.5 conditions because of the cancellation between HC weakening during the austral summer–fall and its strengthening during the spring. This result, which suggests no systematic relationship between HC width and strength changes, is discussed in the context of quasigeostrophic zonal-mean dynamics. Overall findings are also compared with recent studies that are based on transient climate model simulations.

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Evan Weller, Bo-Joung Park, and Seung-Ki Min

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This 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.

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Ariaan Purich, Tim Cowan, Seung-Ki Min, and Wenju Cai

Abstract

In recent decades, Southern Hemisphere midlatitude regions such as southern Africa, southeastern Australia, and southern Chile have experienced a reduction in austral autumn precipitation; the cause of which is poorly understood. This study focuses on the ability of global climate models that form part of the Coupled Model Intercomparison Project phase 5 to simulate these trends, their relationship with extratropical and subtropical processes, and implications for future precipitation changes. Models underestimate both the historical autumn poleward expansion of the subtropical dry zone and the positive southern annular mode (SAM) trend. The multimodel ensemble (MME) is also unable to capture the spatial pattern of observed precipitation trends across semiarid midlatitude regions. However, in temperate regions that are located farther poleward such as southern Chile, the MME simulates observed precipitation declines. The MME shows a strong consensus in twenty-first-century declines in autumn precipitation across southern Chile in both the medium–low and high representative concentration pathway (RCP) scenarios and across southern Africa in the high RCP scenario, but little change across southeastern Australia. Projecting a strong positive SAM trend and continued subtropical dry-zone expansion, the models converge on large SAM and dry-zone-expansion-induced precipitation declines across southern midlatitudes. In these regions, the strength of future precipitation trends is proportional to the strength of modeled trends in these phenomena, suggesting that unabated greenhouse gas–induced climate change will have a large impact on austral autumn precipitation in such midlatitude regions.

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