민승기 교수

This study evaluates global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) for their performance in simulating the climate extreme indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). We compare global climatology patterns of the indices simulated by the CMIP6 models with those from HadEX3 and four reanalysis datasets and the CMIP5 multi-model ensemble using root-mean-square errors for the 1981–2000 period. Regional evalu

The Arctic and northern subpolar regions are critical for climate change. Ice-albedo feedback amplifies warming in the Arctic, and fluctuations of regional fresh water inflow to the Arctic Ocean modulate the deep ocean circulation and thus exert a strong global influence. By comparing observations to simulations from 22 coupled climate models, we find influence from anthropogenic greenhouse gases and sulfate aerosols in the space-time pattern of precipitation change over high-latitude land areas

The sixth assessment report of the IPCC assessed that the Arctic is projected to be on average practically ice-free in September near mid-century under intermediate and high greenhouse gas emissions scenarios, though not under low emissions scenarios, based on simulations from the latest generation Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Here we show, using an attribution analysis approach, that a dominant influence of greenhouse gas increases on Arctic sea ice area is dete

Abstract To investigate the spatial and temporal relationships of drought occurrence and intensity between Korea and East Asia, the Standardized Precipitation Index (SPI), calculated from Climatic Research Unit (CRU) monthly precipitation data, was used from 1951 to 1996. It is found that the frequency of occurrence of droughts in Korea has significant time intervals of 2–3 and 5–8 years and has been increasing since the 1980s. Correlation and composite analyses showed that the occurrence of dro

It is well understood that Australian climate is affected by natural climate variability such as El Niño–Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the Southern Annular Mode (SAM), depending on seasons and regions. However, studies on Australian climate extremes associated with natural climate variability remain limited. This study examines the observed impact of natural climate variability on inter‐annual changes in seasonal extremes of rainfall and temperature over Austral

The Indo-Pacific warm pool (IPWP) has warmed and grown substantially during the past century. The IPWP is Earth's largest region of warm sea surface temperatures (SSTs), has the highest rainfall, and is fundamental to global atmospheric circulation and hydrological cycle. The region has also experienced the world's highest rates of sea-level rise in recent decades, indicating large increases in ocean heat content and leading to substantial impacts on small island states in the region. Previous s

Abstract This study conducts a detection and attribution analysis of the observed changes in extreme precipitation during 1951–2015. Observed and CMIP6 multimodel simulated changes in annual maximum daily and consecutive 5‐day precipitation are compared using an optimal fingerprinting technique for different spatial scales from global land, Northern Hemisphere extratropics, tropics, three continental regions (North America and western and eastern Eurasia), and global “dry” and “wet” land areas (

Abstract. In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44∘ (∼ 50 km), 0.22∘ (∼ 25 km)

The internal variability in a 1000-yr control simulation with the coupled atmosphere’ocean global climate model ECHO-G is analysed using near-surface temperature, precipitation and mean sea level pressure variables, and is compared with observations and other coupled climate model simulations. ECHO-G requires annual mean flux adjustments for heat and freshwater in order to simulate no significant climate drift for 1000 yr, but no flux adjustments for momentum. The ECHO-G control run captures wel

Abstract Recent studies have detected anthropogenic influences due to increases in greenhouse gases on extreme temperature changes during the latter half of the twentieth century at global and regional scales. Most of the studies, however, were based on a limited number of climate models and also separation of anthropogenic influence from natural factors due to changes in solar and volcanic activities remains challenging at regional scales. Here, the authors conduct optimal fingerprinting analys

Human influence has previously been identified in the observed loss of Arctic sea ice, but this hypothesis has not yet been tested with a formal optimal detection approach. By comparing observed and multi‐model simulated changes in Arctic sea ice extent during 1953–2006 using an optimal fingerprinting method, we find that the anthropogenic signal first emerged in the early 1990s, indicating that human influence could have been detected even prior to the recent dramatic sea ice decline. The anthr

A Bayesian approach is introduced to model evaluation and multi‐model averaging with a systematic consideration of model uncertainty, and its application to global mean surface air temperature (SAT) changes is shown from multi‐AOGCM ensembles of IPCC AR4 simulations. The Bayes factor or likelihood ratio of each model to the reference model (where mean is identical to the observation) provides a skill ranging from 0 to 1. Four categories of model skill are derived on the basis of the previous stu