Search

Human activity have caused significant increase in greenhouse gas (GHG) concentration and land use and land cover change (LULCC), which can in turn affect regional and global climate. We investigate the relative contributions of increased GHG concentration and LULCC to the precipitation and surface air temperature (SAT) in Asia through three dynamical downscaling simulations with different land cover maps and GHG concentrations. The results suggest that the increased GHG concentration leads to an increase (decrease) in precipitation over East Asia and Southeast Asia (South Asia) in spring and winter. Over Southeast Asia and the Bay of Bengal, LULCC induced a significant decrease in precipitation in autumn and winter, and the change is greater than that induced by GHG. Moreover, the enhanced GHG concentration generally leads to a decrease in dry days or light rain days and an increase in heavy rain days over the land area. However, LULCC‐induced changes in extreme precipitation are generally weak. The increased GHG concentration induces a significant increase of 1–3°C in the SAT throughout the year. LULCC plays a more important role than the increased GHG concentration in modulating the SAT over South Asia, Southeast Asia, and East Asia throughout the year. The increased GHG concentration and LULCC cause a broader range of changes in the daily temperature frequency. The anomalous warm event of 8–10°C increases by 1–1.5 days per season in the middle latitude regions in boreal spring due to the increased GHG concentration. LULCC also leads to an increase in high‐temperature events except central Asia. [ABSTRACT FROM AUTHOR]

Increases in total and extreme precipitation have been investigated worldwide using limited spatiotemporal data based on surface observations and satellite remote sensing during recent decades. However, it remains unclear whether rain gauge daily precipitation records also show a significant increase in global precipitation. In this study, we first apply the transformed version of the penalized maximum F test ("transPMFred") to homogenize daily precipitation (P) records from 10,629 stations around the world during 1960–2016 from a dataset (GHCN‐CMA) that combines the daily precipitation data from the Global Historical Climatology Network (GHCN‐Daily) dataset and the China Meteorological Administration (CMA), and then utilize the homogenized data to study the frequency of daily precipitation on a global scale. The results indicate that precipitation frequency exhibited significant increasing trends from 1960 to 2016 across most of the globe, except for East Asia. Moreover, the variability of global precipitation frequency was more pronounced in wet regions than dry regions, especially in North America, Europe and East Asia based multiple daily precipitation datasets. The regional average frequency for moderate (30th < P ≤ 60th percentile), heavy (60th < P ≤ 90th percentile) and very heavy (P > 90th percentile) precipitation increased in North America and Europe. Changes in precipitation frequency decreased for light (P ≤ 30th percentile) and moderate precipitation but increased for heavy and very heavy precipitation, which mainly occurs in dry regions of Australia. Moreover, precipitation frequency in wet and dry regions of East Asia showed opposite trends, with a decrease in wet regions and an increase in dry regions. [ABSTRACT FROM AUTHOR]

The impacts and corresponding mechanisms of land use/cover change (LUCC), mainly crops and pasture, on the spatial patterns of summer precipitation over eastern China at the decadal timescale during the last millennium are investigated, using a set of land use/cover sensitivity experiments from the Community Earth System Model (CESM) Last Millennium Ensemble (LME) archive. Two leading modes of summer precipitation over eastern China at decadal scale before (with slight LUCC) and after (with drastic LUCC) 1750 AD are compared. The results show that the LUCC plays an important role in modulating the spatial patterns of summer precipitation over eastern China at decadal scale. Before 1750 AD, the first leading mode exhibits a meridional dipole pattern, while the second leading mode exhibits a meridional tripole pattern. After 1750 AD, the order of the spatial patterns switches, that is, the tripole pattern as the first leading mode and the dipole pattern as the second leading mode. During both periods, the "dry north‐wet south" dipole pattern is associated with an anomalous "A‐C" (anticyclone‐cyclone) low‐level circulation pattern and the related water vapour divergence‐convergence pattern from north to south over the eastern part of East Asia, whereas the tripole pattern corresponds to an anomalous "A‐C‐A" (anticyclone‐cyclone‐anticyclone) circulation pattern along with the corresponding tripole pattern of water vapour divergence/convergence. The regressions of sea surface temperature (SST) during boreal winter resemble obvious Pacific decadal oscillation (PDO) or Atlantic multi‐decadal oscillation (AMO) modes. In addition, the AMO index displays a decreasing trend during the last millennium under the LUCC forcing, while the PDO index does not show an obvious changing trend. The possibility of coupled PDO‐AMO anti‐phase (in‐phase) increases (decreases) after 1750 AD, leading to the increased (decreased) possibility of the tripole (dipole) pattern in eastern China. Our findings confirm the necessity of including LUCC as an important forcing factor in predictions of future climate changes, especially at the regional scale and also at longer timescales. [ABSTRACT FROM AUTHOR]

Water management is a crucial issue in East Asia and is significantly influenced by climate change. Because East Asia's precipitation characteristics are varied and complex, it is necessary to implement the analysis of the future changes in precipitation on an objectively classified, specific sub‐regional level to effectively solve these problems. In this study, sub‐regions were objectively classified according to their precipitation characteristics, based on the present observations in East Asia. Additionally, the bias‐correction technique was applied to the regional climate model (RCM) to yield more reliable future precipitation predictions for the sub‐regions. We obtained the following four key results in this study. (1) The classified sub‐regions corresponded well to the observed annual precipitation distribution and adequately reflected the influence of the summer monsoon. The annual precipitation of the classified sub‐regions exhibited a decreasing trend in arid regions and an increasing trend in humid areas. (2) Because the bias‐corrected RCM was able to simulate annual precipitation reasonably, this technique was applied to future scenarios to analyse future changes in precipitation for each classified sub‐region. (3) Future annual precipitation will increase significantly in the region spanning from the western part of Southern China to the area around the Bohai Sea, while the temporal variations of the climatological daily precipitation indicated that sub‐regions under the influence of the East Asian summer monsoon (EASM) will be predicted an increase in second peaks during the summer. Hence, in the future, the EASM rain belt will be strengthened and its average location will move northward from its present location. (4) Because the high‐intensity extreme precipitation indices are expected to have a more considerable increase in all the classified sub‐regions, there is a need to solidify response measures against disasters that could arise from these changes in the East Asian region. [ABSTRACT FROM AUTHOR]

Based on hourly temperature data collected from 2,307 meteorological stations over China and two sets of climate change simulations over East Asia using the regional climate model version 4.4 (RegCM4.4) driven by the global models of HadGEM2‐ES and MPI‐ESM‐MR, future changes of heating and cooling degree‐hours (HDH and CDH) at the end of the 21st century under RCP4.5 scenario are investigated. Compared against the observation, the spatial distribution, magnitude and annual cycle of present‐day HDH and CDH at different times, as well as the diurnal cycle of them can be realistically simulated by the model. Meanwhile, some bias can also be found and it varies with the times, especially for CDH. At the end of the century, significant decrease of HDH can be found over the Tibetan Plateau, the northern part of Northeast China, and Northwest China at each times while increase of CDH are observed at all the times except some parts of the Tibetan Plateau where the CDH remains zero due to the cold climate there. But for different times, some differences are found in HDH decrease and CDH increase. For example, the changes of HDH at the fifth to the seventh times present a weaker decrease in the northwestern basins compared to other times and the CDH increase are more significant at the fifth and the sixth times. The regional mean changes of HDH and CDH over China in the 21st century (2006–2098) also diverge among different times, which indicates the degree‐hours is needed to precisely calculate the hourly heating and cooling energy demand and then the heating and cooling degree days. [ABSTRACT FROM AUTHOR]

This study examines potential benefits of performance‐based multi‐model ensembles (MMEs) in projecting the impacts of climate change on extreme precipitation indices over East Asia (EA) using the data from 19 GCMs in the coupled model intercomparison project 5 (CMIP5). The Taylor skill score is adopted as the measure of the model skills in simulating the spatial and interannual variability of the selected extreme precipitation indices over four EA regions. The overall rank based on the total skill score (TSC) is used to construct two skill‐based MMEs, MME of high‐skill, MMH (MME of low‐skill, MML) that include the top (bottom) seven models, in addition to the simple ensemble of all 19 GCMs (ENS). Inter‐GCM consistency is measured using the signal‐to‐noise ratio (SNR). In the present‐day period, MMH yields higher skill scores than MML and ENS for almost all extreme precipitation indices as well as regions. Regional variations in biases, inter‐model consistency, and TSC are large. The inter‐model consistency is highest for Northern China and Manchuria and is lowest for Southern China. The most notable differences in the key properties of climate change signals from the three MMEs among the three ensembles are that the climate change signals from MMH and ENS exceed the 90% significance level in much larger areas than those from MML. However, the differences in the climate change signals between MMH and MML are generally below the 90% significance level. The SNR of the projected climate change signals shows that MMH yields more consistent climate change signals than ENS/MML. Both the SNR differences and the area in which statistical significance exceed the 90% level suggest that constructing climate change signals from a group of higher‐skill models may yield more reliable projections than constructing MMEs from the entire models or a group of lower‐skilled models. The domains used in the study (SOUTH: 110°–140°E, 20°–30°N, MIDDLE: 110°–140°E, 30°–40°N), NORTH: 110°–140°E, 40°–50°N, EA: 110°–140°E, 20°–50°N) [ABSTRACT FROM AUTHOR]