PREDICTION OF FUTURE RAINFALL VARIATIONS IN THE KYUSHU ISLAND BASED ON LARGE ENSEMBLE EXPERIMENTS

AbstractLarge-ensemble simulations of the atmosphere-only time-slice experiments for the Polar Amplification Model Intercomparison Project (PAMIP) were carried out by the model group of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L). Eight groups of experiments forced by different combinations of the sea surface temperature (SST) and sea ice concentration (SIC) for pre-industrial, present-day, and future conditions were performed and published. The time-lag method was used to generate the 100 ensemble members, with each member integrating from 1 April 2000 to 30 June 2001 and the first two months as the spin-up period. The basic model responses of the surface air temperature (SAT) and precipitation were documented. The results indicate that Arctic amplification is mainly caused by Arctic SIC forcing changes. The SAT responses to the Arctic SIC decrease alone show an obvious increase over high latitudes, which is similar to the results from the combined forcing of SST and SIC. However, the change in global precipitation is dominated by the changes in the global SST rather than SIC, partly because tropical precipitation is mainly driven by local SST changes. The uncertainty of the model responses was also investigated through the analysis of the large-ensemble members. The relative roles of SST and SIC, together with their combined influence on Arctic amplification, are also discussed. All of these model datasets will contribute to PAMIP multi-model analysis and improve the understanding of polar amplification.

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Anthropogenic climate change has changed frequency of past flood during 2010-2013

Progress in Earth and Planetary Science ◽

10.1186/s40645-021-00431-w ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Yukiko Hirabayashi ◽

Haireti Alifu ◽

Dai Yamazaki ◽

Yukiko Imada ◽

Hideo Shiogama ◽

...

Keyword(s):

Climate Change ◽

South America ◽

Radiative Forcing ◽

Water Cycle ◽

Flood Frequency ◽

Anthropogenic Climate Change ◽

Climate Change Signal ◽

Northern Eurasia ◽

Large Ensemble ◽

The Impact

AbstractThe ongoing increases in anthropogenic radiative forcing have changed the global water cycle and are expected to lead to more intense precipitation extremes and associated floods. However, given the limitations of observations and model simulations, evidence of the impact of anthropogenic climate change on past extreme river discharge is scarce. Here, a large ensemble numerical simulation revealed that 64% (14 of 22 events) of floods analyzed during 2010-2013 were affected by anthropogenic climate change. Four flood events in Asia, Europe, and South America were enhanced within the 90% likelihood range. Of eight snow-induced floods analyzed, three were enhanced and four events were suppressed, indicating that the effects of climate change are more likely to be seen in the snow-induced floods. A global-scale analysis of flood frequency revealed that anthropogenic climate change enhanced the occurrence of floods during 2010-2013 in wide area of northern Eurasia, part of northwestern India, and central Africa, while suppressing the occurrence of floods in part of northeastern Eurasia, southern Africa, central to eastern North America and South America. Since the changes in the occurrence of flooding are the results of several hydrological processes, such as snow melt and changes in seasonal and extreme precipitation, and because a climate change signal is often not detectable from limited observation records, large ensemble discharge simulation provides insights into anthropogenic effects on past fluvial floods.

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d4PDF: large-ensemble and high-resolution climate simulations for global warming risk assessment

Progress in Earth and Planetary Science ◽

10.1186/s40645-020-00367-7 ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Masayoshi Ishii ◽

Nobuhito Mori

Keyword(s):

Risk Assessment ◽

Global Warming ◽

High Resolution ◽

Climate Changes ◽

Future Climate ◽

Atmospheric Models ◽

Large Ensemble ◽

Past Climate ◽

The Past ◽

Climate Simulations

Abstract A large-ensemble climate simulation database, which is known as the database for policy decision-making for future climate changes (d4PDF), was designed for climate change risk assessments. Since the completion of the first set of climate simulations in 2015, the database has been growing continuously. It contains the results of ensemble simulations conducted over a total of thousands years respectively for past and future climates using high-resolution global (60 km horizontal mesh) and regional (20 km mesh) atmospheric models. Several sets of future climate simulations are available, in which global mean surface air temperatures are forced to be higher by 4 K, 2 K, and 1.5 K relative to preindustrial levels. Nonwarming past climate simulations are incorporated in d4PDF along with the past climate simulations. The total data volume is approximately 2 petabytes. The atmospheric models satisfactorily simulate the past climate in terms of climatology, natural variations, and extreme events such as heavy precipitation and tropical cyclones. In addition, data users can obtain statistically significant changes in mean states or weather and climate extremes of interest between the past and future climates via a simple arithmetic computation without any statistical assumptions. The database is helpful in understanding future changes in climate states and in attributing past climate events to global warming. Impact assessment studies for climate changes have concurrently been performed in various research areas such as natural hazard, hydrology, civil engineering, agriculture, health, and insurance. The database has now become essential for promoting climate and risk assessment studies and for devising climate adaptation policies. Moreover, it has helped in establishing an interdisciplinary research community on global warming across Japan.

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Skilful predictions of the Asian summer monsoon one year ahead

Nature Communications ◽

10.1038/s41467-021-22299-6 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Yuhei Takaya ◽

Yu Kosaka ◽

Masahiro Watanabe ◽

Shuhei Maeda

Keyword(s):

Long Range ◽

Summer Monsoon ◽

Southern Oscillation ◽

Asian Summer Monsoon ◽

Boreal Summer ◽

Climate Modelling ◽

Large Ensemble ◽

Asian Society ◽

Asian Summer ◽

One Year

AbstractThe interannual variability of the Asian summer monsoon has significant impacts on Asian society. Advances in climate modelling have enabled us to make useful predictions of the seasonal Asian summer monsoon up to approximately half a year ahead, but long-range predictions remain challenging. Here, using a 52-member large ensemble hindcast experiment spanning 1980–2016, we show that a state-of-the-art climate model can predict the Asian summer monsoon and associated summer tropical cyclone activity more than one year ahead. The key to this long-range prediction is successfully simulating El Niño-Southern Oscillation evolution and realistically representing the subsequent atmosphere–ocean response in the Indian Ocean–western North Pacific in the second boreal summer of the prediction. A large ensemble size is also important for achieving a useful prediction skill, with a margin for further improvement by an even larger ensemble.

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The growth of the red-sequence in clusters since ≃1

Proceedings of the International Astronomical Union ◽

10.1017/s1743921310008410 ◽

2009 ◽

Vol 5 (H15) ◽

pp. 88-88

Author(s):

Roberto P. Muñoz ◽

L. F. Barrientos ◽

B. P. Koester ◽

D. G. Gilbank ◽

M. D. Gladders ◽

...

Keyword(s):

Star Formation ◽

Galaxy Clusters ◽

Evolutionary Model ◽

Large Ensemble ◽

Cluster Galaxies ◽

Nir Imaging ◽

Measured Change ◽

First Time ◽

The Universe ◽

Red Sequence

AbstractWe use deep nIR imaging of 15 galaxy clusters at z ≃ 1 to study the build-up of the red-sequence in rich clusters since the Universe was half its present age. We measured, for the first time, the luminous-to-faint ratio of red-sequence galaxies at z=1 from a large ensemble of clusters, and found an increase of 100% in the ratio of luminous-to-faint red-sequence galaxies from z=0.45 to 1.0. The measured change in this ratio as function of redshift is well-reproduced by a simple evolutionary model developed in this work, that consists in an early truncation of the star formation for bright cluster galaxies and a delayed truncation for faint cluster galaxies.

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Assessment of Near-Real-Time Satellite Precipitation Products from GSMaP in Monitoring Rainfall Variations over Taiwan

Remote Sensing ◽

10.3390/rs13020202 ◽

2021 ◽

Vol 13 (2) ◽

pp. 202

Author(s):

Wan-Ru Huang ◽

Pin-Yi Liu ◽

Jie Hsu ◽

Xiuzhen Li ◽

Liping Deng

Keyword(s):

Real Time ◽

Complex Terrain ◽

Daily Rainfall ◽

Rainfall Estimation ◽

Rainfall Events ◽

Satellite Precipitation ◽

Different Seasons ◽

Daily Scale ◽

Rainfall Variations ◽

Southwestern Taiwan

This study assessed four near-real-time satellite precipitation products (NRT SPPs) of Global Satellite Mapping of Precipitation (GSMaP)—NRT v6 (hereafter NRT6), NRT v7 (hereafter NRT7), Gauge-NRT v6 (hereafter GNRT6), and Gauge-NRT v7 (hereafter GNRT7)— in representing the daily and monthly rainfall variations over Taiwan, an island with complex terrain. The GNRT products are the gauge-adjusted version of NRT products. Evaluations for warm (May–October) and cold months (November–April) were conducted from May 2017 to April 2020. By using observations from more than 400 surface gauges in Taiwan as a reference, our evaluations showed that GNRT products had a greater error than NRT products in underestimating the monthly mean rainfall, especially during the warm months. Among SPPs, NRT7 performed best in quantitative monthly mean rainfall estimation; however, when examining the daily scale, GNRT6 and GNRT7 were superior, particularly for monitoring stronger (i.e., more intense) rainfall events during warm and cold months, respectively. Spatially, the major improvement from NRT6 to GNRT6 (from NRT7 to GNRT7) in monitoring stronger rainfall events over southwestern Taiwan was revealed during warm (cold) months. From NRT6 to NRT7, the improvement in daily rainfall estimation primarily occurred over southwestern and northwestern Taiwan during the warm and cold months, respectively. Possible explanations for the differences between the ability of SPPs are attributed to the algorithms used in SPPs. These findings highlight that different NRT SPPs of GSMaP should be used for studying or monitoring the rainfall variations over Taiwan for different purposes (e.g., warning of floods in different seasons, studying monthly or daily precipitation features in different seasons, etc.).

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