scholarly journals Evaluation of Extreme Characteristics of Typhoon due to Global Warming based on Global Climate Model and Storm Surge Simulations by using GCM Data

2008 ◽  
Vol 55 ◽  
pp. 1331-1335
Author(s):  
Tomohiro YASUDA ◽  
Rie TAKADA ◽  
Soo Youl KIM ◽  
Hajime MASE
2020 ◽  
Vol 162 (2) ◽  
pp. 425-442
Author(s):  
Jung-A Yang ◽  
Sooyoul Kim ◽  
Sangyoung Son ◽  
Nobuhito Mori ◽  
Hajime Mase

Abstract We assess uncertainties in projecting future changes in extreme storm surge height (SSH) based on typhoon data extracted from ensemble experiment results with four sea surface temperature (SST) conditions and three global warming scenarios using a single atmospheric global climate model. In particular, this study focus on typhoons passing around the Korean Peninsula (KP) defined as the region of 32 to 40° N and 122 to 132° E. It is predicted the number of the typhoons affecting the KP will decrease by 4~73% while their strength will increase by 0.8~1.4% under the given future conditions. The locations of genesis and lysis of the typhoons are expected to be shifted towards the northwest and northeast for all ensemble experiment conditions, respectively. However, the extent of their change varies depending on the future SST and global warming conditions. Storm surge simulations were carried out by using predicted typhoon data as an external force. It is found that future SST patterns and climate warming scenarios affect future typhoon characteristics, which influences values of extreme SSH and locations of the vulnerable area to storm surge under the future climate conditions. In particular, the values of extreme SSH and the locations of the vulnerable area to storm surge appear to be strongly influenced by both pathway and frequency of intense typhoons.


2017 ◽  
Vol 114 (6) ◽  
pp. 1258-1263 ◽  
Author(s):  
J. David Neelin ◽  
Sandeep Sahany ◽  
Samuel N. Stechmann ◽  
Diana N. Bernstein

Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.


Author(s):  
Bo-Joung Park ◽  
Seung-Ki Min ◽  
Evan Weller

Abstract Summer season has lengthened substantially across Northern Hemisphere (NH) land over the past decades, which has been attributed to anthropogenic greenhouse gas increases. This study examines additional future changes in summer season onset and withdrawal under 1.5℃ and 2.0℃ global warming conditions using multiple atmospheric global climate model (AGCM) large-ensemble simulations from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project. Five AGCMs provide more than 100 runs of 10-year length for three experiments: All-Hist (current decade: 2006-2015), Plus15, and Plus20 (1.5℃ and 2.0℃ above pre-industrial condition, respectively). Results show that with 1.5℃ and 2.0℃ warmer conditions summer season will become longer by a few days to weeks over entire NH lands, with slightly larger contributions by delay in withdrawal due to stronger warming in late summer. Stronger changes are observed more in middle latitudes than high latitudes and largest expansion (up to three weeks) is found over East Asia and the Mediterranean. Associated changes in summer-like day frequency is further analyzed focusing on the extended summer edges. The hot days occur more frequently in lower latitudes including East Asia, USA and Mediterranean, in accord with largest summer season lengthening. Further, difference between Plus15 and Plus20 indicates that summer season lengthening and associated increases in hot days can be reduced significantly if warming is limited to 1.5℃. Overall, similar results are obtained from CMIP5 coupled GCM simulations (based on RCP8.5 scenario experiments), suggesting a weak influence of air-sea coupling on summer season timing changes.


2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.


2021 ◽  
pp. 1-43
Author(s):  
Aaron Match ◽  
Stephan Fueglistaler

AbstractGlobal warming projections of dynamics are less robust than projections of thermodynamics. However, robust aspects of the thermodynamics can be used to constrain some dynamical aspects. This paper argues that tropospheric expansion under global warming (a thermodynamical process) explains changes in the amplitude of the Quasi-Biennial Oscillation (QBO) in the lower and middle stratosphere (a dynamical process). A theoretical scaling for tropospheric expansion of approximately 6 hPa K−1 is derived, which agrees well with global climate model (GCM) experiments. Using this theoretical scaling, the response of QBO amplitude to global warming is predicted by shifting the climatological QBO amplitude profile upwards by 6 hPa per Kelvin of global warming. In global warming simulations, QBO amplitude in the lower- to mid-stratosphere shifts upwards as predicted by tropospheric expansion. Applied to observations, the tropospheric expansion framework suggests a historical weakening of QBO amplitude at 70 hPa of 3% decade−1 from 1953-2020. This expected weakening trend is half of the 6% decade−1 from 1953-2012 detected and attributed to global warming in a recent study. The previously reported trend was reinforced by record low QBO amplitudes during the mid-2000s, from which the QBO has since recovered. Given the modest weakening expected on physical grounds, past decadal modulations of QBO amplitude are reinterpreted as a hitherto unrecognized source of internal variability. This large internal variability dominates over the global warming signal, such that despite 65 years of observations, there is not yet a statistically significant weakening trend.


2017 ◽  
Vol 30 (20) ◽  
pp. 8033-8044 ◽  
Author(s):  
Kevin M. Quinn ◽  
J. David Neelin

Abstract The total amount of precipitation integrated across a precipitation feature (contiguous precipitating grid cells exceeding a minimum rain rate) is a useful measure of the aggregate size of the disturbance, expressed as the rate of water mass lost or latent heat released (i.e., the power of the disturbance). The probability distribution of cluster power is examined over the tropics using Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite-retrieved rain rates and global climate model output. Observed distributions are scale-free from the smallest clusters up to a cutoff scale at high cluster power, after which the probability drops rapidly. After establishing an observational baseline, precipitation from the High Resolution Atmospheric Model (HiRAM) at two horizontal grid spacings (roughly 0.5° and 0.25°) is compared. When low rain rates are excluded by choosing a minimum rain-rate threshold in defining clusters, the model accurately reproduces observed cluster power statistics at both resolutions. Middle and end-of-century cluster power distributions are investigated in HiRAM in simulations with prescribed sea surface temperatures and greenhouse gas concentrations from a “business as usual” global warming scenario. The probability of high cluster power events increases strongly by end of century, exceeding a factor of 10 for the highest power events for which statistics can be computed. Clausius–Clapeyron scaling accounts for only a fraction of the increased probability of high cluster power events.


2015 ◽  
Vol 804 ◽  
pp. 235-238
Author(s):  
Sunisa Saiuparad

Thailand is an agricultural country. Most farmers still depend on rainfall for cultivation. Global warming may result in changes in the amount and distribution of rainfall both in space and time. This could impact the occurrence of heavy rain and drought in the country. Thus, it is necessary to analyze heavy rain and drought conditions in Thailand under global warming for the purpose of preparedness and impact mitigation. The data used in this study consist of present climate and future climate. The data for present climate are from the National Centers for Environmental Prediction (NCEP) and the Thai Meteorological Department (TMD). The data for future climate are from the Educational Global Climate Model (EdGCM). The results are risk maps of heavy rain and drought in Thailand during the years 2046-2065 and 2081-2099 under a global warming scenario.


2020 ◽  
Author(s):  
Ming Zhao

<p>Atmospheric rivers (ARs) are narrow, elongated, synoptic jets of water vapor that play important roles in the global water cycle and regional weather and climate extremes. Accurate climate projections of high impact global severe flood and drought events hinge on the climate models' ability to simulate and predict the AR phenomenon. This presentation will provide a systematic evaluation of the AR statistics and characteristics simulated by the GFDL new generation high resolution global climate model participating in the CMIP6 High Resolution Model Intercomparison Project (HiResMIP). The analyses include the historical period (1950-2014) compared against the ERA-Interim reanalysis results as well as future projections under global warming scenarios. The AR characteristics such as the spatial distribution, frequency, and intensity are explored in conjunction with large-scale circulation patterns such as the El Niño–Southern Oscillation, the Arctic Oscillation, and the Pacific-North-American teleconnections pattern. Potential changes in AR characteristics with global warming scenarios and their implications to weather and climate extremes will be discussed.</p>


Climate ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 72 ◽  
Author(s):  
Knut Seip ◽  
Hui Wang

Ocean oscillations interact across large regions and these interactions may explain cycles in global temperature anomaly, including hiatus periods. Here, we examine ocean interaction measures and compare results from model simulations to observations for El Niño and the Pacific decadal oscillation (PDO). We use the global climate model of the Met Office Hadley Centre. A relatively novel method for identifying running leading-agging LL-relations show that the observed El Niño generally leads the observed PDO and this pattern is strengthened in the simulations. However, LL-pattern in both observations and models shows that there are three periods, around 1910–1920, around 1960 and around 2000 where El Niño lags PDO, or the leading signature is weak. These periods correspond to hiatus periods in global warming. The power spectral density analysis, (PSD), identifies various ocean cycle lengths in El Niño and PDO, but the LL-algorithm picks out common cycles of 7–8 and 24 years that shows leading-lagging relations between them.


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