scholarly journals Evolution of tropical cyclone properties across the development cycle of the GISS‐E3 global climate model

2021 ◽  
Author(s):  
Rick D. Russotto ◽  
Jeffrey D.O. Strong ◽  
Suzana J. Camargo ◽  
Adam Sobel ◽  
Gregory S. Elsaesser ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Development Cycle

scholarly journals BASIC EXAMINATION OF FUTURE CHANGE OF TROPICAL CYCLONE AND STORM SURGE PROPERTIES UNDER CLIMATE CHANGE

2012 ◽  
Vol 1 (33) ◽  
pp. 23
Author(s):  
Sota Nakajo ◽  
Nobuhito Mori ◽  
Tomohiro Yasuda ◽  
Hajime Mase
Keyword(s):  
Tropical Cyclone ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Temporal Correlation ◽  
Future Change ◽  
Ensemble Averaging ◽  
Global Climate Changes ◽  
Correlation Algorithm ◽  
Future Prediction

Recently high-resolution Global Climate Model (GCM) shows that global climate changes may cause the future change of the Tropical Cyclone (TC) characteristics, such as frequency, developing process and intensity. However, there are two difficulties for assessment of future TC disaster, one is uncertainty of future prediction in GCM, and another is shortage of sample TC data. In this paper, we estimated future changes of TC properties and reduced uncertainty by ensemble averaging of multi-GCM prediction results, and generated many synthetic TC data with Global Stochastic Tropical Cyclone Model (GSTCM). In addition, GSTCM which have empirical temporal correlation algorithm was improved for the reproducibility of arrival TC statistics by cluster analysis of TC data. This upgrade could pave the way to local future prediction of TC disaster.

scholarly journals APPLICABILITY OF D4PDF DATASET TO GLOBAL STOCHASTIC TROPICAL CYCLONE MODEL

2020 ◽  
pp. 26
Author(s):  
Sota Nakajo ◽  
Jinji Umeda ◽  
Nobuhito Mori
Keyword(s):  
Tropical Cyclone ◽  
Climate Model ◽  
Model Simulation ◽  
Global Climate ◽  
Global Climate Model ◽  
Observation Data ◽  
Change Rate ◽  
Regional Area ◽  
Global Climate Model Simulation ◽  
Disaster Event

Disaster damage caused by tropical cyclone has grown every year. However, our experience of tropical cyclone is not enough to evaluate very low frequent and catastrophic disaster event. Stochastic tropical cyclone model has been used for assessment of tropical cyclone disaster. Global stochastic model was improved by using a lot of ensemble Global Climate Model simulation data (d4PDF) instead of limited number of observation data. The model bias included d4PDF was corrected by each regional grid by simple statistical method and interpolation. The accuracy of new model was verified at representative regional area in different basins. Generally, the improvement is remarkable where tropical cyclones rarely passed. The variation of joint PDF of tropical cyclone change rate between previous model and present model agree with model improvement. As an example of application, the frequencies of strong tropical cyclone events of two cases were estimated.

Projections of future tropical cyclone damage with a high-resolution global climate model

2017 ◽  
Vol 146 (3-4) ◽  
pp. 575-585 ◽  
Author(s):  
A. Gettelman ◽  
D. N. Bresch ◽  
C. C. Chen ◽  
J. E. Truesdale ◽  
J. T. Bacmeister
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model

Tropical Cyclone Changes in the Western North Pacific in a Global Warming Scenario

2007 ◽  
Vol 20 (11) ◽  
pp. 2378-2396 ◽  
Author(s):  
Markus Stowasser ◽  
Yuqing Wang ◽  
Kevin Hamilton
Keyword(s):  
Global Warming ◽  
Tropical Cyclone ◽  
North Pacific ◽  
Western North Pacific ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Surface Air Temperature ◽  
Good Representation ◽  
Climate System Model

Abstract The influence of global warming on the climatology of tropical cyclones in the western North Pacific basin is examined using the high-resolution International Pacific Research Center (IPRC) regional climate model forced by ocean temperatures and horizontal boundary fields taken from the NCAR Community Climate System Model version 2 (CCSM2) coupled global climate model. The regional model is first tested in 10 yr of simulation with boundary forcing taken from observations and is shown to produce a reasonably good representation of the observed statistics of tropical cyclone numbers and locations. The model was then run for 10 yr with forcing from a present-day control run of the CCSM2 and then for 10 yr with forcing fields taken from the end of a long run with 6 times the present-day atmospheric CO2 concentration. The global-mean surface air temperature warming in the perturbed run is 4.5 K, while the surface warming in the tropical western North Pacific is about 3 K. The results of these experiments reveal no statistically significant change in basinwide tropical cyclone numbers in the peak season from July to October in response to the CO2 increase. However, a pronounced and statistically significant increase in tropical cyclone occurrence in the South China Sea is found. While the basinwide total number of storms remains nearly unchanged in the warm climate, there is a statistically significant increase in the average strength of the cyclones and in the number of the storms in the strongest wind categories.

scholarly journals Comparison of Explicitly Simulated and Downscaled Tropical Cyclone Activity in a High-Resolution Global Climate Model

2010 ◽  
Vol 2 (4) ◽  
pp. n/a-n/a ◽  
Author(s):  
Kerry Emanuel ◽  
Kazuyoshi Oouchi ◽  
Masaki Satoh ◽  
Hirofumi Tomita ◽  
Yohei Yamada
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Tropical Cyclone Activity ◽  
Cyclone Activity

scholarly journals Real World and Tropical Cyclone World. Part I: High-Resolution Climate Model Verification

2020 ◽  
Vol 33 (4) ◽  
pp. 1455-1472 ◽  
Author(s):  
S. Sharmila ◽  
K. J. E. Walsh ◽  
M. Thatcher ◽  
S. Wales ◽  
S. Utembe
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Geographical Distribution ◽  
Real World ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Verification ◽  
State Dependency

AbstractRecent global climate models with sufficient resolution and physics offer a promising approach for simulating real-world tropical cyclone (TC) statistics and their changing relationship with climate. In the first part of this study, we examine the performance of a high-resolution (~40-km horizontal grid) global climate model, the atmospheric component of the Australian Community Climate and Earth System Simulator (ACCESS) based on the Met Office Unified Model (UM8.5) Global Atmosphere (GA6.0). The atmospheric model is forced with observed sea surface temperature, and 20 years of integrations (1990–2009) are analyzed for evaluating the simulated TC statistics compared with observations. The model reproduces the observed climatology, geographical distribution, and interhemispheric asymmetry of global TC formation rates reasonably well. The annual cycle of regional TC formation rates over most basins is also well captured. However, there are some regional biases in the geographical distribution of TC formation rates. To identify the sources of these biases, a suite of model-simulated large-scale climate conditions that critically modulate TC formation rates are further evaluated, including the assessment of a multivariate genesis potential index. Results indicate that the model TC genesis biases correspond well to the inherent biases in the simulated large-scale climatic states, although the relative effects on TC genesis of some variables differs between basins. This highlights the model’s mean-state dependency in simulating accurate TC formation rates.

High bit rate ACTS experiments for performing global science - Keck Telescope and global climate model

1996 ◽  
Author(s):  
Larry Bergman ◽  
J. Gary ◽  
Burt Edelson ◽  
Neil Helm ◽  
Judith Cohen ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Bit Rate ◽  
Global Science ◽  
High Bit Rate

scholarly journals A comparison of ship and satellite measurements of cloud properties with global climate model simulations in the southeast Pacific stratus deck

2010 ◽  
Vol 10 (14) ◽  
pp. 6527-6536 ◽  
Author(s):  
M. A. Brunke ◽  
S. P. de Szoeke ◽  
P. Zuidema ◽  
X. Zeng
Keyword(s):  
Diurnal Cycle ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Cloud Fraction ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Southeast Pacific ◽  
Cloud Thickness

Abstract. Here, liquid water path (LWP), cloud fraction, cloud top height, and cloud base height retrieved by a suite of A-train satellite instruments (the CPR aboard CloudSat, CALIOP aboard CALIPSO, and MODIS aboard Aqua) are compared to ship observations from research cruises made in 2001 and 2003–2007 into the stratus/stratocumulus deck over the southeast Pacific Ocean. It is found that CloudSat radar-only LWP is generally too high over this region and the CloudSat/CALIPSO cloud bases are too low. This results in a relationship (LWP~h9) between CloudSat LWP and CALIPSO cloud thickness (h) that is very different from the adiabatic relationship (LWP~h2) from in situ observations. Such biases can be reduced if LWPs suspected to be contaminated by precipitation are eliminated, as determined by the maximum radar reflectivity Zmax>−15 dBZ in the apparent lower half of the cloud, and if cloud bases are determined based upon the adiabatically-determined cloud thickness (h~LWP1/2). Furthermore, comparing results from a global model (CAM3.1) to ship observations reveals that, while the simulated LWP is quite reasonable, the model cloud is too thick and too low, allowing the model to have LWPs that are almost independent of h. This model can also obtain a reasonable diurnal cycle in LWP and cloud fraction at a location roughly in the centre of this region (20° S, 85° W) but has an opposite diurnal cycle to those observed aboard ship at a location closer to the coast (20° S, 75° W). The diurnal cycle at the latter location is slightly improved in the newest version of the model (CAM4). However, the simulated clouds remain too thick and too low, as cloud bases are usually at or near the surface.

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