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.

scholarly journals Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

2017 ◽  
Vol 10 (3) ◽  
pp. 1383-1402 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Rainfall Variability ◽  
Global Climate Model ◽  
Small Scale ◽  
Low Resolution ◽  
The Impact ◽  
Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

scholarly journals The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high-resolution global climate model data

2018 ◽  
Vol 18 (11) ◽  
pp. 2991-3006 ◽  
Author(s):  
Matthew D. K. Priestley ◽  
Helen F. Dacre ◽  
Len C. Shaffrey ◽  
Kevin I. Hodges ◽  
Joaquim G. Pinto
Keyword(s):  
High Resolution ◽  
Return Period ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Geographic Region ◽  
Near Surface ◽  
Short Period

Abstract. Extratropical cyclones are the most damaging natural hazard to affect western Europe. Serial clustering occurs when many intense cyclones affect one specific geographic region in a short period of time which can potentially lead to very large seasonal losses. Previous studies have shown that intense cyclones may be more likely to cluster than less intense cyclones. We revisit this topic using a high-resolution climate model with the aim to determine how important clustering is for windstorm-related losses. The role of windstorm clustering is investigated using a quantifiable metric (storm severity index, SSI) that is based on near-surface meteorological variables (10 m wind speed) and is a good proxy for losses. The SSI is used to convert a wind footprint into losses for individual windstorms or seasons. 918 years of a present-day ensemble of coupled climate model simulations from the High-Resolution Global Environment Model (HiGEM) are compared to ERA-Interim reanalysis. HiGEM is able to successfully reproduce the wintertime North Atlantic/European circulation, and represent the large-scale circulation associated with the serial clustering of European windstorms. We use two measures to identify any changes in the contribution of clustering to the seasonal windstorm loss as a function of return period. Above a return period of 3 years, the accumulated seasonal loss from HiGEM is up to 20 % larger than the accumulated seasonal loss from a set of random resamples of the HiGEM data. Seasonal losses are increased by 10 %–20 % relative to randomized seasonal losses at a return period of 200 years. The contribution of the single largest event in a season to the accumulated seasonal loss does not change with return period, generally ranging between 25 % and 50 %. Given the realistic dynamical representation of cyclone clustering in HiGEM, and comparable statistics to ERA-Interim, we conclude that our estimation of clustering and its dependence on the return period will be useful for informing the development of risk models for European windstorms, particularly for longer return periods.

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

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 Parameterization of subgrid aircraft emission plumes for use in large-scale atmospheric simulations

2009 ◽  
Vol 9 (6) ◽  
pp. 24755-24781 ◽  
Author(s):  
A. D. Naiman ◽  
S. K. Lele ◽  
J. T. Wilkerson ◽  
M. Z. Jacobson
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Anthropogenic Pollution ◽  
Scale Model ◽  
Subgrid Scale ◽  
Aircraft Emissions ◽  
Plume Dynamics ◽  
Aircraft Emission

Abstract. Aircraft emissions differ from other anthropogenic pollution in that they occur mainly in the upper troposphere and lower stratosphere where they can form condensation trails (contrails) and affect cirrus cloud cover. In determining the effect of aircraft on climate, it is therefore necessary to examine these processes. Previous studies have approached this problem by treating aircraft emissions on the grid scale, but this neglects the subgrid scale nature of aircraft emission plumes. We present a new model of aircraft emission plume dynamics that is intended to be used as a subgrid scale model in a large scale atmospheric simulation. The model shows good agreement with a large eddy simulation of aircraft emission plume dynamics and with an analytical solution to the dynamics of a sheared Gaussian plume. We argue that this provides a reasonable model of line-shaped contrail dynamics and give an example of how it might be applied in a global climate model.

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 An evaluation of clouds and radiation in a large-scale atmospheric model using a cloud vertical structure classification

2020 ◽  
Vol 13 (2) ◽  
pp. 673-684
Author(s):  
Dongmin Lee ◽  
Lazaros Oreopoulos ◽  
Nayeong Cho
Keyword(s):  
Large Scale ◽  
Vertical Structure ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Atmospheric Model ◽  
Radiative Effects ◽  
Surface Cooling ◽  
Vertical Location ◽  
High Clouds

Abstract. We revisit the concept of the cloud vertical structure (CVS) classes we have previously employed to classify the planet's cloudiness (Oreopoulos et al., 2017). The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an atmospheric global climate model, specifically a version of NASA's GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Such classes can be defined in GEOS-5 thanks to a subcolumn cloud generator paired with the model's radiative transfer algorithm, and their associated radiative effects can be evaluated against observations. We find that the model produces 50 % more clear skies than observations in relative terms and produces isolated high clouds that are slightly less frequent than in observations, but optically thicker, yielding excessive planetary and surface cooling. Low clouds are also brighter than in observations, but underestimates of the frequency of occurrence (by ∼20 % in relative terms) help restore radiative agreement with observations. Overall the model better reproduces the longwave radiative effects of the various CVS classes because cloud vertical location is substantially constrained in the CVS framework.

scholarly journals An evaluation of clouds and radiation in a Large-Scale Atmospheric Model using a Cloud Vertical Structure classification

2019 ◽  
Author(s):  
Dongmin Lee ◽  
Lazaros Oreopoulos ◽  
Nayeong Cho
Keyword(s):  
Large Scale ◽  
Vertical Structure ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Atmospheric Model ◽  
Cloud Radiative Effect ◽  
Scale Models ◽  
High Clouds

Abstract. We revisit Cloud Vertical Structure (CVS) classes we have previously employed to classify the planet’s cloudiness. The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an Atmospheric Global Climate Model (AGCM), specifically NASA’s GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Determination of CVS and associated radiation in the model is possible thanks to the implementation of a subcolumn cloud generator which is paired with the model’s radiative transfer algorithm. We assess GEOS-5 cloudiness in terms of the statistics and geographical distributions of the CVS classes, as well as features of their associated Cloud Radiative Effect (CRE). We decompose the model’s CVS-specific CRE errors into component errors stemming from biases in the frequency of occurrence of the CVSs, and biases in their internal radiative characteristics. Our framework sheds additional light into the verisimilitude of cloudiness in large scale models and can be used to complement cloud evaluations that take advantage of satellite simulator implementations.

scholarly journals Brief Communication: An update of the article "Modelling flood damages under climate change conditions – a case study for Germany"

2016 ◽  
Vol 16 (7) ◽  
pp. 1617-1622 ◽  
Author(s):  
Fred Fokko Hattermann ◽  
Shaochun Huang ◽  
Olaf Burghoff ◽  
Peter Hoffmann ◽  
Zbigniew W. Kundzewicz
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Considerable Increase ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Impact Modelling ◽  
Flood Damages

Abstract. In our first study on possible flood damages under climate change in Germany, we reported that a considerable increase in flood-related losses can be expected in a future warmer climate. However, the general significance of the study was limited by the fact that outcome of only one global climate model (GCM) was used as a large-scale climate driver, while many studies report that GCMs are often the largest source of uncertainty in impact modelling. Here we show that a much broader set of global and regional climate model combinations as climate drivers show trends which are in line with the original results and even give a stronger increase of damages.

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