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 Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in climate simulations

2016 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Rainfall Variability ◽  
Pilot Project ◽  
Small Scale ◽  
Low Resolution ◽  
Climate Simulations ◽  
Advanced Computing ◽  
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 km 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 PBytes of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Center (LRZ) in Garching, Germany. About 140 TBytes of post-processed data are stored on the CINECA supercomputing center archives and are freely accessible to the community thanks to an EUDAT Data Pilot project. This paper presents the technical and scientific setup 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 increases 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.

Constraining the model representation of the aerosol life cycle in relation to sources and sinks.

2020 ◽  
Author(s):  
Paul Kim ◽  
Daniel Partridge ◽  
James Haywood
Keyword(s):  
Climate Change ◽  
Life Cycle ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Evaluation Framework ◽  
Microphysical Properties ◽  
The Impact ◽  
Source And Sink

<p>Global climate model (GCM) ensembles still produce a significant spread of estimates for the future of climate change which hinders our ability to influence policymakers. The range of these estimates can only partly be explained by structural differences and varying choice of parameterisation schemes between GCMs. GCM representation of cloud and aerosol processes, more specifically aerosol microphysical properties, remain a key source of uncertainty contributing to the wide spread of climate change estimates. The radiative effect of aerosol is directly linked to the microphysical properties and these are in turn controlled by aerosol source and sink processes during transport as well as meteorological conditions.</p><p>A Lagrangian, trajectory-based GCM evaluation framework, using spatially and temporally collocated aerosol diagnostics, has been applied to over a dozen GCMs via the AeroCom initiative. This framework is designed to isolate the source and sink processes that occur during the aerosol life cycle in order to improve the understanding of the impact of these processes on the simulated aerosol burden. Measurement station observations linked to reanalysis trajectories are then used to evaluate each GCM with respect to a quasi-observational standard to assess GCM skill. The AeroCom trajectory experiment specifies strict guidelines for modelling groups; all simulations have wind fields nudged to ERA-Interim reanalysis and all simulations use emissions from the same inventories. This ensures that the discrepancies between GCM parameterisations are emphasised and differences due to large scale transport patterns, emissions and other external factors are minimised.</p><p>Preliminary results from the AeroCom trajectory experiment will be presented and discussed, some of which are summarised now. A comparison of GCM aerosol particle number size distributions against observations made by measurement stations in different environments will be shown, highlighting the difficulties that GCMs have at reproducing observed aerosol concentrations across all size ranges in pristine environments. The impact of precipitation during transport on aerosol microphysical properties in each GCM will be shown and the implications this has on resulting aerosol forcing estimates will be discussed. Results demonstrating the trajectory collocation framework will highlight its ability to give more accurate estimates of the key aerosol sources in GCMs and the importance of these sources in influencing modelled aerosol-cloud effects. In summary, it will be shown that this analysis approach enables us to better understand the drivers behind inter-model and model-observation discrepancies.</p>

scholarly journals Indigenous vegetation burning practices and their impact on the climate of the northern Australian monsoon region

2013 ◽  
Vol 10 (8) ◽  
pp. 10313-10332 ◽  
Author(s):  
K.-H. Wyrwoll ◽  
F. H. McRobie ◽  
M. Notaro ◽  
G. Chen
Keyword(s):  
Time Scales ◽  
Vegetation Cover ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Scale ◽  
Northern Australia ◽  
Monsoon Region ◽  
The Impact

Abstract. Here we pose the question: was there a downturn in summer monsoon precipitation over northern Australia due to Aboriginal vegetation practices over prehistoric time scales? In answering this question we consider the results from a global climate model incorporating ocean, land, ice, atmosphere and vegetation interactions, reducing the total vegetation cover over northern Australia by 20% to simulate the effects of burning. The results suggest that burning forests and woodlands in the monsoon region of Australia led to a shift in the regional climate, with a delayed monsoon onset and reduced precipitation in the months preceding the "full" monsoon. We place these results in a global context, drawing on model results from five other monsoon regions, and note that although the precipitation response is highly varied, there is a general but region specific climate response to reduced vegetation cover in all cases. Our findings lead us to conclude that large-scale vegetation modification over millennial time-scales due to indigenous burning practices, would have had significant impacts on regional climates. With this conclusion comes the need to recognise that the Anthropocene saw the impact of humans on regional-scale climates and hydrologies at much earlier times than generally recognized.

scholarly journals A Hybrid Downscaling Approach for Future Temperature and Precipitation Change

2020 ◽  
Vol 59 (11) ◽  
pp. 1793-1807 ◽  
Author(s):  
Helene Birkelund Erlandsen ◽  
Kajsa M. Parding ◽  
Rasmus Benestad ◽  
Abdelkader Mezghani ◽  
Marie Pontoppidan
Keyword(s):  
Regional Climate Model ◽  
Statistical Models ◽  
Large Scale ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Small Scale ◽  
Regional Climate Model Output

AbstractWe used empirical–statistical downscaling in a pseudoreality context, in which both large-scale predictors and small-scale predictands were based on climate model results. The large-scale conditions were taken from a global climate model, and the small-scale conditions were taken from dynamical downscaling of the same global model with a convection-permitting regional climate model covering southern Norway. This hybrid downscaling approach, a “perfect model”–type experiment, provided 120 years of data under the CMIP5 high-emission scenario. Ample calibration samples made rigorous testing possible, enabling us to evaluate the effect of empirical–statistical model configurations and predictor choices and to assess the stationarity of the statistical models by investigating their sensitivity to different calibration intervals. The skill of the statistical models was evaluated in terms of their ability to reproduce the interannual correlation and long-term trends in seasonal 2-m temperature T2m, wet-day frequency fw, and wet-day mean precipitation μ. We found that different 30-yr calibration intervals often resulted in differing statistical models, depending on the specific choice of years. The hybrid downscaling approach allowed us to emulate seasonal mean regional climate model output with a high spatial resolution (0.05° latitude and 0.1° longitude grid) for up to 100 GCM runs while circumventing the issue of short calibration time, and it provides a robust set of empirically downscaled GCM runs.

scholarly journals Separating Dynamic and Thermodynamic Impacts of Climate Change on Daytime Convective Development over Land

2019 ◽  
Vol 32 (16) ◽  
pp. 5213-5234 ◽  
Author(s):  
Wojciech W. Grabowski ◽  
Andreas F. Prein
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Deep Convection ◽  
Convective Available Potential Energy ◽  
Future Research ◽  
Small Scale ◽  
Moist Convection ◽  
The Impact

AbstractClimate change affects the dynamics and thermodynamics of moist convection. Changes in the dynamics concern, for instance, an increase of convection strength due to increases of convective available potential energy (CAPE). Thermodynamics involve increases in water vapor that the warmer atmosphere can hold and convection can work with. Small-scale simulations are conducted to separate these two components for daytime development of unorganized convection over land. The simulations apply a novel modeling technique referred to as the piggybacking (or master–slave) approach and consider the global climate model (GCM)-predicted change of atmospheric temperature and moisture profiles in the Amazon region at the end of the century under a business-as-usual scenario. The simulations show that the dynamic impact dominates because changes in cloudiness and rainfall come from cloud dynamics considerations, such as the change in CAPE and convective inhibition (CIN) combined with the impact of environmental relative humidity (RH) on deep convection. The small RH reduction between the current and future climate significantly affects the mean surface rain accumulation as it changes from a small reduction to a small increase when the RH decrease is eliminated. The thermodynamic impact on cloudiness and precipitation is generally small, with the extreme rainfall intensifying much less than expected from an atmospheric moisture increase. These results are discussed in the context of previous studies concerning climate change–induced modifications of moist convection. Future research directions applying the piggybacking method are discussed.

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-Resolution Climate Change Impact Analysis on Expected Future Water Availability in the Upper Jordan Catchment and the Middle East

2014 ◽  
Vol 15 (4) ◽  
pp. 1517-1531 ◽  
Author(s):  
Gerhard Smiatek ◽  
Harald Kunstmann ◽  
Andreas Heckl
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Water Availability ◽  
Impact Analysis ◽  
River Flow ◽  
Climate Model ◽  
Mesoscale Model ◽  
Global Climate Model ◽  
Full Range ◽  
The Impact

Abstract The impact of climate change on the future water availability of the upper Jordan River (UJR) and its tributaries Dan, Snir, and Hermon located in the eastern Mediterranean is evaluated by a highly resolved distributed approach with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) run at 18.6- and 6.2-km resolution offline coupled with the Water Flow and Balance Simulation Model (WaSiM). The MM5 was driven with NCEP reanalysis for 1971–2000 and with Hadley Centre Coupled Model, version 3 (HadCM3), GCM forcings for 1971–2099. Because only one regional–global climate model combination was applied, the results may not give the full range of possible future projections. To describe the Dan spring behavior, the hydrological model was extended by a bypass approach to allow the fast discharge components of the Snir to enter the Dan catchment. Simulation results for the period 1976–2000 reveal that the coupled system was able to reproduce the observed discharge rates in the partially karstic complex terrain to a reasonable extent with the high-resolution 6.2-km meteorological input only. The performed future climate simulations show steadily rising temperatures with 2.2 K above the 1976–2000 mean for the period 2031–60 and 3.5 K for the period 2070–99. Precipitation trends are insignificant until the middle of the century, although a decrease of approximately 12% is simulated. For the end of the century, a reduction in rainfall ranging between 10% and 35% can be expected. Discharge in the UJR is simulated to decrease by 12% until 2060 and by 26% until 2099, both related to the 1976–2000 mean. The discharge decrease is associated with a lower number of high river flow years.

Revisiting the Krakatau 1883 Volcanic Aerosol Dispersal 

2021 ◽  
Author(s):  
Rafael Castro ◽  
Tushar Mittal ◽  
Stephen Self
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Volcanic Eruptions ◽  
Climate Impact ◽  
Volcanic Plume ◽  
Quasi Biennial Oscillation ◽  
Aerosol Cloud ◽  
Pinatubo Eruption ◽  
The Impact

<p>The 1883 Krakatau eruption is one of the most well-known historical volcanic eruptions due to its significant global climate impact as well as first recorded observations of various aerosol associated optical and physical phenomena. Although much work has been done on the former by comparison of global climate model predictions/ simulations with instrumental and proxy climate records, the latter has surprisingly not been studied in similar detail. In particular, there is a wealth of observations of vivid red sunsets, blue suns, and other similar features, that can be used to analyze the spatio-temporal dispersal of volcanic aerosols in summer to winter 1883. Thus, aerosol cloud dispersal after the Krakatau eruption can be estimated, bolstered by aerosol cloud behavior as monitored by satellite-based instrument observations after the 1991 Pinatubo eruption. This is one of a handful of large historic eruptions where this analysis can be done (using non-climate proxy methods). In this study, we model particle trajectories of the Krakatau eruption cloud using the Hysplit trajectory model and compare our results with our compiled observational dataset (principally using Verbeek 1884, the Royal Society report, and Kiessling 1884).</p><p>In particular, we explore the effect of different atmospheric states - the quasi-biennial oscillation (QBO) which impacts zonal movement of the stratospheric volcanic plume - to estimate the phase of the QBO in 1883 required for a fast-moving westward cloud. Since this alone is unable to match the observed latitudinal spread of the aerosols, we then explore the impact of an  umbrella cloud (2000 km diameter) that almost certainly formed during such a large eruption. A large umbrella cloud, spreading over ~18 degrees within the duration of the climax of the eruption (6-8 hours), can lead to much quicker latitudinal spread than a point source (vent). We will discuss the results of the combined model (umbrella cloud and correct QBO phase) with historical accounts and observations, as well as previous work on the 1991 Pinatubo eruption. We also consider the likely impacts of water on aerosol concentrations and the relevance of this process for eruptions with possible significant seawater interactions, like Krakatau. We posit that the role of umbrella clouds is an under-appreciated, but significant, process for beginning to model the climatic impacts of large volcanic eruptions.</p>

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.

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