Climate Impacts of Large-Scale Wind Farms as Parameterized in a Global Climate Model

2015 ◽  
Vol 28 (15) ◽  
pp. 6160-6180 ◽  
Author(s):  
Anna C. Fitch
Keyword(s):  
Large Scale ◽  
Wind Farm ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Wind Farms ◽  
Electricity Demand ◽  
Climate Impacts ◽  
Maximum Temperature ◽  
Installed Capacity

Abstract The local, regional, and global climate impacts of a large-scale global deployment of wind power in regionally high densities over land are investigated for a 60-yr period. Wind farms are represented as elevated momentum sinks as well as enhanced turbulence to represent turbine blade mixing in the Community Atmosphere Model, version 5 (CAM5), a global climate model. For a total installed capacity of 2.5 TW, to provide 16% of the world’s projected electricity demand in 2050, minimal impacts are found both regionally and globally on temperature, sensible and latent heat fluxes, cloud, and precipitation. A mean near-surface warming of 0.12 ± 0.07 K is seen within the wind farms, with a global-mean temperature change of −0.013 ± 0.015 K. Impacts on wind speed and turbulence are more pronounced but largely confined within the wind farm areas. Increasing the wind farm areas to provide an installed capacity of 10 TW, or 65% of the 2050 electricity demand, causes further impacts; however, they remain slight overall. Maximum temperature changes are less than 0.5 K in the wind farm areas. To provide 20 TW of installed capacity, or 130% of the 2050 electricity demand, impacts both within the wind farms and beyond become more pronounced, with a doubling in turbine density. However, maximum temperature changes remain less than 0.7 K. Representing wind farms instead as an increase in surface roughness generally produces similar mean results; however, maximum changes increase, and influences on wind and turbulence are exaggerated. Overall, wind farm impacts are much weaker than those expected from greenhouse gas emissions, with very slight global-mean climate impacts.

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 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 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 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.

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.

scholarly journals Parameterization of subgrid plume dilution for use in large-scale atmospheric simulations

2010 ◽  
Vol 10 (5) ◽  
pp. 2551-2560 ◽  
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 ◽  
Cross Sectional ◽  
Plume Dynamics ◽  
Eddy Simulation ◽  
Subgrid Model ◽  
Diffusion Parameters ◽  
Sectional Shape

Abstract. A new model of plume dynamics has been developed for use as a subgrid model of plume dilution in a large-scale atmospheric simulation. The model uses mean wind, shear, and diffusion parameters derived from the local large-scale variables to advance the plume cross-sectional shape and area in time. Comparisons with a large eddy simulation of aircraft emission plume dynamics, with an analytical solution to the dynamics of a sheared Gaussian plume, and with measurements of aircraft exhaust plume dilution at cruise altitude show good agreement with these previous studies. We argue that the model also provides a reasonable approximation of line-shaped contrail dilution and give an example of how it can be applied in a global climate model.

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 A Mathematical Framework for Analysis of Water Tracers. Part II: Understanding Large-Scale Perturbations in the Hydrological Cycle due to CO2 Doubling

2016 ◽  
Vol 29 (18) ◽  
pp. 6765-6782 ◽  
Author(s):  
Hansi K. A. Singh ◽  
Cecilia M. Bitz ◽  
Aaron Donohoe ◽  
Jesse Nusbaumer ◽  
David C. Noone
Keyword(s):  
Moisture Transport ◽  
Large Scale ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Model ◽  
Mathematical Framework ◽  
Surface Evaporation ◽  
And Shifts

Abstract The aerial hydrological cycle response to CO2 doubling from a Lagrangian, rather than Eulerian, perspective is evaluated using information from numerical water tracers implemented in a global climate model. While increased surface evaporation (both local and remote) increases precipitation globally, changes in transport are necessary to create a spatial pattern where precipitation decreases in the subtropics and increases substantially at the equator. Overall, changes in the convergence of remotely evaporated moisture are more important to the overall precipitation change than changes in the amount of locally evaporated moisture that precipitates in situ. It is found that CO2 doubling increases the fraction of locally evaporated moisture that is exported, enhances moisture exchange between ocean basins, and shifts moisture convergence within a given basin toward greater distances between moisture source (evaporation) and sink (precipitation) regions. These changes can be understood in terms of the increased residence time of water in the atmosphere with CO2 doubling, which corresponds to an increase in the advective length scale of moisture transport. As a result, the distance between where moisture evaporates and where it precipitates increases. Analyses of several heuristic models further support this finding.

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

2015 ◽  
Vol 3 (12) ◽  
pp. 7231-7245
Author(s):  
F. F. Hattermann ◽  
S. Huang ◽  
O. Burghoff ◽  
P. Hoffmann ◽  
Z. W. Kundzewicz
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Large Scale ◽  
Considerable Increase ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
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 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 large scale climate driver, while many studies report that GCM models are often the largest source of uncertainty in impact modeling. Here we show that a much broader set of global and regional climate model combinations as climate driver shows trends which are in line with the original results and even give a stronger increase of damages.

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