scholarly journals The Role of Large-Scale Feedbacks in Cumulus Convection Parameter Estimation

2016 ◽  
Vol 29 (11) ◽  
pp. 4099-4119 ◽  
Author(s):  
Shan Li ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Xiaosong Yang ◽  
Anthony Rosati ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Cumulus Convection ◽  
State Variables ◽  
Climate Drift ◽  
Convection Parameterization ◽  
Convection Parameter

Abstract Uncertainty in cumulus convection parameterization is one of the most important causes of model climate drift through interactions between large-scale background and local convection that use empirically set parameters. Without addressing the large-scale feedback, the calibrated parameter values within a convection scheme are usually not optimal for a climate model. This study first designs a multiple-column atmospheric model that includes large-scale feedbacks for cumulus convection and then explores the role of large-scale feedbacks in cumulus convection parameter estimation using an ensemble filter. The performance of convection parameter estimation with or without the presence of large-scale feedback is examined. It is found that including large-scale feedbacks in cumulus convection parameter estimation can significantly improve the estimation quality. This is because large-scale feedbacks help transform local convection uncertainties into global climate sensitivities, and including these feedbacks enhances the statistical representation of the relationship between parameters and state variables. The results of this study provide insights for further understanding of climate drift induced from imperfect cumulus convection parameterization, which may help improve climate modeling.

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 Uncertainty in Model Climate Sensitivity Traced to Representations of Cumulus Precipitation Microphysics

2016 ◽  
Vol 29 (2) ◽  
pp. 543-560 ◽  
Author(s):  
Ming Zhao ◽  
J.-C. Golaz ◽  
I. M. Held ◽  
V. Ramaswamy ◽  
S.-J. Lin ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Convective Precipitation ◽  
Climate Projections ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Convection Parameterization ◽  
Comparable Quality

Abstract Uncertainty in equilibrium climate sensitivity impedes accurate climate projections. While the intermodel spread is known to arise primarily from differences in cloud feedback, the exact processes responsible for the spread remain unclear. To help identify some key sources of uncertainty, the authors use a developmental version of the next-generation Geophysical Fluid Dynamics Laboratory global climate model (GCM) to construct a tightly controlled set of GCMs where only the formulation of convective precipitation is changed. The different models provide simulation of present-day climatology of comparable quality compared to the model ensemble from phase 5 of CMIP (CMIP5). The authors demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model’s convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere–land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and the current inability to find a clear observational constraint that favors one version of the authors’ model over the others, the implications of this ability to engineer climate sensitivity need to be considered when estimating the uncertainty in climate projections.

scholarly journals Evaluation of the atmospheric transport in a GCM using radon measurements: sensitivity to cumulus convection parameterization

2008 ◽  
Vol 8 (10) ◽  
pp. 2811-2832 ◽  
Author(s):  
K. Zhang ◽  
H. Wan ◽  
M. Zhang ◽  
B. Wang
Keyword(s):  
Vertical Distribution ◽  
Radon Concentration ◽  
Large Scale ◽  
Atmospheric Transport ◽  
Surface Concentration ◽  
Transport Processes ◽  
Cumulus Convection ◽  
Models Comparison ◽  
Convection Schemes ◽  
Convection Parameterization

Abstract. The radioactive species radon (222Rn) has long been used as a test tracer for the numerical simulation of large scale transport processes. In this study, radon transport experiments are carried out using an atmospheric GCM with a finite-difference dynamical core, the van Leer type FFSL advection algorithm, and two state-of-the-art cumulus convection parameterization schemes. Measurements of surface concentration and vertical distribution of radon collected from the literature are used as references in model evaluation. The simulated radon concentrations using both convection schemes turn out to be consistent with earlier studies with many other models. Comparison with measurements indicates that at the locations where significant seasonal variations are observed in reality, the model can reproduce both the monthly mean surface radon concentration and the annual cycle quite well. At those sites where the seasonal variation is not large, the model is able to give a correct magnitude of the annual mean. In East Asia, where radon simulations are rarely reported in the literature, detailed analysis shows that our results compare reasonably well with the observations. The most evident changes caused by the use of a different convection scheme are found in the vertical distribution of the tracer. The scheme associated with weaker upward transport gives higher radon concentration up to about 6 km above the surface, and lower values in higher altitudes. In the lower part of the atmosphere results from this scheme does not agree as well with the measurements as the other scheme. Differences from 6 km to the model top are even larger, although we are not yet able to tell which simulation is better due to the lack of observations at such high altitudes.

scholarly journals Oceanic Overturning and Heat Transport: The Role of Background Diffusivity

2019 ◽  
Vol 32 (3) ◽  
pp. 701-716 ◽  
Author(s):  
Magnus Hieronymus ◽  
Jonas Nycander ◽  
Johan Nilsson ◽  
Kristofer Döös ◽  
Robert Hallberg
Keyword(s):  
Heat Transport ◽  
Large Scale ◽  
Energy Transport ◽  
Climate Model ◽  
Potential Temperature ◽  
Meridional Heat Transport ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Meridional Overturning

The role of oceanic background diapycnal diffusion for the equilibrium climate state is investigated in the global coupled climate model CM2G. Special emphasis is put on the oceanic meridional overturning and heat transport. Six runs with the model, differing only by their value of the background diffusivity, are run to steady state and the statistically steady integrations are compared. The diffusivity changes have large-scale impacts on many aspects of the climate system. Two examples are the volume-mean potential temperature, which increases by 3.6°C between the least and most diffusive runs, and the Antarctic sea ice extent, which decreases rapidly as the diffusivity increases. The overturning scaling with diffusivity is found to agree rather well with classical theoretical results for the upper but not for the lower cell. An alternative empirical scaling with the mixing energy is found to give good results for both cells. The oceanic meridional heat transport increases strongly with the diffusivity, an increase that can only partly be explained by increases in the meridional overturning. The increasing poleward oceanic heat transport is accompanied by a decrease in its atmospheric counterpart, which keeps the increase in the planetary energy transport small compared to that in the ocean.

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 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 The “faint young Sun paradox”: further exploration of the role of dynamical heat-flux feed backs in maintaining global climate stability

1995 ◽  
Vol 41 (137) ◽  
pp. 87-90 ◽  
Author(s):  
Gyula I. Molnar ◽  
William J. Gutowski
Keyword(s):  
Heat Flux ◽  
Climate Model ◽  
Climate Modeling ◽  
Global Climate ◽  
Early Earth ◽  
Meridional Heat Transport ◽  
Climate Stability ◽  
The Earth ◽  
Physically Based

AbstractThe climate-modeling problems associated with global change underline the importance of understanding paleoclimates. The available evidence, which suggests that the Earth has never been fully glaciated, poses an especially serious problem for the early Earth when the Sun was about 20–30% fainter than today. In conventional explanations of this “faint young Sun paradox”, presumed very high levels of atmospheric greenhouse gases are required to prevent runaway glaciation of the Earth. Here we explore other possible explanations of this paradox. As an extension of our previous work on this subject, we illustrate how-dynamical beat-flux feed backs may have prevented the early Earth from freezing. Our simulations are carried out using a two-dimensional, seasonal-climate model with physically based parameterizations for atmospheric meridional-heat transport and sea ice. It ís found that dynamical heat-flux feed backs alone may have protected the Archean Earth against a runaway glaciation to a considerable degree.

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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