scholarly journals Northern Hemisphere Stationary Waves in Future Climate Projections

2008 ◽  
Vol 21 (23) ◽  
pp. 6341-6353 ◽  
Author(s):  
Jenny Brandefelt ◽  
Heiner Körnich
Keyword(s):  
Northern Hemisphere ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Stationary Wave ◽  
Climate Projections ◽  
Stationary Waves ◽  
Mean Flow ◽  
Wave Response

Abstract The response of the atmospheric large-scale circulation to an enhanced greenhouse gas (GHG) forcing varies among coupled global climate model (CGCM) simulations. In this study, 16 CGCM simulations of the response of the climate system to a 1% yr−1 increase in the atmospheric CO2 concentration to quadrupling are analyzed with focus on Northern Hemisphere winter. A common signal in 14 out of the 16 simulations is an increased or unchanged stationary wave amplitude. A majority of the simulations may be categorized into one of three groups based on the GHG-induced changes in the atmospheric stationary waves. The response of the zonal mean barotropic wind is similar within each group. Fifty percent of the simulations belong to the first group, which is categorized by a stationary wave with five waves encompassing the entire NH and a strengthening of the zonal mean barotropic wind. The second and third groups, respectively consisting of three and two simulations, are characterized by a broadening and a northward shift of the zonal mean barotropic wind, respectively. A linear model of barotropic vorticity is employed to study the importance of these mean flow changes to the stationary wave response. The linear calculations indicate that the GHG-induced mean wind changes explain 50%, 4%, and 37% of the stationary wave changes in each group, respectively. Thus, for the majority of simulations the zonal mean wind changes do significantly explain the stationary wave response.

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 Revisiting the Role of Mountains in the Northern Hemisphere Winter Atmospheric Circulation

2021 ◽  
Author(s):  
R.H. White ◽  
J.M. Wallace ◽  
D.S. Battisti
Keyword(s):  
Northern Hemisphere ◽  
Climate Model ◽  
Stationary Wave ◽  
Stationary Waves ◽  
Mean Flow ◽  
Meridional Heat Transport ◽  
Hemisphere Winter ◽  
Intractable Problem ◽  
The Impact

AbstractThe impact of global orography on Northern Hemisphere wintertime climate is revisited using the Whole Atmosphere Community Climate Model, WACCM6. A suite of experiments explores the roles of both resolved orography, and the parameterized effects of unresolved orographic drag (hereafter parameterized orography), including gravity waves and boundary layer turbulence. Including orography reduces the extra-tropical tropospheric and stratospheric zonal mean zonal wind, , by up to 80%; this is substantially greater than previous estimates. Ultimately parameterized orography accounts for 60-80% of this reduction; however, away from the surface most of the forcing of by parameterized orography is accomplished by resolved planetary waves. We propose that a catalytic wave-mean-flow positive feedback in the stratosphere makes the stratospheric flow particularly sensitive to parameterized orography. Orography and land-sea contrast contribute approximately equally to the strength of the mid-latitude stationary waves in the free troposphere, although orography is the dominant cause of the strength of the Siberian high and Aleutian low at the surface, and of the position of the Icelandic low. We argue that precisely quantifying the role of orography on the observed stationary waves is an almost intractable problem, and in particular should not be approached with linear stationary wave models in which is prescribed. We show that orography has less impact on stationary waves, and therefore on , on a backwards rotating Earth. Lastly, we show that atmospheric meridional heat transport shows remarkable constancy across our simulations, despite vastly different climates and stationary wave strengths.

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 Lengthening of summer season over the Northern Hemisphere under 1.5°C and 2.0°C global warming

2021 ◽  
Author(s):  
Bo-Joung Park ◽  
Seung-Ki Min ◽  
Evan Weller
Keyword(s):  
Global Warming ◽  
East Asia ◽  
Northern Hemisphere ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Late Summer ◽  
Industrial Condition ◽  
Summer Season ◽  
Hot Days

Abstract Summer season has lengthened substantially across Northern Hemisphere (NH) land over the past decades, which has been attributed to anthropogenic greenhouse gas increases. This study examines additional future changes in summer season onset and withdrawal under 1.5℃ and 2.0℃ global warming conditions using multiple atmospheric global climate model (AGCM) large-ensemble simulations from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project. Five AGCMs provide more than 100 runs of 10-year length for three experiments: All-Hist (current decade: 2006-2015), Plus15, and Plus20 (1.5℃ and 2.0℃ above pre-industrial condition, respectively). Results show that with 1.5℃ and 2.0℃ warmer conditions summer season will become longer by a few days to weeks over entire NH lands, with slightly larger contributions by delay in withdrawal due to stronger warming in late summer. Stronger changes are observed more in middle latitudes than high latitudes and largest expansion (up to three weeks) is found over East Asia and the Mediterranean. Associated changes in summer-like day frequency is further analyzed focusing on the extended summer edges. The hot days occur more frequently in lower latitudes including East Asia, USA and Mediterranean, in accord with largest summer season lengthening. Further, difference between Plus15 and Plus20 indicates that summer season lengthening and associated increases in hot days can be reduced significantly if warming is limited to 1.5℃. Overall, similar results are obtained from CMIP5 coupled GCM simulations (based on RCP8.5 scenario experiments), suggesting a weak influence of air-sea coupling on summer season timing changes.

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 Downscaling Atmosphere-Ocean Global Climate Model Precipitation Simulations over Africa Using Bias-Corrected Lateral and Lower Boundary Conditions

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 493 ◽  
Author(s):  
Leonard Druyan ◽  
Matthew Fulakeza
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Lower Boundary ◽  
Climate Projections ◽  
African Easterly Jet ◽  
Modèle Simulation ◽  
Goddard Institute ◽  
Bias Corrections

A prequel study showed that dynamic downscaling using a regional climate model (RCM) over Africa improved the Goddard Institute for Space Studies Atmosphere-Ocean Global Climate Model (GISS AOGCM: ModelE) simulation of June–September rainfall patterns over Africa. The current study applies bias corrections to the lateral and lower boundary data from the AOGCM driving the RCM, based on the comparison of a 30-year simulation to the actual climate. The analysis examines the horizontal pattern of June–September total accumulated precipitation, the time versus latitude evolution of zonal mean West Africa (WA) precipitation (showing monsoon onset timing), and the latitude versus altitude cross-section of zonal winds over WA (showing the African Easterly Jet and the Tropical Easterly Jet). The study shows that correcting for excessively warm AOGCM Atlantic sea-surface temperatures (SSTs) improves the simulation of key features, whereas applying 30-year mean bias corrections to atmospheric variables driving the RCM at the lateral boundaries does not improve the RCM simulations. We suggest that AOGCM climate projections for Africa should benefit from downscaling by nesting an RCM that has demonstrated skill in simulating African climate, driven with bias-corrected SST.

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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