Parameterizing gravity waves in the DYNAMICO-Saturn Global Climate Model to understand Saturn's equatorial oscillation

2020 ◽  
Author(s):  
Deborah Bardet ◽  
Aymeric Spiga ◽  
Sandrine Guerlet ◽  
Ehouarn Millour ◽  
François Lott

<p>To address questions about the driving mechanisms of Saturn's equatorial oscillation, our team at the Laboratoire de Météorologie Dynamique built the DYNAMICO-Saturn Global Climate Model to study tropospheric dynamics, tropospheric waves activity (Spiga et al. 2020) and equatorial stratospheric dynamics (Bardet et al. 2020) of Saturn. Previous studies (Guerlet et al. 2014, Spiga et al. 2020, Cabanes et al. 2020) have shown that our model produces consistent thermal structure and seasonal variability compared to Cassini CIRS measurements, mid-latitude eddy-driven tropospheric eastward and westward jets commensurate to those observed and following the zonostrophic regime, and planetary-scale waves such as Rossby-gravity (Yanai), Rossby and Kelvin waves in the tropical channel. Extending the model top toward the upper stratosphere allowed our model to produce an almost semi-annual equatorial oscillation with opposite eastward and westward phases. Associated temperature anomalies have a similar behavior than the Cassini/CIRS observations, but the amplitude of the temperature oscillation is twice smaller than the observed one. The absence of sub-grid-scale waves in the model produces an imbalance in eastward- and westward-wave forcing on the mean flow and could be an explanation to the irregularity in both the oscillating period and the downward rate propagation of the resolved Saturn equatorial oscillation.</p> <p>To explore the impact of those small-scale waves on the spontaneous equatorial oscillation emerging in the DYNAMICO-Saturn GCM (Bardet et al. 2020), we add a sub-grid-scale non-orographic gravity waves drag parameterization in our model.<br />This parameterization is directly adapted from the stochastic terrestrial model of Lott et al. (2012). This formalism represents a broadband gravity wave spectrum, using the superposition of a large statistical set of monochromatic waves. As the time scale of the life cycles of gravity waves is much longer than the time step of our GCM, our parametrization can launch a few waves whose characteristics are randomly chosen at each time step. This stochastic gravity waves drag parameterization is applied in DYNAMICO-Saturn on all points of the horizontal grid.</p> <p>A key parameter used in the non-orographic gravity waves drag parameterization is the maximum value of the Eliassen-Palm flux. The Eliassen Palm flux represents the momentum carried by waves that could be transferred to the mean flow. This value has never been measured in Saturn's atmosphere and it represents an important degree of freedom in the parameterization of gravity waves.</p> <p>We performed several test simulations, lasting two Saturn years whose initial state is derived from Bardet et al (2020), with an horizontal resolution of 1/2° in longitude/latitude and a vertical resolution ranging between 3 bar to 1 μbar. For these test simulations, the maximum value of the Eliassen-Palm fulx is set to 10<sup>-6</sup>, 10<sup>-5</sup>, 10<sup>-4</sup> and 10<sup>-3</sup> kg m<sup>-1</sup> s<sup>-2</sup>. </p> <p>Preliminary results show that the appropriate value of our main parameter is between 10<sup>-5</sup> and 10<sup>-4</sup> kg m<sup>-1</sup> s<sup>-2</sup>. Eliassen-Palm flux value of 10<sup>-3</sup> kg m<sup>-1</sup> s<sup>-2</sup> demonstrates a too large impact: the equatorial oscillation is entirely vanished is this configuration. The simulation using the value of 10<sup>-6</sup> kg m<sup>-1</sup> s<sup>-2</sup> is equivalent to the control simulation without the gravity waves drag parameterization.  </p> <p>The next step is to test other parameters, as phase velocity of the gravity waves, horizontal wavenumber, to understand how gravity waves impact the equatorial oscillation.</p>

2017 ◽  
Vol 10 (3) ◽  
pp. 1383-1402 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  

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).


2020 ◽  
Vol 33 (5) ◽  
pp. 1659-1675 ◽  
Author(s):  
Min-Seop Ahn ◽  
Daehyun Kim ◽  
Yoo-Geun Ham ◽  
Sungsu Park

AbstractThe Maritime Continent (MC) region is known as a “barrier” in the life cycle of the Madden–Julian oscillation (MJO). During boreal winter, the MJO detours the equatorial MC land region southward and propagates through the oceanic region. Also, about half of the MJO events that initiate over the Indian Ocean cease around the MC. The mechanism through which the MC affects MJO propagation, however, has remained unanswered. The current study investigates the MJO–MC interaction with a particular focus on the role of MC land convection. Using a global climate model that simulates both mean climate and MJO realistically, we performed two sensitivity experiments in which updraft plume radius is set to its maximum and minimum value only in the MC land grid points, making convective top deeper and shallower, respectively. Our results show that MC land convection plays a key role in shaping the 3D climatological moisture distribution around the MC through its local and nonlocal effects. Shallower and weaker MC land convection results in a steepening of the vertical and meridional mean moisture gradient over the MC region. The opposite is the case when MC land convection becomes deeper and stronger. The MJO’s eastward propagation is enhanced (suppressed) with the steeper (lower) mean moisture gradient. The moist static energy (MSE) budget of the MJO reveals the vertical and meridional advection of the mean MSE by MJO wind anomalies as the key processes that are responsible for the changes in MJO propagation characteristics. Our results pinpoint the critical role of the background moisture gradient on MJO propagation.


2020 ◽  
Author(s):  
Nikolai M. Gavrilov ◽  
Sergej P. Kshevetskii

<p>Acoustic-gravity waves (AGWs) measuring at big heights may be generated in the troposphere and propagate upwards. A high-resolution three-dimensional numerical model was developed for simulating nonlinear AGWs propagating from the ground to the upper atmosphere. The model algorithms are based on the finite-difference analogues of the main conservation laws. This methodology let us obtaining the physically correct generalized wave solutions of the nonlinear equations. Horizontally moving sinusoidal structures of vertical velocity on the ground are used for the AGW excitation in the model. Numerical simulations were made in an atmospheric region having horizontal dimensions up to several thousand kilometers and the height extention up to 500 km. Vertical distributions of the mean temperature, density, molecular viscosity and thermal conductivity are specified using standard models of the atmosphere.</p><p>Simulations were made for different horizontal wavelengths, amplitudes and speeds of the wave sources at the ground. After “switch on” the tropospheric wave source, an initial AGW pulse very quickly (for several minutes) could propagate to heights up to 100 km and above. AGW amplitudes increase with height and waves may break down in the middle and upper atmosphere. Wave instability and dissipation may lead to formations of wave accelerations of the mean flow and to producing wave-induced jet flows in the middle and upper atmosphere. Nonlinear interactions may lead to instabilities of the initial wave and to the creation of smaller-scale perturbations. These perturbations may increase temperature and wind gradients and could enhance the wave energy dissipation.</p><p>In this study, the wave sources contain a superposition of two AGW modes with different periods, wavelengths and phase speeds. Longer-period AGW modes served as the background conditions for the shorter-period wave modes. Thus, the larger-scale AGWs can modulate amplitudes of small-scale waves. In particular, interactions of two wave modes could sharp vertical temperature gradients and make easier the wave breaking and generating  turbulence. On the other hand, small-wave wave modes might increase dissipation and modify the larger-scale modes.This study was partially supported by the Russian Basic Research Foundation (# 17-05-00458).</p>


Author(s):  
James B. Elsner ◽  
Thomas H. Jagger

All hurricanes are different. Statistics helps you characterize hurricanes from the typical to the extreme. In this chapter, we provide an introduction to classical (or frequentist) statistics. To get the most out of it, we again encourage you to open an R session and type in the code as you read along. Descriptive statistics are used to summarize your data. The mean and the variance are good examples. So is correlation. Data can be a set of weather records or output from a global climate model. Descriptive statistics provide answers to questions like does Jamaica experience more hurricanes than Puerto Rico? In Chapter 2, you learned some functions for summarizing your data, let us review. Recall that the data set H.txt is a list of hurricane counts by year making landfall in the United States (excluding Hawaii). To input the data and save them as a data object, type . . . > H = read. Table ("H.txt", header=TRUE) . . . Make sure the data file is located in your working directory. To check your working directory, type getwd (). Sometimes all you need are a few summary statistics from your data. You can obtain the mean and variance by typing . . . > mean (H$All); var (H$All) [1] 1.69375 [1] 2.10059 . . . Recall that the semicolon acts as a return so you can place multiple functions on the same text line. The sample mean is a measure of the central tendency and the sample variance is a measure of the spread. These are called the first-and second-moment statistics. Like all statistics, they are random variables. A random variable can be thought of as a quantity whose value is not fixed; it changes depending on the values in your sample. If you consider the number of hurricanes over a different sample of years, the sample mean will almost certainly be different. Same with the variance. The sample mean provides an estimate of the population mean (the mean over all past and future years).


2021 ◽  
Vol 164 (1-2) ◽  
Author(s):  
Bano Mehdi ◽  
Julie Dekens ◽  
Mathew Herrnegger

AbstractThe Ruhezamyenda catchment in Uganda includes a unique lake, Lake Bunyonyi, and is threatened by increasing social and environmental pressures. The COSERO hydrological model was used to assess the impact of climate change on future surface runoff and evapotranspiration in the Lake Bunyonyi catchment (381 km2). The model was forced with an ensemble of CMIP5 global climate model (GCM) simulations for the mid-term future (2041–2070) and for the far future (2071–2100), each with RCP4.5 and RCP8.5. In the Ruhezamyenda catchment, compared to 1971–2000, the median of all GCMs (for both RCPs) showed the mean monthly air temperature to increase by approximately 1.5 to 3.0 °C in the mid-term future and by roughly 2.0 to 4.5 °C in the far future. The mean annual precipitation is generally projected to increase, with future changes between − 25 and + 75% (RCP8.5). AET in the Lake Bunyonyi catchment was simulated to increase for the future by approximately + 8 mm/month in the median of all GCMs for RCP8.5 for the far future. The runoff for future periods showed much uncertainty, but with an overall increasing trend. A combination of no-regrets adaptation options in the five categories of: governance; communication and capacity development; water, soil, land management and livelihoods improvement; data management; and research, was identified and validated with stakeholders, who also identified additional adaptation actions based on the model results. This study contributes to improving scientific knowledge on the impacts of climate change on water resources in Uganda with the purpose to support adaptation.


2020 ◽  
Vol 59 (11) ◽  
pp. 1793-1807 ◽  
Author(s):  
Helene Birkelund Erlandsen ◽  
Kajsa M. Parding ◽  
Rasmus Benestad ◽  
Abdelkader Mezghani ◽  
Marie Pontoppidan

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.


2019 ◽  
Vol 12 (7) ◽  
pp. 2875-2897 ◽  
Author(s):  
Hideaki Kawai ◽  
Seiji Yukimoto ◽  
Tsuyoshi Koshiro ◽  
Naga Oshima ◽  
Taichu Tanaka ◽  
...  

Abstract. The development of the climate model MRI-ESM2 (Meteorological Research Institute Earth System Model version 2), which is planned for use in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) simulations, involved significant improvements to the representation of clouds from the previous version MRI-CGCM3 (Meteorological Research Institute Coupled Global Climate Model version 3), which was used in the CMIP5 simulations. In particular, the serious lack of reflection of solar radiation over the Southern Ocean in MRI-CGCM3 was drastically improved in MRI-ESM2. The score of the spatial pattern of radiative fluxes at the top of the atmosphere for MRI-ESM2 is better than for any CMIP5 model. In this paper, we set out comprehensively the various modifications related to clouds that contribute to the improved cloud representation and the main impacts on the climate of each modification. The modifications cover various schemes and processes including the cloud scheme, turbulence scheme, cloud microphysics processes, interaction between cloud and convection schemes, resolution issues, cloud radiation processes, interaction with the aerosol model, and numerics. In addition, the new stratocumulus parameterization, which contributes considerably to increased low-cloud cover and reduced radiation bias over the Southern Ocean, and the improved cloud ice fall scheme, which alleviates the time-step dependency of cloud ice content, are described in detail.


2019 ◽  
Vol 32 (16) ◽  
pp. 5213-5234 ◽  
Author(s):  
Wojciech W. Grabowski ◽  
Andreas F. Prein

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.


2008 ◽  
Vol 21 (23) ◽  
pp. 6341-6353 ◽  
Author(s):  
Jenny Brandefelt ◽  
Heiner Körnich

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.


2017 ◽  
Vol 30 (15) ◽  
pp. 5715-5728 ◽  
Author(s):  
Hiroaki Tatebe ◽  
Masao Kurogi ◽  
Hiroyasu Hasumi

Atmospheric responses and feedback to meridional ocean heat transport (OHT) have been investigated using a global climate model that is interactively connected with a high-resolution regional ocean model embedded in the western North Pacific. Compared with a global climate model without the regional model, the net heat supply into the Kuroshio–Oyashio Extension (KOE) region is increased as a result of the increase of the mean northward ocean heat transport (OHT) by the western boundary currents and mesoscale eddies. Resultant sea surface temperature (SST) rise sharpens the meridional SST gradient and reinforces the cross-frontal difference of the surface heat flux and thereby enhances lower-tropospheric baroclinicity. These changes cause northward deflection and strengthening of the wintertime storm track over the North Pacific, which leads to the Pacific–North American (PNA)-like pattern anticyclonic response of the mean westerly jet. The increase of the eddy northward atmospheric heat flux (AHF) associated with the enhanced storm-track activity is compensated by the decrease of the mean northward AHF. The changes of the atmospheric circulations reduce the mean northward OHT in the eastern North Pacific that compensates the increase of the mean northward OHT in the KOE region. The atmospheric responses, which have once been excited by the SST fronts in the KOE region, stabilize the trans–North Pacific OHT. The modeling results herein suggest that basinwide Bjerknes-like compensation works in air–sea coupled processes for the formation of the climatic mean state in the North Pacific.


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