Instabilities of low-latitude easterly jets in the presence of moist convection and topography and related cyclogenesis, in a simple atmospheric model

Abstract. The thermospheric temperatures from low and equatorial latitudes during geomagnetically disturbed periods are known to exhibit significant deviations from atmospheric model predictions. Also, the oscillatory features seen in the observations are not accounted for by the models. A simple relation has been established between the difference in the observed and model-predicted temperatures and the rate of change of Dst, the magnetic index representing the ring current variabilities. Using this relation, a correction term has been added to the latest MSIS-90 model algorithm and almost all the observed variations in neutral temperatures spectroscopically determined from Mt.Abu, a low-latitude station in India, are successfully reproduced for two moderate geomagnetic storms.Key words. Low-latitude thermosphere · MSIS model · Stormtime model predictions · FP spectroscopic temperatures

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Predictability in Wet and Dry Convective Turbulence

Journal of the Atmospheric Sciences ◽

10.1175/2007jas2307.1 ◽

2008 ◽

Vol 65 (1) ◽

pp. 220-234 ◽

Cited By ~ 4

Author(s):

K. Spyksma ◽

P. Bartello

Keyword(s):

Convective Motion ◽

Atmospheric Model ◽

Moist Convection ◽

Error Growth ◽

Heating And Cooling ◽

Extra Energy ◽

Moisture Effects ◽

Large Ensembles ◽

Error Energy ◽

Dry Convection

Abstract There is a growing interest in understanding the role that moisture plays in atmospheric dynamics, particularly in its effect on predictability. Current research indicates that when moisture effects are added to an atmospheric model, the error growth produced by the new moist dynamics reduces the predictability times, especially at the scales of moist convection. The issue of moist convection’s effect on predictability is addressed herein. By performing high-resolution large-ensemble runs, it is shown that although nonprecipitating moist convection is less predictable than dry convection resulting from the same forcing, this effect can be explained by the energy injected into the system through the latent heating and cooling arising from the convective motion. This extra energy is spread evenly over most scales of the convective dynamics. When the predictability times are scaled to account for the extra kinetic energy, and the resulting earlier growth of error energy, wet and dry convection have very similar error growth characteristics. Sensitivity tests are performed to ensure that the results from the large ensembles have converged and that they are consistent with either changing resolution, diffusion levels, initial error energy length scales, or forcing amplitude.

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Structure of the Madden–Julian Oscillation in the Superparameterized CAM

Journal of the Atmospheric Sciences ◽

10.1175/2009jas3030.1 ◽

2009 ◽

Vol 66 (11) ◽

pp. 3277-3296 ◽

Cited By ~ 140

Author(s):

James J. Benedict ◽

David A. Randall

Keyword(s):

Boundary Layer ◽

General Circulation ◽

Deep Convection ◽

Circulation Model ◽

Grid Cell ◽

Atmospheric Model ◽

Space Time ◽

Madden Julian Oscillation ◽

Moist Convection ◽

Time Structures

Abstract The detailed dynamic and thermodynamic space–time structures of the Madden–Julian oscillation (MJO) as simulated by the superparameterized Community Atmosphere Model version 3.0 (SP-CAM) are analyzed. Superparameterization involves substituting conventional boundary layer, moist convection, and cloud parameterizations with a configuration of cloud-resolving models (CRMs) embedded in each general circulation model (GCM) grid cell. Unlike most GCMs that implement conventional parameterizations, the SP-CAM displays robust atmospheric variability on intraseasonal space and time (30–60 days) scales. The authors examine a 19-yr SP-CAM simulation based on the Atmospheric Model Intercomparison Project protocol, forced by prescribed sea surface temperatures. Overall, the space–time structures of MJO convective disturbances are very well represented in the SP-CAM. Compared to observations, the model produces a similar vertical progression of increased moisture, warmth, and heating from the boundary layer to the upper troposphere as deep convection matures. Additionally, important advective and convective processes in the SP-CAM compare favorably with those in observations. A deficiency of the SP-CAM is that simulated convective intensity organized on intraseasonal space–time scales is overestimated, particularly in the west Pacific. These simulated convective biases are likely due to several factors including unrealistic boundary layer interactions, a lack of weakening of the simulated disturbance over the Maritime Continent, and mean state differences.

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Spontaneous Generated Convective Anticyclones in Low Latitude --- A Model for the Great Red Spot

10.21203/rs.3.rs-351661/v3 ◽

2021 ◽

Author(s):

Tao Cai ◽

Kwing L. Chan ◽

Kim-Chiu Chow

Keyword(s):

Internal Heat ◽

Critical Value ◽

Driving Mechanism ◽

Moist Convection ◽

Low Latitude ◽

Deep Model ◽

Merging Process ◽

Long Time ◽

Rotating Turbulent Flow ◽

Jovian Atmosphere

Abstract The Great Red Spot at about latitude 22oS of Jupiter has been observed for hundreds of years, yet the driving mechanism on the formation of this giant anticyclone still remains unclear. Two scenarios were proposed to explain its formation. One is a shallow model suggesting that it might be a weather feature formed through a merging process of small shallow storms generated by moist convection, while the other is a deep model suggesting that it might be a deeply rooted anticyclone powered by the internal heat of Jupiter. In this work, we present numerical simulations showing that the Great Red Spot could be naturally generated in a deep rotating turbulent flow and survive for a long time, when the convective Rossby number is smaller than a certain critical value. From this critical value, we predict that the Great Red Spot extends at least about 500 kilometers deep into the Jovian atmosphere. Our results demonstrate that the Great Red Spot is likely to be a feature deep-seated in the Jovian atmosphere.

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Spontaneous Generated Convective Anticyclones in Low Latitude --- A Model for the Great Red Spot

10.21203/rs.3.rs-351661/v1 ◽

2021 ◽

Author(s):

Tao Cai ◽

Kwing L. Chan ◽

Kim-Chiu Chow

Keyword(s):

Internal Heat ◽

Critical Value ◽

Driving Mechanism ◽

Moist Convection ◽

Low Latitude ◽

Deep Model ◽

Merging Process ◽

Long Time ◽

Rotating Turbulent Flow ◽

Jovian Atmosphere

Abstract The Great Red Spot at about latitude 22oS of Jupiter has been observed for hundreds of years, yet the driving mechanism on the formation of this giant anticyclone still remains unclear. Two scenarios were proposed to explain its formation. One is a shallow model suggesting that it might be a weather feature formed through a merging process of small shallow storms generated by moist convection, while the other is a deep model suggesting that it might be a deeply rooted anticyclone powered by the internal heat of Jupiter. In this work, we present numerical simulations showing that the Great Red Spot could be naturally generated in a deep rotating turbulent flow and survive for a long time, when the convective Rossby number is smaller than a certain critical value. From this critical value, we predict that the Great Red Spot extends at least about 500 kilometers deep into the Jovian atmosphere. Our results demonstrate that the Great Red Spot is likely to be a feature deep-seated in the Jovian atmosphere.

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Horizontally Homogeneous Rotating Radiative–Convective Equilibria at GCM Resolution

Journal of the Atmospheric Sciences ◽

10.1175/2007jas2604.1 ◽

2008 ◽

Vol 65 (6) ◽

pp. 2003-2013 ◽

Cited By ~ 37

Author(s):

Isaac M. Held ◽

Ming Zhao

Keyword(s):

Surface Temperature ◽

Atmospheric Model ◽

Tropical Storm ◽

Sea Surface ◽

Tropical Storms ◽

Average Intensity ◽

Moist Convection ◽

Coriolis Parameter ◽

Global Models ◽

Large Domain

Abstract Rotating radiative–convective equilibrium, using the column physics and resolution of GCMs, is proposed as a useful framework for studying the tropical storm–like vortices produced by global models. These equilibria are illustrated using the column physics and dynamics of a version of the GFDL Atmospheric Model 2 (AM2) at resolutions of 220, 110, and 55 km in a large 2 × 104 km square horizontally homogeneous domain with fixed sea surface temperature and uniform Coriolis parameter. The large domain allows a number of tropical storms to exist simultaneously. Once equilibrium is attained, storms often persist for hundreds of days. The number of storms decreases as sea surface temperatures increase, while the average intensity increases. As the background rotation is decreased, the number of storms also decreases. At these resolutions and with this parameterization of convection, a dense collection of tropical storms is always the end state of moist convection in the cases examined.

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Convective Transition Statistics over Tropical Oceans for Climate Model Diagnostics: GCM Evaluation

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-19-0132.1 ◽

2020 ◽

Vol 77 (1) ◽

pp. 379-403 ◽

Cited By ~ 4

Author(s):

Yi-Hung Kuo ◽

J. David Neelin ◽

Chih-Chieh Chen ◽

Wei-Ting Chen ◽

Leo J. Donner ◽

...

Keyword(s):

Large Scale ◽

Climate Model ◽

Task Force ◽

Probability Distributions ◽

Atmospheric Model ◽

Fast Time ◽

Tropospheric Temperature ◽

Moist Convection ◽

Hourly Output ◽

Large Scale Flow

Abstract To assess deep convective parameterizations in a variety of GCMs and examine the fast-time-scale convective transition, a set of statistics characterizing the pickup of precipitation as a function of column water vapor (CWV), PDFs and joint PDFs of CWV and precipitation, and the dependence of the moisture–precipitation relation on tropospheric temperature is evaluated using the hourly output of two versions of the GFDL Atmospheric Model, version 4 (AM4), NCAR CAM5 and superparameterized CAM (SPCAM). The 6-hourly output from the MJO Task Force (MJOTF)/GEWEX Atmospheric System Study (GASS) project is also analyzed. Contrasting statistics produced from individual models that primarily differ in representations of moist convection suggest that convective transition statistics can substantially distinguish differences in convective representation and its interaction with the large-scale flow, while models that differ only in spatial–temporal resolution, microphysics, or ocean–atmosphere coupling result in similar statistics. Most of the models simulate some version of the observed sharp increase in precipitation as CWV exceeds a critical value, as well as that convective onset occurs at higher CWV but at lower column RH as temperature increases. While some models quantitatively capture these observed features and associated probability distributions, considerable intermodel spread and departures from observations in various aspects of the precipitation–CWV relationship are noted. For instance, in many of the models, the transition from the low-CWV, nonprecipitating regime to the moist regime for CWV around and above critical is less abrupt than in observations. Additionally, some models overproduce drizzle at low CWV, and some require CWV higher than observed for strong precipitation. For many of the models, it is particularly challenging to simulate the probability distributions of CWV at high temperature.

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Short-lived storms inside long-lived cyclones: Simulations of the 2020 storm in the South Temperate Belt

10.5194/egusphere-egu21-10741 ◽

2021 ◽

Author(s):

Peio Iñurrigarro ◽

Ricardo Hueso ◽

Agustín Sanchez-Lavega ◽

Clyde Foster ◽

Jon Legarreta ◽

...

Keyword(s):

Large Scale ◽

Atmospheric Model ◽

Moist Convection ◽

Convective Storm ◽

The South ◽

Infrared Observations ◽

Convective Storms ◽

Methane Absorption ◽

Before And After ◽

Weak Winds

Convective storms on Jupiter usually develop in the cyclonic side of the jets or inside cyclones (Vasavada and Showman, 2005). On 31 May 2020 a convective storm developed inside a small cyclone (3&#186; in longitudinal extent) in the South Temperate Belt at planetographic latitude 30&#186;S. The storm outbreak was captured by amateur astronomer Clyde Foster becoming widely known as Clyde&#8217;s spot. The storm was observed 2.5 days later by JunoCam with images displaying an apparent cyclonic structure with two main lobes and high-clouds observable in the methane absorption band. Analysis of these observations show the storm in a decaying phase with associated weak winds. Observations over the following months combined with prior observations (2 years) obtained by JunoCam, HST, IRTF and amateur observers show the long-term evolution of the cyclone before and after the convective eruption. The short-lived storm made the cyclone to display large changes in morphology and colour but not in its size or latitude, except for small fluctuations around a mean latitude and mean drift rate. Ground-based infrared observations at 5 &#956;m show the region where the vortex was located characterized by a weakly warm radiance several months after the convective outbreak, indicating a relative clearing of clouds and haze. We have used the Explicit Planetary Isentropic-Coordinate (EPIC) numerical model (Dowling et. al., 1998) to simulate the cyclone and the effects of convective storms of different strengths and durations on it. These simulations were partially guided by our previous study of a similar convective storm in a different type of cyclone: an elongated structure known as the STB Ghost at the same latitude in 2018 (I&#241;urrigarro et. al., 2020). Both storms and cyclones were different in terms of their size, morphology and later evolution, but our simulations suggest that in both cases the convective eruptions were of similar power but with different lifetimes indicating that the energy source is water moist convection. We compare these storms and simulations with a similar convective storm observed in 1979 by Voyager 2 at 38&#186;S that quickly evolved into a Folded-Filamentary Region and investigate the outcome of convective storms at different latitudes from these simulations.References:Dowling et al., 1998. The Explicit Planetary Isentropic-Coordinate (EPIC) Atmospheric Model, Icarus, 132, 221-238.I&#241;urrigarro et al., 2020. Observations and numerical modelling of a convective disturbance in a large-scale cyclone in Jupiter&#8217;s South Temperate Belt, Icarus, 336, 113475.Vasavada and Showman, 2005. Jovian atmospheric dynamics: an update after Galileo and Cassini, Reports on Progress in Physics, 68, 1935-1996.

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Spontaneous Generated Convective Anticyclones in Low Latitude --- A Model for the Great Red Spot

10.21203/rs.3.rs-351661/v2 ◽

2021 ◽

Author(s):

Tao Cai ◽

Kwing L. Chan ◽

Kim-Chiu Chow

Keyword(s):

Internal Heat ◽

Critical Value ◽

Driving Mechanism ◽

Moist Convection ◽

Low Latitude ◽

Deep Model ◽

Merging Process ◽

Long Time ◽

Rotating Turbulent Flow ◽

Jovian Atmosphere

Abstract The Great Red Spot at about latitude 22oS of Jupiter has been observed for hundreds of years, yet the driving mechanism on the formation of this giant anticyclone still remains unclear. Two scenarios were proposed to explain its formation. One is a shallow model suggesting that it might be a weather feature formed through a merging process of small shallow storms generated by moist convection, while the other is a deep model suggesting that it might be a deeply rooted anticyclone powered by the internal heat of Jupiter. In this work, we present numerical simulations showing that the Great Red Spot could be naturally generated in a deep rotating turbulent flow and survive for a long time, when the convective Rossby number is smaller than a certain critical value. From this critical value, we predict that the Great Red Spot extends at least about 500 kilometers deep into the Jovian atmosphere. Our results demonstrate that the Great Red Spot is likely to be a feature deep-seated in the Jovian atmosphere.

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Radon activity in the lower troposphere and its impact on ionization rate: a global estimate using different radon emissions

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-11-3251-2011 ◽

2011 ◽

Vol 11 (1) ◽

pp. 3251-3300

Author(s):

K. Zhang ◽

J. Feichter ◽

J. Kazil ◽

H. Wan ◽

W. Zhuo ◽

...

Keyword(s):

Cosmic Rays ◽

Radioactive Decay ◽

Lower Troposphere ◽

Atmospheric Model ◽

Ionization Rate ◽

Aerosol Size Distribution ◽

Low Latitude ◽

Near Surface ◽

Global Estimate ◽

Global Atmospheric Model

Abstract. The radioactive decay of radon and its progeny can lead to ionization of air molecules and consequently influence aerosol size distribution. In order to provide a global estimate of the radon-related ionization rate, we use the global atmospheric model ECHAM5 to simulate transport and decay processes of the radioactive tracers. A global radon emission map is put together using regional fluxes reported recently in the literature. The near-surface radon concentrations simulated with this new map compare well with measurements. Radon-related ionization rate is calculated and compared to that caused by cosmic rays. The contribution of radon and its progeny clearly exceeds that of the cosmic rays in the mid- and low-latitude land areas in the surface layer. In winter, strong radon-related ionization coincides with low temperature in China, USA, and Russia, providing favorable condition for the formation of aerosol particles. This suggests that it is probably useful to include the radon-induced ionization in global models when investigating the interaction between aerosol and climate.

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