Seasonal modulation of trapped gravity waves and their imprints on trade wind clouds

Author(s):  
Claudia Stephan

<p>Idealized simulations have shown decades ago that shallow clouds generate internal gravity waves, which under certain atmospheric background conditions become trapped inside the troposphere and influence the development of clouds. These feedbacks, which occur at horizontal scales of up to several tens of km are neither resolved, nor parameterized in traditional global climate models (GCMs), while the newest generation of GCMs is starting to resolve them. The interactions between the convective boundary layer and trapped waves have almost exclusively been studied in highly idealized frameworks and it remains unclear to what degree this coupling affects the organization of clouds and convection in the real atmosphere. Here, the coupling between clouds and trapped waves is examined in storm-resolving simulations that span the entirety of the tropical Atlantic and are initialized and forced by meteorological analyses. The coupling between clouds and trapped waves is sufficiently strong to be detected in these simulations of full complexity.  Stronger upper-tropospheric westerly winds are associated with a stronger cloud-wave coupling. In the simulations this results in a highly-organized scattered cloud field with cloud spacings of about 19 km, matching the dominant trapped wavelength. Based on the large-scale atmospheric state wave theory can reliably predict the regions and times where cloud-wave feedbacks become relevant to convective organization. Theory, the simulations and satellite imagery imply a seasonal cycle in the trapping of gravity waves. </p>

2020 ◽  
Vol 77 (9) ◽  
pp. 2993-3009
Author(s):  
Claudia Christine Stephan

Abstract Shallow convection over the oceans is responsible for the largest uncertainties in climate projections. Idealized simulations have shown decades ago that shallow clouds generate internal gravity waves, which under certain atmospheric background conditions become trapped inside the troposphere and influence the development of clouds. These feedbacks, which occur at horizontal scales of up to several tens of kilometers. are neither resolved nor parameterized in traditional global climate models (GCMs), while the newest generation of GCMs (grid spacings < 5 km) is starting to resolve them. The interactions between the convective boundary layer and trapped waves have almost exclusively been studied in highly idealized frameworks and it remains unclear to what degree this coupling affects the organization of clouds in the real atmosphere or in the new generation of GCMs. Here, the coupling between clouds and trapped waves is examined in 2.5-km simulations that span the entirety of the tropical Atlantic and are initialized and forced with meteorological analyses. The coupling between clouds and trapped waves is sufficiently strong to be detected in these simulations of full complexity. Stronger upper-tropospheric westerly winds are associated with a stronger cloud–wave coupling. In the simulations this results in a highly organized scattered cloud field with cloud spacings of about 19 km, matching the dominant trapped wavelength. Based on the large-scale atmospheric state, wave theory can reliably predict the regions and times where cloud–wave feedbacks become relevant to convective organization. Theory, the simulations, and satellite imagery imply a seasonal cycle in the trapping of gravity waves.


2020 ◽  
Author(s):  
Harald Rieder ◽  
Petr Šácha ◽  
Roland Eichinger ◽  
Aleš Kuchař ◽  
Nadja Samtleben ◽  
...  

<p>In the atmosphere, internal gravity waves (GWs) are a naturally occurring and ubiquitous, though intermittent phenomenon. In addition, GWs (especially orographic; OGWs) are asymmetrically distributed around the globe. In current generation global climate models (GCMs), GWs are usually smaller than the model grid resolution and the majority of their spectrum therefore must be parameterized. To some extent, the intermittency and asymmetry of a spatial distribution of the resulting OGW drag (OGWD) is present also in GCMs. As the GW parameterization schemes in GCMs are usually tuned to get the zonal mean climatology of particular features right, an important question emerges: what kind of influence do GW parameterizations have on the individual models atmosphere locally? Here we focus on answering this question regarding the impact of spatiotemporally intermittent OGW forcing in the extra-tropical lower stratosphere region (LS). The LS region is characterized by a strong interplay of chemical, physical and dynamical processes. To date, the representation of this dynamically active region in models frequently mismatches observations. Although we can find a climatological maximum of oGWD in the LS, the role of OGW forcing for the transport and composition in this region is poorly understood. We combine observational evidence, idealized modeling and statistical analysis of GCM outputs to study both the short-term and long-term model response to the OGW forcing. The results presented will question the relationship between the advective part of the Brewer- Dobson circulation and the zonally asymmetric GW forcing, and a so-far neglected link between oGWD and large-scale quasi-isentropic stirring will be discussed.</p>


2014 ◽  
Vol 71 (9) ◽  
pp. 3376-3391 ◽  
Author(s):  
Claudia Stephan ◽  
M. Joan Alexander

Abstract Gravity waves have important effects on the middle atmosphere circulation, and those generated by convection are prevalent in the tropics and summer midlatitudes. Numerous case studies have been carried out to investigate their characteristics in high-resolution simulations. Here, the impact of the choice of physics parameterizations on the generation and spectral properties of these waves in models is investigated. Using the Weather Research and Forecasting Model (WRF) a summertime squall line over the Great Plains is simulated in a three-dimensional, nonlinear, and nonhydrostatic mesoscale framework. The distributions of precipitation strength and echo tops in the simulations are compared with radar data. Unsurprisingly, those storm features are most sensitive to the microphysics scheme. However, it is found that these variations in storm morphology have little influence on the simulated stratospheric momentum flux spectra. These results support the fundamental idea behind climate model parameterizations: that the large-scale storm conditions can be used to predict the spectrum of gravity wave momentum flux above the storm irrespective of the convective details that coarse-resolution models cannot capture. The simulated spectra are then contrasted with those obtained from a parameterization used in global climate models. The parameterization reproduces the shape of the spectra reasonably well but their magnitudes remain highly sensitive to the peak heating rate within the convective cells.


2016 ◽  
Vol 16 (5) ◽  
pp. 2765-2783 ◽  
Author(s):  
Shipeng Zhang ◽  
Minghuai Wang ◽  
Steven J. Ghan ◽  
Aijun Ding ◽  
Hailong Wang ◽  
...  

Abstract. Aerosol–cloud interactions continue to constitute a major source of uncertainty for the estimate of climate radiative forcing. The variation of aerosol indirect effects (AIE) in climate models is investigated across different dynamical regimes, determined by monthly mean 500 hPa vertical pressure velocity (ω500), lower-tropospheric stability (LTS) and large-scale surface precipitation rate derived from several global climate models (GCMs), with a focus on liquid water path (LWP) response to cloud condensation nuclei (CCN) concentrations. The LWP sensitivity to aerosol perturbation within dynamic regimes is found to exhibit a large spread among these GCMs. It is in regimes of strong large-scale ascent (ω500  <  −25 hPa day−1) and low clouds (stratocumulus and trade wind cumulus) where the models differ most. Shortwave aerosol indirect forcing is also found to differ significantly among different regimes. Shortwave aerosol indirect forcing in ascending regimes is close to that in subsidence regimes, which indicates that regimes with strong large-scale ascent are as important as stratocumulus regimes in studying AIE. It is further shown that shortwave aerosol indirect forcing over regions with high monthly large-scale surface precipitation rate (> 0.1 mm day−1) contributes the most to the total aerosol indirect forcing (from 64 to nearly 100 %). Results show that the uncertainty in AIE is even larger within specific dynamical regimes compared to the uncertainty in its global mean values, pointing to the need to reduce the uncertainty in AIE in different dynamical regimes.


2015 ◽  
Vol 15 (17) ◽  
pp. 23683-23729 ◽  
Author(s):  
S. Zhang ◽  
M. Wang ◽  
S. J. Ghan ◽  
A. Ding ◽  
H. Wang ◽  
...  

Abstract. Aerosol-cloud interactions continue to constitute a major source of uncertainty for the estimate of climate radiative forcing. The variation of aerosol indirect effects (AIE) in climate models is investigated across different dynamical regimes, determined by monthly mean 500 hPa vertical pressure velocity (ω500), lower-tropospheric stability (LTS) and large-scale surface precipitation rate derived from several global climate models (GCMs), with a focus on liquid water path (LWP) response to cloud condensation nuclei (CCN) concentrations. The LWP sensitivity to aerosol perturbation within dynamic regimes is found to exhibit a large spread among these GCMs. It is in regimes of strong large-scale ascend (ω500 < −25 hPa d−1) and low clouds (stratocumulus and trade wind cumulus) where the models differ most. Shortwave aerosol indirect forcing is also found to differ significantly among different regimes. Shortwave aerosol indirect forcing in ascending regimes is as large as that in stratocumulus regimes, which indicates that regimes with strong large-scale ascend are as important as stratocumulus regimes in studying AIE. It is further shown that shortwave aerosol indirect forcing over regions with high monthly large-scale surface precipitation rate (> 0.1 mm d−1) contributes the most to the total aerosol indirect forcing (from 64 to nearly 100 %). Results show that the uncertainty in AIE is even larger within specific dynamical regimes than that globally, pointing to the need to reduce the uncertainty in AIE in different dynamical regimes.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.


2008 ◽  
Vol 80 (2) ◽  
pp. 397-408 ◽  
Author(s):  
David M. Lapola ◽  
Marcos D. Oyama ◽  
Carlos A. Nobre ◽  
Gilvan Sampaio

We developed a new world natural vegetation map at 1 degree horizontal resolution for use in global climate models. We used the Dorman and Sellers vegetation classification with inclusion of a new biome: tropical seasonal forest, which refers to both deciduous and semi-deciduous tropical forests. SSiB biogeophysical parameters values for this new biome type are presented. Under this new vegetation classification we obtained a consensus map between two global natural vegetation maps widely used in climate studies. We found that these two maps assign different biomes in ca. 1/3 of the continental grid points. To obtain a new global natural vegetation map, non-consensus areas were filled according to regional consensus based on more than 100 regional maps available on the internet. To minimize the risk of using poor quality information, the regional maps were obtained from reliable internet sources, and the filling procedure was based on the consensus among several regional maps obtained from independent sources. The new map was designed to reproduce accurately both the large-scale distribution of the main vegetation types (as it builds on two reliable global natural vegetation maps) and the regional details (as it is based on the consensus of regional maps).


2017 ◽  
Author(s):  
Imme Benedict ◽  
Chiel C. van Heerwaarden ◽  
Albrecht H. Weerts ◽  
Wilco Hazeleger

Abstract. The hydrological cycle of river basins can be simulated by combining global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. To further improve simulations of precipitation and river-runoff on a global scale, we assess and compare the benefits of an increased resolution for a GCM and a GHM. We focus on the Rhine and Mississippi basin. Increasing the resolution of a GCM (1.125° to 0.25°) results in more realistic large-scale circulation patterns over the Rhine and an improved precipitation budget. These improvements with increased resolution are not found for the Mississippi basin, most likely because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, because the hydrological processes depend highly on other parameter values that are not readily available at high resolution. Therefore, increasing the resolution of the GCM provides the most straightforward route to better results. This route works best for basins driven by large-scale precipitation, such as the Rhine basin. For basins driven by convective processes, such as the Mississippi basin, improvements are expected with even higher resolution convection permitting models.


2021 ◽  
Vol 34 (2) ◽  
pp. 509-525
Author(s):  
David P. Rowell ◽  
Rory G. J. Fitzpatrick ◽  
Lawrence S. Jackson ◽  
Grace Redmond

AbstractProjected changes in the intensity of severe rain events over the North African Sahel—falling from large mesoscale convective systems—cannot be directly assessed from global climate models due to their inadequate resolution and parameterization of convection. Instead, the large-scale atmospheric drivers of these storms must be analyzed. Here we study changes in meridional lower-tropospheric temperature gradient across the Sahel (ΔTGrad), which affect storm development via zonal vertical wind shear and Saharan air layer characteristics. Projected changes in ΔTGrad vary substantially among models, adversely affecting planning decisions that need to be resilient to adverse risks, such as increased flooding. This study seeks to understand the causes of these projection uncertainties and finds three key drivers. The first is intermodel variability in remote warming, which has strongest impact on the eastern Sahel, decaying toward the west. Second, and most important, a warming–advection–circulation feedback in a narrow band along the southern Sahara varies in strength between models. Third, variations in southern Saharan evaporative anomalies weakly affect ΔTGrad, although for an outlier model these are sufficiently substantive to reduce warming here to below that of the global mean. Together these uncertain mechanisms lead to uncertain southern Saharan/northern Sahelian warming, causing the bulk of large intermodel variations in ΔTGrad. In the southern Sahel, a local negative feedback limits the contribution to uncertainties in ΔTGrad. This new knowledge of ΔTGrad projection uncertainties provides understanding that can be used, in combination with further research, to constrain projections of severe Sahelian storm activity.


2006 ◽  
Vol 63 (11) ◽  
pp. 2813-2830 ◽  
Author(s):  
Roger Marchand ◽  
Nathaniel Beagley ◽  
Sandra E. Thompson ◽  
Thomas P. Ackerman ◽  
David M. Schultz

Abstract A classification scheme is created to map the synoptic-scale (large scale) atmospheric state to distributions of local-scale cloud properties. This mapping is accomplished by a neural network that classifies 17 months of synoptic-scale initial conditions from the rapid update cycle forecast model into 25 different states. The corresponding data from a vertically pointing millimeter-wavelength cloud radar (from the Atmospheric Radiation Measurement Program Southern Great Plains site at Lamont, Oklahoma) are sorted into these 25 states, producing vertical profiles of cloud occurrence. The temporal stability and distinctiveness of these 25 profiles are analyzed using a bootstrap resampling technique. A stable-state-based mapping from synoptic-scale model fields to local-scale cloud properties could be useful in three ways. First, such a mapping may improve the understanding of differences in cloud properties between output from global climate models and observations by providing a physical context. Second, this mapping could be used to identify the cause of errors in the modeled distribution of clouds—whether the cause is a difference in state occurrence (the type of synoptic activity) or the misrepresentation of clouds for a particular state. Third, robust mappings could form the basis of a new statistical cloud parameterization.


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