scholarly journals Insights into Atmospheric Predictability through Global Convection-Permitting Model Simulations

2018 ◽  
Vol 75 (5) ◽  
pp. 1477-1497 ◽  
Author(s):  
Falko Judt
Keyword(s):  
Isotropic Turbulence ◽  
Weather Prediction ◽  
Baroclinic Instability ◽  
Complex Problem ◽  
Finite Limit ◽  
Wind Component ◽  
Moist Convection ◽  
Error Growth ◽  
Growth Regime ◽  
Atmospheric Predictability

Global convection-permitting models enable weather prediction from local to planetary scales and are therefore often expected to transform the weather prediction enterprise. This potential, however, depends on the predictability of the atmosphere, which was explored here through identical twin experiments using the Model for Prediction Across Scales. The simulations were produced on a quasi-uniform 4-km mesh, which allowed the illumination of error growth from convective to global scales. During the first two days, errors grew through moist convection and other mesoscale processes, and the character of the error growth resembled the case of [Formula: see text] turbulence. Between 2 and 13 days, errors grew with the background baroclinic instability, and the character of the error growth mirrored the case of [Formula: see text] turbulence. The existence of an error growth regime with properties similar to [Formula: see text] turbulence confirmed the radical idea of E. N. Lorenz that the atmosphere has a finite limit of predictability, no matter how small the initial error. The global-mean predictability limit of the troposphere was estimated here to be around 2–3 weeks, which is in agreement with previous work. However, scale-dependent predictability limits differed between the divergent and rotational wind component and between vertical levels, indicating that atmospheric predictability is a more complex problem than that of homogeneous, isotropic turbulence. The practical value of global cloud-resolving models is discussed in light of the various aspects of atmospheric predictability.

scholarly journals A New Theoretical Framework for Understanding Multiscale Atmospheric Predictability

2020 ◽  
Vol 77 (7) ◽  
pp. 2297-2309
Author(s):  
Y. Qiang Sun ◽  
Fuqing Zhang
Keyword(s):  
Energy Spectrum ◽  
Numerical Models ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Theoretical Framework ◽  
Growth Behavior ◽  
Small Scale ◽  
Growth Equation ◽  
Error Growth ◽  
Atmospheric Predictability

AbstractHere we present a new theoretical framework that connects the error growth behavior in numerical weather prediction (NWP) with the atmospheric kinetic energy spectrum. Building on previous studies, our newly proposed framework applies to the canonical observed atmospheric spectrum that has a −3 slope at synoptic scales and a −5/3 slope at smaller scales. Based on this realistic hybrid energy spectrum, our new experiment using hybrid numerical models provides reasonable estimations for the finite predictable ranges at different scales. We further derive an analytical equation that helps understand the error growth behavior. Despite its simplicity, this new analytical error growth equation is capable of capturing the results of previous comprehensive theoretical and observational studies of atmospheric predictability. The success of this new theoretical framework highlights the combined effects of quasi-two-dimensional dynamics at synoptic scales (−3 slope) and three-dimensional turbulence-like small-scale chaotic flows (−5/3 slope) in dictating the error growth. It is proposed that this new framework could serve as a guide for understanding and estimating the predictability limit in the real world.

Intrinsic versus Practical Limits of Atmospheric Predictability and the Significance of the Butterfly Effect

2016 ◽  
Vol 73 (3) ◽  
pp. 1419-1438 ◽  
Author(s):  
Y. Qiang Sun ◽  
Fuqing Zhang
Keyword(s):  
Large Scale ◽  
Initial Perturbation ◽  
Forecast Accuracy ◽  
Initial Condition ◽  
Moist Convection ◽  
Error Growth ◽  
Initial Error ◽  
Baroclinic Waves ◽  
Atmospheric Predictability ◽  
Butterfly Effect

Abstract Limits of intrinsic versus practical predictability are studied through examining multiscale error growth dynamics in idealized baroclinic waves with varying degrees of convective instabilities. In the dry experiment free of moist convection, error growth is controlled primarily by baroclinic instability under which forecast accuracy is inversely proportional to the amplitude of the baroclinically unstable initial-condition error (thus the prediction can be continuously improved without limit through reducing the initial error). Under the moist environment with strong convective instability, rapid upscale growth from moist convection leads to the forecast error being increasingly less sensitive to the scale and amplitude of the initial perturbations when the initial-error amplitude is getting smaller; these diminishing returns may ultimately impose a finite-time barrier to the forecast accuracy (limit of intrinsic predictability and the so-called “butterfly effect”). However, if the initial perturbation is sufficiently large in scale and amplitude (as for most current-day operational models), the baroclinic growth of large-scale finite-amplitude initial error will control the forecast accuracy for both dry and moist baroclinic waves; forecast accuracy can be improved (thus the limit of practical predictability can be extended) through the reduction of initial-condition errors, especially those at larger scales. Regardless of the initial-perturbation scales and amplitude, the error spectrum will adjust toward the slope of the background flow. Inclusion of strong moist convection changes the mesoscale kinetic energy spectrum slope from −3 to ~−5/3. This change further highlights the importance of convection and the relevance of the butterfly effect to both the intrinsic and practical limits of atmospheric predictability, especially at meso- and convective scales.

scholarly journals Atmospheric Predictability of the Tropics, Middle Latitudes, and Polar Regions Explored through Global Storm-Resolving Simulations

2019 ◽  
Vol 77 (1) ◽  
pp. 257-276 ◽  
Author(s):  
Falko Judt
Keyword(s):  
Weather Prediction ◽  
Middle Latitude ◽  
Polar Regions ◽  
Equatorial Waves ◽  
Error Growth ◽  
Future Studies ◽  
Middle Latitudes ◽  
Atmospheric Predictability ◽  
Conventional Models ◽  
The Tropics

Abstract The predictability of the atmosphere has important implications for weather prediction, because it determines what forecast problems are potentially tractable. Even though our general understanding of error growth and predictability has been increasing, relatively little is known about the detailed structure of atmospheric predictability, such as how it varies between climate regions. The present study addresses this issue by exploring error growth and predictability in three latitude zones, using model output from a previous global storm-resolving predictability experiment by Judt published in 2018. It was determined that the tropics have longer predictability than the middle latitudes and polar regions (tropics, >20 days; middle latitudes and polar regions, a little over 2 weeks). Each latitude zone had distinct error growth characteristics, and error growth was broadly consistent with the underlying dynamics of each zone. Evidence suggests that equatorial waves play a role in the comparatively long predictability of the tropics; specifically, equatorial waves seem to be less prone to error growth than middle-latitude baroclinic disturbances. Even though the generality of the findings needs to be assessed in future studies, the overall conclusions agree with previous work in that current numerical weather prediction procedures have not reached the limits of atmospheric predictability, especially in the tropics. One way to exploit tropical predictability is to reduce model error, for example, by using global storm-resolving models instead of conventional models that parameterize convection.

scholarly journals Mesoscale Predictability of Moist Baroclinic Waves: Convection-Permitting Experiments and Multistage Error Growth Dynamics

2007 ◽  
Vol 64 (10) ◽  
pp. 3579-3594 ◽  
Author(s):  
Fuqing Zhang ◽  
Naifang Bei ◽  
Richard Rotunno ◽  
Chris Snyder ◽  
Craig C. Epifanio
Keyword(s):  
Large Scale ◽  
Random Noise ◽  
Baroclinic Instability ◽  
Growth Dynamics ◽  
Small Scale ◽  
Moist Convection ◽  
Error Growth ◽  
Baroclinic Waves ◽  
Convective Scale ◽  
Shear Production

Abstract A recent study examined the predictability of an idealized baroclinic wave amplifying in a conditionally unstable atmosphere through numerical simulations with parameterized moist convection. It was demonstrated that with the effect of moisture included, the error starting from small random noise is characterized by upscale growth in the short-term (0–36 h) forecast of a growing synoptic-scale disturbance. The current study seeks to explore further the mesoscale error-growth dynamics in idealized moist baroclinic waves through convection-permitting experiments with model grid increments down to 3.3 km. These experiments suggest the following three-stage error-growth model: in the initial stage, the errors grow from small-scale convective instability and then quickly [O(1 h)] saturate at the convective scales. In the second stage, the character of the errors changes from that of convective-scale unbalanced motions to one more closely related to large-scale balanced motions. That is, some of the error from convective scales is retained in the balanced motions, while the rest is radiated away in the form of gravity waves. In the final stage, the large-scale (balanced) components of the errors grow with the background baroclinic instability. Through examination of the error-energy budget, it is found that buoyancy production due mostly to moist convection is comparable to shear production (nonlinear velocity advection). It is found that turning off latent heating not only dramatically decreases buoyancy production, but also reduces shear production to less than 20% of its original amplitude.

Rotating Shallow-Water Models with Moist Convection

2018 ◽  
Author(s):  
Vladimir Zeitlin
Keyword(s):  
Baroclinic Instability ◽  
Potential Temperature ◽  
Moist Convection ◽  
Mathematical Properties ◽  
Vertical Fluxes ◽  
Equivalent Potential ◽  
Shallow Water Models ◽  
Wave Emission ◽  
Rotating Shallow Water ◽  
Convective Fluxes

It is shown how the standard RSW can be ’augmented’ to include phase transitions of water. This chapter explains how to incorporate extra (convective) vertical fluxes in the model. By using Lagrangian conservation of equivalent potential temperature condensation of the water vapour, which is otherwise a passive tracer, is included in the model and linked to convective fluxes. Simple relaxational parameterisation of condensation permits the closure of the system, and surface evaporation can be easily included. Physical and mathematical properties of thus obtained model are explained, and illustrated on the example of wave scattering on the moisture front. The model is applied to ’moist’ baroclinic instability of jets and vortices. Condensation is shown to produce a transient increase of the growth rate. Special attention is paid to the moist instabilities of hurricane-like vortices, which are shown to enhance intensification of the hurricane, increase gravity wave emission, and generate convection-coupled waves.

scholarly journals Potential Vorticity Diagnostics to Quantify Effects of Latent Heating in Extratropical Cyclones. Part I: Methodology

2017 ◽  
Vol 74 (11) ◽  
pp. 3567-3590 ◽  
Author(s):  
Dominik Büeler ◽  
Stephan Pfahl
Keyword(s):  
Potential Vorticity ◽  
Weather Prediction ◽  
Baroclinic Instability ◽  
Numerical Weather Prediction Model ◽  
Cloud Formation ◽  
Extratropical Cyclones ◽  
Latent Heating ◽  
Strongly Coupled ◽  
Cyclone Intensity ◽  
Diabatic Processes

Abstract Extratropical cyclones develop because of baroclinic instability, but their intensification is often substantially amplified by diabatic processes, most importantly, latent heating (LH) through cloud formation. Although this amplification is well understood for individual cyclones, there is still need for a systematic and quantitative investigation of how LH affects cyclone intensification in different, particularly warmer and moister, climates. For this purpose, the authors introduce a simple diagnostic to quantify the contribution of LH to cyclone intensification within the potential vorticity (PV) framework. The two leading terms in the PV tendency equation, diabatic PV modification and vertical advection, are used to derive a diagnostic equation to explicitly calculate the fraction of a cyclone’s positive lower-tropospheric PV anomaly caused by LH. The strength of this anomaly is strongly coupled to cyclone intensity and the associated impacts in terms of surface weather. To evaluate the performance of the diagnostic, sensitivity simulations of 12 Northern Hemisphere cyclones with artificially modified LH are carried out with a numerical weather prediction model. Based on these simulations, it is demonstrated that the PV diagnostic captures the mean sensitivity of the cyclones’ PV structure to LH as well as parts of the strong case-to-case variability. The simple and versatile PV diagnostic will be the basis for future climatological studies of LH effects on cyclone intensification.

scholarly journals Predictability in Wet and Dry Convective Turbulence

2008 ◽  
Vol 65 (1) ◽  
pp. 220-234 ◽  
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.

scholarly journals Relative importance of tropopause structure and diabatic heating for baroclinic instability

2021 ◽  
Vol 2 (3) ◽  
pp. 695-712
Author(s):  
Kristine Flacké Haualand ◽  
Thomas Spengler
Keyword(s):  
Potential Vorticity ◽  
Wind Shear ◽  
Lower Stratosphere ◽  
Prediction Models ◽  
Weather Prediction ◽  
Baroclinic Instability ◽  
Polar Vortex ◽  
Dominant Factor ◽  
Latent Heating ◽  
The Impact

Abstract. Misrepresentations of wind shear and stratification around the tropopause in numerical weather prediction models can lead to errors in potential vorticity gradients with repercussions for Rossby wave propagation and baroclinic instability. Using a diabatic extension of the linear quasi-geostrophic Eady model featuring a tropopause, we investigate the influence of such discrepancies on baroclinic instability by varying tropopause sharpness and altitude as well as wind shear and stratification in the lower stratosphere, which can be associated with model or data assimilation errors or a downward extension of a weakened polar vortex. We find that baroclinic development is less sensitive to tropopause sharpness than to modifications in wind shear and stratification in the lower stratosphere, where the latter are associated with a net change in the vertical integral of the horizontal potential vorticity gradient across the tropopause. To further quantify the relevance of these sensitivities, we compare these findings to the impact of including mid-tropospheric latent heating. For representative modifications of wind shear, stratification, and latent heating intensity, the sensitivity of baroclinic instability to tropopause structure is significantly less than that to latent heating of different intensities. These findings indicate that tropopause sharpness might be less important for baroclinic development than previously anticipated and that latent heating and the structure in the lower stratosphere could play a more crucial role, with latent heating being the dominant factor.

scholarly journals Sensitivity experiments of a severe rainfall event in north-western Italy: 17 August 2006

2008 ◽  
Vol 2 (1) ◽  
pp. 133-138 ◽  
Author(s):  
M. Milelli ◽  
E. Oberto ◽  
A. Parodi
Keyword(s):  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Precipitation Forecast ◽  
Small Scale ◽  
Moist Convection ◽  
Cosmo Model ◽  
Quantitative Precipitation Forecast ◽  
Scale Modelling ◽  
North Western ◽  
Priority Project

Abstract. This study is embedded into a wider project named "Tackle deficiencies in Quantitative Precipitation Forecast (QPF)'' in the framework of the COSMO (COnsortium for Small-scale MOdelling) community. In fact QPF is an important purpose of a numerical weather prediction model, for forecasters and customers. Unfortunately, precipitation is also a very difficult parameter to forecast quantitatively. This priority project aims at looking into the COSMO Model deficiencies concerning QPF by running different numerical simulations of various events not correctly predicted by the model. In particular, this work refers to a severe event (moist convection) happened in Piemonte region during summer 2006. On one side the results suggest that details in orography representation have a strong influence on accuracy of QPF. On the other side COSMO Model exhibits a poor sensitivity on changes in numerical and physical settings when measured in terms of QPF improvements. The conclusions, although not too general, give some hint towards the behaviour of the COSMO Model in a typical convective situation.

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