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

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.

2021 ◽  
Author(s):  
Kristine Flacké Haualand ◽  
Thomas Spengler

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 is less important for baroclinic development than previously anticipated and that latent heating and the structure in the lower stratosphere play a more crucial role, with latent heating being the dominant factor.


2017 ◽  
Vol 74 (11) ◽  
pp. 3567-3590 ◽  
Author(s):  
Dominik Büeler ◽  
Stephan Pfahl

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.


2012 ◽  
Vol 69 (6) ◽  
pp. 2042-2060 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Alexander V. Ryzhkov

Abstract Differential sedimentation of precipitation occurs because heavier hydrometeors fall faster than lighter ones. Updrafts and vertical wind shear can maintain this otherwise transient size sorting, resulting in prolonged regions of ongoing particle sorting in storms. This study quantifies the impact of size sorting on the S-band polarimetric radar variables (radar reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, specific differential phase KDP, and the copolar cross-correlation coefficient ρhv). These variables are calculated from output of two idealized bin models: a one-dimensional model of pure raindrop fallout and a two-dimensional rain shaft encountering vertical wind shear. Additionally, errors in the radar variables as simulated by single-, double-, and triple-moment bulk microphysics parameterizations are quantified for the same size sorting scenarios. Size sorting produces regions of sparsely concentrated large drops with a lack of smaller drops, causing ZDR enhancements as large as 1 dB in areas of decreased ZH, often along a ZH gradient. Such areas of enhanced ZDR are offset from those of high ZH and KDP. Illustrative examples of polarimetric radar observations in a variety of precipitation regimes demonstrate the widespread occurrence of size sorting and are consistent with the bin model simulations. Single-moment schemes are incapable of size sorting, leading to large underestimations in ZDR (>2 dB) compared to the bin model solution. Double-moment schemes with a fixed spectral shape parameter produce excessive size sorting by incorrectly increasing the number of large raindrops, overestimating ZDR by 2–3 dB. Three-moment schemes with variable shape parameters better capture the narrowing drop size distribution resulting from size sorting but can underestimate ZDR and overestimate KDP by as much as 20%. Implications for polarimetric radar data assimilation into storm-scale numerical weather prediction models are discussed.


2007 ◽  
Vol 135 (4) ◽  
pp. 1424-1438 ◽  
Author(s):  
Andrew R. Lawrence ◽  
James A. Hansen

Abstract An ensemble-based data assimilation approach is used to transform old ensemble forecast perturbations with more recent observations for the purpose of inexpensively increasing ensemble size. The impact of the transformations are propagated forward in time over the ensemble’s forecast period without rerunning any models, and these transformed ensemble forecast perturbations can be combined with the most recent ensemble forecast to sensibly increase forecast ensemble sizes. Because the transform takes place in perturbation space, the transformed perturbations must be centered on the ensemble mean from the most recent forecasts. Thus, the benefit of the approach is in terms of improved ensemble statistics rather than improvements in the mean. Larger ensemble forecasts can be used for numerous purposes, including probabilistic forecasting, targeted observations, and to provide boundary conditions to limited-area models. This transformed lagged ensemble forecasting approach is explored and is shown to give positive results in the context of a simple chaotic model. By incorporating a suitable perturbation inflation factor, the technique was found to generate forecast ensembles whose skill were statistically comparable to those produced by adding nonlinear model integrations. Implications for ensemble forecasts generated by numerical weather prediction models are briefly discussed, including multimodel ensemble forecasting.


2021 ◽  
Author(s):  
Kristine Flacké Haualand ◽  
Thomas Spengler

<p>Many weather and climate models fail to represent the sharp vertical changes of vertical wind shear and stratification near the tropopause. This discrepancy results in errors in the horizontal gradient of potential vorticity (PV), which acts as a wave guide for Rossby waves that highly influence surface weather in midlatitudes. In an idealised quasi-geostrophic model developed from the Eady model, we investigate how variations in vertical wind shear and stratification near the tropopause affect baroclinic growth. Comparing sharp and smooth vertical profiles of wind shear and stratification across the tropopause for different tropopause altitudes, we find that both smoothing and tropopause altitude have little impact on the growth rate, wavelength, phase speed, and structure of baroclinic waves, despite a sometimes significant weakening of the maximum PV gradient for extensive smoothing. Instead, we find that baroclinic growth is more sensitive if the vertical integral of the PV gradient is not conserved across the tropopause. Furthermore, including mid-tropospheric latent heating highlights that errors in baroclinic growth related to a misrepresentation of latent heating intensity are typically much larger than those associated with the correct representation of vertical wind shear and stratification in the tropopause region. Our results thus indicate that the correct representation of latent heating in weather forecast models is of higher importance than adequately resolving the tropopause.</p>


2021 ◽  
Author(s):  
Aristofanis Tsiringakis ◽  
Natalie Theeuwes ◽  
Janet Barlow ◽  
Gert-Jan Steeneveld

<p>The low-level jet (LLJ) is an important phenomenon that can affect (and is affected by) the turbulence in the nocturnal urban boundary layer (UBL). We investigate the interaction of a regional LLJ with the UBL during a 2-day period over London. Observations from two Doppler Lidars and two numerical weather prediction models (Weather Research & Forecasting model and UKV Met Office Unified Model) are used to compared the LLJ characteristics (height, speed and fall-off) between a urban (London) and a rural (Chilbolton) site. We find that LLJs are elevated (70m) over London, due to the deeper UBL, an effect of the increased vertical mixing over the urban area and the difference in the topography between the two sites. Wind speed and fall-off are slightly reduced with respect to the rural LLJ. The effects of the urban area and the surrounding topography on the LLJ characteristics over London are isolated through idealized sensitivity experiments. We find that topography strongly affects the LLJ characteristics (height, falloff, and speed), but there is still a substantial urban influence.</p>


2011 ◽  
Vol 50 (6) ◽  
pp. 1225-1235 ◽  
Author(s):  
Zhigang Yao ◽  
Jun Li ◽  
Jinlong Li ◽  
Hong Zhang

AbstractAn accurate land surface emissivity (LSE) is critical for the retrieval of atmospheric temperature and moisture profiles along with land surface temperature from hyperspectral infrared (IR) sounder radiances; it is also critical to assimilating IR radiances in numerical weather prediction models over land. To investigate the impact of different LSE datasets on Atmospheric Infrared Sounder (AIRS) sounding retrievals, experiments are conducted by using a one-dimensional variational (1DVAR) retrieval algorithm. Sounding retrievals using constant LSE, the LSE dataset from the Infrared Atmospheric Sounding Interferometer (IASI), and the baseline fit dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) are performed. AIRS observations over northern Africa on 1–7 January and 1–7 July 2007 are used in the experiments. From the limited regional comparisons presented here, it is revealed that the LSE from the IASI obtained the best agreement between the retrieval results and the ECMWF reanalysis, whereas the constant LSE gets the worst results when the emissivities are fixed in the retrieval process. The results also confirm that the simultaneous retrieval of atmospheric profile and surface parameters could reduce the dependence of soundings on the LSE choice and finally improve sounding accuracy when the emissivities are adjusted in the iterative retrieval. In addition, emissivity angle dependence is investigated with AIRS radiance measurements. The retrieved emissivity spectra from AIRS over the ocean reveal weak angle dependence, which is consistent with that from an ocean emissivity model. This result demonstrates the reliability of the 1DVAR simultaneous algorithm for emissivity retrieval from hyperspectral IR radiance measurements.


2014 ◽  
Vol 21 (5) ◽  
pp. 1027-1041 ◽  
Author(s):  
K. Apodaca ◽  
M. Zupanski ◽  
M. DeMaria ◽  
J. A. Knaff ◽  
L. D. Grasso

Abstract. Lightning measurements from the Geostationary Lightning Mapper (GLM) that will be aboard the Geostationary Operational Environmental Satellite – R Series will bring new information that can have the potential for improving the initialization of numerical weather prediction models by assisting in the detection of clouds and convection through data assimilation. In this study we focus on investigating the utility of lightning observations in mesoscale and regional applications suitable for current operational environments, in which convection cannot be explicitly resolved. Therefore, we examine the impact of lightning observations on storm environment. Preliminary steps in developing a lightning data assimilation capability suitable for mesoscale modeling are presented in this paper. World Wide Lightning Location Network (WWLLN) data was utilized as a proxy for GLM measurements and was assimilated with the Maximum Likelihood Ensemble Filter, interfaced with the Nonhydrostatic Mesoscale Model core of the Weather Research and Forecasting system (WRF-NMM). In order to test this methodology, regional data assimilation experiments were conducted. Results indicate that lightning data assimilation had a positive impact on the following: information content, influencing several dynamical variables in the model (e.g., moisture, temperature, and winds), and improving initial conditions during several data assimilation cycles. However, the 6 h forecast after the assimilation did not show a clear improvement in terms of root mean square (RMS) errors.


2021 ◽  
Author(s):  
Julian Quimbayo-Duarte ◽  
Juerg Schmidli

<p>An accurate representation of the momentum budget in numerical models is essential in the quest for reliable weather forecasting, from large scales (climate models) to small scales (numerical weather prediction models, NWP). It is well known that orographic waves play an important role in large-scale circulation. The vertical propagation of such waves is associated with a vertical flux of horizontal momentum, which may be transferred to the mean flow by wave-mean flow interaction and wave-breaking (Sandu et al., 2019). The orography scales inducing such phenomena are often smaller than the model resolution, even for NWP models, leading to the need for parameterisation schemes for orographic drag. Yet, such parameterization in current models is fairly limited (Vosper et al., 2020). The present work aims to contribute to an improved understanding and parameterization of the impact of small-scale orography on the lower atmosphere with a focus on the stable atmospheric boundary layer.</p><p>As a first step, an idealized set of experiments has been designed to explore the capabilities of the Icosahedral Nonhydrostatic model in its large eddy simulation mode (ICON-LES, Dipankar et al., 2015) to represent turbulence processes in the stably-stratified atmosphere. Initial experiments testing the model performance over flat terrain (GABLS experiment, Beare et al., 2006), orographic wave generation (shallow bell-shaped topography, Xue et al., 2000) and moderate complex terrain (U-shaped valley, Burns and Chemel 2014) have been conducted. The results demonstrate that ICON-LES adequately represents the boundary layer processes for the investigated cases in comparison to the literature.</p><p>In a second step, an idealized set of experiments of atmospheric flow over idealized sinusoidal and multiscale terrain has been designed to study the impact of the orographically-induced gravity waves on the total surface drag and the vertical flux of horizontal momentum. The influence of different atmospheric conditions is assessed by varying the background wind speed and the temperature stratification at the initial time.</p>


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