scholarly journals Sensitivity of Cloud-Resolving Simulations of Warm-Season Convection to Cloud Microphysics Parameterizations

2007 ◽  
Vol 135 (8) ◽  
pp. 2854-2868 ◽  
Author(s):  
Changhai Liu ◽  
Mitchell W. Moncrieff
Keyword(s):  
Large Scale ◽  
Prediction Models ◽  
Weather Prediction ◽  
Warm Season ◽  
Cloud Microphysics ◽  
Mixed Phase ◽  
Fine Grid ◽  
Upper Level ◽  
Heating Profiles ◽  
Microphysical Parameterization

Abstract This paper investigates the effects of cloud microphysics parameterizations on simulations of warm-season precipitation at convection-permitting grid spacing. The objective is to assess the sensitivity of summertime convection predictions to the bulk microphysics parameterizations (BMPs) at fine-grid spacings applicable to the next generation of operational numerical weather prediction models. Four microphysical parameterization schemes are compared: simple ice (Dudhia), four-class mixed phase (Reisner et al.), Goddard five-class mixed phase (Tao and Simpson), and five-class mixed phase with graupel (Reisner et al.). The experimentation involves a 7-day episode (3–9 July 2003) of U.S. midsummer convection under moderate large-scale forcing. Overall, the precipitation coherency manifested as eastward-moving organized convection in the lee of the Rockies is insensitive to the choice of the microphysics schemes, and the latent heating profiles are also largely comparable among the BMPs. The upper-level condensate and cloudiness, upper-level radiative cooling/heating, and rainfall spectrum are the most sensitive, whereas the domain-mean rainfall rate and areal coverage display moderate sensitivity. Overall, the three mixed-phase schemes outperform the simple ice scheme, but a general conclusion about the degree of sophistication in the microphysics treatment and the performance is not achievable.

scholarly journals Medicane Zorbas: Origin and impact of an uncertain potential vorticity streamer

2019 ◽  
Author(s):  
Raphael Portmann ◽  
Juan Jesús González-Alemán ◽  
Michael Sprenger ◽  
Heini Wernli
Keyword(s):  
Potential Vorticity ◽  
Large Scale ◽  
Prediction Models ◽  
Initial Conditions ◽  
Thermal Structure ◽  
Weather Prediction ◽  
Medium Range Weather Forecast ◽  
The Mediterranean ◽  
Upper Level ◽  
Jet Streak

Abstract. Mediterranean tropical-like cyclones (Medicanes) can have high societal impact and their accurate forecast remains a challenge for numerical weather prediction models. They are often triggered by upper-level potential vorticity (PV) anomalies, such as PV streamers and cut-offs. But knowledge is incomplete about their detailed formation processes and factors limiting their predictability. This study exploits a European Centre for Medium-Range Weather Forecast (ECMWF) operational ensemble forecast with an uncertain PV streamer over the Mediterranean, which, three days after initialisation, resulted in an uncertain development of Medicane Zorbas in September 2018. Using an ad-hoc clustering of the ensemble members according to the PV streamer position, it is demonstrated that uncertainty in the initial conditions near an upper-level jet streak over the Gulf of Saint Lawrence is the dominant source of the subsequent uncertainty in the position of the PV streamer over the Mediterranean. The initial condition uncertainty strongly amplifies baroclinically after 18 h in a region of strong quasi-geostrophic forcing for ascent in the left exit of a jet streak over the North Atlantic. The further amplification and downstream propagation of the tropopause-level PV uncertainty leads to a large spread in the position of the PV streamer over the Mediterranean after three days, directly limiting the predictability of the position, thermal structure and evolution of Zorbas. Two low-level airstreams possibly play a key role in linking the uncertainties of the large-scale upper-level flow with meso-scale uncertainties in the cyclone structure. Overall, this study is an illustrative example that uncertainties in large-scale initial conditions can determine the practical predictability limits of a high-impact weather event.

scholarly journals The structure of turbulence and mixed-phase cloud microphysics in a highly supercooled altocumulus cloud

2020 ◽  
Vol 20 (4) ◽  
pp. 1921-1939 ◽  
Author(s):  
Paul A. Barrett ◽  
Alan Blyth ◽  
Philip R. A. Brown ◽  
Steven J. Abel
Keyword(s):  
Prediction Models ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Cloud Microphysics ◽  
In Situ Measurements ◽  
Cloud Layer ◽  
Mixed Phase ◽  
Ice Cloud ◽  
Cloud Properties

Abstract. Observations of vertically resolved turbulence and cloud microphysics in a mixed-phase altocumulus cloud are presented using in situ measurements from an instrumented aircraft. The turbulence spectrum is observed to have an increasingly negative skewness with distance below cloud top, suggesting that long-wave radiative cooling from the liquid cloud layer is an important source of turbulence kinetic energy. Turbulence measurements are presented from both the liquid cloud layer and ice virga below. Vertical profiles of both bulk and microphysical liquid and ice cloud properties indicate that ice is produced within the liquid layer cloud at a temperature of −30 ∘C. These high-resolution in situ measurements support previous remotely sensed observations from both ground-based and space-borne instruments and could be used to evaluate numerical model simulations of altocumulus clouds at spatial scales from eddy-resolving models to global numerical weather prediction models and climate simulations.

Spurious Grid-Scale Precipitation in the North American Regional Reanalysis

2007 ◽  
Vol 135 (6) ◽  
pp. 2168-2184 ◽  
Author(s):  
Gregory L. West ◽  
W. James Steenburgh ◽  
William Y. Y. Cheng
Keyword(s):  
North American ◽  
Prediction Models ◽  
Weather Prediction ◽  
Regional Climate ◽  
Potential Temperature ◽  
Climate Data ◽  
The North ◽  
North American Regional Reanalysis ◽  
Upper Level ◽  
Regional Reanalysis

Abstract Spurious grid-scale precipitation (SGSP) occurs in many mesoscale numerical weather prediction models when the simulated atmosphere becomes convectively unstable and the convective parameterization fails to relieve the instability. Case studies presented in this paper illustrate that SGSP events are also found in the North American Regional Reanalysis (NARR) and are accompanied by excessive maxima in grid-scale precipitation, vertical velocity, moisture variables (e.g., relative humidity and precipitable water), mid- and upper-level equivalent potential temperature, and mid- and upper-level absolute vorticity. SGSP events in environments favorable for high-based convection can also feature low-level cold pools and sea level pressure maxima. Prior to 2003, retrospectively generated NARR analyses feature an average of approximately 370 SGSP events annually. Beginning in 2003, however, NARR analyses are generated in near–real time by the Regional Climate Data Assimilation System (R-CDAS), which is identical to the retrospective NARR analysis system except for the input precipitation and ice cover datasets. Analyses produced by the R-CDAS feature a substantially larger number of SGSP events with more than 4000 occurring in the original 2003 analyses. An oceanic precipitation data processing error, which resulted in a reprocessing of NARR analyses from 2003 to 2005, only partially explains this increase since the reprocessed analyses still produce approximately 2000 SGSP events annually. These results suggest that many NARR SGSP events are not produced by shortcomings in the underlying Eta Model, but by the specification of anomalous latent heating when there is a strong mismatch between modeled and assimilated precipitation. NARR users should ensure that they are using the reprocessed NARR analyses from 2003 to 2005 and consider the possible influence of SGSP on their findings, particularly after the transition to the R-CDAS.

The Bow and Arrow Mesoscale Convective Structure

2013 ◽  
Vol 141 (5) ◽  
pp. 1648-1672 ◽  
Author(s):  
Kelly M. Keene ◽  
Russ S. Schumacher
Keyword(s):  
Heavy Rainfall ◽  
Prediction Models ◽  
Weather Prediction ◽  
Warm Season ◽  
Severe Weather ◽  
Cold Pool ◽  
Horizontal Shear ◽  
Convective Systems ◽  
Wind Speeds ◽  
Bow And Arrow

Abstract The accurate prediction of warm-season convective systems and the heavy rainfall and severe weather associated with them remains a challenge for numerical weather prediction models. This study looks at a circumstance in which quasi-stationary convection forms perpendicular to, and above the cold-pool behind strong bow echoes. The authors refer to this phenomenon as a “bow and arrow” because on radar imagery the two convective lines resemble an archer’s bow and arrow. The “arrow” can produce heavy rainfall and severe weather, extending over hundreds of kilometers. These events are challenging to forecast because they require an accurate forecast of earlier convection and the effects of that convection on the environment. In this study, basic characteristics of 14 events are documented, and observations of 4 events are presented to identify common environmental conditions prior to the development of the back-building convection. Simulations of three cases using the Weather Research and Forecasting Model (WRF) are analyzed in an attempt to understand the mechanisms responsible for initiating and maintaining the convective line. In each case, strong southwesterly flow (inducing warm air advection and gradual isentropic lifting), in addition to directional and speed convergence into the convective arrow appear to contribute to initiation of convection. The linear orientation of the arrow may be associated with a combination of increased wind speeds and horizontal shear in the arrow region. When these ingredients are combined with thermodynamic instability, there appears to be a greater possibility of formation and maintenance of a convective arrow behind a bow echo.

scholarly journals Progress toward the Application of a Localized Particle Filter for Numerical Weather Prediction

2019 ◽  
Vol 147 (4) ◽  
pp. 1107-1126 ◽  
Author(s):  
Jonathan Poterjoy ◽  
Louis Wicker ◽  
Mark Buehner
Keyword(s):  
Data Assimilation ◽  
Particle Filter ◽  
Numerical Weather Prediction ◽  
Large Scale ◽  
Sequential Monte Carlo ◽  
Prediction Models ◽  
Weather Prediction ◽  
Coupled Systems ◽  
State Variables ◽  
Numerical Weather

Abstract A series of papers published recently by the first author introduce a nonlinear filter that operates effectively as a data assimilation method for large-scale geophysical applications. The method uses sequential Monte Carlo techniques adopted by particle filters, which make no parametric assumptions for the underlying prior and posterior error distributions. The filter also treats the underlying dynamical system as a set of loosely coupled systems to effectively localize the effect observations have on posterior state estimates. This property greatly reduces the number of particles—or ensemble members—required for its implementation. For these reasons, the method is called the local particle filter. The current manuscript summarizes algorithmic advances made to the local particle filter following recent tests performed over a hierarchy of dynamical systems. The revised filter uses modified vector weight calculations and probability mapping techniques from earlier studies, and new strategies for improving filter stability in situations where state variables are observed infrequently with very accurate measurements. Numerical experiments performed on low-dimensional data assimilation problems provide evidence that supports the theoretical benefits of the new improvements. As a proof of concept, the revised particle filter is also tested on a high-dimensional application from a real-time weather forecasting system at the NOAA/National Severe Storms Laboratory (NSSL). The proposed changes have large implications for researchers applying the local particle filter for real applications, such as data assimilation in numerical weather prediction models.

scholarly journals Seamless Stratocumulus Simulation across the Turbulent Gray Zone

2014 ◽  
Vol 142 (4) ◽  
pp. 1655-1668 ◽  
Author(s):  
I. A. Boutle ◽  
J. E. J. Eyre ◽  
A. P. Lock
Keyword(s):  
Boundary Layer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Aircraft Observations ◽  
Microphysical Parameterization ◽  
Grid Length ◽  
Numerical Weather Prediction Models

Abstract A pragmatic approach for representing partially resolved turbulence in numerical weather prediction models is introduced and tested. The method blends a conventional boundary layer parameterization, suitable for large grid lengths, with a subgrid turbulence scheme suitable for large-eddy simulation. The key parameter for blending the schemes is the ratio of grid length to boundary layer depth. The new parameterization is combined with a scale-aware microphysical parameterization and tested on a case study forecast of stratocumulus evolution. Simulations at a range of model grid lengths between 1 km and 100 m are compared to aircraft observations. The improved microphysical representation removes the correlation between precipitation rate and model grid length, while the new turbulence parameterization improves the transition from unresolved to resolved turbulence as grid length is reduced.

Atmospheric angular momentum forecasts as novel tests of global numerical weather prediction models

1991 ◽  
Vol 334 (1633) ◽  
pp. 55-92 ◽  
Keyword(s):  
Angular Momentum ◽  
Numerical Weather Prediction ◽  
Large Scale ◽  
Prediction Models ◽  
Weather Prediction ◽  
Atmospheric Angular Momentum ◽  
Axial Component ◽  
Practical Applications ◽  
Numerical Weather ◽  
Three Components

The global circulation of the terrestrial atmosphere exhibits fluctuations of considerable amplitude in all three components of its total angular momentum on interannual, seasonal and shorter timescales. The fluctuations must be intimately linked with nonlinear barotropic and baroclinic energetic conversion processes throughout the whole atmosphere and it is advocated that studies of routinely produced determinations of atmospheric angular momentum (AAM) changes be incorporated into systematic diagnostic investigations of large-scale atmospheric flows, AAM fluctuations are generated by dynamical interactions between the atmosphere and the underlying planet. These excite tiny but measurable compensating fluctuations in the rotation vector of the massive solid Earth, thereby ensuring conservation of the angular momentum of the whole system. Forecasts and analyses of changes in AAM from the output of a global numerical weather prediction (GNWP) model constitute a stringent test of the model. Successful forecasts of the axial com ponent of AAM, and hence of irregular non-tidal components of short-term changes in the Earth’s rotation, would find practical applications in various areas of astronomy and geodesy, such as spacecraft navigation. Reported in this paper are the main findings of intercomparisons of analyses and forecasts of changes in all three components of AAM obtained from the operational GNWP models at the United Kingdom Meteorological Office (UKMO) and the European Centre for Medium Range Weather Forecasts (ECMWF), over the period covering the two years 1987 and 1988. Included in the results obtained is the finding that useful forecasts of changes in the axial component of AAM can be made out to 5 days and even slightly longer.

Application of COSMO-SPECS for remote sensing observations of mixed-phase clouds during CyCare and DACAPO-PESO

2021 ◽  
Author(s):  
Roland Schrödner ◽  
Johannes Bühl ◽  
Fabian Senf ◽  
Oswald Knoth ◽  
Jens Stoll ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Conditions ◽  
Case Studies ◽  
Weather Prediction ◽  
Cloud Microphysics ◽  
Horizontal Resolution ◽  
Model System ◽  
Mixed Phase ◽  
Real Case ◽  
Mixed Phase Clouds

<p>During the campaigns CyCyare (Limassol, Cyprus) and DACAPO-PESO (Punta Arenas, Chile), remote sensing methods were applied to study mixed-phase clouds. The two sites show contrasting aerosol loads with very clean, marine atmosphere over southern Chile and higher aerosol mass and number concentrations over Cyprus, which frequently are dust-laden. The observations suggest differing cloud properties. To further study the properties and evolution of the observed clouds as well as their relation to the ambient aerosol, the detailed coupled cloud microphysical model COSMO-SPECS is applied for selected real case studies.</p><p>The SPECtral bin cloud microphysicS model SPECS was developed to simulate cloud processes using fixed-bin size distributions of aerosol particles and of liquid and frozen hydrometeors. It was implemented in the numerical weather prediction model COSMO. COSMO-SPECS has been used for idealized case studies with horizontally periodic boundary conditions. Recently, the model system has been enhanced by considering lateral boundary conditions for the hydrometeor spectra allowing for high-resolution real case studies on nested domains. The simulations are carried out by first applying the meteorological driver COSMO using its standard two-moment microphysics scheme on multiple nests with increasing horizontal resolution. Finally, the COSMO-SPECS model system is applied on the innermost domain with a horizontal resolution of a few hundred meters using boundary data derived from the finest driving COSMO domain. For this purpose, the bulk hydrometeor fields of the driving model need to be translated into the corresponding hydrometeor mass and number distributions of SPECS’ hydrometeor spectra.</p><p>In this work, we present first results for selected case-studies of mixed-phase clouds observed during CyCyare and DACAPO-PESO. The results of the model simulations are compared against the LIDAR and cloud radar observations at the two sites.</p>

Evaluating Convective Initiation in High-Resolution Numerical Weather Prediction Models Using GOES-16 Infrared Brightness Temperatures

2021 ◽  
Vol 149 (4) ◽  
pp. 1153-1172
Author(s):  
David S. Henderson ◽  
Jason A. Otkin ◽  
John R. Mecikalski
Keyword(s):  
High Resolution ◽  
Prediction Models ◽  
Weather Prediction ◽  
Cloud Microphysics ◽  
Cloud Water ◽  
Convective Initiation ◽  
Model Simulations ◽  
Brightness Temperatures ◽  
Cloud Characteristics ◽  
Verification Methods

AbstractThe evolution of model-based cloud-top brightness temperatures (BT) associated with convective initiation (CI) is assessed for three bulk cloud microphysics schemes in the Weather Research and Forecasting Model. Using a composite-based analysis, cloud objects derived from high-resolution (500 m) model simulations are compared to 5-min GOES-16 imagery for a case study day located near the Alabama–Mississippi border. Observed and simulated cloud characteristics for clouds reaching CI are examined by utilizing infrared BTs commonly used in satellite-based CI nowcasting methods. The results demonstrate the ability of object-based verification methods with satellite observations to evaluate the evolution of model cloud characteristics, and the BT comparison provides insight into a known issue of model simulations producing too many convective cells reaching CI. The timing of CI from the different microphysical schemes is dependent on the production of ice in the upper levels of the cloud, which typically occurs near the time of maximum cloud growth. In particular, large differences in precipitation formation drive differences in the amount of cloud water able to reach upper layers of the cloud, which impacts cloud-top glaciation. Larger cloud mixing ratios are found in clouds with sustained growth leading to more cloud water lofted to the upper levels of the cloud and the formation of ice. Clouds unable to sustain growth lack the necessary cloud water needed to form ice and grow into cumulonimbus. Clouds with slower growth rates display similar BT trends as clouds exhibiting growth, which suggests that forecasting CI using geostationary satellites might require additional information beyond those derived at cloud top.

The Convective Instability Pathway to Warm Season Drought in Texas. Part II: Free-Tropospheric Modulation of Convective Inhibition

2010 ◽  
Vol 23 (17) ◽  
pp. 4474-4488 ◽  
Author(s):  
Boksoon Myoung ◽  
John W. Nielsen-Gammon
Keyword(s):  
United States ◽  
Convective Instability ◽  
Large Scale ◽  
Potential Temperature ◽  
Warm Season ◽  
Air Transport ◽  
Southern United States ◽  
Back Trajectory ◽  
Convective Inhibition ◽  
Upper Level

Abstract This study is concerned with the modulation by convective instability of summertime precipitation in Texas as a mechanism for maintaining or enhancing drought. The important role of convective inhibition (CIN), its dependence on the temperature at 700 hPa and the surface dewpoint, and the mechanism by which soil moisture modulates precipitation through CIN were described in Part I of this two-part series study. This study, Part II, examines the dynamic and physical processes controlling the temperature at 700 hPa and elucidates the large-scale influences on convective instability and precipitation integrating the principal processes found in both Parts I and II. Back-trajectory analysis indicates that a significant contributor to warming at 700 hPa is the inversion caused by warm air transport from the Rocky Mountains and the Mexican Plateau where the surface potential temperature is greater than 307.5 K, rather than by subsidence. It was found that downward motion and warm air transport are enhanced in Texas when an upper-level anticyclonic circulation develops in the southern United States. Upper-level anticyclonic circulations in the southern United States, one of the distinctive features of central U.S. droughts, strongly affect Texas summertime precipitation by modulating the thermodynamic structure of the atmosphere and thus convective instability. Stationary anticyclonic anomalies increase CIN not only by enhancing warm air transport from the high terrain but also by suppressing the occurrence of traveling disturbances. The resulting reduced precipitation and dry soil significantly modulate surface conditions, which elevates CIN and decreases precipitation. The aforementioned chain reaction of upper-level anticyclone influences that is expected to play an important role in initiating and maintaining Texas summer droughts can be understood within the context of CIN.

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