scholarly journals Vertical Temperature Structure Associated with Evaporation of Stratiform Precipitation in Idealized WRF Simulations

2020 ◽  
Vol 77 (5) ◽  
pp. 1851-1864
Author(s):  
M. Virman ◽  
M. Bister ◽  
V. A. Sinclair ◽  
J. Räisänen ◽  
H. Järvinen
Keyword(s):  
Initial Conditions ◽  
Numerical Models ◽  
Wrf Model ◽  
Lower Troposphere ◽  
Horizontal Distribution ◽  
Temperature Structure ◽  
Maximum Magnitude ◽  
Vertical Temperature ◽  
Warm Anomaly ◽  
Stratiform Precipitation

Abstract A recent study based on observations has shown that after precipitation over tropical oceans rather shallow temperature structures occur in the lower troposphere and that their magnitude depends on climatological low- to midtropospheric humidity. As any process that produces temperature perturbations in the lower troposphere can be of great significance for the formation of atmospheric deep convection, the vertical temperature structure associated with evaporation of stratiform precipitation and its sensitivity to low- to midtropospheric humidity are studied by conducting three-dimensional, high-resolution, idealized simulations with the Advanced Research version of the Weather Research and Forecasting (WRF) Model. In the simulations, rainwater with mixing ratio and number concentration characteristic of stratiform precipitation associated with mesoscale convective systems is added in a large round area at roughly 560 hPa. Evaporative cooling and subsidence warming below result in a cold anomaly at roughly 560–750 hPa and, especially, a warm anomaly at roughly 750–900 hPa. The cold-over-warm anomalies are stronger with smaller low- to midtropospheric relative humidity in the initial conditions, with the maximum magnitude of the warm anomaly ranging between 0.7 and 1.2 K. The temperature anomalies propagate to the environment and still remain present after precipitation stops. The results show that evaporation of stratiform precipitation alone can lead to temperature structures, which are on the same order of magnitude as the observed ones, that potentially inhibit subsequent convection by increasing convective inhibition. Therefore, the representation of microphysical processes affecting the location, amount, and vertical and horizontal distribution of stratiform precipitation and its evaporation in numerical models requires special attention.

scholarly journals A Two-Season Impact Study of Radiative Forced Tropospheric Response to Stratospheric Initial Conditions Inferred From Satellite Radiance Assimilation

Climate ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 114
Author(s):  
Min Shao ◽  
Yansong Bao ◽  
George P. Petropoulos ◽  
Hongfang Zhang
Keyword(s):  
Weather Forecasting ◽  
Initial Conditions ◽  
Stratospheric Ozone ◽  
Wrf Model ◽  
Lower Troposphere ◽  
Short Wave ◽  
Advanced Technology ◽  
Short Term ◽  
Radiative Processes ◽  
Stratospheric Temperature

This study investigated the impacts of stratospheric temperatures and their variations on tropospheric short-term weather forecasting using the Advanced Research Weather Research and Forecasting (WRF-ARW) system with real satellite data assimilation. Satellite-borne microwave stratospheric temperature measurements up to 1 mb, from the Advanced Microwave Sounding Unit-A (AMSU-A), the Advanced Technology Microwave Sounder (ATMS), and the Special Sensor microwave Imager/Sounder (SSMI/S), were assimilated into the WRF model over the continental U.S. during winter and summer 2015 using the community Gridpoint Statistical Interpolation (GSI) system. Adjusted stratospheric temperature related to upper stratospheric ozone absorption of short-wave (SW) radiation further lead to vibration in downward SW radiation in winter predictions and overall reduced with a maximum of 5.5% reduction of downward SW radiation in summer predictions. Stratospheric signals in winter need 48- to 72-h to propagate to the lower troposphere while near-instant tropospheric response to the stratospheric initial conditions are observed in summer predictions. A schematic plot illustrated the physical processes of the coupled stratosphere and troposphere related to radiative processes. Our results suggest that the inclusion of the entire stratosphere and better representation of the upper stratosphere are important in regional NWP systems in short-term forecasts.

A Comparative Study to Quantify Sensitive Dependence in Numerical Models for a Developing Low in the Southern Plains

2010 ◽  
Vol 44-45 (2010-2011) ◽  
pp. 29-40
Author(s):  
Amy E. Schnetzler ◽  
Justin M. Glisan ◽  
H. Athar ◽  
Patrick S. Market ◽  
Anthony R. Lupo
Keyword(s):  
Chaotic Systems ◽  
Initial Conditions ◽  
Numerical Models ◽  
Wrf Model ◽  
Convective Precipitation ◽  
Southern Plains ◽  
Southeast United States ◽  
Sensitive Dependence ◽  
Trajectory Divergence

Abstract Studies have shown that numerical models display the characteristics of chaotic systems, and that the solutions can be sensitive to the initial conditions, the model used, or the parameterizations used. Using the Kain-Fritsch, Grell, and modified Kuo convective parameterizations in the MASS and the WRF model, the results from a case study show that 48-h forecasts were not identical. Lyapunov exponents were calculated by plotting forecast trajectories in a phase diagram and estimating the rate of trajectory divergence for two time periods outside the study of the main cyclone. These calculations did show divergence at a rate which was consistent with differences in model height in 48-h forecasts from other studies. Additionally, the integrated enstrophy can be used to estimate the Lyapunov value. Finally, a qualitative analysis comparing various model runs (pseudo-ensemble) was performed to determine if there were regions or areas where consistent differences in the runs existed between the indexes used for forecasting convective precipitation. Results demonstrated that the region of the southeast United States associated with the developing cyclone showed the most significant differences in these indexes and for heights and temperatures. The differences in the model forecasts between convective parameterizations (intramodel forecasts) in this case were not as great as the model-to-model forecast differences (intermodel forecasts).

scholarly journals A Rational Numerical Method for Simulation of Drop-Impact Dynamics of Oleo-Pneumatic Landing Gear

2021 ◽  
Vol 11 (9) ◽  
pp. 4136
Author(s):  
Rosario Pecora
Keyword(s):  
Numerical Method ◽  
Initial Conditions ◽  
Impact Load ◽  
Numerical Models ◽  
Landing Gear ◽  
Design Stage ◽  
Impact Dynamics ◽  
State Variables ◽  
Adopted Model ◽  
The Impact

Oleo-pneumatic landing gear is a complex mechanical system conceived to efficiently absorb and dissipate an aircraft’s kinetic energy at touchdown, thus reducing the impact load and acceleration transmitted to the airframe. Due to its significant influence on ground loads, this system is generally designed in parallel with the main structural components of the aircraft, such as the fuselage and wings. Robust numerical models for simulating landing gear impact dynamics are essential from the preliminary design stage in order to properly assess aircraft configuration and structural arrangements. Finite element (FE) analysis is a viable solution for supporting the design. However, regarding the oleo-pneumatic struts, FE-based simulation may become unpractical, since detailed models are required to obtain reliable results. Moreover, FE models could not be very versatile for accommodating the many design updates that usually occur at the beginning of the landing gear project or during the layout optimization process. In this work, a numerical method for simulating oleo-pneumatic landing gear drop dynamics is presented. To effectively support both the preliminary and advanced design of landing gear units, the proposed simulation approach rationally balances the level of sophistication of the adopted model with the need for accurate results. Although based on a formulation assuming only four state variables for the description of landing gear dynamics, the approach successfully accounts for all the relevant forces that arise during the drop and their influence on landing gear motion. A set of intercommunicating routines was implemented in MATLAB® environment to integrate the dynamic impact equations, starting from user-defined initial conditions and general parameters related to the geometric and structural configuration of the landing gear. The tool was then used to simulate a drop test of a reference landing gear, and the obtained results were successfully validated against available experimental data.

scholarly journals The Process of Stellar Tidal Disruption by Supermassive Black Holes

2021 ◽  
Vol 217 (3) ◽  
Author(s):  
E. M. Rossi ◽  
N. C. Stone ◽  
J. A. P. Law-Smith ◽  
M. Macleod ◽  
G. Lodato ◽  
...  
Keyword(s):  
Black Holes ◽  
Initial Conditions ◽  
Numerical Models ◽  
Binary Star ◽  
Tidal Disruption ◽  
Massive Black Hole ◽  
Accretion Flows ◽  
Simple Order ◽  
Order Of Magnitude ◽  
A Chain

AbstractTidal disruption events (TDEs) are among the brightest transients in the optical, ultraviolet, and X-ray sky. These flares are set into motion when a star is torn apart by the tidal field of a massive black hole, triggering a chain of events which is – so far – incompletely understood. However, the disruption process has been studied extensively for almost half a century, and unlike the later stages of a TDE, our understanding of the disruption itself is reasonably well converged. In this Chapter, we review both analytical and numerical models for stellar tidal disruption. Starting with relatively simple, order-of-magnitude physics, we review models of increasing sophistication, the semi-analytic “affine formalism,” hydrodynamic simulations of the disruption of polytropic stars, and the most recent hydrodynamic results concerning the disruption of realistic stellar models. Our review surveys the immediate aftermath of disruption in both typical and more unusual TDEs, exploring how the fate of the tidal debris changes if one considers non-main sequence stars, deeply penetrating tidal encounters, binary star systems, and sub-parabolic orbits. The stellar tidal disruption process provides the initial conditions needed to model the formation of accretion flows around quiescent massive black holes, and in some cases may also lead to directly observable emission, for example via shock breakout, gravitational waves or runaway nuclear fusion in deeply plunging TDEs.

scholarly journals Application of Adjoint-Derived Forecast Sensitivities to the 24–25 January 2000 U.S. East Coast Snowstorm

2005 ◽  
Vol 133 (11) ◽  
pp. 3148-3175 ◽  
Author(s):  
Daryl T. Kleist ◽  
Michael C. Morgan
Keyword(s):  
Response Function ◽  
Initial Conditions ◽  
Forecast Error ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Vertical Motion ◽  
Initial Condition ◽  
Response Functions ◽  
Eastern United States ◽  
Surface Cyclone

Abstract The 24–25 January 2000 eastern United States snowstorm was noteworthy as operational numerical weather prediction (NWP) guidance was poor for lead times as short as 36 h. Despite improvements in the forecast of the surface cyclone position and intensity at 1200 UTC 25 January 2000 with decreasing lead time, NWP guidance placed the westward extent of the midtropospheric, frontogenetically forced precipitation shield too far to the east. To assess the influence of initial condition uncertainties on the forecast of this event, an adjoint model is used to evaluate forecast sensitivities for 36- and 48-h forecasts valid at 1200 UTC 25 January 2000 using as response functions the energy-weighted forecast error, lower-tropospheric circulation about a box surrounding the surface cyclone, 750-hPa frontogenesis, and vertical motion. The sensitivities with respect to the initial conditions for these response functions are in general very similar: geographically isolated, maximized in the middle and lower troposphere, and possessing an upshear vertical tilt. The sensitivities are maximized in a region of enhanced low-level baroclinicity in the vicinity of the surface cyclone’s precursor upper trough. However, differences in the phase and structure of the gradients for the four response functions are evident, which suggests that perturbations could be constructed to alter one response function but not necessarily the others. Gradients of the forecast error response function with respect to the initial conditions are used in an iterative procedure to construct initial condition perturbations that reduce the forecast error. These initial condition perturbations were small in terms of both spatial scale and magnitude. Those initial condition perturbations that were confined primarily to the midtroposphere grew rapidly into much larger amplitude upper-and-lower tropospheric perturbations. The perturbed forecasts were not only characterized by reduced final time forecast error, but also had a synoptic evolution that more closely followed analyses and observations.

scholarly journals Nondissipative and Dissipative Momentum Deposition by Mountain Wave Events in Sheared Environments

2018 ◽  
Vol 75 (8) ◽  
pp. 2721-2740 ◽  
Author(s):  
Christopher G. Kruse ◽  
Ronald B. Smith
Keyword(s):  
Broad Spectrum ◽  
Numerical Models ◽  
Wrf Model ◽  
Vertical Wind Shear ◽  
Mountain Wave ◽  
Subsequent Evolution ◽  
Event Duration ◽  
Mountain Waves ◽  
Vertical Dispersion ◽  
Nonlinear Transient

AbstractMountain waves (MWs) are generated during episodic cross-barrier flow over broad-spectrum terrain. However, most MW drag parameterizations neglect transient, broad-spectrum dynamics. Here, the influences of these dynamics on both nondissipative and dissipative momentum deposition by MW events are quantified in a 2D, horizontally periodic idealized framework. The influences of the MW spectrum, vertical wind shear, and forcing duration are investigated. MW events are studied using three numerical models—the nonlinear, transient WRF Model; a linear, quasi-transient Fourier-ray model; and an optimally tuned Lindzen-type saturation parameterization—allowing quantification of total, nondissipative, and dissipative MW-induced decelerations, respectively. Additionally, a pseudomomentum diagnostic is used to estimate nondissipative decelerations within the WRF solutions. For broad-spectrum MWs, vertical dispersion controls spectrum evolution aloft. Short MWs propagate upward quickly and break first at the highest altitudes. Subsequently, the arrival of additional longer MWs allows breaking at lower altitudes because of their greater contribution to u variance. As a result, minimum breaking levels descend with time and event duration. In zero- and positive-shear environments, this descent is not smooth but proceeds downward in steps as a result of vertically recurring steepening levels. Nondissipative decelerations are nonnegligible and influence an MW’s approach to breaking, but breaking and dissipative decelerations quickly develop and dominate the subsequent evolution. Comparison of the three model solutions suggests that the conventional instant propagation and monochromatic parameterization assumptions lead to too much MW drag at too low an altitude.

scholarly journals Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC<sup>4</sup>RS and DISCOVER-AQ airborne campaigns

2017 ◽  
Vol 10 (8) ◽  
pp. 3085-3104 ◽  
Author(s):  
Min Huang ◽  
Gregory R. Carmichael ◽  
James H. Crawford ◽  
Armin Wisthaler ◽  
Xiwu Zhan ◽  
...  
Keyword(s):  
Case Studies ◽  
Air Temperature ◽  
Initial Conditions ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Heat Fluxes ◽  
Aircraft Observation ◽  
Near Surface ◽  
Boundary Layer Height ◽  
Small Scales

Abstract. Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ∼ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

scholarly journals Assimilation of Lightning Data Using a Nudging Method Involving Low-Level Warming

2014 ◽  
Vol 142 (12) ◽  
pp. 4850-4871 ◽  
Author(s):  
Max R. Marchand ◽  
Henry E. Fuelberg
Keyword(s):  
Numerical Models ◽  
Deep Convection ◽  
Computational Cost ◽  
Wrf Model ◽  
Stage Iv ◽  
Simulated Precipitation ◽  
Synoptic Forcing ◽  
Total Lightning ◽  
Mu Method ◽  
Short Time

Abstract This study presents a new method for assimilating lightning data into numerical models that is suitable at convection-permitting scales. The authors utilized data from the Earth Networks Total Lightning Network at 9-km grid spacing to mimic the resolution of the Geostationary Lightning Mapper (GLM) that will be on the Geostationary Operational Environmental Satellite-R (GOES-R). The assimilation procedure utilizes the numerical Weather Research and Forecasting (WRF) Model. The method (denoted MU) warms the most unstable low levels of the atmosphere at locations where lightning was observed but deep convection was not simulated based on the absence of graupel. Simulation results are compared with those from a control simulation and a simulation employing the lightning assimilation method developed by Fierro et al. (denoted FO) that increases water vapor according to a nudging function that depends on the observed flash rate and simulated graupel mixing ratio. Results are presented for three severe storm days during 2011 and compared with hourly NCEP stage-IV precipitation observations. Compared to control simulations, both the MU and FO assimilation methods produce improved simulated precipitation fields during the assimilation period and a short time afterward based on subjective comparisons and objective statistical scores (~0.1, or 50%, improvement of equitable threat scores). The MU generally performs better at simulating isolated thunderstorms and other weakly forced deep convection, while FO performs better for the case having strong synoptic forcing. Results show that the newly developed MU method is a viable alternative to the FO method, exhibiting utility in producing thunderstorms where observed, and providing improved analyses at low computational cost.

scholarly journals The Use of Moist Potential Vorticity Vector as Diagnostic Variable of Rainfall Events in Tanzania

2017 ◽  
Vol 9 (5) ◽  
pp. 1
Author(s):  
Philbert Modest Luhunga ◽  
Agnes Kijazi ◽  
Ladislaus Chang a ◽  
Chuki A Sangalugembe ◽  
Doreen Mwara Anande ◽  
...  
Keyword(s):  
Potential Vorticity ◽  
Wrf Model ◽  
Lower Troposphere ◽  
Topographic Effects ◽  
New Paradigm ◽  
Rainfall Events ◽  
North Eastern ◽  
Vorticity Vector ◽  
Moist Potential Vorticity ◽  
Thermodynamic Variables

The work of this paper is a first step of the new paradigm, to use the Moist Potential Vorticity Vector (MPVV) as a diagnostic variable of rainfall events in Tanzania. The paper aims at computing and assessing the usefulness of MPVV in the diagnosis of rainfall events that occurred on 08th and 09th May 2017 over different regions in Tanzania. The relative contributions of horizontal, vertical components and the magnitude of MPVV on diagnosis of rainfall events are assessed. Hourly dynamic and thermodynamic variables of wind speed, temperature, atmospheric pressure and relative humidity from the numerical output generated by the Weather Research and Forecasting (WRF) Model, running at Tanzania Meteorological Agency (TMA) are used in computation of MPVV. The computed MPVV is then compared with WRF model forecasts and observed rainfall. It is found that in most parts of the country, particularly over coastal areas and North-Eastern Highlands, MPVV exhibited positive values in the lower troposphere (925hPa) and (850hPa) indicating local instability possibly associated with topographic effects, and continent/ocean contrast. MPVV is mostly positive with slightly negative values indicating instabilities (due to possible convective instability). Moreover, MPVV provides remarkably accurate tracking of the locations received rainfall, suggesting its potential use as a dynamic diagnostic variable of rainfall events in Tanzania.

scholarly journals Assessing the Potential of a Long-Term Climate Forecast for Cuba Using the WRF Model

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Lourdes Álvarez-Escudero ◽  
Yandy G. Mayor ◽  
Israel Borrajero-Montejo ◽  
Arnoldo Bezanilla-Morlot
Keyword(s):  
Mesoscale Model ◽  
Initial Conditions ◽  
Wrf Model ◽  
Reanalysis Data ◽  
Weather Research And Forecasting ◽  
Tropical Storms ◽  
Precipitation Regime ◽  
Wide Debate ◽  
One Year ◽  
Cumulative Precipitation

Seasonal climatic prediction studies are a matter of wide debate all over the world. Cuba, a mainly agricultural nation, should greatly benefit from the knowledge, which is available months in advance of the precipitation regime and allows for the proper management of water resources. In this work, a series of six experiments were made with a mesoscale model WRF (Weather Research and Forecasting Model) that produced a 15-month forecast for each month of cumulative precipitation starting at two dates, and for three non-consecutive years with different meteorological characteristics: one dry year (2004), one year that started dry and turned rainy (2005), and one year where several tropical storms occurred (2008). ERA-Interim reanalysis data were used for the initial and border conditions and experiments started 1 month before the beginning of the rainy and the dry seasons, respectively. In a general sense, the experience of using WRF indicated that it was a valid resource for seasonal forecast, since the results obtained were in the same range as those reported by the literature for similar cases. Several limitations were revealed by the results: the forecasts underestimated the monthly cumulative precipitation figures, tropical storms entering through the borders sometimes followed courses different from the real courses inside the working domain, storms that developed inside the domain were not reproduced by WRF, and differences in initial conditions led to significantly different forecasts for the corresponding time steps (nonlinearity). Changing the model parameterizations and initial conditions of the ensemble forecast experiments was recommended.

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