scholarly journals Multiscale Mountain Waves Influencing a Major Orographic Precipitation Event

2007 ◽  
Vol 64 (3) ◽  
pp. 711-737 ◽  
Author(s):  
Matthew F. Garvert ◽  
Bradley Smull ◽  
Cliff Mass
Keyword(s):  
Mesoscale Model ◽  
Precipitation Forecast ◽  
Precipitation Event ◽  
Small Scale ◽  
Second Phase ◽  
Mountain Waves ◽  
Low Level ◽  
Orographic Rainfall ◽  
Vertically Propagating ◽  
Horizontal Wavelength

Abstract This study combines high-resolution mesoscale model simulations and comprehensive airborne Doppler radar observations to identify kinematic structures influencing the production and mesoscale distribution of precipitation and microphysical processes during a period of heavy prefrontal orographic rainfall over the Cascade Mountains of Oregon on 13–14 December 2001 during the second phase of the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) field program. Airborne-based radar detection of precipitation from well upstream of the Cascades to the lee allows a depiction of terrain-induced wave motions in unprecedented detail. Two distinct scales of mesoscale wave–like air motions are identified: 1) a vertically propagating mountain wave anchored to the Cascade crest associated with strong midlevel zonal (i.e., cross barrier) flow, and 2) smaller-scale (<20-km horizontal wavelength) undulations over the windward foothills triggered by interaction of the low-level along-barrier flow with multiple ridge–valley corrugations oriented perpendicular to the Cascade crest. These undulations modulate cloud liquid water (CLW) and snow mixing ratios in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), with modeled structures comparing favorably to radar-documented zones of enhanced reflectivity and CLW measured by the NOAA P3 aircraft. Errors in the model representation of a low-level shear layer and the vertically propagating mountain waves are analyzed through a variety of sensitivity tests, which indicated that the mountain wave’s amplitude and placement are extremely sensitive to the planetary boundary layer (PBL) parameterization being employed. The effects of 1) using unsmoothed versus smoothed terrain and 2) the removal of upstream coastal terrain on the flow and precipitation over the Cascades are evaluated through a series of sensitivity experiments. Inclusion of unsmoothed terrain resulted in net surface precipitation increases of ∼4%–14% over the windward slopes relative to the smoothed-terrain simulation. Small-scale waves (<20-km horizontal wavelength) over the windward slopes significantly impact the horizontal pattern of precipitation and hence quantitative precipitation forecast (QPF) accuracy.

scholarly journals Heavy Rainfall Associated with Double Low-Level Jets over Southern China. Part II: Convection Initiation

2019 ◽  
Vol 147 (2) ◽  
pp. 543-565 ◽  
Author(s):  
Yu Du ◽  
Guixing Chen
Keyword(s):  
Heavy Rainfall ◽  
Mesoscale Model ◽  
Southern China ◽  
Northern South China Sea ◽  
Lower Troposphere ◽  
Small Scale ◽  
The South ◽  
Low Level ◽  
Low Level Jets ◽  
Convection Initiation

Abstract Heavy rainfall that occurred at the south coast of China on 10–11 May 2014 was associated with a synoptic-system-related low-level jet (SLLJ) and a boundary layer jet (BLJ). To clarify the role of the double low-level jets in convection initiation (CI), we perform convective-permitting simulations using a nonhydrostatic mesoscale model. The simulations reproduce the occurrence location and mesoscale evolution of new convective cells as well as their small-scale wavelike structures at the elevated layers, which are generally consistent with radar observations despite some differences in their orientation. The nighttime BLJ over the northern South China Sea strengthens the convergence at ~950 hPa near the coast where the BLJ’s northern terminus reaches the coastal terrain. Meanwhile, the SLLJ to the south of the inland cold front provides divergence at ~700 hPa near the SLLJ’s entrance region. Such low-level convergence and midlevel divergence collectively produce strong mesoscale lifting for CI at the coast. In addition to the enhanced mesoscale lifting, the double low-level jets also provide favorable conditions for the superimposed small-scale disturbances that can serve as effective moistening mechanisms of the lower troposphere during CI. In a sensitivity experiment with coastal terrain removed, CI still occurs near the coast but is delayed and weaker compared to the control run. This latter experiment suggests that double low-level jets and their coupling indeed exert key effects on CI, while the BLJ colliding with terrain may enhance coastal convergence for amplifying CI. These findings provide new insights into the occurrence of coastal heavy rainfall in the warm sector far ahead of the fronts.

scholarly journals Occurrence and Development of an Extreme Precipitation Event in the Ili Valley, Xinjiang, China and Analysis of Gravity Waves

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 752
Author(s):  
Xin Huang ◽  
Yushu Zhou ◽  
Lu Liu
Keyword(s):  
Gravity Waves ◽  
Extreme Precipitation ◽  
Extreme Precipitation Event ◽  
Precipitation Event ◽  
Energy Propagation ◽  
Mesoscale Vortex ◽  
Low Level ◽  
Convergence Line ◽  
Upper Level ◽  
Horizontal Wavelength

We used observational data and the results from a high-resolution numerical simulation model to analyze the occurrence and development of an extreme precipitation event in the Ili Valley, Xinjiang, China on 26 June 2015. We analyzed the horizontal wavelength, period, speed, ducting, energy propagation and feedback mechanism of inertial gravity waves. A low-level convergence line was formed in the valley by the northerly and westerly winds as a result of Central Asian vortices and the trumpet-shaped topography of the Ili Valley. There was sufficient water vapor in the valley for the precipitation event to develop. A mesoscale vortex formed and developed on the low-level convergence line and the rainfall was distributed either near the convergence line or the mesoscale vortex. The low-level convergence line and the uplift caused by the terrain triggered convection, and then the convection triggered waves at lower levels. The combination of ascending motion induced by the lower level waves and the mesoscale vortex led to the development of convection, causing the precipitation to intensify. When the convection moved eastward to Gongliu County, it was coupled with the ascending phase of upper level waves, causing both the convection and precipitation to intensify again. We applied spectral analysis methods to verify that the waves were inertial gravity waves. The upper level inertial gravity waves propagated westward at a mean speed of −12 m s−1 with periods of 73–179 min and horizontal wavelengths of 50–55 km. The lower level inertial gravity waves propagated eastward at a mean speed of 8 m s−1 with periods of 73–200 min and a horizontal wavelength of 85 km. The more (less) favorable waveguide conditions determined whether the gravity waves persisted for a long (short) time and propagated for a longer (shorter) distance. Based on the mesoscale Eliassen–Palm flux theory, the wave energy of inertial gravity waves had an important effect on the maintenance and development of convection and precipitation by affecting wind strength and wind divergence. Feedback was mainly through the meridional and vertical transport of zonal momentum and the meridional transport of heat.

scholarly journals Analysis of Mountain Wave Effects on a Hard Landing Incident in Pico Aerodrome Using the AROME Model and Airborne Observations

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 350 ◽  
Author(s):  
Jin Maruhashi ◽  
Pedro Serrão ◽  
Margarida Belo-Pereira
Keyword(s):  
Froude Number ◽  
Wind Shear ◽  
Mesoscale Model ◽  
Stable Stratification ◽  
Flight Path ◽  
Civil Aviation ◽  
Mountain Waves ◽  
Wind Speeds ◽  
Wave Effects ◽  
Vertically Propagating

A hard landing incident in Pico Aerodrome (LPPI) involving an Airbus A320-200 aircraft is investigated using airborne observations and forecasts of the AROME (Applications of Research to Operations at Mesoscale) model. A second flight is also analyzed. The severity of the wind shear during both flights is quantified using the intensity factor “I” that is based on aerial data and recommended by ICAO (International Civil Aviation Organization). During Flight 1, 36% of the landing phase (below 2100 ft) occurred under “severe” wind shear conditions and 16% occurred under “strong” conditions. Upstream characteristics included southwest winds, stable stratification and a Froude number close to 1. According to the AROME model, these circumstances triggered the development of vertically propagating mountain waves, with maximum vertical velocities above 400 ft/min and exceeding 200 ft/min in the flight path. These conditions, together with the severe wind shear, may have caused the incident. During the second flight, a wake with lee vortices and reversed flow developed in the region of the flight path, which is consistent with a low upstream Froude number and/or with the flow regime diagram of previous studies. During the approach phase of this flight, “severe” wind shear conditions were absent, with “strong” ones occurring 4% of the time. It predominantly displayed “light” conditions during 68% of this phase. As a result of the comparison between “I” and the AROME turbulence indicators, preliminary thresholds are proposed for these indexes. Lastly, this study provides an objective verification of AROME wind forecasts, showing a good agreement with airborne observations for wind speeds above 10 kt, but a poor skill for weaker winds.

The Impact of Moisture on Mountain Waves during T-REX

2009 ◽  
Vol 137 (11) ◽  
pp. 3888-3906 ◽  
Author(s):  
Qingfang Jiang ◽  
James D. Doyle
Keyword(s):  
Sierra Nevada ◽  
Mesoscale Model ◽  
Buoyancy Frequency ◽  
Mountain Range ◽  
Linear Wave ◽  
Owens Valley ◽  
Mountain Waves ◽  
Low Level ◽  
The Impact ◽  
Moist Layer

Abstract The impact of moist processes on mountain waves over Sierra Nevada Mountain Range is investigated in this study. Aircraft measurements over Owens Valley obtained during the Terrain-induced Rotor Experiment (T-REX) indicate that mountain waves were generally weaker when the relative humidity maximum near the mountaintop level was above 70%. Four moist cases with a RH maximum near the mountaintop level greater than 90% have been further examined using a mesoscale model and a linear wave model. Two competing mechanisms governing the influence of moisture on mountain waves have been identified. The first mechanism involves low-level moisture that enhances flow–terrain interaction by reducing windward flow blocking. In the second mechanism, the moist airflow tends to damp mountain waves through destratifying the airflow and reducing the buoyancy frequency. The second mechanism dominates in the presence of a deep moist layer in the lower to middle troposphere, and the wave amplitude is significantly reduced associated with a smaller moist buoyancy frequency. With a shallow moist layer and strong low-level flow, the two mechanisms can become comparable in magnitude and largely offset each other.

Evaluation of Convection-Permitting Precipitation Forecast Products Using WRF, NMMB, and FV3 for the 2016–17 NOAA Hydrometeorology Testbed Flash Flood and Intense Rainfall Experiments

2019 ◽  
Vol 34 (3) ◽  
pp. 781-804 ◽  
Author(s):  
Nathan Snook ◽  
Fanyou Kong ◽  
Keith A. Brewster ◽  
Ming Xue ◽  
Kevin W. Thomas ◽  
...  
Keyword(s):  
Mesoscale Model ◽  
Flash Flood ◽  
Precipitation Forecast ◽  
Small Scale ◽  
Intense Rainfall ◽  
Ensemble Forecasts ◽  
Probabilistic Forecasts ◽  
Ensemble Mean ◽  
Substantial Bias ◽  
Cubed Sphere

Abstract During the summers of 2016 and 2017, the Center for Analysis and Prediction of Storms (CAPS) ran real-time storm-scale ensemble forecasts (SSEFs) in support of the Hydrometeorology Testbed (HMT) Flash Flood and Intense Rainfall (FFaIR) experiment. These forecasts, using WRF-ARW and Nonhydrostatic Mesoscale Model on the B-grid (NMMB) in 2016, and WRF-ARW and GFDL Finite Volume Cubed-Sphere Dynamical Core (FV3) in 2017, covered the contiguous United States at 3-km horizontal grid spacing, and supported the generation and evaluation of precipitation forecast products, including ensemble probabilistic products. Forecasts of 3-h precipitation accumulation are evaluated. Overall, the SSEF produces skillful 3-h accumulated precipitation forecasts, with ARW members generally outperforming NMMB members and the single FV3 member run in 2017 outperforming ARW members; these differences are significant at some forecast hours. Statistically significant differences exist in the performance, in terms of bias and ETS, among subensembles of members sharing common microphysics and PBL schemes. Year-to-year consistency is higher for PBL subensembles than for microphysical subensembles. Probability-matched (PM) ensemble mean forecasts outperform individual members, while the simple ensemble mean exhibits substantial bias. A newly developed localized probability-matched (LPM) ensemble mean product was produced in 2017; compared to the simple ensemble mean and the conventional PM mean, the LPM mean exhibits improved retention of small-scale structures, evident in both 2D forecast fields and variance spectra. Probabilistic forecasts of precipitation exceeding flash flood guidance (FFG) or thresholds associated with recurrence intervals (RI) ranging from 10 to 100 years show utility in predicting regions of flooding threat, but generally overpredict the occurrence of such events; however, they may still be useful in subjective flash flood risk assessment.

scholarly journals The 13–14 December 2001 IMPROVE-2 Event. Part I: Synoptic and Mesoscale Evolution and Comparison with a Mesoscale Model Simulation

2005 ◽  
Vol 62 (10) ◽  
pp. 3474-3492 ◽  
Author(s):  
Matthew F. Garvert ◽  
Brian A. Colle ◽  
Clifford F. Mass
Keyword(s):  
Large Scale ◽  
Mesoscale Model ◽  
Model Simulation ◽  
Heavy Precipitation ◽  
Middle Level ◽  
Model Verification ◽  
Precipitation Event ◽  
Low Level ◽  
Baroclinic Zone

Abstract This paper describes the large-scale synoptic and mesoscale features of a major precipitation event that affected the second Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) study area on 13–14 December 2001. The fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) was used to simulate both the synoptic and mesoscale features of the storm. Extensive model verification was performed utilizing the wealth of observational assets available during the experiment, including in situ aircraft measurements, radiosondes, radar data, and surface observations. The 13–14 December 2001 storm system was characterized by strong low-level cross-barrier flow, heavy precipitation, and the passage of an intense baroclinic zone. The model realistically simulated the three-dimensional thermodynamic and kinematic fields, the forward-tilted vertical structure of the baroclinic zone, and the associated major precipitation band. Deficiencies in the model simulations included an attenuated low-level jet accompanying the middle-level baroclinic zone and the lack of precipitation associated with the surface front; NOAA P-3 aircraft in situ data indicated that the model required 1.33-km grid spacing to capture realistically the complex mesoscale forcing related to terrain features. Despite the relatively skillful portrayal of mesoscale and synoptic structures, the model overpredicted precipitation in localized areas on the windward slopes and over a broad area to the lee of the Oregon Cascades.

scholarly journals Low-Level Wind Shear Identification along the Glide Path at BCIA by the Pulsed Coherent Doppler Lidar

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 50
Author(s):  
Hongwei Zhang ◽  
Xiaoying Liu ◽  
Qichao Wang ◽  
Jianjun Zhang ◽  
Zhiqiang He ◽  
...  
Keyword(s):  
Wind Shear ◽  
Vertical Direction ◽  
Small Scale ◽  
Observation Data ◽  
Doppler Lidar ◽  
Low Level ◽  
Glide Path ◽  
Coherent Doppler Lidar ◽  
Scanning Strategies ◽  
Meteorological Phenomenon

Low-level wind shear is usually to be a rapidly changing meteorological phenomenon that cannot be ignored in aviation security service by affecting the air speed of landing and take-off aircrafts. The lidar team in Ocean University of China (OUC) carried out the long term particular researches on the low-level wind shear identification and regional wind shear inducement search at Beijing Capital International Airport (BCIA) from 2015 to 2020 by operating several pulsed coherent Doppler lidar (PCDL) systems. On account of the improved glide path scanning strategy and virtual multiple wind anemometers based on the rang height indicator (RHI) modes, the small-scale meteorological phenomenon along the glide path and/or runway center line direction can be captured. In this paper, the device configuration, scanning strategies, and results of the observation data are proposed. The algorithms to identify the low-level wind shear based on the reconstructed headwind profiles data have been tested and proved based on the lidar data obtained from December 2018 to January 2019. High spatial resolution observation data at vertical direction are utilized to study the regional wind shear inducement at the 36L end of BCIA under strong northwest wind conditions.

scholarly journals The South Georgia Wave Experiment: A Means for Improved Analysis of Gravity Waves and Low-Level Wind Impacts Generated from Mountainous Islands

2018 ◽  
Vol 99 (5) ◽  
pp. 1027-1040 ◽  
Author(s):  
D. R. Jackson ◽  
A. Gadian ◽  
N. P. Hindley ◽  
L. Hoffmann ◽  
J. Hughes ◽  
...  
Keyword(s):  
High Resolution ◽  
Gravity Waves ◽  
Numerical Models ◽  
Small Island ◽  
Small Scale ◽  
The South ◽  
South Georgia ◽  
Low Level ◽  
Wave Experiment ◽  
Realistic Representation

AbstractGravity waves (GWs) play an important role in many atmospheric processes. However, the observation-based understanding of GWs is limited, and representing them in numerical models is difficult. Recent studies show that small islands can be intense sources of GWs, with climatologically significant effects on the atmospheric circulation. South Georgia, in the South Atlantic, is a notable source of such “small island” waves. GWs are usually too small scale to be resolved by current models, so their effects are represented approximately using resolved model fields (parameterization). However, the small-island waves are not well represented by such parameterizations, and the explicit representation of GWs in very-high-resolution models is still in its infancy. Steep islands such as South Georgia are also known to generate low-level wakes, affecting the flow hundreds of kilometers downwind. These wakes are also poorly represented in models.We present results from the South Georgia Wave Experiment (SG-WEX) for 5 July 2015. Analysis of GWs from satellite observations is augmented by radiosonde observations made from South Georgia. Simulations were also made using high-resolution configurations of the Met Office Unified Model (UM). Comparison with observations indicates that the UM performs well for this case, with realistic representation of GW patterns and low-level wakes. Examination of a longer simulation period suggests that the wakes generally are well represented by the model. The realism of these simulations suggests they can be used to develop parameterizations for use at coarser model resolutions.

scholarly journals The Effect of Upstream Convection on Downstream Precipitation

2007 ◽  
Vol 22 (2) ◽  
pp. 255-277 ◽  
Author(s):  
Kelly M. Mahoney ◽  
Gary M. Lackmann
Keyword(s):  
Moisture Transport ◽  
Weather Prediction ◽  
The United States ◽  
Cold Season ◽  
Precipitation Forecast ◽  
Study Region ◽  
Low Level ◽  
Convective Systems ◽  
Eta Model ◽  
Nwp Model

Abstract Operational forecasters in the southeast and mid-Atlantic regions of the United States have noted a positive quantitative precipitation forecast (QPF) bias in numerical weather prediction (NWP) model forecasts downstream of some organized, cold-season convective systems. Examination of cold-season cases in which model QPF guidance exhibited large errors allowed identification of two representative cases for detailed analysis. The goals of the case study analyses are to (i) identify physical mechanisms through which the upstream convection (UC) alters downstream precipitation amounts, (ii) determine why operational models are challenged to provide accurate guidance in these situations, and (iii) suggest future research directions that would improve model forecasts in these situations and allow forecasters to better anticipate such events. Two primary scenarios are identified during which downstream precipitation is altered in the presence of UC for the study region: (i) a fast-moving convective (FC) scenario in which organized convective systems oriented parallel to the lower-tropospheric flow are progressive relative to the parent synoptic system, and appear to disrupt poleward moisture transport, and (ii) a situation characterized by slower-moving convection (SC) relative to the parent system. Analysis of a representative FC case indicated that moisture consumption, stabilization via convective overturning, and modification of the low-level flow to a more westerly direction in the postconvective environment all appear to contribute to the reduction of downstream precipitation. In the FC case, operational Eta Model forecasts moved the organized UC too slowly, resulting in an overestimate of downstream moisture transport. A 4-km explicit convection model forecast from the Weather Research and Forecasting model produced a faster-moving upstream convective system and improved downstream QPF. In contrast to the FC event, latent heat release in the primary rainband is shown to enhance the low-level jet ahead of the convection in the SC case, thereby increasing moisture transport into the downstream region. A negative model QPF bias was observed in Eta Model forecasts for the SC event. Suggestions are made for precipitation forecasting in UC situations, and implications for NWP model configuration are discussed.

scholarly journals Impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges

2017 ◽  
Vol 14 ◽  
pp. 187-194 ◽  
Author(s):  
Stefano Federico ◽  
Marco Petracca ◽  
Giulia Panegrossi ◽  
Claudio Transerici ◽  
Stefano Dietrich
Keyword(s):  
Data Assimilation ◽  
Mesoscale Model ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Probability Of Detection ◽  
Precipitation Forecast ◽  
Time Range ◽  
False Alarms ◽  
Forecast Time ◽  
The Impact

Abstract. This study investigates the impact of the assimilation of total lightning data on the precipitation forecast of a numerical weather prediction (NWP) model. The impact of the lightning data assimilation, which uses water vapour substitution, is investigated at different forecast time ranges, namely 3, 6, 12, and 24 h, to determine how long and to what extent the assimilation affects the precipitation forecast of long lasting rainfall events (> 24 h). The methodology developed in a previous study is slightly modified here, and is applied to twenty case studies occurred over Italy by a mesoscale model run at convection-permitting horizontal resolution (4 km). The performance is quantified by dichotomous statistical scores computed using a dense raingauge network over Italy. Results show the important impact of the lightning assimilation on the precipitation forecast, especially for the 3 and 6 h forecast. The probability of detection (POD), for example, increases by 10 % for the 3 h forecast using the assimilation of lightning data compared to the simulation without lightning assimilation for all precipitation thresholds considered. The Equitable Threat Score (ETS) is also improved by the lightning assimilation, especially for thresholds below 40 mm day−1. Results show that the forecast time range is very important because the performance decreases steadily and substantially with the forecast time. The POD, for example, is improved by 1–2 % for the 24 h forecast using lightning data assimilation compared to 10 % of the 3 h forecast. The impact of the false alarms on the model performance is also evidenced by this study.

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