Small-Scale Precipitation Elements in Midlatitude Cyclones Crossing the California Sierra Nevada

2015 ◽  
Vol 143 (7) ◽  
pp. 2842-2870 ◽  
Author(s):  
Socorro Medina ◽  
Robert A. Houze
Keyword(s):  
Sierra Nevada ◽  
Radar Data ◽  
Small Scale ◽  
Particle Collisions ◽  
Mountain Ranges ◽  
Rain Gauges ◽  
Moisture Fluxes ◽  
Frontal Systems ◽  
Microphysical Processes ◽  
Scale Turbulence

Abstract Radar data in some frontal systems passing over the Sierra Nevada of California show large variance on scales of ~10 km. The most prominent features are a few kilometers in scale and are similar to small-scale precipitation cells embedded in fronts seen over other mountain ranges. Other frontal systems crossing the Sierras are characterized by more uniform air motions. Updrafts in large-variance storms have characteristics of shear-induced turbulence, although buoyant instability may also contribute. Large-variance storms occur under stronger upstream winds and vertically integrated cross- and along-barrier moisture fluxes. Rain gauges indicate that large-variance storms have precipitation greater than smaller-variance storms. Stronger horizontal moisture fluxes may provide greater mean upslope condensation rates; however, it is hypothesized that accelerated microphysical processes are needed to most efficiently convert the condensate into precipitation that falls out on the lower slopes before being carried downstream. Radar data indicate that the turbulence embodied in the cellular motions of the large-variance cases is consistent with microphysical enhancement resulting from updraft elements producing pockets of liquid water conducive to riming and coalescence. In addition, radar spectrum-width data show that the cells contain strong subcell-scale turbulence conducive to particle collisions and aggregation. Polarimetric radar data just below the 0°C level show large raindrops in the cells, consistent with aggregation occurring in cells just above the melting layer. It is hypothesized that such enhanced microphysical processes in large-variance cases hasten the growth and fallout in the regions of maximum condensation over the windward slopes.

scholarly journals Joint statistical correction of clutters, spokes and beam height for a radar derived precipitation climatology in southern Germany

2012 ◽  
Vol 16 (11) ◽  
pp. 4101-4117 ◽  
Author(s):  
A. Wagner ◽  
J. Seltmann ◽  
H. Kunstmann
Keyword(s):  
Statistical Analysis ◽  
Cell Tracking ◽  
Weather Radar ◽  
Radar Data ◽  
Small Scale ◽  
Correction Algorithm ◽  
Rain Gauges ◽  
Radar Images ◽  
Statistical Correction ◽  
High Level

Abstract. First results of radar derived climatology have emerged over the last years, as datasets of appropriate extent are becoming available. Usually, these statistics are based on time series lasting up to ten years as continuous storage of radar data was often not achieved before. This kind of climatology demands a high level of data quality. Small deviations or minor systematic under- or overestimations in single radar images become a major cause of error in statistical analysis. Extensive corrections of radar data are a crucial prerequisite for radar derived climatology. We present a new statistical post-correction scheme based on a climatological analysis of seven years of radar data of the Munich weather radar (2000–2006) operated by DWD (German Weather Service). Original radar products are used subject only to corrections within the signal processor without any further corrections on single radar images. The aim of this statistical correction is to make up for the average systematic errors caused by clutter, propagation, or measuring effects but to conserve small-scale natural variations in space. The statistical correction is based on a thorough analysis of the different causes of possible errors for the Munich weather radar. This analysis revealed the following basic effects: the decrease of rain amount as a function of height and distance from the radar, clutter effects such as clutter remnants after filtering, holes by eliminated clutter or shading effects from obstacles near the radar, visible as spokes, as well as the influence of the bright band. The correction algorithm is correspondingly based on these results. It consists of three modules. The first one is an altitude correction which minimises measuring effects. The second module corrects clutter effects and disturbances and the third one realises a mean adjustment to selected rain gauges. Two different sets of radar products are used. The statistical analysis as well as module 1 and module 2 of the correction algorithm are based on frequencies of the six reflectivity levels within the so-called PX product. For correction module 3 and for the validation of the correction algorithm, rain amounts are calculated from the 8-bit so-called DX product. The correction algorithm is created to post-correct climatological or statistical analysis of radar data with a temporal resolution larger than one year. The correction algorithm is used for frequencies of occurrence of radar reflectivities which enables its application even for radar products such as DWD's cell-tracking-product CONRAD. Application (2004–2006) and validation (2007–2009) periods of this correction algorithm with rain gauges show an increased conformity for radar climatology after the statistical correction. In the years 2004 to 2006 the Root-Mean-Square-Error (RMSE) between mean annual rain amounts of rain gauges and corresponding radar pixels decreases from 262 mm to 118 mm excluding those pairs of values where the rain gauges are situated in areas of obviously corrupted radar data. The results for the validation period 2007 to 2009 are based on all pairs of values and show a decline of the RMSE from 322 mm to 174 mm.

scholarly journals Evaluation of Operational and Experimental Precipitation Algorithms and Microphysical Insights during IPHEx

2018 ◽  
Vol 19 (1) ◽  
pp. 113-125 ◽  
Author(s):  
Jessica M. Erlingis ◽  
Jonathan J. Gourley ◽  
Pierre-Emmanuel Kirstetter ◽  
Emmanouil N. Anagnostou ◽  
John Kalogiros ◽  
...  
Keyword(s):  
Radar Data ◽  
Great Smoky Mountains ◽  
Rain Gauges ◽  
Microphysical Parameters ◽  
X Band ◽  
Smoky Mountains ◽  
Precipitation Estimates ◽  
Intensive Observation ◽  
Microphysical Processes ◽  
Observation Period

Abstract During May and June 2014, NOAA X-Pol (NOXP), the National Severe Storms Laboratory’s dual-polarized X-band mobile radar, was deployed to the Pigeon River basin in the Great Smoky Mountains of North Carolina as part of the NASA Integrated Precipitation and Hydrology Experiment. Rain gauges and disdrometers were positioned within the basin to verify precipitation estimates from various radar and satellite precipitation algorithms. First, the performance of the Self-Consistent Optimal Parameterization–Microphysics Estimation (SCOP-ME) algorithm for NOXP was examined using ground instrumentation as validation and was found to perform similarly to or slightly outperform other precipitation algorithms over the course of the intensive observation period (IOP). Radar data were also used to examine ridge–valley differences in radar and microphysical parameters for a case of stratiform precipitation passing over the mountains. Inferred coalescence microphysical processes were found to dominate within the upslope region, while a combination of processes were present as the system propagated over the valley. This suggests that enhanced updrafts aided by orographic lift sustain convection over the upslope regions, leading to larger median drop diameters.

scholarly journals Joint statistical correction of clutters, spokes and beam height for a radar climatology in Southern Germany

2012 ◽  
Vol 9 (4) ◽  
pp. 4703-4746
Author(s):  
A. Wagner ◽  
J. Seltmann ◽  
H. Kunstmann
Keyword(s):  
Statistical Analysis ◽  
Weather Radar ◽  
Radar Data ◽  
Small Scale ◽  
Correction Algorithm ◽  
Rain Gauges ◽  
Radar Images ◽  
Statistical Correction ◽  
First Results ◽  
High Level

Abstract. Extensive corrections of radar data are a crucial prerequisite for radar derived climatology. This kind of climatology demands a high level of data quality. Little deviations or minor systematic underestimations or overestimations in single radar images become a major cause of error in statistical analysis. First results of radar derived climatology have emerged over the last years, as data sets of appropriate extent are becoming available. Usually, these statistics are based on time series lasting up to ten years as storage of radar data was not achieved before. We present a new statistical post-correction scheme, which is based on seven years of radar data of the Munich weather radar (2000–2006) that is operated by DWD (German Weather Service). The typical correction algorithms for single radar images, such as clutter corrections, are used. Then an additional statistical post-correction based on the results of a climatological analysis from radar images follows. The aim of this statistical correction is to correct systematic errors caused by clutter effects or measuring effects but to conserve small-scale natural variations in space. The statistical correction is based on a thorough analysis of the different causes of possible errors for the Munich weather radar. This robust analysis revealed the following basic effects: the decrease of rain rate in relation to height and distance from the radar, clutter effects such as remaining clutter, eliminated clutter or shading effects from obstacles near the radar, visible as spokes, as well as the influence of the Bright Band. The correction algorithm is correspondingly based on these results. It consists of three modules. The first one is an altitude correction, which minimizes measuring effects. The second module corrects clutter effects and the third one realizes a mean adjustment to selected rain gauges. Two different radar products are used. The statistical analysis as well as module one and module two of the correction algorithm are based on frequencies of occurrence of the so-called PX-product with six reflectivity levels. For correction module 3 and for the validation of the correction algorithm rain rates are calculated from the 8-bit-depth so-called DX-product. An application (2004–2006) and a validation (2007–2009) of this correction algorithm with rain gauges show a much higher conformity for radar climatology after the statistical correction. In the years 2004 to 2006 the Root-Mean-Square-Error (RMSE) decreases from 262 mm to 118 mm excluding those pair of values where the rain gauges are situated in areas of obviously corrupted radar data. The results for the validation period 2007 to 2009 are based on all pairs of values and show a decline of the RMSE from 322 mm to 174 mm.

scholarly journals Detailed dual-Doppler structure of Kelvin-Helmholtz waves from an airborne profiling radar over complex terrain. Part II: Evidence for precipitation enhancement from observations and modeling

2021 ◽  
Author(s):  
Coltin Grasmick ◽  
Bart Geerts ◽  
Xia Chu ◽  
Jeffrey R. French ◽  
Robert M. Rauber
Keyword(s):  
Cloud Microphysics ◽  
Mixed Phase ◽  
Small Scale ◽  
Eddy Simulation ◽  
Stratiform Clouds ◽  
Ice Water Content ◽  
Microphysical Processes ◽  
Scale Turbulence ◽  
Ice Water ◽  
Quantitative Impact

AbstractKelvin-Helmholtz (KH) waves are a frequent source of turbulence in stratiform precipitation systems over mountainous terrain. KH waves introduce large eddies into otherwise laminar flow, with updrafts and downdrafts generating small-scale turbulence. When they occur in-cloud, such dynamics influence microphysical processes that impact precipitation growth and fallout. Part I of this paper used dual-Doppler, 2D wind and reflectivity measurements from an airborne cloud radar to demonstrate the occurrence of KH waves in stratiform orographic precipitation systems and identified four mechanisms for triggering KH waves. In Part II, we use similar observations to explore the effects of KH wave updrafts and turbulence on cloud microphysics. Measurements within KH wave updrafts reveal the production of liquid water in otherwise ice-dominated clouds, which can contribute to snow generation or enhancement via depositional and accretional growth. Fallstreaks beneath KH waves contain higher ice water content, composed of larger and more numerous ice particles, suggesting that KH waves and associated turbulence may also increase ice nucleation.A Large-Eddy Simulation (LES), designed to model the microphysical response to the KH wave eddies in mixed phase cloud, shows that depositional and accretional growth can be enhanced in KH waves, resulting in more precipitation when compared to a baseline simulation. While sublimation and evaporation occur in KH downdrafts, persistent supersaturation with respect to ice allows for net increase in ice mass. These modeling results and observations suggest that KH waves embedded in mixed-phase stratiform clouds may increase precipitation, although the quantitative impact remains uncertain.

Similarity of dissipation and enstrophy in particle-induced small-scale turbulence

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Zhuo Wang ◽  
Kun Luo ◽  
Junhua Tan ◽  
Dong Li ◽  
Jianren Fan
Keyword(s):  
Small Scale ◽  
Scale Turbulence

scholarly journals Role of large-scale advection and small-scale turbulence on vertical migration of gyrotactic swimmers

2019 ◽  
Vol 4 (12) ◽  
Author(s):  
C. Marchioli ◽  
H. Bhatia ◽  
G. Sardina ◽  
L. Brandt ◽  
A. Soldati
Keyword(s):  
Vertical Migration ◽  
Large Scale ◽  
Small Scale ◽  
Scale Turbulence

scholarly journals Fabrication of freestanding Pt nanowires for use as thermal anemometry probes in turbulence measurements

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Hai Le-The ◽  
Christian Küchler ◽  
Albert van den Berg ◽  
Eberhard Bodenschatz ◽  
Detlef Lohse ◽  
...  
Keyword(s):  
Room Temperature ◽  
Fluid Velocity ◽  
Current Mode ◽  
Constant Current ◽  
Small Scale ◽  
Turbulence Measurements ◽  
High Dynamic ◽  
Scale Turbulence ◽  
Constant Current Mode ◽  
Pt Nanowires

AbstractWe report a robust fabrication method for patterning freestanding Pt nanowires for use as thermal anemometry probes for small-scale turbulence measurements. Using e-beam lithography, high aspect ratio Pt nanowires (~300 nm width, ~70 µm length, ~100 nm thickness) were patterned on the surface of oxidized silicon (Si) wafers. Combining wet etching processes with dry etching processes, these Pt nanowires were successfully released, rendering them freestanding between two silicon dioxide (SiO2) beams supported on Si cantilevers. Moreover, the unique design of the bridge holding the device allowed gentle release of the device without damaging the Pt nanowires. The total fabrication time was minimized by restricting the use of e-beam lithography to the patterning of the Pt nanowires, while standard photolithography was employed for other parts of the devices. We demonstrate that the fabricated sensors are suitable for turbulence measurements when operated in constant-current mode. A robust calibration between the output voltage and the fluid velocity was established over the velocity range from 0.5 to 5 m s−1 in a SF6 atmosphere at a pressure of 2 bar and a temperature of 21 °C. The sensing signal from the nanowires showed negligible drift over a period of several hours. Moreover, we confirmed that the nanowires can withstand high dynamic pressures by testing them in air at room temperature for velocities up to 55 m s−1.

scholarly journals 3–D Models of Galaxy Magnetic Fields with Spiral Shocks

1990 ◽  
Vol 140 ◽  
pp. 133-134
Author(s):  
J. Panesar ◽  
A.H. Nelson
Keyword(s):  
Gas Flow ◽  
Density Wave ◽  
Shock Velocity ◽  
Small Scale ◽  
Hydrodynamic Simulation ◽  
Dynamo Equation ◽  
Scale Turbulence ◽  
Wave Induced ◽  
The Magnetic Field ◽  
Stellar Density

We report here some preliminary results of 3–D numerical simulations of an α–ω dynamo in galaxies with differential rotation, small–scale turbulence, and a shock wave induced by a stellar density wave. We obtain the magnetic field from the standard dynamo equation, but include the spiral shock velocity field from a hydrodynamic simulation of the gas flow in a gravitational field with a spiral perturbation (Johns and Nelson, 1986).

scholarly journals Predictability of Deep Convection in Idealized and Operational Forecasts: Effects of Radar Data Assimilation, Orography, and Synoptic Weather Regime

2019 ◽  
Vol 148 (1) ◽  
pp. 63-81 ◽  
Author(s):  
Kevin Bachmann ◽  
Christian Keil ◽  
George C. Craig ◽  
Martin Weissmann ◽  
Christian A. Welzbacher
Keyword(s):  
Data Assimilation ◽  
Deep Convection ◽  
Radar Data ◽  
Ensemble Prediction ◽  
Small Scale ◽  
Model Errors ◽  
Ensemble Prediction System ◽  
Beneficial Impact ◽  
The Impact ◽  
Radar Data Assimilation

Abstract We investigate the practical predictability limits of deep convection in a state-of-the-art, high-resolution, limited-area ensemble prediction system. A combination of sophisticated predictability measures, namely, believable and decorrelation scale, are applied to determine the predictable scales of short-term forecasts in a hierarchy of model configurations. First, we consider an idealized perfect model setup that includes both small-scale and synoptic-scale perturbations. We find increased predictability in the presence of orography and a strongly beneficial impact of radar data assimilation, which extends the forecast horizon by up to 6 h. Second, we examine realistic COSMO-KENDA simulations, including assimilation of radar and conventional data and a representation of model errors, for a convectively active two-week summer period over Germany. The results confirm increased predictability in orographic regions. We find that both latent heat nudging and ensemble Kalman filter assimilation of radar data lead to increased forecast skill, but the impact is smaller than in the idealized experiments. This highlights the need to assimilate spatially and temporally dense data, but also indicates room for further improvement. Finally, the examination of operational COSMO-DE-EPS ensemble forecasts for three summer periods confirms the beneficial impact of orography in a statistical sense and also reveals increased predictability in weather regimes controlled by synoptic forcing, as defined by the convective adjustment time scale.

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