scholarly journals A New Bulk Microphysical Scheme That Includes Riming Intensity and Temperature-Dependent Ice Characteristics

2011 ◽  
Vol 139 (3) ◽  
pp. 1013-1035 ◽  
Author(s):  
Yanluan Lin ◽  
Brian A. Colle
Keyword(s):  
Wrf Model ◽  
Computationally Efficient ◽  
Fall Velocity ◽  
Surface Precipitation ◽  
Ice Particles ◽  
Microphysical Processes ◽  
Empirical Coefficients ◽  
Oregon Cascades ◽  
Microphysical Parameterization ◽  
Ice Water

Abstract A new bulk microphysical parameterization (BMP) scheme is presented that includes a diagnosed riming intensity and its impact on ice characteristics. As a result, the new scheme represents a continuous spectrum from pristine ice particles to heavily rimed particles and graupel using one prognostic variable [precipitating ice (PI)] rather than two separate variables (snow and graupel). In contrast to most existing parameterization schemes that use fixed empirical relationships to describe ice particles, general formulations are proposed to consider the influences of riming intensity and temperature on the projected area, mass, and fall velocity of PI particles. The proposed formulations are able to cover the variations of empirical coefficients found in previous observational studies. The new scheme also reduces the number of parameterized microphysical processes by ∼50% as compared to conventional six-category BMPs and thus it is more computationally efficient. The new scheme (called SBU-YLIN) has been implemented in the Weather Research and Forecasting (WRF) model and compared with three other schemes for two events during the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) over the central Oregon Cascades. The new scheme produces surface precipitation forecasts comparable to more complicated BMPs. The new scheme reduces the snow amounts aloft as compared to other WRF schemes and compares better with observations, especially for an event with moderate riming aloft. Sensitivity tests suggest both reduced snow depositional growth rate and more efficient fallout due to the contribution of riming to the reduction of ice water content aloft in the new scheme, with a larger impact from the partially rimed snow and fallout.

Comparison of Two-Moment Bulk Microphysics Schemes in Idealized Supercell Thunderstorm Simulations

2011 ◽  
Vol 139 (4) ◽  
pp. 1103-1130 ◽  
Author(s):  
Hugh Morrison ◽  
Jason Milbrandt
Keyword(s):  
Three Dimensional ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Cold Pool ◽  
Fall Velocity ◽  
Surface Precipitation ◽  
Single Category ◽  
Supercell Thunderstorm ◽  
Drop Size Distributions ◽  
Reduced Surface

Idealized three-dimensional supercell simulations were performed using the two-moment bulk microphysics schemes of Morrison and Milbrandt–Yau in the Weather Research and Forecasting (WRF) model. Despite general similarities in these schemes, the simulations were found to produce distinct differences in storm structure, precipitation, and cold pool strength. In particular, the Morrison scheme produced much higher surface precipitation rates and a stronger cold pool, especially in the early stages of storm development. A series of sensitivity experiments was conducted to identify the primary differences between the two schemes that resulted in the large discrepancies in the simulations. Different approaches in treating graupel and hail were found to be responsible for many of the key differences between the baseline simulations. The inclusion of hail in the baseline simulation using the Milbrant–Yau scheme with two rimed-ice categories (graupel and hail) had little impact, and therefore resulted in a much different storm than the baseline run with the single-category (hail) Morrison scheme. With graupel as the choice of the single rimed-ice category, the simulated storms had considerably more frozen condensate in the anvil region, a weaker cold pool, and reduced surface precipitation compared to the runs with only hail, whose higher terminal fall velocity inhibited lofting. The cold pool strength was also found to be sensitive to the parameterization of raindrop breakup, particularly for the Morrison scheme, because of the effects on the drop size distributions and the corresponding evaporative cooling rates. The use of a more aggressive implicit treatment of drop breakup in the baseline Morrison scheme, by limiting the mean–mass raindrop diameter to a maximum of 0.9 mm, opposed the tendency of this scheme to otherwise produce large mean drop sizes and a weaker cold pool compared to the hail-only run using the Milbrandt–Yau scheme.

Evaluation and Comparison of Microphysical Algorithms in ARW-WRF Model Simulations of Atmospheric River Events Affecting the California Coast

2009 ◽  
Vol 10 (4) ◽  
pp. 847-870 ◽  
Author(s):  
Isidora Jankov ◽  
Jian-Wen Bao ◽  
Paul J. Neiman ◽  
Paul J. Schultz ◽  
Huiling Yuan ◽  
...  
Keyword(s):  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Test Bed ◽  
Cool Season ◽  
Model Simulations ◽  
Surface Precipitation ◽  
Low Level ◽  
Atmospheric River ◽  
Microphysical Parameterization ◽  
Precipitation Events

Abstract Numerical prediction of precipitation associated with five cool-season atmospheric river events in northern California was analyzed and compared to observations. The model simulations were performed by using the Advanced Research Weather Research and Forecasting Model (ARW-WRF) with four different microphysical parameterizations. This was done as a part of the 2005–06 field phase of the Hydrometeorological Test Bed project, for which special profilers, soundings, and surface observations were implemented. Using these unique datasets, the meteorology of atmospheric river events was described in terms of dynamical processes and the microphysical structure of the cloud systems that produced most of the surface precipitation. Events were categorized as “bright band” (BB) or “nonbright band” (NBB), the differences being the presence of significant amounts of ice aloft (or lack thereof) and a signature of higher reflectivity collocated with the melting layer produced by frozen precipitating particles descending through the 0°C isotherm. The model was reasonably successful at predicting the timing of surface fronts, the development and evolution of low-level jets associated with latent heating processes and terrain interaction, and wind flow signatures consistent with deep-layer thermal advection. However, the model showed the tendency to overestimate the duration and intensity of the impinging low-level winds. In general, all model configurations overestimated precipitation, especially in the case of BB events. Nonetheless, large differences in precipitation distribution and cloud structure among model runs using various microphysical parameterization schemes were noted.

scholarly journals Evaluation of the COSMO model (v5.1) in polarimetric radar space – Impact of uncertainties in model microphysics, retrievals, and forward operator

2021 ◽  
Author(s):  
Prabhakar Shrestha ◽  
Jana Mendrok ◽  
Velibor Pejcic ◽  
Silke Trömel ◽  
Ulrich Blahak ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Model Space ◽  
Polarimetric Radar ◽  
Surface Precipitation ◽  
The Difference ◽  
Microphysical Processes ◽  
Nwp Model ◽  
Two Parameters ◽  
Ice Water ◽  
Forward Operator

Abstract. Sensitivity experiments with a numerical weather prediction (NWP) model and polarimetric radar forward operator (FO) are conducted for a long-duration stratiform event over northwestern Germany, to evaluate uncertainties in the partitioning of the ice water content and assumptions of hydrometeor scattering properties in the NWP model and FO, respectively. Polarimetric observations from X-band radar and retrievals of hydrometeor classifications are used for comparison with the multiple experiments in radar and model space. Modifying two parameters (Dice and Tgr) responsible for the production of snow and graupel, respectively, was found to improve the synthetic polarimetric moments and simulated hydrometeor population, while keeping the difference in surface precipitation statistically insignificant at model resolvable grid scales. However, the model still exhibited a low bias in simulated polarimetric moments at lower levels above the melting layer (−3 to −13 °C) where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g., fragmentation due to ice-ice collisions), and use of more reliable snow scattering models to draw valid conclusions.

Impact of Moisture Flux and Freezing Level on Simulated Orographic Precipitation Errors over the Pacific Northwest

2013 ◽  
Vol 14 (1) ◽  
pp. 140-152 ◽  
Author(s):  
Yanluan Lin ◽  
Brian A. Colle ◽  
Sandra E. Yuter
Keyword(s):  
Pacific Northwest ◽  
Mesoscale Model ◽  
Moisture Flux ◽  
Orographic Precipitation ◽  
Surface Precipitation ◽  
Freezing Level ◽  
The Pacific ◽  
Using Data ◽  
Oregon Cascades ◽  
Ice Water

Abstract Two cool seasons (November–March) of daily simulations using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) over the Pacific Northwest are used to investigate orographic precipitation bias. Model simulations are compared with data from a radiosonde site at Salem, Oregon, just upstream (west) of the Oregon Cascades; precipitation gauges over a portion of the Pacific Northwest; and a National Weather Service Weather Surveillance Radar-1988 Doppler (WSR-88D) in Portland, Oregon. The 77 storms analyzed are partitioned into warm/cold storms based on the freezing level above/below the Oregon Cascades crest (~1600 m MSL). Although the seasonal precipitation is well simulated, the model has a tendency to overpredict surface precipitation for cold storms. The correlation between the upstream relative humidity–weighted integrated moisture transport and precipitation for warm storms (r2 = 0.81) is higher than that for cold storms (r2 = 0.54). Comparisons of model ice water content (IWC) and derived reflectivity with radar-retrieved IWC and observed reflectivity for the 38 well-simulated storms show reasonably good agreement for warm storms but an overprediction of IWC and reflectivity aloft for cold storms. One plausible reason for the persistent overprediction of IWC in cold storms might be related to the positive bias in snow depositional growth formulation in the model bulk microphysics parameterization. A favorable overlap of the maximum snow depositional growth region with the mountain wave ascent region in cold storms magnifies the bias and likely contributes to the precipitation overprediction. This study also highlights the benefit of using data aloft from an operational radar to complement surface precipitation gauges for model precipitation evaluation over mountainous terrain.

scholarly journals Aerosol effects on electrification and lightning discharges in a multicell thunderstorm simulated by the WRF-ELEC model

2021 ◽  
Vol 21 (18) ◽  
pp. 14141-14158
Author(s):  
Mengyu Sun ◽  
Dongxia Liu ◽  
Xiushu Qie ◽  
Edward R. Mansell ◽  
Yoav Yair ◽  
...  
Keyword(s):  
Latent Heat ◽  
Phase Particle ◽  
Wrf Model ◽  
Lightning Activity ◽  
Cloud Droplets ◽  
Beijing Area ◽  
Ice Particles ◽  
Lightning Discharges ◽  
Upper Level ◽  
Microphysical Processes

Abstract. To investigate the effects of aerosols on lightning activity, the Weather Research and Forecasting (WRF) Model with a two-moment bulk microphysical scheme and bulk lightning model was employed to simulate a multicell thunderstorm that occurred in the metropolitan Beijing area. The results suggest that under polluted conditions lightning activity is significantly enhanced during the developing and mature stages. Electrification and lightning discharges within the thunderstorm show characteristics distinguished by different aerosol conditions through microphysical processes. Elevated aerosol loading increases the cloud droplets numbers, the latent heat release, updraft and ice-phase particle number concentrations. More charges in the upper level are carried by ice particles and enhance the electrification process. A larger mean-mass radius of graupel particles further increases non-inductive charging due to more effective collisions. In the continental case where aerosol concentrations are low, less latent heat is released in the upper parts and, as a consequence, the updraft speed is weaker, leading to smaller concentrations of ice particles, lower charging rates and fewer lightning discharges.

Variational Assimilation of Cloud Liquid/Ice Water Path and Its Impact on NWP

2015 ◽  
Vol 54 (8) ◽  
pp. 1809-1825 ◽  
Author(s):  
Yaodeng Chen ◽  
Hongli Wang ◽  
Jinzhong Min ◽  
Xiang-Yu Huang ◽  
Patrick Minnis ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Liquid Water ◽  
Weather Prediction ◽  
Wrf Model ◽  
Liquid Water Path ◽  
Cloud Liquid Water ◽  
Water Path ◽  
Ice Water Path ◽  
Ice Water ◽  
The Impact

AbstractAnalysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this research, the variational data assimilation (DA) system for the Weather Research and Forecasting (WRF) Model (WRFDA) is further developed to assimilate satellite cloud products that will produce the cloud liquid water and ice water analysis. Observation operators for the cloud liquid water path and cloud ice water path are developed and incorporated into the WRFDA system. The updated system is tested by assimilating cloud liquid water path and cloud ice water path observations from Global Geostationary Gridded Cloud Products at NASA. To assess the impact of cloud liquid/ice water path data assimilation on short-term regional numerical weather prediction (NWP), 3-hourly cycling data assimilation and forecast experiments with and without the use of the cloud liquid/ice water paths are conducted. It is shown that assimilating cloud liquid/ice water paths increases the accuracy of temperature, humidity, and wind analyses at model levels between 300 and 150 hPa after 5 cycles (15 h). It is also shown that assimilating cloud liquid/ice water paths significantly reduces forecast errors in temperature and wind at model levels between 300 and 150 hPa. The precipitation forecast skills are improved as well. One reason that leads to the improved analysis and forecast is that the 3-hourly rapid update cycle carries over the impact of cloud information from the previous cycles spun up by the WRF Model.

Refinements to Ice Particle Mass Dimensional and Terminal Velocity Relationships for Ice Clouds. Part II: Evaluation and Parameterizations of Ensemble Ice Particle Sedimentation Velocities

2007 ◽  
Vol 64 (4) ◽  
pp. 1068-1088 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Gerd-Jan van Zadelhoff ◽  
David P. Donovan ◽  
Frederic Fabry ◽  
Robin J. Hogan ◽  
...  
Keyword(s):  
Climate Models ◽  
Doppler Radar ◽  
Terminal Velocity ◽  
Fall Velocity ◽  
Particle Sedimentation ◽  
Cloud Properties ◽  
Wide Range ◽  
Single Moment ◽  
Ice Water Content ◽  
Ice Water

Abstract This two-part study addresses the development of reliable estimates of the mass and fall speed of single ice particles and ensembles. Part I of the study reports temperature-dependent coefficients for the mass-dimensional relationship, m = aDb, where D is particle maximum dimension. The fall velocity relationship, Vt = ADB, is developed from observations in synoptic and low-latitude, convectively generated, ice cloud layers, sampled over a wide range of temperatures using an assumed range for the exponent b. Values for a, A, and B were found that were consistent with the measured particle size distributions (PSD) and the ice water content (IWC). To refine the estimates of coefficients a and b to fit both lower and higher moments of the PSD and the associated values for A and B, Part II uses the PSD from Part I plus coincident, vertically pointing Doppler radar returns. The observations and derived coefficients are used to evaluate earlier, single-moment, bulk ice microphysical parameterization schemes as well as to develop improved, statistically based, microphysical relationships. They may be used in cloud and climate models, and to retrieve cloud properties from ground-based Doppler radar and spaceborne, conventional radar returns.

scholarly journals A Microphysical Bulk Formulation Based on Scaling Normalization of the Particle Size Distribution. Part I: Description

2005 ◽  
Vol 62 (12) ◽  
pp. 4206-4221 ◽  
Author(s):  
Wanda Szyrmer ◽  
Stéphane Laroche ◽  
Isztar Zawadzki
Keyword(s):  
Particle Size ◽  
High Resolution ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Numerical Models ◽  
Radar Data ◽  
Retrieval Algorithm ◽  
Microphysical Processes ◽  
The Moment ◽  
Microphysical Parameterization

Abstract The authors address the problem of optimization of the microphysical information extracted from a simulation system composed of high-resolution numerical models and multiparameter radar data or other available measurements. As a tool in the exploration of this question, a bulk microphysical scheme based on the general approach of scaling normalization of particle size distribution (PSD) is proposed. This approach does not rely on a particular functional form imposed on the PSD and naturally leads to power-law relationships between the PSD moments providing an accurate and compact PSD representation. To take into account the possible evolution of the shape/curvature of the distribution, ignored within standard one- and two-moment microphysical schemes, a new three-moment scheme based on the two-moment scaling normalization is proposed. The methodology of the moment retrieval included in the three-moment scheme can also be useful as a retrieval algorithm combining different remote sensing observations. The developed bulk microphysical scheme presents a unified formulation for microphysical parameterization using one, two, or three independent moments, suitable in the context of data assimilation. The effectiveness of the scheme with different combinations of independent moments is evaluated by comparison with a very high resolution spectral model within a 1D framework on representative microphysical processes: rain sedimentation and evaporation.

Pathways to the Production of Precipitating Hydrometeors and Tropical Cyclone Development

2016 ◽  
Vol 144 (6) ◽  
pp. 2395-2420 ◽  
Author(s):  
J.-W. Bao ◽  
S. A. Michelson ◽  
E. D. Grell
Keyword(s):  
Tropical Cyclone ◽  
Wrf Model ◽  
Cloud Microphysics ◽  
Weather Research And Forecasting ◽  
Rapid Intensification ◽  
Latent Heating ◽  
Vertical Distributions ◽  
Double Moment ◽  
Microphysical Processes ◽  
Definition Of

Abstract Pathways to the production of precipitation in two cloud microphysics schemes available in the Weather Research and Forecasting (WRF) Model are investigated in a scenario of tropical cyclone intensification. Comparisons of the results from the WRF Model simulations indicate that the variation in the simulated initial rapid intensification of an idealized tropical cyclone is due to the differences between the two cloud microphysics schemes in their representations of pathways to the formation and growth of precipitating hydrometeors. Diagnoses of the source and sink terms of the hydrometeor budget equations indicate that the major differences in the production of hydrometeors between the schemes are in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes, such as accretion growth and sedimentation. These differences lead to different horizontally averaged vertical profiles of net latent heating rate associated with significantly different horizontally averaged vertical distributions and production rates of hydrometeors in the simulated clouds. Results from this study also highlight the possibility that the advantage of double-moment formulations can be overshadowed by the uncertainties in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes.

Forecast of low clouds over a snow surface in the Arctic using WRF model

2021 ◽  
Author(s):  
M. Hagman ◽  
G. Svensson ◽  
W.M. Angevine
Keyword(s):  
Forecast Error ◽  
Wrf Model ◽  
Armed Forces ◽  
The Arctic ◽  
Bulk Liquid ◽  
Wave Radiation ◽  
Initial Profile ◽  
Near Surface ◽  
Low Clouds ◽  
Ice Water

AbstractThe Swedish Armed Forces configuration of the Weather Research and Forecasting Model (WRF) has problems in forecasting low clouds in stably stratified conditions when the ground is covered by snow. Reforecasts for January and February 2018, together with observations from Sodankylä in northern Finland, are analyzed to find the cause. The investigation is done iteratively between the Single Column Model (SCM), applied at Sodankylä, and the full 3D version. Our experiments show that the forecast error arises due to inadequate initialization of Stratocumulus (Sc) clouds in WRF using the ECMWF global model, Integrated Forecast System (IFS). By including bulk liquid water and bulk ice water content, from IFS in the initial profile, the downwelling long wave radiation increases and prevents the near surface temperature from dropping abnormally. This, in turn, prevents artificial clouds from forming at the first model level. When no clouds are present in the IFS initial profile, the Sc clouds can be initialized using information from the observed vertical profiles. Generally, initialization of Sc clouds in WRF improves the forecast substantially.

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