Evaluation of WRF Cloud Microphysics Schemes Using Radar Observations

Abstract The Korea Meteorological Administration (KMA) implemented a 10-yr project to develop its own global model (GM) by 2020. To reflect the complex topography and unique weather characteristics of the Korean Peninsula, a high-resolution model with accurate physics and input data is required. The WRF single-moment 6-class microphysics scheme (WSM6) and WRF double-moment 6-class microphysics scheme (WDM6) that will be implemented in the Korea GM (KGM) are evaluated. Comparisons of the contoured frequency by altitude diagram (CFAD), time–height cross sections, and vertical profiles of hydrometeors are utilized to assess the two schemes in simulating summer monsoon and convective precipitation cases over the Korean Peninsula during 2011. The results show that WSM6 and WDM6 overestimate the height of the melting level and bright band as compared to radar observations. However, the accuracy of WDM6 is in better agreement with radar observations. This is attributed to the difference in the sedimentation process simulated by the additional second-moment total number concentrations of liquid-phase particles in WDM6. WDM6 creates larger raindrops and higher relative humidity beneath the melting layer, allowing the scheme to simulate a more realistic reflectivity profile than WSM6 for the summer monsoon case. However, for the convective case, both schemes underestimate the precipitation and there is resolution dependence in the WRF Model’s ability to simulate convective precipitation.

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Comparison of Cloud Microphysics Schemes in a Warn-on-Forecast System Using Synthetic Satellite Objects

Weather and Forecasting ◽

10.1175/waf-d-18-0112.1 ◽

2018 ◽

Vol 33 (6) ◽

pp. 1681-1708 ◽

Cited By ~ 6

Author(s):

Thomas A. Jones ◽

Patrick Skinner ◽

Kent Knopfmeier ◽

Edward Mansell ◽

Patrick Minnis ◽

...

Keyword(s):

Prediction Models ◽

Negative Impact ◽

Cloud Condensation Nuclei ◽

Weather Prediction ◽

Weather Conditions ◽

Variable Density ◽

Cloud Microphysics ◽

Convective Precipitation ◽

Microphysics Scheme ◽

Double Moment

AbstractForecasts of high-impact weather conditions using convection-allowing numerical weather prediction models have been found to be highly sensitive to the selection of cloud microphysics scheme used within the system. The Warn-on-Forecast (WoF) project has developed a rapid-cycling, convection-allowing, data assimilation and forecasting system known as the NSSL Experimental WoF System for ensembles (NEWS-e), which is designed to utilize advanced cloud microphysics schemes. NEWS-e currently (2017–18) uses the double-moment NSSL variable density scheme (NVD), which has been shown to generate realistic representations of convective precipitation within the system. However, very little verification on nonprecipitating cloud features has been performed with this system. During the 2017 Hazardous Weather Testbed (HWT) experiment, an overestimation of the areal coverage of convectively generated cirrus clouds was observed. Changing the cloud microphysics scheme to Thompson generated more accurate cloud fields. This research undertook the task of improving the cloud analysis generated by NVD while maintaining its skill for other variables such as reflectivity. Adjustments to cloud condensation nuclei (CCN), fall speed, and collection efficiencies were made and tested over a set of six severe weather cases occurring during May 2017. This research uses an object-based verification approach in which objects of cold infrared brightness temperatures, high cloud-top pressures, and cloud water path are generated from model output and compared against GOES-13 observations. Results show that the modified NVD scheme generated much more skillful forecasts of cloud objects than the original formulation without having a negative impact on the skill of simulated composite reflectivity forecasts.

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The Ensemble Kalman Filter Analyses and Forecasts of the 8 May 2003 Oklahoma City Tornadic Supercell Storm Using Single- and Double-Moment Microphysics Schemes

Monthly Weather Review ◽

10.1175/mwr-d-12-00237.1 ◽

2013 ◽

Vol 141 (10) ◽

pp. 3388-3412 ◽

Cited By ~ 87

Author(s):

Nusrat Yussouf ◽

Edward R. Mansell ◽

Louis J. Wicker ◽

Dustan M. Wheatley ◽

David J. Stensrud

Keyword(s):

Kalman Filter ◽

Data Assimilation ◽

Short Range ◽

Oklahoma City ◽

Radar Observation ◽

Microphysics Scheme ◽

Radar Observations ◽

Supercell Storm ◽

Single Moment ◽

Double Moment

Abstract A combined mesoscale and storm-scale ensemble data-assimilation and prediction system is developed using the Advanced Research core of the Weather Research and Forecasting Model (WRF-ARW) and the ensemble adjustment Kalman filter (EAKF) from the Data Assimilation Research Testbed (DART) software package for a short-range ensemble forecast of an 8 May 2003 Oklahoma City, Oklahoma, tornadic supercell storm. Traditional atmospheric observations are assimilated into a 45-member mesoscale ensemble over a continental U.S. domain starting 3 days prior to the event. A one-way-nested 45-member storm-scale ensemble is initialized centered on the tornadic event at 2100 UTC on the day of the event. Three radar observation assimilation and forecast experiments are conducted at storm scale using a single-moment, a semi-double-moment, and a full double-moment bulk microphysics scheme. Results indicate that the EAKF initializes the supercell storm into the model with good accuracy after a 1-h-long radar observation assimilation window. The ensemble forecasts capture the movement of the main supercell storm that matches reasonably well with radar observations. The reflectivity structure of the supercell storm using a double-moment microphysics scheme appears to compare better to the observations than that using a single-moment scheme. In addition, the ensemble system predicts the probability of a strong low-level vorticity track of the tornadic supercell that correlates well with the observed rotation track. The rapid 3-min update cycle of the storm-scale ensemble from the radar observations seems to enhance the skill of the ensemble and the confidence of an imminent tornado threat. The encouraging results obtained from this study show promise for a short-range probabilistic storm-scale forecast of supercell thunderstorms, which is the main goal of NOAA's Warn-on-Forecast initiative.

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Ensemble Probabilistic Prediction of a Mesoscale Convective System and Associated Polarimetric Radar Variables Using Single-Moment and Double-Moment Microphysics Schemes and EnKF Radar Data Assimilation

Monthly Weather Review ◽

10.1175/mwr-d-16-0162.1 ◽

2017 ◽

Vol 145 (6) ◽

pp. 2257-2279 ◽

Cited By ~ 12

Author(s):

Bryan J. Putnam ◽

Ming Xue ◽

Youngsun Jung ◽

Nathan A. Snook ◽

Guifu Zhang

Keyword(s):

Mesoscale Convective System ◽

Radar Data ◽

Convective Precipitation ◽

Convective System ◽

Ensemble Forecasts ◽

Verification Methods ◽

Probabilistic Forecasts ◽

Mesoscale Convective ◽

Single Moment ◽

Double Moment

Abstract Ensemble-based probabilistic forecasts are performed for a mesoscale convective system (MCS) that occurred over Oklahoma on 8–9 May 2007, initialized from ensemble Kalman filter analyses using multinetwork radar data and different microphysics schemes. Two experiments are conducted, using either a single-moment or double-moment microphysics scheme during the 1-h-long assimilation period and in subsequent 3-h ensemble forecasts. Qualitative and quantitative verifications are performed on the ensemble forecasts, including probabilistic skill scores. The predicted dual-polarization (dual-pol) radar variables and their probabilistic forecasts are also evaluated against available dual-pol radar observations, and discussed in relation to predicted microphysical states and structures. Evaluation of predicted reflectivity (Z) fields shows that the double-moment ensemble predicts the precipitation coverage of the leading convective line and stratiform precipitation regions of the MCS with higher probabilities throughout the forecast period compared to the single-moment ensemble. In terms of the simulated differential reflectivity (ZDR) and specific differential phase (KDP) fields, the double-moment ensemble compares more realistically to the observations and better distinguishes the stratiform and convective precipitation regions. The ZDR from individual ensemble members indicates better raindrop size sorting along the leading convective line in the double-moment ensemble. Various commonly used ensemble forecast verification methods are examined for the prediction of dual-pol variables. The results demonstrate the challenges associated with verifying predicted dual-pol fields that can vary significantly in value over small distances. Several microphysics biases are noted with the help of simulated dual-pol variables, such as substantial overprediction of KDP values in the single-moment ensemble.

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Development of a Single-Moment Cloud Microphysics Scheme with Prognostic Hail for the Weather Research and Forecasting (WRF) Model

Asia-Pacific Journal of Atmospheric Sciences ◽

10.1007/s13143-018-0066-3 ◽

2018 ◽

Vol 55 (2) ◽

pp. 233-245 ◽

Cited By ~ 6

Author(s):

Soo Ya Bae ◽

Song-You Hong ◽

Wei-Kuo Tao

Keyword(s):

Wrf Model ◽

Cloud Microphysics ◽

Weather Research And Forecasting ◽

Microphysics Scheme ◽

Single Moment ◽

Weather Research

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Using Varied Microphysics to Account for Uncertainty in Warm-Season QPF in a Convection-Allowing Ensemble

Monthly Weather Review ◽

10.1175/mwr-d-13-00297.1 ◽

2014 ◽

Vol 142 (6) ◽

pp. 2198-2219 ◽

Cited By ~ 28

Author(s):

Jeffrey D. Duda ◽

Xuguang Wang ◽

Fanyou Kong ◽

Ming Xue

Keyword(s):

Positive Impact ◽

Warm Season ◽

Weather Research And Forecasting ◽

Lead Times ◽

Ensemble Forecasts ◽

Microphysics Scheme ◽

Relative Operating Characteristic ◽

Single Moment ◽

Double Moment ◽

Range Of Values

Abstract Two approaches for accounting for errors in quantitative precipitation forecasts (QPFs) due to uncertainty in the microphysics (MP) parameterization in a convection-allowing ensemble are examined. They include mixed MP (MMP) composed mostly of double-moment schemes and perturbing parameters within the Weather Research and Forecasting single-moment 6-class microphysics scheme (WSM6) MP scheme (PPMP). Thirty-five cases of real-time storm-scale ensemble forecasts produced by the Center for Analysis and Prediction of Storms during the NOAA Hazardous Weather Testbed 2011 Spring Experiment were examined. The MMP ensemble had better fractions Brier scores (FBSs) for most lead times and thresholds, but the PPMP ensemble had better relative operating characteristic (ROC) scores for higher precipitation thresholds. The pooled ensemble formed by randomly drawing five members from the MMP and PPMP ensembles was no more skillful than the more accurate of the MMP and PPMP ensembles. Significant positive impact was found when the two were combined to form a larger ensemble. The QPF and the systematic behaviors of derived microphysical variables were also examined. The skill of the QPF among different members depended on the thresholds, verification metrics, and forecast lead times. The profiles of microphysics variables from the double-moment schemes contained more variation in the vertical than those from the single-moment members. Among the double-moment schemes, WDM6 produced the smallest raindrops and very large number concentrations. Among the PPMP members, the behaviors were found to be consistent with the prescribed intercept parameters. The perturbed intercept parameters used in the PPMP ensemble fell within the range of values retrieved from the double-moment schemes.

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The microphysics of clouds over the Antarctic Peninsula – Part 2: modelling aspects within Polar WRF

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-10195-2017 ◽

2017 ◽

Vol 17 (17) ◽

pp. 10195-10221 ◽

Cited By ~ 17

Author(s):

Constantino Listowski ◽

Tom Lachlan-Cope

Keyword(s):

Liquid Phase ◽

Antarctic Peninsula ◽

Supercooled Liquid ◽

Cloud Microphysics ◽

Horizontal Resolution ◽

Surface Energy Budget ◽

Ice Shelf ◽

Single Moment ◽

Double Moment ◽

The Antarctic

Abstract. The first intercomparisons of cloud microphysics schemes implemented in the Weather Research and Forecasting (WRF) mesoscale atmospheric model (version 3.5.1) are performed on the Antarctic Peninsula using the polar version of WRF (Polar WRF) at 5 km resolution, along with comparisons to the British Antarctic Survey's aircraft measurements (presented in part 1 of this work; Lachlan-Cope et al., 2016). This study follows previous works suggesting the misrepresentation of the cloud thermodynamic phase in order to explain large radiative biases derived at the surface in Polar WRF continent-wide (at 15 km or coarser horizontal resolution) and in the Polar WRF-based operational forecast model Antarctic Mesoscale Prediction System (AMPS) over the Larsen C Ice Shelf at 5 km horizontal resolution. Five cloud microphysics schemes are investigated: the WRF single-moment five-class scheme (WSM5), the WRF double-moment six-class scheme (WDM6), the Morrison double-moment scheme, the Thompson scheme, and the Milbrandt–Yau double-moment seven-class scheme. WSM5 (used in AMPS) and WDM6 (an upgrade version of WSM5) lead to the largest biases in observed supercooled liquid phase and surface radiative biases. The schemes simulating clouds in closest agreement to the observations are the Morrison, Thompson, and Milbrandt schemes for their better average prediction of occurrences of clouds and cloud phase. Interestingly, those three schemes are also the ones allowing for significant reduction of the longwave surface radiative bias over the Larsen C Ice Shelf (eastern side of the peninsula). This is important for surface energy budget consideration with Polar WRF since the cloud radiative effect is more pronounced in the infrared over icy surfaces. Overall, the Morrison scheme compares better to the cloud observation and radiation measurements. The fact that WSM5 and WDM6 are single-moment parameterizations for the ice crystals is responsible for their lesser ability to model the supercooled liquid clouds compared to the other schemes. However, our investigation shows that all the schemes fail at simulating the supercooled liquid mass at some temperatures (altitudes) where observations show evidence of its persistence. An ice nuclei parameterization relying on both temperature and aerosol content like DeMott et al. (2010) (not currently used in WRF cloud schemes) is in best agreement with the observations, at temperatures and aerosol concentration characteristic of the Antarctic Peninsula where the primary ice production occurs (part 1), compared to parameterization only relying on the atmospheric temperature (used by the WRF cloud schemes). Overall, a realistic double-moment ice microphysics implementation is needed for the correct representation of the supercooled liquid phase in Antarctic clouds. Moreover, a more realistic ice-nucleating particle alone is not enough to improve the cloud modelling, and water vapour and temperature biases also need to be further investigated and reduced.

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Improvement in Global Cloud-System-Resolving Simulations by Using a Double-Moment Bulk Cloud Microphysics Scheme

Journal of Climate ◽

10.1175/jcli-d-14-00241.1 ◽

2015 ◽

Vol 28 (6) ◽

pp. 2405-2419 ◽

Cited By ~ 24

Author(s):

Tatsuya Seiki ◽

Chihiro Kodama ◽

Akira T. Noda ◽

Masaki Satoh

Keyword(s):

Radiative Forcing ◽

Atmospheric Temperature ◽

Cloud Microphysics ◽

Radiative Heating ◽

Cloud System ◽

Microphysics Scheme ◽

Climate Simulations ◽

Double Moment ◽

Cloud Ice ◽

The Impact

Abstract This study examines the impact of an alteration of a cloud microphysics scheme on the representation of longwave cloud radiative forcing (LWCRF) and its impact on the atmosphere in global cloud-system-resolving simulations. A new double-moment bulk cloud microphysics scheme is used, and the simulated results are compared with those of a previous study. It is demonstrated that improvements within the new cloud microphysics scheme have the potential to substantially improve climate simulations. The new cloud microphysics scheme represents a realistic spatial distribution of the cloud fraction and LWCRF, particularly near the tropopause. The improvement in the cirrus cloud-top height by the new cloud microphysics scheme substantially reduces the warm bias in atmospheric temperature from the previous simulation via LWCRF by the cirrus clouds. The conversion rate of cloud ice to snow and gravitational sedimentation of cloud ice are the most important parameters for determining the strength of the radiative heating near the tropopause and its impact on atmospheric temperature.

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libcloudph++ 0.2: single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in C++

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-8275-2014 ◽

2014 ◽

Vol 7 (6) ◽

pp. 8275-8360

Author(s):

S. Arabas ◽

A. Jaruga ◽

H. Pawlowska ◽

W. W. Grabowski

Keyword(s):

Open Source Software ◽

Graphics Processing Units ◽

Numerical Models ◽

Cloud Microphysics ◽

Warm Rain ◽

Large Eddy ◽

Single Moment ◽

Double Moment ◽

Graphics Processing ◽

Programming Interface

Abstract. This paper introduces a library of algorithms for representing cloud microphysics in numerical models. The library is written in C++, hence the name libcloudph++. In the current release, the library covers three warm-rain schemes: the single- and double-moment bulk schemes, and the particle-based scheme with Monte-Carlo coalescence. The three schemes are intended for modelling frameworks of different dimensionality and complexity ranging from parcel models to multi-dimensional cloud-resolving (e.g. large-eddy) simulations. A two-dimensional prescribed-flow framework is used in example simulations presented in the paper with the aim of highlighting the library features. The libcloudph++ and all its mandatory dependencies are free and open-source software. The Boost.units library is used for zero-overhead dimensional analysis of the code at compile time. The particle-based scheme is implemented using the Thrust library that allows to leverage the power of graphics processing units (GPU), retaining the possibility to compile the unchanged code for execution on single or multiple standard processors (CPUs). The paper includes complete description of the programming interface (API) of the library and a performance analysis including comparison of GPU and CPU setups.

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A Comparative Study of Bin and Bulk Cloud Microphysics Schemes in Simulating a Heavy Precipitation Case

Atmosphere ◽

10.3390/atmos9120475 ◽

2018 ◽

Vol 9 (12) ◽

pp. 475 ◽

Cited By ~ 2

Author(s):

Hyunho Lee ◽

Jong-Jin Baik

Keyword(s):

Heat Release ◽

Latent Heat ◽

Wrf Model ◽

Heavy Precipitation ◽

Cloud Microphysics ◽

Latent Heat Release ◽

Microphysics Scheme ◽

Surface Precipitation ◽

Double Moment ◽

Bin Microphysics

Comparisons between bin and bulk cloud microphysics schemes are conducted by simulating a heavy precipitation case using a bin microphysics scheme and four double-moment bulk microphysics schemes in the Weather Research and Forecasting (WRF) model. For this, we implemented an updated bin microphysics scheme in the WRF model. All of the microphysics schemes underestimate observed strong precipitation, but the bin microphysics scheme yields the result that is closest to observations. The differences among the schemes are more pronounced in terms of hydrometeor number concentration than in terms of hydrometeor mixing ratio. In this case, the bin scheme exhibits remarkably more latent heat release by deposition and riming than the bulk schemes. This causes stronger updrafts and more upward transport of water vapor, which leads to more deposition, and again, increases the latent heat release. An additional simulation using the bin scheme but excluding the riming of cloud droplets on ice crystals, which is not or poorly treated in the examined bulk schemes, shows that surface precipitation is slightly weakened and moved farther downwind compared to that of the control simulation. This implies that the more appropriate representation of microphysical processes in the bin microphysics scheme contributes to the more accurate prediction of precipitation in this case.

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