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.

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.

scholarly journals Evaluation of Two Cloud-Resolving Models Using Bin or Bulk Microphysics Representation for the HyMeX-IOP7a Heavy Precipitation Event

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1177
Author(s):  
Diana Arteaga ◽  
Céline Planche ◽  
Christina Kagkara ◽  
Wolfram Wobrock ◽  
Sandra Banson ◽  
...  
Keyword(s):  
Hydrological Cycle ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Sensitivity Study ◽  
Precipitation Event ◽  
Convective System ◽  
Wind Fields ◽  
Massif Central ◽  
Surface Precipitation ◽  
Low Level

The Mediterranean region is frequently affected in autumn by heavy precipitation that causes flash-floods or landslides leading to important material damage and casualties. Within the framework of the international HyMeX program (HYdrological cycle in Mediterranean EXperiment), this study aims to evaluate the capabilities of two models, WRF (Weather Research and Forecasting) and DESCAM (DEtailed SCAvenging Model), which use two different representations of the microphysics to reproduce the observed atmospheric properties (thermodynamics, wind fields, radar reflectivities and precipitation features) of the HyMeX-IOP7a intense precipitating event (26 September 2012). The DESCAM model, which uses a bin resolved representation of the microphysics, shows results comparable to the observations for the precipitation field at the surface. On the contrary, the simulations made with the WRF model using a bulk representation of the microphysics (either the Thompson scheme or the Morrison scheme), commonly employed in NWP models, reproduce neither the intensity nor the distribution of the observed precipitation—the rain amount is overestimated and the most intense cell is shifted to the East. The different simulation results show that the divergence in the surface precipitation features seems to be due to different mechanisms involved in the onset of the precipitating system: the convective system is triggered by the topography of the Cévennes mountains (i.e., south-eastern part of the Massif Central) in DESCAM and by a low-level flux convergence in WRF. A sensitivity study indicates that the microphysics properties have impacted the thermodynamics and dynamics fields inducing the low-level wind convergence simulated with WRF for this HyMeX event.

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.

scholarly journals Impact of Coupling an Ocean Model to WRF Nor’easter Simulations

2015 ◽  
Vol 143 (12) ◽  
pp. 4997-5016 ◽  
Author(s):  
Stephen D. Nicholls ◽  
Steven G. Decker
Keyword(s):  
Storm Track ◽  
Wrf Model ◽  
Ocean Model ◽  
Weather Research And Forecasting ◽  
Model Coupling ◽  
Sea Level Pressure ◽  
Model Simulations ◽  
Simulated Precipitation ◽  
Ocean Atmosphere ◽  
The Impact

Abstract The impact of ocean–atmosphere coupling and its possible seasonal dependence upon Weather Research and Forecasting (WRF) Model simulations of seven, wintertime cyclone events was investigated. Model simulations were identical aside from the degree of ocean model coupling (static SSTs, 1D mixed layer model, full-physics 3D ocean model). Both 1D and 3D ocean model coupling simulations show that SSTs following the passage of a nor’easter did tend to cool more strongly during the early season (October–December) and were more likely to warm late in the season (February–April). Model simulations produce SST differences of up to 1.14 K, but this change did not lead to significant changes in storm track (<100 km), maximum 10-m winds (<2 m s−1), or minimum sea level pressure (≤5 hPa). Simulated precipitation showed little sensitivity to model coupling, but all simulations did tend to overpredict precipitation extent (bias > 1) and have low-to-moderate threat scores (0.31–0.59). Analysis of the storm environment and the overall simulation failed to reveal any statistically significant differences in model error attributable to ocean–atmosphere coupling. Despite this result, ocean model coupling can reduce dynamical field error at a single level by up to 20%, and this was slightly greater (1%–2%) with 3D ocean model coupling as compared to 1D ocean model coupling. Thus, while 3D ocean model coupling tended to generally produce more realistic simulations, its impact would likely be more profound for longer-term simulations.

scholarly journals Terrain Trapped Airflows and Precipitation Variability during an Atmospheric River Event

2020 ◽  
Vol 21 (2) ◽  
pp. 355-375 ◽  
Author(s):  
Ju-Mee Ryoo ◽  
Sen Chiao ◽  
J. Ryan Spackman ◽  
Laura T. Iraci ◽  
F. Martin Ralph ◽  
...  
Keyword(s):  
Wrf Model ◽  
Wind Fields ◽  
Low Level ◽  
Atmospheric River ◽  
Gap Flow ◽  
Period 2 ◽  
Modeling Systems ◽  
In Situ Observations ◽  
Aircraft Data

AbstractWe examine thermodynamic and kinematic structures of terrain trapped airflows (TTAs) during an atmospheric river (AR) event impacting Northern California 10–11 March 2016 using Alpha Jet Atmospheric eXperiment (AJAX) aircraft data, in situ observations, and Weather and Research Forecasting (WRF) Model simulations. TTAs are identified by locally intensified low-level winds flowing parallel to the coastal ranges and having maxima over the near-coastal waters. Multiple mechanisms can produce TTAs, including terrain blocking and gap flows. The changes in winds can significantly alter the distribution, timing, and intensity of precipitation. We show here how different mechanisms producing TTAs evolve during this event and influence local precipitation variations. Three different periods are identified from the time-varying wind fields. During period 1 (P1), a TTA develops during synoptic-scale onshore flow that backs to southerly flow near the coast. This TTA occurs when the Froude number (Fr) is less than 1, suggesting low-level terrain blocking is the primary mechanism. During period 2 (P2), a Petaluma offshore gap flow develops, with flows turning parallel to the coast offshore and with Fr > 1. Periods P1 and P2 are associated with slightly more coastal than mountain precipitation. In period 3 (P3), the gap flow initiated during P2 merges with a pre-cold-frontal low-level jet (LLJ) and enhanced precipitation shifts to higher mountain regions. Dynamical mixing also becomes more important as the TTA becomes confluent with the approaching LLJ. The different mechanisms producing TTAs and their effects on precipitation pose challenges to observational and modeling systems needed to improve forecasts and early warnings of AR events.

scholarly journals Radar-based characterisation of heavy precipitation in the eastern Mediterranean and its representation in a convection-permitting model

2020 ◽  
Vol 24 (3) ◽  
pp. 1227-1249 ◽  
Author(s):  
Moshe Armon ◽  
Francesco Marra ◽  
Yehouda Enzel ◽  
Dorita Rostkier-Edelstein ◽  
Efrat Morin
Keyword(s):  
High Resolution ◽  
Eastern Mediterranean ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Spatial Location ◽  
Radar Data ◽  
Weather Research And Forecasting ◽  
Model Simulations ◽  
Rain Gauges ◽  
Rainfall Patterns

Abstract. Heavy precipitation events (HPEs) can lead to natural hazards (e.g. floods and debris flows) and contribute to water resources. Spatiotemporal rainfall patterns govern the hydrological, geomorphological, and societal effects of HPEs. Thus, a correct characterisation and prediction of rainfall patterns is crucial for coping with these events. Information from rain gauges is generally limited due to the sparseness of the networks, especially in the presence of sharp climatic gradients. Forecasting HPEs depends on the ability of weather models to generate credible rainfall patterns. This paper characterises rainfall patterns during HPEs based on high-resolution weather radar data and evaluates the performance of a high-resolution, convection-permitting Weather Research and Forecasting (WRF) model in simulating these patterns. We identified 41 HPEs in the eastern Mediterranean from a 24-year radar record using local thresholds based on quantiles for different durations, classified these events into two synoptic systems, and ran model simulations for them. For most durations, HPEs near the coastline were characterised by the highest rain intensities; however, for short durations, the highest rain intensities were found for the inland desert. During the rainy season, the rain field's centre of mass progresses from the sea inland. Rainfall during HPEs is highly localised in both space (less than a 10 km decorrelation distance) and time (less than 5 min). WRF model simulations were accurate in generating the structure and location of the rain fields in 39 out of 41 HPEs. However, they showed a positive bias relative to the radar estimates and exhibited errors in the spatial location of the heaviest precipitation. Our results indicate that convection-permitting model outputs can provide reliable climatological analyses of heavy precipitation patterns; conversely, flood forecasting requires the use of ensemble simulations to overcome the spatial location errors.

The 4–5 December 2001 IMPROVE-2 Event: Observed Microphysics and Comparisons with the Weather Research and Forecasting Model

2009 ◽  
Vol 137 (4) ◽  
pp. 1372-1392 ◽  
Author(s):  
Yanluan Lin ◽  
Brian A. Colle
Keyword(s):  
Water Conservation ◽  
Wrf Model ◽  
Spherical Particles ◽  
Weather Research And Forecasting ◽  
Coast Range ◽  
Surface Precipitation ◽  
Orographic Rainfall ◽  
Convective Cells ◽  
Weather Research

Abstract This paper highlights the observed and simulated microphysical evolution of a moderate orographic rainfall event over the central Oregon Cascade Range during 4–5 December 2001 of the Second Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2). Airborne in situ measurements illustrate the spatial variations in ice crystal distributions and amounts over the windward Cascades and within some convective cells. The in situ microphysical observations, ground radars, and surface observations are compared with four bulk microphysical parameterizations (BMPs) within the Weather Research and Forecasting (WRF) model. Those WRF BMP schemes that overpredict surface precipitation along the Cascade windward slopes are shown to have too rapid graupel (rimed snow) fallout. Most BMP schemes overpredict snow in the maximum snow depositional growth region aloft, which results in excessive precipitation spillover into the immediate lee of the Cascades. Meanwhile, there is underprediction to the east of the Cascades in all BMP schemes. Those BMPs that produce more graupel than snow generate nearly twice as much precipitation over the Oregon Coast Range as the other BMPs given the cellular convection in this region. Sensitivity runs suggest that the graupel accretion of snow generates too much graupel within select WRF BMPs. Those BMPs that generate more graupel than snow have shorter cloud residence times and larger removal of available water vapor. Snow depositional growth may be overestimated by 2 times within the BMPs when a capacitance for spherical particles is used rather than for snow aggregates. Snow mass–diameter relationships also have a large impact on the snow and cloud liquid water generation. The positive definite advection scheme for moisture and hydrometeors in the WRF reduces the surface precipitation by 20%–30% over the Coast Range and improves water conservation, especially where there are convective cells.

scholarly journals Evaluating Warm and Cold Rain Processes in Cloud Microphysical Schemes Using OLYMPEX Field Measurements

2020 ◽  
Vol 148 (5) ◽  
pp. 2163-2190
Author(s):  
Aaron R. Naeger ◽  
Brian A. Colle ◽  
Na Zhou ◽  
Andrew Molthan
Keyword(s):  
Wrf Model ◽  
Field Measurements ◽  
Weather Research And Forecasting ◽  
Flow Conditions ◽  
Surface Precipitation ◽  
Particle Properties ◽  
Warm Rain ◽  
Simulated Precipitation ◽  
Rain Fall ◽  
Western Washington

Abstract Field observations from the Olympic Mountain Experiment (OLYMPEX) around western Washington State during two atmospheric river (AR) events in November 2015 were used to evaluate several bulk microphysical parameterizations (BMPs) within the Weather Research and Forecasting (WRF) Model. These AR events were characterized by a prefrontal period of stable, terrain-blocked flow with an abundance of cold rain over the lowland region followed by less stable, unblocked flow with more warm rain, and a shift in the largest precipitation amounts to over the windward Olympic slopes. Our WRF simulations underpredicted the precipitation by 19%–36% in the Morrison (MORR) and Thompson (THOM) BMPs and 10%–23% in the predicted particle properties (P3) BMP, with the largest underpredictions over the windward slopes during the more convective, unblocked flow conditions. Several important processes related to the BMPs led to the differences in simulated precipitation. First, the prognostic single ice category parameterization in the P3 scheme promoted a more realistic evolution of rimed particles and larger cold rain production, which led to the lowest underpredictions in precipitation among the schemes. Second, efficient melting processes associated with the production of nonspherical ice and snow in the P3 and THOM BMPs, respectively, promoted a more realistic transition to rain fall speeds within the warm layer compared to the spherical snow assumption in MORR. Last, all BMPs underpredict the contribution of warm rain processes to the surface precipitation, particularly during the unblocked flow period, which may be partly explained by too weak condensational and collisional growth processes due to the neglect of turbulence parameterizations within the schemes.

scholarly journals A case study of wind farm effects using two wake parameterizations in WRF (V3.7) in the presence of low level jets

2020 ◽  
Author(s):  
Xiaoli G. Larsén ◽  
Jana Fischereit
Keyword(s):  
Wind Farm ◽  
Wrf Model ◽  
Wind Farms ◽  
Weather Research And Forecasting ◽  
Flow Acceleration ◽  
Low Level ◽  
Low Level Jets ◽  
Flight Measurements

Abstract. While the wind farm parameterization by Fitch et al. (2012) in Weather Research and Forecasting (WRF) model has been used and evaluated frequently, the Explicit Wake Parameterization (EWP) by Volker et al. (2015) is less well explored. The openly available high frequency flight measurements from Bärfuss et al. (2019) provide an opportunity to directly compare the simulation results from the EWP and Fitch scheme with in situ measurements. In doing so, this study aims to compliment the recent study by Siedersleben et al. (2020) by (1) comparing the EWP and Fitch schemes in terms of turbulent kinetic energy (TKE) and velocity deficit, together with FINO 1 measurements and Synthetic Aperture Radar (SAR) data and (2) exploring the interactions of the wind farm with Low Level Jets. Both the Fitch and the EWP schemes can capture the mean wind field in the presence of the wind farm consistently and well. However, their skill is limited in capturing the flow acceleration along the farm edge. TKE in the EWP scheme is significantly underestimated, suggesting that an explicit turbine-induced TKE source should be included in addition to the implicit source from shear. The position of the LLJ nose and the shear beneath the jet nose are modified by the presence of wind farms.

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