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Joseph P. Zagrodnik, Lynn McMurdie, and Robert Conrick

Abstract

High-resolution numerical model simulations of six different cases during the 2015/16 Olympic Mountains Experiment (OLYMPEX) are used to examine dynamic and microphysical precipitation processes on both the full barrier-scale and smaller sub-barrier-scale ridges and valleys. The degree to which stratiform precipitation within midlatitude cyclones is modified over the coastal Olympic Mountains range was found to be strongly dependent on the synoptic environment within a cyclone’s prefrontal and warm sectors. In prefrontal sectors, barrier-scale ascent over stably stratified flow resulted in enhanced ice production aloft at the coast and generally upstream of higher terrain. At low levels, stable flow orientated transverse to sub-barrier-scale windward ridges generated small-scale mountain waves, which failed to produce enough cloud water to appreciably enhance precipitation on the scale of the windward ridges. In moist-neutral warm sectors, the upstream side of the barrier exhibited broad ascent oriented along the windward ridges with lesser regions of adjacent downward motion. Significant quantities of cloud water were produced over coastal foothills with further production of cloud water on the lower-windward slopes. Ice production above the melting layer occurred directly over the barrier where the ice particles were further advected downstream by cross-barrier winds and spilled over into the lee. The coastal foothills were found to be essential for the production and maintenance of cloud water upstream of the primary topographic barrier, allowing additional time for hydrometeors to grow to precipitation size by autoconversion and collection before falling out on the lower-windward slopes.

Open access
Ousmane O. Sy, Simone Tanelli, Stephen L. Durden, Andrew Heymsfield, Aaron Bansemer, Kwo-Sen Kuo, Noppasin Niamsuwan, Robert M. Beauchamp, V. Chandrasekar, Manuel Vega, and Michael P. Johnson

Abstract

This article illustrates how multifrequency radar observations can refine the mass–size parameterization of frozen hydrometeors in scattering models and improve the correlation between the radar observations and in situ measurements of microphysical properties of ice and snow. The data presented in this article were collected during the GPM Cold Season Precipitation Experiment (GCPEx) (2012) and Olympic Mountain Experiment (OLYMPEx) (2015) field campaigns, where the true mass–size relationship was not measured. Starting from size and shape distributions of ice particles measured in situ, scattering models are used to simulate an ensemble of reflectivity factors for various assumed mass–size parameterizations (MSP) of the power-law type. This ensemble is then collocated to airborne and ground-based radar observations, and the MSPs are refined by retaining only those that reproduce the radar observations to a prescribed level of accuracy. A versatile “retrieval dashboard” is built to jointly analyze the optimal MSPs and associated retrievals. The analysis shows that the optimality of an MSP depends on the physical assumptions made in the scattering simulators. This work confirms also the existence of a relationship between parameters of the optimal MSPs. Through the MSP optimization, the retrievals of ice water content M and mean diameter D m seem robust to the change in meteorological regime (between GCPEx and OLYMPEx); whereas the retrieval of the diameter spread S m seems more campaign dependent.

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Aaron R. Naeger, Brian A. Colle, Na Zhou, and Andrew Molthan

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.

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Ali Tokay, Leo Pio D’Adderio, David A. Marks, Jason L. Pippitt, David B. Wolff, and Walter A. Petersen

Abstract

The ground-based-radar-derived raindrop size distribution (DSD) parameters—mass-weighted drop diameter D mass and normalized intercept parameter N W—are the sole resource for direct validation of the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM) mission Core Observatory satellite-based retrieved DSD. Both D mass and N W are obtained from radar-measured reflectivity Z H and differential reflectivity Z DR through empirical relationships. This study uses existing relationships that were determined for the GPM ground validation (GV) program and directly compares the NASA S-band polarimetric radar (NPOL) observables of Z H and Z DR and derived D mass and N W with those calculated by two-dimensional video disdrometer (2DVD). The joint NPOL and 2DVD datasets were acquired during three GPM GV field campaigns conducted in eastern Iowa, southern Appalachia, and western Washington State. The comparative study quantifies the level of agreement for Z H, Z DR, D mass, and log(N W) at an optimum distance (15–40 km) from the radar as well as at distances greater than 60 km from radar and over mountainous terrain. Interestingly, roughly 10%–15% of the NPOL Z HZ DR pairs were well outside the envelope of 2DVD-estimated Z HZ DR pairs. The exclusion of these pairs improved the comparisons noticeably.

Free access
Robert Conrick, Joseph P. Zagrodnik, and Clifford F. Mass

Abstract

Radar retrievals of drop size distribution (DSD) parameters are developed and evaluated over the mountainous Olympic Peninsula of Washington State. The observations used to develop retrievals were collected during the 2015/16 Olympic Mountain Experiment (OLYMPEX) and included the NASA S-band dual-polarimetric (NPOL) radar and a collection of second-generation Particle Size and Velocity (PARSIVEL2) disdrometers over the windward slopes of the barrier. Nonlinear and random forest regressions are applied to the PARSIVEL2 data to develop retrievals for median volume diameter, liquid water content, and rain rate. Improvement in DSD retrieval accuracy, defined by the mean error of the retrieval relative to PARSIVEL2 observations, was achieved when using the random forest model when compared with nonlinear regression. Evaluation of disdrometer observations and the retrievals from NPOL indicate that the radar retrievals can accurately reproduce observed DSDs in this region, including the common wintertime regime of small but numerous raindrops that is important there. NPOL retrievals during the OLYMPEX period are further evaluated using two-dimensional video disdrometers (2DVD) and vertically pointing Micro Rain Radars. Results indicate that radar retrievals using random forests may be skillful in capturing DSD characteristics in the lowest portions of the atmosphere.

Free access
Yagmur Derin, Emmanouil Anagnostou, Marios Anagnostou, and John Kalogiros

Abstract

The difficulty of representing high rainfall variability over mountainous areas using ground-based sensors is an open problem in hydrometeorology. Observations from locally deployed dual-polarization X-band radar have the advantage of providing multiparameter measurements near ground that carry significant information useful for estimating drop size distribution (DSD) and surface rainfall rate. Although these measurements are at fine spatiotemporal scale and are less inhibited by complex topography than operational radar network observations, uncertainties in their estimates necessitate error characterization based upon in situ measurements. During November 2015–February 2016, a dual-polarized Doppler on Wheels (DOW) X-band radar was deployed on the Olympic Peninsula of Washington State as part of NASA’s Olympic Mountain Experiment (OLYMPEX). In this study, rain gauges and disdrometers from a dense network positioned within 40 km of DOW are used to evaluate the self-consistency and accuracy of the attenuation and brightband/vertical profile corrections, and rain microphysics estimation by SCOP-ME, an algorithm that uses optimal parameterization and best-fitted functions of specific attenuation coefficients and DSD parameters with radar polarimetric measurements. In addition, the SCOP-ME precipitation microphysical retrievals of median volume diameter D 0 and normalized intercept parameter N W are evaluated against corresponding parameters derived from the in situ disdrometer spectra observations.

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Robert Conrick and Clifford F. Mass

Abstract

The OLYMPEX field campaign, which took place around the Olympic Mountains of Washington State during winter 2015/16, provided data for evaluating the simulated microphysics and precipitation over and near that barrier. Using OLYMPEX observations, this paper assesses precipitation and associated microphysics in the WRF-ARW model over the U.S. Pacific Northwest. Model precipitation from the University of Washington real-time WRF forecast system during the OLYMPEX field program (November 2015–February 2016) and an extended period (2008–18) showed persistent underprediction of precipitation, reaching 100 mm yr−1 over the windward side of the coastal terrain. Increasing horizontal resolution does not substantially reduce this underprediction. Evaluating surface disdrometer observations during the 2015/16 OLYMPEX winter, it was found that the operational University of Washington WRF modeling system using Thompson microphysics poorly simulated the rain drop size distribution over a windward coastal valley. Although liquid water content was represented realistically, drop diameters were overpredicted, and, consequently, the rain drop distribution intercept parameter was underpredicted. During two heavy precipitation periods, WRF realistically simulated environmental conditions, including wind speed, thermodynamic structures, integrated moisture transport, and melting levels. Several microphysical parameterization schemes were tested in addition to the Thompson scheme, with each exhibiting similar biases for these two events. We show that the parameterization of aerosols over the coastal Northwest offered only minor improvement.

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Joseph P. Zagrodnik, Lynn A. McMurdie, Robert A. Houze Jr., and Simone Tanelli

Abstract

As midlatitude cyclones pass over a coastal mountain range, the processes producing their clouds and precipitation are modified, leading to considerable spatial variability in precipitation amount and composition. Statistical diagrams of airborne precipitation radar transects, surface precipitation measurements, and particle size distributions are examined from nine cases observed during the Olympic Mountains Experiment (OLYMPEX). Although the pattern of windward enhancement and leeside diminishment of precipitation was omnipresent, the degree of modulation was largely controlled by the synoptic environment associated with the prefrontal, warm, and postfrontal sectors of midlatitude cyclones. Prefrontal sectors contained homogeneous stratiform precipitation with a slightly enhanced ice layer on the windward slopes and rapid diminishment to a near-complete rain shadow in the lee. Warm sectors contained deep, intense enhancement over both the windward slopes and high terrain and less prominent rain shadows owing to downstream spillover of ice particles generated over terrain. Surface particle size distributions in the warm sector contained a broad spectrum of sizes and concentrations of raindrops on the lower windward side where high precipitation rates were achieved from varying degrees of both liquid and ice precipitation-generating processes. Spillover precipitation was rather homogeneous in nature and lacked the undulations in particle size and concentration that occurred at the windward sites. Postfrontal precipitation transitioned from isolated convective cells over ocean to a shallow, mixed convective–stratiform composition with broader coverage and greater precipitation rates over the sloping terrain.

Open access
Robert Conrick and Clifford F. Mass

Abstract

This study evaluates moist physics in the Weather Research and Forecasting (WRF) Model using observations collected during the Olympic Mountains Experiment (OLYMPEX) field campaign by the Global Precipitation Measurement (GPM) satellite, including data from the GPM Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR) instruments. Even though WRF using Thompson et al. microphysics was able to realistically simulate water vapor concentrations approaching the barrier, there was underprediction of cloud water content and rain rates offshore and over western slopes of terrain. We showed that underprediction of rain rate occurred when cloud water was underpredicted, establishing a connection between cloud water and rain-rate deficits. Evaluations of vertical hydrometeor mixing ratio profiles indicated that WRF produced too little cloud water and rainwater content, particularly below 2.5 km, with excessive snow above this altitude. Simulated mixing ratio profiles were less influenced by coastal proximity or midlatitude storm sector than were GMI profiles. Evaluations of different synoptic storm sectors suggested that postfrontal storm sectors were simulated most realistically, while warm sectors had the largest errors. DPR observations confirm the underprediction of rain rates noted by GMI, with no dependence on whether rain occurs over land or water. Finally, WRF underpredicted radar reflectivity below 2 km and overpredicted above 2 km, consistent with GMI vertical mixing ratio profiles.

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Minda Le and V. Chandrasekar

Abstract

Extensive evaluations have been performed on the dual-frequency classification module in the Global Precipitation Mission (GPM) Dual-Frequency Precipitation Radar (DPR) level-2 algorithm. Both rain type classification and melting-layer detection continue to show promising results in the validations. Surface snowfall identification is a feature newly added in the classification module to the recently released version to provide a surface snowfall flag for each qualified vertical profile. This algorithm is developed upon vertical features of Ku- and Ka-band reflectivity and dual-frequency ratio from DPR. In this paper, we validate this surface snowfall identification algorithm with ground radars including NEXRAD, NASA Polarimetric Radar (NPOL), and CSU–CHILL radar during concurrent precipitation events and GPM validation campaign Olympic Mountain Experiment (OLYMPEX). Other ground truth such as Precipitation Imaging Package (PIP) and ground report is also included in the validation. Based on 16 validation cases in the years 2014–18, the average match ratio between surface snowfall flag from space radar and ground radar is around 87.8%. Promising agreements are achieved with different validation sources. Algorithm limitation and potential improvement are discussed.

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