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Abstract During late June 2021, a record-breaking heatwave impacted western North America, with all-time high temperatures reported across Washington, Oregon, British Columbia, and Alberta. The heatwave was forced by a highly anomalous upper-level ridge, strong synoptic-scale subsidence, and downslope flow resulting in lower-tropospheric adiabatic warming. This study examines the impact of antecedent soil moisture on this extreme heat event. During the cool season of 2020/21, precipitation over the Pacific Northwest was above or near normal, followed by a dry spring that desiccated soils to 50%–75% of normal moisture content by early June. Low surface soil moisture affects the surface energy balance by altering the partitioning between sensible and latent heat fluxes, resulting in warmer temperatures. Using numerical model simulations of the heatwave, this study demonstrates that surface air temperatures were warmed by an average of 0.48°C as a result of dry soil moisture conditions, compared to a high-temperature anomaly of 10°–20°C during the event. Air temperatures over eastern Washington and southern British Columbia were most sensitive to soil moisture anomalies, with 0000 UTC temperature anomalies ranging from 1.2° to 2.2°C. Trajectory analysis indicated that rapid subsidence of elevated parcels prevented air parcels from being affected by surface heat fluxes over a prolonged period of time, resulting in a relatively small temperature sensitivity to soil moisture. Changes to soil moisture also altered regional pressure, low-level wind, and geopotential heights, as well as modified the marine air intrusion along the Pacific coast of Washington and Oregon. Significance Statement The record-breaking western North American heatwave of late June 2021 was preceded by below-normal soil moisture over the region. This study evaluates the role of soil moisture on the 2021 heatwave, demonstrating that the anomalous temperatures during this extreme event were not significantly increased by below-normal soil moisture. 

Abstract This paper describes the downscaling of an ensemble of 12 general circulation models (GCMs) using the Weather Research and Forecasting (WRF) Model at 12-km grid spacing over the period 1970–2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. The 1 April snowpack declines are large over the lower-to-middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCMs producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the twenty-first century. Significance Statement This paper provides a unique high-resolution view of projected climate change over the Pacific Northwest and does so using an ensemble of regional climate models, affording a look at the uncertainties in local impacts of global warming. The paper examines regional meteorological processes influenced by global warming and provides guidance for adaptation and preparation. 

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⁻¹over 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. 

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. 

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.