Robert M. Banta, Yelena L. Pichugina, W. Alan Brewer, Kelly A. Balmes, Bianca Adler, Joseph Sedlar, Lisa S. Darby, David D. Turner, Jaymes S. Kenyon, Edward J. Strobach, Brian J. Carroll, Justin Sharp, Mark T. Stoelinga, Joel Cline, Harindra J.S. Fernando
{"title":"Measurements and model improvement: Insight into NWP model error using Doppler lidar and other WFIP2 measurement systems","authors":"Robert M. Banta, Yelena L. Pichugina, W. Alan Brewer, Kelly A. Balmes, Bianca Adler, Joseph Sedlar, Lisa S. Darby, David D. Turner, Jaymes S. Kenyon, Edward J. Strobach, Brian J. Carroll, Justin Sharp, Mark T. Stoelinga, Joel Cline, Harindra J.S. Fernando","doi":"10.1175/mwr-d-23-0069.1","DOIUrl":"https://doi.org/10.1175/mwr-d-23-0069.1","url":null,"abstract":"Abstract Doppler-lidar wind-profile measurements at three sites were used to evaluate NWP model errors from two versions of NOAA’s 3-km-grid HRRR model, to see whether updates in the latest version-4 reduced errors when compared against the original version-1. Nested (750-m-grid) versions of each were also tested to see how grid spacing affected forecast skill. The measurements were part of the field phase of the Second Wind Forecasting Improvement Project (WFIP2), an 18-month deployment into central Oregon/Washington, a major wind-energy producing region. This study focuses on errors in simulating marine intrusions, a summertime, 600-to-800-m deep, regional sea-breeze flow found to generate large errors. HRRR errors proved to be complex and site dependent. The most prominent error resulted from a premature drop in modeled marine-intrusion wind speeds after local midnight, when lidar-measured winds of greater than 8 m s −1 persisted through the next morning. These large negative errors were offset at low levels by positive errors due to excessive mixing, complicating the interpretation of model ‘improvement,’ such that the updates to the full-scale versions produced mixed results, sometimes enhancing but sometimes degrading model skill. Nesting consistently improved model performance, version-1’s nest producing the smallest errors overall. HRRR’s ability to represent the stages of sea-breeze forcing was evaluated using radiation-budget, surface-energy balance, and near-surface temperature measurements available during WFIP2. The significant site-to-site differences in model error and the complex nature of these errors means that field-measurement campaigns having dense arrays of profiling sensors are necessary to properly diagnose and characterize model errors, as part of a systematic approach to NWP model improvement.","PeriodicalId":18824,"journal":{"name":"Monthly Weather Review","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135825950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michael J. Hosek, Conrad L. Ziegler, M. Biggerstaff, Todd A. Murphy, Zhien Wang
{"title":"Relation Between Baroclinity, Horizontal Vorticity, and Mesocyclone Evolution in the 6-7 April 2018 Monroe, LA Tornadic Supercell During VORTEX-SE","authors":"Michael J. Hosek, Conrad L. Ziegler, M. Biggerstaff, Todd A. Murphy, Zhien Wang","doi":"10.1175/mwr-d-22-0313.1","DOIUrl":"https://doi.org/10.1175/mwr-d-22-0313.1","url":null,"abstract":"\u0000This case study analyzes a tornadic supercell observed in northeast Louisiana as part of the Verification of the Origins of Rotation in Tornadoes Experiment Southeast (VORTEX-SE) on April 6-7 2018. One mobile research radar (SR1-P), one WSR-88D equivalent (KULM), and two airborne radars (TAFT and TFOR) have sampled the storm at close proximity for ~70 minutes through its mature phase, tornadogenesis at 2340 UTC, and dissipation and subsequent ingestion into a developing MCS segment. The 4-D wind field and reflectivity from up to four-Doppler analyses, combined with 4-D diabatic Lagrangian analysis (DLA, Ziegler 2013a,b) retrievals, has enabled kinematic and thermodynamic analysis of storm-scale boundaries leading up to, during, and after the dissipation of the NWS-surveyed EF-0 tornado.\u0000The kinematic and thermodynamic analyses reveal a transient current of low-level streamwise vorticity leading into the low-level supercell updraft, appearing similar to the streamwise vorticity current (SVC) that has been identified in supercell simulations and previously observed only kinematically. Vorticity dynamical calculations demonstrate that both baroclinity and horizontal stretching play significant roles in the generation and amplification of streamwise vorticity associated with this SVC. While the SVC does not directly feed streamwise vorticity to the tornado-cyclone, its development coincides with tornadogenesis and an intensification of the supercell’s main low-level updraft, although a causal relationship is unclear.\u0000Although the mesoscale environment is not high-shear/low-CAPE (HSLC), the updraft of the analyzed supercell shares some similarities to past observations and simulations of HSLC storms in the Southeast US, most notably a pulse-like updraft which is maximized in the low to mid-levels of the storm.","PeriodicalId":18824,"journal":{"name":"Monthly Weather Review","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47544728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identifying Important Microphysical Properties and Processes for Marine Fog Forecasts","authors":"Nathan Hexum Pope, A. Igel","doi":"10.1175/mwr-d-22-0294.1","DOIUrl":"https://doi.org/10.1175/mwr-d-22-0294.1","url":null,"abstract":"\u0000In this study, a marine fog event that occurred from 0000 to 1800 UTC 7 September 2018 near Canada’s Grand Banks is used to investigate the sensitivity of simulated fog properties to six model parameters found primarily in the microphysics scheme. To do so, we ran a large suite of regional simulations that spanned the life cycle of the fog event using the Regional Atmospheric Modeling System (RAMS). We randomly selected parameter combinations for the simulation suite and used Gaussian process regression to emulate the response of a variety of simulated fog properties to the parameters. We find that the microphysics shape parameter, which controls the relative width of the droplet size distribution, and the aerosol number concentration have the greatest impact on fog in terms of spatial extent, duration, and surface visibility. In general, parameters that reduce mean fall speed of droplets and/or suppress drizzle formation lead to reduced visibility in fog but also delayed onset, shorter lifetimes, and reduced spatial extent. The importance of the distribution width suggests a need for better characterization of this property for fog droplet distributions and better treatment of this property in microphysics schemes.","PeriodicalId":18824,"journal":{"name":"Monthly Weather Review","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47293533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Equity, Inclusion, and Justice: An Opportunity for Action for AMS\u0000 Publications Stakeholders","authors":"","doi":"10.1175/mwr-d-23-0173.1","DOIUrl":"https://doi.org/10.1175/mwr-d-23-0173.1","url":null,"abstract":"","PeriodicalId":18824,"journal":{"name":"Monthly Weather Review","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48818460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}