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  • Carley, Jacob R.  (5)
  • 2015-2019  (5)
  • Geography  (5)
  • 1
    Online Resource
    Online Resource
    Improvements to the Assimilation of Doppler Radial Winds for Convection-Permitting Forecasts of a Heavy Rain Event
    American Meteorological Society ; 2019
    In:  Monthly Weather Review Vol. 147, No. 10 ( 2019-10-01), p. 3609-3632
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 147, No. 10 ( 2019-10-01), p. 3609-3632
    Abstract: This work describes developments to improve the Doppler radial wind data assimilation scheme used in the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) data assimilation system with a focus on convection-permitting, 0–18-h forecasts of a heavy precipitation single case study. This work focuses on two aspects: 1) the extension of the radial wind observation operator to include vertical velocity and 2) a refinement of the radial wind super-observation processing. The refinement includes reducing the magnitude of observation smoothing and allowing observations from higher scan angles into the analysis with the intent to improve the assimilation of the radar data for operational, convection-permitting models. The results of this study demonstrate that there is sensitivity to the refinement in super-observation settings. The inclusion of vertical velocity in the observation operator is shown to have a neutral to slightly positive impact on the forecast. Results from this study are suggested to be used as a foundation to prioritize future research into the effective assimilation of radial winds in an operational setting.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/MWR-D-18-0411.1
    RVK:
    RA 1000
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2019
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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  • 2
    Online Resource
    Online Resource
    Modified NAM Microphysics for Forecasts of Deep Convective Storms
    American Meteorological Society ; 2018
    In:  Monthly Weather Review Vol. 146, No. 12 ( 2018-12-01), p. 4115-4153
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 146, No. 12 ( 2018-12-01), p. 4115-4153
    Abstract: The Ferrier–Aligo (FA) microphysics scheme has been running operationally in the National Centers for Environmental Prediction (NCEP) North American Mesoscale Forecast System (NAM) since August 2014. It was developed to improve forecasts of deep convection in the NAM contiguous United States (CONUS) nest, and it replaces previous versions of the NAM microphysics. The FA scheme is the culmination of extensive microphysical scheme sensitivity experiments made over nearly a dozen warm- and cool-season severe weather cases, as well as an extensive real-time testing in a full, system-wide developmental version of the NAM. While the FA scheme advects each hydrometeor species separately, it was the mass-weighted rime factor (RF) that allowed rimed ice to be advected to very cold temperatures aloft and improved the vertical structure of deep convection. Rimed ice fall speeds were reduced in order to offset an increase in bias of heavy precipitation as a consequence of the mass-weighted RF advection. The FA scheme also incorporated findings from 3-km model runs using the Thompson scheme, including 1) improved closure assumptions for large precipitating ice that targeted the convective and anvil regions of storms, 2) a new diagnostic calculation of radar reflectivity from rimed ice in association with intense convection, and 3) a variable rain intercept parameter that reduced widespread spurious weak reflectivity from shallow boundary layer clouds and increased stratiform rainfall.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/MWR-D-17-0277.1
    RVK:
    RA 1000
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2018
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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  • 3
    Online Resource
    Online Resource
    Assessment of NWP Forecast Models in Simulating Offshore Winds through the Lower Boundary Layer by Measurements from a Ship-Based Scanning Doppler Lidar
    American Meteorological Society ; 2017
    In:  Monthly Weather Review Vol. 145, No. 10 ( 2017-10), p. 4277-4301
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 145, No. 10 ( 2017-10), p. 4277-4301
    Abstract: Evaluation of model skill in predicting winds over the ocean was performed by comparing retrospective runs of numerical weather prediction (NWP) forecast models to shipborne Doppler lidar measurements in the Gulf of Maine, a potential region for U.S. coastal wind farm development. Deployed on board the NOAA R/V Ronald H. Brown during a 2004 field campaign, the high-resolution Doppler lidar (HRDL) provided accurate motion-compensated wind measurements from the water surface up through several hundred meters of the marine atmospheric boundary layer (MABL). The quality and resolution of the HRDL data allow detailed analysis of wind flow at heights within the rotor layer of modern wind turbines and data on other critical variables to be obtained, such as wind speed and direction shear, turbulence, low-level jet properties, ramp events, and many other wind-energy-relevant aspects of the flow. This study will focus on the quantitative validation of NWP models’ wind forecasts within the lower MABL by comparison with HRDL measurements. Validation of two modeling systems rerun in special configurations for these 2004 cases—the hourly updated Rapid Refresh (RAP) system and a special hourly updated version of the North American Mesoscale Forecast System [NAM Rapid Refresh (NAMRR)]—are presented. These models were run at both normal-resolution (RAP, 13 km; NAMRR, 12 km) and high-resolution versions: the NAMRR-CONUS-nest (4 km) and the High-Resolution Rapid Refresh (HRRR, 3 km). Each model was run twice: with (experimental runs) and without (control runs) assimilation of data from 11 wind profiling radars located along the U.S. East Coast. The impact of the additional assimilation of the 11 profilers was estimated by comparing HRDL data to modeled winds from both runs. The results obtained demonstrate the importance of high-resolution lidar measurements to validate NWP models and to better understand what atmospheric conditions may impact the accuracy of wind forecasts in th e marine atmospheric boundary layer. Results of this research will also provide a first guess as to the uncertainties of wind resource assessment using NWP models in one of the U.S. offshore areas projected for wind plant development.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/MWR-D-16-0442.1
    RVK:
    RA 1000
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2017
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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  • 4
    Online Resource
    Online Resource
    A Comparison of Multiscale GSI-Based EnKF and 3DVar Data Assimilation Using Radar and Conventional Observations for Midlatitude Convective-Scale Precipitation Forecasts
    American Meteorological Society ; 2015
    In:  Monthly Weather Review Vol. 143, No. 8 ( 2015-08-01), p. 3087-3108
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 143, No. 8 ( 2015-08-01), p. 3087-3108
    Abstract: A GSI-based data assimilation (DA) system, including three-dimensional variational assimilation (3DVar) and ensemble Kalman filter (EnKF), is extended to the multiscale assimilation of both meso- and synoptic-scale observation networks and convective-scale radar reflectivity and velocity observations. EnKF and 3DVar are systematically compared in this multiscale context to better understand the impacts of differences between the DA techniques on the analyses at multiple scales and the subsequent convective-scale precipitation forecasts. Averaged over 10 diverse cases, 8-h precipitation forecasts initialized using GSI-based EnKF are more skillful than those using GSI-based 3DVar, both with and without storm-scale radar DA. The advantage from radar DA persists for ~5 h using EnKF, but only ~1 h using 3DVar. A case study of an upscale growing MCS is also examined. The better EnKF-initialized forecast is attributed to more accurate analyses of both the mesoscale environment and the storm-scale features. The mesoscale location and structure of a warm front is more accurately analyzed using EnKF than 3DVar. Furthermore, storms in the EnKF multiscale analysis are maintained during the subsequent forecast period. However, storms in the 3DVar multiscale analysis are not maintained and generate excessive cold pools. Therefore, while the EnKF forecast with radar DA remains better than the forecast without radar DA throughout the forecast period, the 3DVar forecast quality is degraded by radar DA after the first hour. Diagnostics revealed that the inferior analysis at mesoscales and storm scales for the 3DVar is primarily attributed to the lack of flow dependence and cross-variable correlation, respectively, in the 3DVar static background error covariance.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/MWR-D-14-00345.1
    RVK:
    RA 1000
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2015
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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  • 5
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    Online Resource
    Comparing the Assimilation of Radar Reflectivity Using the Direct GSI-Based Ensemble–Variational (EnVar) and Indirect Cloud Analysis Methods in Convection-Allowing Forecasts over the Continental United States
    American Meteorological Society ; 2019
    In:  Monthly Weather Review Vol. 147, No. 5 ( 2019-05-01), p. 1655-1678
    Details
    In: Monthly Weather Review, American Meteorological Society, Vol. 147, No. 5 ( 2019-05-01), p. 1655-1678
    Abstract: Two methods for assimilating radar reflectivity into deterministic convection-allowing forecasts were compared: an operationally used, computationally less expensive cloud analysis (CA) scheme and a relatively more expensive, but rigorous, ensemble Kalman filter–variational hybrid method (EnVar). These methods were implemented in the Nonhydrostatic Multiscale Model on the B-grid and were tested on 10 cases featuring high-impact deep convective storms and heavy precipitation. A variety of traditional, neighborhood-based, and features-based verification metrics support that the EnVar produced superior free forecasts compared to the CA procedure, with statistically significant differences extending up to 9 h into the forecast. Despite being inferior, the CA scheme was able to provide benefit compared to not assimilating radar reflectivity at all, but limited to the first few forecast hours. While the EnVar is able to partially suppress spurious convection by assimilating 0-dBZ reflectivity observations directly, the CA is not designed to reduce or remove hydrometeors. As a result, the CA struggles more with suppression of spurious convection in the first-guess field, which resulted in high-frequency biases and poor forecast evolution, as illustrated in a few case studies. Additionally, while the EnVar uses flow-dependent ensemble covariances to update hydrometers, thermodynamic, and dynamic variables simultaneously when the reflectivity is assimilated, the CA relies on a radar reflectivity-derived latent heating rate that is applied during a separate digital filter initialization (DFI) procedure to introduce deep convective storms into the model, and the results of CA are shown to be sensitive to the window length used in the DFI.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    URL: Article
    DOI: 10.1175/MWR-D-18-0171.1
    RVK:
    RA 1000
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2019
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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