Sensitivity of hurricane forecasts to cumulus parameterizations in the HWRF model

2014 ◽  
Vol 41 (24) ◽  
pp. 9113-9119 ◽  
Author(s):  
Mrinal K. Biswas ◽  
Ligia Bernardet ◽  
Jimy Dudhia
Keyword(s):  
Cumulus Parameterizations ◽  
Hwrf Model

scholarly journals Vortex Initialization in the NCEP Operational Hurricane Models

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 968
Author(s):  
Qingfu Liu ◽  
Xuejin Zhang ◽  
Mingjing Tong ◽  
Zhan Zhang ◽  
Bin Liu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Background Field ◽  
Initial Field ◽  
The Future ◽  
Background Fields ◽  
Vortex Relocation ◽  
Hwrf Model ◽  
Vortex Initialization

This paper describes the vortex initialization (VI) currently used in NCEP operational hurricane models (HWRF and HMON, and possibly HAFS in the future). The VI corrects the background fields for hurricane models: it consists of vortex relocation, and size and intensity corrections. The VI creates an improved background field for the data assimilation and thereby produces an improved analysis for the operational hurricane forecast. The background field after VI can be used as an initial field (as in the HMON model, without data assimilation) or a background field for data assimilation (as in HWRF model).

scholarly journals Convective distribution of dust over the Arabian Peninsula: the impact of model resolution

2019 ◽  
Author(s):  
Jennie Bukowski ◽  
Susan C. van den Heever
Keyword(s):  
Arabian Peninsula ◽  
Dust Emission ◽  
Dust Storms ◽  
Radiation Budget ◽  
Grid Spacing ◽  
Heating Rates ◽  
Dust Transport ◽  
Order Of Magnitude ◽  
The Impact ◽  
Cumulus Parameterizations

Abstract. Along the coasts of the Arabian Peninsula, convective dust storms are a considerable source of mineral dust to the atmosphere. Reliable predictions of convective dust events are necessary to determine their effects on air quality, visibility, and the radiation budget. In this study, the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) is used to simulate a 2016 summertime dust event over the Arabian Peninsula and examine the variability in dust fields and associated vertical transport due to the choice of convective parameterization and explicit versus parameterized convection. Simulations are run at 45 km and 15 km grid spacing with multiple cumulus parameterizations, and are compared to a 3 km simulation that permits explicit convective processes. Five separate cumulus parameterizations at 15 km grid spacing were tested to quantify the spread across different parameterizations. Finally, the impact these variations have on radiation, specifically aerosol heating rates is also investigated. On average, in these simulations the explicit case produces higher quantities of dust than the parameterized cases in terms of dust uplift potential, vertical dust concentrations, and vertical dust fluxes. Major drivers of this discrepancy between the simulations stem from the explicit case exhibiting higher surface windspeeds during convective activity, lower dust emission wind threshold velocities due to drier soil, and more frequent, stronger vertical velocities which transport dust aloft and increase the atmospheric lifetime of these particles. For aerosol heating rates in the lowest levels, the shortwave effect prevails in the explicit case with a net cooling effect, whereas a longwave net warming effect is present in the parameterized cases. The spread in dust concentrations across cumulus parameterizations at the same grid resolution (15 km) is an order of magnitude lower than the impact of moving from parameterized to explicit convection. We conclude that tuning dust emissions in coarse resolution simulations can only improve the results to first-order and cannot fully rectify the discrepancies originating from disparities in the representation of convective dust transport.

scholarly journals Improving Hurricane Analyses and Predictions with TCI, IFEX Field Campaign Observations, and CIMSS AMVs Using the Advanced Hybrid Data Assimilation System for HWRF. Part I: What is Missing to Capture the Rapid Intensification of Hurricane Patricia (2015) when HWRF is already Initialized with a More Realistic Analysis?

2019 ◽  
Vol 147 (4) ◽  
pp. 1351-1373 ◽  
Author(s):  
Xu Lu ◽  
Xuguang Wang
Keyword(s):  
Data Assimilation ◽  
Initial Conditions ◽  
Surface Wind ◽  
Rapid Intensification ◽  
Model Resolution ◽  
Field Campaign ◽  
Horizontal Diffusion ◽  
Intensity Forecast ◽  
Physics Parameterizations ◽  
Hwrf Model

Abstract Assimilating inner-core observations collected from recent field campaign programs such as Tropical Cyclone Intensity (TCI) and Intensity Forecasting Experiment (IFEX) together with the enhanced atmospheric motion vectors (AMVs) produce realistic three-dimensional (3D) analyses using the newly developed GSI-based, continuously cycled, dual-resolution hybrid ensemble–variational data assimilation (DA) system for the Hurricane Weather Research and Forecasting (HWRF) Model for Hurricane Patricia (2015). However, more persistent surface wind maximum spindown is found in the intensity forecast initialized from the realistic analyses produced by the DA system but not from the unrealistic initial conditions produced through vortex modification. Diagnostics in this study reveal that the spindown issue is likely attributed to the deficient HWRF Model physics that are unable to maintain the realistic 3D structures from the DA analysis. The horizontal diffusion is too strong to maintain the realistically observed vertical oscillation of radial wind near the eyewall region. The vertical diffusion profile cannot produce a sufficiently strong secondary circulation connecting the realistically elevated upper-level outflow produced in the DA analysis. Further investigations with different model physics parameterizations demonstrate that spindown can be alleviated by modifying model physics parameterizations. In particular, a modified turbulent mixing parameterization scheme together with a reduced horizontal diffusion is found to significantly alleviate the spindown issue and to improve the intensity forecast. Additional experiments show that the peak-simulated intensity and rapid intensification rate can be further improved by increasing the model resolution. But the model resolution is not as important as model physics in the spindown alleviation.

scholarly journals Assessing the Accuracy of the Cloud and Water Vapor Fields in the Hurricane WRF (HWRF) Model Using Satellite Infrared Brightness Temperatures

2017 ◽  
Vol 145 (5) ◽  
pp. 2027-2046 ◽  
Author(s):  
Jason A. Otkin ◽  
William E. Lewis ◽  
Allen J. Lenzen ◽  
Brian D. McNoldy ◽  
Sharanya J. Majumdar
Keyword(s):  
Forecast Accuracy ◽  
Cloud Microphysics ◽  
Cumulus Parameterization ◽  
Upper Troposphere ◽  
Wind Speeds ◽  
Parameterization Schemes ◽  
Brightness Temperatures ◽  
Cumulus Parameterization Schemes ◽  
Hwrf Model ◽  
Infrared Brightness

Abstract In this study, cycled forecast experiments were performed to assess the ability of different cloud microphysics and cumulus parameterization schemes in the Hurricane Weather Research and Forecasting (HWRF) Model to accurately simulate the evolution of the cloud and moisture fields during the entire life cycle of Hurricane Edouard (2014). The forecast accuracy for each model configuration was evaluated through comparison of observed and simulated Geostationary Operational Environmental Satellite-13 (GOES-13) infrared brightness temperatures and satellite-derived tropical cyclone intensity estimates computed using the advanced Dvorak technique (ADT). Overall, the analysis revealed a large moist bias in the mid- and upper troposphere during the entire forecast period that was at least partially due to a moist bias in the initialization datasets but was also affected by the microphysics and cumulus parameterization schemes. Large differences occurred in the azimuthal brightness temperature distributions, with two of the microphysics schemes producing hurricane eyes that were much larger and clearer than observed, especially for later forecast hours. Comparisons to the forecast 10-m wind speeds showed reasonable agreement (correlations between 0.58 and 0.74) between the surface-based intensities and the ADT intensity estimates inferred via cloud patterns in the upper troposphere. It was also found that model configurations that had the smallest differences between the ADT and surface-based intensities had the most accurate track and intensity forecasts. Last, the cloud microphysics schemes had the largest impact on the forecast accuracy.

scholarly journals Estimations of Mass Fluxes for Cumulus Parameterizations from High-Resolution Spatial Data

2004 ◽  
Vol 61 (7) ◽  
pp. 829-842 ◽  
Author(s):  
Jun-Ichi Yano ◽  
Francoise Guichard ◽  
Jean-Philippe Lafore ◽  
Jean-Luc Redelsperger ◽  
Peter Bechtold
Keyword(s):  
High Resolution ◽  
Spatial Data ◽  
Mass Fluxes ◽  
Cumulus Parameterizations

Improving the Four-Dimensional Incremental Analysis Update (4DIAU) with the HWRF 4DEnVar Data Assimilation System for Rapidly Evolving Hurricane Prediction

2021 ◽  
Author(s):  
Xu Lu ◽  
Xuguang Wang
Keyword(s):  
Data Assimilation ◽  
Inner Core ◽  
Weather Research And Forecasting ◽  
Incremental Analysis ◽  
Short Term ◽  
Linear Evolution ◽  
Oscillation Model ◽  
Incremental Update ◽  
Hurricane Prediction ◽  
Hwrf Model

AbstractShort-term spin-up for strong storms is a known difficulty for the operational Hurricane Weather Research and Forecasting (HWRF) model after assimilating high-resolution inner-core observations. Our previous study associated this short-term intensity prediction issue with the incompatibility between the HWRF model and the data assimilation (DA) analysis. While improving physics and resolution of the model was found helpful, this study focuses on further improving the intensity predictions through the four-dimensional incremental analysis update (4DIAU).In the traditional 4DIAU, increments are pre-determined by subtracting background forecasts from analyses. Such pre-determined increments implicitly require linear evolution assumption during the update, which are hardly valid for rapid-evolving hurricanes. To confirm the hypothesis, a corresponding 4D analysis nudging (4DAN) method which uses online increments is first compared with the 4DIAU in an oscillation model. Then, variants of 4DIAU are proposed to improve its application for nonlinear systems. Next, 4DIAU, 4DAN and their proposed improvements are implemented into the HWRF 4DEnVar DA system and are investigated with hurricane Patricia (2015).Results from both oscillation model and HWRF model show that: 1. the pre-determined increments in 4DIAU can be detrimental when there are discrepancies between the updated and background forecasts during a nonlinear evolution. 2. 4DAN can improve the performance of incremental update upon 4DIAU, but its improvements are limited by the over-filtering. 3. Relocating initial background before the incremental update can improve the corresponding traditional methods. 4. the feature-relative 4DIAU method improves the incremental update the most and produces the best track and intensity predictions for Patricia among all experiments.

The hourly precipitation frequencies in the tropical-belt version of WRF: sensitivity to cumulus parameterization and radiative schemes

2021 ◽  
pp. 1-59
Author(s):  
Xianghui Kong ◽  
Aihui Wang ◽  
Xunqiang Bi ◽  
Biyun Sun ◽  
Jiangfeng Wei
Keyword(s):  
Heavy Precipitation ◽  
Cumulus Parameterization ◽  
Weather Research And Forecasting ◽  
Tropical Region ◽  
Rain Event ◽  
Grid Spacing ◽  
Precipitation Frequency ◽  
Hourly Precipitation ◽  
Moderate Rate ◽  
Cumulus Parameterizations

AbstractThe sensitivity of hourly precipitation to cumulus parameterizations and radiative schemes is explored by using the tropical-belt configuration of the Weather Research and Forecasting Model. The domain covers the entire tropical region from 45°S to 45°N with a grid spacing of about 45 km. A series of 5-year simulations with four cumulus parameterizations (New Tiedtke, NT; Kain-Fritsch, KF; New SAS, NS; and Tiedtke, TK) and two radiative schemes (RRTMG, CAM) are carried out. We focus on the frequencies of hourly precipitation above three thresholds (0.02 mm h-1, light drizzle rate; 0.2 mm h-1, moderate rate; and 2 mm h-1, heavy rate) between the observed CMORPH products and simulations. The sensitivity is higher for precipitation frequency than amount, and frequency is dominated by the cumulus parameterization. Frequencies above the moderate rate are well-reproduced, while frequencies above the other two rates present large deviations. No combination of physical schemes is found to perform best in reproducing the frequencies above all thresholds. Simulations using the NT and NS schemes show higher (lower) precipitation frequencies above the light drizzle rate (heavy rate) than those simulations using the KF and TK schemes. Precipitation frequency is higher reproduced by experiments using the RRTMG scheme than those using the CAM scheme, except for frequencies above the light rate over oceans. The overestimation of frequency is mainly caused by too-frequent convective rainfall. The results imply that the triggering based on the vertical velocity may increases the occurrence of rain event, while CAPE-based closure maybe increase the heavy precipitation frequency in the cumulus parameterizations.

Influence of Assimilating CYGNSS Ocean Surface Wind Data on Tropical Cyclone Analyses and Predictions

2020 ◽  
Author(s):  
Bachir Annane ◽  
Mark Leidner ◽  
Ross Hoffman ◽  
Feixiong Huang ◽  
James Garrisson
Keyword(s):  
Tropical Cyclones ◽  
Surface Wind ◽  
Ocean Surface ◽  
Convective Precipitation ◽  
Weather Research And Forecasting ◽  
Wind Speeds ◽  
Ocean Surface Winds ◽  
Ocean Surface Wind ◽  
The Impact ◽  
Hwrf Model

<div> <div><em>For the analysis and forecasting of tropical cyclones, the main benefits of data from the CYGNSS constellation of satellites are the increased revisit frequency compared with polar-orbiting satellites and the ability to provide ocean surface wind observations through convective precipitation. Consequently, CYGNSS delivers an improved capability to observe the structure and evolution of ocean surface winds in and around tropical cyclones. This study quantifies the impact of assimilating CYGNSS delay-Doppler maps, CYGNSS retrieved wind speeds and derived CYGNSS wind vectors on 6-hourly analyses and 5-day forecasts of developing tropical cyclones, using the 2019 version of NOAA's operational Hurricane Weather Research and Forecasting (HWRF) model.</em></div> </div>

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