scholarly journals Diagnosing Conditions Associated with Large Intensity Forecast Errors in the Hurricane Weather Research and Forecasting (HWRF) Model

2018 ◽  
Vol 33 (1) ◽  
pp. 239-266 ◽  
Author(s):  
Daniel J. Halperin ◽  
Ryan D. Torn
Keyword(s):  
Inner Core ◽  
Small Error ◽  
Intensity Change ◽  
Weather Research And Forecasting ◽  
Forecast Errors ◽  
Large Intensity ◽  
Small Intensity ◽  
Systematic Biases ◽  
Hwrf Model ◽  
Weather Research

Abstract Understanding and forecasting tropical cyclone (TC) intensity change continues to be a paramount challenge for the research and operational communities, partly because of inherent systematic biases contained in model guidance, which can be difficult to diagnose. The purpose of this paper is to present a method to identify such systematic biases by comparing forecasts characterized by large intensity errors with analog forecasts that exhibit small intensity errors. The methodology is applied to the 2015 version of the Hurricane Weather Research and Forecasting (HWRF) Model retrospective forecasts in the North Atlantic (NATL) and eastern North Pacific (EPAC) basins during 2011–14. Forecasts with large 24-h intensity errors are defined to be in the top 15% of all cases in the distribution that underforecast intensity. These forecasts are compared to analog forecasts taken from the bottom 50% of the error distribution. Analog forecasts are identified by finding the case that has 0–24-h intensity and wind shear magnitude time series that are similar to the large intensity error forecasts. Composite differences of the large and small intensity error forecasts reveal that the EPAC large error forecasts have weaker reflectivity and vertical motion near the TC inner core from 3 h onward. Results over the NATL are less clear, with the significant differences between the large and small error forecasts occurring radially outward from the TC core. Though applied to TCs, this analog methodology could be useful for diagnosing systematic model biases in other applications.

scholarly journals On the growth of intensity forecast errors in the operational hurricane weather research and forecasting (HWRF) model

2018 ◽  
Vol 144 (715) ◽  
pp. 1803-1819 ◽  
Author(s):  
Chanh Kieu ◽  
Kushal Keshavamurthy ◽  
Vijay Tallapragada ◽  
Sundararaman Gopalakrishnan ◽  
Samuel Trahan
Keyword(s):  
Weather Research And Forecasting ◽  
Forecast Errors ◽  
Intensity Forecast ◽  
Hwrf Model ◽  
Weather Research

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.

Impact of Secondary Eyewall Heating on Tropical Cyclone Intensity Change*

2011 ◽  
Vol 68 (3) ◽  
pp. 450-456 ◽  
Author(s):  
Xiaqiong Zhou ◽  
Bin Wang ◽  
Xuyang Ge ◽  
Tim Li
Keyword(s):  
Potential Temperature ◽  
Tropical Rainfall Measuring Mission ◽  
Convective Precipitation ◽  
Intensity Change ◽  
Weather Research And Forecasting ◽  
Large Intensity ◽  
Cyclone Intensity ◽  
Storm Intensity ◽  
Intensity Changes ◽  
Intensity Weakening

Abstract The primary goal of this study is to explore the factors that might influence the intensity change of tropical cyclones (TCs) associated with secondary eyewall replacement. Concentric eyewall structures in TCs with and without large intensity weakening are compared using the Tropical Rainfall Measuring Mission (TRMM) 2A12 and 2A25 data. It is found that the secondary eyewalls with a stratiform-type heating profile show a marked weakening, while those TCs with a convective-type heating weaken insignificantly or even intensify. This observed feature is supported by a set of sensitivity numerical experiments performed with the Weather Research and Forecasting model. With more active convection, the latent heat released in the outer eyewall and moat region can better sustain storm intensity. The prevailing stratiform precipitation results in low equivalent potential temperature air in the moat and reduces the entropy of the boundary layer inflow to the inner eyewall through persistent downdrafts, leading to a large intensity fluctuation. Comparison of observations and numerical model results reveals that the model tends to overproduce convective precipitation in the outer eyewall and the moat. It is possible that the model underestimates the storm intensity changes associated with eyewall replacement events.

Evaluating the Impact of Improvement in the Horizontal Diffusion Parameterization on Hurricane Prediction in the Operational Hurricane Weather Research and Forecast (HWRF) Model

2018 ◽  
Vol 33 (1) ◽  
pp. 317-329 ◽  
Author(s):  
Jun A. Zhang ◽  
Frank D. Marks ◽  
Jason A. Sippel ◽  
Robert F. Rogers ◽  
Xuejin Zhang ◽  
...  
Keyword(s):  
Positive Impact ◽  
Intensity Change ◽  
Horizontal Diffusion ◽  
Warm Core ◽  
Forecast Models ◽  
Hurricane Prediction ◽  
Core Height ◽  
The Impact ◽  
Hwrf Model ◽  
Weather Research

Abstract Improving physical parameterizations in forecast models is essential for hurricane prediction. This study documents the upgrade of horizontal diffusion parameterization in the Hurricane Weather Research and Forecasting (HWRF) Model and evaluates the impact of this upgrade on hurricane forecasts. The horizontal mixing length Lh was modified based on aircraft observations and extensive idealized and real-case numerical experiments. Following an earlier work by the first two authors, who focused on understanding how the horizontal diffusion parameterization worked in HWRF and its dynamical influence on hurricane intensification using idealized simulations, a series of sensitivity experiments was conducted to simulate Hurricane Earl (2010) in which only Lh was varied. Results from the Earl forecasts confirmed the findings from previous theoretical and idealized numerical studies, in that both the simulated maximum intensity and intensity change rate are dependent on Lh. Comparisons between the modeled and observed structure of Hurricane Earl, such as storm size, boundary layer heights, warm-core height and temperature anomaly, and eyewall slope, suggested that the Lh used in the HWRF Model should be decreased. Lowering Lh in HWRF has a positive impact on hurricane prediction based on over 200 retrospective forecasts of 10 Atlantic storms. Biases in both storm intensity and storm size are significantly reduced with the modified Lh.

A Statistical Analysis of High Frequency Track and Intensity Forecasts from NOAA’s Operational Hurricane Weather Research and Forecast (HWRF) Modeling System

2021 ◽  
Author(s):  
Zhan Zhang ◽  
Jun A. Zhang ◽  
Ghassan J. Alaka ◽  
Keqin Wu ◽  
Avichal Mehra ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
High Frequency ◽  
Low Frequency ◽  
Intensity Change ◽  
Weather Research And Forecasting ◽  
Track Forecast ◽  
The North ◽  
Operational Forecasting ◽  
Large Fluctuations ◽  
Weather Research

AbstractA statistical analysis is performed on the high-frequency (3 1/3 s) output from NOAA’s cloud-permitting, high-resolution operational Hurricane Weather Research and Forecasting (HWRF) model for all tropical cyclones (TCs) in the North Atlantic basin over a 3-year period (2017-2019). High-frequency HWRF forecasts of TC track and 10-m maximum wind speed (Vmax) exhibited large fluctuations that were not captured by traditional low-frequency (6 h) model output. Track fluctuations were inversely proportional to Vmax with average values of 6-8 km. Vmax fluctuations were as high as 20 kt in individual forecasts and were a function of maximum intensity, with a standard deviation of 5.5 kt for category 2 hurricanes and smaller fluctuations for tropical storms and major hurricanes. The radius of Vmax contracted or remained steady when TCs rapidly intensified in high-frequency HWRF forecasts, consistent with observations. Running mean windows of 3-9 h were applied at synoptic times to smooth the high-frequency HWRF output to investigate its utility to operational forecasting. Smoothed high-frequency HWRF output improved Vmax forecast skill by up to 8% and produced a more realistic distribution of 6-h intensity change when compared with low-frequency, instantaneous output. Furthermore, the high-frequency track forecast output may be useful for investigating characteristics of TC trochoidal motions.

scholarly journals SHIPS-MI Forecast Analysis of Hurricanes Claudette (2003), Isabel (2003), and Dora (1999)

2007 ◽  
Vol 22 (4) ◽  
pp. 689-707 ◽  
Author(s):  
Thomas A. Jones ◽  
Daniel J. Cecil
Keyword(s):  
Inner Core ◽  
Forecast Accuracy ◽  
Precipitation Forecast ◽  
Intensity Change ◽  
Forecast Errors ◽  
Positive Contribution ◽  
Hurricane Intensity ◽  
Intensity Prediction ◽  
Prediction Scheme ◽  
Dependent Sample

Abstract Three hurricanes, Claudette (2003), Isabel (2003), and Dora (1999), were selected to examine the Statistical Hurricane Intensity Prediction Scheme with Microwave Imagery (SHIPS-MI) forecast accuracy for three particular storm types. This research was conducted using model analyses and tropical cyclone best-track data, with forecasts generated from a dependent sample. The model analyses and best-track data are assumed to be a “perfect” representation of the actual event (e.g., perfect prog assumption). Analysis of intensity change forecasts indicated that SHIPS-MI performed best, compared to operational SHIPS output, for tropical cyclones that were intensifying from tropical storm to hurricane intensity. Passive microwave imagery, which is sensitive to the intensity and coverage of precipitation, improved intensity forecasts during these periods with a positive intensity change contribution resulting from above normal inner-core precipitation. Forecast improvement was greatest for 12–36-h forecasts, where the microwave contribution to SHIPS-MI was greatest. Once a storm reached an intensity close to its maximum potential intensity, as in the case of Isabel and Dora, both SHIPS and SHIPS-MI incorrectly forecast substantial weakening despite the positive contribution from microwave data. At least in Dora’s case, SHIPS-MI forecasts were slightly stronger than those of SHIPS. Other important contributions to SHIPS-MI forecasts were examined to determine their importance relative to the microwave inputs. Inputs related to sea surface temperature (SST) and persistence–climatology proved to be very important to intensity change forecasts, as expected. These predictors were the primary factor leading to the persistent weakening forecasts made by both models for Isabel and Dora. For Atlantic storms (Claudette and Isabel), the contribution from shear also proved important at characterizing the conduciveness of the environment toward intensification. However, the shear contribution was often small as a result of multiple offsetting shear-related predictors. Finally, it was observed that atmospheric parameters not included in SHIPS, such as eddy momentum flux, could substantially affect the intensity, leading to large forecast errors. This was especially true for the Claudette intensity change forecasts throughout its life cycle.

scholarly journals Representing Multiple Scales in the Hurricane Weather Research and Forecasting Modeling System: Design of Multiple Sets of Movable Multilevel Nesting and the Basin-Scale HWRF Forecast Application

2016 ◽  
Vol 31 (6) ◽  
pp. 2019-2034 ◽  
Author(s):  
Xuejin Zhang ◽  
Sundararaman G. Gopalakrishnan ◽  
Samuel Trahan ◽  
Thiago S. Quirino ◽  
Qingfu Liu ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Multiple Scales ◽  
Hurricane Sandy ◽  
Weather Research And Forecasting ◽  
Forecast Errors ◽  
Ocean Coupling ◽  
Outer Domain ◽  
Basin Scale ◽  
New System ◽  
Weather Research

Abstract In this study, the design of movable multilevel nesting (MMLN) in the Hurricane Weather Research and Forecasting (HWRF) modeling system is documented. The configuration of a new experimental HWRF system with a much larger horizontal outer domain and multiple sets of MMLN, referred to as the “basin scale” HWRF, is also described. The performance of this new system is applied for various difficult forecast scenarios such as 1) simulating multiple storms [i.e., Hurricanes Earl (2010), Danielle (2010), and Frank (2010)] and 2) forecasting tropical cyclone (TC) to extratropical cyclone transitions, specifically Hurricane Sandy (2012). Verification of track forecasts for the 2011–14 Atlantic and eastern Pacific hurricane seasons demonstrates that the basin-scale HWRF produces similar overall results to the 2014 operational HWRF, the best operational HWRF at the same resolution. In the Atlantic, intensity forecasts for the basin-scale HWRF were notably worse than for the 2014 operational HWRF, but this deficiency was shown to be from poor intensity forecasts for Hurricane Leslie (2012) associated with the lack of ocean coupling in the basin-scale HWRF. With Leslie removed, the intensity forecast errors were equivalent. The basin-scale HWRF is capable of predicting multiple TCs simultaneously, allowing more realistic storm-to-storm interactions. Even though the basin-scale HWRF produced results only comparable to the regular operational HWRF at this stage, this configuration paves a promising pathway toward operations.

scholarly journals A Review and Evaluation of Planetary Boundary Layer Parameterizations in Hurricane Weather Research and Forecasting Model Using Idealized Simulations and Observations

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1091
Author(s):  
Jun A. Zhang ◽  
Evan A. Kalina ◽  
Mrinal K. Biswas ◽  
Robert F. Rogers ◽  
Ping Zhu ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Planetary Boundary Layer ◽  
Doppler Radar ◽  
Deep Convection ◽  
Eddy Diffusivity ◽  
Intensity Change ◽  
Weather Research And Forecasting ◽  
Pbl Scheme ◽  
Weather Research

This paper reviews the evolution of planetary boundary layer (PBL) parameterization schemes that have been used in the operational version of the Hurricane Weather Research and Forecasting (HWRF) model since 2011. Idealized simulations are then used to evaluate the effects of different PBL schemes on hurricane structure and intensity. The original Global Forecast System (GFS) PBL scheme in the 2011 version of HWRF produces the weakest storm, while a modified GFS scheme using a wind-speed dependent parameterization of vertical eddy diffusivity (Km) produces the strongest storm. The subsequent version of the hybrid eddy diffusivity and mass flux scheme (EDMF) used in HWRF also produces a strong storm, similar to the version using the wind-speed dependent Km. Both the intensity change rate and maximum intensity of the simulated storms vary with different PBL schemes, mainly due to differences in the parameterization of Km. The smaller the Km in the PBL scheme, the faster a storm tends to intensify. Differences in hurricane PBL height, convergence, inflow angle, warm-core structure, distribution of deep convection, and agradient force in these simulations are also examined. Compared to dropsonde and Doppler radar composites, improvements in the kinematic structure are found in simulations using the wind-speed dependent Km and modified EDMF schemes relative to those with earlier versions of the PBL schemes in HWRF. However, the upper boundary layer in all simulations is much cooler and drier than that in dropsonde observations. This model deficiency needs to be considered and corrected in future model physics upgrades.

scholarly journals Understanding Biases in Tropical Cyclone Intensity Forecast Error

2018 ◽  
Vol 33 (1) ◽  
pp. 129-138 ◽  
Author(s):  
Wei Na ◽  
John L. McBride ◽  
Xing-Hai Zhang ◽  
Yi-Hong Duan
Keyword(s):  
Tropical Cyclone ◽  
Forecast Error ◽  
Correlation Coefficients ◽  
Rate Of Change ◽  
Intensity Change ◽  
Forecast Errors ◽  
Second Derivative ◽  
Rapid Intensification ◽  
Time Curve ◽  
Large Intensity

Abstract The characteristics of 24-h official forecast errors (OFEs) of tropical cyclone (TC) intensity are analyzed over the North Atlantic, east Pacific, and western North Pacific. The OFE is demonstrated to be strongly anticorrelated with TC intensity change with correlation coefficients of −0.77, −0.77, and −0.68 for the three basins, respectively. The 24-h intensity change in the official forecast closely follows a Gaussian distribution with a standard deviation only ⅔ of that in nature, suggesting the current official forecasts estimate fewer cases of large intensity change. The intensifying systems tend to produce negative errors (underforecast), while weakening systems have consistent positive errors (overforecast). This asymmetrical bias is larger for extreme intensity change, including rapid intensification (RI) and rapid weakening (RW). To understand this behavior, the errors are analyzed in a simple objective model, the trend-persistence model (TPM). The TPM exhibits the same error-intensity change correlation. In the TPM, the error can be understood as it is exactly inversely proportional to the finite difference form of the concavity or second derivative of the intensity–time curve. The occurrence of large negative (positive) errors indicates the intensity–time curve is concave upward (downward) in nature during the TC’s rapid intensification (weakening) process. Thus, the fundamental feature of the OFE distribution is related to the shape of the intensity–time curve, governed by TC dynamics. All forecast systems have difficulty forecasting an accelerating rate of change, or a large second derivative of the intensity–time curve. TPM may also be useful as a baseline in evaluating the skill of official forecasts. According to this baseline, official forecasts are more skillful in RW than in RI.

scholarly journals Evaluation of the Grell–Freitas Convective Scheme in the Hurricane Weather Research and Forecasting (HWRF) Model

2020 ◽  
Vol 35 (3) ◽  
pp. 1017-1033 ◽  
Author(s):  
Mrinal K. Biswas ◽  
Jun A. Zhang ◽  
Evelyn Grell ◽  
Evan Kalina ◽  
Kathryn Newman ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Angular Momentum ◽  
Storm Track ◽  
Superior Performance ◽  
Weather Research And Forecasting ◽  
Budget Analysis ◽  
Eddy Transport ◽  
The Difference ◽  
Hwrf Model ◽  
Weather Research

Abstract The Developmental Testbed Center (DTC) tested two convective parameterization schemes in the Hurricane Weather Research and Forecasting (HWRF) Model and compared them in terms of performance of forecasting tropical cyclones (TCs). Several TC forecasts were conducted with the scale-aware Simplified Arakawa Schubert (SAS) and Grell–Freitas (GF) convective schemes over the Atlantic basin. For this sample of over 100 cases, the storm track and intensity forecasts were superior for the GF scheme compared to SAS. A case study showed improved storm structure for GF when compared with radar observations. The GF run had increased inflow in the boundary layer, which resulted in higher angular momentum. An angular momentum budget analysis shows that the difference in the contribution of the eddy transport to the total angular momentum tendency is small between the two forecasts. The main difference is in the mean transport term, especially in the boundary layer. The temperature tendencies indicate higher contribution from the microphysics and cumulus heating above the boundary layer in the GF run. A temperature budget analysis indicated that both the temperature advection and diabatic heating were the dominant terms and they were larger near the storm center in the GF run than in the SAS run. The above results support the superior performance of the GF scheme for TC intensity forecast.

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