The Naval Research Laboratory’s Coupled Ocean/Atmosphere Mesoscale Prediction System – Tropical Cyclone ensemble (COAMPS-TC ensemble)

2021 ◽  
Author(s):  
William A. Komaromi ◽  
Patrick A. Reinecke ◽  
James D. Doyle ◽  
Jonathan R. Moskaitis
Keyword(s):  
Tropical Cyclone ◽  
Boundary Conditions ◽  
Skill Score ◽  
Horizontal Resolution ◽  
Naval Research ◽  
Lead Times ◽  
Prediction System ◽  
Intensity Forecast ◽  
Probabilistic Forecasts ◽  
Ocean Atmosphere

AbstractThe 11-member Coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) ensemble has been developed by the Naval Research Laboratory (NRL) to produce probabilistic forecasts of tropical cyclone (TC) track, intensity and structure. All members run with a storm-following inner grid at convection-permitting 4-km horizontal resolution. The COAMPS-TC ensemble is constructed via a combination of perturbations to initial and boundary conditions, the initial vortex, and model physics to account for a variety of different sources of uncertainty that affect track and intensity forecasts. Unlike global model ensembles, which do a reasonable job capturing track uncertainty but not intensity, mesoscale ensembles such as the COAMPS-TC ensemble are necessary to provide a realistic intensity forecast spectrum.The initial and boundary condition perturbations are responsible for generating the majority of track spread at all lead times, as well as the intensity spread from 36-120 h. The vortex and physics perturbations are necessary to produce meaningful spread in the intensity prediction from 0-36 h. In a large sample of forecasts from 2014-2017, the ensemble-mean track and intensity forecast is superior to the unperturbed control forecast at all lead times, demonstrating a clear advantage to running an ensemble versus a deterministic forecast. The spread-skill relationship of the ensemble is also examined, and is found to be very well calibrated for track, but is under-dispersive for intensity. Using a mixture of lateral boundary conditions derived from different global models is found to improve upon the spread-skill score for intensity, but it is hypothesized that additional physics perturbations will be necessary to achieve realistic ensemble spread.

Naval Research Laboratory Multiscale Targeting Guidance for T-PARC and TCS-08

2010 ◽  
Vol 25 (2) ◽  
pp. 526-544 ◽  
Author(s):  
Carolyn A. Reynolds ◽  
James D. Doyle ◽  
Richard M. Hodur ◽  
Hao Jin
Keyword(s):  
Tropical Cyclone ◽  
Research Laboratory ◽  
Large Scale ◽  
Adjoint System ◽  
Horizontal Resolution ◽  
Naval Research Laboratory ◽  
Naval Research ◽  
Prediction System ◽  
Initial State ◽  
The North

Abstract As part of The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) and the Office of Naval Research’s (ONR’s) Tropical Cyclone Structure-08 (TCS-08) experiments, a variety of real-time products were produced at the Naval Research Laboratory during the field campaign that took place from August through early October 2008. In support of the targeted observing objective, large-scale targeting guidance was produced twice daily using singular vectors (SVs) from the Navy Operational Global Atmospheric Prediction System (NOGAPS). These SVs were optimized for fixed regions centered over Guam, Taiwan, Japan, and two regions over the North Pacific east of Japan. During high-interest periods, flow-dependent SVs were also produced. In addition, global ensemble forecasts were produced and were useful for examining the potential downstream impacts of extratropical transitions. For mesoscale models, TC forecasts were produced using a new version of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) developed specifically for tropical cyclone prediction (COAMPS-TC). In addition to the COAMPS-TC forecasts, mesoscale targeted observing products were produced using the COAMPS forecast and adjoint system twice daily, centered on storms of interest, at a 40-km horizontal resolution. These products were produced with 24-, 36-, and 48-h lead times. The nonhydrostatic adjoint system used during T-PARC/TCS-08 contains an exact adjoint to the explicit microphysics. An adaptive response function region was used to target favorable areas for tropical cyclone formation and development. Results indicate that forecasts of tropical cyclones in the western Pacific are very sensitive to the initial state.

Performance of a Dynamic Initialization Scheme in the Coupled Ocean–Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC)

2011 ◽  
Vol 26 (5) ◽  
pp. 650-663 ◽  
Author(s):  
Eric A. Hendricks ◽  
Melinda S. Peng ◽  
Xuyang Ge ◽  
Tim Li
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Initial Conditions ◽  
Layer Structure ◽  
North Pacific Ocean ◽  
Surface Wind ◽  
Naval Research ◽  
Prediction System ◽  
Ocean Atmosphere ◽  
Initialization Scheme

Abstract A dynamic initialization scheme for tropical cyclone structure and intensity in numerical prediction systems is described and tested. The procedure involves the removal of the analyzed vortex and, then, insertion of a new vortex that is dynamically initialized to the observed surface pressure into the numerical model initial conditions. This new vortex has the potential to be more balanced, and to have a more realistic boundary layer structure than by adding synthetic data in the data assimilation procedure to initialize the tropical cyclone in a model. The dynamic initialization scheme was tested on multiple tropical cyclones during 2008 and 2009 in the North Atlantic and western North Pacific Ocean basins using the Naval Research Laboratory’s tropical cyclone version of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS-TC). The use of this initialization procedure yielded significant improvements in intensity forecasts, with no degradation in track performance. Mean absolute errors in the maximum sustained surface wind were reduced by approximately 5 kt for all lead times up to 72 h.

scholarly journals A calibrated and consistent combination of probabilistic forecasts for the exceedance of several precipitation thresholds using neural networks.

2021 ◽  
Author(s):  
Peter Schaumann ◽  
Reinhold Hess ◽  
Martin Rempel ◽  
Ulrich Blahak ◽  
Volker Schmidt
Keyword(s):  
Neural Networks ◽  
Processing System ◽  
Skill Score ◽  
Horizontal Resolution ◽  
Grid Size ◽  
Ensemble Prediction ◽  
Lead Times ◽  
Ensemble Prediction System ◽  
Probabilistic Forecasts ◽  
Precipitation Thresholds

<p>In this talk we present a new statistical method for the seamless combination of two different ensemble precipitation forecasts (Nowcasting and NWP) using neural networks (NNs), see [1]. The method generates probabilistic forecasts for the exceedance of a set of predetermined thresholds (from 0.1mm up to 5mm). The aim of the combination model is to produce seamless and calibrated forecasts which outperform both input forecasts for all lead times and which are consistent regarding the considered thresholds. First, the hyper-parameters of the NNs are chosen according to a certain hyper-parameter optimization algorithm (not to be confused with the training of the NNs itself) on a 3-month dataset (dataset A). Then, the resulting NNs are tested via a rolling origin validation scheme on two 3-month datasets (datasets B & C) with different input forecasts each. Datasets A & B contain forecasts of DWD's RadVOR, a radar-based nowcasting system, and Ensemble-MOS, a post-processing system of NWP ensembles made by COSMO-DE-EPS, with a horizontal resolution of 20km, which is a predecessor of ICON-D2-EPS. Ensemble-MOS forecasts were provided for up to +6h, while RadVOR forecasts were available up to +2h. For dataset C, forecasts with a grid size of 2.2km are used from STEPS-DWD, a new implementation of the Short-term Ensemble Prediction System (STEPS) by  DWD, and ICON-D2-EPS as a NWP ensemble system. Forecasts were made up to +6h. In both validation datasets (B & C), the forecasts show the well-known behavior that the nowcasting systems RadVOR & STEPS are superior for short lead times, while NWP forecasts (Ensemble-MOS & ICON-D2-EPS) outperform these systems for later lead times. Based on the comparison of several validation scores (bias, Brier skill score, reliability and reliability diagram) we can show that the combination is indeed calibrated, consistent and outperforms both input forecasts for all lead times. It should be noted that the combination works on dataset C, although the hyper-parameters were chosen based on dataset A, which contains different forecasts for a different grid size.<br><br>[1] P. Schaumann, R. Hess, M. Rempel, U. Blahak and V. Schmidt, A calibrated and consistent combination of probabilistic forecasts for the exceedance of several precipitation thresholds using neural networks. Weather and Forecasting (in print)</p>

scholarly journals A View of Tropical Cyclones from Above: The Tropical Cyclone Intensity Experiment

2017 ◽  
Vol 98 (10) ◽  
pp. 2113-2134 ◽  
Author(s):  
James D. Doyle ◽  
Jonathan R. Moskaitis ◽  
Joel W. Feldmeier ◽  
Ronald J. Ferek ◽  
Mark Beaubien ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Lower Stratosphere ◽  
Inner Core ◽  
Horizontal Resolution ◽  
Intensity Change ◽  
Naval Research ◽  
Atmospheric Conditions ◽  
Tropical Cyclone Intensity ◽  
High Definition ◽  
Cyclone Intensity

Abstract Tropical cyclone (TC) outflow and its relationship to TC intensity change and structure were investigated in the Office of Naval Research Tropical Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from the innovative new High-Definition Sounding System (HDSS) and remotely sensed observations from the Hurricane Imaging Radiometer (HIRAD), both on board the NASA WB-57 that flew in the lower stratosphere. Three noteworthy hurricanes were intensively observed with unprecedented horizontal resolution: Joaquin in the Atlantic and Marty and Patricia in the eastern North Pacific. Nearly 800 dropsondes were deployed from the WB-57 flight level of ∼60,000 ft (∼18 km), recording atmospheric conditions from the lower stratosphere to the surface, while HIRAD measured the surface winds in a 50-km-wide swath with a horizontal resolution of 2 km. Dropsonde transects with 4–10-km spacing through the inner cores of Hurricanes Patricia, Joaquin, and Marty depict the large horizontal and vertical gradients in winds and thermodynamic properties. An innovative technique utilizing GPS positions of the HDSS reveals the vortex tilt in detail not possible before. In four TCI flights over Joaquin, systematic measurements of a major hurricane’s outflow layer were made at high spatial resolution for the first time. Dropsondes deployed at 4-km intervals as the WB-57 flew over the center of Hurricane Patricia reveal in unprecedented detail the inner-core structure and upper-tropospheric outflow associated with this historic hurricane. Analyses and numerical modeling studies are in progress to understand and predict the complex factors that influenced Joaquin’s and Patricia’s unusual intensity changes.

Extended Prediction of North Indian Ocean Tropical Cyclones

2012 ◽  
Vol 27 (3) ◽  
pp. 757-769 ◽  
Author(s):  
James I. Belanger ◽  
Peter J. Webster ◽  
Judith A. Curry ◽  
Mark T. Jelinek
Keyword(s):  
Tropical Cyclone ◽  
Indian Ocean ◽  
Tropical Cyclones ◽  
North Indian Ocean ◽  
Ensemble Prediction ◽  
Tropical Cyclone Genesis ◽  
Lead Times ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
The North

Abstract This analysis examines the predictability of several key forecasting parameters using the ECMWF Variable Ensemble Prediction System (VarEPS) for tropical cyclones (TCs) in the North Indian Ocean (NIO) including tropical cyclone genesis, pregenesis and postgenesis track and intensity projections, and regional outlooks of tropical cyclone activity for the Arabian Sea and the Bay of Bengal. Based on the evaluation period from 2007 to 2010, the VarEPS TC genesis forecasts demonstrate low false-alarm rates and moderate to high probabilities of detection for lead times of 1–7 days. In addition, VarEPS pregenesis track forecasts on average perform better than VarEPS postgenesis forecasts through 120 h and feature a total track error growth of 41 n mi day−1. VarEPS provides superior postgenesis track forecasts for lead times greater than 12 h compared to other models, including the Met Office global model (UKMET), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Global Forecasting System (GFS), and slightly lower track errors than the Joint Typhoon Warning Center. This paper concludes with a discussion of how VarEPS can provide much of this extended predictability within a probabilistic framework for the region.

Evaluation of Multiple Dynamic Initialization Schemes for Tropical Cyclone Prediction

2013 ◽  
Vol 141 (11) ◽  
pp. 4028-4048 ◽  
Author(s):  
Eric A. Hendricks ◽  
Melinda S. Peng ◽  
Tim Li
Keyword(s):  
Tropical Cyclone ◽  
Three Dimensional ◽  
Equation Model ◽  
Naval Research ◽  
Lead Times ◽  
Second Stage ◽  
The North ◽  
Initialization Scheme ◽  
Prediction Systems ◽  
Tc Prediction

Abstract Three different dynamic initialization schemes for tropical cyclone (TC) prediction in numerical prediction systems are described and evaluated. The first scheme involves the removal of the analyzed vortex, followed by the insertion of a dynamically initialized vortex into the model analyses. This scheme is referred to as the tropical cyclone dynamic initialization scheme (TCDI) because the TC component is nudged to the observed surface pressure in an independent three-dimensional primitive equation model prior to insertion. The second scheme is a 12-h relaxation to the analyses' horizontal momentum before the forecast integration begins, and is called the dynamic initialization (DI) scheme. The third scheme is a combination of the previous two schemes, and is called the two-stage dynamic initialization scheme (TCDI/DI). In the first stage, TCDI is implemented in order to improve the representation of the TC vortex. In the second stage, DI is invoked in order to improve the balance between the inserted TC vortex and its environment. All three dynamic initialization schemes are compared with a control (CNTL) scheme, which creates the initial vortex using synthetic TC observations that match the observed intensity and structure in a three-dimensional variational data assimilation (3DVAR) system. The four schemes are tested on 120 cases in the North Atlantic and western North Pacific basins during 2010 and 2011 using the Naval Research Laboratory's TC prediction model: Coupled Ocean–Atmosphere Mesoscale Prediction System-Tropical Cyclones (COAMPS-TC). It is demonstrated that TCDI/DI performed the best overall with regard to intensity forecasts, reducing the average minimum central pressure error for all lead times by 24.4% compared to the CNTL scheme.

scholarly journals Evaluation of Tropical Cyclone Forecasts in the Next Generation Global Prediction System

2019 ◽  
Vol 147 (9) ◽  
pp. 3409-3428 ◽  
Author(s):  
Jan-Huey Chen ◽  
Shian-Jiann Lin ◽  
Linjiong Zhou ◽  
Xi Chen ◽  
Shannon Rees ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
False Alarm ◽  
Cloud Microphysics ◽  
Lead Times ◽  
Prediction System ◽  
Next Generation ◽  
Microphysics Scheme ◽  
Great Opportunity ◽  
Dynamical Core ◽  
Intensity Prediction

Abstract A new global model using the GFDL nonhydrostatic Finite-Volume Cubed-Sphere Dynamical Core (FV3) coupled to physical parameterizations from the National Centers for Environmental Prediction’s Global Forecast System (NCEP/GFS) was built at GFDL, named fvGFS. The modern dynamical core, FV3, has been selected for the National Oceanic and Atmospheric Administration’s Next Generation Global Prediction System (NGGPS) due to its accuracy, adaptability, and computational efficiency, which brings a great opportunity for the unification of weather and climate prediction systems. The performance of tropical cyclone (TC) forecasts in the 13-km fvGFS is evaluated globally based on 363 daily cases of 10-day forecasts in 2015. Track and intensity errors of TCs in fvGFS are compared to those in the operational GFS. The fvGFS outperforms the GFS in TC intensity prediction for all basins. For TC track prediction, the fvGFS forecasts are substantially better over the northern Atlantic basin and the northern Pacific Ocean than the GFS forecasts. An updated version of the fvGFS with the GFDL 6-category cloud microphysics scheme is also investigated based on the same 363 cases. With this upgraded microphysics scheme, fvGFS shows much improvement in TC intensity prediction over the operational GFS. Besides track and intensity forecasts, the performance of TC genesis forecast is also compared between the fvGFS and operational GFS. In addition to evaluating the hit/false alarm ratios, a novel method is developed to investigate the lengths of TC genesis lead times in the forecasts. Both versions of fvGFS show higher hit ratios, lower false alarm ratios, and longer genesis lead times than those of the GFS model in most of the TC basins.

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