Sensitivity of Typhoon Track Predictions in a Regional Prediction System to Initial and Lateral Boundary Conditions

2009 ◽  
Vol 48 (9) ◽  
pp. 1913-1928 ◽  
Author(s):  
Ling-Feng Hsiao ◽  
Melinda S. Peng ◽  
Der-Song Chen ◽  
Kang-Ning Huang ◽  
Tien-Chiang Yeh
Keyword(s):  
Boundary Conditions ◽  
Initial Conditions ◽  
Forecast Model ◽  
Western Pacific ◽  
Lateral Boundary ◽  
Global Forecast System ◽  
Forecast System ◽  
Lateral Boundary Conditions ◽  
The Western Pacific ◽  
Ncep Global Forecast System

Abstract Tropical cyclone (TC) track predictions from the operational regional nonhydrostatic TC forecast system of the Taiwanese Central Weather Bureau (CWB) are examined for their sensitivities to initial and lateral boundary conditions. Five experiments are designed and discussed, each using a combination of different initial and lateral boundary conditions coming either from the CWB or the National Centers for Environmental Prediction (NCEP) global forecast system. Eight typhoons in the western Pacific Ocean with 51 cases in 2004 and 2005 are tested with the five designed experiments for the 3-day forecast. The average track forecasts are the best when both the initial and lateral boundary conditions are from the NCEP global forecast system. This reflects the generally superior performance of the NCEP global forecast system relative to that of the CWB. Using different lateral boundary conditions has a greater impact on the track than using different initial conditions. Diagnostics using piecewise inversion of potential vorticity perturbations are carried out to identify synoptic features surrounding the featured typhoon that impact the track the most in each experiment. For the two cases demonstrated with the largest track improvement using NCEP global fields, the diagnostics indicate that the prediction of the strength and extent of the subtropical high in the western Pacific plays the major role in affecting these storm tracks. Using the analysis and predictions of the CWB global forecast system as the initial and lateral boundary conditions produces an overintensified subtropical ridge in the regional TC forecast model. Because most of the typhoons studied are located in the southwestern peripheral of the western Pacific subtropical high, the stronger steering from the more intense and extended high system is the main cause of the poleward bias in the predicted typhoon tracks in the operational run, which uses the CWB global forecast fields. The study suggests that, when efforts are made to improve a regional TC forecast model, it is also critically important to improve the global forecast system that provides the lateral boundary and initial conditions to the regional system.

scholarly journals Estimating the Uncertainty in a Regional Climate Model Related to Initial and Lateral Boundary Conditions

2005 ◽  
Vol 18 (7) ◽  
pp. 917-933 ◽  
Author(s):  
Wanli Wu ◽  
Amanda H. Lynch ◽  
Aaron Rivers
Keyword(s):  
Boundary Conditions ◽  
Climate Model ◽  
Initial Conditions ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Regional Model ◽  
Lateral Boundary ◽  
Lateral Boundary Conditions ◽  
The Impact

Abstract There is a growing demand for regional-scale climate predictions and assessments. Quantifying the impacts of uncertainty in initial conditions and lateral boundary forcing data on regional model simulations can potentially add value to the usefulness of regional climate modeling. Results from a regional model depend on the realism of the driving data from either global model outputs or global analyses; therefore, any biases in the driving data will be carried through to the regional model. This study used four popular global analyses and achieved 16 driving datasets by using different interpolation procedures. The spread of the 16 datasets represents a possible range of driving data based on analyses to the regional model. This spread is smaller than typically associated with global climate model realizations of the Arctic climate. Three groups of 16 realizations were conducted using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) in an Arctic domain, varying both initial and lateral boundary conditions, varying lateral boundary forcing only, and varying initial conditions only. The response of monthly mean atmospheric states to the variations in initial and lateral driving data was investigated. Uncertainty in the regional model is induced by the interaction between biases from different sources. Because of the nonlinearity of the problem, contributions from initial and lateral boundary conditions are not additive. For monthly mean atmospheric states, biases in lateral boundary conditions generally contribute more to the overall uncertainty than biases in the initial conditions. The impact of initial condition variations decreases with the simulation length while the impact of variations in lateral boundary forcing shows no clear trend. This suggests that the representativeness of the lateral boundary forcing plays a critical role in long-term regional climate modeling. The extent of impact of the driving data uncertainties on regional climate modeling is variable dependent. For some sensitive variables (e.g., precipitation, boundary layer height), even the interior of the model may be significantly affected.

scholarly journals Cloud-Resolving Ensemble Simulations of Mediterranean Heavy Precipitating Events: Uncertainty on Initial Conditions and Lateral Boundary Conditions

2011 ◽  
Vol 139 (2) ◽  
pp. 403-423 ◽  
Author(s):  
Benoît Vié ◽  
Olivier Nuissier ◽  
Véronique Ducrocq
Keyword(s):  
Boundary Conditions ◽  
Case Studies ◽  
Short Range ◽  
Initial Conditions ◽  
Ensemble Prediction ◽  
Lateral Boundary ◽  
Synoptic Scale ◽  
Lateral Boundary Conditions ◽  
Convective Scale ◽  
The Impact

Abstract This study assesses the impact of uncertainty on convective-scale initial conditions (ICs) and the uncertainty on lateral boundary conditions (LBCs) in cloud-resolving simulations with the Application of Research to Operations at Mesoscale (AROME) model. Special attention is paid to Mediterranean heavy precipitating events (HPEs). The goal is achieved by comparing high-resolution ensembles generated by different methods. First, an ensemble data assimilation technique has been used for assimilation of perturbed observations to generate different convective-scale ICs. Second, three ensembles used LBCs prescribed by the members of a global short-range ensemble prediction system (EPS). All ensembles obtained were then evaluated over 31- and/or 18-day periods, and on 2 specific case studies of HPEs. The ensembles are underdispersive, but both the probabilistic evaluation of their overall performance and the two case studies confirm that they can provide useful probabilistic information for the HPEs considered. The uncertainty on convective-scale ICs is shown to have an impact at short range (under 12 h), and it is strongly dependent on the synoptic-scale context. Specifically, given a marked circulation near the area of interest, the imposed LBCs rapidly overwhelm the initial differences, greatly reducing the spread of the ensemble. The uncertainty on LBCs shows an impact at longer range, as the spread in the coupling global ensemble increases, but it also depends on the synoptic-scale conditions and their predictability.

A Numerical Case Study on the Initiation of the Madden–Julian Oscillation

2009 ◽  
Vol 66 (2) ◽  
pp. 310-331 ◽  
Author(s):  
Pallav Ray ◽  
Chidong Zhang ◽  
Jim Dudhia ◽  
Shuyi S. Chen
Keyword(s):  
Boundary Conditions ◽  
Channel Model ◽  
Initial Conditions ◽  
Lateral Boundary ◽  
Madden Julian Oscillation ◽  
Lateral Boundary Conditions ◽  
Sensitivity Tests ◽  
Global Reanalysis ◽  
Numerical Case Study

Abstract A mesoscale tropical channel model is used to study the long-standing problem of the initiation of the Madden–Julian oscillation (MJO). With initial and lateral boundary conditions provided by a global reanalysis, this model is able to reproduce the initiation and gross features of two observed MJO events up to 2 months after the start of simulations. This leads to a conjecture that these two MJO events are generated by the influences from the lateral boundaries. This conjecture is supported by a series of sensitivity tests. These sensitivity tests demonstrate that the simulated MJO initiation does not critically depend on detailed characteristics of sea surface temperature (varying versus constant in time, mean distribution from boreal spring versus winter), initial conditions (within a 10-day period), the latitudinal location of the lateral boundaries (21°–38°N and S), or even latent heating and moist processes. The only factor found critical to the reproduction of the MJO initiation is time-varying lateral boundary conditions from the reanalysis. When such lateral boundary conditions are replaced by time-independent conditions, the model fails to reproduce the MJO initiation. These results support the idea that extratropical influences can be an efficient mechanism for MJO initiation. Implications of these results are discussed.

scholarly journals Sensitivities of the NCEP Global Forecast System

2019 ◽  
Vol 147 (4) ◽  
pp. 1237-1256 ◽  
Author(s):  
Jih-Wang A. Wang ◽  
Prashant D. Sardeshmukh ◽  
Gilbert P. Compo ◽  
Jeffrey S. Whitaker ◽  
Laura C. Slivinski ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Surface Air Temperature ◽  
Precipitable Water ◽  
Forecast Model ◽  
Forecast Errors ◽  
Global Forecast System ◽  
Forecast System ◽  
Ensemble Forecasts ◽  
Near Surface ◽  
Surface Precipitation

Abstract An important issue in developing a forecast system is its sensitivity to additional observations for improving initial conditions, to the data assimilation (DA) method used, and to improvements in the forecast model. These sensitivities are investigated here for the Global Forecast System (GFS) of the National Centers for Environmental Prediction (NCEP). Four parallel sets of 7-day ensemble forecasts were generated for 100 forecast cases in mid-January to mid-March 2016. The sets differed in their 1) inclusion or exclusion of additional observations collected over the eastern Pacific during the El Niño Rapid Response (ENRR) field campaign, 2) use of a hybrid 4D–EnVar versus a pure EnKF DA method to prepare the initial conditions, and 3) inclusion or exclusion of stochastic parameterizations in the forecast model. The Control forecast set used the ENRR observations, hybrid DA, and stochastic parameterizations. Errors of the ensemble-mean forecasts in this Control set were compared with those in the other sets, with emphasis on the upper-tropospheric geopotential heights and vorticity, midtropospheric vertical velocity, column-integrated precipitable water, near-surface air temperature, and surface precipitation. In general, the forecast errors were found to be only slightly sensitive to the additional ENRR observations, more sensitive to the DA methods, and most sensitive to the inclusion of stochastic parameterizations in the model, which reduced errors globally in all the variables considered except geopotential heights in the tropical upper troposphere. The reduction in precipitation errors, determined with respect to two independent observational datasets, was particularly striking.

scholarly journals Regional Model Nesting within GFS Daily Forecasts Over West Africa

2010 ◽  
Vol 4 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Leonard M. Druyan ◽  
Matthew Fulakeza ◽  
Patrick Lonergan ◽  
Ruben Worrell
Keyword(s):  
West Africa ◽  
Boundary Conditions ◽  
Initial Conditions ◽  
Regional Model ◽  
Precipitation Forecast ◽  
Lateral Boundary ◽  
Systems Research ◽  
Lateral Boundary Conditions ◽  
Realistic Information ◽  
Mean Square Errors

The study uses the RM3, the regional climate model at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies (CCSR/GISS). The paper evaluates 30 48-hour RM3 weather forecasts over West Africa during September 2006 made on a 0.5° grid nested within 1° Global Forecast System (GFS) global forecasts. September 2006 was the Special Observing Period # 3 of the African Monsoon Multidisciplinary Analysis (AMMA). Archived GFS initial conditions and lateral boundary conditions for the simulations from the US National Weather Service, National Oceanographic and Atmospheric Administration were interpolated four times daily. Results for precipitation forecasts are validated against Tropical Rainfall Measurement Mission (TRMM) satellite estimates and data from the Famine Early Warning System (FEWS), which includes rain gauge measurements, and forecasts of circulation are compared to reanalysis 2. Performance statistics for the precipitation forecasts include bias, root-mean-square errors and spatial correlation coefficients. The nested regional model forecasts are compared to GFS forecasts to gauge whether nesting provides additional realistic information. They are also compared to RM3 simulations driven by reanalysis 2, representing “high potential skill” forecasts, to gauge the sensitivity of results to lateral boundary conditions. Nested RM3/GFS forecasts generate excessive moisture advection toward West Africa, which in turn causes prodigious amounts of model precipitation. This problem is corrected by empirical adjustments in the preparation of lateral boundary conditions and initial conditions. The resulting modified simulations improve on the GFS precipitation forecasts, achieving time-space correlations with TRMM of 0.77 on the first day and 0.63 on the second day. One realtime RM3/GFS precipitation forecast made at and posted by the African Centre of Meteorological Application for Development (ACMAD) in Niamey, Niger is shown.

scholarly journals Sensitivity of Tropical Cyclone Idai Simulations to Cumulus Parametrization Schemes

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 932
Author(s):  
Mary-Jane M. Bopape ◽  
Hipolito Cardoso ◽  
Robert S. Plant ◽  
Elelwani Phaduli ◽  
Hector Chikoore ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Boundary Conditions ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Cumulus Parameterization ◽  
Grey Zone ◽  
Lateral Boundary ◽  
Convection Scheme ◽  
Weather System ◽  
Lateral Boundary Conditions

Weather simulations are sensitive to subgrid processes that are parameterized in numerical weather prediction (NWP) models. In this study, we investigated the response of tropical cyclone Idai simulations to different cumulus parameterization schemes using the Weather Research and Forecasting (WRF) model with a 6 km grid length. Seventy-two-hour (00 UTC 13 March to 00 UTC 16 March) simulations were conducted with the New Tiedtke (Tiedtke), New Simplified Arakawa–Schubert (NewSAS), Multi-Scale Kain–Fritsch (MSKF), Grell–Freitas, and the Betts–Miller–Janjic (BMJ) schemes. A simulation for the same event was also conducted with the convection scheme switched off. The twenty-four-hour accumulated rainfall during all three simulated days was generally similar across all six experiments. Larger differences in simulations were found for rainfall events away from the tropical cyclone. When the resolved and convective rainfall are partitioned, it is found that the scale-aware schemes (i.e., Grell–Freitas and MSKF) allow the model to resolve most of the rainfall, while they are less active. Regarding the maximum wind speed, and minimum sea level pressure (MSLP), the scale aware schemes simulate a higher intensity that is similar to the Joint Typhoon Warning Center (JTWC) dataset, however, the timing is more aligned with the Global Forecast System (GFS), which is the model providing initial conditions and time-dependent lateral boundary conditions. Simulations with the convection scheme off were found to be similar to those with the scale-aware schemes. It was found that Tiedtke simulates the location to be farther southwest compared to other schemes, while BMJ simulates the path to be more to the north after landfall. All of the schemes as well as GFS failed to simulate the movement of Idai into Zimbabwe, showing the potential impact of shortcomings on the forcing model. Our study shows that the use of scale aware schemes allows the model to resolve most of the dynamics, resulting in higher weather system intensity in the grey zone. The wrong timing of the peak shows a need to use better performing global models to provide lateral boundary conditions for downscalers.

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