Effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensities
Abstract The background error covariance is an important component in data assimilation systems, which largely dominates the error correlations between different analysis variables. This study aimed to assess the impact of the determination of the background error length and variance scale factors o...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Meteorological Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/met.1820 |
| _version_ | 1797900502165356544 |
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| author | Dongmei Xu Feifei Shen Jinzhong Min |
| author_facet | Dongmei Xu Feifei Shen Jinzhong Min |
| author_sort | Dongmei Xu |
| collection | DOAJ |
| description | Abstract The background error covariance is an important component in data assimilation systems, which largely dominates the error correlations between different analysis variables. This study aimed to assess the impact of the determination of the background error length and variance scale factors on the track and intensity forecast of hurricane systems for radar radial velocity (Vr) data assimilation. To test the sensitivity of the background error length scale and variance scale, multiple data assimilation analyses were performed using a 3D variational data assimilation method with a parameter‐sweeping strategy for the case of Hurricane Ike (2008) by varying the decorrelation length scale (LEN_SCALING) and the variance (VAR_SCALING) of the background error step by step. It is shown that, in radar Vr data assimilation, generally smaller variance scale and length scale factors tend to improve the prediction of the hurricane track. Setting both VAR_SCALING and LEN_SCALING equivalent to 0.4 provides a better track than other combinations. In particular, the impact of the variance scale factor on the track forecasts is larger than that of the length scale factor. There is no direct impact of tuning variance scales and length scales on the forecast intensity for the first few forecast hours. Tuning length scale factors less than 0.4 provides smaller forecast errors of minimum sea level pressure and maximum surface wind with increasing forecast lead time. |
| first_indexed | 2024-04-10T08:47:06Z |
| format | Article |
| id | doaj.art-98c8c1afd2ab40deab8c98fa669363c4 |
| institution | Directory Open Access Journal |
| issn | 1350-4827 1469-8080 |
| language | English |
| last_indexed | 2024-04-10T08:47:06Z |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Meteorological Applications |
| spelling | doaj.art-98c8c1afd2ab40deab8c98fa669363c42023-02-22T07:11:33ZengWileyMeteorological Applications1350-48271469-80802020-01-01271n/an/a10.1002/met.1820Effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensitiesDongmei Xu0Feifei Shen1Jinzhong Min2Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD) Nanjing University of Information Science & Technology Nanjing ChinaKey Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD) Nanjing University of Information Science & Technology Nanjing ChinaKey Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD) Nanjing University of Information Science & Technology Nanjing ChinaAbstract The background error covariance is an important component in data assimilation systems, which largely dominates the error correlations between different analysis variables. This study aimed to assess the impact of the determination of the background error length and variance scale factors on the track and intensity forecast of hurricane systems for radar radial velocity (Vr) data assimilation. To test the sensitivity of the background error length scale and variance scale, multiple data assimilation analyses were performed using a 3D variational data assimilation method with a parameter‐sweeping strategy for the case of Hurricane Ike (2008) by varying the decorrelation length scale (LEN_SCALING) and the variance (VAR_SCALING) of the background error step by step. It is shown that, in radar Vr data assimilation, generally smaller variance scale and length scale factors tend to improve the prediction of the hurricane track. Setting both VAR_SCALING and LEN_SCALING equivalent to 0.4 provides a better track than other combinations. In particular, the impact of the variance scale factor on the track forecasts is larger than that of the length scale factor. There is no direct impact of tuning variance scales and length scales on the forecast intensity for the first few forecast hours. Tuning length scale factors less than 0.4 provides smaller forecast errors of minimum sea level pressure and maximum surface wind with increasing forecast lead time.https://doi.org/10.1002/met.1820background error covarianceDoppler radar dataWRF model |
| spellingShingle | Dongmei Xu Feifei Shen Jinzhong Min Effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensities Meteorological Applications background error covariance Doppler radar data WRF model |
| title | Effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensities |
| title_full | Effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensities |
| title_fullStr | Effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensities |
| title_full_unstemmed | Effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensities |
| title_short | Effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensities |
| title_sort | effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensities |
| topic | background error covariance Doppler radar data WRF model |
| url | https://doi.org/10.1002/met.1820 |
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