scholarly journals Assimilation of Himawari-8 Imager Radiance Data with the WRF-3DVAR system for the prediction of Typhoon Soulder

2020 ◽  
Author(s):  
Dongmei Xu ◽  
Aiqing Shu ◽  
Zhankui Zhang

Abstract. Himawari-8 is a new generation geostationary meteorological satellite launched by Japan Meteorological Agency (JMA). It carries the Advanced Himawari imager (AHI) onboard, which can continuously monitor high-impact weather events with high frequency space and time. The assimilation of AHI was implemented with the framework of the mesoscale numerical model WRF and its three-dimensional variational assimilation system (3DVAR) for the analysis and prediction of typhoon Soudelor in the Pacific Typhoon season in 2015. The effective assimilation of AHI Imager data in tropical cyclone with rapid intensify development has been realized. The results show that after assimilating the AHI imager data under clear sky conditions, the typhoon position in the background field in the model is effectively corrected compared with the control experiment without AHI data. It is found that assimilation of AHI imager data is able to improve the analyses of the water vapor and wind in typhoon inner-core region. The analyses and forecast of the typhoon minimum sea level pressure, the maximum near-surface wind speed, and the typhoon track are further improved.

2021 ◽  
Vol 21 (5) ◽  
pp. 1569-1582
Author(s):  
Feifei Shen ◽  
Aiqing Shu ◽  
Hong Li ◽  
Dongmei Xu ◽  
Jinzhong Min

Abstract. Himawari-8 is a next-generation geostationary meteorological satellite launched by the Japan Meteorological Agency. It carries the Advanced Himawari Imager (AHI) on board, which can continuously monitor high-impact weather events with high frequency in space and time. The assimilation of AHI radiance data was implemented with the three-dimensional variational data assimilation system (3DVAR) of the Weather Research and Forecasting Model for the analysis and prediction of Typhoon Soudelor (2015) in the Pacific typhoon season. The effective assimilation of AHI radiance data in improving the forecast of the tropical cyclone during its rapid intensification has been realized. The results show that, after assimilating the AHI radiance data under clear-sky conditions, the typhoon position in the background field of the model was effectively corrected compared with the control experiment without AHI radiance data assimilation. It is found that the assimilation of AHI radiance data is able to improve the analyses of the water vapor and wind in a typhoon's inner-core region. The analyses and forecasts of the minimum sea level pressure, the maximum surface wind, and the track of the typhoon are further improved.


2008 ◽  
Vol 136 (8) ◽  
pp. 3168-3192 ◽  
Author(s):  
Juliane Schwendike ◽  
Jeffrey D. Kepert

Abstract This paper describes the boundary layer wind structure and dynamics of Hurricanes Danielle (1998) and Isabel (2003), based on the analysis of high-resolution global positioning system dropwindsonde data and simulation of the flow by a three-dimensional boundary layer model produced by Kepert and Wang. The observations show that the hurricane boundary layer has a complex three-dimensional structure with large variability over small distances. The analysis emphasizes three aspects: the degree of gradient-wind balance, the radially varying depth of the boundary layer, and the strength of the near-surface wind speed relative to that at a higher level. Each aspect is compared both with results obtained in a simulation of the individual storm by Kepert and Wang’s model and with theoretical predictions. The observations show that the boundary layer depth decreases toward the center of the storm, consistent with theoretical arguments. The strongest azimuthal winds occur near the top of, but still within, the frictional inflow layer. These strong azimuthal winds are marginally supergradient in Hurricane Danielle but strongly so in Hurricane Isabel, where the imbalance amounts to approximately 10 m s−1 near the radius of maximum winds and is statistically significantly nonzero. This layer of supergradient flow is surmounted by a layer of outflow, in which the flow returns to gradient balance. The maximum storm-relative azimuthal wind occurs in the left front of Hurricane Danielle, and the strongest inflow is located in the right front. These asymmetries rotate anticyclonically with height, but there is also a clear wavenumber-2 asymmetry superimposed, which shows less rotation with height and is possibly forced by environmental factors associated with the storm’s impending recurvature. In Hurricane Isabel, the azimuthal wind maximum is located in the left rear and the inflow maximum in the left front, with neither showing much tendency to vary in azimuth with height. The ratio of the near-surface wind speed to that farther aloft increases toward the storm center for both storms. The largest values are located near the radius of maximum wind, and in general higher values are found on the left of the storm’s track than on the right. Simulations of the two storms with the boundary layer model are able to explain several of these factors; they also show some ability to reproduce individual dropsonde wind observed profiles. Important is that the model predicts weakly supergradient flow in Danielle and strongly supergradient flow in Isabel, in excellent agreement with the observational analysis. Based on these simulations, physical arguments, and earlier studies, the authors conclude that the differences between these storms in this respect result from their differing radial profiles of gradient wind and argue that the occurrence of supergradient flow in the upper boundary layer of individual hurricanes should be readily predictable.


2020 ◽  
Vol 33 (10) ◽  
pp. 4027-4043 ◽  
Author(s):  
Xu Dong ◽  
Yetang Wang ◽  
Shugui Hou ◽  
Minghu Ding ◽  
Baoling Yin ◽  
...  

AbstractNear-surface wind speed observations from 30 manned meteorological stations and 26 automatic weather stations over the Antarctic Ice Sheet are used to examine the robustness of wind speed climatology in six recent global reanalysis products: the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), the Japan Meteorological Agency 55-Year Reanalysis (JRA-55), the Climate Forecast System Reanalysis (CFSR), the National Centers for Environmental Prediction–U.S. Department of Energy (DOE) Reanalysis 2 (NCEP2), and the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) and fifth-generation reanalysis (ERA5). Their skills for representing near-surface wind speeds vary by season, with better performance in summer than in winter. At the regional scale, all reanalysis datasets perform more poorly for the magnitude, but better for their year-to-year changes in wind regimes in the escarpment than the coastal and plateau regions. By comparison, ERA5 has the best performance for the monthly averaged wind speed magnitude and the interannual variability of the near-surface wind speed from 1979 onward. Intercomparison exhibits high and significant correlations for annual and seasonal wind speed Antarctic-wide averages from different datasets during their overlapping timespans (1980–2018), despite some regional disagreements between the different reanalyses. Furthermore, all of the reanalyses show positive trends of the annual and summer wind speeds for the 1980–2018 period, which are linked with positive polarity of the southern annular mode.


2014 ◽  
Vol 599-601 ◽  
pp. 1605-1609 ◽  
Author(s):  
Ming Zeng ◽  
Zhan Xie Wu ◽  
Qing Hao Meng ◽  
Jing Hai Li ◽  
Shu Gen Ma

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.


Author(s):  
David A. Schecter

Abstract A cloud resolving model is used to examine the intensification of tilted tropical cyclones from depression to hurricane strength over relatively cool and warm oceans under idealized conditions where environmental vertical wind shear has become minimal. Variation of the SST does not substantially change the time-averaged relationship between tilt and the radial length scale of the inner core, or between tilt and the azimuthal distribution of precipitation during the hurricane formation period (HFP). By contrast, for systems having similar structural parameters, the HFP lengthens superlinearly in association with a decline of the precipitation rate as the SST decreases from 30 to 26 °C. In many simulations, hurricane formation progresses from a phase of slow or neutral intensification to fast spinup. The transition to fast spinup occurs after the magnitudes of tilt and convective asymmetry drop below certain SST-dependent levels following an alignment process explained in an earlier paper. For reasons examined herein, the alignment coincides with enhancements of lower–middle tropospheric relative humidity and lower tropospheric CAPE inward of the radius of maximum surface wind speed rm. Such moist-thermodynamic modifications appear to facilitate initiation of the faster mode of intensification, which involves contraction of rm and the characteristic radius of deep convection. The mean transitional values of the tilt magnitude and lower–middle tropospheric relative humidity for SSTs of 28-30 °C are respectively higher and lower than their counterparts at 26 °C. Greater magnitudes of the surface enthalpy flux and core deep-layer CAPE found at the higher SSTs plausibly compensate for less complete alignment and core humidification at the transition time.


2016 ◽  
Vol 33 (7) ◽  
pp. 1363-1375 ◽  
Author(s):  
Sungwook Hong ◽  
Hwa-Jeong Seo ◽  
Young-Joo Kwon

AbstractThis study proposes a sea surface wind speed retrieval algorithm (the Hong wind speed algorithm) for use in rainy and rain-free conditions. It uses a combination of satellite-observed microwave brightness temperatures, sea surface temperatures, and horizontally polarized surface reflectivities from the fast Radiative Transfer for TOVS (RTTOV), and surface and atmospheric profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF). Regression relationships between satellite-observed brightness temperature and satellite-simulated brightness temperatures, satellite-simulated brightness temperatures, rough surface reflectivities, and between sea surface roughness and sea surface wind speed are derived from the Advanced Microwave Scanning Radiometer 2 (AMSR-2). Validation results of sea surface wind speed between the proposed algorithm and the Tropical Atmosphere Ocean (TAO) data show that the estimated bias and RMSE for AMSR-2 6.925- and 10.65-GHz bands are 0.09 and 1.13 m s−1, and −0.52 and 1.21 m s−1, respectively. Typhoon intensities such as the current intensity (CI) number, maximum wind speed, and minimum pressure level based on the proposed technique (the Hong technique) are compared with best-track data from the Japan Meteorological Agency (JMA), the Joint Typhoon Warning Center (JTWC), and the Cooperative Institute for Mesoscale Meteorological Studies (CIMSS) for 13 typhoons that occurred in the northeastern Pacific Ocean throughout 2012. Although the results show good agreement for low- and medium-range typhoon intensities, the discrepancy increases with typhoon intensity. Consequently, this study provides a useful retrieval algorithm for estimating sea surface wind speed, even during rainy conditions, and for analyzing characteristics of tropical cyclones.


Urban Climate ◽  
2020 ◽  
Vol 34 ◽  
pp. 100703
Author(s):  
Yonghong Liu ◽  
Yongming Xu ◽  
Fangmin Zhang ◽  
Wenjun Shu

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 738 ◽  
Author(s):  
Wenqing Xu ◽  
Like Ning ◽  
Yong Luo

With the large-scale development of wind energy, wind power forecasting plays a key role in power dispatching in the electric power grid, as well as in the operation and maintenance of wind farms. The most important technology for wind power forecasting is forecasting wind speed. The current mainstream methods for wind speed forecasting involve the combination of mesoscale numerical meteorological models with a post-processing system. Our work uses the WRF model to obtain the numerical weather forecast and the gradient boosting decision tree (GBDT) algorithm to improve the near-surface wind speed post-processing results of the numerical weather model. We calculate the feature importance of GBDT in order to find out which feature most affects the post-processing wind speed results. The results show that, after using about 300 features at different height and pressure layers, the GBDT algorithm can output more accurate wind speed forecasts than the original WRF results and other post-processing models like decision tree regression (DTR) and multi-layer perceptron regression (MLPR). Using GBDT, the root mean square error (RMSE) of wind speed can be reduced from 2.7–3.5 m/s in the original WRF result by 1–1.5 m/s, which is better than DTR and MLPR. While the index of agreement (IA) can be improved by 0.10–0.20, correlation coefficient be improved by 0.10–0.18, Nash–Sutcliffe efficiency coefficient (NSE) be improved by −0.06–0.6. It also can be found that the feature which most affects the GBDT results is the near-surface wind speed. Other variables, such as forecast month, forecast time, and temperature, also affect the GBDT results.


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