**1.4 Vortex tracking method**

Constructing a suitable vortex-tracking algorithm is a must-have procedure to detect the formation of a newly developed TC center in all ensemble members since their outputs are diverse. A good detection scheme allows one to define and verify the location and the timing of TC formation centers. This step is crucial in every TC formation study, due to the difficulties in capturing the incoherent structure of tropical cyclones at the early genesis stages. More precisely, one cannot apply general criteria such as a midlevel warm-core anomaly, maximum vorticity center for the tropical disturbances as for mature TCs. Instead, the early formation of a tropical depression is often imprinted by the existence of an upper-level cold core and/or a weak surface low pressure rather than a midlevel warm core (see, e.g., [29, 30]). Thus, very few conditions can be practically applied to detect a formation center during the genesis stage. To detect TC formation centers for real-time forecast, a simple scheme has been built upon standard conditions related to the maximum surface wind and the minimum central pressure, as follows:

First, the minimum sea level pressure Pmin within the study area is searched at every model grid point of each ensemble member output at each forecast lead time. Any location with Pmin < 1004 hPa will be noted down as a potential candidate for TC formation location at that forecast lead time for that particular ensemble member.

Second, once a possible location of TC formation is defined, the maximum 10-m wind speed Vmax in an area of 4<sup>0</sup> <sup>4</sup><sup>0</sup> surrounding the minimum pressure center is checked and recorded. A TC formation center will be marked if the condition Vmax ≥ 10 ms<sup>1</sup> is satisfied. It is noteworthy that this value is considerably smaller than the global definition of a tropical depression wind speed (17 ms<sup>1</sup> ), due to the relatively coarse 27/9-km resolution configuration of WRF-LETKF system. Visualizing verification of each TC circulation center detected based on this threshold proves that these criteria can properly identify the center of tropical cyclone like vortex during the genesis stage. Therefore, this threshold for Vmax is used for all genesis analyses. In fact, these criteria of tracking TC formation centers are somewhat intuitive and require further verification. However, this approach is acceptable in evaluating the augmented observational data impacts on TC formation forecasts among ensemble forecasts. As long as the tracking scheme remains certain in all analyses, the comparison of TC formation forecasts should answer the question about the performance of augmented observations in ensemble forecasts.

#### *1.4.1 Example 1*

The WRF-LETKF (WRF V3.6) system has been applied to study the formation of Typhoon Wutip. With target is to evaluate the sensitivity of TC formation forecast to different types of augmented observations. The WRF-LETKF system is designed in such a way that all observations are subject to quality control by the WRF data assimilation (WRFDA) component before used by the LETKF algorithm (More details about the implementation of the WRF-LETKF design can be found in [12, 22]. There is a total of 21 ensemble members was made (due to limited computational and storage resources) and all ensemble experiments are integrated for three days starting from 1200 UTC 23 September, which is approximately 48 h before a tropical depression precursor of Wutip was first reported in the TC vital record at 1200 UTC 25 September. The multiple physical schemes have been used in categorizing among ensemble experiments are 1) two cumulus parameterization schemes including the Betts–Miller–Janjic´ (BMJ) cumulus parameterization and the Kain–Fritsch with shallow convection schemes, 2) three planetary boundary

## *Application of Kalman Filter and Breeding Ensemble Technique to Forecast the Tropical… DOI: http://dx.doi.org/10.5772/intechopen.97783*

layer (PBL) parameterization schemes including the Yonsei University, the Mellor– Yamada–Janjic´, and the simple Medium-Range Forecast (MRF) schemes, 3) three microphysical schemes including the WSM 3 microphysics, the Kessler, and the Lin et al. schemes; and 4) two longwave radiative schemes including the Dudhia and the Goddard schemes for both longwave and shortwave radiations. The cold start cycle is therefore initialized at 0000 UTC 23 September to generate a background ensemble for the first-guess cycle at 1200 UTC 23 September. Afterwards, the subsequent cycles are implemented at every 6 h from 1200 UTC 23 September to 1200 UTC 26 September.

The augmented observational data used in the WRF-LETKF assimilation scheme include two main sources. The first is the satellite data (CIMSS-AMV) derived atmospheric motion vector (AMV) data maintained by the Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin [21, 31–34] due to this data covers a large area where TC genesis may take place. The second source of local augmented observations in the domain of influence to Vietnam's coastal region (DOIV) is also used, including 96 aviation routine weather (METAR) reports from routine scheduled observations, 31 ship/buoy (SHIP/BUOY) station reports, 59 enhanced sounding stations (SOUND), and 404 surface synoptic observations (SYNOP) reports of weather observations during the 0000 UTC 24 September–0000 UTC 27 September period.

Results show critical impacts of the (CIMSS-AMV) data in improving the large – scale environment favorable or hostile to the formation of Typhoon Wutip among ensemble members, which is dynamically controlled by monsoon trough. The results show the optimality of data impacts at cycle 36 h prior to Wutip's observed formation and decrease as forecast cycles are closer to formation period. In contrast, the data assimilation with only surface and local station data proves that these source data are not enough to help describe the strength of monsoon trough due to their scattered distributions (**Figures 1**–**3**).

By choosing Typhoon Wutip as a case study, it was demonstrated that the initial conditions for tropical cyclogeneses in large-scale monsoon trough environment are sensitive to augmented observations. It could allow a range of outcomes for timing and location predictability of TC formation, especially at 36-hr cycle ensemble. Our results could present the importance of augmented observations, especially the

#### **Figure 1.**

*Boxplots of the timing for Wutip formation for three consecutive cycles 1200 UTC 23 Sep, 0000 UTC 24 Sep, and 1200 UTC 24 Sep, corresponding to 48, 36, and 24 h prior to the formation of Wutip depression for (a) the WRF-LETKF, (b) assimilation without the CIMSS-AMV data (NAMV), and (c) the GFS initial data [hereafter to as no data assimilation (NDA) ensemble]. The bold cross denotes the actual time that Wutip first became a tropical depression at 1200 UTC 25 Sep [35].*

#### **Figure 2.**

*Distribution of the location of the Wutip's formation centers as forecast by the WRF-LETKF (triangle), the assimilation without the CIMSS-AMV data ensemble (circle), and no data assimilation ensemble (cross) for (a) 48-, (b) 36-, and (c) 24-h cycles. Color symbols denote the ensemble means of corresponding forecasts [35].*

#### **Figure 3.**

*Ensemble mean distance errors between the forecasted and observed location of Wutip's formation reported at 1200 UTC 25 Sep for three cycles of 48, 36, and 24 h obtained from the WRF-LETKF forecast (black), NDA forecast (stripe), and NAMV forecasts (light shaded) [35].*

satellite AMV data, for the prediction of TC formation at certain lead times that are vital for operational TC forecasts. This case study is typical for TC formation in the WPAC basin, but not representative and may not be applied to other tropical cyclogenesis pathways. While WRF-LETKF has been utilized in forecasting tropical cyclogenesis in the marsupial paradigm of African Easterly Wave [36, 37], it has not been focused in the physical mechanisms of TCs formation in the BIEN DONG basin before. Wutip's formation is strongly rooted in the monsoon trough, as most of the tropical cyclones in the BIEN DONG form within this pattern per year. The performance of WRF-LETKF with augmented observations in this case study has

innovated to the upcoming studies in more properly general examination when designing future observing systems.
