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Jan 20, 2015 - simulations associated with ISV include the following: Cyclone Nargis (2008) in the northern Indian Ocean. [Shen et al., 2010; Taniguchi et al., ...
PUBLICATIONS Geophysical Research Letters RESEARCH LETTER 10.1002/2014GL062479 Key Points: • NICAM produces 31 extended-range forecasts in August 2004 • Tropical cyclogenesis is reproduced up to 2 weeks in advance • Predicting modulation of large-scale fields by ISV is needed for TCG forecasts

Supporting Information: • Readme • Figures S1–S3 Correspondence to: M. Nakano, [email protected]

Citation: Nakano, M., M. Sawada, T. Nasuno, and M. Satoh (2015), Intraseasonal variability and tropical cyclogenesis in the western North Pacific simulated by a global nonhydrostatic atmospheric model, Geophys. Res. Lett., 42, 565–571, doi:10.1002/2014GL062479. Received 10 NOV 2014 Accepted 14 DEC 2014 Accepted article online 17 DEC 2014 Published online 20 JAN 2015

Intraseasonal variability and tropical cyclogenesis in the western North Pacific simulated by a global nonhydrostatic atmospheric model Masuo Nakano1, Masahiro Sawada2, Tomoe Nasuno1, and Masaki Satoh1,2 1

Japan Agency for Marine-Earth Science and Technology, Yokohama, Kanagawa, Japan, 2Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Chiba, Japan

Abstract Thirty-one successive daily experiments for extended-range (30 day) forecasts are conducted using a global nonhydrostatic atmospheric model without convective parameterization. The model successfully reproduces tropical cyclogenesis (TCG) in six out of eight cases in the western North Pacific in August 2004, up to 2 weeks prior to cyclone formation. Detailed analyses reveal that Typhoon Songda’s genesis is related to the eastward extension of the monsoon trough associated with the intraseasonal variability (ISV). The successful simulation of the migration and extension of the monsoon trough leads to a 2 week forecast for Songda’s genesis. These findings highlight the need for a model capable of predicting the modulation of large-scale fields by ISV for TCG forecasts and that a global nonhydrostatic cloud-system-resolving model is a promising tool for TCG forecasts. 1. Introduction Since tropical cyclones (TCs) frequently cause tremendous damage to human lives and property, it is important to prevent and mitigate disasters based on accurate predictions of their tracks, intensity, and genesis with enough lead time to take action. Prediction of genesis is particularly needed for inhabitants in low latitudes where TCs are generated. Between June and September 2004, convective activity was modulated by the Madden-Julian oscillation (MJO) [Madden and Julian, 1972] with a period of 60 days. The modulation of convective activity, in turn, modified TC formation in the western North Pacific (WNP) [Nakazawa, 2006]. Convective activity was high in the western North Pacific (WNP) in June and August, and more TCs are generated (five and eight, respectively) than climatological average (1.7 ± 1.2 and 5.9 ± 1.4, respectively, for 1981–2010). On the other hand, convective activity was low in July and September and less TC genesis (TCG) occurred (two and three, respectively) than normal (3.6 ± 1.5 and 4.8 ± 1.4, respectively). It is known that intraseasonal variability (ISV), such as the MJO and the boreal summer intraseasonal oscillation [Wang and Rui, 1990; Wang and Xie, 1997], impacts TC activity [cf. Nakazawa, 1986; Camargo et al., 2009; Wang and Zhou, 2008; Satoh et al., 2012; Yoshida et al., 2014]. This implies that numerical models that can reproduce ISV have potential to successfully simulate TCG under ISV-modulated atmospheric conditions. Successful TCG simulations associated with ISV include the following: Cyclone Nargis (2008) in the northern Indian Ocean [Shen et al., 2010; Taniguchi et al., 2010; Yanase et al., 2010; Fu and Hsu, 2011], TC Isobel (2007) in the southern Indian Ocean [Fudeyasu et al., 2008], and Typhoon Mindulle (2004) in the WNP [Oouchi et al., 2009]. In particular, Fu and Hsu [2011], Fudeyasu et al. [2008], and Oouchi et al. [2009] showed that a TCG associated with ISV can be simulated 2 or 3 weeks in advance.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Predicting high-impact weather in extended-range forecasts (from 2 weeks to 2 months) is desirable for damage mitigation. These studies showed that there may be potential to successfully predict TCG. However, these studies only simulated one TC or used only one initial condition, so the mechanisms that control TCG predictability are not fully understood. Recently, numerical experiments have been conducted with a global nonhydrostatic model to examine TCG [Fudeyasu et al., 2008; Oouchi et al., 2009; Taniguchi et al., 2010; Yanase et al., 2010]. Moreover, the

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K computer, a 10 Peta Floating-point operations per second (FLOPS) supercomputer built in 2012, has enabled us to conduct many extended-range forecast experiments using a global nonhydrostatic model to investigate what determines predictability of TCG. In this study, we examine the predictability of TCG in August 2004, when eight TCs occurred successively in the WNP. We conduct daily 30 day simulations using a global nonhydrostatic model and examine, in particular, the simulation of the relationship between ISV and TCG.

2. Model and Analysis Method 2.1. Model Experiments and Data Used for Validation This study uses the 2012 version of the Nonhydrostatic Icosahedral Atmospheric Model (NICAM.12) [Tomita and Satoh, 2004; Satoh et al., 2008, 2014]. The global horizontal grid interval is approximately 14 km. There are 38 vertical layers, and the upper boundary of the model is located at 36.7 km. Since recent numerical studies show that ISV is better simulated if convective parameterization is excluded for a mesh size of around 10 km [Holloway et al., 2013] and sensitivity experiments to the horizontal mesh size indicate that the 14 km mesh model shows much better performance of reproducing frequency of daily precipitation amounts than that of the 28 km mesh model (Figure S1 in the supporting information) and Miyakawa et al. [2014] showed a good MJO forecast skill using the 14 km mesh model, moist processes are calculated by the NICAM Single-moment Water 6 cloud microphysics scheme [Tomita, 2008] without any convective parameterization. Longwave and shortwave radiation transfer is calculated using the broadband radiative transfer code named mstrnX [Sekiguchi and Nakajima, 2008]. Planetary boundary layer processes are calculated using the Mellor-YamadaNakanishi-Niino level 2 scheme [Nakanishi and Niino, 2004; Noda et al., 2010]. The initial atmospheric conditions are derived from the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) data [Dee et al., 2011] by linear interpolation. Any TC bogus schemes are not used in ERA-Interim data and NICAM simulations. Initial sea surface temperature (SST) is also from ERA-Interim data, and SST is forecast using a slab ocean model, and then nudged to have a persistent SST anomaly at the initial time with daily climatological SST from 30 year (1980–2009) ERA-Interim data with an e-folding time of 7 days. Therefore, except for the initial conditions, no SST observations are input to the model. The model is initialized at 0000 UTC each day in August 2004 and integrated for 30 days. Each integration takes 13 h of computing time using 640 nodes (0.4%) of the K computer. We use the Japanese 25 year Reanalysis (JRA-25) [Onogi et al., 2007] for observed atmospheric fields, along with the National Oceanic and Atmospheric Administration interpolated outgoing longwave radiation (OLR) data [Liebmann and Smith, 1996]. The International Best Track Archive for Climate Stewardship (IBTrACS v03r03) [Knapp et al., 2010] is used for validation of the TCG forecast. 2.2. Tracking of Tropical Storms and Validation Method We categorize a storm as a TC in the simulations if it meets the following criteria over at least 36 h [Oouchi et al., 2006]: (i) 10 m wind speed is greater than 17.5 m s 1, (ii) the sum of the temperature anomaly at 700 hPa, 500 hPa, and 300 hPa is greater than 2 K, (iii) the maximum relative vorticity at 850 hPa is greater than 3.5 × 10 5 s 1, and (iv) wind speed at 850 hPa is greater than that at 200 hPa. We validate simulated TCG as follows. First, we select a simulated disturbance that (i) passed within 10° of the closest position of an observed TCG location within ±1 day and (ii) meets the criteria described above within ±5 days of the genesis time of the observed TC. Second, if the disturbance meets the TC criteria within ±1 day of the genesis time of the observed TC, we judge the TCG forecast to be a “hit.” If the disturbance meets the TC criteria outside +1 day ( 1 day) of the genesis time of the observed TC, we judge the TCG forecast to be successful, but the timing to be “late” (“early”). If there is no simulated disturbance that corresponds to the observed TC, we judge the observed TC to be “missed.” Any simulated TCs that do not meet these criteria are classified as “false alarms.”

3. Results 3.1. TC Genesis Forecast for Eight TCs Table 1 shows the validation results of the TCG forecasts. The model successfully reproduces five TCGs in the WNP in almost all the experiments initialized before their geneses, with a low missing (M) rate. The weak TCs,

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Geophysical Research Letters Table 1. Validation Summary of Tropical Cyclogenesis Forecasts Name Genesis Time (dd/hh) Maximum Intensity (hPa) Lifetime (Days) Genesis Longitude Genesis Latitude 0801 0802 0803 0804 0805 0806 0807 0808 0809 0810 0811 0812 0813 0814 0815 0816 0817 0818 0819 0820 0821 0822 0823 0824 0825 0826 0827 0828 0829 0830 0831

10.1002/2014GL062479

a

MALOU

MERANTI

RANANIM

MALAKAS

MEGI

CHABA

AERE

SONGDA

4/00 996 0.875

4/12 960 4.75

8/12 950 4.5

11/00 990 2.75

16/06 970 4.125

19/12 910 11.75

20/00 955 6.25

28/00 925 11

137.6°E 29.9°N

165.3°E 23.7°N

130.3°E 18.2°N

158.5°E 26.5°N

130.8°E 18.8°N

160.4°E 13.1°N

136.0°E 14.3°N

165.0°E 11.3°N

1–10

11–20

21–30

Total

M M M XM N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

H H H H X XM XM XM XM N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

H M H E E E H L XM X X XM N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

M M E E E M M M M M XM XM XM N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

M L E E E E E E M E E E E E H H XM XM XM XM N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

H M H H M E M M E M H E M L L L L L L X X X X X X X X X X XM XM

E M M E H H M M L M E M E E E E E E H X X X X X XM XM N/A N/A N/A N/A N/A

M M M E M M H M M E M E L M M M E E E H H H M E H H L X X X X

1 3 1 0 3 1 2 3 2 3 2 4 2 2 1 3 0 0 0 1 1 2 2 3 1 3 3 5 1 2 1

1 1 3 0 2 1 2 2 1 3 1 2 0 0 1 0 0 2 1 0 1 2 0 0 1 1 0 2 2 1 0

1 0 0 0 1 0 0 2 1 0 1 0 0 0 0 0 1 1 0 1 1 1 0 1 1 1 0 1 1 1 0

3 4 4 0 6 2 4 7 4 6 4 6 2 2 2 3 1 3 1 2 3 5 2 4 3 5 3 8 4 4 1

False Alarms Forecast Time (Days)

a

The letters M, H, E, and L denote miss, hit, early genesis, and late genesis, respectively. The letter X indicates that a typhoon existed at the initial date, and XM indicates that a typhoon existed at the initial date, but it did not meet tropical cyclone criteria. N/A indicates that a simulation started after the lysis time for the typhoon. The last four columns show the number of false alarms for each 10 day forecast time and total, respectively.

Malou and Malakas, are the exceptions. The northward migration of convection in August and suppressed phase in September associated with ISV in the WNP (i.e., 120–150°E), as seen in observation [Nakazawa, 2006], is also well simulated (Figure S2). Typhoon Songda’s genesis is well reproduced in the experiments initialized after 12 August (about 2 weeks before its genesis) with a low missing (M) rate but not in the experiments initialized 3 weeks before. Detailed analysis of Songda’s genesis is presented in the next subsection. The last four columns of Table 1 show the number of false alarms in each simulation. The number of false alarms decreases in forecast time; 1.9, 1.1, and 0.5 false alarms occurred during the first 10 day, the latter 10 day, and the last 10 day simulations, respectively. The average number of false alarms throughout the 30 day simulations is 3.5 ± 1.8. The geneses of Rananim, Megi, and Aere, are simulated earlier (E) than observed. This may be due to the relatively coarse horizontal resolution of the model as discussed later. Meanwhile, Rananim is generated late in the experiment initialized on 8 August, just 12 h before Rananim’s genesis. Chaba is also generated late in the experiments initialized after 14 August. The validation results also show that the forecasts sometimes “jump.” For example, Chaba is generated in the experiment initialized on 1 August but missed in the experiment initialized on 2 August since no vortex is

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Figure 1. Observed and ensemble mean of 10 day mean OLR (green contour) and zonal wind at 850 hPa (color shading) averaged during (a) 1–10 August, (b, d) 11–20 August, and (c, e, f) 21–30 August 2004, respectively. Figure 1d (Figure 1b) shows NICAM simulation initialized from 5 (12) to 11 (18) August, respectively. 2 2 Black crosses in Figure 1a indicate the locations of tropical cyclogenesis. OLR values less than 200 W m are shown with contour intervals of 20 W m . Broken lines depict the shear line.

simulated around observed Chaba’s genesis location. In the experiment initialized on 5, 7, 8, and 10 August, a vortex is simulated around observed Chaba’s genesis location. The vortex, however, reaches TC criteria more than 5 days before observed Chaba’s genesis time. Therefore, the simulated vortex is not judged as Chaba and is counted as a false alarm. In the experiment initialized on 13 August, a vortex is simulated around observed Chaba’s location, but the vortex does not intensify to a TC. False alarms due to early development may relate to the relatively coarse horizontal mesh size used in the present study. Figure S1 shows that the frequency of the simulated daily precipitation amounts with different horizontal mesh sizes. The 14 km mesh NICAM overestimate the frequency of heavy precipitation in the WNP. It indicates that intensity of convection is overestimated. Therefore, coupling between vortices and convection may be also overestimated, resulting in the rapid spin-up of the incipient vortex when deep convection is initiated near the vortex. Sensitivity experiments show that a finer mesh model (e.g., 7 km mesh) is able to simulate the frequency of daily precipitation amounts. The finer mesh model should simulate coupling between vortices and convection, resulting in better simulation of TCGs. The weak TCs (Malou and Malakas) were not successfully reproduced in the model experiments. Malou’s genesis is not reproduced by any of the experiments. Malakas’s genesis is reproduced in the experiments initialized on 3–5 August (about 1 week before its genesis), but its genesis cannot be reproduced in experiments initialized after 6 August. These two TCs were generated in relatively high latitudes (north of 26°N); the minimum central pressure never deepened to less than 990 hPa, and their lifetime was less than 3 days. The simulations miss TCs in some cases which already existed at the initial time due to lack of appropriate representation of TCs in the initial conditions. 3.2. Relationship Between the Forecasts of Songda and the Monsoon Trough In the WNP, TCs are often generated in the so-called shear line, where the meridional shear of zonal wind occurs. This zone is associated with the monsoon trough and confluent zone of monsoonal southwesterly

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and trade winds [Ritchie and Holland, 1999]. As Nakazawa [2006] pointed out, the monsoon trough in the WNP was mature in terms of relative vorticity in August 2004, and it is therefore useful to investigate the relationship between the monsoon trough forecast and the predictability of Songda’s genesis.

Figure 2. Results of experiments that predict 3 day (25–27 August 2004) mean westerly wind, initialized during (a) 5–11 August, (b) 12–18 August, and (c) 19–25 August. The color shading indicates the number of experiments (out of a maximum of seven) that successfully predict mean westerly wind. The black contour shows zonal wind speeds of zero derived from JRA-25. The black open circles show the observed genesis location of Typhoon Songda, and the black broken circles have radii of 10° from these locations. The blue letters H, E, and L show the simulated genesis location of Typhoon Songda, classified as hit, early genesis, and late genesis locations, respectively.

Figures 1a–1c show observed 10 day mean OLR and zonal wind at 850 hPa. This shows active convection at 12°N, between 120°E and 140°E, which is oriented northwest-southeast between 140°E and 160°E in early August (Figure 1a). The shear line associated with the monsoon trough is located about 20°N, which is north of active convection and extends eastward up to 155°E. In mid-August (Figure 1b), active convection between 140°E and 160°E becomes west-east oriented and extends eastward to 170°E. The shear line associated with the eastward extension of active convection also extends to 170°E. In late August (Figure 1c), active convection still has a line shape structure that extends to 165°E, but this has migrated north about 5°, and the shear line extends farther east to 175°E.

Next, we examine the relationship between observed convective regions, the monsoon trough, and TCG locations. Five of the eight TCs are generated in the active convective region. Aside from Typhoon Songda, they tend to form on the northern edge of the convective region (Figure 1c), which is consistent with the findings of Camargo et al. [2009]. In addition, five of the eight TCs are generated near the shear line. Thus, the eastward extension of the shear line is closely related to Songda’s genesis, which occurred in the central Pacific near the shear line (165.0°E, 11.3°N; Figure 1c).

What is the relationship between the eastward extension of the shear line and Songda’s genesis in simulations? Convective activity and the shear line associated with the monsoon trough in mid-August are well reproduced in simulations initialized 3 weeks before Songda’s genesis (5–11 August, Figure 1d), but convective activity weakens and the shear line retreats in late August (Figure 1e). On the other hand, convective activity and the shear line in late August are well reproduced in simulations initialized 2 weeks before Songda’s genesis (12–18 August, Figure 1f). Sensitivity experiments of horizontal resolution show that location and west-east orientation of the shear line are well reproduced even in 28 km mesh model without convective parameterization. In the coarser resolution models, the shear line shifted northward and it becomes northwest-southeast oriented (Figure S3). Figure 2 illustrates the number of experiments (out of a total of seven in each case) that successfully simulate 3 day average (25–27 August) westerly winds at different lead times. The observed westerly (black line) extends east of the date line (175°W) through south of Songda’s genesis location. In the experiments

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initialized about 3 weeks before Songda’s genesis (Figure 2a), only one experiment simulates westerly winds near Songda’s genesis location and only two experiments simulate Songda’s genesis. With later initialization dates, the number of experiments that capture the westerly winds near Songda’s genesis location increases to four (seven) for experiments initialized about 2 (1) weeks in advance, respectively (Figures 2b and 2c). The simulations also reproduce the timing of Songda’s genesis but with varying success depending on the timing of the initialization. No experiments initialized 2 weeks in advance capture the timing of genesis, but four experiments initialized about 1 week in advance reproduce the timing successfully. For the position of cyclogenesis, two and five experiments initialized about 2 weeks and 1 week in advance, respectively, generate the location of Songda’s genesis to within 10°. These results indicate that the eastward extension of the shear line is closely related to Songda’s genesis, and if models reproduce the longitudinal evolution of the monsoon trough, the associated TC genesis will also be effectively simulated.

4. Summary and Discussion In this study, we investigate the predictability of TCG in the WNP in August 2004 by conducting daily forecast experiments for extended-range (30 day) time periods using a global nonhydrostatic atmospheric model (NICAM). Eight TCs were generated over this month, and the northward migration of active convection associated with ISV was observed. The ISV and TCGs are successfully simulated for six TCs with central pressures less than 990 hPa. It is also shown that the eastward extension of the shear line associated with the monsoon trough in an active period of the ISV is closely related to Typhoon Songda’s genesis. The evolution of the monsoon trough was simulated approximately 2 weeks before Songda’s genesis, and this led to a successful reproduction of this event. Taniguchi et al. [2010], Yanase et al. [2010], and Fu and Hsu [2011] showed that reproducing the northward migration of monsoon circulation leads to the simulation of Cyclone Nargis’s (2008) genesis in the northern Indian Ocean. Oouchi et al. [2009] showed similar results for Typhoon Mindulle’s (2004) genesis in the WNP. In this study, we show that reproducing the eastward extension of monsoon circulation results in the simulation of Typhoon Songda’s genesis. In 2004, typical El Niño Modoki conditions were observed, with above-average SST in the central Pacific [Ashok et al., 2007]. This may also facilitate the Songda’s genesis. As it is thought that the relationship between ISV and TCG depends on large-scale conditions in a particular year, it is not clear whether the findings of this study are applicable to the other TCGs. More case studies are required to deepen the understanding of the mechanisms between TCG and ISV, particularly for extended-range forecasts of TCG. The importance of producing extended-range forecasts of high-impact weather is increasing, and there is a high priority given to understanding the mechanisms and predictability of these weather systems [Vitart et al., 2012]. Results of this study suggest that reproducing large-scale circulation modulated by ISV (e.g., the monsoon trough) lead to accurate TCG forecasts. As also shown by Satoh et al. [2012], these results highlight the promise of a global nonhydrostatic model, such as NICAM in predicting ISV. Acknowledgments This work was supported by HPCI Strategic Programs Field 3 of the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan. All numerical simulations are conducted on the K computer in the RIKEN Advanced Institute for Computational Science (proposal hp120313 and hp130010). All figures were produced using the GFD-DENNOU library (http://www.gfd-dennou.org/). The Editor thanks two anonymous reviewers for their assistance in evaluating this paper.

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Geophysical Research Letters

10.1002/2014GL062479

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