Simulation of Typhoon Muifa Using a Mesoscale Coupled Atmosphere

Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133 DOI: 10.1007/s13131-014-0561-z http://www.hyxb.org.cn E-mail: [email protected]

Simulation of Typhoon Muifa using a mesoscale coupled atmosphere–ocean model SUN Minghua1,2,3, DUAN Yihong1*, ZHU Jianrong4, WU Hui4, ZHANG Jin3, HUANG Wei5 1 Chinese Academy of Meteorological Sciences, Beijing 100081, China 2 University of Chinese Academy of Sciences, Beijing 100049, China 3 National Meteorological Center, Beijing 100081, China 4 State Key Laboratory of Estuary and Coastal, East China Normal University, Shanghai 200062, China 5 Shanghai Typhoon Institute of China Meteorological Administration, Shanghai 200030, China

Received 25 March 2013; accepted 23 October 2013

©The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg 2014

Abstract A mesoscale coupled atmosphere–ocean model has been developed based on the GRAPES (Global and Re- gional Assimilation and Prediction System) regional typhoon model (GRAPES_TYM) and ECOM-si (estuary, coast and ocean model (semi-implicit)). Coupling between the typhoon and ocean models was conducted by exchanging wind stress, heat, moisture fluxes, and sea surface temperatures (SSTs) using the coupler OASIS3.0. Numerical prediction experiments were run with and without coupling for the case of Typhoon Muifa in the western North Pacific. To investigate the impact of using more accurate SST information on the simulation of the track and the intensity of Typhoon Muifa, experiments were also conducted using increased SST resolution in the initial condition field of the control test. The results indicate that increasing SST resolution in the initial condition field somewhat improved the intensity forecast, and use of the coupled model improved the intensity forecast significantly, with mean absolute errors in maximum wind speed within 48 and 72 h reduced by 32% and 20%, respectively. Use of the coupled model also resulted in less pronounced over-prediction of the intensity of Typhoon Muifa by the GRAPES_TYM. Moreover, the effects of using the coupled model on the intensity varied throughout the different stages of the development of Muifa owing to changes in the oceanic mixed layer depth. The coupled model had pronounced effects during the later stage of Muifa but had no obvious effects during the earlier stage. The SSTs predicted by the coupled model decreased by about 5–6°C at most after the typhoon passed, in agreement with satellite data. Furthermore, based on analysis on the sea surface heat flux, wet static energy of the boundary layer, atmospheric temperature, and precipitation forecasted by the coupled model and the control test, the simulation results of this coupled atmosphere–ocean model can be considered to reasonably reflect the primary mechanisms underlying the interactions between tropical cyclones and oceans. Key words: coupled atmosphere-ocean model, GRAPES, ECOM-si, TC intensity, SST Citation: Sun Minghua, Duan Yihong, Zhu Jianrong, Wu Hui, Zhang Jin, Huang Wei. 2014. Simulation of Typhoon Muifa using a mesoscale coupled atmosphere–ocean model. Acta Oceanologica Sinica, 33(11): 123–133, doi: 10.1007/s13131-014-0561-z

1 Introduction been developed to simulate the interactions between tropical During the last two decades, little improvement has been cyclones and oceans; these models offer potentially significant achieved in the skill of predicting TC intensity changes, despite improvements in the prediction of tropical cyclone intensity. steady improvements in tropical cyclone (TC) track forecast- To date, in addition to idealized studies, a large number of ing. An obvious disadvantage of using numerical models in numerical simulations and forecast studies have been conduct- the forecasting of TC intensity is that the interactions between ed based on real TC cases and adopting coupled atmosphere– tropical cyclones and oceans and their effects on TC intensity ocean models (Bender et al., 1993; Shade and Emanuel, 1999; remain poorly understood. Most typhoon models that are cur- Chan et al., 2001; Ginis, 2002). For instance, Emanuel (1999) ap- rently in use assume sea surface temperature (SST) conditions plied a simple coupled atmosphere–ocean model including one to remain fixed over time. However, many observational and axisymmetric typhoon model and one one-dimensional ocean numerical studies have confirmed that important positive and model to simulate several historic hurricanes in the Atlantic negative feedback mechanisms exist in the tropical cyclone– Ocean, including hurricanes Hugo, Andrew, and Opal. The re- ocean system and that SSTs are sensitive to the intensity of TCs sults indicated that consideration of SST negative feedback (Chang and Madala, 1980; Price, 1981; Emanuel, 1986). Thus, mechanisms improved the forecasting of TC intensity signifi- uncoupled atmospheric models that exclude some description cantly and that TC intensity in the model was very sensitive to of the above-mentioned processes exhibit only limited ability to the thermal structure of the upper ocean. However, some of the simulate and forecast TC intensity. To address this issue, three- model runs of Emanuel (1999) resulted in failed forecasts, likely dimensional coupled atmosphere–ocean models have recently owing to the use of climatological ocean data. Furthermore, the

Foundation item: The National Basic Research and Development Program (973 Program) of China under contract No. 2009CB421506; the National Natural Science Foundation of China under contract No. 40975035; China Meteorological Administration GRAPES Research Fund. *Corresponding author, E-mail: [email protected] 124 SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133

applicability of the axisymmetric model is limited for cases in coupled atmosphere–ocean model covering the western North which the vertical wind shear effect or dynamic interactions Pacific area has been established based on the GRAPES_TYM with other weather systems play an important role in tropical and the regional oceanic general circulation model ECOM-si. In cyclone evolution. Bender and Ginis (2000) studied the effects particular, numerical prediction experiments were conducted of tropical cyclone–ocean interactions by coupling the Geo- for the entirety of Typhoon Muifa (typhoon number 1109) us- physical Fluid Dynamics Laboratory (GFDL) hurricane model ing both the coupled and uncoupled models. Section 2 intro- with a high-resolution Princeton Ocean Model(POM) and con- duces the establishment and initialization of the coupled atmo- ducted prediction experiments for hurricanes Opal and Gilbert sphere–ocean model. Section 3 describes typhoon conditions, (Gulf of Mexico) and Felix and Fran (West Atlantic). The results experimental methods, and data sources. Section 4 analyzes the indicated that significant cooling of the sea surface induced by experimental results and discusses the effects of atmosphere– coupling interactions resulted in a substantial decrease in the ocean coupling on the intensity forecast for Muifa. Finally, the evaporation and wet static energy of the boundary layer over conclusions and discussions are presented in Section 5. the cold wake; this had a considerable effect on storm intensity, particularly for slow-moving storms. Bender and Ginis (2000) 2 Introduction to the coupled atmosphere–ocean model also conducted sensitivity experiments to demonstrate that the wake of Hurricane Edouard greatly impacted the intensity 2.1 Outline of the atmospheric model of Hurricane Fran when crossing or passing near to its wake. The atmospheric model used in this study is the regional These results demonstrate the crucial role of accurate initial typhoon model, which was configured with a horizontal reso- SST analysis in improving intensity forecasts based on dynami- lution of 0.15° and has 31 vertical layers. The time step of the cal models. In each of the seven forecasts Bender et al. made, model integration was set to 120 s. The model physics include the inclusion of ocean coupling typically produced substantial the following: the simplified Arakawa–Schubert cumulus pa- improvements in the prediction of storm intensity but had little rameterization; a WSM-6 scheme for microphysical process; influence on track forecasts. Similarly, hurricane prediction ex- the YSU scheme for parameterization of boundary layer pro- periments using the United States’ GFDL coupled atmosphere– cesses; the RRTM scheme for parameterization of longwave ocean numerical model (Bender et al., 2007) indicated that the radiation processes; the Goddard scheme for parameterization coupled model could improve forecasts of hurricane intensity, of shortwave radiation processes; and the SLAB/thermal diffu- and the results of real runs for 163 cases that occurred during sion scheme for land surface process. All parameter settings are the 1995–1998 hurricane seasons demonstrated that use of a the same as those for the current operational model, although coupled atmosphere–ocean model that incorporate oceanic the model domain is slightly smaller in the new model (0°–45°N, feedback could reduce the error in forecasts of hurricane in- 100°–160°E) than in the operational model (0°–51°N, 90°–170°E). tensity by 26%, on average (Ginis et al., 1999). The application The GRAPES_TYM uses a new vortex initialization scheme of coupled atmosphere–wave–ocean models has also been in- developed with a synthetic vortex described by a nonlinear bal- vestigated recently. For example, Chen et al. (2007) applied an ance model (Wang, 1995) combined with the typhoon isolation atmosphere–wave–ocean model to study the effects of SST and technique of GFDL (Kurihara et al., 1993, 1995). The tangential ocean waves on hurricane evolution. However, research into wind of the synthetic vortex is distributed as follows: the effects of surface waves on tropical cyclone intensity is still in its early stages, and such processes have rarely been included r VrT (,σ ) =×Vm  in operational models. rm

The GRAPES_TYM is a mesoscale typhoon model developed bb   by the Numerical Prediction Center of China Meteorological 11r rr− m r0 exp1−− exp1−× Administration based on GRAPES_MESO Version 3.3 (Xue and brrr− br m0mm Chen, 2008), which was put into operation in July 2012. Accord- ing to verifications of typhoon track and intensity forecasts dur- ð sinσ rr< 0 , ing 2008–2011, the errors in the forecasts of both mean track 2 (1) and intensity in the GRAPES_TYM are smaller than those in the operational T213 global typhoon model, although the in- VT (rr,)σ = 0 ≥ r0 , tensity forecast has shown a stronger tendency than the observations. Wada (2007) concluded that overestimation of the where, Vm is the maximum wind at the surface, rm is the radius speed of intensification in simulations could be attributed in of the maximum wind, r is the radius from the vortex center, part to uncertainty in the physical schemes incorporated into r0=1 000 km is the maximum radius that can be affected by the these sophisticated models and that overestimation of inten- vortex, and b is a parameter determining the horizontal shape sity at later stages of the integrations may be associated with of the wind profile. The vertical profile of the tangential wind is model representations of tropical cyclone–ocean interaction. given as a sine function of σ. Wang et al. (2012) previously coupled the GRAPES mesoscale In addition, the parameterization scheme for the drag coef- model with an oceanic mixed layer model (OMLM) and con- ficient presented by Moon et al. (2007) has been applied to the ducted numerical simulation of Typhoon Chanchu; the results GRAPES regional typhoon model to improve the calculation of indicated that the coupled model could simulate the primary the sea surface drag coefficient during strong winds. physical processes producing the typhoon weather and of- fered considerable improvements in the simulation of intensity 2.2 Outline of the ocean model with respect to the uncoupled model, while also improving the The regional oceanic general circulation model used in simulation of typhoon track. In the present study, a mesoscale this study is based on ECOM-si (Blumberg, 1994). ECOM-si SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133 125

is a three-dimensional estuary–ocean model developed from munication between models components, and interpolation POM (Blumberg and Mellor, 1987). The POM level equation between atmospheric and oceanic fluxes. Under the control of adopts both internal and external model splitting for calcula- OASIS3, two-way exchange between the physical parameters of tion, whereas the ECOM-si level equation adopts an implicit the ground layer of the typhoon model and the surface of the expression for calculation. Moreover, the ECOM-si model uses ocean model was conducted every 360 s. The ocean model ob- spherical coordinates, nests with a 2.5-order turbulence closure tained sea surface wind stress, solar shortwave radiation flux, model, and provides vertical viscosity and diffusion coefficients sensible heat flux, latent heat flux, net long wave radiation flux, of turbulence (Galperin et al., 1988; Mellor and Yamada, 1982). and vapor flux, which were computed in the typhoon model. Chen et al. (2001) improved the model by introducing nonor- The new SST calculated by the ocean model was then used in thogonal coordinates, using the “Arakawa C” grid difference the typhoon model, with a constant SST applied outside the scheme for calculation. Further improvements in the calcula- coupling area. tion of the baroclinic pressure gradient force and the advection scheme were made by Zhu and Zhu (2003) and Wu and Zhu 3 Experimental design (2010), respectively. On this basis, the model can now better simulate changes in oceanic circulation and thermohaline dis- 3.1 Introduction to typhoon case tribution. Typhoon Muifa was generated over the western North Pacif- For the atmosphere–ocean coupled model, SST forecast is ic at 14:00 on July 28, 2011 (Beijing time) and first moved north- the most important component of the ocean model. The pres- ward before turning westward at night on August 2 and con- ent study improved the vertical σ-coordinate by transforming tinuing directly north along China’s coastal areas. The typhoon it to the stretched coordinate (S-coordinate) to refine the near- finally landed in the coastal area to the northwest of North Ko- surface layers, thus enabling the ocean model to better simulate rea, where it weakened and disappeared in Northeast China. the surface flow field and temperature (Shen et al., 2012) and Since its formation on July 28, the intensity of Muifa developed simultaneously fitting the terrain on the bottom layer. rapidly to produce a super typhoon at night on July 30, subse- The calculation domain of the ocean model is slightly quently weakening to a severe typhoon at 14:00 on August 1. smaller than that for the atmospheric model: it has a horizon- The maximum wind speed reached grade 18 (65 m/s) when ty- tal resolution of 0.25° and 21 layers in the vertical direction, phoon intensity was greatest, and the intensity was maintained and the time step of the model integration is set to 180 s. Wa- such that a severe typhoon or typhoon was sustained until 14:00 ter depth data were interpolated to grids at a resolution of 1'× on August 7, after which time the intensity weakened gradually. 1'. The main purpose of the present study is the investigation Figure 1 illustrates the changes in the track and intensity of Mui- of general circulation at the sea surface and sea surface tem- fa based on information derived from the CMA–STI best track peratures; thus, the maximum water depth was set to 1 000 m. dataset for tropical cyclones (www.typhoon.gov.cn). The 12-monthly sea surface temperatures of the section simulated by the ocean model agree well with the measured data; in 3.2 Design of forecasting experiments particular, the equatorial current and strong western boundary In the present study, numerical prediction contrast tests current (Kuroshio) have previously been simulated successfully were conducted for the entirety of Typhoon Muifa. These ex- by the model (Shen et al., 2010) periments can be divided into three groups. (1) The control To demonstrate the true oceanic initial state as precisely as forecast test for the GRAPES typhoon model does not consider possible in the coupled atmosphere–ocean model, the oceanic interactions between the sea and the atmosphere; this test is numerical model requires accurate and reasonable initial con- referred to as uncoupled_1 (control test). Where possible, the dition , including temperature, salinity, sea surface height, ve- parameters and physical processes of uncoupled_1 were set to locity distribution, and so on. For the model used in the present be consistent with those of the existing operational typhoon study, the initialization scheme for ECOM-si first applies high- model, although the calculation domain of the control forecast precision sea surface temperature, salinity, flow velocity, and was slightly smaller. (2) The forecast test of the GRAPES_TYM sea surface height obtained from the analysis products of the replaced the NCEP 1°×1° SST data provided by the original back- global Hybrid Coordinate Ocean Model (HYCOM) and interpo- ground fields with 0.25°×0.25° SST data obtained from AVHRR lates into the ECOM-si model domain, thus providing the initial and AMSR-E satellite data. SSTs were held constant during this field and boundary conditions for 30 days prior to the arrival forecast, which is referred to as uncoupled_2 test. (3) The fore- of the typhoon. Then, the ocean model is driven by the wind cast test of the coupled atmosphere–ocean model considered field, heat flux, and other factors (with values obtained from the interactions between the sea and the atmosphere based on the NCEP FNAL data) four times daily to calculate one month uncoupled_1 and is referred to as the coupled test. prior to occurrence of the typhoon. This allows dynamical ad- The uncoupled_2 experiment was conducted because the justment to occur and enables the model to reach steady state; resolution of the NCEP 1°×1° SST analysis data is too low to thus, the model can be considered to include a realistic oceanic describe SSTs well at the mesoscale, particularly for the tem- initial state that persists until the initiation of forecasting by the perature decreases that occur at the sea surface after typhoons coupled model. have passed: because all the three group tests consider continuous forecasts, the initial SST data in the background field will 2.3 Process of atmosphere–ocean coupling likely deviate from the observed data considerably for the later Two-way coupling of the GRAPES_TYM and the ECOM- forecast test of Muifa in uncoupled_1 test. Thus, uncoupled_2 si model has been realized previously via the coupler OASIS3 experiment was added to examine the influence of the atmo- (CERFACS) (Valcke, 2006; Valcke, 2013). This coupler is used spheric model on track and intensity forecasts with respect to primarily to control the running of the coupled model, com- mesoscale SST information in the initial field. 126 SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133

105° 111°117° 123° 129° 135° E 70 1 020 45° ab N 60 1 000 40°

−1 980 s 50 35° 960 40 30° 940 30 25° 920 20 900 20°

Maxmum wind speed/m∙ 10 880 Minimum sea surface pressure/hPa 15° Vmax MSLP 0 860 10° Jul.27 00:00 Jul.30 18:00 Aug.3 12:00 Aug.7 06:00 Time (UTC)

Fig.1. Changes in track (a) and intensity (b) of Typhoon Muifa. Vmax denotes the maximum wind speed and MLSP the minium sea surface pressure.

The forecast period covered from July 28 to August 7, 2011, the resolution of the SST data and introducing the mesoscale and the model made two 72-h forecasts each day. In total, the coupled model acted primarily to change the mesoscale char- three groups of experiments obtained 21 forecasts of 24-h, 19 acteristics of the air and sea. Neither of these methods resulted forecasts of 48-h, and 17 forecasts of 72-h. in any obvious improvements in the forecast of typhoon track, which is consistent with the results of previous studies (e.g., 3.3 Data Bender and Ginis, 2000). The initial and lateral boundary conditions of the typhoon model corresponded to those of the NCEP global forecast sys- 4.2 Intensity forecast tem data. The typhoon data used to build a bogus vortex were According to the general average errors for intensity fore- real-time typhoon location data from the forecaster at the Na- casts (Figs 2a and b), the coupled test performed better than tional Meteorological Center of CMA. The typhoon observa- both the uncoupled_1 and uncoupled_2 tests: compared to the tion data used to verify the forecasts of the model were from uncoupled_1 test, the mean absolute error in central pressure the CMA-STI Best Track Dataset for Tropical Cyclones (on www. (maximum wind speed) for 24-h, 48-h, and 72-h forecasts was typhoon.gov.cn). SST analysis data from the AVHRR and AMSR- reduced by about 29% (30%), 31% (32%), and 32% (20%), respec- E satellites (NCEP) were used for comparison with the model tively. Moreover, the data demonstrate that any improvements forecasts. in the intensity forecast produced by the coupled test were not evident within the initial 12 h of the simulation; rather, these improvements increased gradually after this initial period. 4 Results Based on the forecasts for the different period of the typhoon, the control test performs relatively well in predicting 4.1 Track forecast intensity in the earlier stages of the development of Muifa, but Table 1 presents the average track forecast errors of Typhoon produces overdevelopment in the later stage. The forecasted Muifa for all three groups. In general, all three groups displayed values predicted by the uncoupled_1 and coupled tests were a similar ability to forecast the track of Muifa. The forecast of compared with the observed values for the same time period uncoupled_1 indicated that the typhoon track adopted a west- to produce scatterplots (Figs 3a and b). It is clear that the inten- ward trend after 00UTC on August 4 and predicted that Typhoon sity values predicted by the control test are greater than those Muifa would land on mainland China, in contrast to the actual observed. However, when typhoon intensity is very strong (i.e., track, where Muifa moved directly northward. The uncoupled_2 maximum wind speed greater than 50 m/s), the predicted in- and coupled tests exhibited slight improvements in track fore- tensity is relatively weak, possibly owing to the relatively low casting (compared to uncoupled_1) in the initial stage of the resolution and imperfect physical parameterizations used. The typhoon, although some deviation from the observed track was coupled model overpredicted the intensity of Typhoon Muifa to still simulated in these experiments. The ability of these mod- a lesser degree than the uncoupled models. els to forecast the typhoon’s track appeared to depend primar- The forecast tests initiated from 00:00UTC on July 30 and ily on the large-scale environmental field; however, increasing August 5, 2011 were applied to compare the abilities of three groups of tests in simulating intensity during two different stages in the development of the typhoon. The test initiated at Table 1. Tracking errors of Typhoon Muifa in different forecast- 00:00UTC on July 30 represented the stage in which intensity ing models developed rapidly, during which time the typhoon was locat- Uncoupled_1 Uncoupled_2 Coupled ed primarily over the sea to the west of the Philippine Islands 24 h 68.06 68.64 69.45 and the Bashi Channel and moved very slowly (i.e., at speeds 48 h 178.90 181.09 175.87 of only 10–15 km/h); in contrast, the test initiated at 00:00UTC 72 h 317.71 321.67 323.91 on August 5 represented the stage in which intensity weakened SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133 127

slowly, during which time the typhoon was located primarily sity reaching a maximum level corresponding to that of a su- over the East China and Yellow Seas and moved relatively fast per typhoon. It is clear that all three groups of tests predicted (i.e., with a speed of 30 km/h). Figure 4a illustrates changes in this trend very well, although they underestimated the speed of the maximum wind speed of Muifa within 72 h of 00:00UTC on the strengthening in the earlier stage. It can also be seen that July 30. The observed data indicate that Muifa first intensified the maximum wind speeds of the uncoupled_2 and coupled before weakening and leveling out within 72 h, with the inten- tests differ only slightly from those of uncoupled_1, with wind

30 10

a uncoupled_1 25 uncoupled_2 −1

s 8 coupled 20 6 15 4 10 uncoupled_1

Maxmum wind speed/m∙ 2 5 uncoupled_2

Minimum sea surface pressure/hP abcoupled 0 0 0 12 24 36 48 60 72 0 12 24 36 48 60 72 Forecast time/h Forecast time/h

Fig.2. Time series of Typhoon Muifa intensity; mean error in the uncoupled_1 forecast (solid line), uncoupled_2 forecast (dotted- dashed line) and coupled experiment (dashed line). a. Mean error in minimum sea level pressure, and b. mean error in maximum wind speed.

70 70 ab 60 60 −1 −1 s s 50 50

40 40

30 30 0 h 0 h 24 h 20 24 h 20

Forecast wind speed/m∙ Forecast wind speed/m∙ 48 h 10 48 h 10 72 h 72 h 0 0 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 Observation/m∙s−1 Observation/m∙s−1

Fig.3. Distribution of the forecast maximum wind speed vs. observed wind speed of Typhoon Muifa in the uncoupled_1 experiment (a) and the coupled experiment (b).

70 70 ab

−1 60 −1 60 s s

50 50

40 40

30 30

20 observation 20 observation coupled coupled Maxmum wind speed/m∙ Maxmum wind speed/m∙ 10 uncoupled_1 10 uncoupled_1 uncoupled_2 uncoupled_2 0 0 0 6 12 18 24 30 36 42 48 54 60 66 72 0 6 12 18 24 30 36 42 48 54 60 66 72 Forecast time/h Forecast time/h

Fig.4. Forecasted time series of Typhoon Muifa maximum wind speed; uncoupled_1 experiment (green), uncoupled_2 experiment (purple) and coupled experiment (red). The best-track values (black) are also plotted for comparison. a. Initial time 00 UTC 30 Jul., 2011 initial time, and b. initial time 00:00UTC 5 Aug. 2011. 128 SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133

speed reductions of about 5 m/s at most, which indicates that coupling were more pronounced. However, the intensities pre- the introduction of the initial SST and coupled model has no dicted for the two stages were similar, suggesting that TC inten- obvious effect on the intensity forecast for the period from July sity and speed are not the primary factors controlling the extent 30 to August 2. Figure 5b illustrates changes in the intensity of of the effects of atmosphere–ocean coupling. Thus, the depth of Muifa within 72 h of 00:00UTC on August 5, during which time the mixing layer may be the primary controlling factor in this Muifa was weakening slowly. The uncoupled_1 test predicted regard; this will be analyzed further below. that the typhoon would first intensify and then weaken, and The results demonstrate that uncoupled_2 was able to im- over predictions are apparent for the whole period. The coupled prove the intensity forecast somewhat with respect to that of test predicted that the typhoon would first stabilize and then the control test. In particular, it was able to reflect the SST de- weaken, and the intensity values predicted by this model agree crease that resulted from interactions between the typhoon and well with those observed; such results reflect the negative feed- the ocean at the initial time by increasing the resolution of the back mechanisms by which typhoons change in response to initial SST data used; this implies that this method enables the SST change. In contrast to the period that started on July 30, the model to partially consider the interactions between sea and atmosphere–ocean coupling has a more obvious effect in this atmosphere. later period: maximum wind speed decreased by up to 11 m/s and the central pressure is reduced by 14 hPa. 4.3 SST decrease caused by Typhoon Muifa Preliminary research findings have shown that the extent to As the lower boundary condition of the atmospheric model which sea–atmosphere interactions affect TC intensity depends used here, SST can be considered the most appropriate param- primarily on TC intensity, TC speed, and the depth of the mixing eter for assessing the performance of the ocean and coupled layer (Ginis, 2002). The models in the present study predicted models. The observations indicate that tropical cyclones could that Muifa moved slowly in its earlier stages, when the effects lead to SST decreases of 1–6°C (Black, 1983); such decreases are of atmosphere-ocean coupling were unclear, but moved much likely to have been a primary cause of changes in TC intensity. faster in its later stages, when the effects of atmosphere–ocean However, the single atmospheric model does not include this

105° 111°117° 123° 129° 135° E 105° 111°117° 123° 129° 135° E 42° 42° N N ab33 33 32 32 36° 36° 31 31 30 30 29 29 30° 30° 28 28 27 27 26 26 SST/° C 24° 24° SST/° C 25 25 24 24 23 18° 18° 23 22 22 21 21 12° 20 12° 20

105° 111°117° 123° 129° 135° E 105° 111°117° 123° 129° 135° E 42° 42° N N c 33 d 33 32 32 36° 36° 31 31 30 30 29 29 30° 30° 28 28 27 27 26 26 24° SST/° C 24° SST/° C 25 25 24 24 18° 23 18° 23 22 22 21 21 12° 20 12° 20

Fig.5. The SST distribution before and after the passing of Typhoon Muifa. a. SST analysis distribution used by uncoupled_1 model, beginning at 00:00UTC 5 Aug. 2011, b. cyclone track from 00:00UTC 28 Jul. to 00:00UTC 5 Aug. 2011 superimposed on SST (AVHRR + AMSR-E) at 00:00UTC 5 Aug., forecasted by the uncoupled_2 model, c. cyclone track from 00:00UTC 5–8 Aug. 2011 superimposed on SST (AVHRR + AMSR-E) at 00:00UTC 8 Aug., and d. 72 h: cyclone forecast track superimposed on the SST beginning at 00:00UTC 5 Aug. 2011, forecasted by the coupled model. SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133 129

important effect. To remedy this omission, we will now alter the over the sea for a significant period. SST during the predicted periods (beginning 00:00UTC on Au- The SST analyzed from the satellite data and the observed gust 5 and July 30), and conduct further analyses. 72 h track, as well as the 72 h forecast SST and the predicted Figure 5a shows the constant SST data used in the uncou- track, are shown in Figs 5c and d, respectively; Fig. 6a shows the pled_1 test beginning at 00:00UTC on August 5. The resolution distribution of SST decrease analyzed from the satellite data of the SST data is 1°×1°. Figure 5b shows the observed track and and the observed track, while Fig. 6b shows the forecasted SST the SST satellite data at higher resolution (0.25°×0.25°), which decrease and the track predicted by the coupled test within also constitutes the more precise SST data used in the un- the same period. From observations, it is known that the sur- coupled_2 test. By 00:00UTC on August 5, Typhoon Muifa had face temperatures of the Yellow Sea and the East China Sea de- moved over the sea for about 8 days. During this time, the en- creased along the typhoon track. Since the mixing layers of both trainment effect had conveyed deep-layer cold sea water up to seas are very shallow, cold sea waters easily convey to the sea the surface, forming an obvious channel of decreased SST, espe- surface. The maximum SST decrease (up to 5–6°C in the eastern cially at the right sides of the TC track. The SST “cold pool” was East China Sea) occurred at the radius of maximum wind speed. not visible in Fig. 5a because of the low resolution; consequent- The temperature drop along the typhoon track is clearly asym- ly, the typhoon intensity was overestimated in the uncoupled_1 metric, being higher at the right side than at the left. According test while the intensity forecast is improved in the uncoupled_2 to the forecast of the coupled test, the SST should decrease to test. Bender and Ginis (2000) analyzed a TC passing through the varying extent along the moving track of the typhoon, drop- cold wake flow formed by another TC, and concluded that the ping by about 3–4°C within 48 h and by 5–6°C within 72 h. Since intensity forecast of the model was unambiguously improved the forecasted track is slightly west of the observed track, the when the cold wake flow was considered. The results of the main domain of decreased SST appears at the right side of the current study further indicate that including the SST decrease forecasted track. The SST distribution predicted by the coupled generated by the TC in the earlier stages could affect the subse- model is much closer to the observations than that predicted by quent intensity forecast, especially when the TCs have moved the uncoupled model, implying that the coupled model could

116° 120° 124° 128° 132° E 116° 120° 124° 128° 132° E

ab 40° 40° N 4 N 4 3 3 36° 2 36° 2 1 1 −1 −1 32° 32° −2 −2

−3 cooling/°C −3 cooling/°C

28° −4 SST 28° −4 SST −5 −5 −6 −6 24° 24° −7 −7

20° 20° 105° 111°117° 123° 129° 135° E 105° 111°117° 123° 129° 135° E 42° 42° N c N d 4 4 36° 36° 3 3 2 2 30° 1 30° 1 −1 −1 −2 −2

24° −3 cooling/°C 24° −3 cooling/°C

−4 SST −4 SST −5 −5 18° 18° −6 −6 −7 −7 12° 12°

Fig.6. Distribution of SST cooling after passing by Typhoon Muifa. a. Cyclone track superimposed on SST cooling (AVHRR + AMSR- E) during 5–8 Aug. 2011, b. coupled model forecasts at 72 h: cyclone track superimposed on SST cooling beginning at 00:00UTC 5 Aug. 2011. c. cyclone track superimposed on SST cooling (AVHRR + AMSR-E) from 30 Jul. to 2 Aug. 2011, and d. coupled model forecasts at 72 h: cyclone track superimposed on SST cooling beginning at 00:00UTC 30 Jul. 2011. 130 SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133

better forecast the SST change during Typhoon Muifa and also In Eq. (2), ρh and Th denote the density and temperature of improve the forecasting of typhoon intensity. sea water, respectively, in each layer, Cp is the specific heat at For comparison, the forecasted SST decreases throughout constant pressure, and Zh is the thickness of each layer. the event starting at 00:00UTC on July 30 were also analyzed. The TCHP is largely responsible for changes in TC intensity Figure 6c shows the distribution of SST decrease analyzed from (Shay et al., 2000). If the TC passes through seas of high TCHP the satellite data and the observed track, and Fig. 6d shows the under favorable atmospheric conditions, its intensity will in- SST decrease and forecasted track of the coupled model with- crease. The depth of the 26°C Isotherm, as well as the TCHP in the same period. This test was conducted during the ear- distribution in the Yellow Sea and East China Sea before and lier formation stage of Typhoon Muifa. Though Muifa moved after Muifa, was calculated from the coupled model. Figure 8 slowly during this period, the mixing layer of the underlying shows the changes in the depth of the 26°C Isotherm close to sea was much deeper and unfavorable for the upturn of colder the typhoon center within 72 h from 00:00UTC on August 5, sea water to the surface; consequently, the SST decreases by a 2011. In this area, the water and the depth of the 26°C isotherm mere 1–2°C. The domain of the SST decrease predicted by the are both shallow. The depth of the 26°C Isotherm of the sea area coupled model coincides with the satellite observations. The surrounding the typhoon center reduces after 72 h, indicating non-obvious SST drops are consistent with the little intensity that both the surface and subsurface of the sea become colder. changes predicted by the coupled and uncoupled models. This phenomenon is attributable to entrainment of the upper sea layers by the strong TC wind. The upper and lower layers 4.4 Heat flux exchanges at the air-sea interface are mixed, colder sea water is conveyed from the lower layer The sensible and latent heat fluxes transmitted to the at- toward the surface, and the temperature of the upper layer de- mosphere from the sea are important in the development and creases. Figure 9 shows the changes in TCHP at 72 h forecasted maintenance of the TC. The heat flux changes in the coupled by the coupled model. Figures 8 and 9 show similar changes in model and the control test were analyzed using the forecast the depth of the 26°C isotherm and the TCHP calculated by the process with obvious atmosphere-ocean coupling effects start- model. Prior to the typhoon, the TCHP of the Yellow Sea and East ing at 00:00UTC on August 5. Compared with the uncoupled_1 China Sea typhoon is moderately low. Thus, the oceanic ther- test (Fig. 7), the sensible and latent heat fluxes of the coupled modynamic conditions are unfavorable for further strengthen- test are reduced by a maximum of 75 W/m2 and 300 W/m2, re- ing the typhoon, and the TCHP considerably reduces once the spectively, within 48 h, and by a maximum of 75 and 200 W/m2 typhoon has passed. Typhoon development is suppressed by within 72 h. Thus, the latent heat flux is much more sensitive the reduction of upward heat flux from the sea. to SST than the sensible heat flux. The reductions in both heat Xu et al. (2011), who analyzed the changing intensity of Mui- fluxes are related to the SST decrease, which reduces the up- fa, pointed out that the vertical shear of Muifa’s environmen- ward heat flux at the sea surface and suppresses the typhoon tal wind gradually increased. Especially after Muifa had shifted intensity predicted by the model. to the East China Sea, the vertical shear of the environmental In recent years, researchers have recognized that TC inten- wind remained strong. Moreover, the reduced moisture in the sity also depends on the vertical temperature profile of the sea air prevented the intensity from strengthening. The analysis of subsurface. Indeed, an important relationship exists between the current study revealed that once Muifa had entered the East the tropical cyclone heat potential (TCHP) and cyclone intensi- China Sea, both the atmospheric and the oceanic conditions ty. The TCHP depends on the incremental heat capacities of sea were unfavorable for continuous intensity strengthening. water between the surface and the depth of the 26°C isotherm, and is defined as follows (Leipper and Volgenau, 1972): 4.5 Changes in main atmospheric factors The decreased SST caused by a TC reduces the sensible and H latent heat fluxes transmitted from the sea to the atmosphere. Q=ρ CT −∆26 Z . (2) TCHP ∑ hp( h ) h Such heat flux reduction decreases the wet static energy of the h=0

116° 120° 124° 128° 132° E 116° 120° 124° 128° 132° E 40° 40° N N ab150 400 125 300 36° 100 36°

−2 200

75 −2 m 50 100 m 32° 25 32° −100 −25 −200 −50 −300 28° −75 28° −400 −100 −500 Latent heat fulx/W∙

−125 Sensible heat fulx/W∙ −600 −150 24° 24° −700 −275 −800 −200 20° 20°

Fig.7. Differences in heat flux calculated by the coupled and uncoupled_1 experiments beginning at 00:00UTC 5 Aug. 2011. a. Sensible heat flux (W/m2), and b. latent heat flux (W/m2). SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133 131

boundary layer that is crucial to developing and maintaining coupled test than in the uncoupled_1 test, implying that cou- the TC (Bender and Ginis, 2000). Figure 11 displays the changes pling weakens the warm-core structure of the typhoon center in the ground equivalent potential temperature predicted by the and thereby reduces typhoon intensity. coupled and uncoupled models started at 00:00UCT on August The reduced heat flux transmitted upward from the sea 5. After 48 h, the equivalent potential temperature predicted by inhibits the ascending motion and vapor, thus weakening the the coupled test was several degrees lower than that predicted convective precipitation. In this research, the convective pre- by the uncoupled_1 test in some areas, and the reduction in cipitation at 72 h predicted by the coupled test (at most 80 mm) the typhoon core area was most obvious at 7 K. Therefore, the is significantly less than that forecasted by the uncoupled_1 coupled ocean makes an obvious contribution to the supply of test. The non-convective precipitation irregularly increases and wet static energy. decreases. The distribution pattern of overall precipitation ac- In the coupled model, the decreased SST reduces the up- cumulated within 72 h (see Fig. 12) is similar in the coupled and ward heat flux across the atmosphere-ocean interface. Conse- uncoupled tests, although the coupled model restricts the ac- quently, the heat and temperature of the lower atmospheric lay- cumulated precipitation to 150 mm at most over the East China er decrease. Eventually, this decrease is conveyed to the higher Sea. atmospheric layer. Corresponding to the domain of decreased SST, the temperature at 2 m predicted by the Coupled model is 5 Conclusions 2–3°C lower than that of the uncoupled_1 test after 72 h. Ana- An atmosphere–ocean model was developed for the west- lyzing the vertical atmospheric temperature profile, the atmo- ern North Pacific area, in which the GRAPES_TYM was coupled spheric temperature from the lower to the higher levels in the with the ECOM-si ocean model. The forecasting performance typhoon center is also 1–2°C lower in the coupled than in the of the model was assessed by numerical prediction experiments uncoupled model. From Fig. 10, the vertical temperature gradi- of the entire progress of No. 1109 Typhoon Muifa. The experi- ent within the region of the typhoon core is 4°C weaker in the ments also aimed to analyze the effect of air-atmosphere inter-

118° 120° 122° 124° 126° 128° 130° 132° E 118° 120° 122° 124° 126° 128° 130° 132° E 38° 38° N abN 36° 36° 80 80 34° 70 34° 70 60 60 32° 32° 50 50 40 40 30° 30°

30 Depth/ m 30 Depth/ m 28° 20 28° 20 10 10 26° 0 26° 0

24° 24°

Fig.8. Depth of the 26°C isotherm (m) around the center of Muifa, predicted by the coupled model. a. Initial time at 00:00UTC 5 Aug., 2011, and b. 72-hour forecast.

118° 120° 122° 124° 126° 128° 130° 132° E 118° 120° 122° 124° 126° 128° 130° 132° E 38° 38° N abN 36° 36°

34° 34°

32° 32°

30° 30°

28° 28°

26° 26°

24° 24°

Fig.9. TCHP (kJ/cm2) around the center of Muifa predicted by the coupled model. a. Initial time at 00:00UTC 5 Aug. 2011, and b. 72 h forecast. 132 SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133

121.2° 121.8° 122.4° 123° 123.6° E 121.2° 121.8° 122.4° 123° 123.6° E 33° 33° N abN

32° 384 32° 384 380 380 376 376 31° 372 31° 372 368 368 364 364 30° 360 30° 360 356 356 Equivialent potential temperature/K Equivialent potential temperature/K

29° 29°

Fig.10. The 48 h distribution of the equivalent potential temperature (K) at the sea surface, predicted by the uncoupled_1 experiment (a) and the coupled experiment (b) beginning at 00:00UTC 5 Aug. 2011.

110°E114°E118°E 122°E 126°E 130°E 134°E 110°E114°E118°E 122°E 126°E 130°E 134°E 100 100 ab 200 200 18 18 300 16 300 16

14 C 14 C 400 12 400 12 500 10 500 10 8 8 600 6 600 6 Pressure/hPa Pressure/hPa 700 4 700 4 2 2 temperature anomaly/° temperature anomaly/° 800 0 800 0 −2 −2 900 900

1 000 1 000

Fig.11. The 48 h distribution of the vertical temperature anomaly across the center of typhoon Muifa, predicted by the uncou- pled_1 experiment (a) and the coupled experiment (b) beginning at 00:00UTC 5 Aug. 2011.

116° 120° 124° 128° 132° E 116° 120° 124° 128° 132° E 40° 40° N N 700 700 650 650 36° 600 36° 600 550 550 500 500 32° 450 32° 450 400 400 350 350 28° 300 28° 300 250 250 200 200

24° 150 Accumulated precipitation/mm 24° 150 Accumulated precipitation/mm 100 100 ab50 50 20° 20°

Fig.12. Superimposed on the sea level pressure (hPa) and the 72 h distribution of the accumulated precipitation predicted by the uncoupled_1 experiment (a) and the coupled experiment (b) beginning at 00:00UTC 5 Aug. 2011. actions on Muifa’s progress. At improved SST resolution in the atmosphere–ocean model significantly improved the inten- initial field of GRAPES, the model could identify the initial SST sity forecast. In particular, the overestimates of the uncoupled “cold pool”, and the intensity forecast was improved, especially GRAPES_TYM were corrected by including instantaneous SST after Muifa had crossed over the sea for a period. The coupled changes. The extent of atmosphere–ocean coupling at differ- SUN Minghua et al. Acta Oceanol. Sin., 2014, Vol. 33, No. 11, P. 123–133 133

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