Research Toics

Takahashi et al. 2015b

Takahashi, H. G., S. A. Adachi, T. Sato, M. Hara, X. Ma, and F. Kimura, 2015: An Oceanic Impact of the Kuroshio on Surface Air Temperature on the Pacific Coast of Japan in Summer: Regional H2O Greenhouse Gas Effect, Journal of Climate, Vol. 28, No.18, September 2015: 7128-7144.[Web Page]

Fig. Regression coefficient of the simulated precipitable water (mm) and vertically integrated water vapor fluxes (kgm-1 s-1) in August on the normalized SST over REF Kuroshio during the 31-yr period from 1982 to 2012. All plotted vectors are statistically significant at the 99.9% level, as determined by correlation coefficients based on 29 degrees of freedom.

Takahashi et al. 2015a

Takahashi H.G., H. Fujinami, T. Yasunari, J. Matsumoto, and S. Baimoung, 2014: Role of tropical cyclones along the monsoon trough in the 2011 Thai flood and interannual variability, Journal of Climate, November 2014. [Web Page]

Fig. (a) Precipitation time series generated from theCMAP dataset for the rainy season (May–September) over the reference region of Indochina (12.58–208N, 97.58–107.58E) from 1979–2011. The reference region is used for the regression analysis in (b),(c) and is indicated by a solid rectangle in these panels. (b)Regression ofCMAPdata during the rainy season against the normalized data (mmday21) shown in (a) from 1979 to 2011. (c) As in (b), but for the 850-hPa zonal and meridional winds and streamfunction (colors) during the rainy season. Areas with colors in (b) and plotted vectors (winds;ms21) and contours and colors (streamfunction; 106m2 s21) in(c) are statistically significant at the 90% level, as determined by correlation coefficients based on 31 degrees of freedom (df).

Yamaji and Takahashi 2014

Yamaji M. and H.G. Takahashi, 2014: Asymmetrical interannual variation in aerosol optical depth over the tropics in terms of aerosol-cloud interaction, SOLA (Scientific Online Letters on the Atmosphere), October 2014, doi:10.2151/sola.2014-039.[Web Page]

Left Fig. Composite anomalies in aerosol optical depth in (a) SON of the El Niño years, (b) SON of the La Niña years, (c) DJF of the El Niño years, and (d) DJF of the La Niña years (95% confidence limit as determined by Student’s t-test). Gray portions indicate missing values.

Right Fig. Scatterplot between three-month mean precipitation (unit is mm day−1) and AOD (from Terra and Aqua) over the Maritime Continent (105°E−140°E, 10°S−5°N) from 2000 to 2012 in (a) SON and (b) DJF. Red, blue rhombus, and asterisk symbols are values for dry (El Niño), wet (La Niña), and neutral years respectively. Lines in (a) are least-squares regression fits to data points using values from the El Niño and La Niña years together (dotted line) and separately (solid lines).

Takahashi et al. 2013a

Takahashi, H.G., N. N. Ishizaki, H. Kawase, M. Hara, T. Yoshikane, X. Ma, and F. Kimura 2013: Potential impact of sea surface temperature on winter precipitation over the Japan Sea side of Japan: A regional climate modeling study. Journal of the Meteorological Society of Japan (JMSJ), April 2013.[Web Page]

Fig. Time series of simulatedprecipitation over the reference region 1 (137-140°E, 36.5-38.5°N; shown in Fig. 1), except for the ocean. Black, pink, red, and light-blue lines indicate CTL, SST+1K, SST+2K, and SST−1K, respectively. The precipitation was accumulatedfrom 00 UTC 1 January 2006. The unit is millimeters.

Takahashi et al. 2010

Takahashi, H.G., T. Yoshikane, M. Hara, K. Takata, and T. Yasunari 2010: High-resolution modelling of the potential impact of land-surface conditions on regional climate over Indochina associated with the diurnal precipitation cycle, International Journal of Climatology, 30(13), 2004-2020, Janurary 2010, doi:10.1002/joc.2119.[PDF]

Fig. Total amount of monthly precipitation of (a) WET and (b) DRY. Differences in monthly precipitation (c) between DRY and CTL (CTL–WET) and (d) between CTL and DRY (DRY–CTL) are shown. The numbers of pentads out of 18 that calculate increase in pentad precipitation (e) between DRY and CTL (CTL–WET) and (f) between CTL and DRY (DRY–CTL) are shown. The calculation period of each experiment is three months, which is 18 pentads (90 days). The numbers of pentads that show increase in precipitation were counted at each half-degree grid. White and black lines indicate the disturbed region.

Climate System

 Water cycle (Global and regional climate changes): Changes in evapotranspiration, moisture transport, residual period of water vapor, clouds and precipitation due to global warming and their interactions.

 Regional climate changes: Rainfall over Southeast Asia and its association with tropical cyclone activity (Thai flood 2011)

 Reseach method: Climate model (Particularly, regional climate model), ground-based observation, satellite-based observation