著者

Nobuhito Mori Tomohiro Yasuda Hajime Mase Tracey Tom Yuichiro Oku

出版者

Japan Society of Hydrology and Water Resources (JSHWR) / Japanese Association of Groundwater Hydrology (JAGH) / Japanese Association of Hydrological Sciences (JAHS) / Japanese Society of Physical Hydrology (JSPH)

雑誌

Hydrological Research Letters (ISSN:18823416)

巻号頁・発行日

vol.4, pp.15-19, 2010 (Released:2010-03-03)

参考文献数

11

被引用文献数

126 187

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The influence of global climate change due to greenhouse effects on the earth’s environment will require impact assessment, mitigation and adaptation strategies for the future of our society. This study predicts future ocean wave climate in comparison with present wave climate based on the atmospheric general circulation model and global wave model. The annual averaged and extreme sea surface winds and waves are analyzed in detail. There are clear regional dependences of both annual average and also extreme wave height changes from present to future climates. The wave heights of future climate will increase at both middle latitudes and also in the Antarctic Ocean, with a decrease at the equator.

著者

Yuhei YAMAMOTO Hirohiko ISHIKAWA Yuichiro OKU Zeyong HU

出版者

Meteorological Society of Japan

雑誌

気象集誌. 第2輯 (ISSN:00261165)

巻号頁・発行日

vol.96B, pp.59-76, 2018 (Released:2018-03-16)

参考文献数

53

被引用文献数

27

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This paper presents a method for estimating the land surface temperature (LST) from Himawari-8 data. The Advanced Himawari Imager onboard Himawari-8 has three thermal infrared bands in the spectral range of 10-12.5 μm. We developed a nonlinear three-band algorithm (NTB) that makes the best use of these bands to estimate the LST. The formula of the algorithm includes 10 coefficients. The optimum values of these coefficients were derived using a statistical regression method from the simulated data, as obtained by a radiative transfer model. The simulated data sets correspond to a variety of values of LST, as well as surface emissivity, type and season of temperature and water vapor profiles. Viewing zenith angles (VZAs) from 0° to 60° were considered. For the coefficients obtained in this way, we verified the root-mean-square error (RMSE) in terms of the VZA, LST and precipitable water dependence. We showed that the NTB can accurately estimate the LST with an RMSE less than 0.9 K compared with the nonlinear split-window algorithm developed by Sobrino and Romaguera (2004). Moreover, we evaluated the sensitivities of the LST algorithms to the uncertainties in input data by using the dataset independent of the dataset used to obtain coefficients. Consequently, we showed that the NTB has the highest robustness against the uncertainties in input data. Finally, the stepwise LST retrieval method was constructed. This method includes a simple cloud mask procedure and the land surface emissivity estimation. The LST product was evaluated using in-situ data over the Tibetan Plateau, and the validity was confirmed.