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An accurate and spatially explicit large-scale rice calendar can enhance the understanding of agricultural practices and their ecological services, particularly in monsoon Asia. However, currently available global- or continental-scale rice calendars suffer from coarse resolution, poor recording, and outdated information; thus, they do not provide detailed and consistent information on rice phenology. To address this limitation, this study mapped a new (2019–2020) gridded (0.5°×0.5° resolution) rice calendar for monsoon Asia based on Sentinel-1 and Sentinel-2 satellite images. The novelty of this rice calendar lies in the development of a consistent optimal methodological framework that allows the spatially explicit characterization of the rice transplanting date, harvesting date, and number of rice cropping seasons. The methodological framework incorporates two steps: (1) detection of rice phenological dates and number of rice cropping seasons via the combination of a feature-based algorithm and the fitted Weibull function; (2) spatiotemporal integration of the detected transplanting and harvesting dates derived from Step 1 using von Mises maximum likelihood estimates. Results revealed that the proposed rice calendar can accurately identify the rice phenological dates for three croppings in monsoon Asia. When compared with single rice data from the census-based RiceAtlas calendar, the proposed calendar exhibited better results than the MODIS-based Rice Crop Calendar for Asia (RICA). It exhibited biases of 4 and - 6 d for the transplanting and harvesting dates, respectively, with 10 and 15 d lower MAE values and 6 and 15 d lower RMSE values for the transplanting and harvesting dates, respectively. In total, the proposed rice calendar can detect single-, double-, and triple-rice-cropping seasons with an area of 0.53×106 , 0.45×106 , and 0.09×106 km 2 , respectively. This novel gridded rice calendar fills the gaps in 0.5° rice calendars across major global rice production areas, facilitating research on rice phenology that is relevant to climate change. The developed gridded Monsoon Asia Rice Calendar (MARC) is available at 10.17595/20230728.001 (Zhao and Nishina, 2023). [ABSTRACT FROM AUTHOR]

Byline: Hideo Shiogama (1), Naota Hanasaki (1), Yuji Masutomi (2), Tatsuya Nagashima (1), Tomoo Ogura (1), Kiyoshi Takahashi (1), Yasuaki Hijioka (1), Toshihiko Takemura (3), Toru Nozawa (1), Seita Emori (1,4,5) Abstract: Anthropogenic global warming will lead to changes in the global hydrological cycle. The uncertainty in precipitation sensitivity per 1 K of global warming across coupled atmosphere-ocean general circulation models (AOGCMs) has been actively examined. On the other hand, the uncertainty in precipitation sensitivity in different emission scenarios of greenhouse gases (GHGs) and aerosols has received little attention. Here we show a robust emission-scenario dependency (ESD) smaller global precipitation sensitivities occur in higher GHG and aerosol emission scenarios. Although previous studies have applied this ESD to the multi-AOGCM mean, our surprising finding is that current AOGCMs all have the common ESD in the same direction. Different aerosol emissions lead to this ESD. The implications of the ESD of precipitation sensitivity extend far beyond climate analyses. As we show, the ESD potentially propagates into considerable biases in impact assessments of the hydrological cycle via a widely used technique, so-called pattern scaling. Since pattern scaling is essential to conducting parallel analyses across climate, impact, adaptation and mitigation scenarios in the next report from the Intergovernmental Panel on Climate Change, more attention should be paid to the ESD of precipitation sensitivity. Author Affiliation: (1) National Institute for Environmental Studies, 16--2 Onogawa, Tsukuba, Ibaraki, 305-8506, Japan (2) Center for Environmental Science in Saitama, 914 Kamitanadare, Kisai Town, Kita-Saitama-gun, Saitama, 347-0115, Japan (3) Research Institute for Applied Mechanics, Kyushu University, 6-1 Kasuga-kouen, Kasuga, Fukuoka, 816-8580, Japan (4) Center for Climate System Research, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8568, Japan (5) Yokohama Institute for Earth Sciences, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showamachi, Kanazawa-ku, Yokohama City, Kanagawa, 236-0001, Japan Article History: Registration Date: 01/12/2009 Received Date: 11/08/2009 Accepted Date: 25/11/2009 Online Date: 07/01/2010 Article note: Electronic supplementary material The online version of this article (doi: 10.1007/s10584-009-9765-1) contains supplementary material, which is available to authorized users.

In this study, we aimed to evaluate the monthly precipitation forecasts of JMA/MRI-CPS2, a global dynamical seasonal climate forecast (Dyn-SCF) system operated in the Japan Meteorological Agency, by comparing them with the forecasts of a statistical SCF (St-SCF) system using climate indices systematically and globally. Accordingly, we developed a new global St-SCF system using 18 climate indices and compared the monthly precipitation of this system with those of JMA/MRI-CPS2. Consequently, it was found that JMA/MRI-CPS2 forecasts are superior to St-SCFs around the equator (10° S-10° N) even for six-month lead forecasts. For one-month lead forecasts, the accuracy of JMA/MRI-CPS2 forecasts was higher than that of St-SCFs when viewed globally. In contrast, for forecasts made two months or longer in advance, St-SCFs had an advantage in global forecasts. In addition to evaluating the accuracy of JMA/MRI-CPS2 forecasts, the slow dynamics of the ocean and atmosphere, not reproduced by the JMA/MRI-CPS2 system, were determined by comparing the evaluations, and it was concluded that this could contribute to improving Dyn-SCF systems. [ABSTRACT FROM AUTHOR]

• Analytical solutions proposed for the coupled A n - G s model have several problems. • A new method is proposed to solve these problems. • We showed the proposed method works and can select only one analytical solution. • The method proposed here can be used in various studies on A n and G s. Models coupling photosynthesis (A n) and stomatal conductance (G s) have been widely used for their estimation since it was found that A n and G s are correlated. Although a cubic equation for A n can be derived from the coupled A n - G s model for C3 plants and a method of obtaining analytical solutions has been proposed, these analytical solutions have several problems like no solutions, changes in appropriate solutions, and no physical and biological logic for selecting the appropriate solution. In this study, a method is proposed to solve these problems using a different expression of analytical solutions and imposing requirements. The proposed method was then numerically tested under a wide range of environmental conditions. By proving the existence and uniqueness of physically and biologically appropriate solutions, this study showed that the proposed method can solve all the above problems and can provide an appropriate analytical solution for each of environmental conditions tested. The proposed method can be used in various studies on photosynthesis and stomatal conductance in the future. [ABSTRACT FROM AUTHOR]