RESEARCH ON THE PHOTO-TEMPERATURE MODEL FOR THE DEVELOPMENTAL RATE OF RICE

Lan Hongdi; Jiang Maoji

doi:10.1007/BF02678753

Impact Factor: 5.8

Volume 2 Issue 4

Oct. 1985

Article Contents

Article > ADVANCES IN ATMOSPHERIC SCIENCES > 1985 > 2(4): 549-552

RESEARCH ON THE PHOTO-TEMPERATURE MODEL FOR THE DEVELOPMENTAL RATE OF RICE

1.
AcademyofMeteorologicalScience,StateMeteorologicalAdministration,Beijing,BureauofMeteorologyofJiangsu,Nanjing

doi: 10.1007/BF02678753

Abstract
References
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Abstract:
Rice is one kind of crops with short length of light, its developmental rate in the photophase depends on the light-length and temperature. Since uncultivated rice was discovered in China, about 40,000 species of rice, including photo-sensitive and temperature-sensitive types, have been growing. A number of researches have been carried out by agrometeorologists in this field. The purpose of this paper is to develop a photo-temperature model based on a considerable amount of experimental data.
References

[1]	Ding Aiju, Wang Mingxing, 1996: Model for Methane Emission from Rice Fields and Its Application in Southern China, ADVANCES IN ATMOSPHERIC SCIENCES, 13, 159-168. doi: 10.1007/BF02656859
[2]	Xinyi XING, Xianghui FANG, Da PANG, Chaopeng JI, 2024: Seasonal Variation of the Sea Surface Temperature Growth Rate of ENSO, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 465-477. doi: 10.1007/s00376-023-3005-x
[3]	ZOU Jianwen, HUANG Yao, ZONG Lianggang, ZHENG Xunhua, WANG Yuesi, 2004: Carbon Dioxide, Methane, and Nitrous Oxide Emissions from a Rice-Wheat Rotation as Affected by Crop Residue Incorporation and Temperature, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 691-698. doi: 10.1007/BF02916366
[4]	Shili Yang, Wenjie Dong, JieMing Chou, Yong Zhang, Weixing Zhao, 2024: Regional climate damage quantifications and its impacts on future emission paths using the RICE model, ADVANCES IN ATMOSPHERIC SCIENCES. doi: 10.1007/s00376-024-3193-z
[5]	Peng LIU, Jianning SUN, Lidu SHEN, 2016: Parameterization of Sheared Entrainment in a Well-developed CBL. Part II: A Simple Model for Predicting the Growth Rate of the CBL, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1185-1198. doi: 10.1007/s00376-016-5209-9
[6]	Bian Jianchun, Chen Hongbin, Sun Haibing, Yang Peicai, Lu Daren, Zhou Xiuji, 1999: Retrievals of Rain-Rate over Oceans from SSM/ I Data Using SOM Model, ADVANCES IN ATMOSPHERIC SCIENCES, 16, 355-360. doi: 10.1007/s00376-999-0014-3
[7]	Xun Zhu, 1989: A Parameterization of Cooling Rate Calculation under the Non-LTE Condition: Multi-Level Model, ADVANCES IN ATMOSPHERIC SCIENCES, 6, 403-413. doi: 10.1007/BF02659075
[8]	ZHOU Zaixing, ZHENG Xunhua, XIE Baohua, HAN Shenghui, LIU Chunyan, 2010: A process-based model of N2O emission from a rice-winter wheat rotation agroecosystem: structure, validation and sensitivity, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 137-150. doi: 10.1007/s00376-009-8191-7
[9]	JIN Ling, Fanyou KONG, LEI Hengchi, and HU Zhaoxia, 2014: A Methodological Study on Using Weather Research and Forecasting (WRF) Model Outputs to Drive a One-Dimensional Cloud Model, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 230-240. doi: 10.1007/s00376-013-2257-2*
[10]	Rui WANG, Yiting ZHU, Fengxue QIAO, Xin-Zhong LIANG, Han ZHANG, Yang DING, 2021: High-resolution Simulation of an Extreme Heavy Rainfall Event in Shanghai Using the Weather Research and Forecasting Model: Sensitivity to Planetary Boundary Layer Parameterization, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 98-115. doi: 10.1007/s00376-020-9255-y
[11]	HUANG Ping, WANG Pengfei, HU Kaiming, HUANG Gang, ZHANG Zhihua, LIU Yong, YAN Bangliang, 2014: An Introduction to the Integrated Climate Model of the Center for Monsoon System Research and Its Simulated Influence of El Nio on East Asian-Western North Pacific Climate, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 1136-1146. doi: 10.1007/s00376-014-3233-1
[12]	Xiaojuan LIU, Guangjin TIAN, Jinming FENG, Bingran MA, Jun WANG, Lingqiang KONG, 2018: Modeling the Warming Impact of Urban Land Expansion on Hot Weather Using the Weather Research and Forecasting Model: A Case Study of Beijing, China, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 723-736. doi: 10.1007/s00376-017-7137-8
[13]	Rajabu J. MANGARA, Zhenhai GUO, Shuanglin LI, 2019: Performance of the Wind Farm Parameterization Scheme Coupled with the Weather Research and Forecasting Model under Multiple Resolution Regimes for Simulating an Onshore Wind Farm, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 119-132. doi: 10.1007/s00376-018-8028-3
[14]	Haochen LI, Chen YU, Jiangjiang XIA, Yingchun WANG, Jiang ZHU, Pingwen ZHANG, 2019: A Model Output Machine Learning Method for Grid Temperature Forecasts in the Beijing Area, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1156-1170. doi: 10.1007/s00376-019-9023-z
[15]	Yueliang CHEN, Changxiang YAN, Jiang ZHU, 2018: Assimilation of Sea Surface Temperature in a Global Hybrid Coordinate Ocean Model, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 1291-1304. doi: 10.1007/s00376-018-7284-6
[16]	NIU Shengjie, LU Chunsong, YU Huaying, ZHAO Lijuan, LU Jingjing, 2010: Fog Research in China: An Overview, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 639-662. doi: 10.1007/s00376-009-8174-8
[17]	Wang Mingxing, Shangguan Xingjian, Shen Renxing, Wassmann Reiner, Seiler Wolfgang, 1993: Methane Production, Emission and Possible Control Measures in the Rice Agriculture, ADVANCES IN ATMOSPHERIC SCIENCES, 10, 307-314. doi: 10.1007/BF02658136
[18]	YANG Yang, REN Rongcai, Ming CAI, RAO Jian, 2015: Attributing Analysis on the Model Bias in Surface Temperature in the Climate System Model FGOALS-s2 through a Process-Based Decomposition Method, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 457-469. doi: 10.1007/s00376-014-4061-z
[19]	Jianfeng WANG, Ricardo M. FONSECA, Kendall RUTLEDGE, Javier MARTÍN-TORRES, Jun YU, 2020: A Hybrid Statistical-Dynamical Downscaling of Air Temperature over Scandinavia Using the WRF Model, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 57-74. doi: 10.1007/s00376-019-9091-0
[20]	ZHANG Xiaohui, GAO Zhiqiu, WEI Dongping, 2012: The Sensitivity of Ground Surface Temperature Prediction to Soil Thermal Properties Using the Simple Biosphere Model (SiB2)}, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 623-634. doi: 10.1007/s00376-011-1162-9

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Manuscript History

Manuscript received: 10 October 1985

Manuscript revised: 10 October 1985

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

RESEARCH ON THE PHOTO-TEMPERATURE MODEL FOR THE DEVELOPMENTAL RATE OF RICE

1. AcademyofMeteorologicalScience,StateMeteorologicalAdministration,Beijing,BureauofMeteorologyofJiangsu,Nanjing

Manuscript received: 1985-10-10
Manuscript revised: 1985-10-10

Abstract: Rice is one kind of crops with short length of light, its developmental rate in the photophase depends on the light-length and temperature. Since uncultivated rice was discovered in China, about 40,000 species of rice, including photo-sensitive and temperature-sensitive types, have been growing. A number of researches have been carried out by agrometeorologists in this field. The purpose of this paper is to develop a photo-temperature model based on a considerable amount of experimental data.