李森,
郭安红,
王纯枝
国家气象中心 北京 100081
基金项目: 国家重点研发计划课题2017YFD03001
国家重点研发计划课题2017YFC1502402
详细信息
作者简介:张蕾, 主要从事农业气象灾害监测预警与风险评估。E-mail:leizhang@cma.gov.cn
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出版历程
收稿日期:2020-03-21
录用日期:2020-05-15
刊出日期:2020-10-01
Thermal resource change dynamics for single-season rice in China under RCP scenarios
ZHANG Lei,LI Sen,
GUO Anhong,
WANG Chunzhi
National Meteorological Center, Beijing 100081, China
Funds: the National Key R & D Projects of China2017YFD03001
the National Key R & D Projects of China2017YFC1502402
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摘要
摘要:本文基于20个统计降尺度的高分辨率全球气候模式模拟数据，以平均气温、≥10℃积温和温度适宜度作为热量资源指数，分析了未来2种典型浓度路径情景下全国不同产区一季稻热量资源的变化特性，以期掌握未来水稻热量资源动态调整水稻生产。结果表明：一季稻主要生长季平均气温、≥10℃积温和温度适宜度地区间差异明显；RCP4.5和RCP8.5情景下，不同地区平均气温、≥10℃积温呈现不同程度的增加，且RCP8.5情景下的增幅较RCP4.5更为明显。1986—2005年，四川盆地和长江中下游地区一季稻温度适宜度较其他地区高；RCP4.5情景下，东北、宁夏、西南地区南部和东南部温度适宜度呈增大趋势，RCP8.5情景下这种变化趋势更为显著，可见热量资源的变化将利于这些地区一季稻生长；而四川盆地和长江中下游地区温度适宜度呈减小趋势，主要归因于高温日数的显著增加，因而热量资源变化并不利于该两地的一季稻生长。未来不同地区热量资源的变化特征将有助于指导不同地区合理优化水稻生产，趋利避害以应对气候变化。
Abstract:Rice production is affected by current climate change, but future changes are rarely mentioned. A better understanding of the thermal resource dynamics of rice production is important for future optimization. Changes in the spatial-temporal dynamics of the thermal resources for future single-season rice was analyzed under two representative concentration pathways (i.e., RCP4.5 and RCP8.5), using the mean air temperature, accumulated temperature above 10 ℃, and temperature suitability as indices. The analysis was based on daily reproduction data from 20 global climate models at a high resolution of 0.25°×0.25°, which was downscaled by Bias Correction Spatial Disaggregation. The results indicated that the mean air temperature, accumulated temperature above 10 ℃, and temperature suitability differed spatially. During the baseline period from 1986-2005, a higher mean air temperature and accumulated temperature above 10 ℃ were detected in the Sichuan Basin, as well as in the middle and lower reaches of the Yangtze River. Relative to the baseline, the mean air temperature and accumulated temperature above 10 ℃ during the future periods (i.e., 2021-2040, 2041-2060, 2061-2080, and 2081-2100) under RCP4.5 and RCP8.5 increased by varying magnitudes in different regions (increment magnitudes under RCP8.5 were larger than RCP4.5). Increasing mean air temperature and accumulated temperature suggest that more thermal resources will be available for rice in the future, making it appropriate to replace the early-mid rice variety with the mid-late variety. However, increasing temperature is not always beneficial to rice growing. Temperature suitability based on the temperature requirements were implemented for different rice-growing periods. During the baseline years, the temperature suitability was greater than 0.95 in the Sichuan Basin, as well as in the middle and lower reaches of the Yangtze River, which was higher than the other regions (i.e., Northeast China, Ningxia, and the southern and southeastern regions of Southwest China). No obvious (or negative) temperature suitability trends were observed in the Sichuan Basin or the middle and lower reaches of the Yangtze River, but positive trends were observed in other regions. Under future period predictions, there was a decreasing temperature suitability trend in the Sichuan Basin and in the middle and lower reaches of the Yangtze River, with a tendency of -0.03 - 0·(10a)-1 and -0.11- -0.03· (10a)-1 under RCP4.5 and RCP8.5, respectively. This was attributed to more days in the future with maximum temperatures greater than 35 ℃ and implies that a significant increase in heat stress would threaten rice growing. Comparatively, temperature suitability in Northeast China, Ningxia, the southern and southeastern regions of Southwest China increased at a rate of 0.00-0.03·(10a)-1 under RCP4.5, which was smaller than under RCP8.5. This, combined with increasing mean air temperature and accumulated temperature above 10 ℃, would benefit rice growing in these regions. Understanding the thermal characteristics can help to optimize rice production among regions in response to climate change.
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图1不同情景下不同时段一季稻区5—9月平均气温
Figure1.Mean air temperature during May to September in different periods of time across the single-season rice area of China under RCP4.5 and RCP8.5 scenarios
下载: 全尺寸图片幻灯片
图2不同情景下不同时段一季稻区5—9月≥10 ℃活动积温
Figure2.Accumulated temperature above 10 ℃ during May-September in different periods of time across the single-season rice area of China under RCP4.5 and RCP8.5 scenarios
下载: 全尺寸图片幻灯片
图3不同情景下不同时段一季稻区5—9月温度适宜度
Figure3.Temperature suitability during May-September in different periods of time across the single-season rice area of China under RCP4.5 and RCP8.5 scenarios
下载: 全尺寸图片幻灯片
图4不同情景下一季稻区5—9月温度适宜度的变化趋势
Figure4.Trend of temperature suitability during May-September across the single-season rice area of China under RCP4.5 and RCP8.5 scenarios
下载: 全尺寸图片幻灯片
图5不同月份黑龙江(a)、湖北(b)和云南(c)不同情景下的温度适宜度变化(P0、P1、P2、P3和P4分别代表1986—2005年、2021—2040年、2041—2060年、2061—2080年和2081—2100年)
Figure5.Changes of monthly temperature suitability in Heilongjiang (a), Hubei (b) and Yunnan (c) during May-September under RCP4.5 and RCP8.5 scenarios (P0, P1, P2, P3 and P4 represent 1986-2005, 2021-2040, 2041-2060, 2061-2080 and 2081-2100, respectively)
下载: 全尺寸图片幻灯片表1全球气候模式基本信息
Table1.Basic information of global climate models
| 模式 Model | 分辨率 Resolution | 机构 Institution | 国家 Country |
| ACCESS 1.0 | 1.875°×1.25° | Commonwealth Scientific and Industrial Research Organization and Bureau of Meteorology | Australia |
| BNU-ESM | 2.8°×2.8° | Beijing Normal University | China |
| CanESM2 | 2.8°×2.8° | Canadian Centre for Climate Modeling and Analysis | Canada |
| CCSM4 | 0.9°×1.25° | National Center for Atmospheric Research | USA |
| CNRM-CM5 | 1.4°×1.4° | Centre National de Recherches Météorologiques | France |
| CSIRO-Mk3-6-0 | 1.875°×1.875° | Commonwealth Scientific and Industrial Research Organization | Australia |
| GFDL-CM3 | 2.5°×2.0° | Geophysical Fluid Dynamics Laboratory | USA |
| GFDL-ESM2G | 2.5°×2.0° | Geophysical Fluid Dynamics Laboratory | USA |
| GFDL-ESM2M | 2.5°×2.0° | Geophysical Fluid Dynamics Laboratory | USA |
| HadGEM2-ES | 1.875°×1.25° | Hadley Centre | UK |
| inmcm4 | 1.5°×2.0° | Institute for Numerical Mathematics | Russia |
| IPSL-CM5A-LR | 3.75°×1.895° | Institute Pierre-Simon Laplace | France |
| IPSL-CM5A-MR | 2.5°×1.27° | Institute Pierre-Simon Laplace | France |
| MIROC5 | 1.4°×1.4° | Atmosphere and Ocean Research Institute | Japan |
| MIROC-ESM | 2.8°×2.8° | Atmosphere and Ocean Research Institute | Japan |
| MIROCESM-CHEM | 2.8°×2.8° | Atmosphere and Ocean Research Institute | Japan |
| MPI-ESM-LR | 1.875°×1.875° | Max Planck Institute for Meteorology | Germany |
| MPI-ESM-MR | 1.875°×1.875° | Max Planck Institute for Meteorology | Germany |
| MRI-CGCM3 | 1.125°×1.125° | Meteorological Research Institute | Japan |
| NorESM1-M | 1.895°×2.500° | Norwegian Climate Centre | Norway |
下载: 导出CSV表2不同地区一季稻生长季不同月份温度临界值(最低, 最高, 最适温度)
Table2.Typical values of temperature at different months of single-season rice season in different regions (minimum temperature, maximum temperature, optimal temperature)?
| 地区 Region | 5月 May | 6月 June | 7月 July | 8月 August | 9月 September |
| 东北?Northeast China | 12, 40, 20 | 13, 35, 18 | 15, 40, 26 | 15, 37, 26 | 13, 35, 23 |
| 西北?Northwest China | 12, 40, 20 | 13, 35, 18 | 15, 40, 26 | 15, 37, 26 | 13, 35, 23 |
| 长江中下游?Middle and lower reaches of the Yangtze River | 10, 40, 21 | 12, 35, 25 | 15, 40, 28 | 18, 35, 26 | 13, 35, 23 |
| 西南?Southwest China | 12, 33, 23 | 17, 30, 25 | 22, 35, 28 | 15, 35, 26 | 13, 35, 23 |
下载: 导出CSV表3不同情景下不同地区一季稻生长季平均高温日数变化
Table3.Change of days of heat stress during single-season rice season at different regions under RCP4.5 and RCP8.5 scenarios
| 地区 Region | RCP4.5 | RCP8.5 | ||||||||
| P0 | P1 | P2 | P3 | P4 | P1 | P2 | P3 | P4 | ||
| 安徽?Anhui | 7.55 | 14.94 | 23.63 | 31.06 | 33.62 | 17.48 | 30.66 | 48.46 | 68.03 | |
| 湖北?Hubei | 7.57 | 15.06 | 23.57 | 30.89 | 33.09 | 17.51 | 30.47 | 47.91 | 67.15 | |
| 湖南?Hunan | 7.59 | 15.07 | 23.52 | 30.80 | 32.85 | 17.50 | 30.39 | 47.68 | 66.79 | |
| 江苏?Jiangsu | 7.64 | 14.99 | 23.76 | 31.26 | 34.08 | 17.54 | 30.82 | 48.90 | 68.62 | |
| 江西?Jiangxi | 7.51 | 14.86 | 23.40 | 30.78 | 33.16 | 17.35 | 30.36 | 47.95 | 67.32 | |
| 浙江?Zhejiang | 7.49 | 14.70 | 23.41 | 30.86 | 33.71 | 17.26 | 30.43 | 48.47 | 68.17 | |
| 四川盆地?Sicuan Basin | 5.29 | 12.58 | 19.07 | 23.81 | 24.89 | 14.35 | 24.03 | 37.55 | 55.92 | |
| P0、P1、P2、P3、P4分别代表1986—2005年、2021—2040年、2041—2060年、2061—2080年和2081—2100年。P0, P1, P2, P3 and P4 represent 1986-2005, 2021-2040, 2041-2060, 2061-2080 and 2081-2100, respectively. | ||||||||||
下载: 导出CSV参考文献
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