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Journal of Geographical Sciences >

2017 , Vol. 27 >Issue 9: 1044 - 1058

DOI: https://doi.org/10.1007/s11442-017-1420-6

Research Articles

Impacts of future climate change on agroclimatic resources in Northeast China

  • CHU Zheng , 1 ,
  • GUO Jianping , 1, 2, * ,
  • ZHAO Junfang 2
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*Corresponding author: Guo Jianping (1963-), PhD and Professor, E-mail:

Author: Chu Zheng (1985-), PhD, specialized in agricultural meteorology and related fields. E-mail:

Received date: 2016-08-08

  Accepted date: 2017-02-22

  Online published: 2017-09-05

Supported by

National Natural Science Foundation of China, No.31371530

Jiangsu Province Innovative Postgraduate Training Program, No.KYLX_0846

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Journal of Geographical Sciences, All Rights Reserved
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Abstract

In this study, the spatial distribution and changing trends of agricultural heat and precipitation resources in Northeast China were analyzed to explore the impacts of future climate changes on agroclimatic resources in the region. This research is based on the output meteorological data from the regional climate model system for Northeast China from 2005 to 2099, under low and high radiative forcing scenarios RCP4.5 (low emission scenario) and RCP8.5 (high emission scenario) as proposed in IPCC AR5. Model outputs under the baseline scenario, and RCP4.5 and RCP8.5 scenarios were assimilated with observed data from 91 meteorological stations in Northeast China from 1961 to 2010 to perform the analyses. The results indicate that: (1) The spatial distribution of temperature decreases from south to north, and the temperature is projected to increase in all regions, especially under a high emission scenario. The average annual temperature under the baseline scenario is 7.70°C, and the average annual temperatures under RCP4.5 and RCP8.5 are 9.67°C and 10.66°C, respectively. Other agricultural heat resources change in accordance with temperature changes. Specifically, the first day with temperatures ≥10°C arrives 3 to 4 d earlier, the first frost date is delayed by 2 to 6 d, and the duration of the growing season is lengthened by 4 to 10 d, and the accumulated temperature increases by 400 to 700°C·d. Water resources exhibit slight but not significant increases. (2) While the historical temperature increase rate is 0.35°C/10a, the rate of future temperature increase is the highest under the RCP8.5 scenario at 0.48°C/10a, compared to 0.19°C/10a under the RCP4.5 scenario. In the later part of this century, the trend of temperature increase is significantly faster under the RCP8.5 scenario than under the RCP4.5 scenario, with faster increases in the northern region. Other agricultural heat resources exhibit similar trends as temperature, but with different specific spatial distributions. Precipitation in the growing season generally shows an increasing but insignificant trend in the future, with relatively large yearly fluctuations. Precipitation in the eastern region is projected to increase, while a decrease is expected in the western region. The future climate in Northeast China will change towards higher temperature and humidity. The heat resource will increase globally, however its disparity with the change in precipitation may negatively affect agricultural activities.

Key words： climate change; agroclimatic resources; Northeast China

Cite this article

CHU Zheng , GUO Jianping , ZHAO Junfang . Impacts of future climate change on agroclimatic resources in Northeast China[J]. Journal of Geographical Sciences, 2017 , 27(9) : 1044 -1058 . DOI: 10.1007/s11442-017-1420-6

1 Introduction

In recent years, the issue of climate change as represented by rising temperatures is receiving intense research interest. Its influence encompasses many aspects of human activities, such as environment, agriculture, manufacturing and industry, and livelihood (ALexandrov and Hoogenboom, 2000; Tang et al., 2000; Füssel and Klein, 2006). Research indicates that by 2100, it is possible that the global temperature could increase by more than 2°C (Solomon, 2007). Agriculture is arguably the most sensitive sector to climate change, and will thus be impacted greatly by climate change. Changes in agroclimatic resources such as light, heat and water will directly alter the agricultural production condition and level (Li et al., 2010a), and ultimately determine the quantity and quality of agricultural production (Yu et al., 1985; Li et al., 2003). Research shows that in the past 50 years, China’s climate has become warmer and drier as a whole. In terms of regions, Southwest, North and Northeast China are trending warmer and drier, while Northwest and South China are trending warmer and wetter (Liu et al., 2009; Li et al., 2010b; Dai et al., 2011; Yang et al., 2011). Due to the impact of the temperature increase, wheat production in China could be reduced by 15% and corn production may also decrease (Yang et al., 2014; Ma et al., 2015). The change in precipitation increases the frequency of drought and flood events, which changes soil humidity and runoff, and reduces the available water resource for crops. Therefore, changes in agroclimatic resources are of crucial importance to food security.
Based on the intensity of atmospheric radiation (2.6-8.5 W/m2), the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) proposed four representative concentration pathway (RCP) scenarios, and it incorporated policy factors for the first time. The four RCPs are: RCP2.6, RCP4.5, RCP6 and RCP8.5. Compared to the 2007 Special Report on Emissions Scenarios (SRES) in AR4, RCPs based models show better performance in simulating extreme weather events (Hu and Liu, 2013). When applied to evaluating agriculture, which is more sensitive to daily climate change, RCP results are more realistic. The northeastern region, i.e., Northeast China (Heilongjiang, Jilin and Liaoning provinces, and the four leagues of eastern Inner Mongolia) is regarded as a climate change sensitive area. Its average temperature has increased by 1.70°C in the past 50 years, significantly higher than the global average warming of 0.74°C/100a (Li, 2012). Meanwhile, Northeast China accounts for 22.9% of all arable land of the country, and the food grain yield is approximately one-third of the total domestic food yield, with 80% of planting areas used for growing major food crops including rice (Oryza sativa), maize and soybeans (Wu et al., 2014). The region plays an important role in China’s food security. As such, what impact will future climate change have on agroclimatic resources in Northeast China? It will have a direct impact on agricultural layout and grain yield, and influence Chinese food production safety strategy. However, as of 2015, only a few scholars have analyzed the changes of growing seasons in Liaoning and Ningxia over the next 50 years by using SRES scenarios from AR4. Presently, there are no related researches on changes to the northeastern climate resources under multiple future climate change scenarios. This study utilizes the latest RCPs future scenarios data from the 5th IPCC report and incorporates historical resources (baseline) to perform an accurate analysis of the spatiotemporal evolution of agroclimatic resources under the influence of climate change in Northeast China. The objective of this research is to provide a more rational scientific basis for developing and utilizing agroclimatic resources, and for guiding agricultural production responses to possible future climate change.

2 Data resources and processing

This study used atmospheric radiation strength (2.6-8.5 W/m2) proposed by the National Climate Center based on the IPCC’s Fifth Assessment Report (AR5), which includes three types of emission concentration drives (RCPrf, RCP4.5, RCP8.5). We adopted the regional climate model in BCC_CSM1.0 and daily meteorological elements data with a simulated spatial resolution of 0.5°×0.5°. Among these three scenarios, RCPrf is the contemporary scenario data with simulated time series from 1951-2005, and is used primarily for data assimilation; RCP4.5 is the scenario that balances greenhouse gas emissions and economic development, with the highest priority on development; RCP8.5 is the highest pathway for greenhouse gas emissions. Both RCP4.5 and RCP8.5 have a simulated time series of 2006-2099.
The daily meteorological data was obtained from the national weather service meteorological data-sharing websites of the National Climate Center. It includes the daily average (T), daily maximum (Tmax), daily minimum (Tmin) temperature, and daily precipitation data. Data are recorded at 91 weather stations in Northeast China from 1961 to 2010 (baseline). These historical data were primarily used to verify the simulation results.
Assimilation and verification process of simulated data:
To eliminate systematic errors in the simulation results on climate modes, we first assimilated the simulated data with recorded historical data from the same time period to obtain new data series with reduced systematic errors. The process can be described in detail as follows:
Assimilation method for climate elements that changed continuously:
$$X_i=[\overline{X}(average\ of\ observed\ data\ of\ the\ same\ day)\\ -\overline{X}_1(average\ of\ simiuation\ data\ of\ the\ same\ day)] \\ +X_i (simulation\ of\ a\ particular\ day) \ \ (1)$$
Assimilation method for climate elements that did not change continuously:
Xi=Xi (simulation data of a particular day)×…, X., average of observed data of a
-10|day period where the day belongs.. -, Xi., average of simulation data of a
-10|day period where the day belongs| (2)
The daily average temperature (T), daily minimum temperature (Tmin), daily maximum temperature (Tmax) and annual precipitation (P) after assimilation were verified individually (Table 1 and Figure 1). As shown, data series after assimilation showed increased accuracy and reduced error for each element compared to the data series before assimilation. Precipitation (P) had the most significant reduction in absolute error, with the accuracy increased by 99%. Accuracy improvement for Tmin and Tmax were 68% and 92%, respectively. The accuracy for T increased by 36%. After assimilation, the root mean square error (RMSE) for all climate elements decreased (Figure 2). The reduction of RMSE for P, T, Tmax and Tmin was 50.01%, 34.58%, 13.94% and 18.10%, respectively. Evidently, by assimilating and correcting the climate model simulation output data with recorded historical data, the climate modeling results became closer to the observed data. Therefore, this study used equations (1) and (2) to regenerate new data series for all elements with the 2006-2099 time scale.
Table 1 Assimilation results of the RCP data
Observed
data		 Pre-assimilation Post-assimilation
Average value Error RMSE Average value Error RMSE
P 547.50 959.95 412.45 1.1238 540.20 7.30 0.5616
T 4.52 4.24 0.28 4.0893 4.70 0.18 2.9605
Tmin -1.18 -0.43 0.75 3.6150 -0.94 0.24 3.4786
Tmax 10.86 9.71 1.15 9.6059 11.07 0.21 8.2661
Figure 1 Comparison of different element data before and after assimilation with the observed data
Figure 2 RMSE of the data before and after assimilation

3 Methods

3.1 Agricultural temperature limits

In Northeast China, generally the first day with temperatures ≥10°C marks the beginning of crop growth and the first frost day marks the end of crop growth. This time period is referred to as the potential growing season. The process to determine the occurrence dates of temperature limits is as follows: take the 5-day moving average (Liu et al., 2013), when the moving average is consistently above 10°C, select the first five consecutive days that have moving average temperatures above 10°C, and then select the first day with temperatures ≥10°C within the 5 days as the initial day. The first frost day is the first day in autumn when the daily minimum temperature is ≤2°C. It is noted that crops can grow and reproduce between the first day with temperatures ≥10°C and the first frost day, this time period is therefore called the potential growing season.

3.2 Assurance rate

Precipitation assurance rate is the probability of precipitation above a certain threshold level. It is widely used in climate analysis for agriculture. The accumulated frequency of precipitation that is higher (or lower) than a certain threshold level is the precipitation assurance rate. For example, 80% precipitation assurance rate means the annual precipitation will be lower than this value only once every five years. It is calculated as follows:
$$P_m=\frac{m}{n+1}\times 100\% \ \ (3)$$
where m is the serial number of all elements ranking from maximum to minimum, n is the sample size and Pm is the assurance rate of the serial number m.

4 Results and discussion

4.1 Future change in heat resources in Northeast China

Heat resources cover five factors in our study, namely, annual average temperature, first day with temperatures ≥10°C, first frost day, potential growing season, and ≥10°C accumulated temperature.
4.1.1 Change in annual average temperature
Compared to the baseline scenario, RCP4.5 and RCP8.5 showed increasing annual average temperatures (Table 2, Figures 3 and 4). Spatially, under RCP4.5, RCP8.5 and baseline scenarios, identical accumulated temperature zones were all moving north, with their areas expanding. Under the RCP4.5 scenario, zones below 0°C were significantly reduced in area, and zones over 12°C emerged in the south, which was absent in baseline. Under RCP8.5, zones below 0°C disappeared entirely, and zones over 12°C expanded to the north significantly.
Under both future RCP4.5 and RCP8.5 scenarios, temperature increased continuously and at a faster rate than baseline. The temperature continued to increase over the entire Songnen Plain area. However, under the baseline scenario, the slope of the annual temperature increase for the entire region was 0.35°C/10a. Compared to the baseline, the temperature increase rate is lower over the entire region at 0.19°C/10a under the RCP4.5 scenario, while under the RCP8.5 scenario, the temperature increase rate is much faster (Table 3), with a slope of 0.48°C/10a.
Table 2 The 80% assurance rate of the annual average of agroclimatic resources from 1961 to 2099
Annual average temperature (°C) First day with temperatures ≥10°C (d) First frost day (d) Potential growing season (d) Accumulated temperature for the growing season (°C·d) Precipitation during the growing season (mm)
Baseline 7.70 128 292 183 3435 608
RCP4.5 9.67 125 294 187 3867 624
RCP8.5 10.66 124 298 193 4127 619
Figure 3 Change in 80% assurance rate of agroclimatic resources in Northeast China from 1961 to 2099
Table 3 Slope percentages of agroclimatic resources with 80% assurance rate from 1961 to 2099 that are statistically significant (%)
Temperature First day with
temperatures ≥10°C		 First frost day Potential growing season Accumulated
temperature		 Precipitation during the growing season
Signifi-
cant		 Highly significant Signifi-
cant		 Highly significant Signifi-
cant		 Highly significant Signifi-
cant		 Highly significant Signifi-
cant		 Highly significant Signifi-
cant		 Highly significant
Baseline 99 98 3 4 43 28 48 26 87 83 0 0
RCP4.5 100 100 76 46 96 93 94 83 100 100 0 0
RCP8.5 100 100 100 100 100 100 100 100 100 100 0 0
Figure 4 Distribution of annual average temperature (a, b, c) and climate slope (d, e, f) with 80% assurance rate in Northeast China
4.1.2 Change in the first day with temperatures ≥10°C in Northeast China
Compared to the baseline scenario, the first day with temperatures ≥10°C under RCP4.5 and RCP8.5 scenarios arrives 3 d and 4 d earlier, respectively. With 80% assurance rate, the first day with temperatures ≥10°C in Songnen Plain region arrived earlier, gradually from south to north (Figure 5). Under the baseline scenario, regions under 100 d concentrated in the south and center of Liaoning Province. Under RCP 4.5 and RCP 8.5 scenarios, these regions increased in area and expanded to the north significantly. Under RCP 8.5, regions under 100 d nearly covered the entire Liaoning Province, while the 100-110 d region covered most of Jilin Province and expanded north to the east of Heilongjiang Province. The region over 130 d accounted for an insignificant portion of Northeast China and mostly occupied areas north of Inner Mongolia.
Figure 5 Spatial distribution of the first day with temperatures ≥10°C (a, b, c) and climate slope (d, e, f) with 80% assurance rate
Under future RCP 4.5 and RCP 8.5 scenarios, the first day with temperatures ≥10°C showed a trend of gradually arriving earlier. The average slope under baseline is -1.02 d/10a. The slopes for RCP 4.5 and RCP 8.5 scenarios are -0.54 d/10a and -1.51 d/10a, respectively. Although the slope for RCP 4.5 was smaller than the baseline slope, the first day with temperatures ≥10°C was still trending earlier. This trend is observed throughout the entire Songnen Plain region. Compared to the baseline scenario, the early arrival trend for the first day with temperatures ≥10°C subsided over the whole region under the RCP4.5 scenario, while the arrival of the first day with temperatures ≥10°C advanced significantly faster over the entire region under RCP 8.5 (Table 3).
4.1.3 Change in the first frost day in Northeast China
Compared to the baseline scenario, under RCP4.5 and RCP8.5 scenarios, the first frost day was delayed by 2 d and 6 d, respectively. With 80% assurance rate, the first frost day in Songnen Plain region was gradually delayed from north to south (Figure 6). The region over 330 d did not exhibit a significant change. The region over 300 d was concentrated in the south and center of Liaoning Province under the baseline scenario, expanding to the north under both RCP4.5 and RCP8.5 scenarios. Under the RCP8.5 scenario, the region over 300 d nearly occupied the entire Liaoning Province, and the 270-280 d region moved north almost out of Jilin Province and was reduced to the north of Heilongjiang Province. The under 280 d region only occupied areas north of the Greater Khingan Mountains and small areas in the north of Inner Mongolia in Northeast China.
Figure 6 Spatial distribution of first frost day (a, b, c) and climate slope (d, e, f) with 80% assurance rate in Northeast China
Under future RCP4.5 and RCP8.5 scenarios, the first frost day in Songnen Plain region was gradually delayed with a slope lower than the baseline (1.78 d/10a). The slopes under RCP4.5 and RCP8.5 scenarios are 0.75 d/10a and 1.43 d/10a, respectively. The delay rate of the first frost day under RCP4.5 decreased significantly over time, while the decrease of the delay rate was insignificant under RCP8.5. While the slopes under RCP4.5 and RCP8.5 scenarios were lower compared to the baseline, the first frost day in Songnen Plain region still trended late from 1960 to 2099.
4.1.4 Change in potential growing season in Northeast China
Compared to the baseline scenario, growing seasons under RCP4.5 and RCP8.5 scenarios were lengthened by 4 d and 10 d, respectively. As shown in Figures 7a, 7b and 7c, under both RCP4.5 and RCP8.5 scenarios, regions with all lengths of growing season expanded towards the north, with the expansion being greater in scale under RCP8.5. Under the RCP8.5 scenario for instance, regions with a growing season over 200 d nearly covered the entire Liaoning Province, while it only covered areas south of Liaoning Province under the baseline scenario. The region with a growing season of 180-200 d expanded north to southwest and east of Heilongjiang Province, while no such region existed in Heilongjiang Province under baseline. The region with a growing season of 140-200 d shrank significantly, and only existed in areas north of Inner Mongolia and northwest of Heilongjiang Province; it occupied the majority of northern Inner Mongolia and significant areas in northwest of Heilongjiang Province under the baseline scenario.
Furthermore, under future RCP4.5 and RCP8.5 scenarios, the growing season showed a lengthening trend throughout the entire region (Figure 7d, 7e and 7f). The average slopes under baseline, RCP4.5 and RCP8.5 scenarios are 2.81 d/10a, 1.30 d/10a and 2.95 d/10a, respectively. The slope under the RCP8.5 scenario is larger than the baseline scenario. The slope under RCP4.5 is relatively small, yet it showed a lengthening trend over the entire Songnen Plain region.
Figure 7 Spatial distribution of growing season length (a, b, c) and climate slope (d, e, f) with 80% assurance rate in Northeast China
4.1.5 Changes in ≥10°C accumulated temperature in Northeast China
Compared to the baseline scenario, the ≥10°C accumulated temperature increased significantly under RCP4.5 and RCP8.5 scenarios, with annual increments of 400°C·d and 700°C·d, respectively (Figure 8). Under future RCP4.5 and RCP8.5 scenarios, regions with highly accumulated temperature levels expanded significantly towards the north. Low accumulated temperature level regions shrank significantly. The RCP8.5 scenario showed the highest increase in accumulated temperature. Under the baseline scenario, the region with accumulated temperature over 4000°C·d only occupied a small area in the south of Liaoning Province. Under the RCP4.5 scenario, it covered the majority of the areas in Liaoning Province. And under the RCP8.5 scenario, it covered Liaoning Province entirely and expanded to the west of Jilin Province and south of Inner Mongolia. Under the baseline scenario, accumulated temperature in most of Heilongjiang Province was 2000-2500°C·d. Under future RCP4.5 and RCP8.5 scenarios, the accumulated temperatures over the region shifted to 3000-3500°C·d and 3500-4000°C·d, respectively. The region with accumulated temperature less than 2000°C·d completely disappeared under the two future scenarios RCP4.5 and RCP8.5, and the area of the region with accumulated temperature at 2000-2500°C·d decreased significantly.
Under both of the future scenarios RCP4.5 and RCP8.5, the ≥10°C accumulated temperature exhibited an increasing trend in Northeast China. The slopes for baseline, RCP4.5 and RCP8.5 scenarios are 69°C·d/10a, 41°C·d/10a and 106°C·d/10a, respectively. The trend manifested as an increase in accumulated temperature over the entire region, and the increment was the highest under the RCP8.5 scenario.
Figure 8 Spatial distribution of ≥10°C accumulated temperature (a, b, c) and climate slope (d, e, f) with 80% assurance rate in Northeast China

4.2 Future change in water resource in Northeast China

Compared to the baseline scenario, precipitation under RCP4.5 and RCP8.5 scenarios showed a slight increase of 16 mm and 9 mm, respectively (Figure 9). Under the three scenarios, the spatial distribution of precipitation was essentially the same, and exhibited a gradual decreasing trend from southeast to northwest, with local variations. For example, under RCP8.5, the region with 300-400 mm precipitation increased in area size but decreased in average precipitation in the southwest region. Precipitation in eastern Heilongjiang Province showed an increase, from the baseline scenario level of 400-500 mm to 500-600 mm. Precipitation also increased at the southern boundary between Heilongjiang and Jilin provinces.
The slopes for average precipitation in growing season under RCP4.5 and RCP8.5 were 3.47 mm/10a and 6.51 mm/10a, respectively. Both were higher than the -5.93 mm/10a under the baseline scenario, and showed an increasing trend. In the future Northeast China, precipitation is projected to increase overall, but not at a significant level. The increment is faster in the eastern region, with the fastest increase occurring along the coastal areas, mainly around Liaodong Peninsula. Under the RCP4.5 scenario, Inner Mongolia and a part of Jilin Province showed a declining trend in precipitation. Under the RCP8.5 scenario, the only region with declining precipitation was around the Greater Khingan Mountains.
Figure 9 Spatial distribution of precipitation in growing season (a, b, c) and climate slope (d, e, f) with 80% assurance rate in Northeast China

5 Conclusions

(1) From 1961 to 2099, influenced by climate change, the heat resource is projected to increase significantly, with a spatial distribution of higher in the south and lower in the north. The average temperature in Northeast China is trending higher, with temperature increments of 2°C and 3°C under low emission scenario RCP4.5 and high emission scenario RCP8.5, respectively. The first day with temperatures ≥10°C arrived 3-4 d earlier and the first frost day was delayed by 2-6 d, leading to a 4-10 d increase in the potential growing season length.
The temperature increase and lengthening of the growing season significantly increased the accumulated temperature. By the end of this century, the increment is projected to be 400 to 700°C·d.
The significance tests for the slopes of heat resources in response to climate, temperature and accumulated temperature showed good results under the baseline scenario, with more than 80% of the data passing the significance test. The percentage of data that passed the significance test for the first frost day and potential growing season was 40%-50%. The percentage for the first day with temperatures ≥10°C that passed the significance test was the lowest. Under future RCP4.5 and RCP8.5 scenarios, heat resources passed the test at a higher percentage, with a 100% pass rate for all heat resources under the RCP8.5 scenario.
The slope of heat resource variation changed significantly. The rate of temperature increase was faster under the high emission scenario. The slopes for RCP4.5 and RCP8.5 were 0.19/10a and 0.48/10a, respectively, with even faster temperature increases in the north. The slopes for the first day with temperatures ≥10°C were -0.54 d/10a and -1.51 d/10a, respectively, with the slope greater in the eastern and western regions. The slopes for the delay of first frost day were 0.75 d/10a and 1.43 d/10a, respectively, with the delay being more prominent in the west and north. The slopes for potential growing season length were 1.30 d/10a and 2.95 d/10a, respectively.
(2) From 1961 to 2099, under different future scenarios, the rate of change for agroclimatic resources showed variations. Compared to baseline, the increase in heat resources was faster and more prominent under the RCP8.5 scenario with unlimited emission. In comparison, the increase was slower under the RCP4.5 scenario.
(3) Water resource showed an increasing trend, but not at a significant level. From the yearly projections, precipitation will fluctuate significantly, with increasing frequency of extreme precipitation events. The range of fluctuation changed from 450-800 mm to 400-950 mm. While the average precipitation is projected to increase in the future, the increase is insignificant. RCP4.5 scenario showed the highest increase in precipitation at 16 mm, and the increment is less than 3%. In summary, Northeast China is projected to change towards warmer and more humid conditions in the future, with significant increases in heat resources.

6 Discussion

(1) The impact of future climate change on agroclimatic resources will have a direct impact on agricultural production. Therefore, accurate analysis of the change in agroclimatic resources will be of significant importance to guiding agricultural production. Employing scenario-based climate data to analyze the impact of future climate change on agriculture has become a commonly used method to investigate the impact of future climate change on agriculture. As a result, scenario-based climate data are of crucial importance. Previously, IPCC’s future scenarios were constructed based on greenhouse gases, suspended particulate matter, etc., with the same emission rate in all climate models. This yielded some limitations (Han et al., 2014). The latest RCPs proposed in the IPCC AR5 improved upon the scenario structure. The RCPs are based on atmospheric radiation, and take different emission policies into account to define criteria for temperature change. The process is more scientific and logical. This study was based on climate data under RCP scenarios, which makes the results more reliable.
(2) We used the AR5 scenarios to analyze the impact of climate change on agroclimatic resources in Northeast China. The results are in agreement with previous studies. By 2050, the average annual accumulated temperature increment is 205°C·d, which matched well with conclusions reported by Hu Yanan and Liu Yingjie (2013) that showed an accumulated temperature increment of around 200°C·d in Northeast China using analysis based on RCP4.5. From 2071 to 2099, under the RCP4.5 scenario, the ≥10°C accumulated temperature in Liaoning Province fluctuates between 3900 and 4500°C·d, with a mean of 4200°C·d. Under the RCP8.5 scenario, the ≥10°C accumulated temperature is 4300-5000°C·d, with a mean of 4694°C·d. Results of this study were comparable with findings reported by Yuan Bin et al. that the accumulated temperature of Liaoning Province will increase by 4000-5000°C·d. From 2011 to 2050, the first frost day was delayed by 2 d under the RCP4.5 scenario and precipitation during the growing season fell by 12 mm, which matched with results reported by Liu Jingli et al. (2012) using B2 scenario analysis.
(3) Climate change as represented by rising temperatures has certain positive impacts on agriculture in Northeast China. The expansion of the growing season and the increment of accumulated temperature deliver more usable heat resources to crops. Regions that were previously inarable because of limited heat resources will shrink. Arable regions will expand and crop breed variety will increase. Regions where early mature varieties are planted will now be able to grow mid-late mature varieties, and regions capable of growing late mature varieties will expand. For example, corn, a late mature variety, requires an accumulated temperature of 3000°C·d (Xu, 2014), and its growing region can expand from the current Songnen Plain region to the north, up to areas around the Greater Khingan Mountains. In some parts of Liaoning Province, it may even be possible to plant varieties that can be harvested twice per year.
Yet, the negative impacts of climate change cannot be overlooked. Assuming that crop yield is not enhanced by technological developments and that the accumulated temperature requirement for each crop is unchanged within the growing season, the growing season will get shorter as the temperature accumulation gets faster with climate change. As a result, the dry mass accumulation period for crops will shrink, and thus lead to a reduction in overall yield. Liu Dan et al. (2013) found that the number of empty corn kernels increased when the temperature increased by 2°C under laboratory conditions, which led to a 40% reduction in yield. Additionally, water stress caused by the mismatch between temperature and precipitation will also potentially lead to reduced yield. Ma Shuqing et al. (2008) found that in regard to crop yield, the negative impact of water reduction outweighed the positive impact of temperature increases.
(4) In this study, we assimilated the output of climate model data with recorded historical data. Compared to traditional methods that only used modeling output data, data assimilation assured the rationality and consistency of the historical recorded data and the future modeling data. The resulting new time series thus closely approximates real climate conditions.
(5) The scenario data used in this study are the output of a regional climate model. The climate model takes various factors into consideration, in particular, using data assimilation to reduce systematic errors in the simulation. However, the variable nature of climate change adds inherent uncertainties to the future scenario data.

The authors have declared that no competing interests exist.

References

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DOI

[2]
Dai Shuwei, Yang Xiaoguang, Zhao Menget al., 2011. Changes of China agricultural climate resources under the background of climate change II: Spatiotemporal change characteristics of agricultural climate resources in Southwest China.Chinese Journal of Applied Ecology, 22(12): 3177-3188. (in Chinese)Based on the 1961-2007 ground surface meteorological data from 558 meteorological stations in China, this paper analyzed the differences of agricultural climate resources in China different regions, and compared the change characteristics of the agricultural climate resources in 1961-1980 (periodⅠ) and 1981-2007 (period Ⅱ), taking the year 1981 as the time node. As compared with period Ⅰ, the mean annual temperature in China in period Ⅱ increased by 0.6 ℃, and the ≥ 0 ℃ active accumulated temperature in the growth periods of chimonophilous crops and the ≥ 10 ℃ active accumulated temperature in the growth periods of thermophilic crops increased averagely by 123.3 ℃·d and 125.9 ℃·d, respectively. In 1961-2007, the mean annual temperature increased most in Northeast China, and the ≥ 10 ℃ active accumulated temperature in the growth periods of thermophilic crops increased most in South China. The whole year sunshine hours and the sunshine hours in the growth periods of chimonophilous crops and of thermophilic crops in period Ⅱ decreased by 125.7 h, 32.2 h, and 53.6 h, respectively, compared with those in periodⅠ.In 1961-2007, the annual sunshine hours decreased most in the middle and lower reaches of Yangtze River,while the sunshine hours in the growth periods of chimonophilous crops and of thermophilic crops decreased most in North China and South China, respectively.In the whole year and in the growth periods of chimonophilous and thermophilic crops, both the precipitation and the reference crop evapotranspiration in this country all showed a decreasing trend, with the largest decrement in the precipitation in the whole year and in the growth periods of chimonophilous and thermophilic crops in North China, the largest decrement in the reference crop evapotranspiration in the whole year and in the growth periods of thermophilic crops in the middle and lower reaches of Yangtze River, and the largest decrement in the reference crop evapotranspiration in the growth periods of chimonophilous crops in Northwest China. In 1961-2007, the climate in China in the whole year and in the growth periods of thermophilic crops showed an overall tendency of warm and dry, and the climate in the growth periods of thermophilic crops became warm and dry in Southwest China, North China, and Northeast China, but warm and wet in the middle and lower reaches of Yangtze River, Northwest China, and South China, whereas the climate in the growth periods of chimonophilous crops became warm and dry in North China, but became warm and wet in Northwest China.

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[3]
Füssel H M, Klein R J T, 2006. Climate change vulnerability assessments: An evolution of conceptual thinking.Climatic Change, 75(3): 301-329.

[4]
Gou Shiwei, Zhang Yingxian, Xu Yinlong, 2012. Analysis of climate resource changes during maize growth period in Ningxia under SRES A1B scenario.Chinese Journal of Eco-Agriculture, 20(10): 1394-1403. (in Chinese)Maize is one of the three main food crops in Ningxia and is widely cultivated in central arid and south mountain zones; where maize is mainly cultivated under rain-fed conditions and with significant influence of climatic conditions. Climate change has adversely affected local agricultural production in Ningxia and several other studies have reported even further adversities under SRES A2 and B2 scenarios. Also climate change has reportedly led to temperature and precipitation anomalies in Ningxia. This study therefore analyzed the impact of future climate change on maize production under moderate emission scenario. The analysis was based on revised data of the PRECIS regional climate model simulation under SRES A1B scenario. The data included changes in average temperature, maximum temperature, minimum temperature, ≥10 ℃ effective accumulated temperature and precipitation for the periods from April to September of 2011-2040 (for the 2020s), 2041-2070 (for the 2050s), 2071-2100 (for the 2080s) and 1961-1990 (the baseline period of climate). In the first step, the study analyzed the distribution of climatic factors in Ningxia for the baseline period and compared that with observed data for the same period. This was followed by distribution and variation analysis of 5 climatic factors for the 2020s, 2050s and 2080s under A1B scenario. These future values minus those of the baseline period yielded the changes in the climatic factors, where precipitation was specifically expressed in anomaly percent. In the final step, climate change during maize growth period was discussed for the future scenarios. The results showed that simulated average temperature, maximum temperature, minimum temperature and ≥10 ℃ effective accumulated temperature were generally lower than the observation values. However, the simulated distributions were similar to the actual situation; i.e., temperatures were high in the north and low in the south. Also while simulated precipitations for relatively large regions were higher than observation values, the simulated and observed precipitation distributions were similar. Overall, the simulated climatic factors reflected the observed conditions in Ningxia. Average temperature, maximum temperature, minimum temperature, ≥10 ℃ effective accumulated temperature and precipitation for the 2020s, 2050s and 2080s were higher than those of the baseline period and the gaps also widened with time. In south Ningxia, maximum temperature intensely increased while average temperature, minimum temperature and ≥10 ℃ effective accumulated temperature more or less increased in north Ningxia under the scenario simulations. Also precipitation increased in the north and decreased in the south of Ningxia under the scenario simulations. The future scenario analysis showed that maximum temperature and precipitation respectively increased and fluctuated with high likelihoods of extreme hot weathers, droughts and floods. Climate change in the future scenario facilitated maize production in the north irrigation zone of Ningxia, especially increase in ≥10 ℃ effective accumulated temperature provided additional heat for higher maize production. In the south mountain zone of Ningxia, however, limited precipitation negatively affected rain-fed production of maize despite any positive effect of increased temperature on maize production. This paper put forward and discussed appropriate countermeasures for crops production in the rain-fed condition.

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[5]
Han Leqiong, Han Zhe, Li Shuanglin, 2014. Projection of heavy rainfall events in the middle and lower reaches of the Yangtze River valley in the 21st century under different representative concentration pathways.Transactions of Atmospheric Sciences, 37(5): 529-540. (in Chinese)This paper evaluates the future projection of heavy rainfall events in the middle and lower reaches of the Yangtze River valley based on outputs of eight coupled models attending the Coupled Model Intercomparison Project phase 5( CMIP5) from IPCC AR5. The experiments under different representative concentration pathways( RCPs) are compared with each other,and with the previous CMIP3 experiments as well. The outputs from the historical simulation of CMIP5 are also utilized as a base to derive future trends. The results suggest an agreement among all the CMIP5 models,in that both the strength and the occurrence frequency of heavy rainfall events are projected to increase in the 21 st century relative to the last twenty years of the 20 th century(1980-1999). In contrast,the strength increase in the east of the re-gion is even greater than that in the west. Besides,the interannual variability of heavy rainfall events is also projected to enhance in the future. As for different RCPs,the projected increases in the strength and occurrence frequency of heavy rainfall events in RCP2. 6 and RCP8. 5 are greater than those in RCP4. 5. In comparison to CMIP3,the projected increases in the strength and occurrence frequency are even larger,albeit a significant difference in the spatial distribution in the latter projection. The projected maximum increase in the rainfall amplitude in CMIP3 is located in the central region,while it is in the east of the region in CMIP5.

[6]
Hu Yanan, Liu Yingjie, 2013. Planting distribution of spring maize and its productivity under RCP4.5 scenario in Northeast China in 2011-2050.Scientia Agricultura Sinica, 46(15): 3105-3114. (in Chinese)Objective】The study was aiming at the response of planting suitable areas for spring maize，its growth period and production to climate change. 【Method】 Based on the daily climate data of RCP4.5 scenario calculated by the regional climate model RegCM4 in Northeast China in 2011-2050, the empirical frequency method was used to predict the changes of planting area under 80% guaranteed rate for early maturity, mid-maturity and late maturity spring maize varieties, combined with crop model DSSAT4.5 to evaluate the changes of growth period and yield, and the planting suitability at the area expanded by climate change for late maturity spring maize in Heilongjiang province in the future. 【Result】 The ≥10℃ accumulated temperature showed an increasing trend in Northeast China. The planting northern boundary of different maize varieties will be moved northward or eastward at different degrees and the probable cultivation region will be larger than before. It is suitable for late maturity variety to grow at the expanded region in Heilongjiang province in 2011-2050. The impact of climate change on reproduction growth period is going to be bigger than the vegetation growth period for late maturity variety in this following 40 years in the original planting area, which was existed in 1981-2010 in Heilongjiang province, and the whole growth period will be shortened by 2-11 days. Meanwhile, the changes of yield in the future compared with present level will have a significant spatial difference. Yield change range will be both in ±20% with considering the CO2 fertilizer effect or not, but the yield of the considered one is higher. 【Conclusion】Planting suitability of the expanded region due to climate change needs to be evaluated with many factors contained for maize. The whole growth stage change of maize is mainly caused by the shortened reproduction growth of maize. The effects of CO2 concentration enrichment in air will counterbalance a part of disadvantage of increased temperature for maize yield.

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[7]
Li Qiang, 2012. The drought characteristics and its mechanism in the main arid regions of the globe in the background of global warming [D]. Lanzhou: Lanzhou University. (in Chinese)

[8]
Li Yong, Yang Xiaoguang, Dai Shuweiet al., 2010a. Spatiotemporal change characteristics of agricultural climate resources in middle and lower reaches of Yangtze River.The Journal of Applied Ecology, 21(11): 2912-2921. (in Chinese)The period 1961-2007 was divided into two by the time node of year 1981,and the change characteristics of the agricultural climate resources both in period Ⅰ(1961-1980) and in period Ⅱ(1981-2007) were analyzed and compared.The results showed that under the background of global warming,the average climatic trend rate of ≥10 ℃ accumulated temperature in the middle and lower reaches of Yangtze River in temperature-defined growth season during 1961 2007 was 74 ℃·d·10 a-1,and the ≥10 ℃ accumulated temperature in period Ⅱ was 124 ℃· d higher than that in period I.Comparing with that in period I,the safe planting boundary of double cropping rice in period Ⅱ moved 0.79° northward.In 1961-2007,the precipitation in temperature-defined growth season had an overall increasing trend.Comparing with those in period I,the precipitation and the area of ≥767 mm precipitation(water requirement for normal growth of double cropping rice) in period II were increased by 1.6% and 1.13 × 104 km2,respectively.The average sunshine hour in temperature-defined growth season in period II was reduced by 8.1%,comparing with that in period I.In recent 47 years,about 91.1% stations in the reaches showed a decreasing trend in sunshine hours.Comparing with that in period I,the reference crop evapotranspiration in temperature-defined growth season in periodⅡshowed a slightly decreasing trend,and its low value region expanded while its high value region narrowed.The beginning date of daily temperature over 10 ℃ was averagely 2 days earlier in periodⅡthan that in period I,while the ending date was in reverse.The ending date of daily temperature over 22 ℃ was almost the same in periods Ⅰ and Ⅱ.

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[9]
Li Yong, Yang Xiaoguang, Wang Wenfenget al., 2010b. Change of China agricultural climate resources under the background of climate change I: Spatiotemporal change characteristics of agricultural climate resources in South China.The Journal of Applied Ecology, 21(10): 2605-2614. (in Chinese)Abstract Based on the 1961-2007 observation data from 66 meteorological stations in the sub-humid and warm-temperate irrigated wheat-maize agricultural area of Huang-Huai-Hai Plain, this paper analyzed the spatiotemporal change characteristics of agro-climate resources for chimonophilous and thermophilic crops in the area in 1961-1980 and 1981-2007. The analyzed items included the length of temperature-defined growth season and the active accumulative temperature, sunshine hours, precipitation, reference evapotranspiration, and aridity index during the temperature-defined growth season. With climate warming, the length of temperature-defined growth season of chimonophilous and thermophilic crops in the area in 1981-2007 extended by 7. 4 d and 6. 9 d, and the > or = 0 degrees C and > or = 10 degrees C accumulative temperature increased at a rate of 4.0-137.0 and 1.0-142.0 degrees C d (10 a)(-1), respectively, compared with those in 1961-1980. The sunshine hours during the temperature-defined growth season of the crops decreased markedly; and the precipitation during the temperature-defined growing season decreased in most parts of the area, being obvious in Hebei and north Shandong Province, but increased in north Anhui and southeast Henan Province. In most parts of the area, the reference evapotranspiration of chimonophilous and thermophilic crops during their temperature-defined growth season decreased, and the aridity index increased.

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[10]
Lin Xiaosong, 2003. Research progress in the agroclimatic resources.Journal of Hainan Normal University, 16(4): 87-91. (in Chinese)Agroclimatic resources is one of the important factors affecting agricultural produce. This paper aims to expound on the research progress in the agroclimatic resources in terms of the distributing regulation, the layout of main farm crops, the simulation of productive potentiality, the quantitative evaluation and the information management and analysis.

[11]
Liu Dan, Zhang Jiahua, Meng Fanchaoet al., 2013. Effects of different soil moisture and air temperature regimes on the growth characteristics and grain yield of maize in Northeast China.Chinese Journal of Ecology, 32(11): 2904-2910. (in Chinese)It is an indisputable fact that climate change has affected crop growth and development. In order to predict the possible effects of future climate change on C4 plant maize and to test the simulated results of crop model, an infrared temperatureincreasing simulation experiment was conducted in Jinzhou of Liaoning Province, Northeast China. With the applications of free air temperatureincreasing system and water control devices, different soil moisture and air temperature gradients were installed to simulate the effects of climate change on maize growth. The results showed that increasing temperature alone decreased the plant height by 6.5%, while increasing both temperature and soil moisture had little effects on the plant height. Increasing temperature decreased the leaf area by 13.8%, while increasing soil moisture had little effect. Both increasing temperature and increasing soil moisture were unfavorable to the dry matter accumulation, but the difference with the control was not significant. Increasing temperature had positive effects on the leaf distribution coefficient, but increasing soil moisture was in reverse. Increasing both temperature and soil moisture had no obvious effects on the leaf distribution coefficient. Increasing temperature decreased the grain yield by 40%, mainly due to the decrease of ear length, ear diameter, rows per ear, and full grain number and the increase of shriveled grain number.

[12]
Liu Jingli, Ji Yanghui, Mi Naet al., 2012. Evolvement character of agricultural climate resources in Liaoning province from 2011 to 2050 based on B2 climate change scenarios.Journal of Meteorology & Environment, 28(6): 81-87. (in Chinese)Based on the output data of the regional climate model PRECIS,the temporal and spatial evolvement characteristics of agricultural climate resources considering future climate change scenarios of B2(2011-2050)in Liaoning province were investigated by the methods of a time series analysis and a spatial analysis.The results indicate that the increasing trend of radiation resources is not significant,but has a peak value from 2031 to 2040.Precipitation is in a decreasing trend during the growing season,and the changes of radiation resource and precipitation are contrary.The decreasing amplitude of precipitation increases from the west to the east,and reaches 20 mm/decade in the east of Liaoning province.Precipitation is indicative to flood and drought events in the different periods.The accumulated temperature(≥10 ℃)is in an obvious increasing trend,and its increasing amplitude is 100 ℃ · d/decade in most of Liaoning province.The beginning date of frost is delayed 1-3 days in the east of western Liaoning province and the west of northern Liaoning province,while the ending date of frost is advanced in about 1-2 days in the north and the east of Liaoning province.The changes of the beginning and ending dates make frost-free season are prolonged,and it suggests that the thermal resource will increase obviously in future 40 years,which will provide the references for the adjustment of agricultural planting structure in order to respond to climate change.

[13]
Liu Zhijuan, Yang Xiaoguang, Wang Wenfenget al., 2009. Characteristics of agricultural climate resources in three provinces of Northeast China under global climate change.The Journal of Applied Ecology, 20(9): 2199-2206. (in Chinese)Based on the 1961-2007 weather data from 72 meteorological stations in three provinces of Northeast China,the change characteristics of agricultural climatic factors including yearly and temperature-defined growing season's mean air temperature,≥10 ℃ accumulated temperature,precipitation,reference evapotranspiration,and sunshine hours were analyzed.In 1961-2007,the yearly mean air temperature in the three provinces had an increasing trend,with a rate of 0.38 ℃·10 a-1.The ≥10 ℃ accumulated temperature in temperature-defined growing season also had an increasing trend,and the border of ≥10 ℃ accumulated temperature belt moved northward and eastward.The area of ≥3200 ℃·d accumulated temperature increased by 2.2×104 km2.The belt of 2800-3200 ℃·d moved northward about 0.85° and eastward about 0.67°,while that of 2400-2800 ℃·d moved northward about 1.1°.The sunshine hours decreased significantly,especially in the east part of Songnen Plain,central and west plains of Jilin Province,and west part of Liaohe River Plain.The area with sunshine hours 2800 h decreased from 13.6×104 km2 to 4.1×104 km2,and the zone with sunshine hours 2600-2800 h moved westward about 1.5°.The average sunshine hour in temperature-defined growing season was 1174 h.Comparing with that in 1961-1980,the region with more sunshine hours in temperature-defined growing season in 1981-2007 narrowed significantly,and the zone with sunshine hours 1200-1400 h moved westward about 0.9°.In 1961-2007,both the yearly and the temperature-defined growing season's precipitation decreased,and the yearly reference evapotranspiration increased in Heilongjiang Province and in the eastern mountain areas of Jilin Province but decreased in the central and west plains of Jilin Province and in Liaoning Province.Comparing with that in 1961-1980,the zone of reference evapotranspiration with the value of ≥900 mm in 1981-2007 moved westward about 1°,and the reference evapotranspiration in temperature-defined growing season increased in most regions of Heilongjiang and Jilin Province but decreased in a rate of 0-14 mm·10 a-1 in most regions of Liaoning Province.

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[14]
Ma Shuqing, Wang Qi, Luo Xinlan, 2008. Effect of climate change on maize growth and yield based on stage sowing.Acta Ecologica Sinica, 28(5): 2131-2139. (in Chinese)The experiment of sowing by stages can develop different conditions of climate change for maize(Zea mays) growth in natural fields.Using method of statistic analyses,effect of climate change on maize growth and yield was researched according to 6 years' data of the experiment of sowing by stages in the middle of the maize belt of the Northeast China.Here climate change indicated mainly changes of temperature and humidity.The seedling emergence rate,growth rate,filling process,and accumulation of dry matter were indications of the situation of maize growth.Changes of air temperature and humidity can influence obviously vegetative and reproductive growth and production of maize.Under the conditions of normal moisture,if air temperature rises 1鈩,there will be 3 days ahead of time in sprouting stage of maize;about 6 days and 4 days will be reduced during the period of seedling emergence to tasseling stage and tasseling to mature stage respectively;the seedling emergence rate and growth rate after sprouting stage will increase by 17%.If relatively cumulative temperature increases by 10%,relative dry weight of 100 grains of maize will increase by 13%.However,filling time will shorten obviously and grain weight will lighten if air humidity is low during filling period.If cumulative temperature of main growing season increases by 100 鈩兟穌,per unit area yield of maize will increase by about 6.3%;and if mean temperature rises 1 鈩 during the period of tasseling to mature stage,per hectare yield of maize will increase by about 550 kg;but if aridity index increases 0.1 during the same time,per hectare yield will decrease about 860 kg.When temperature is above 22 鈩 during the period of tasseling to mature stage,if aridity index is between 0.75 and 0.9,maize yield will reach to the maximum,that means that cooperation between higher temperature and larger humidity is favorable to maize filling and mature and yield increase.Under the conditions of suitable moisture,climate warming speeds up maize development and filling and makes biomass increase,so that per unit area yield of maize increases;however,climate drying limits use of heat resources,shortens maize filling time and rate,and decreases weight of 1000 grains of maize in growth season of the Northeast China,so that maize yield decreases.In the future,under the conditions of climate warming and suitable moisture,planting area of late maize should be expanded and the maize belt should extend to the north and the east of the Northeast China,per unit area yield and ultimate production of maize will increase.But trend of climate warming and drying would result in more serious and frequent drought of main planting area of maize in the middle and the west of the Northeast China,which will bring about maize yield decrease and uncertainty and threaten seriously future development of maize production.So,to enhance comprehensive defense of agricultural drought is prerequisite for to suit future climate warming and drying and spread middle-late and late variety of maize.

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[15]
Ma Yuping, Sun Linli, E Youhaoet al., 2015. Predicting the impact of climate change in the next 40 years on the yield of maize in China.The Journal of Applied Ecology, 26(1): 224-232. (in Chinese)Abstract Climate change will significantly affect agricultural production in China. The combination of the integral regression model and the latest climate projection may well assess the impact of future climate change on crop yield. In this paper, the correlation model of maize yield and meteorological factors was firstly established for different provinces in China by using the integral regression method, then the impact of climate change in the next 40 years on China's maize production was evaluated combined the latest climate prediction with the reason be ing analyzed. The results showed that if the current speeds of maize variety improvement and science and technology development were constant, maize yield in China would be mainly in an increasing trend of reduction with time in the next 40 years in a range generally within 5%. Under A2 climate change scenario, the region with the most reduction of maize yield would be the Northeast except during 2021-2030, and the reduction would be generally in the range of 2.3%-4.2%. Maize yield reduction would be also high in the Northwest, Southwest and middle and lower reaches of Yangtze River after 2031. Under B2 scenario, the reduction of 5.3% in the Northeast in 2031-2040 would be the greatest across all regions. Other regions with considerable maize yield reduction would be mainly in the Northwest and the Southwest. Reduction in maize yield in North China would be small, generally within 2%, under any scenarios, and that in South China would be almost unchanged. The reduction of maize yield in most regions would be greater under A2 scenario than under B2 scenario except for the period of 2021-2030. The effect of the ten day precipitation on maize yield in northern China would be almost positive. However, the effect of ten day average temperature on yield of maize in all regions would be generally negative. The main reason of maize yield reduction was temperature increase in most provinces but precipitation decrease in a few provinces. Assessments of the future change of maize yield in China based on the different methods were not consistent. Further evaluation needs to consider the change of maize variety and scientific and technological progress, and to enhance the reliability of evaluation models.

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[16]
Solomon S, 2007. Working Group 1 Contribution to the IPCC Fifth Assessment Report: Climate Change 2013: The Physical Science Basis.What is happening to the climate? Climate Change 2007-The Physical Science Basis is the most comprehensive and up-to-date scientific assessment of past, present and future climate change. This report has been produced by some 600 authors from 40 countries, over 620

[17]
Tang Guoping, Li Xiubin, Fischer Get al., 2000. Climate change and its impacts on China’s agriculture.Acta Geographica Sinica, 55(2): 129-138. (in Chinese)Though analyze the potential impacts of global climate change on China's agriculture, the meaningful reference for China's agriculture in the future can be shown. First, according to the historical meteorological data from 310 climatological stations during 1958~1997, the baseline climate in China is analyzed. Then, three general circulation models, i.e., HadCM2, CGCM1 and ECHAM4 are chosen and meanwhile six climate change scenarios constructed. Three models above are used to simulate China's climate changes under different scenarios for three periods 2020s, 2050s and 2080s. Under three model runs, air temperature is expected to increase in all regions of China. For example, under HadCM2 GX scenario, annual mean air temperature will increase 1.5鈩, 2.5鈩 and 3.8鈩 in 2020s, 2050s, 2080s respectively. In addition, the increasing magnitude of air temperature in high latitude area is larger than that in low latitude area, and in inland area larger than that in coastal area. Finally, based on three GCMs results, an explicit geographic model, i.e., the AEZ model developed and improved at IIASA, is applied to assess the impacts of climate change on China's agricultural land productivity. The impact assessment mainly focuses on the changes of multi cropping index, land productivity, arable land area and total potential cereal production. The findings show: (1) The average magnitude of increase in multi cropping index is larger in the southwest, central and north of China than that in the northwest and south of China. (2) Due to climate change, the increasing temperature and rainfall in the northeast, northwest and plateau of China has a positive influence on their arable land area and total potential cereal production. Conversely, the increasing temperature and decreasing rainfall in the southeast, central and southwest of China has a negative influence on their arable land area and potential cereal production. For whole China, arable land area is projected to increase in a new climate condition. The changing scope of arable land area varies from 2 5% to 16 2% under irrigated and rain fed condition, and from 2 3% to 18 0% under rain fed condition. (3) Climate change affects land productively in northeastern China positively. However, it has a negative influence on land productively in southwestern China and Tibet. On the average, climate change affects land productivity in China negatively. The decreasing scope changes from 1.5% to 7.0% under irrigated and rain fed condition, and from 1.1% to 12.6% under rain fed condition.

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[18]
Wu Haiyan, Sun Tiantian, Fan Zuoweiet al., 2014. The major food crops in response to climate change and its yield effect in Northeast of China.Journal of Agricultural Resources & Environment, (4): 299-307. (in Chinese)This article reviewed the effect of climate changes on the variation of agricultural climate resources, characteristics of agricultural disaster and the response of the main crops in Northeast China under the condition of global warming. The results showed that there were advantages and disadvantages to the effects of climate warming on agriculture of China. The growing temperature in main crop season in North-east China, the increasing of heat resources, the extended growth period and the expansion of region suitable for crop, which were potential possible for raising the output of crop production and light-temperature potential productivity. Because of the light and the limitation of water resources and the increase of CO2 concentration which were caused by the greenhouse effect, the yield and quality of the crop had a negative effect. With extreme weather events increasing, agricultural ecological environment deterioration, drought, flood and waterlogging, salinization speed, the most obvious effect was drought disaster in Northeast China, especially for the effect of global warming in recent years. With the to-tal amount of precipitation reduction and precipitation uneven distribution, the Northeast China became one of the most sensitive and vulner-able areas affected by climate change.

[19]
Xu Yanhong, 2014. Evaluation on the effect of adaptation countermeasures of maize on climate resources utilization in Northeast China under climate change [D]. Beijing: Chinese Academy of Meteorological Sciences. (in Chinese)

[20]
Yang Xiaoguang, Li Yong, Dai Shuweiet al., 2011. Changes of China agricultural climate resources under the background of climate change IV: Spatiotemporal change characteristics of agricultural climate resources in sub-humid warm-temperate irrigated wheat-maize agricultural area of Huang-Huai-Hai Plain.Chinese Journal of Applied Ecology, 22(12): 3177-3188. (in Chinese)Based on the 1961-2007 ground surface meteorological data from 558 meteorological stations in China, this paper analyzed the differences of agricultural climate resources in China different regions, and compared the change characteristics of the agricultural climate resources in 1961-1980 (periodⅠ) and 1981-2007 (period Ⅱ), taking the year 1981 as the time node. As compared with period Ⅰ, the mean annual temperature in China in period Ⅱ increased by 0.6 ℃, and the ≥ 0 ℃ active accumulated temperature in the growth periods of chimonophilous crops and the ≥ 10 ℃ active accumulated temperature in the growth periods of thermophilic crops increased averagely by 123.3 ℃·d and 125.9 ℃·d, respectively. In 1961-2007, the mean annual temperature increased most in Northeast China, and the ≥ 10 ℃ active accumulated temperature in the growth periods of thermophilic crops increased most in South China. The whole year sunshine hours and the sunshine hours in the growth periods of chimonophilous crops and of thermophilic crops in period Ⅱ decreased by 125.7 h, 32.2 h, and 53.6 h, respectively, compared with those in periodⅠ.In 1961-2007, the annual sunshine hours decreased most in the middle and lower reaches of Yangtze River,while the sunshine hours in the growth periods of chimonophilous crops and of thermophilic crops decreased most in North China and South China, respectively.In the whole year and in the growth periods of chimonophilous and thermophilic crops, both the precipitation and the reference crop evapotranspiration in this country all showed a decreasing trend, with the largest decrement in the precipitation in the whole year and in the growth periods of chimonophilous and thermophilic crops in North China, the largest decrement in the reference crop evapotranspiration in the whole year and in the growth periods of thermophilic crops in the middle and lower reaches of Yangtze River, and the largest decrement in the reference crop evapotranspiration in the growth periods of chimonophilous crops in Northwest China. In 1961-2007, the climate in China in the whole year and in the growth periods of thermophilic crops showed an overall tendency of warm and dry, and the climate in the growth periods of thermophilic crops became warm and dry in Southwest China, North China, and Northeast China, but warm and wet in the middle and lower reaches of Yangtze River, Northwest China, and South China, whereas the climate in the growth periods of chimonophilous crops became warm and dry in North China, but became warm and wet in Northwest China.

[21]
Yang Xuan, Tang Xu, Chen Baodeet al., 2010. Impacts of climate change on wheat yield in China simulated by CMIP5 multi-model ensemble projections.The Journal of Applied Ecology, 21(10): 2605-2614. (in Chinese)Objective】 By applying climate projections based on 30 Atmosphere-Ocean General Circulation Models(AOGCMs) under representative concentration pathway(RCP) scenarios in the Coupled Model Inter-comparison Project Phase 5(CMIP5), the effects of climate change on wheat yield in China were assessed in terms of ensemble method. 【Method】 The impact assessment of climate change on crops is typically based on daily data. However, significant uncertainties exist among the AOGCM outputs, particularly in daily data. In this paper, a pseudo global warming(PGW) method was assumed to be a linear coupling of contemporary weather fields and the difference component of climate perturbation signals by AOGCMs. CERES-Wheat model was employed to stimulate the wheat yield in the future and a probabilistic approach is used to address the uncertainties. 【Result】Warming is expected in all representative stations during the wheat growth period. Temperature increase under the RCP8.5 scenario is higher than that under the RCP2.6 scenario. The temperature in the representative stations of winter wheat is projected to increase by 2.7-2.9℃, and increase by 3.0-3.3℃ in the representative stations of spring wheat at the end of the 21 st century. The precipitation rate is projected to significantly increase in the future. Compared with the baseline, the observation data collected from 1996 to 2005 show that the climate-change-induced wheat yield reduced in all representative stations under irrigation conditions. The reduction probabilities increased with climate change. The irrigated yield reduction in the representative stations of spring wheat was greater than that in the representative stations of winter wheat. By the end of the 21 st century, the yield in the representative stations of winter wheat is projected to be decreased by 2% under the RCP 2.6 scenario. The yield reduction will be decreased by approximately 6% under the RCP 4.5 scenario and decreased by 9% under the RCP 8.5 scenario with a probability of 85%. In the representative stations of spring wheat, yield will be decreased by 5% under the RCP 2.6 scenario, by more than 8% under the RCP 4.5 scenario, and by more than 15% under the RCP 8.5 scenario with a probability of 90%. In comparison with the baseline, the rain-fed yield in the representative stations of winter wheat will be increased significantly. By the end of the 21 st century, the yield in winter wheat is projected to be increased by more than 21% under the RCP 2.6 scenario, more than 22% under the RCP 4.5 scenario, and more than 25% under the RCP 8.5 scenario with a probability of 90%.【Conclusion】The ensemble of daily data were obtained through the PGW method, which efficiently reserve the contemporary weather information, particularly that of extreme weather events. Effects of climate change on wheat yield under RCP2.6, RCP4.5, and RCP8.5 scenarios were assessed through the ensemble method. The results indicate that, with the increasing greenhouse gas emissions, the climate-change-induced yield-reduction probabilities of irrigated wheat in China gradually increased. Rain-fed wheat yield will be increased in the future, with large uncertainties.

[22]
Yu Huning, 1985. Analysis and Use of Agricultural Climate Resources. Beijing: China Meteorological Press. (in Chinese)

[23]
Yuan Bin, 2012. Climatic potential productivity and climate resources utilization rate of spring maize in Northeast China under climate change [D]. Beijing: Chinese Academy of Meteorological Sciences.

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