生态与农业气象

生态与农业气象研究进展

Progress in Ecological and Agricultural Meteorology Research

1 生态气象

1 Ecological meteorology

1.1 Critical leaf water content for maize photosynthesis under drought stress and its response to rewatering

Crop photosynthesis is closely related to leaf water content (LWC), and clarifying the LWC conditions at critical points in crop photosynthesis has great theoretical and practical value for accurately monitoring drought and providing early drought warnings. This experiment was conducted to study the response of LWC to drought and rewatering and to determine the LWC at which maize photosynthesis reaches a maximum and minimum and thus changes from a state of stomatal limitation (SL) to non-stomatal limitation (NSL). The effects of rehydration were different after different levels of drought stress intensity at different growth stages,and the maize LWC recovered after rewatering following different drought stresses at the jointing stage;however, the maize LWC recovered more slowly after rewatering following 43 days and 36 days of drought stress at the tasseling and silking stages, respectively. The LWC when maize photosynthesis changed from SL to NSL was 75.4% ± 0.38%, implying that the maize became rehydrated under physiologically impaired conditions. The LWCs at which the maize Vcmax25reached maximum values and zero differed between the drought and rewatering periods. After exposure to drought stress, the maize exhibited enhanced drought stress tolerance, an obviously reduced suitable water range, and significantly weakened photosynthetic capacity.These results provide profound insight into the turning points in maize photosynthesis and their responses to drought and rewatering. They may also help to improve crop water management, which will be useful in coping with the increased frequency of drought and extreme weather events expected under global climate change. (Zhou Guangsheng)

1.2 Quantitative response of maize Vcmax25 to persistent drought stress at different growth stages

Drought stress has adverse effects on crop growth and yield, and its identification and monitoring play vital roles in precision crop water management. Accurately evaluating the effect of drought stress on crop photosynthetic capacity can provide a basis for decisions related to crop drought stress identification and monitoring as well as drought stress resistance and avoidance. In this study, the effects of different degrees of persistent droughts in different growth stages (3rd leaf stage, 7th leaf stage and jointing stage) on the maximum carboxylation rate at a reference temperature of 25 (Vcmax25) of the first fully expanded leaf and its relationship to the leaf water content (LWC) were studied in a field experiment from 2013 to 2015. The results indicated that the LWC decreased continuously as drought stress continued and that the LWC decreased faster in the treatment with more irrigation. Vcmax25showed a decreasing trend as the drought progressed but had no clear relationship to the growth stage in which the persistent drought occurred. Vcmax25showed a significantly parabolic relationship (R2= 0.701, p < 0.001) with the LWC, but the different degrees of persistent drought stress occurring in different growth stages had no distinct effect on the LWC values when Vcmax25reached its maximum value or zero. The findings of this study also suggested that the LWC was 82.5 ± 0.5% when Vcmax25reached its maximum value (42.6 ± 3.6 μmol m−2s−1) and 67.6 ± 1.2% (extreme drought) when Vcmax25reached zero. These findings will help to improve crop drought management and will be an important reference for crop drought identification, classification and monitoring as well as for the development of drought monitoring and early warning systems for other crops or maize varieties. (Zhou Guangsheng)

1.3 The interrelationship between water use efficiency and radiation use efficiency under progressive soil drying in maize

The maximizing of water use efficiency (WUE) and radiation use efficiency (RUE) is vital to improving crop production in dryland farming systems. However, the fundamental question as to the association of WUE with RUE and its underlying mechanism under limited-water availability remains contentious. Here, a twoyear field trial for maize designed with five progressive soil drying regimes applied at two different growth stages (three-leaf stage and seven-leaf stage) was conducted during the 2013–2014 growing seasons. Both environmental variables and maize growth traits at the leaf and canopy levels were measured during the soil drying process. The results showed that leaf WUE increased with irrigation reduction at the early stage, while it decreased with irrigation reduction at the later stage. Leaf RUE thoroughly decreased with irrigation reduction during the progressive soil drying process. Aboveground biomass (AGB), leaf area index (LAI), a fraction of absorbed photosynthetically active radiation (fAPAR), and light extinction coefficient (k) of the maize canopy were significantly decreased by water deficits regardless of the growth stages when soil drying applied. The interrelationships between WUE and RUE were linear across the leaf and canopy scales under different soil drying patterns. Specifically, a positive linear relationship between WUE and RUE is unexpectedly found when soil drying was applied at the three-leaf stage, while it turned out to be negative when soil drying was applied at the seven-leaf stage. Moreover, the interaction between canopy WUE and RUE was more regulated by fAPAR than by LAI under soil drying. Our findings suggest that more attention must be paid to fAPAR in evaluating the effect of drought on crops and may bring new insights into the interrelationships of water and radiation use processes in dryland agricultural ecosystems. (Zhou Guangsheng)

1.4 Capability of leaf water content and its threshold values in reflection of soil-plant water status in maize during prolonged drought

Leaves play an important role in plant growth and development through photosynthesis and transpiration.Many studies have explored the effects of short-term drought stress on leaf water status; however, few studies have focused on the leaf water content capacity as an indicator of soil-plant water status during prolonged droughts. The results of a field experiment with various irrigation regimes that was conducted during two consecutive maize growing seasons from 2013 to 2014, indicated that the water content of the first fully expanded leaf (LWCtop1) was representative of the soil–plant water status with the development of drought.LWCtop1 was closely linked to the water condition of other leaves and different plant parts in response to progressive water stress. LWCtop1 shared a quadratic relationship with the photosynthetic rate (Pn), and Pnpeaked when LWCtop1 approached 84.11% and decreased to zero when LWCtop1 dropped to 68.26%.Moreover, three stages (slow-fast-slow) were observed as leaf water content responded to soil drying, and two important threshold values (minimum: 70.86 ± 0.80%, maximum: 84.58 ± 1.10%) of the leaf water content were determined. The results of this study may provide a physiological and ecological basis for the identification and monitoring of crop drought. (Zhou Guangsheng)

1.5 Increasing temperature shortened the carbon uptake period and decreased the cumulative net ecosystem productivity in a maize cropland in Northeast China

Phenology—mainly associated with climatic factors—is crucial for the accurate estimation of cumulative annual carbon exchange between terrestrial ecosystems and the atmosphere. However, the effects of changes in phenology on annual vegetation productivity and its regulatory mechanisms remain unclear, particularly in agricultural ecosystems. Therefore, in this study, we examined the associations among cumulative net ecosystem productivity (NEP), phenological metrics, and climatic factors based on long-term (2005–2014)eddy covariance flux and meteorological observations in a maize cropland in Northeast China. The results showed that carbon uptake period (CUP) was mainly determined by the end date of CUP (ECUP) in autumn.Cumulative NEP from May to September (NEP5-9), a period generally corresponding to the growing season,significantly increased with NEPmax(defined in this study as the 90th percentile of daily NEP during CUP) and CUP. NEPmaxexplained greater interannual variation in NEP5-9 than CUP. The start date of CUP (SCUP) and ECUP were both advanced with increasing winter temperature, but ECUP was more temperature-sensitive than SCUP. Thus, CUP tended to shorten with increasing temperature, ultimately decreasing cumulative NEP. In addition, NEPmaxdecreased with increasing precipitation in summer and autumn. The Greenup and MidGreendown dates from the MODIS Global Vegetation Phenology (MCD12Q2) product generally captured the interannual variation in the carbon flux-based SCUP and ECUP, respectively, well. The results of this study would be of great significance for predicting the response of ecosystem productivity to plant phenology shifts in agricultural ecosystems in future climate change scenarios. (Zhou Guangsheng)

1.6 Climatic warming enhances soil respiration resilience in an arid ecosystem

Precipitation plays a vital role in maintaining desert ecosystems in which rain events after drought cause soil respiration (Rs) pulses. However, this process and its underlying mechanism remain ambiguous,particularly under climatic warming conditions. This study aims to determine the magnitude and drive Rsof Rsresilience to rewetting. We conducted a warming experiment in situ in a desert steppe with three climatic warming scenarios—ambient temperature as the control, long-term and moderate warming treatment, and short-term and acute warming treatment. Our findings showed that the average Rsover the measurement period in the control, moderate and acute warming plots were 0.51, 0.30 and 0.30 μm(CO2) m−2s−1, respectively, and significantly increased to 1.72, 1.41 and 1.72 μm(CO2) m−2s−1, respectively, after rewetting. Both microbial and root respiration substantially increased by rewetting; microbial respiration contributed more than root respiration to total Rs. The Rssignificantly increased with microbial biomass carbon and soil organic carbon(SOC) contents. The Rsincrease by rewetting might be due to the greater microbial respiration relying heavily on microbial biomass and the larger amount of available SOC after rewetting. A trackable pattern of Rsresilience changes occurred during the daytime. The resilience of Rsin acute warming plots was significantly higher than those in both moderate warming and no warming plots, indicating that Rsresilience might be enhanced with drought severity induced by climatic warming. These results suggest that climatic warming treatment would enhance the drought resilience of soil carbon effluxes following rewatering in arid ecosystems,consequently accelerating the positive feedback of climate change. Therefore, this information should be included in carbon cycle models to accurately assess ecosystem carbon budgets with future climate change scenarios in terrestrial ecosystems, particularly in arid areas. （Zhou Guangsheng）

1.7 Resistance, recovery, and resilience of desert steppe to precipitation alterations with nitrogen deposition

Precipitation fluctuations with high nitrogen (N) deposition severely impact terrestrial ecosystem functioning, particularly in arid areas. Here, with rainout shelter facility, a field experiment with a large variation in precipitation and N addition was conducted to disentangle the responses of the plant community to normal precipitation, less precipitation, and rewetting conditions in a desert steppe, Inner Mongolia, the northern China. The field experiment established a unique annual precipitation change cycle across normal precipitation, less precipitation, and rewetting processes to quantify drought resistance, recovery, and resilience by calculating functional differences among three years. Furthermore, the relationships between plant community functional traits and response indices (i.e., the resistance, recovery, and resilience) were tested to clarify the mechanisms driving their responses to precipitation regimes and N addition. The aboveground net primary production (ANPP) increased with annual precipitation and was enhanced by N addition. ANPP with reduced precipitation regimes was less resistant to drought but recovered significantly greater than that with increased precipitation regimes. The perennial species, C3 plants, and forbs mainly contributed to the variations in vegetation productivity in response to drought and wet status cycles. Drought resistance and the recovery of species’ functional diversity, evenness, and ANPP stability were closely associated with precipitation changes. The present findings suggested that altered precipitation patterns, community composition, and functional stability contribute to ecosystem stability during water change cycles and are mediated slightly by N deposition. These findings advance understanding of the mechanisms of ecosystem functioning underlying the responses to climatic change. （Zhou Guangsheng）

1.8 Vertical distribution of gas exchanges and their integration throughout the entire canopy in a maize field

Fluxes of carbon and water along a vertical profile within a canopy, particularly the associations between canopy and ecosystem levels, are not well studied. In this study, gas exchange along the vertical profile in a maize canopy was examined. The relationships between leaf- and ecosystem-level carbon and water fluxes were compared. The results from research conducted over two growing seasons showed that during vegetative growth, the top and middle leaf layers in the canopy contribute most to the carbon and water fluxes of the entire canopy. During the grain-filling stage, gas exchange processes were performed mostly in the middle leaves with and near the ears. Significant relationships were observed between the net ecosystem CO2exchange rate(NEE) plus soil respiration and the assumed canopy levels (Acanopy) and between evapotranspiration rates at the ecosystem (ET) and assumed canopy levels (Ecanopy). This highlights the close associations between these parameters by integrating the leaf gas exchange rates measured in a conventional leaf cuvette and those at the ecosystem level via the eddy covariance technique. These results improve our understanding of how carbon assimilation varies vertically within a canopy, highlighting the critical role of ear leaves. （Zhou Guangsheng）

1.9 Effects of mosaic representation of land use/land cover on skin temperature and energy fluxes in Noah-MP land surface model over China

The representations of land use/land cover (LULC) play an important role in land surface models (LSMs)for the simulation of the energy flux partition, soil moisture redistribution, and runoff generation. This study was designed to investigate the regional effects of mosaic LULC representations on skin temperature (Ts) and energy fluxes over China at three horizontal resolutions and how these effects changed with climate regimes,using Noah with multi-parameterization (Noah-MP) LSM. The current officially released Noah-MP only considered the most abundant LULC type within one model grid. In this study, the mosaic method considering all the LULC types existing in one model grid was implemented into Noah-MP. Against the reference data(including MODIS land surface temperature products, FLUXCOM energy flux data and numerical terra dynamic simulation group evapotranspiration data), the mosaic method generally performed better than the default method and reduced the root-mean-squared-error of Tsand energy fluxes significantly over urban region. The mosaic method affected the Tsand energy fluxes by changing leaf area index and soil moisture,mainly by the former. The warm (monthly mean air temperature larger than 10 ) and relatively humid climate(annual total precipitation larger than 200 mm) could enlarge the effect of mosaic method on Tsand energy fluxes. The mosaic method reduced discrepancies of Tsand energy fluxes among three horizontal resolutions(0.0625º, 0.25º, and 0.50º), especially over the heterogeneous vegetated and urban region. （Zhou Guangsheng）

1.10 Climate warming-induced drought constrains vegetation productivity by weakening the temporal stability of the plant community in an arid grassland ecosystem

An investigation of the influences of climatic warming on ecosystem function and stability is crucial to project the impact of global climate change on terrestrial ecosystems. However, few studies have applied multiple warming treatments in arid ecosystems, which play a critical role in the global carbon cycle and are among the ecosystems most sensitive to future climatic change. To explore the effects of climatic warming on plant community function and stability, moderate warming and acute warming treatments were conducted in desert grassland, Inner Mongolia, China, using free-air temperature increase facilities. Aboveground net primary production (ANPP) of plant community significantly decreased with climatic warming, particularly in warmer years with drier conditions. The decrease in ANPP was mainly caused by decreased soil moisture induced by climatic warming. Climatic warming reduced the temporal stability of the plant community by weakening plant species asynchrony and shifting key functional groups, such as perennial vs annual grass and C3 vs C4 species. Our findings indicate that climatic warming could hamper plant community productivity via decreased soil moisture and constrain plant community functioning by weakening community stability. This result highlights that shifts in plant community composition and consequent functional changes can play a key role in predicting the responses of arid ecosystems to climatic change. （Zhou Guangsheng）

1.11 Photosynthetic resistance and resilience under drought, flooding and rewatering in maize plants

Abnormally altered precipitation patterns induced by climate change have profound global effects on crop production. However, the plant functional responses to various precipitation regimes remain unclear. Here,greenhouse and field experiments were conducted to determine how maize plant functional traits respond to drought, flooding, and rewatering. Drought and flooding hampered photosynthetic capacity, particularly when severe and/or prolonged. Most photosynthetic traits recovered after rewatering, with few compensatory responses. Rewatering often elicited high photosynthetic resilience in plants exposed to severe drought at the end of plant development, with the response strongly depending on the drought severity/duration. The associations of chlorophyll concentrations with photosynthetically functional activities were stronger during post-tasseling than during pre-tasseling, implying an involvement of leaf age/senescence in responses to episodic drought and subsequent rewatering. Coordinated changes in chlorophyll content, gas exchange,fluorescence parameters (PSII quantum efficiency and photochemical/non-photochemical radiative energy dissipation) possibly contributed to the enhanced drought resistance and resilience and suggested a possible regulative trade-off. These findings provide fundamental insights into how plants regulate their functional traits to deal with sporadic alterations in precipitation. Breeding and management of plants with high resistance and resilience traits could help crop production under future climate change. （Zhou Guangsheng）

1.12 Quantitative evaluation of the trade-off growth strategies of maize leaves under different drought severities

The leaf is one of the most drought-sensitive plant organs. Investigating how leaf traits change and their trade-off growth during a drought would contribute to developing targeted drought-resistance measures. We investigated changes in five key maize leaf traits (leaf area, dry mass, effective number, water content, and specific weight) and their trade-off growth based on a drought simulation experiment. We also developed an indicator (0, 1) to quantitatively evaluate drought severity. The results showed a trade-off growth between different leaf traits of maize plants under drought conditions. Maize maintained relatively high leaf water content to maintain high leaf metabolic activity until drought severity was greater than 0. When drought severity was (0, 0.48), maize tended to adopt rapid growth strategy by maintaining regular leafing intensity and investing more energy into leaf area rather than specific leaf weight so that more energy could be absorbed.When the drought severity exceeded 0.48, maize conserved its resources for survival by maintaining relatively lower metabolic activity and thicker leaves to minimize water loss. The results provide an insight into the acclimation strategies of maize under drought, and contribute to targeted drought prevention and relief measures to reduce drought-induced risks to food security. （Zhou Guangsheng）

1.13 Growth variations of dahurian larch plantations across Northeast China: Understanding the effects of temperature and precipitation

Climate change is affecting the growth and distribution of trees in the Chinese boreal forest. Such changes in China, the southern terminus of the extensive Eurasian boreal forests, reflect on the changes that could occur further north under a warming climate. Most studies have found that tree growth increases with increasing temperature and precipitation in boreal forests, but there is little observational evidence of the climate thresholds that might slow these growth rates at the more extreme temperatures which are predicted to occur under future global warming. Here, we examine growth responses of this dominant boreal tree species (Larix gmelinii) to climate based on the data from plantation sample plots across a broad region (40º51'–52º58' N,118º12'E−133º42' E) in Northeast China. From statistically significant fits to quadratic equations, temperature and precipitation are the important climatic factors determining tree growth in L. gmelinii plantations at two age classes (<10 year and 10–30 years-old stands). The maximum rates of tree height and diameter at breast height (DBH) were about 0.53 m year−1and 0.46 cm year−1at <10 year stands, and about 0.63 m/year and 0.60 cm/year at 10–30-year stands, respectively. For stands with the highest values of mean annual increment(MAI), the corresponding optimal mean annual temperature (MATopt) focused between 0.66 and 1.57 .The optimal mean annual precipitation (MAPopt) between 663 mm and 708 mm produced the maximal growth increments. With mean annual temperature of −2.4 and precipitation of 470 mm averaged over 1954–2005 in Chinese boreal forest region as baseline, we conservatively estimated that trees in Chinese boreal forest appear to have higher growth potentials with the maximum temperature increase of 3.6 and precipitation increase of 40%. （Zhou Guangsheng）

1.14 Responses of plant biomass and yield component in rice, wheat, and maize to climatic warming: A meta-analysis

The responses of crop yields to climatic warming have been extensively reported from experimental results, historical yield collections, and modeling research. However, an integrative report on the responses of plant biomass and yield components of three major crops to experimental warming is lacking. Here, a metaanalysis based on the most recent warming experiments was conducted to quantify the climatic warming responses of the biomass, grain yield (GY), and yield components of three staple crops. The results showed that the wheat total aboveground biomass (TAGB) increased by 6.0% with general warming, while the wheat GY did not significantly respond to warming; however, the responses shifted with increases in the mean growing season temperature (MGST). Negative effects on wheat TAGB and GY appeared when the MGSTs were above 15 and 13 , respectively. The wheat GY and the number of grains per panicle decreased by 8.4% and 7.5%, respectively, per increase. Increases in temperature significantly reduced the rice TAGB and GY by 4.3% and 16.6%, respectively, but rice straw biomass increased with increasing temperature. However,the rice grain weight and the number of panicles decreased with continuous increasing temperature (ΔTa). The maize biomass, GY, and yield components all generally decreased with climatic warming. Finally, the crop responses to climatic warming were significantly influenced by warming time, warming treatment facility, and methods. Our findings can improve the assessment of crop responses to climatic warming and are useful for ensuring food security while combating future global climate change. （Zhou Guangsheng）

1.15 ChinaSpec: A network for long-term ground-based measurements of solar-induced fluorescence in China

Remotely sensed solar-induced fluorescence (SIF) has emerged as a novel and powerful approach for terrestrial vegetation monitoring. Continuous measurements of SIF in synergy with concurrent eddy covariance(EC) flux measurements can provide a new opportunity to advance terrestrial ecosystem science. Here, we introduce a network of ground-based continuous SIF observations at flux tower sites across the mainland China referred to as ChinaSpec. The network consists of 16 tower sites until 2019 including six cropland sites, four grassland sites, four forest sites, and two wetland sites. An automated SIF system was deployed at each of these sites to collect continuous high-resolution spectra for high-frequency SIF retrievals in synergy with EC flux measurements. The goal of ChinaSpec is to provide long-term ground-based SIF measurements and promote the collaborations between optical remote sensing and EC flux observation communities in China. We present here the details of instrument specifications, data collection and processing procedures, data sharing and utilization protocols, and future plans. Furthermore, we show the examples how ground-based SIF observations can be used to track vegetation photosynthesis from diurnal to seasonal scales, and to assist in the validation of fluorescence models and satellite SIF products (e.g., from OCO-2 and TROPOMI) with the measurements from these sites since 2016. This network of SIF observations could improve our understanding of the controls on the biosphere-atmosphere carbon exchange and enable the improvement of carbon flux predictions. It will also help integrate ground-based SIF measurements with EC flux networks which will advance ecosystem and carbon cycle researches globally. （Zhou Guangsheng）

1.16 Grated remote sensing and model approach for impact assessment of future climate change on the carbon budget of global forest ecosystems

At present, global warming is an indisputable fact, and more and more attention has been paid to the impacts of climate warming on global ecological environments. Forests play increasing significant roles in regulating global carbon balance and mitigating climate change. Therefore, to understand the response mechanisms of the carbon budget of global forest ecosystems to future climate change, an improved version of the FORest ecosystem Carbon budget model for CHiNa (FORCCHN) and future Representative Concentration Pathway (RCP) scenario RCP4.5 and RCP8.5 were applied in this study. The results demonstrated that the global forest ecosystems will play a major role in the carbon sink under the future two climate change scenarios. In particular, the average carbon budget of global forest ecosystems under RCP4.5 scenario was estimated to be 0.017 kg(C) m−2yr−1from 2007 to 2100. The future carbon sink areas of global forest ecosystems will increase significantly. Under RCP4.5 and RCP8.5 climate scenarios, the carbon sink areas of global forest ecosystems during 2026‒2100 would be significantly been expanded than those in 2007‒2025,with increases of 83.16%‒87.26% and 23.53%‒29.70%, respectively. The impacts of future climate change on carbon budget of global forest ecosystems will significantly vary between different regions. The carbon budget of forests will be enhanced in the Northern Hemisphere and significantly weakened in the Southern Hemisphere under the future two climate change scenarios. The carbon sink regions of global forests will be mainly distributed in the middle and high latitudes of the Northern Hemisphere. In particular, the forests’carbon budget in the northeastern and central Asia, northern Europe and western North America will increase by 40% to 80%. However, the carbon budget of forests will decrease by 20% to 40% in the most regions of the Southern Hemisphere. In northern South America and central Africa, the forests’ carbon budget will be reduced by more than 40%. In the future, in some areas of Southern Hemisphere, where the forests’ carbon budget was predicted to be reduced, some measures for improving forest carbon sink, such as strengthening forest tending,enforcing prohibiting deforestation laws and scientific forest management, and so on, should be implemented to ensure immediate mitigation and adaptation to climate change. (Zhao Junfang)

1.17 Analysis of wheat yield losses at the county level in mainland China

There have been few pieces of research focused on quantifying wheat yield loss risk based on highresolution long-term historical data. What is more, the existence of the area scale effect reduces the certainty and spatial comparability of results. In this study, long-term wheat yield and planting area data at the county level from 1981 to 2010 were used. The spatial distribution of wheat yield loss risks was analyzed in the mainland of the People’s Republic of China (China for short). An improved comprehensive risk index of yield loss risk was established by integrating the reduction rate, coefficient of variation, and the probability of occurrence for different yield reduction rates after removing the effect of area scale. The main wheat-growing areas of 874 counties in the mainland of China were divided into lowest, lower, moderate, higher, and highest risk areas based on it. The high-risk areas are located in the Yellow-Huai-Hai Plain, including Shandong,Henan, northern Anhui, and parts of Jiangsu Province. （Fang Shibo）

1.18 Using long-term earth observation data to reveal the factors contributing to the early 2020 desert locust upsurge and the resulting vegetation loss

Massive desert locust swarms have been threatening and devouring natural vegetation and agricultural crops in East Africa and West Asia since 2019, and the event developed into a rare and globally concerning locust upsurge in early 2020. The breeding, maturation, concentration and migration of locusts rely on appropriate environmental factors, mainly precipitation, temperature, vegetation coverage and land-surface soil moisture. Remotely sensed images and long-term meteorological observations across the desert locust invasion area were analyzed to explore the complex drivers, vegetation losses and growing trends during the locust upsurge in this study. The results revealed that (1) the intense precipitation events in the Arabian Peninsula during 2018 provided suitable soil moisture and lush vegetation, thus promoting locust breeding, multiplication and gregarization; (2) the regions affected by the heavy rainfall in 2019 shifted from the Arabian Peninsula to West Asia and Northeast Africa, thus driving the vast locust swarms migrating into those regions and causing enormous vegetation loss; (3) the soil moisture and NDVI anomalies corresponded well with the locust swarm movements; and (4) there was a low chance the eastwardly migrating locust swarms would fly into the Indochina Peninsula and Southwest China. （Fang Shibo）

1.19 Analyzing the probability of acquiring cloud-free imagery in China with AVHRR cloud mask data

Optical remote sensing data are used widely in many fields (such as agriculture, resource management and the environment), especially for the vast territory of China; however, the application of these data is usually limited by clouds. Although it is valuable to analyze the probability of acquiring cloud-free imagery (PACI),PACI using different sensors at the pixel level across China has not been reported. In this study, the PACI of China was calculated with daily advanced very high resolution radiometer (AVHRR) cloud mask data from 1990 to 2019. The results showed that (1) PACI varies dramatically in different regions and months in China.The value was larger in autumn and winter, and the largest figure reached 49.55% in October in Inner Mongolia(NM). In contrast, relatively small values occurred in summer, and the minimum value (5.26%) occurred in June in South China (SC). (2) As the climate changes, the PACI has increased significantly throughout the country, especially in North China (NC), with a growth rate of 1.9% per decade. The results can be used as a reference for selecting appropriate optical sensors and observation times in areas of interest. （Fang Shibo）

1.20 Analysis of variation in reference evapotranspiration and its driving factors in mainland China from 1960 to 2016

Understanding the variation in reference evapotranspiration (ET0) is vital for hydrological cycles, drought monitoring, and water resource management. With 1507 meteorological stations and 130 radiation-measured stations, the annual and seasonal ET0were calculated at each site from 1960 to 2016 in mainland China. The phenomenon of coefficient a being less than 0.25 and coefficient b being greater than 0.50 in the Angstrom–Prescott model occurred in almost the whole country, except for a small area of western and northeastern China. Moreover, the Xiao’s method was more applicable to calculate the net longwave radiation (Rnl) and then improve the estimation accuracy of ET0. The annual ET0varied from 538.8 to 1559.8 mm and had a high-value center located in the plateau and desert of the northwestern China and a low-value center located in Northeast China and near the Sichuan Basin. The spatial distribution of seasonal ET0was roughly similar to that of annual ET0, except for that in winter when ET0was high in the south and low in the north. In mainland China,the annual ET0decreased by 21.2 mm per decade because of the declining sunshine duration before 1993 and increased by 21.1 mm per decade due to the decreased relative humidity (RH) after 1993. Generally, the abrupt change of ET0mainly occurred in the southern China rather than northern China (except for Qinghai Tibet Plateau). Basically, the dominant driving factors of annual and seasonal ET0were RH and/or Tmaxafter the abrupt change in most parts of China. （Fang Shibo）

1.21 New aricultural drought index for monitoring the water stress of winter wheat

Timely and effectively monitoring agricultural droughts for winter wheat production is crucial for water resource management, drought mitigation and even national food security. With soil moisture and actual evapotranspiration (ET) products from 2001 to 2018 supplied by the European Centre for Medium-Range Weather Forecasts (ECMWF) and moderate resolution imaging spectroradiometer (MODIS) data, respectively,two agricultural drought indices, i.e., the univariate soil moisture and evapotranspiration index (USMEI) and bivariate soil moisture and evapotranspiration index (BSMEI), were developed to reflect water stress for winter wheat. Our case study on the North China Plain (NCP) indicated that the USMEI could effectively monitor agricultural drought, especially in autumn and winter from October to January. Furthermore, compared with the evaporative stress index (ESI) and soil moisture anomaly percentage index (SMAPI), the correlations between the USMEI and climatic yields were acceptable at the county level or site scale. However, for the rest of the winter wheat growing season, the ESI and SMAPI performed better than the USMEI. In addition,the BSMEI was not suitable for monitoring droughts for winter wheat because this index overestimated the drought intensity. （Fang Shibo）

1.22 生态气象：起源、概念和展望

生态气象是应人类面临的生存环境危机而兴起的地球系统科学新兴学科，已经成为大气科学的二级学科。本文阐述了生态气象的学科起源、概念、主要研究内容与特征，指出生态气象是研究生态系统与气象条件之间相互关系的科学，是地球系统多圈层相互作用的核心，服务于人与自然和谐发展；探讨了生态气象观测的主要指标与可能的业务服务产品；阐释了生态气象研究与生态文明气象保障、气象防灾减灾和应对气候变化的关系。当前生态气象迫切需要开展的重点研究任务如下：（1）生态气象长期观测联网研究；（2） 基于大数据与人工智能的生态气象信息提取与分析技术； （3） 生态系统对气候变化的适应性及其变化归因； （4） 生态系统主要气象灾变机制及其致灾临界气象条件； （5） 陆地生态系统关键物候期对多环境要素响应的生理生态机制与模拟模型研究； （6） 耦合生物—物理—化学—管理过程的生态气象数值模式研发； （7） 陆地生态系统变化对气候系统的反馈作用与可持续发展对策研究。（周广胜）

1.23 河水生态承载力的流域整体性和时空连通性

黄河是中华民族的母亲河，黄河流域是中华文明的重要发育地。在中国5000多年的历史长河中，黄河流域作为全国政治、经济和文化中心占据了3000多年，孕育了河洛文化、河湟文化、关中文化等，分布有西安、郑州、洛阳、开封等古都，诞生了四大发明和《诗经》《老子》《史记》等经典著作。黄河流域是连接青藏高原、黄土高原和华北平原的生态廊道，是西北和华北地区的重要水源，以其占全国2.2%的径流量灌溉了占全国15%的耕地，哺育了流域9省近23.3%的全国人口（2019年），贡献了21.6%的全国GDP（2018年）。不仅如此，黄河流域还是中国最重要的煤炭生产地带。中国排名前14的大型煤炭生产基地中有9个地处黄河流域，已经探明的煤炭储量累计达7292亿吨（原煤）。特别是，煤炭工业已经成为黄河流域中、上游晋陕蒙宁甘地区（即山西、陕西、内蒙古、宁夏和甘肃五省区）经济发展的主要经济支柱产业，煤炭年产量约28亿t，占全国总产量的近70%。因此，黄河流域生态保护和高质量发展直接关系到中国生态文明建设的成败。长期以来，黄河存在水土流失、泥沙淤积和洪水威胁等问题。特别是近几十年来，黄河流域气温升高、极端事件及自然灾害频发，径流减少；同时，大规模的能源开发、煤炭开采也需要大量的水资源。气候变化和不合理人类活动使得黄河上游部分生态系统质量退化、水源涵养功能下降；中游水土流失严重；下游生态流量偏低，部分河口湿地萎缩。目前，黄河流域水资源短缺、自然生态脆弱、经济社会发展相对滞后，是中国生态安全保障和经济社会发展的重点和难点地区。为此，需要梳理制约黄河流域生态保护与高质量可持续发展存在的问题，凝炼关键科学问题，提出当前迫切需要开展的任务。（周广胜）

1.24 中国生态与农业气象研究进展

目前中国生态与农业气象研究主要关注气候变化的影响，而脆弱性与风险预估研究仍存在很大不确定性，甚至无法进行预估研究。以生态/农业气象的脆弱性和风险为切入点，从生态/农业的地理/种植分布、物候/生育期和生产力/产量等方面，综述了中国生态/农业气象的研究进展，指出现有研究成果难以满足高质量生态保护与粮食安全的需求，为此提出了未来拟重点开展的研究任务，即生态/农业气象承载力及其优化布局、生态/农业气象的灾变过程与调控机制、生态/农业变化的气象条件贡献率评估及其适应技术、高质量生态保护与粮食提质增效的气候资源高效利用和定向调控研究，以推进中国生态与农业气象脆弱性与风险研究，为中国生态/农业气象科学应对气候变化提供依据。（周广胜）

1.25 2000—2019年秦岭地区植被生态质量演变特征及驱动力分析

为了阐明2000—2019年秦岭地区植被生态质量变化的空间异质性，以及植被生态质量变化的驱动力，该文采用模型模拟和卫星观测的方法对植被生态质量演变及其驱动力进行研究。结果显示：（1）秦岭地区植被生态质量整体显著改善，植被净初级生产力（NPP）和植被覆盖度（VFC）的平均增加速率分别为8 g（C）/（m2·a）和0.0054/a。空间上，秦岭地区85%～95%区域的植被生态质量明显改善，但是以西安市为代表的局部地区植被NPP和VFC显著下降。（2）秦岭地区80%～85%区域的降水量和气温呈上升趋势，与植被NPP和VFC增加的空间范围大体一致，证实气候暖湿化对改善植被质量有重要驱动作用。（3）人类保护活动（天然林保护、退耕还林还草等）使秦岭地区大范围植被生态系统得到抚育，林地、草地和水域面积大幅度增加。以秦岭北麓为代表的建设用地扩张是秦岭部分地区植被生态质量恶化的主要原因，但是人类破坏活动被限制在局部区域。（周广胜）

1.26 增温背景下克氏针茅枯黄期物候对降水响应的光合生理机制

基于红外线辐射增温与控水相结合的原位模拟试验资料，分析了克氏针茅（Stipa krylovii）枯黄期对水热变化响应的光合生理机制。结果表明，增温背景下降水是枯黄期的主要影响因子，增水（减水）导致枯黄始期和枯黄盛期的发生时间均延迟（提前），枯黄期持续时间均延长，减水处理对枯黄期持续时间的延长作用更显著。增温背景下，降水变化显著影响枯黄期的生理生态特性，且在枯黄始期最为显著，净光合速率、气孔导度、蒸腾速率、核酮糖-1,5-二磷酸（RuBP）羧化的最大速率（Vcmax）、RuBP再生能力的最大速率（Jmax）均与降水量呈显著正相关。通径分析表明，克氏针茅枯黄期的光合生理机制因水热变化的不同而异。当前环境条件下，枯黄期物候变化的主要影响因子是Jmax，主要限制因子是Vcmax。未来暖干和暖湿气候下枯黄期物候变化的主要影响因子均是Vcmax；但在暖干气候下主要限制因子为Jmax，而在暖湿气候下则无限制因子。这表明克氏针茅枯黄期物候的变化取决于气候环境条件变化对其光合能力的影响。（周广胜）

1.27 温度和光周期协同作用对蒙古栎幼苗春季物候的影响

植物物候对气候变化非常敏感，但关于物候对不同气候因子协同作用的响应机制仍不清楚。为此，以蒙古栎为研究对象，针对蒙古栎物候的主要影响因子温度和光周期，利用大型人工气候室，模拟研究了温度与光周期协同作用（对照、增温1.5 ℃、增温2.0 ℃，不同光周期（10 h、14 h、18 h） 及其协同作用（对照处理、增温1.5 ℃×18 h、增温1.5 ℃×10 h、增温2.0 ℃×18 h、增温2.0 ℃×10 h） ）对蒙古栎春季物候的影响与机制。结果表明， （1）相同水分条件下，不同升温程度对蒙古栎幼苗春季物候的影响不同。温升1.5 ℃促进蒙古栎幼苗春季物候（芽膨大期、芽开放期、展叶始期和展叶盛期）提前; 而温升2.0 ℃则对不同春季物候的影响不同，表现为促进芽休眠解除和芽开放，但抑制叶片展开。（2）相同水分条件下，不同光周期对蒙古栎幼苗不同春季物候的影响存在差异。长光周期对蒙古栎幼苗展叶盛期影响最大，短光周期对芽膨大期影响最大，但均表现为抑制作用。（3）相同水分条件下，温度升高与光周期增加协同作用有助于促进蒙古栎幼苗春季物候提前，但温度升高与光周期缩短协同作用则对春季物候有抑制作用。（4）蒙古栎幼苗春季物候变化与前期气候胁迫程度存在显著正相关，表明前期气候因子也是物候变化的重要影响因子。研究结果丰富了蒙古栎物候响应多气候因子协同作用的认知，有助于促进物候模型的完善。（周广胜）

1.28 1969—2018年金华市舒适度和冷/热日特征分析

利用1969—2018年气象观测资料对金华市年、季尺度的舒适度和冷/热日数进行分析。结果表明：金华市全年和各季节的平均有效温度均呈显著上升趋势，2000年前后稳定超过平均值且上升趋势增加；年均气候倾向率为0.67 ℃/10a，各季节的上升趋势不同，其中冬季最大，夏季最小。暖冬或冷冬的概率呈先增后减再略增的N型变化趋势，热夏或凉夏的概率呈弱增加趋势。舒适期呈双峰型分布，主要集中在4—6月和9—10月，其中5月的舒适日数最多。舒适期的50 a平均初、终日分别为4月4日和11月8日，随时间推移，初日呈显著提前趋势(约5.7 d/10a)，终日呈显著延后趋势(约4 d/10a)，气候舒适率总体呈不显著的弱上升趋势。年舒适日数和热日数呈显著增加趋势，分别为5.08 d/10a和2.31 d/10a，冷日数呈显著下降趋势，达7.39 d/10a。 整体来看，金华市冬季气温较以往更为温暖，夏季更热，春季舒适时间明显增多，秋季的冷不舒适体感时间明显减少。（周广胜）

1.29 基于大气-土壤-植被系统干旱发生发展过程的综合干旱指标构建与应用

适宜的干旱指标和高分辨率数据是准确监测干旱的基础。本研究从气象干旱和土壤干旱以及植被对干旱的响应出发，整合中国国家气象观测站、中国气象局陆面数据同化系统（CLDAS）土壤湿度0.0625°×0.0625°）和MODIS 叶面积指数（500 m×500 m）等多源数据信息，构建了基于气象干旱指数（标准化降水蒸散指数）、土壤干旱指数（土壤湿度百分位）和植被干旱指数（叶面积指数百分位）的综合干旱指数，并在中国东北地区开展了典型站点和区域10 km×10 km 空间分辨率干旱监测试验。结果表明，综合干旱指数克服了单一气象干旱指数不能准确反映农业旱情及单一植被长势指数会将其他灾害引起的植被长势变差误判为干旱的不足，能够反映灌溉对干旱的影响，实现对大气—土壤—植被系统干旱发生、发展及其影响的监测。（周广胜）

1.30 蒙古栎展叶盛期变化的光谱特征及其影响因素研究

植物生长状况是反映环境变化的重要指标，在全球环境变化格局下，研究多环境因子及交互作用对植物的影响尤为重要。为探究植物光谱特征响应环境变化，从而探究环境变化对植物生长状况的影响，同时实现遥感对植物的监测，该研究以东北地区优势树种蒙古栎为研究对象，分析研究了不同光周期、温度和氮沉降交互作用引起的蒙古栎展叶盛期冠层光谱反射特征变化。基于大型人工气候室模拟试验，设置3个温度，3个光周期和2个氮沉降交互处理，每个处理4个重复。当蒙古栎进入展叶盛期时，每个处理选择差异较小的3个重复，使用Fieldspec Pro FR2500型背挂式野外高光谱辐射仪测量光谱反射率。对不同处理的蒙古栎冠层光谱反射率进行分析，选取NDVI（归一化植被指数）、Chl NDI（归一化叶绿素指数）和PRI（光化学反射指数）3个常用的光谱指数作为辅助分析，同时计算一阶导数光谱以得到红边斜率、红边位置、红边面积等参数。不同处理展叶盛期的蒙古栎光谱反射率趋势大体一致，均符合植物特有的光谱反射特征，在350～680 nm范围内有一个小的波峰，680～750 nm反射率显著上升，750 nm后进入反射平台。结果表明：（1）光周期对于蒙古栎冠层的光谱反射率没有明显的影响；（2）增温会减小蒙古栎冠层在350～750 nm波段处的光谱反射率；（3）施氮会导致蒙古栎展叶盛期350～750 nm波段和750～1100 nm波段处的光谱反射率降低；（4）增温和施氮的交互作用会显著减小蒙古栎的光谱反射率；（5）通过一阶导数光谱可清晰地指示植物的红边特征。研究结果可为物候变化的监测与影响因素分析提供理论依据。（周广胜）

1.31 横断山区地表真实面积与垂直投影面积差异分析——以雅江县为例

横断山脉地形起伏复杂，以垂直投影面积作为地表真实面积进行定量计算会产生较大误差。本文以横断山脉中部雅江县为例，基于DEM数据和地表覆盖产品数据集，利用地表粗糙度的地学意义，计算了雅江县不同土地利用类型地表真实面积，并分析了地表真实面积与垂直投影面积之间的差异。结果表明：雅江县地表面积与投影面积的差异与DEM分辨率呈正相关，与海拔呈负相关，坡度是地表面积与投影面积差异的主要影响因素，坡度越大，差异越大，差异的增长速率越大；不同土地利用类型对面积差异有不同程度的影响。（周广胜）

1.32 不同灌溉量夏玉米叶绿素含量的高光谱特征及其反演

植物叶绿素含量直接影响其光合作用，并与植物的光谱特征密切相关。以夏玉米为研究对象，采用人工控水方法研究了夏玉米七叶期不同灌溉量下冠层叶绿素含量特征及其与光谱特征之间的关系。结果表明：灌溉量越少，夏玉米叶片叶绿素含量越低，冠层光谱反射率越高，绿峰位置“红移”，而红边位置“蓝移”。叶绿素含量与光谱特征参数、植被光谱指数之间存在极显著相关关系，据此建立了冠层叶绿素含量高光谱估算模型，且基于植被指数模型较基于单一光谱特征参数模型模拟效果更好。研究结果可为夏玉米叶绿素含量的快速无损测定以及夏玉米干旱监测提供依据。（周广胜）

1.33 中国毛葡萄和刺葡萄分布的气候适宜性

毛葡萄和刺葡萄是起源于中国且用于葡萄酒酿造的两大野生葡萄品种。本研究基于已有中国毛葡萄和刺葡萄的气候影响因子研究成果，利用最大熵原理从充分性与必要性方面确定了影响中国毛葡萄和刺葡萄种植分布的主导气候因子，并基于这些因子综合作用反映的毛葡萄和刺葡萄种植分布的存在概率分析了中国毛葡萄和刺葡萄分布区的气候适宜性。结果表明，影响中国毛葡萄、刺葡萄分布的主导气候因子是年日照时数、开花期5月降水量、年极端最低气温、最冷月平均气温。中国毛葡萄、刺葡萄气候高适宜区分布在湖南西部和南部、广西中北部、贵州东南部、重庆中部。气候高适宜区、适宜区、低适宜区面积分别占研究区域总面积的2%、14%和16%。毛葡萄、刺葡萄气候适宜及以上区域的年日照时数阈值为1200～1800 h，年极端最低气温-8 ℃以上，最冷月平均气温阈值为2 ～13 ℃，5月降水量为110～320 mm。（周广胜）

1.34 中国欧亚种酿酒葡萄种植分布的主要气候影响因子与气候适宜性

开展酿酒葡萄气候适宜性研究对于优化酿酒葡萄布局、气候资源开发利用具有重要意义。基于欧亚种酿酒葡萄（Vitis vinifera L．）分布数据和影响其分布的气候因子，利用最大熵模型（MaxEnt）和地理信息系统（ArcGIS），研究影响欧亚种酿酒葡萄种植分布的主导气候因子及其气候适宜性。结果表明: MaxEnt 模型能够很好地模拟我国欧亚种酿酒葡萄的潜在分布，模拟效果达到“非常好”（AUC 平均值0.936） 的水平。基于气候因子对欧亚种酿酒葡萄地理分布影响的贡献确定了主导气候因子，即无霜期、干燥度、极端最低气温、年降水量、生长季日照时数、≥10 ℃活动积温。当前，我国欧亚种酿酒葡萄种植分布的气候高适宜区、适宜区、次适宜区分别占次适宜及以上区域总面积的2.9%、20.4%和76.7%。欧亚种酿酒葡萄气候高适宜区主要分布在宁夏、山西、陕西、内蒙古、山东、河北、新疆、甘肃等省，只考虑气候因子，陕西、山西、内蒙古具有较大的发展空间。（周广胜）

1.35 基于微波数据与光学数据集成的机器学习技术在作物产量估算中的应用

各类光学植被指数已成功地应用于各种植被监测与作物产量估算中，但这些指数易受大气状况的影响。由星载微波辐射计得到的植被光学厚度数据（VOD）与植被密度、含水量密切相关，数据可全天候获得，在农业遥感监测中呈现着巨大的潜力。作为来自不同传感器的遥感数据，微波遥感数据与光学遥感数据可以提供不同波长范围内的植被信息。为了更准确地进行作物产量估算，本研究提出将微波遥感数据与光学遥感数据共同应用于冬小麦单产估算中。研究选择L波段微波辐射计SMAP卫星的VOD数据与MODIS的标准归一化植被指数NDVI、增强型植被指数EVI、叶面积指数LAI、光合有效辐射分量FPAR数据作为研究变量，分别使用BP神经网络、GA-BP神经网络和PSO-BP神经网络建立冬小麦产量估算模型。结果表明，3种神经网络回归模型的P值均小于0.001，通过了显著性检验。GA-BP神经网络回归模型的估算值与真实值在3种神经网络回归模型中表现了最高的相关性（R = 0.755）与最低的均方根误差（RMSE = 529.145 kg/hm2），平均绝对误差（MAE = 425.168 kg/hm2）和平均相对误差（MRE = 6.530%）。为了分析多源遥感数据的结合在作物产量估算中的优势，研究同时构建了仅使用NDVI和LAI，使用NDVI、EVI、LAI、FPAR等光学数据进行冬小麦产量估算的3种GA-BP神经网络回归模型作为对比。结果表明，使用微波遥感数据与光学遥感数建立的GA-BP神经网络回归模型较上述3种作为对比的GA-BP神经网络回归模型的相关系数R值分别提高了0.163，0.229与0.056，均方根误差RMSE分别降低了122.334、158.462和46.923 kg/hm2，使用多源遥感数据的组合可以很好地提高作物产量估算的准确性。（房世波）

2 农业气象

2 Agricultural meteorology

2.1 Integrated remote sensing and crop model approach for impact assessment of aerosols on biomass accumulation of maize

The remote sensing data and crop model were used to explore the dynamic changes and accumulation of maize biomass in China caused by aerosols in this study. Maize varieties were divided into spring maize and summer maize. Two spring maize and three summer maize stations were selected. The results indicated that the solar radiation through all stages of maize development was reduced by aerosols, with daily average reductions of 3.23 MJ m−2d−1for spring maize and 8.96 MJ m−2d−1for summer maize from 2001 to 2014.Aerosols reduced the daily actual maize biomass in the study area, with an average daily decrease of 3.78 g m−2d−1from 2001 to 2014. Moreover, the changes in daily actual biomass caused by aerosols varied in different growth stages. The reduction in daily actual biomass caused by aerosols in the stage of emergence‒flowering was larger than that in the stage of flowering‒maturity. For spring maize, the changes in daily actual biomass caused by aerosols were –2.12 to –2.29 g m−2d−1from emergence to flowering and ‒0.72 to 0.08 g m−2d−1from flowering to maturity. For summer maize, the changes in daily actual biomass caused by aerosols were–8.94 to –3.45 g m−2d−1from emergence to flowering and ‒6.50 to ‒2.24 g m−2d−1from flowering to maturity.In addition, the annual maize biomass from 2001 to 2014 at five stations clearly decreased owing to aerosols.Moreover, the decrease in the annual biomass of summer maize was greater than that of spring maize, with an average decrease of 27.77% in summer maize biomass and 10.94% in spring maize biomass. ( Zhao Junfang)

2.2 Long-term variations in solar radiation, diffuse radiation, and diffuse radiation fraction caused by aerosols in China during 1961–2016

The effects of atmospheric aerosols on the terrestrial climate system are more regional than those of greenhouse gases, which are more global. Thus, it is necessary to examine the typical regional effects of how aerosols affect solar radiation in order to develop a more comprehensive understanding. In this study, we used global AErosol RObotic NETwork (AERONET) data and robust radiation observational evidence to investigate the impact of aerosols on total radiation, diffuse radiation, and the diffuse radiation fraction in China from 1961 to 2016. Our results showed that there were different temporal changes in the aerosol optical depth (AOD),total solar radiation, diffuse radiation, and diffuse radiation fraction over the past 56 years. Specifically, the 550 nm AOD from 2005 to 2016 decreased significantly, with annual average AOD of 0.51. Meanwhile, the average total solar radiation reduced by 2.48%, while there was a slight increase in average diffuse radiation at a rate of 3.10 MJ m−2yr−1. Moreover, the spatial heterogeneities of AOD, total radiation, diffuse radiation,and the diffuse radiation fraction in China were significant. Aerosol particle emissions in the developed eastern and southern regions of China were more severe than those in the western regions, resulting in higher total radiation and diffuse radiation in the western plateau than in the eastern plain. In addition, aerosols were found to have negative effects on total radiation and sunshine hours, and positive effects on diffuse radiation and diffuse radiation fraction. Further, the diffuse radiation fraction was negatively correlated with sunshine hours.However, there was a positive correlation between AOD and sunshine hours. These results could be used to assess the impacts of climate change on terrestrial ecosystem productivity and carbon budgets. ( Zhao Junfang)

2.3 Assessment of seasonal variability of extreme temperature in mainland China under climate change

Some studies have suggested that variations in the seasonal cycle of temperature and season onset could affect the efficiency in the use of radiation by plants, which would then affect yield. However, the study of the temporal variation in extreme climatic variables is not sufficient in China. Using seasonal trend analysis (STA),this article evaluates the distribution of extreme temperature seasonality trends in mainland China, describes the trends in the seasonal cycle, and detects changes in extreme temperature characterized by the number of hot days (HD) and frost days (FD), the frequency of warm days (TX90p), cold days (TX10p), warm nights(TN90p), and cold nights (TN10p). The results show a statistically significant positive trend in the annual average amplitudes of extreme temperatures. The amplitude and phase of the annual cycle experience less variation than that of the annual average amplitude for extreme temperatures. The phase of the annual cycle in maximum temperature mainly shows a significant negative trend, accounting for approximately 30% of the total area of China, which is distributed across the regions except for northeast and southwest. The amplitude of the annual cycle indicates that the minimum temperature underwent slightly greater variation than the maximum temperature, and its distribution has a spatial characteristic that is almost bounded by the 400 mm isohyet, increasing in the northwest and decreasing in the southeast. In terms of the extreme air temperature indices, HD, TX90p, and TN90p show an increasing trend, FD, TX10p, and TN10p show a decreasing trend.They are statistically significant (p < 0.05). This number of days also suggests that temperature has increased over mainland China in the past 42 years. ( Zhao Junfang)

2.4 Indicator-based spatiotemporal characteristics of apple drought in North China

Frequent occurrences of drought stress caused by dry weather create severe destroy in apple yield and quality in North China. Although appropriate drought stress is beneficial to apple planting, it might change to apple drought disaster when dry weather continues and reaches to a certain magnitude. So, precisely identification of apple drought based on weather condition is of great merit to provide a basis for targeted apple drought monitoring, early warning and evaluation. To explore the trigger dry weather condition of an apple drought event, apple drought index (ADI) was firstly constructed by the consideration of physiological water demand and precipitation characteristics. The ADIs in historical apple drought disaster samples were reanalysed in North China, and the distribution-type fitting and confidence interval method were used to identify the drought trigger thresholds in the apple drought indicators. Afterwards, spatiotemporal characteristics of apple drought in North China from 1981 to 2018 were explored based on the apple drought indicators. Drought trigger thresholds were ADI 0.86, 0.84 and 0.76 for apple tree germinating to bud brush (P1), bud brush to flowering (P2) and flowering to maturity (P3), respectively. A percentage of 81.82% of drought indicatorbased results were strongly consistent with historical records about apple drought disasters. Indicator-based regional average apple drought ratios in North China from 1981 to 2018 were 28.27%, 28.33% and 20.82% in P1, P2 and P3, respectively. 2009, 2000 and 2001 were detected the highest drought frequency years for P1,P2 and P3, with drought ratio 57.07%, 60.00% and 40.98%, respectively. The results can provide technical and theoretical support for targeted apple drought detection, and information and measures for apple drought prevention and mitigation can be implemented according to the indicator-based results. (Yang Jianying)

2.5 Process-based indicators for timely identification of apricot frost disaster on the warm temperate zone, China

Frequent occurrences of late spring frost disaster create severe agricultural/forest damage, even given the background of global warming. In the warm temperate zone of China, which is the largest planting area for fresh apricot, late spring frost disaster has become one of the major meteorological hazards during flowering.To prevent cold weather-induced apricot frost disaster and reduce potential losses in related fruit economic value, it is vital to establish a meteorological indicator for timely and accurate identification of cold weather process-based apricot frost disaster, to provide support for timely apricot frost monitoring and warning in late spring. In this study, daily minimax temperature (Tmin) and apricot frost disaster data during flowering were combined to establish meteorological identification indicators of apricot frost based on cold weather processes.A process-based apricot frost model f (D,T Tcum) was firstly constructed, and characteristics of Tcum(accumulated harmful temperature) were explored under different D (duration days) based on the representation of historical apricot frost processes. Thresholds for the Tcumfor apricot frost in 1, 2, 3, 4 and more than 5 days of apricot frost process were determined as −1.5, −2.9, −4.4, −5.8 and −7.3 °C, respectively. Validation results by reserved independent disaster samples were generally consistent with the historical records of apricot frost disasters,with 89.00% accuracy for indicator-based identification results. Typical process tracking of the proposed identification indicator to an apricot frost event that occurred in North Hebei during April 3−9, 2018 revealed that the indicator-based identification result basically coincides with the historical disaster record and can reflect more detailed information about the apricot frost process. (Yang Jianying)

2.6 Threshold-based characteristics of apricot frost exposure at young fruit in the warm temperate zone, China

Late spring frost stress is one of the major environmental limiting factors for apricot in the warm zoon in China. Investigation of frost exposure of apricot is of particular interest for estimating the frost risk, thus representing the potential damage for apricot production. In this study, daily minimum temperature (Tmin),disaster and phenological data of apricot from 1981 to 2020 in the warm zoon were integrated to explore the temperature threshold on apricot at young fruit, facilitating the assessment of apricot frost exposure under the background of climate warming. The daily Tminwas firstly extracted according to the historical disaster records,to identify the per- and ongoing weather conditions of the low-temperature events. The overall accuracy and receiver operating characteristics curve (ROC) were combined to identify the trigger threshold of apricot frost.The temperature of 1.9 was identified as the apricot frost trigger threshold in regional assessment, with relatively higher correct rate for disaster (90.2%) and lower incorrect rate for none-disaster (23.4%). An area under the ROC curve (AUC) of 0.88 was obtained, demonstrating a good performance of Tminas the trigger factor in discriminating between apricot frost and no frost. High frequency of days suffered from apricot and frost exposure (E) at young fruit were mainly found in the northwestern and middle parts of the region, with frequencies of more than 2 days and E more than 3. Regional days suffered from apricot frost and E were found to have a negative trend with slope −0.0317 and −0.789, respectively, whereas the northwest and middle part of the study region were found to have an increasing trend. The results can provide technical and theoretical support for targeted apricot frost detection and risk assessment, and measures for apricot frost prevention and mitigation can be implemented according to the threshold-based results. (Yang Jianying)

2.7 Dryland maize yield potentials and constraints: A case study in western Kansas

Water-limited environments account for half of the earth’s land surface and dryland agriculture acreage is projected to expand due to climate changes. Examining typical dryland yield potentials and yield improvement measures is crucial for developing future dryland crop production systems. This case study used crop modeling to analyze dryland maize yield potential (YPd), farmers’ yield potential (YPf), and actual farm yields (Ya)in 1990−2015 in three counties in western Kansas (i.e., Thomas, Greeley and Finney in the U.S. Great Plains region). The calibrated APSIM-Maize model along with actual yields was used to estimate yield gaps attributed to: (1) agronomic factors (YG1 = YPd − YPf) and, (2) socio-economic constraints (YG2 = YPf − Ya).Observed climate conditions during maize growing seasons showed warming, brightening, and drying trends for all three counties in western Kansas from 1990 to 2015. Our results showed that the current actual farm yields (Ya) in western Kansas represented only 34%, 32%, and 28% of YPd in Thomas, Greeley, and Finney counties respectively, indicating significant exploitable yield gaps. Agronomic factors (YG1) contributed the greatest to the yield gap in Greeley and Finney counties whereas socioeconomic constraints (YG2) offered the greatest opportunity for improvement in Thomas county. Our analysis suggested that improving agronomic management could be a greater priority for further yield improvement in Greeley county but selecting an appropriate hybrid was a greater priority in Finney county. (Sun Shuang)

2.8 Standardized relative humidity index can be used to identify agricultural drought for summer maize in the Huang-Huai-Hai Plain, China

Maize (Zea mays L.) is a staple food in most parts of the world, and is also one of the most important food crops in China. Frequent occurrences of drought events can lead to summer maize drought disasters. The air relative humidity has the predominant superiority in spatio-temporal continuity compared to precipitation.In this study, meteorological data, phenophase observations, and disaster records of summer maize in the Huang-Huai-Hai Plain (the HHH Plain) were jointly used to establish a standardized relative humidity index(SRHI) to identify and characterize summer maize drought disasters and to provide support for summer maize drought monitoring, prevention, and mitigation. Results showed that the threshold values of SRHI10 (at tenday scale) during the V0-VT (planting-tasseling) and VT-R6 (tasseling-physiological maturity) periods were−0.05 and −0.25, and the values of SRHI30 (at monthly scale) during the V0-VT and VT-R6 periods were −0.10 and −0.50, respectively. Both SRHI10 and SRHI30 could reasonably identify the actual drought conditions of summer maize in the HHH Plain. Validation with independent drought samples showed that SRHI10 was the most effective among SRHI10, SRHI30, and SPI10. The province-wide validation within 55 years also revealed that the drought of summer maize identified with SRHI10 was basically consistent with historical disaster records, with the average identification accuracy being of 94.0%. Additionally, SRHI10 could indicate the occurrence of drought relatively earlier than actual drought records during both the V0-VT and VT-R6 periods of summer maize. Therefore, the spatio-temporal distribution characteristics of drought for summer maize in the HHH Plain were mapped based on SRHI10. Drought occurred in 38% and 25% of the years during the V0-VT and VT-R6 periods, respectively, from 1961 to 2015. The drought extent during the V0-VT period was greater than that during the VT-R6 period in 64% of the study years, indicating that summer maize in the HHH Plain was more exposed to drought during the vegetative growth period. The spatial distribution pattern of drought severity increased from the south to north during the V0-VT period, while during the VTR6 period it exhibited the same spatial pattern to drought frequency. The drought in both the V0-VT and VTR6 periods of summer maize showed the increasing trend in most of the HHH Plain of China. SRHI10 can be a useful indicator for monitoring and assessing summer maize drought disasters at regional scale. This index can also provide a new method for agricultural drought analysis. (Wang Peijuan )

2.9 Spring frost damage to tea plants can be identified with daily minimum air temperatures estimated by MODIS land sur-face temperature products

Tea (Camellia sinensis) is one of the most dominant economic plants in China and plays an important role in agricultural economic benefits. Spring tea is the most popular drink due to Chinese drinking habits.Although the global temperature is generally warming, spring frost damage (SFD) to tea plants still occurs from time to time, and severely restricts the production and quality of spring tea. Therefore, monitoring and evaluating the impact of SFD on tea plants in a timely and precise manner is a significant and urgent task for scientists and tea producers in China. The region designated as the middle and lower reaches of the Yangtze River (MLRYR) in China is a major tea plantation area producing small tea leaves and low shrubs.This region was selected to study SFD to tea plants using meteorological observations and remotely sensed products. Comparative analysis between minimum air temperature (Tmin) and two MODIS nighttime land surface temperature (LST) products at six pixel-window scales was used to determine the best suitable product and spatial scale. Results showed that the LST nighttime product derived from MYD11A1 data at the 3×3 pixel window resolution was the best proxy for daily minimum air temperature. A Tminestimation model was established using this dataset and digital elevation model (DEM) data, employing the standard lapse rate of air temperature with elevation. Model validation with 145210 ground-based Tminobservations showed that the accuracy of estimated Tminwas acceptable with a relatively high coefficient of determination (R2=0.841), low root mean square error (RMSE=2.15 °C) and mean absolute error (MAE=1.66 °C), and reasonable normalized RMSE (NRMSE=25.4%) and Nash-Sutcliffe model efficiency (EF=0.12), with significantly improved consistency of LST and Tminestimation. Based on the Tminestimation model, three major cooling episodes recorded in the “Yearbook of Meteorological Disasters in China” in spring 2006 were accurately identified, and several highlighted regions in the first two cooling episodes were also precisely captured. This study confirmed that estimating Tminbased on MYD11A1 nighttime products and DEM is a useful method for monitoring and evaluating SFD to tea plants in the MLRYR. Furthermore, this method precisely identified the spatial characteristics and distribution of SFD and will therefore be helpful for taking effective preventative measures to mitigate the economic losses resulting from frost damage. (Wang Peijuan )

2.10 Mapping threats of spring frost damage to tea plants using satellite-based minimum temperature estimation in China

Spring frost damage (SFD), defined as the disaster during the period of newly formed tea buds in spring caused by lower temperature and frost damage, is a particular challenge for tea plants (Camellia sinensis),whose capacity to adapt to extreme weather and climate impacts is limited. In this paper, the region of the middle and lower reaches of the Yangtze River (MLRYR) in China was selected as the major tea plantation study area, and the study period was focused on the concentrated occurrence of SFD, i.e., from March to April. By employing the standard lapse rate of air temperature with elevation, a minimum temperature (Tmin)estimation model that had been previously established was used based on reconstructed MYD11A1 nighttime LST values for 3×3 pixel windows and digital elevation model data. Combined with satellite-based Tminestimates and ground-based Tminobservations, the spatiotemporal characteristics of SFD for tea plants were systematically analyzed from 2003 to 2020 in the MLRYR. The SFD risks at three scales (temporal, spatial,and terrain) were then evaluated for tea plants over the MLRYR. The results show that both SFD days at the annual scale and SFD areas at the daily scale exhibited a decreasing trend at a rate of 2.7 days decade−1and 2.45×104ha day−1, respectively (significant rates at the 0.05 and 0.01 levels, respectively). The period with the highest SFD risk appeared mainly in the first twenty days of March. However, more attention should be given to the mid-to-late April time period due to the occurrence of late SFD from time to time. Spatially, areas with relatively higher SFD days and SFD risks were predominantly concentrated in the higher altitude areas of northwestern parts of MLRYR for both multi-year averages and individual years. Fortunately, in regions with a higher risk of SFD, the distribution of tea plants was relatively scattered and the area was small. These findings will provide helpful guidance for all kinds of people, including government agencies, agricultural insurance agencies, and tea farmers, in order that reasonable and effective strategies to reduce losses caused by spring frost damage to tea plants may be recommended and implemented. (Wang Peijuan )

2.11 GHCN-CAMS和CMFD两种尺度再分析资料对宁夏气温反映能力评估

再分析资料能有效弥补实际观测数据时空分布不均的缺陷，开展再分析资料区域适应性评估对地气过程研究、气候分析等具有重要意义。论文利用宁夏24 个气象观测站的平均气温，从2种空间尺度（0.5°×0.5°和0.1°×0.1°）和2种时间尺度（年、月），采用偏差、绝对偏差、均方根误差和相关系数等多个统计指标，评估了再分析资料对宁夏地区地面气温的反映能力。结果表明：（1）GHCNCAMS（Global Historical Climatology Network and the Climate Anomaly Monitoring System）和CMFD（China Meteorological Forcing Dataset）2 套再分析资料对宁夏气温的反映能力整体上均较强，前者对宁夏气温略高估，后者略低估。（2）年和月2种时间尺度上，2种尺度的再分析资料存在阶段性正偏差和负偏差，且年尺度上的相关性好于月尺度的。（3）2套再分析资料对下垫面主要为农田(压砂种植)的气温均存在冷季高估、暖季低估的情况，对城镇两者总体均低估，对草地整体表现为CMFD 在冷季低估、暖季略高估，而GHCN-CAMS在冷季高估、暖季低估。总体看，空间分辨率较高的CMFD再分析资料对宁夏气温的反映能力更好一些。(赵俊芳)

2.12 作物发育模式重构及基于甘蔗的模拟检验

发育进程是作物的生理年龄， 发育模式是作物生长模型的时间指针。 但目前的发育模式只关注某时段（日）气象条件对作物发育的影响，其准确率也难以满足作物生长模拟的需求。 根据作物发育速率不仅与气象条件有关、还与其所处发育期有关的理论假设， 重构发育进程模式， 并利用1980—2019年我国甘蔗发育实测数据进行模式适应性分析， 比较传统模式与重构模式的模拟能力。 结果表明：重构模式中，发育单位日序模式和温度日序模式对甘蔗发育进程的适应性均较好， 尤其在后期温度不断降低的发育进程以及低温年型的模拟中， 其适应能力明显优于传统模式。 重构及传统模式模拟能力从强到弱依次为发育单位日序模式、 温度日序模式、 响应适应模式、 发育单位模式、 发育单位温度修正模式、 热量单位模式， 均方根误差计算的模拟能力值依次为4.3、3.9、3.7、3.3、3.0、2.8。（马玉平）

2.13 中国普通油茶种植气候适宜性区划

发展油茶产业可有效增加农民收益，促进精准扶贫并改善生态环境。对油茶进行全国尺度的气候适宜性区划，可以为油茶产业的发展提供科学依据。本研究以中国分布面积最广、产量最高的普通油茶为对象，选择年平均气温、1月和7月平均气温、年降水量和日照时数为关键气候因子，计算主产区（即种植面积在6667 hm2以上的县市） 的关键因子值。基于这些因子值，采用改进的气候相似距法进行全国1 km×1 km网格的普通油茶种植气候适宜性区划。结果表明：中国普通油茶的最适宜区面积为98×104km2，主要分布在湖南、江西、福建和浙江四省及周围省的相邻区域；适宜区面积和次适宜区分别为52×104km2和80×104km2，依次分布在最适宜区的外围；次适宜区北界约为北纬33.5°，西界约为东经111.5°，南界和东界不明显；湖南省的最适宜区面积最大，其次是江西、广西、浙江和福建，五省合计约占全国最适宜区面积的70%；与多种来源实际种植面积资料对比表明，区划较好地反映了普通油茶的种植状况；与主产区气候特征对比表明，区划较为准确地区分了普通油茶最适宜区、适宜区和次适宜区的气候特征。本研究明确了普通油茶种植气候适宜区的分布，可为油茶产业的规划布局提供科学支撑。(邬定荣)

2.14 中国电线积冰灾害研究进展

电线积冰灾害是导致电力系统发生事故的重要自然灾害之一。基于已有研究成果，从电线积冰相关概念与分类出发，对电线积冰的影响与危害、时空分布、成因、影响因子、预报模型、风险评估以及预防措施等方面进行归纳。我国电线积冰灾害以雾凇型积冰和雨凇型积冰为主，主要环境成因包括准静止锋、大气垂直结构和逆温层，同时还受到地形、高度和导线自身特性等的影响。电线积冰灾害总体上呈现北方多雾凇而南方多雨凇的分布特征，20世纪80—90年代的积冰日数较多，90年代后呈下降趋势。为更好地实现电线积冰灾害的模拟与预测，预报模型也在不断完善，包括物理数值模型和统计预测模型；而对于电线积冰灾害风险评估的研究较少，主要集中在电线积冰灾害的危险性和线路的脆弱性。基于多学科指标构建的电线积冰综合性指标、基于灾变过程的综合风险评估及气候变化对电线积冰的影响将是今后重点研究方向。（霍治国）

2.15 中国北方冬小麦蚜虫气候风险评估

基于1958—2018年中国北方冬小麦主产区8个主产省（市）小麦蚜虫发生面积、防治面积和小麦播种面积、产量损失、561个气象站点逐日气象资料和典型农业气象站小麦发育期资料，采用相关分析、主成分分析和回归分析等方法，构建华北、黄淮及苏皖地区小麦蚜虫分区域的气候致灾指数。以小麦蚜虫年代际气候致灾指数所划分不同致灾等级发生频次作为小麦蚜虫气候危险性指标，采用小麦蚜虫发生面积率作为脆弱性指标，防治面积与发生面积比值作为防灾减灾能力指标，综合评估小麦蚜虫气候风险趋势。结果表明：北方冬小麦主产区小麦蚜虫气候危险性呈增加态势，年代际差异明显；小麦蚜虫发生脆弱性随年代变化也呈逐步加重态势；小麦蚜虫防灾减灾能力总体呈逐步增强趋势，20世纪90年代提升显著；90年代起小麦蚜虫气候风险逐步加重，高风险范围逐渐扩大，华北、黄淮分别于21世纪初、2011—2018年风险等级达最高；小麦蚜虫气候风险高的区域主要分布在北京、天津、河北中南部大部、山东北部部分地区，较高区域分布在山东大部、河南北部等地。（霍治国）

2.16 季节性冻土的分布与变化特征及对多样性农区农业生产的影响

研究季节性冻土的分布与变化对多样性农区农业生产的影响，对于合理利用气候资源，指导当地农业生产具有重要的意义。文章以临汾市为例，选用1960—2019年临汾市17个观测站逐日的冻土深度、温度、地温、降水量和蒸发量等资料数据，采用克里金空间插值法分析研究区冻土的空间分布，并运用M-K检验、一元线性回归、相关分析等方法分析研究区不同海拔高度季节性冻土的变化趋势及影响因素。（1）临汾市季节性冻土深度在山区大于盆地，北部大于南部，冻土深度与海拔高度正相关显著，相关系数为0.712 （P＜0.01）具有明显的垂直分布特征。（2）近年来最大冻土深度呈明显下降趋势，变化倾向率平均为-2.304 cm/10a，高海拔地区变化趋势尤为显著，1982年冻土深度发生突变，突变后从一个相对偏深期跃变为相对较浅期。（3）冻土始冻日山区早于平川，北部早于南部，解冻日刚好相反，冻土持续期平均相差1个月左右；多年来临汾市土壤表面始冻日推迟，解冻日提前，冻土期明显减少，平均变化率分别为2.088 d/10a、1.762 d/10a和4.069 d/10a，低海拔地区变化趋势更为明显。（4）相关分析表明，冻土深度受冬季地面最低气温影响极显著，其中1月的地面最低气温升高对冻土深度变化起到主要的促进作用，这种影响在高海拔地区更为明显；春、秋两季的地面最低气温升高，使研究区始冻日推迟，解冻日提前，相关系数分别为-0.741、-0.408（P＜0.01），冻土期明显缩短，蒸发量的相对减少对冻土期和冻土深度变化起到一定抑制作用，降水量对冻土期和冻土深度影响甚微。临汾市冻土期缩短，冻土深度变浅，使越冬农作物干旱加剧，病虫害发生几率增加，同时增加了植物安全越冬系数，使作物生长季延长，对农业增产起到一定作用。（霍治国）

2.17 山西省干旱灾害风险评估与区划

分析山西省干旱灾害风险的关键作用因子，并进行风险评估和区划，对于提升该地干旱灾害风险管理和决策水平、减轻干旱损失具有重要指导意义。文章利用改进的相对湿润度指数、DEM资料、地形坡度资料和1990—2016年以县（市）为单元的行政区域的人口密度、GDP、人均GDP、耕地面积等社会经济数据来定量化评价山西干旱风险，从干旱灾害致灾因子的危险性、孕灾环境的脆弱性、承灾体的易损性和防灾减灾能力4个方面选取因子，构建相应的指数模型并分析其空间分布状况，在此基础上进一步构建山西省干旱灾害风险综合评估模型，并基于GIS 绘制山西省干旱灾害风险区划图。山西省干旱致灾因子危险性呈北高南低的趋势，大同、朔州、忻州北部和西部、太原南部的干旱致灾因子危险性最强；孕灾环境脆弱性呈东西两侧高、中间低的趋势，而承灾体易损性和防灾减灾能力均呈东西两侧低、中间高的趋势；从干旱灾害风险区划图可以看出，山西省干旱风险总体呈北高南低，从西北向东南递减的趋势。高风险区主要分布在大同、朔州东部，较高风险区包括朔州西部、忻州中西部、太原大部，吕梁大部、晋中西部、临汾中部、运城西部为中风险区，临汾西部、晋中大部、长治东北部为较低风险区，临汾东部、运城东部、晋城大部、长治西部和南部风险最低。山西省干旱灾害的精细化风险区划，可为相关区域有效地开展抗旱活动提供定量化依据，增强干旱灾害防御的科学性、实用性和可操作性。（霍治国）

2.18 山西省主要粮食作物气候资源利用率评估

分析和评价区域农业气候资源状况，找出影响农业气候资源有效匹配的限制因子，提高农业气候资源利用率，对促进农业生产、提升农业产能具有重要的实践意义。本文基于山西省1981—2018 年108 个地面气象观测站的逐日气温、降水、日照等气象资料及31个农业气象观测站春玉米、夏玉米和冬小麦的发育期观测资料，采用平均资源适宜指数、平均效能适宜指数和平均资源利用指数分析了山西省不同作物种植区的气候资源适宜程度、匹配状况和利用率，结果表明：（1）山西省春玉米种植区大部气候资源适宜程度、匹配程度和利用率均较高，西部呈增加趋势、中东部大部呈降低趋势；朔州和忻州中西部温度偏低，制约了该区域光、温、水的合理匹配，利用率较低。（2） 山西省夏玉米种植区气候资源适宜度较高，但匹配一般，尤其是运城中西部受降水偏少的影响，气候资源利用率相对较低；全区大部夏玉米气候资源适宜程度、匹配状况及利用率均呈下降趋势。（3） 山西省冬小麦种植区平均资源适宜指数、平均效能适宜指数和平均资源利用指数均呈西北低、东南高的空间分布格局，西北部降水偏少导致光、温、水匹配不佳，利用率较低，长治、晋城、临汾中部和运城东部等地资源利用率呈上升趋势，吕梁、太原、晋中和运城西部等地呈下降趋势。由此可见，晋北地区提高农业气候资源利用率的有效途径重点是提升热量资源的利用率，晋中盆地区域以提高水资源利用率为主，晋南运城及临汾盆地区域除提升水资源利用率外，还需考虑温度持续增高对作物生长发育带来的不利影响。（郭建平）

2.19 中国主产区玉米冠层对降水的截留研究

基于13个农业气象试验站2010—2017年逐日气象观测数据和玉米观测数据，采用针对玉米的截留模型，研究自然降雨条件下中国主产区玉米冠层截留及其变化规律。结果表明：在不同气候条件和生长状况下，玉米全生育期冠层截留差异较大。玉米冠层生长季平均截留量为4.3～23.5 mm，拔节到成熟期降水量≤70 mm时，截留量不足8 mm，随着降水量增加，截留量先是同时受降水量和最大面积指数制衡，后变为对最大叶面积指数更敏感。平均截留率为1.9%～11.6%，中国四大玉米主产区中的黄淮海夏播玉米区截留率最稳定，生长季降水量＜120 mm的地区截留率超过10%，按玉米主产区和气候干湿度两种分类提供平均截留率范围。依据拔节到成熟期降水量、最大叶面积指数及截留变化规律可以估算不同地区玉米冠层截留量和截留率，为有效降水评估、干旱指标修正、农田水分循环等方面提供科学依据。（郭建平）

2.20 中国北方苹果干旱等级指标构建及危险性评价

构建苹果干旱等级指标体系，评估苹果干旱危险性，对开展苹果干旱防灾减灾、灾害保险意义重大。本文以中国北方苹果主产区为研究对象，利用气象资料、苹果干旱灾情史料和发育期资料，在干旱指数（DI）构建的基础上，以历史灾情反演、灾害样本重建和历史灾害过程解析为主线，采用独立样本T检验、K-S检验、累积概率反函数值等方法，构建适用于中国北方苹果主产区的苹果干旱等级指标体系，并在此基础上开展苹果干旱危险性评价，结果表明：构建的干旱指数（DI）能有效表征苹果干旱灾害；同一等级苹果干旱指标阈值果树萌动—萌芽期＞萌芽—盛花期＞盛花—成熟期；苹果危险性萌芽—盛花期＞果树萌动—萌芽期＞盛花—成熟期，渤海湾产区及黄土高原产区北部是苹果干旱的高危险区域。基于历史灾情资料加工与再分析的苹果干旱等级指标体系构建方法可为经济林果气象灾害研究提供新的思路，研究结果可为中国北方苹果干旱防灾减损气象服务、灾害保险提供基础支撑。（杨建莹）

2.21 从土壤气候视角解析农业文化遗产地的自然禀赋——以宽城传统板栗栽培系统为例

宽城传统板栗栽培系统是中国重要农业文化遗产，宽城板栗栽培历史悠久，品质优良,为了从土壤气候角度解析宽城板栗栽培系统的自然禀赋和不足，本文利用宽城县基本气象站和自动气象站的观测资料以及专项进行的土壤取样分析数据全面分析了宽城板栗栽培的土壤和气候条件，综合评价了宽城板栗栽培的气候适宜性及其空间分布。结果表明：宽城板栗林土壤酸碱度适宜，有机质丰富，N、K含量和Fe、Mn、 Mg等微量元素含量较高，宽城光热资源完全满足板栗生长成熟需要，果实生长期水分供应充足，果实成熟期气温日较差大，板栗主要栽培区域综合气候条件优于板栗栽培适宜指标。总之，宽城板栗栽培系统拥有较好的土壤气候环境，具备栽培高产优质板栗的条件和潜力，春季降水偏少是宽城板栗高产的一个限制因素，适当的春季灌溉可较大幅度地促进板栗高产优质潜力的发挥。（谭凯炎）

2.22 华北平原不同等级干旱对冬小麦产量的影响

华北平原是中国重要的粮食生产基地，其中冬小麦播种面积和产量均居中国首位，在国家粮食安全中具有重要作用，干旱是影响该区域冬小麦产量的最主要农业气象灾害。该研究基于华北平原44个气象站点1981—2017年的逐日气象数据以及作物、土壤和田间管理资料，以作物水分亏缺指数为农业干旱指标，基于调参验证后的农业生产系统模型（APSIM），评估了冬小麦生长发育中后期各生育阶段不同等级干旱对冬小麦单产和总产的影响。结果表明，冬小麦拔节—开花和开花—成熟阶段干旱造成冬小麦减产率空间上均呈北高南低的分布特征，且开花—成熟阶段干旱引起的减产率（26.8%）高于拔节—开花阶段干旱引起的减产率（19.1%），区域间比较均表现为干旱对京津冀地区冬小麦单产影响最大，对河南省冬小麦单产影响最小；随着干旱等级的加重减产率增大，开花—成熟阶段轻旱、中旱和重旱的减产率分别为16.5%、32.8%和44.9%，拔节—开花阶段轻旱、中旱和重旱的减产率分别为10.3%、18.8%和28.6%。结合冬小麦实际播种面积得到各生育阶段干旱对总产的影响，区域间比较均表现为干旱对山东省冬小麦总产影响最大，对河南省冬小麦总产影响最小。（孙爽）

2.23 我国北方一作区马铃薯高产稳产区分布特征

北方一作区马铃薯种植面积和总产居我国首位，明确其高产稳产区分布，对马铃薯合理布局具有重要意义。基于研究区域内234个气象站点1981—2019年逐日气象数据以及作物、土壤资料，利用APSIM-Potato模型，以产量平均值和变异系数为高产性和稳产性评价指标，将研究区域划分为高产高稳、高产低稳、低产高稳和低产低稳4个亚区，明确了过去39年不同生产水平下我国北方一作区马铃薯高产稳产区分布特征，解析了降水和土壤对马铃薯高产性和稳产性的影响。结果表明：过去39年不同生产水平下马铃薯高产区比例呈下降趋势；随着限制因素增加，高产高稳区面积比例逐渐降低，气候—土壤潜在生产水平下高产高稳区面积比例仅占研究区域总面积的13%；高产低稳区是潜在的高产高稳区，需重点关注，及时采取有效措施提升稳产性。降水对马铃薯高产性和稳产性的影响大于土壤因素。实际生产中，降水和土壤限制下高产性和稳产性降低的区域，应注意结合当地灌溉条件配合耕作措施，以确保马铃薯高产稳产。（孙爽）

2.24 中国大陆茶树种植气候适宜性区划

基于1961—2019年全国1903个气象站点的气候数据以及1115条茶树分布站点记录，利用最大熵模型和GIS技术筛选影响茶树种植的主导气候因子，根据自然间断点分级法将中国大陆茶树气候适宜性划分为不适宜区、次适宜区、适宜区和高适宜区4个等级，厘定不同区划等级的主导气候因子阈值。结果表明，影响中国大陆地区茶树种植分布的主导气候因子为多年平均极端最低气温、春霜冻频率、年平均气温、年降水量和3—9月平均相对湿度。模型区划结果与名茶之乡、地理标志茶叶所在地吻合较好。茶树适生区的北界总体呈现出由东部高纬度向西部低纬度降低的分布态势，北界界限移动较明显地区主要分布在东部高纬度省份。整体茶树适生区质心的年代际变化较为平缓，除20世纪60—70年代和80—90年代的适生区范围有所缩小外，其他相邻年代际间茶树适生区的面积均呈现出不同程度的增长趋势，与质心迁移情况相吻合。（王培娟）

2.25 中国茶树春霜冻害研究进展

茶树作为我国主要的经济作物，在早春萌发时易遭受霜冻害。本文系统归纳了茶树春霜冻害的研究进展和取得的主要成果，并对未来茶树春霜冻害研究进行展望。我国茶树春霜冻多发于长江中下游，霜冻灾害指标可按照获取方法、数据类别、气象数据的时间尺度进一步细分。在全球变暖的背景下，茶树春霜冻发生次数虽呈下降趋势，但其危害不可忽视；其中，江南茶区茶树春霜冻的发生频率呈现出由南向北逐渐增加的纬向分布以及随海拔的升高而增大的地形分布特征。茶树春霜冻影响评估目前多集中于江苏、浙江、安徽、江西等茶区，且逐步由定性向定量发展；风险评估主要基于自然灾害风险形成机制划分不同的风险等级。今后，完善茶树春霜冻的气象指标、构建基于茶园小气候的茶树春霜冻灾害指标、阐明国家尺度上茶树春霜冻的时空分布特征、开展精细化茶树春霜冻风险评估将备受关注。（王培娟）

2.26 基于多种算法的果树果实生长模型研究——以云南昭通苹果为例

针对果树果实与生长过程中的气象因子关联密切，且生长过程多为非线性、非平稳序列，直接对其连续测定难度较大的问题，对比多种模型对果实直径的模拟能力，为果树及其果实的生长发育监测和预测、适时灌溉施肥、生长环境调控等提供科学参考。以云南昭通苹果为例，分析2019和2020年果实生长期间直径变化特征及其与环境气候因子的关系。引入深度学习中的长短期记忆模型（LSTM），使用LSTM模型对苹果果实直径进行模拟及预测，与多元线性回归模型（MLR）和机器学习模型中的决策树（DT）及随机森林（RF）模型的模拟结果进行对比分析，并使用3种采样方法对不同模型模拟的结果进行评估。苹果果实直径有明显日变化特征，呈夜间直径增长而白天缩小为主的规律，一般早晨直径达到最大，然后逐渐微缩，在日落前后直径到达当日最小。苹果果实直径的增长速率在果实膨大初期较高，在果实生长后期降低。苹果果实小时和日平均直径与土壤温度和土壤湿度呈中度或高度正相关，与紫外线指数（UVI）呈高度负相关。苹果果实直径的日平均增长量（FMDG）、日增长量（FDG）、日最大变化量（MDFS）与60 cm土壤温度和20、40 cm土壤湿度呈低负相关（-0.5≤R＜-0.3）。4个模型的模拟结果相比，LSTM模型的模拟精度高于MLR、DT和RF模型。LSTM模型比MLR模型在相关系数R增加3%～20%的情况下，RMSE和MAE下降50%～75%，而机器学习模型DT和RF对苹果果实直径的预测相对较差，可能存在过度拟合。对比统计学、机器学习和深度学习等方法，LSTM模型在苹果果实直径的模拟中表现出更高的精度和可靠性，能更好地解决果实生长过程中的复杂非线性问题。（孙擎）