Effects of different long-term crop straw management practices on ammonia volatilization from subtropical calcareous agricultural soil

长期秸秆还田或秸秆焚烧会显著影响土壤肥力及土壤氮素循环,但该措施对土壤氨挥发的影响仍尚不明确。本研究利用秸秆还田长期定位试验小区,研究了无秸秆配施(CK),配施100%或50%秸秆(SI1, SI2)和配施50%秸秆焚烧(SI2B)对土壤氨挥发的影响。结果表明:氨挥发在小麦季持续38天,而玉米季持续7–10天。秸秆还田显著影响混施基肥期的土壤氨挥发而非表施追肥期。与CK相比, SI1和SI2分别降低了35.1%和16.1%的年累积氨排放,可能因为秸秆的高C/N比及较高的微生物活性促进了无机氮的固定降低土壤NH4+的浓度。SI2B比SI2增加了29.9%的氨排放。因此,长期合理的秸秆还田可为石灰性旱地土壤氨挥发减排提供选择和依据。     

Winter crop sensitivity to inter-annual climate variability in central India

India is predicted to be one of the most vulnerable agricultural regions to future climate changes. Here, we examined the sensitivity of winter cropping systems to inter-annual climate variability in a local market and subsistence-based agricultural system in central India, a data-rich validation site, in order to identify the climate parameters to which winter crops – mainly wheat and pulses in this region – might be sensitive in the future. We used satellite time-series data to quantify inter-annual variability in multiple climate parameters and in winter crop cover, agricultural census data to quantify irrigation, and field observations to identify locations for specific crop types. We developed three mixed-effect models (250 m to 1 km scale) to identify correlations between crop cover (wheat and pulses) and twenty-two climate and environmental parameters for 2001-2013. We find that winter daytime mean temperature (November–January) is the most significant factor affecting winter crops, irrespective of crop type, and is negatively associated with winter crop cover. With pronounced winter warming projected in the coming decades, effective adaptation by smallholder farmers in similar landscapes would require additional strategies, such as access to fine-scale temperature forecasts and heat-tolerant winter crop varieties.     

Rainfall and crop modeling-based water stress assessment for rainfed maize cultivation in peninsular India

Theoretical and Applied Climatology - Water stress due to uneven rainfall distribution causes a significant impact on the agricultural production of monsoon-dependent peninsular India. In the...     

季尺度副热带高压中心内降水分析

利用10年NCEP/NCAR逐日再分析资料和GPCP-1DD降水资料,依据频次分析,研究了季节尺度副热带高压（副高）中心内降水分布的特点。研究结果表明：副高中心内四季均存在降水,其中夏季副高中心降水频次为40%—80%,而其他季节副高中心降水频次不超过50%;季平均副高中心降水率冬季约1—2 mm/d、夏季不超过4 mm/d,它对局地总降水的贡献变化在30%—90%,其中,夏季的贡献基本为50%—90%,其他季节的多数区域贡献一般不超过40%。统计表明,夏季副高中心上升运动频次变化范围为25%—75%,其他季节上升运动频次在25%以下。研究结果还发现夏季西太平洋副高中心频次约30%出现在中国东部大陆,相应的降水频次及上升运动频次分别为25%和15%,从而形成夏季中国东部一种独特的降水天气形势,即500 hPa副高控制下的降水。另外,文中还指出副高中心内降水有一半以上出现在500 hPa存在上升运动的情况下,而半数以下的降水出现时,500 hPa存在下沉运动,前者降水可能为深厚性质,而后者则可能表明为浅薄降水。     

Sensitivity of crop yields and land resource potential to climatic change in Ontario,Canada

Increasing concentrations of atmospheric CO₂ and other greenhouse gases are expected to contribute to a global warming. This paper examines the potential implications of a climatic change corresponding to a doubling of atmospheric concentrations of CO₂ on crop production opportunities throughout Ontario, a major food producing region in Canada. The climate is projected to become warmer and drier, but the extent of these shifts are expected to vary from region to region within Ontario. The effect of this altered climate on crop yields and the area of land capable of supporting specific crops varies according to region, soil quality and crop type. Most notable are the enhanced opportunities for grains and oilseeds in the northern regions, and the diminished production prospects for most crops in the most southerly parts of Ontario.     

Trends of precipitation extreme indices over a subtropical semi-arid area using PERSIANN-CDR

In this study, satellite-based daily precipitation estimation data from precipitation estimation from remotely sensed information using artificial neural networks (PERSIANN)-climate data record (CDR) are being evaluated in Iran. This dataset (0.25°, daily), which covers over three decades of continuous observation beginning in 1983, is evaluated using rain-gauge data for the period of 1998–2007. In addition to categorical statistics and mean annual amount and number of rainy days, ten standard extreme indices were calculated to observe the behavior of daily extremes. The results show that PERSIANN-CDR exhibits reasonable performance associated with the probability of detection and false-alarm ratio, but it overestimates precipitation in the area. Although PERSIANN-CDR mostly underestimates extreme indices, it shows relatively high correlations (between 0.6316–0.7797) for intensity indices. PERSIANN-CDR data are also used to calculate the trend in annual amounts of precipitation, the number of rainy days, and precipitation extremes over Iran covering the period of 1983–2012. Our analysis shows that, although annual precipitation decreased in the western and eastern regions of Iran, the annual number of rainy days increased in the northern and northwestern areas. Statistically significant negative trends are identified in the 90th percentile daily precipitation, as well as the mean daily precipitation from wet days in the northern part of the study area. The positive trends of the maximum annual number of consecutive dry days in the eastern regions indicate that the dry periods became longer in these arid areas.     

环太湖地区土地利用变化的局地气候效应

利用WRF模式和1985年、2005年环太湖区域的土地利用资料,模拟了环太湖区域土地利用变化的局地气候效应,并从陆面过程的角度进行了分析。模拟结果显示：城市扩张区域净短波辐射通量增多,地面温度升高,感热通量增大,潜热通量减小。近地面水平风场在城市化地区风速减小,在城市化带方向上形成狭长的动能衰减区域。湖陆风和城市热岛环流增强,城市化地区向上垂直速度增大,积云性降水增多。老城区和郊区下沉运动增强,对流受到抑制,积云性降水减少。层云降水的改变,集中在层云降水的大值区,且多呈带状分布。总降水在城市化区域增强,在老城区和郊区减少,积云性降水占总降水的比值增大。在土地利用没有变化的区域,降水的改变与地表能量通量的改变在空间分布上大致吻合。     

阿克苏河灌区作物需水量对气候变化的敏感性分析

阿克苏河灌区是中纬度干旱区典型的绿洲灌溉系统,同时也是新疆第二大灌区,了解灌区作物需水量可为灌区种植结构调整、水资源优化配置提供科学依据。本研究基于联合国粮农组织(FAO)的Penman-Monteith蒸散发模型,结合作物系数法估算了阿克苏灌区作物需水量的时空变化及其对气候因子和作物种植结构的敏感性。结果表明,1960—2015年阿克苏灌区多年平均作物需水量为586 mm,且呈显著上升趋势,上升速率为38.43 mm/10 a。随着气候变化和作物种植结构的改变,1990—2015年间作物需水量急剧增加,增加速率高达99.37 mm/10 a。对于不同作物类型,果林的需水量最大,高达829.8 mm,其次是棉花、水稻和玉米,小麦需水量最低。阿克苏灌区的作物需水量对日最高气温和日照时数较为敏感,而对最低气温、风速和水汽压的敏感度较低。当日最高气温升高2℃时,作物需水量增加4%,当日照时数增加10%时,作物需水量将增加3.2%。另外,作物需水量对作物种植结构非常敏感,当果林的种植面积比例增加10%时,作物需水量增加了12.1%。     

Decline of forest area in Sabah,Malaysia: Relationship to state policies,land code and land capability

Forest decline in Sabah has resulted from state policies operating within the federal context. Approximately two-thirds of Sabah's natural forest remains but estimates vary with the data source. Logging and shifting cultivation have degraded forest quality but commercial estate agriculture, especially oil palm, is now the major cause of forest loss, aided by Sabah's land tenure code and the ethnic equality and modernisation agendas of national and state agriculture policy. The pattern of forest decline is explained by partitioning of the land resource between gazetted Forest Reserves and land alienated to agriculture, guided by the 1976 land capability classification.     

冬季北太平洋副高面积和强度指数的一个计算方案

月（季）平均海平面气压场中的北太平洋副高（H,）是北半球的永久性大气活动中心,它与大气环流及区域气候异常关系密切。利用闭合气压系统面积指数S、强度指数P简要描述H,性状,并用它们分析H,气候及异常特征,以及H,与热带东太平洋海表温度异常等关系。因冬季H,明显减弱,在计算H,的S、P指数序列时,难以找出适于整个分析时段的、环流意义明晰的特征等压线。针对该问题,本文给出一个计算方案,先选择一个值较高的f0,用它计算多数年份环流指数5、P;再选择一个值较低的．东,计算少数H_P极端偏弱年份的环流指数S、P;最后用一元线性回归方程,将．矗计算结果S、P订正至f0计算结果S、P,得到S、P的完整序列。应用结果表明,由此求得的H,该完整序列是适当的。     

ECMWF模式副热带高压指数释用产品的应用

应用2006年6—8月欧洲中心数值预报资料,从计算出的副热带高压面积指数、强度指数和西伸脊点、脊线位置及北界位置分析入手,对副热带高压的特征预报进行统计学检验和误差对比分析。结果表明:基于欧洲中心数值预报模式的计算产品对于副热带高压的预报在96 h内误差较小,120—168 h误差较大,副热带高压的预报总体上呈现强度偏强、面积偏大、西脊点偏西和脊线及北界偏北的误差特点。     

副热带云团发展成的台风

本文对8010台风(即Lex台风)的形成进行了分析.8010台风是太平洋副热带高压西部边缘的副热带扰动云团在中纬度西风槽东移作用下发展形成的.这种在副热带地区形成的初始扰动云团发展为台风的事实,是比较少见的.     

Modeling land surface phenology in a mixed temperate forest using MODIS measurements of leaf area index and land surface temperature

The development of satellite-derived vegetation indices and metrics has enabled researchers to monitor land surface phenology (LSP). While the use of satellite data to monitor LSP is prevalent, there has been minimal effort to model LSP in temperate climates using satellite observations of the land surface. Satellite-derived LSP models are beneficial for studying past and future changes in phenology and related ecosystem processes (e.g., water, energy, and carbon fluxes). The purpose of this study was to model LSP during the spring in a mixed temperate forest using satellite-derived measurements of leaf area index (LAI) and land surface temperature (LST). As part of the model validation process, the use of LST as a proxy for air temperature to model LSP was also investigated. The results indicate that LST derived from the MODIS Terra sensor at 10:30?a.m. (local solar time) can be used to develop a LSP model that predicts the full profile of LAI from winter dormancy to maturity and the date when LAI reaches half of the annual maximum (LAI_50%) with relatively low error. In addition, the modeled LAI values closely tracked in situ observations of the phenological development of the dominant deciduous tree species located in the study area where the model was developed. A comparison of LST and daily maximum air temperature at two levels above the ground surface revealed distinct differences and nonlinearities in the relationship between these two variables. However, accumulated growing degree-days calculated from each of these variables were similar because the largest differences between LST and daily maximum air temperature occurred prior to the beginning of heat accumulation. Consequently, the model predictions of LAI_50% derived from the use of LST and daily maximum air temperature were similar. When the developed model was applied in two other mixed forests, the errors were larger due to substantial interannual variability in the relationship between LAI and heat accumulation and systematic differences in this relationship between sites. Although the model cannot be successfully applied in these other mixed forests, the ability of the model to capture a consistent relationship between satellite estimates of LAI and LST in the study area where it was developed demonstrates that satellite observations of the land surface can be used in certain locations to create LSP phenology models. When validated, the models can be used to examine past and future changes in phenology and related ecosystem processes.     

共享社会经济路径在土地利用、能源与碳排放研究的应用

情景是气候变化研究的重要工具。为了科学支撑气候变化科学评估和研究,2010年政府间气候变化专门委员会(IPCC)提出了共享社会经济路径(Shared Socioeconomic Pathways, SSPs)。作为从社会经济变化视角构建的气候情景,SSPs促进了气候变化科学基础、影响、脆弱性、风险、适应和减缓等学科的综合研究。本文介绍了SSPs情景研发与应用过程;阐述了全球和中国的人口经济、土地利用、能源和碳排放的模拟和预估主要成果;探讨了全球和中国碳排放路径及其与“双碳”目标的关系;并展望了SSPs应用前景。     

Scenarios of land use and land cover change in the conterminous United States: Utilizing the special report on emission scenarios at ecoregional scales

Global environmental change scenarios have typically provided projections of land use and land cover for a relatively small number of regions or using a relatively coarse resolution spatial grid, and for only a few major sectors. The coarseness of global projections, in both spatial and thematic dimensions, often limits their direct utility at scales useful for environmental management. This paper describes methods to downscale projections of land-use and land-cover change from the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios to ecological regions of the conterminous United States, using an integrated assessment model, land-use histories, and expert knowledge. Downscaled projections span a wide range of future potential conditions across sixteen land use/land cover sectors and 84 ecological regions, and are logically consistent with both historical measurements and SRES characteristics. Results appear to provide a credible solution for connecting regionalized projections of land use and land cover with existing downscaled climate scenarios, under a common set of scenario-based socioeconomic assumptions.     

Development of daily temperature scenarios and their impact on paddy crop evapotranspiration in Kangsabati command area

Theoretical and Applied Climatology - Production of the principal paddy crop in West Bengal state of India is vulnerable to climate change due to limited water resources and strong dependence on...     

Estimating crop top microclimates from weather station data

Abstract

A mathematical model (Microsim) was developed to estimate the microclimate at the top of nearby crops using inputs of weather station data and some knowledge about crop characteristics, such as height, albedo, and leaf area index. The model was tested using data measured simultaneously over a weather station and over each of two crops ‐ corn and soybean. Temperatures at the top of unstressed, uniform crops on level terrain within 1600 m of a recording weather station were estimated within 1.0° C 96% of the time for a corn crop and 92% of the time for a soybean crop. Winds at crop top were estimated within 0.4 m s^?1 92% of the time for corn and 100% of the time for soybean. Energy balance flux density estimates for the corn crop resulted in correlation coefficients of r > 0.89 for each of R_n, LE, H and G. microsim worked well under atmospheric conditions that ranged from very stable to unstable.

An enhancement was made to the model to describe wind and temperature profiles based on the complete fetch characteristics of the sites. This resulted in significantly better wind estimates, but had the disadvantage of requiring more information about the crop and weather station surroundings.     

Carbon Monoxide emission and concentration models for Chiang Mai urban area

An emission inventory containing emissions from traffic and other sources was complied. Based on the analysis, Carbon Monoxide （CO） emissions from traffic play a very important role in CO levels in Chiang Mai area. Analysis showed that CO emissions from traffic during rush hours contributed approximately 90% of total CO emissions. Regional Atmospheric Modeling System （RAMS） was applied to simulate wind fields and temperatures in the Chiang Mai area, and eight ca~es were selected to study annual variations in wind fields and temperatures. Model results can reflect major features of wind fields and diurnal variations in temperatures. For evaluating the model performance, model results were compared with observed wind speed, wind direction and temperature, which were monitored at a meteorological tower. Comparison showed that model results are in good agreement with observations, and the model captured many of the observed features. HYbrid Particle And Concentration Transport model （HYPACT） was used to simulate CO concentration in the Chiang Mai area. Model results generally agree well with observed CO concentrations at the air quality monitoring stations, and can explain observed CO diurnal variations.