Long-term evapotranspiration rates for rainfed corn versus perennial bioenergy crops in a mesic landscape

Perennial cellulosic crops are promoted for their potential contributions to a sustainable energy future. However, a large-scale perennial bioenergy production requires extensive land use changes through diversion of croplands or conversion of uncultivated lands, with potential implications for local and regional hydrology. To assess the impact of such land use conversions on ecosystem water use, we converted three 22 year-old Conservation Reserve Program (CRP) grasslands and three 50+ year-old conventionally tilled corn-soybean crop fields (AGR) to either no-till continuous maize (corn) or perennial (switchgrass or restored prairie) bioenergy crops. We also maintained one CRP grassland without conversion. We measured evapotranspiration (ET) rates on all fields for 9 years using eddy covariance methods. Results show that: (a) mean growing-season ET rates for perennial crops were similar to the ET rate of the corn they replaced at the previously cultivated (AGR) field but ET rates for perennial crops at CRP fields were 5–9% higher than ET rate for corn on former CRP fields; and (b) mean nongrowing season ET rates for perennial fields were 11–15% lower than those for corn fields, regardless of land use history. On an annual basis, mean ET rates for perennial crops tended to be lower (4–7%) than ET rate of the corn that they replaced at AGR fields but ET rates for perennial crops and corn at CRP fields were similar. Over 9 years, mean ET rates for the same crop across land use histories were remarkably similar for corn, whereas for the perennial crops they were 4–10% higher at former CRP than at former AGR fields, mainly due to differences in growing season ET. Over the 9 years and across all fields, ET returned ~60% of the precipitation back to the atmosphere. These findings suggest that large-scale substitution of perennial bioenergy crops for rainfed corn in mesic landscapes would have little if any (0 to −3%) impact on terrestrial water balances.     

中低风速下海洋飞沫对海气热通量的影响

基于2016-02-01—2016-05-21在南海博贺海洋气象观测平台观测的实验资料,首先利用整体空气动力学算法分别计算海气界面处感热通量与潜热通量,同时利用涡动相关法计算液滴蒸发层处总的感热通量与潜热通量。然后比较海气界面处热通量与液滴蒸发层处热通量的值,并利用差比法分别对2处感热通量和潜热通量进行做差计算。结果表明:液滴蒸发层处热通量与海气界面处热通量存在明显差异。通过与海洋飞沫引起的热通量值比较,结果表明液滴蒸发层处热通量与海气界面处热通量的差值由海洋飞沫作用引起;且在中低风速条件下,海洋飞沫引起的热通量与风速呈正相关;相比感热通量而言,潜热通量随着风速的变化更为显著。     

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Assimilation of historical SST data for long-term ENSO retrospective forecasts

In this study, the assimilation of historic SST (sea surface temperature) data was performed for long-term ENSO hindcasts. The emphasis was placed on the design of background error covariance (BEC) that dominates the transfer of SST information to the subsurface. Four different data-assimilation schemes, based on Optimal Interpolation (OI) algorithm, were proposed, and compared in terms of ENSO simulation and prediction skills for the period from 1876 to 2000.It was found that the data-assimilation scheme that has a three-dimensional BEC constructed from model simulations forced by observed wind stress can effectively correct the second-layer temperature in the SST assimilation and lead to the best ENSO prediction skill. Further analysis for the long-term hindcasts shows that the prediction skills have a striking decadal/interdecadal variability similar to that found in other models. These results provide a fundamental basis for the further study of ENSO predictability.     

观测分析非洲南部地区土壤湿度异常对南半球大气环流的显著影响

本文基于44年ERA40再分析月平均土壤湿度资料和大气环流变量场资料,去除ENSO遥相关以及趋势影响后,利用滞后最大协方差方法分析非洲南部地区土壤湿度分布与南半球大气环流异常之间的线性耦合。第一最大协方差模态的结果表明:在南半球冬季（Jun-Jul-Aug,6～8月）和夏季（Jan-Feb-Mar,1～3月）,大气中类似南极涛动（Antarctic Oscillation,简称AAO）正位相的环流型与超前月份（最长时间达到5个月）的非洲南部地区土壤湿度的异常分布显著相关。基于土壤湿度变率中心的线性回归分析方法证实非洲南部地区其北部土壤湿度正异常、中南部土壤湿度负异常的空间分布对后期夏季和冬季的大气有显著的反馈作用。诊断结果显示由于夏秋季节和春季初夏非洲南部地区土壤湿度异常均有显著的持续性,同时对后期AAO产生持续增强作用,所以滞后最大协方差方法可以检测出它们对后期AAO的显著影响。以上非洲南部地区土壤湿度异常超前于南极涛动的信号,将有助于加强对土壤湿度反馈机制及其对南半球大尺度环流变率影响的认识。     

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先验协方差阵误差对动态Kalman滤波解的影响

分别讨论当标准Kalman滤波动力学模型的状态参数协方差阵、状态噪声的协方差阵及观测噪声的协方差阵含有误差时,对滤波结果的影响并导出相应的解式。利用GPS/INS紧组合导航系统的实测数据对上述分析进行了实验,结果表明,动力学模型信息的协方差阵和观测信息的协方差阵在滤波中具有一个理想的平衡点,该平衡点能够合理分配动力学模型信息和观测信息对滤波解的贡献,从而可以得到可靠的滤波解。     

Carbon and water exchange in semiarid ecosystems in SE Spain

The changing climate is affecting biological and physical processes occurring in the biosphere, including the biogeochemical cycles of water and carbon. The response of ecosystem carbon exchange to changes in temperature and the water balance is still very uncertain, a fact that highlights the need for research in order to understand the role of the biosphere in the future global carbon budget. South east Spain is on the borderline between the tropical and mid-latitude climate zones, with climates ranging from sub-humid to arid, and the majority representing the driest area in Europe. Initial predictions on climate change for this region point to decreases in total precipitation and the number of precipitation events, meaning a decrease in water availability underlining the vulnerability of the region to desertification. This region, due to these special climatic conditions, has been the subject of experimental carbon and water field research in recent years. This paper defines the state of the art of carbon and water balance measurement and modelling studies in this region, analyses the different processes involved in aggregate exchanges (vegetation and soil; net ecosystem carbon balance–evapotranspiration, photosynthesis–transpiration, soil respiration–evaporation), and identifies needs for future research.     

Simulating evapotranspiration of Qinghai spruce (Picea crassifolia) forest in the Qilian Mountains, northwestern China

Qinghai spruce (Picea crassifolia) forests play an important role in regulating the regional water balance of the Qilian Mountains in northwestern China. The objective of this study was to estimate evapotranspiration (ET) of the Qinghai spruce forest in the middle section of the Qilian Mountains. A modified Penman-Monteith equation was used to simulate two sub-components of ET: canopy transpiration (E_t) and soil evaporation (E_s). The third sub-component of ET, canopy interception evaporation (E_i), was directly measured. The results show that the total ET of the Qinghai spruce forest was 313.6 mm during the 2008 growing season (from May 1 to September 30). E_i, E_t, and E_s were 100.9 mm, 160.8 mm and 51.9 mm, and accounted for 32.2%, 51.3% and 16.5% of the total ET, respectively. The total modeled ET during the 2008 growing season is acceptably consistent with the directly measured ET (298.2 mm) by eddy covariance system. The consistency implies that the modified Penman-Monteith equation is an effective method to estimate ET using conventional meteorological data with additional measurements of net radiation, and the method can thus be applied to similar situations where reliable direct measurements are not practical.     

A GPP assimilation model for the southeastern Tibetan Plateau based on CO2 eddy covariance flux tower and remote sensing data

The gross primary production (GPP) at individual CO₂ eddy covariance flux tower sites (GPP_Tower) in Dali (DL), Wenjiang (WJ) and Linzhi (LZ) around the southeastern Tibetan Plateau were determined by the net ecosystem exchange of CO₂ (NEE) and ecosystem respiration (R_e). The satellite remote sensing-VPM model estimates of GPP values (GPP_MODIS) used the satellite-derived 8-day surface reflectance product (MOD09A1), including satellite-derived enhanced vegetation index (EVI) and land surface water index (LSWI). In this paper, we assembled a subset of flux tower data at these three sites to calibrate and test satellite-VPM model estimated GPP_MODIS, and introduced the satellite data and site-level environmental factors to develop four new assimilation models. The new assimilation models’ estimates of GPP values were compared with GPP_MODIS and GPP_Tower, and the final optimum model among the four assimilation models was determined and used to calibrate GPP_MODIS. The results showed that GPP_MODIS had similar temporal variations to the GPP_Tower, but GPP_MODlS were commonly higher in absolute magnitude than GPP_Tower with relative error (RE) about 58.85%. While, the assimilation models’ estimates of GPP values (GPP_MODEL) were much more closer to GPP_Tower with RE approximately 6.98%, indicating that the capacity of the simulation in the new assimilation model was greatly improved, the R² and root mean square error (RMSE) of the new assimilation model were 0.57–4.90% higher and 0.74–2.47 g C m⁻² s⁻¹ lower than those of the GPP_MODIS, respectively. The assimilation model was used to predicted GPP dynamics around the Tibetan Plateau and showed a reliable result compared with other researches. This study demonstrated the potential of the new assimilation model for estimating GPP around the Tibetan Plateau and the performances of site-level biophysical parameters in related to satellite-VPM model GPP.