A quality control method for high-resolution radiosonde temperature and wind data 高频探空温度和风速的质量控制方法研究

This study proposes a method to derive the climatological limit thresholds that can be used in an operational/historical quality control procedure for Chinese high vertical resolution (5–10 m) radiosonde temperature and wind speed data. The whole atmosphere is divided into 64 vertical bins, and the profiles are constructed by the percentiles of the values in each vertical bin. Based on the percentile profiles (PPs), some objective criteria are developed to obtain the thresholds. Tibetan Plateau field data are used to validate the effectiveness of the method in the application of experimental data. The results show that the derived thresholds for 120 operational stations and 3 experimental stations are effective in detecting the gross errors, and those PPs can clearly and instantly illustrate the characteristics of a radiosonde variable and reveal the distribution of errors.摘要针对中国高分辨率探空资料, 本文提出了一种计算气候学界限值的方法以满足业务中对资料进行质量控制的需求.首先在垂直方向上将整个大气划分为64层, 将落在每层范围内的观测数据都收集到一起进行排序并计算百分位, 在此基础上通过比较不同百分位廓线值来获得气候学界限值.除了业务台站, 本文还使用了TIPEX-III的探空数据来验证本方法在科学试验数据中的应用效果.评估表明, 应用气候学界限值可以有效检测到业务站和试验站观测数据中的粗大误差;百分位廓线则可以清晰的体现出探空观测的整体变化特征并揭示出误差的整体分布范围.     

U-Net: A deep-learning method for improving summer precipitation forecasts in China

A deep-learning method named U-Net was applied to improve the skill in forecasting summer (June–August) precipitation for at a one-month lead during the period 1981–2020 in China. The variables of geopotential height, soil moisture, sea level pressure, sea surface temperature, ocean salinity, and snow were considered as the model input to revise the seasonal prediction of the Climate Forecast System, version 2 (CFSv2). Results showed that on average U-Net reduced the root-mean-square error of the original CFSv2 prediction by 49.7% and 42.7% for the validation and testing set, respectively. The most improved areas were Northwest, Southwest, and Southeast China. The anomaly same sign percentages and temporal and spatial correlation coefficients did not present significant improvement but maintained the comparable performances of CFSv2. Sensitivity experiments showed that soil moisture is the most crucial factor in predicting summer rainfall in China, followed by geopotential height. Due to its advantages in handling small training dataset sizes, U-Net is a promising deep-learning method for seasonal rainfall prediction.摘要本研究应用了名为U-Net的深度学习方法来提高中国夏季 (6–8月) 降水的预报技能, 预报时段为1981–2020年, 预报提前期为一个月. 将位势高度场, 土壤湿度, 海平面气压, 海表面温度, 海洋盐度和青藏高原积雪等变量作为模型输入, 本文对美国NCAR气候预报系统第2版 (CFSv2) 的季节性预报结果进行了修正. 结果显示, 在验证集和测试集上, U-Net平均将原CFSv2预测的均方根误差分别减少了49.7%和42.7%. 预报结果改善最大的地区是中国的西北,西南和东南地区. 然而, 同号率和时空相关系数没有得到明显改善, 但仍与CFSv2的预测技巧持平. 敏感性实验表明, 土壤湿度是预测中国夏季降雨的最关键因素, 其次是位势高度场. 本研究显示了U-Net模型在训练小样本数据集方面的优势, 为我国汛期季节性降雨预测提供了一种有效的深度学习方法.     

Prediction of ENSO using multivariable deep learning

A novel multivariable prediction system based on a deep learning (DL) algorithm, i.e., the residual neural network and pure observations, was developed to improve the prediction of the El Niño–Southern Oscillation (ENSO). Optimal predictors are automatically determined using the maximal information for spatial filtering and the Taylor diagram criteria, enabling the best prediction skills at lead times of eight months compared with most operational prediction models. The hindcast skill for the most challenging decade (2011–18) outperforms the multi-model ensemble operational forecasts. At the six-month lead, the correlation (COEF) skill of the DL model reaches 0.82 with a normalized root-mean-square error (RMSE) of 0.58 °C, which is significantly better than the average multi-model performance (COEF = 0.70 and RMSE = 0.73°C). DL prediction can effectively alleviate the long-standing spring predictability barrier problem. The automatically selected optimal precursors can explain well the typical ENSO evolution driven by both tropical dynamics and extratropical impacts.摘要本文基于残差神经网络和观测数据构建了一套深度学习多因子预报测模型, 以改进厄尔尼诺-南方涛动(ENSO)的预报. 该模型基于最大信息系数进行因子时空特征提取, 并根据泰勒图的评估标准可自动确定关键预报因子进行预报. 该模型在超前8个月以内的预报性能要优于当前传统的业务预报模式. 2011–2018年间, 该模型的预报性能优于多模式集成预报的结果. 在超前6个月预报时效上, 模型预报相关性可达0.82, 标准化后的均方根误差仅为0.58°C, 多模式集成预报的相关性和标准化后的均方根误差分别为0.70和0.73°C. 该模型春季预报障碍问题有所缓解, 并且自动选取的关键预报因子可用于解释热带和副热带热动力过程对于ENSO变化的影响.     

Characteristics of diurnal variations of warm-season precipitation over Xinjiang Province in China

降水日变化受大气热力,动力过程以及复杂地形影响,演变特征复杂且区域差异显著.本文采用中国气象局发布的中国地面与CMORPH融合逐小时降水产品(2008-2019年),分析了新疆省暖季降水日变化特征.研究结果表明:(1)新疆大部分地区降水主峰值发生在清晨;(2)持续时间超过三小时的降水事件是新疆地区主要降水事件,贡献了南...     

Short-term wind speed forecasting bias correction in the Hangzhou area of China based on a machine learning model

Accurate wind speed forecasting is of great societal importance. In this study, the short-term wind speed forecasting bias at automatic meteorological stations in Hangzhou, Zhejiang Province, China, was corrected using an XGBoost machine learning model called WSFBC-XGB. The products of the local NWP (numerical weather prediction) system were used as the inputs of WSFBC-XGB. The WSFBC-XGB-corrected results were compared with those corrected using the traditional MOS (model output statistics) method. Results showed that WSFBC-XGB performed better than MOS, with the root-mean-square errors (RMSEs)/accuracy rates of the wind speed forecasting (ACCs) of WSFBC-XGB being reduced/ promoted by 26.1% and 7.64%/35.6% and 7.02% relative to NWP and MOS, respectively. The RMSEs/ACCs of WSFBC-XGB were smaller/higher than those of MOS at 90% stations. In addition, the mean decrease in impurity method was used to analyze the interpretability of WSFBC-XGB to help users gain trust in the model. Results showed that the four most important features were the wind speed at 10 m (47.35%), meridional component of wind at 10 m (12.73%), diurnal cycle (9.97%), and meridional component of wind at 1000 hPa (7.45%). The WSFBC-XGB model will help improve the accuracy of short-term wind speed forecasting and provide support for large-scale outdoor activities.摘要准确的风速预报具有重要的社会意义. 在本研究中, 使用名为WSFBC-XGB的XGBoost机器学习模型对中国浙江省杭州市自动气象站的短期风速预报误差进行校正. WSFBC-XGB使用本地数值天气预报系统的产品作为输入. 将WSFBC-XGB校正的结果与传统MOS(模型输出统计)方法校正的结果进行了比较. 结果表明: WSFBC-XGB预报风速的均方根误差(RMSE)/准确率(ACC)分别比NWP和MOS降低/提高了26.1%和7.64%/35.6%和7.02%; 对于90%的站点WSFBC-XGB的RMSE/ACC均小于/高于MOS. 此外, 采用平均杂质减少法对WSFBC-XGB的可解释性进行分析, 以帮助用户增加对模型的信任. 结果表明: 10米风速(47.35%), 10米风的经向分量(12.73%), 日循环(9.97%)和1000百帕风的经向分量(7.45%)是前4个最重要的特征. WSFBC-XGB模型将有助于提高短期风速预报的准确性, 为大型户外活动提供支持.     

CWRF-based ensemble simulation of tropical cyclone activity near China and its sensitivity to the model physical parameterization schemes: 基于CWRF的中国近海热带气旋集合模拟及其对物理参数化方案的敏感性研究

To evaluate the downscaling ability with respect to tropical cyclones (TCs) near China and its sensitivity to the model physics representation, the authors performed a multi-physics ensemble simulation with the regional Climate–Weather Research and Forecasting (CWRF) model at a 30 km resolution driven by ERA-Interim reanalysis data. The ensemble consisted of 28 integrations during 1979–2016 with varying CWRF physics configurations. Both CWRF and ERA-Interim can generally capture the seasonal cycle and interannual variation of the TC number near China, but evidently underestimate them. The CWRF downscaling and its multi-physics ensemble can notably reduce the underestimation and significantly improve the simulation of the TC occurrences. The skill enhancement is especially large in terms of the interannual variation, which is most sensitive to the cumulus scheme, followed by the boundary layer, surface and radiation schemes, but weakly sensitive to the cloud and microphysics schemes. Generally, the Noah surface scheme, CAML(CAM radiation scheme as implemented by Liang together with the diagnostic cloud cover scheme of Xu and Randall(1996)) radiation scheme, prognostic cloud scheme, and Thompson microphysics scheme stand out for their better performance in simulating the interannual variation of TC number. However, the Emanuel cumulus and MYNN boundary layer schemes produce severe interannual biases. Our study provides a valuable reference for CWRF application to improve the understanding and prediction of TC activity.摘要为评估CWRF模式的降尺度能力和其热带气旋模拟对物理参数化方案的敏感性, 本文利用ERI再分析资料驱动CWRF在30km网格上对1982-2016年中国近海热带气旋开展了一次集合模拟.结果表明:CWRF与ERI均能模拟出热带气旋的季节变化和年际变化形势且均存在低估, 但相较ERI, CWRF的降尺度技术和集合模拟可以再现更多的热带气旋, 显著减少低估.年际变化结果提升最为明显, 它对积云方案最为敏感, 其次是边界层, 陆面和辐射方案, 对云和微物理方案较弱.该研究为应用CWRF理解和预报热带气旋提供了参考.     

China Ocean ReAnalysis (CORA) version 1.0 products and validation for 2009–18: 2009–18年西北太平洋区域海洋再分析CORA1.0产品研制及检验

China Ocean ReAnalysis (CORA) version 1.0 products for the period 2009–18 have been developed and validated. The model configuration and assimilation algorithm have both been updated compared to those of the 51-year (1958–2008) products. The assimilated observations include temperature and salinity field data, satellite remote sensing sea surface temperature, and merged sea surface height (SSH) anomaly data. The validation includes the following three aspects: (1) Temperature, salinity, and SSH anomaly root-mean-square errors (RMSEs) are computed as a primary evaluation of the reanalysis quality. The 0–2000 m domain-averaged RMSEs of temperature and salinity are 0.61°C and 0.08 psu, respectively. The SSH anomaly RMSE is less than 0.2 m in most regions. (2) The 35°N temperature section is used to evaluate the ability to reproduce the thermocline, mixing layer, and Yellow Sea cold water mass. In summer, the thermocline is reinforced, with the gradient changing from 3°C in May to 10°C in August. The mixing-layer depth reproduced by CORA is consistent with that computed from the observed climatology. The Yellow Sea cold water mass forms at a depth of 50 m. (3) The reanalysis current is examined against the tracks of some drifting buoys. The results show that the reanalysis current can capture the mesoscale eddies near the Kuroshio, which are similar to those described by the drifting buoys. Overall, the 2009–18 CORA reanalysis products are capable of reproducing major oceanic phenomena and processes in the coastal waters of China and adjacent seas.摘要在51年 (1958–2008) 西北太平洋区域海洋再分析CORA1.0产品的基础上, 改进了模式配置和同化方法, 研制了2009-18年的CORA产品并对其进行以下检验: (1) 温盐和海表高度异常均方根误差分布检验; (2) 35°N处温度断面分布检验; (3) 再分析流场和表漂浮标轨迹对比检验.结果显示, 2009–18年的CORA产品可以再现海洋要素长时间序列,时空多尺度的变化特征, 为研究特征海洋现象和过程提供背景信息.     

Soil–vegetation–atmosphere interaction over a hilly forest in the southern Huaihe River Basin: Long-term field experiment and preliminary analysis of basic observations 淮河流域南部丘陵森林地区土壤-植被-大气相互作用:长期野外试验观测的初步分析

To improve the understanding of the CO₂ exchange and the cycling of energy and water between the land surface and atmosphere over a typical hilly forest in southeastern China, a long-term field experimental observatory was established in Huainan, Anhui Province. Here, the authors briefly describe the three parts of ongoing research activities: the environmental monitoring at the site, the meteorological observations on a high tower, and particularly the intensive measurement of soil–vegetation–atmosphere interaction on a lower tower. Specifically, the diurnal variation of basic meteorological variables on a typical clear day (13 July 2018), and their temporal variation in the first three months of the low tower's operation (4 June to 31 August 2018), and in combination with simultaneous data from the high tower, are analyzed. Results show that the data demonstrate reasonable variabilities, and the variables exhibit significant diurnal variation, characteristics of summer values, and considerable differences in summer months. The daily and monthly average albedos above the forest canopy were both 0.13. The daily average soil CO₂ concentration was 1726 and 4481 ppm at 2 and 10 cm, respectively. The soil CO₂ concentration changed with soil volumetric moisture contents, but showed a weak correlation with soil temperature in summer 2018. As the observatory continues to run and data continue to be collated, further investigation of the long-term variation of monsoon characteristics should be performed in the future. The experiment is useful in ecosystem and atmosphere interaction research, as well as for the development and evaluation of climate models, in the transitional climate zone of the Huaihe River basin.摘要本文简要介绍了包括三部分观测的安徽淮南长期野外试验观测站, 特别是土壤-植被-大气的集中观测, 对小塔运行前三个月 (2018年6月至8月) 的数据, 并结合同一时段大塔获得的数据, 进行了初步分析.结果表明这些资料有合理的变化特征, 日变化和夏季值特征显著, 各月份间气象变化有明显差异.土壤水分和温度受降雨影响, 在不同的下垫面条件下表现出不同的变化.土壤CO₂日平均浓度在2 cm和10 cm处分别为1726和4481 ppm.2018年夏季土壤CO₂浓度随土壤体积含水量的变化而变化, 但与土壤温度呈弱相关.     

Strengthening the three-dimensional comprehensive observation system of multi-layer interaction on the Tibetan Plateau to cope with the warming and wetting trend

Changes in the water cycle on the Tibetan Plateau (TP) have a significant impact on local agricultural production and livelihoods and its downstream regions. Against the background of widely reported warming and wetting, the hydrological cycle has accelerated and the likelihood of extreme weather events and natural disasters occurring (i.e., snowstorms, floods, landslides, mudslides, and ice avalanches) has also intensified, especially in the high-elevation mountainous regions. Thus, an accurate estimation of the intensity and variation of each component of the water cycle is an urgent scientific question for the assessment of plateau environmental changes. Following the transformation and movement of water between the atmosphere, biosphere and hydrosphere, the authors highlight the urgent need to strengthen the three-dimensional comprehensive observation system (including the eddy covariance system; planetary boundary layer tower; profile measurements of temperature, humidity, and wind by microwave radiometers, wind profiler, and radiosonde system; and cloud and precipitation radars) in the TP region and propose a practical implementation plan. The construction of such a three-dimensional observation system is expected to promote the study of environmental changes and natural hazards prevention.摘要青藏高原的水循环变化对于高原及其下游区域人类的生产生活具有举足轻重的影响. 在高原暖湿化的背景下, 其水文循环加快, 极端天气和自然灾害事件概率增大, 比如, 雪灾, 洪水, 滑坡, 泥石流, 冰崩在山区频发. 因此, 如何准确的估算青藏高原水循环各分量的大小及变化幅度是评估高原环境变化影响亟需解决的科学问题. 根据水在各圈层间转换过程, 我们提出了建立第三极地区 (尤其是复杂山区) 的三维立体多圈层地气相互作用综合观测系统(包括涡动相关系统, 行星边界层塔, 微波辐射计, 风廓线仪和无线电探空系统观测的风温湿廓线及云雨雷达等)的紧迫性和具体方案, 进而为研究青藏高原环境变化和山区灾害预测服务.     

The ocean response to climate change guides both adaptation and mitigation efforts

The ocean's thermal inertia is a major contributor to irreversible ocean changes exceeding time scales that matter to human society. This fact is a challenge to societies as they prepare for the consequences of climate change, especially with respect to the ocean. Here the authors review the requirements for human actions from the ocean's perspective. In the near term (～2030), goals such as the United Nations Sustainable Development Goals (SDGs) will be critical. Over longer times (～2050–2060 and beyond), global carbon neutrality targets may be met as countries continue to work toward reducing emissions. Both adaptation and mitigation plans need to be fully implemented in the interim, and the Global Ocean Observation System should be sustained so that changes can be continuously monitored. In the longer-term (after ～2060), slow emerging changes such as deep ocean warming and sea level rise are committed to continue even in the scenario where net zero emissions are reached. Thus, climate actions have to extend to time scales of hundreds of years. At these time scales, preparation for “high impact, low probability” risks — such as an abrupt showdown of Atlantic Meridional Overturning Circulation, ecosystem change, or irreversible ice sheet loss — should be fully integrated into long-term planning.摘要在全球变化背景下, 海洋的很多变化在人类社会发展的时间尺度上 (百年至千年) 具有不可逆转性, 海洋巨大的热惯性是造成该不可逆性的主要原因. 这个特征为人类和生态系统应对海洋变化提出一系列挑战. 本文从海洋变化的角度总结了人类应对气候变化的要求, 提出需要进行多时间尺度的规划和统筹. 在近期 (到2030年) , 实现联合国可持续发展目标至关重要. 在中期 (2050–2060年前后) , 全球需要逐步减排并实现碳中和目标. 同时, 适应和减缓气候变化的行动和措施必须同步施行; 全球海洋观测系统需要得以维持并完善以持续监测海洋变化. 在远期 (在2060年之后) , 即使全球达到净零排放, 包括深海变暖和海平面上升在内的海洋变化都将持续, 因此应对全球变化的行动需持续数百年之久. 在该时间尺度, 应对“低概率, 高影响”气候风险 (即发生的可能性较低, 但一旦发生影响极大的事件带来的风险, 例如: 大西洋经圈反转环流突然减弱, 海洋生态系统跨过临界点, 无可挽回的冰盖质量损失等) 的准备应充分纳入长期规划.     

Impact of global sea surface temperature on the recent early winter Arctic tropospheric warming in coordinated large ensemble simulations 协调大集合模拟下全球海表面温度对北极对流层早冬增暖的影响

Coordinated numerical ensemble experiments with six different state-of-the-art atmosphere models were used to evaluate and quantify the impact of global SST (from reanalysis data) on the early winter Arctic warming during 1982–2014. Two sets of experiments were designed: in the first set (EXP1), OISSTv2 daily sea-ice concentration and SST variations were used as the lower boundary forcing, while in the second set (EXP2) the SST data were replaced by the daily SST climatology. In the results, the multi-model ensemble mean of EXP1 showed a near-surface (~850 hPa) warming trend of 0.4 °C/10 yr, which was 80% of the warming trend in the reanalysis. The simulated warming trend was robust across the six models, with a magnitude of 0.36–0.50 °C/10 yr. The global SST could explain most of the simulated warming trend in EXP1 in the mid and low troposphere over the Arctic, and accounted for 58% of the simulated near-surface warming. The results also suggest that the upper-tropospheric warming (~200 hPa) over the Arctic in the reanalysis is likely not a forced signal; rather, it is caused by natural climate variability. The source regions that can potentially impact the early winter Arctic warming are explored and the limitations of the study are discussed.摘要本文使用六个不同的最新大气模式进行了协调数值集合实验, 评估和量化了全球海表面温度 (SST) 对1982–2014年冬季早期北极变暖的影响.本研究设计了两组实验:在第一组 (EXP1) 中, 将OISSTv2逐日变化的海冰密集度和SST数据作为下边界强迫场;在第二组 (EXP2) 中, 将逐日变化的SST数据替换为逐日气候态.结果表明: (1) EXP1的多模式集合总体平均值显示0.4 °C/10年的近地表 (约850 hPa) 升温趋势, 为再分析数据结果中升温趋势的80%. (2) 在这六个模式中, 模拟的变暖趋势均很强, 幅度为0.36–0.50 °C/10年. (3) 全球海表温度可以解释北极对流层中低层EXP1的大部分模拟的变暖趋势, 占再分析数据结果的58%. (4) 再分析数据结果中, 北极上空的对流层上层变暖 (约200 hPa) 不是由强迫信号而可能是由自然气候变率引起的.本文还探索了影响北极初冬变暖的可能源区, 并讨论了该研究的局限性.     

Evaluation of global high-resolution reanalysis products based on the Chinese global oceanography forecasting system: 基于中国全球海洋预报系统(CGOFS)的全球高分辨率再分析产品评估

The global high-resolution marine reanalysis products that were independently developed by the National Marine Environmental Forecasting Center based on the Chinese Global Oceanography Forecasting System (CGOFS), are evaluated by comparing their climatologies with internationally recognized data from WOA (Word Ocean Atlas), SODA (Simple Ocean Data Assimilation), AVISO (Archiving, Validation, and Interpretation of Satellite Oceanographic Data), and C-GLORS (Global Ocean Reanalysis System). The results show that the SST RMSEs of CGOFS and SODA against WOA are 0.51 °C and 0.43 °C respectively; and in the North Pacific, the SST of CGOGS is closer to that of WOA than SODA. The SSS RMSEs of CGOFS and SODA compared with WOA are 0.48 PSU and 0.40 PSU, respectively. CGOFS can reproduce the main large-scale ocean circulation globally, and obtain a similar vertical structure of the Equatorial Undercurrent as SODA. The RMSE of the CGOFS global sea-level anomaly against AVISO is 0.018 m. The monthly averaged sea-ice extents are between those of SODA and C-GLORS in each month; the growth and ablation characteristics of the ice volume are consistent with SODA and C-GLORS; but the ice volume of CGOFS is greater than that of SODA and C-GLORS. In general, the climatology of the CGOFS global high-resolution reanalysis products are basically consistent with similar international products, and can thus provide reliable data for the improvement of marine science and technology in China.摘要通过同化系统将观测资料与海洋数值模式融合得到的海洋再分析产品为海洋科学研究提供了重要的资料基础.本文采用WOA,SODA,AVISO和GLORS四种数据资料与我国自主研发的中国全球海洋预报系统(CGOFS)的气候态结果进行了对比, 结果表明:CGOFS和SODA的全球海表面温度与WOA的均方根误差分别为0.51 和 0.43°C.CGOFS和SODA的海表面盐度与WOA的均方根误差分别为0.48和0.40 PSU;海流方面, CGOFS能较好的刻画主要大洋环流分布及赤道潜流的垂向结构;CGOFS的全球海表面高度异常与AVISO的均方根误差为0.018m;多年月平均海冰外缘线覆盖面积介于SODA 和 GLORS之间, 海冰体积的生消规律与SODA 和 GLORS一致.总体来看, CGOFS全球高分辨率海洋再分析产品的气候态结果与国际同类产品基本一致, 可为提升我国海洋综合科技实力提供可靠的资料保障.     

Decadal–centennial hydroclimate variability over eastern China during the last millennium: Results from the product of Paleo Hydrodynamics Data Assimilation: 过去千年中国东部年代际-百年尺度干湿变化特征:基于古水文动力同化数据

Decadal–centennial hydroclimate variability over eastern China during the last millennium is investigated using the product of Paleo Hydrodynamics Data Assimilation (PHYDA). Results reveal that the PHYDA depicts a more homogeneous temporal pattern during the early part of the Little Ice Age with other reconstructions than those during the other periods, and could also identify the droughts of 1352–90 AD, 1445–98 AD, 1580–94 AD, and 1626–65 AD during this period. On centennial time scales, the PHYDA shows that the linkage between the Palmer drought severity index over eastern China and the Atlantic Multidecadal Oscillation (AMO) index is more marked than that with the El Niño–Southern Oscillation and the location of the intertropical convergence zone over the Asian–Australian monsoon area during the period after the 1350s. For the decadal droughts, the PHYDA suggests most of the drought events during the last millennium were linked to the El Niño–like mean states and the negative AMO states.摘要利用古水文动力同化数据 (PHYDA) 研究了过去千年中国东部年代际-百年尺度干湿变化特征.结果表明, 对比其它重建数据PHYDA在百年尺度上对小冰期前期中国东部干湿变化的再现能力最好, 其对这一时期发生的年代际干旱事件包括1352–90年,1445–98年,1580–94年和1626–65年干旱事件的再现能力也最强.通过与强迫因子的对比和回归分析, 发现1350年后中国东部百年尺度干事变化主要受北大西洋年代际振荡影响, 而年代际干旱事件的主导因子则是厄尔尼诺和负位相的北大西洋年代际振荡.     

Changes in the seasonal amplitude of northern ecosystem productivity under future global warming

Observations have shown a largely enhanced seasonal amplitude of northern atmospheric CO₂ in the past several decades, and this enhancement is attributable to the increased seasonal amplitude of northern net ecosystem productivity (NEP amplitude). In the future, however, the changes in NEP amplitude are not clear, because of the uncertainties in climate change and vegetation dynamics. This study investigated the changes in NEP amplitude north of 45°N under future global warming by using a dynamic global vegetation model (DGVM). The authors conducted two sets of simulations: a present-day simulation (1981–2000) and future simulations (2081–2100) forced by RCP8.5 outputs from CMIP5. The results showed an overall enhanced northern NEP amplitude under the RCP8.5 scenario because of the increased maximum NEP and the decreased minimum NEP. The increases (decreases) in the maximum (minimum) NEP resulted from stronger (weaker) positive changes in gross primary production (GPP) than ecosystem respiration (ER). Changes in GPP and ER are both dominantly driven by surface air temperature and vegetation dynamics. This work highlights the key role of vegetation dynamics in regulating the northern terrestrial carbon cycle and the importance of including a DGVM in Earth system models.摘要观测显示过去几十年北半球大气二氧化碳季节幅度大幅增加, 这主要是由北半球陆地净生态系统生产力季节幅度的增加所致. 但是, 因为气候变化和植被动态的不确定性, 未来陆地净生态系统生产力季节幅度的变化还很不清楚. 本工作利用全球植被动力学模式研究了全球变暖背景下北纬45°以北陆地净生态系统生产力季节幅度的变化. 作者做了两大类试验: 当代试验 (1981−2000) 和CMIP5 RCP8.5 变暖情景驱动的未来试验 (2081−2100) . 结果显示, 在RCP8.5变暖情景下北半球中高纬陆地净生态系统生产力季节幅度整体增加, 这是因为陆地净生态系统生产力的月最大值增加且月最小值减小. 最大 (最小) 陆地净生态系统生产力的增加 (减小) 是由于总初级生产力的增加强 (弱) 于生态系统总呼吸. 总初级生产力和生态系统总呼吸的变化都主要受地表气温和植被动态的驱动. 本工作强调了植被动态对北半球中高纬陆地生态系统碳循环的关键调制作用, 也强调了在地球系统模式中包含全球植被动力学模式的重要性.     

Discrepancies in surface temperature between NCEP reanalysis data and station observations over China and their implications: 中国地区NCEP再分析资料与台站观测的地表温度差异及其影响

Previous studies show that temporal irreversibility (TI), as an important indicator of the nonlinearity of time series, is almost uniformly overestimated in the daily air temperature anomaly series over China in NCEP reanalysis data, as compared with station observations. Apart from this highly overestimated TI in the NCEP reanalysis, some other important atmospheric metrics, such as predictability and extreme events, might also be overestimated since there are close relations between nonlinearity and predictability/extreme events. In this study, these issues are fully addressed, i.e., intrinsic predictability, prediction skill, and the number of extreme events. The results show that intrinsic predictability, prediction skill, and the occurrence number of extreme events are also almost uniformly overestimated in the NCEP reanalysis daily minimum and maximum air temperature anomaly series over China. Furthermore, these overestimations of intrinsic predictability, prediction skill, and the number of extreme events are only weakly correlated with the overestimated TI, which indicates that the quality of the NCEP reanalysis should be carefully considered when conclusions on both predictability and extreme events are derived.摘要作为时间序列非线性的一个重要指标, 从NCEP再分析得到日气温异常的时间不可逆性 (TI) 与观测站的相比几乎一致地被高估了.因为非线性与可预报性/极端事件之间有着密切的关系, 除了高估的TI外, 这些大气测度也可能被高估.本文结果表明:NCEP再分析的日最低和最高气温异常序列的内在可预报性,预报技巧和极端事件发生次数也几乎一致被高估.而且, 这些高估的测度与高估的TI只存在微弱的相关性, 这表明利用NCEP再分析研究可预测性和极端事件时, 需要仔细考虑其质量对结论的可能影响.     

Computational uncertainty and optimal grid size and time step of the Lax–Friedrichs scheme for the 1D advection equation

This paper examines truncation and round-off errors in the numerical solution of the 1D advection equation with the Lax–Friedrichs scheme, and accumulation of the errors as they are propagated to high temporal layers. The authors obtain a new theoretical approximation formula for the upper bound of the total error of the numerical solution, as well as theoretical formulae for the optimal grid size and time step. The reliability of the obtained formulae is demonstrated with numerical experimental examples. Next, the ratio of the optimal time steps under two different machine precisions is found to satisfy a universal relation that depends only on the machine precision involved. Finally, theoretical verification suggests that this problem satisfies the computational uncertainty principle when the grid ratio is fixed, demonstrating the inevitable existence of an optimal time step size under a finite machine precision.摘要本文对于应用Lax- Friedrichs 格式数值求解一维平流方程, 研究数值求解过程中产生的截断误差与舍入误差, 以及两种误差逐层向高时间层传播的累积, 得到新的数值解总误差上界的理论近似公式, 以及最优格距和最优时间步长的理论公式. 通过数值算例验证了所得公式的可靠性. 然后, 发现了两种不同机器精度下最优时间步长之比满足的一个仅与机器精度有关的普适关系. 最后, 理论验证了在网格比固定的情况下, 此问题满足数值计算的不确定性原理, 以及在机器有限精度下最优时间步长的必然存在.     

Inversion method for multi-point source pollution identification: Sensitivity analysis and application to European Tracer Experiment data

Fast and accurate identification of unknown pollution sources plays a crucial role in the emergency response and source control of air pollution. In this work, the applicability of a previously proposed two-step inversion method is investigated with sensitivity experiments and real data from the first release of the European Tracer Experiment (ETEX-1). The two-step inversion method is based on the principle of least squares and carries out additional model correction through the residual iterative process. To evaluate its performance, its retrieval results are compared with those of two other existing algorithms. It is shown that for those cases with richer measurements, all three methods are less sensitive to errors, while for cases where measurements are sparse, their retrieval accuracy will rapidly decrease as errors increase. From the results of sensitivity experiments, the new method provides higher estimation accuracy and a more stable performance than the other two methods. The new method presents the smallest maximum location error of 18.20 km when the amplitude of the measurement error increases to 100%, and 22.67 km when errors in the wind fields increase to 200%. Moreover, when applied to ETEX-1 data, the new method also exhibits good performance, with a location error of 4.71 km, which is the best estimation with respect to source location.摘要快速并且准确地识别未知污染源, 在大气污染应急响应和源头控制过程中起着至关重要的作用. 本文利用敏感性试验及欧洲示踪物测场试验(ETEX-1)数据研究了新提出的两步反演算法的实用性, 并将其反演结果与现有的两种算法进行了对比分析. 敏感试验表明, 在观测数据较为丰富的情况下, 三种算法对观测误差和风场误差的敏感性均较低; 而当观测数据较为稀疏时, 所有算法的估计精度都将随着误差的增加而下降, 但与其他两种算法相比, 两步反演算法具有更高的估计精度以及更稳定的估计性能. 此外, 欧洲示踪物测场试验的源项估计结果也表明, 在三个算法中, 两步反演算法具有最小的位置估计误差.     

Possible contribution of Arctic sea ice decline to intense warming over Siberia in June

西伯利亚地区异常的升温可能会给生态系统带来灾难性的影响.本文从气候角度分析西伯利亚地区初夏升温的特征以及北极海冰减小的可能贡献.观测和再分析资料表明,1979-2020年间西伯利亚地区6月地表气温有很强的升温趋势(0.9℃/10年),明显高于同纬度地区平均的升温趋势(0.46℃/10年).升温从地表延伸至300hPa左...     

Evaluating the performance of a WRF microphysics ensemble through comparisons with aircraft observations: 与飞机观测资料对比评估WRF微物理方案集合的模拟能力

Aircraft observation data obtained in a mesoscale convective system are compared to Weather Research and Forecasting (WRF) model simulations using four microphysics schemes (Morrison, WSM6, P3, SBM) with different complexities. The main purpose of this paper is to assess the performance of the microphysics ensemble in terms of cloud microphysical properties. Results show that although the vertical distributions of liquid water content (LWC) and ice water content (IWC) simulated by the four members are quite different in the convective cloud region, they are relatively uniform in the stratiform cloud region. Overall, the results of the Morrison scheme are very similar to the ensemble average, and both of them are closer to the observations compared to the other schemes. Besides, the authors also note that all members still overpredict the LWC by a factor of 2–8 in some regions, resulting in large deviation between the observation and ensemble average.摘要使用 WRF 模式中的 Morrison,WSM6,SBM,P3 四种微物理方案的集合, 模拟中尺度对流系统降水过程.研究发现不同的微物理方案模拟的对流云区液态含水量,冰水含量的垂直分布各不相同, 而模拟的层状云区液态含水量, 冰水含量的垂直分布结果相似. 总的来说与其他方案相比, Morrison 方案和集合平均的结果最接近观测值.我们也注意到在一些区域, 所有成员均高估了液态含水量 2–8 倍, 这也导致了在这些区域集合平均值与观测相比仍然有很大的差距.     

Analysis of lower-boundary climate factors contributing to the summer heatwave frequency over eastern Europe using a machine-learning model

A machine-learning (ML) model, the light gradient boosting machine (LightGBM), was constructed to simulate the variation in the summer (June–July–August) heatwave frequency (HWF) over eastern Europe (HWF_EUR) and to analyze the contributions of various lower-boundary climate factors to the HWF_EUR variation. The examined lower-boundary climate factors were those that may contribute to the HWF_EUR variation—namely, the sea surface temperature, soil moisture, snow-cover extent, and sea-ice concentration from the simultaneous summer, preceding spring, and winter. These selected climate factors were significantly correlated to the summer HWF_EUR variation and were used to construct the ML model. Both the hindcast simulation of HWF_EUR for the period 1981–2020 and its real-time simulation for the period 2011–2020, which used the constructed ML model, were investigated. To evaluate the contributions of the climate factors, various model experiments using different combinations of the climate factors were examined and compared. The results indicated that the LightGBM model had comparatively good performance in simulating the HWF_EUR variation. The sea surface temperature made more contributions to the ML model simulation than the other climate factors. Further examination showed that the best ML simulation was that which used the climate factors in the preceding winter, suggesting that the lower-boundary conditions in the preceding winter may be critical in forecasting the summer HWF_EUR variation.摘要本文使用LightGBM机器学习模型模拟了欧洲东部夏季热浪频率的变化, 并分析了多个底边界层气候因子的贡献. 所选取的气候因子包括前期冬季, 前期春季以及同期夏季的下垫面海温, 土壤湿度, 积雪以及海冰. 分析结果说明LightGBM模型能够较好的模拟出欧洲东部夏季热浪频率的变化, 其中海温因子对模拟的贡献最大. 进一步的分析研究显示, 使用前期冬季的气候因子进行的模拟可以获得最佳模拟结果, 意味着前期冬季的下垫面气候因子可能对夏季欧洲东部热浪频率变化的预报能起到关键作用.