初值对中国东部初夏土壤湿度可预报性影响

土壤湿度是影响天气和气候非常重要的因子之一,但目前针对土壤湿度可预报性的研究报道相对较少。该文在对BCC_CSM模式进行了适合的陆面初始化的条件下,设计了两组在中国东部地区采用不同土壤湿度初值的回报试验研究该地区土壤湿度的可预报性及初值对其可预报性影响问题。试验结果表明:BCC_CSM模式在真实的外场强迫下可以模拟出相对合理的土壤湿度;土壤湿度的可预报性在表层约为3候,随着深度的增加,土壤湿度的可预报性持续时间增加,在中层预报性甚至能达到月尺度以上;初值对于土壤湿度的预报存在影响,在表层影响时间约为2~3候,影响时间随着深度增加;浅层土壤湿度受降水的影响较大,浅层土壤湿度变化滞后降水变化约1~2 d,中层土壤湿度变化与降水变化存在5 d左右的滞后关系。     

Evaluating Soil Moisture Predictions Based on Ensemble Kalman Filter and SiB2 Model

Soil moisture is an important variable in the fields of hydrology, meteorology, and agriculture, and has been used for numerous applications and forecasts. Accurate soil moisture predictions on both a large scale and local scale for different soil depths are needed. In this study, a soil moisture assimilation and prediction based on the Ensemble Kalman Filter(EnKF) and Simple Biosphere Model(SiB2) have been performed in Meilin watershed, eastern China, to evaluate the initial state values with different assimilation frequencies and precipitation influences on soil moisture predictions. The assimilated results at the end of the assimilation period with different assimilation frequencies were set to be the initial values for the prediction period. The measured precipitation, randomly generated precipitation,and zero precipitation were used to force the land surface model in the prediction period. Ten cases were considered based on the initial value and precipitation. The results indicate that, for the summer prediction period with the deeper water table depth, the assimilation results with different assimilation frequencies influence soil moisture predictions significantly. The higher assimilation frequency gives better soil moisture predictions for a long lead-time. The soil moisture predictions are affected by precipitation within the prediction period. For a short lead-time, the soil moisture predictions are better for the case with precipitation, but for a long lead-time, they are better without precipitation. For the winter prediction period with a lower water table depth, there are better soil moisture predictions for the whole prediction period. Unlike the summer prediction period, the soil moisture predictions of winter prediction period are not significantly influenced by precipitation. Overall, it is shown that soil moisture assimilations improve its predictions.     

土壤湿度——一个跨季度降水预测中的重要因子及其应用探讨

阐述了土壤湿度对短期气候变化的重要作用,结合我国的业务现状提出亟需将这一因子应用于跨季度降水预测。通过将一个土壤湿度反演模型引入IAP跨季度气候预测系统,探讨了土壤湿度应用于季节降水预测的可行性及其效果。初步的个例分析表明:前期土壤湿度的异常分布对降水变化有较显著的影响,继续改进土壤湿度反演模型可望获得更好的降水预测效果。同时,提出的基于常规气象观测进行反演以获得大范围土壤湿度分布的办法在当前业务预测中具有很强的可操作性。     

Recent Researches on the Short-Term Climate Prediction at IAP－A Brief Review

回顾了近年来在中国科学院大气物理研究所开展的有关短期气候预测研究的进展。第一个短期气候数值预测是曾庆存等利用一个耦合了热带太平洋海洋环流模式的全球大气环流模式作出的。1997年，一个基于海气耦合模式的ENSO预测系统，包括一个海洋初始化方案被建立起来，同时也开展了基于海温异常的东亚气候可预测性研究。利用气候变动的准两年信号，王会军等提出了一个可以显著改进模式预测准确率的模式结果修正方案。为了考虑土壤湿度的初始异常对夏季气候的影响，一个利用大气资料如温度、降水等经验地反演土壤湿度的方法也被建立起来。还通过一系列的数值试验研究了 1998年夏季大水发生当中海温异常和大气环流初始异常的作用。     

Recent Researches on the Short-Term Climate Prediction at IAP－A Brief Review

Studies on the seasonal to extraseasonal climate prediction at the Institute of Atmospheric Physics (IAP) in recent years were reviewed. The first short-term climate prediction experiment was carried out based on the atmospheric general circulation model (AGCM) coupled to a tropical Pacific oceanic general circulation model (OGCM). In 1997, an ENSO prediction system including an oceanic initialization scheme was set up. At the same time, researches on the SST-induced climate predictability over East Asia were made. Based on the biennial signal in the interannual climate variability, an effective method was proposed for correcting the model predicted results recently. In order to consider the impacts of the initial soil mois ture anomalies, an empirical scheme was designed to compute the soil moisture by use of the atmospheric quantities like temperature, precipitation, and so on. Sets of prediction experiments were carried out to study the impacts of SST and the initial atmospheric conditions on the flood occurring over China in 1998.     

水汽场初值调整及其对华南降水预报贡献的研究

该文利用GMS多通道气象卫星资料推导得到的降水资料估算出的加热率, 作为非绝热的非线性正规模初始化过程中的非绝热强迫项, 进行风压场的初值调整, 再采用一个与模式中的对流参数化方案相反的逆运算方案, 进行水汽场的初值调整.以保证初始时刻按模式的物理参数化方案计算得到的加热率与由卫星推导的加热率一致. 这一方法在非绝热的非线性正规模初值化的框架中, 使初始时刻的水汽场得到调整.既实现了传统的初始化目标, 又提高了模式对降水的短时预报效果.对华南的两个个例的试验结果表明该文的方法是有效的.     

三江平原土壤湿度记忆性及其与水热气候条件的关系

利用1982—2020年三江平原19个国家气象观测站土壤湿度及同期降水、气温数据, 基于相关系数和自相关系数统计方法, 分析了黑龙江省三江平原土壤湿度记忆性及与降水、气温之间的关系。结果表明: 春、夏季三江平原土壤湿度记忆时间均在10—40 d, 各层土壤湿度记忆性的空间分布以中间层(10—20 cm)土壤湿度平均记忆时间最长, 呈上下层递减的趋势; 春季三江平原10—20 cm土层土壤湿度的记忆时长平均20 d, 夏季平均17 d; 夏季土壤湿度记忆性强度大于春季, 空间分布以三江平原西部的记忆性较强, 随着土层的增加土壤湿度记忆性有增大的趋势。降水是三江平原土壤湿度主要来源, 受降水和气温协同作用的影响, 夏、秋季土壤湿度与同期降水量、温湿指数均存在显著的正相关关系; 春季土壤湿度与前期秋冬季降水亦呈显著正相关, 与前期温湿指数呈负相关, 前期秋冬季气温的升高会促进土壤的融冻, 从而使当年春季土壤水分增加。     

Soil moisture effects on seasonal temperature and precipitation forecast scores in Europe

The Second Global Land Atmosphere Coupling Experiment (GLACE2) is designed to explore the improvement of forecast skill of summertime temperature and precipitation up to 8?weeks ahead by using realistic soil moisture initialization. For the European continent, we show in this study that for temperature the skill does indeed increase up to 6 weeks, but areas with (statistically significant) lower skill also exist at longer lead times. The skill improvement is smaller than shown earlier for the US, partly because of a lower potential predictability of the European climate at seasonal time scales. Selection of extreme soil moisture conditions or a subset of models with similar initial soil moisture conditions does improve the forecast skill, and sporadic positive effects are also demonstrated for precipitation. Using realistic initial soil moisture data increases the interannual variability of temperature compared to the control simulations in the South-Central European area at longer lead times. This leads to better temperature forecasts in a remote area in Western Europe. However, the covered range of forecast dates (1986–1995) is too short to isolate a clear physical mechanism for this remote correlation.     

Modulation of soil moisture–precipitation interactions over France by large scale circulation

How soil moisture affects precipitation is an important question—with far reaching consequences, from weather prediction to centennial climate change—, albeit a poorly understood one. In this paper, an analysis of soil moisture–precipitation interactions over France based on observations is presented. A first objective of this paper is to investigate how large scale circulation modulates soil moisture–precipitation interactions, thanks to a weather regime approach. A second objective is to study the influence of soil moisture not only on precipitation but also on the difference between precipitation and evapotranspiration. Indeed, to have a total positive soil moisture–precipitation feedback, the potential decrease in precipitation associated with drier soils should be larger than the decrease in evapotranspiration that drier soils may also cause. A potential limited impact of soil moisture on precipitation is found for some weather regimes, but its sign depends on large scale circulation. Indeed, antecedent dry soil conditions tend to lead to smaller precipitation for the negative phase of the North Atlantic Oscillation (NAO) regime but to larger precipitation for the Atlantic Low regime. This differential response of precipitation to soil moisture anomalies depending on large scale circulation is traced back to different responses of atmospheric stability. For all circulation regimes, dry soils tend to increase the lifted condensation level, which is unfavorable to precipitation. But for the negative phase of the NAO, low soil moisture tends to lead to an increase of atmospheric stability while it tends to lead to a decrease of stability for Atlantic Low. Even if the impact of soil moisture anomalies varies depending on large scale circulation (it is larger for Atlantic low and the positive phase of the NAO), dry soils always lead to a decrease in evapotranspiration. As the absolute effect of antecedent soil moisture on evapotranspiration is always much larger than its effects on precipitation, for all circulation regimes dry soil anomalies subsequently lead to positive precipitation minus evapotranspiration anomalies i.e. the total soil moisture feedback is found to be negative. This negative feedback is stronger for the Atlantic Low and the positive phase of the NAO regimes.     

基于土壤湿度和年际增量方法的我国夏季降水预测试验

选取欧亚大陆9个关键区的土壤湿度年际增量作为预测因子,采用变形的典型相关分析(BP-CCA)结合集合典型相关分析(ECC)方法建立集合预测模型,对我国东部夏季降水的年际增量进行预测,进而预测夏季降水。其中,1980~2004年的资料用于历史预测试验,而2005~2014年的资料用于独立样本预测试验。首先利用BP-CCA方法对9个因子分别建立单因子预测模型,然后采用ECC方法对9个预测因子按照不同的组合方式建立集合预测模型,并且对独立样本检验的效果进行了评估。结果表明,不同预测因子的组合对我国夏季降水均表现出一定的预测能力:东欧平原、贝加尔湖以北、我国河套地区及长江以南地区的土壤湿度对华北夏季降水预测效果较好;而巴尔喀什湖以北地区、我国西北地区、河套地区以及长江以南地区的土壤湿度对江淮夏季降水有较好预测效果;东欧平原、巴尔喀什湖以北地区以及我国河套地区的土壤湿度对华南降水预测技巧较高。这三组模型预测出的降水变化趋势与相应区域的观测结果较为一致,且预测评分(PS)均超过70分,距平相关系数(ACC)均为正值。研究表明土壤湿度因子中包含了对我国夏季降水有用的预测信号,可以考虑将土壤湿度应用于夏季降水的预测业务中。     

Soil moisture prediction over the Australian continent

Summary This paper describes an attempt to model soil moisture over the Australian continent with an integrated system of dynamic models and a Geographic Information System (GIS) data base. A land surface scheme with improved treatment of soil hydrological processes is described. The non-linear relationships between soil hydraulic conductivity, matric potential and soil moisture are derived from the Broadbridge and White soil model. For a single location, the prediction of the scheme is in good agreement with the measurements of the Hydrological and Atmospheric Pilot Experiment (HAPEX). High resolution atmospheric and geographic data are used in soil moisture prediction over the Australian continent. The importance of reliable land surface parameters is emphasized and details are given for deriving the parameters from a GIS. Predicted soil moisture patterns over the Australian continent in summer, with a 50 km spatial resolution, are found to be closely related to the distribution of soil types, apart from isolated areas and times under the influence of precipitation. This is consistent with the notion that the Australian continent in summer is generally under water stress. In contrast, predicted soil temperatures are more closely related to radiation patterns and changes in atmospheric circulation. The simulation can provide details of soil moisture evolution both in space and time, that are very useful for studies of land use sustainability, such as plant growth modelling and soil erosion prediction.With 12 Figures     

中国地区土壤湿度记忆性及其与降水特征变化的关系

本文首先利用中国气象局国家气象信息中心提供的中国732个站点观测的土壤体积含水量,评估了CLM4.5（Community Land Model version 4.5）在CFSR（Climate Forecast System Reanalysis）近地面大气数据驱动下模拟的逐月土壤湿度（记为CLM4.5-CFSR）,然后基于CLM4.5-CFSR比较了皮尔逊相关法和自相关法计算得到的1980～2009年中国地区土壤湿度记忆性的区域及季节分布特征,量化了土壤湿度的记忆能力,研究了降水频率、降水强度和近地表气温分别对土壤湿度记忆性的影响。结果表明:CLM4.5-CFSR能较好地反映出大部分地区月时间尺度上土壤湿度的变化特征。两种方法描述的土壤湿度记忆性的空间分布特征相似,但季节特征不同。不同深度土壤湿度的记忆时长相差不大,在0.85～2.2个月不等,其中内蒙古东北部较大,新疆西南部较小。春季,较湿的土壤记忆性也较强。当降水频率较低时,其对蒸发速率较大的地区土壤湿度的记忆性影响很小,当降水强度较大时,它会迅速补充土壤散失的水分,破坏初始时刻土壤的干湿状态,引起其记忆性减弱。近地表气温变化主要通过影响土壤的蒸发过程减弱土壤湿度的记忆性。未来可利用气候模式开展数值敏感性试验对本文得到的结论进行机理研究,为进一步提高季节和季节内尺度的降水预报提供依据。     

Relative contribution of soil moisture and snow mass to seasonal climate predictability: a pilot study

Land surface hydrology (LSH) is a potential source of long-range atmospheric predictability that has received less attention than sea surface temperature (SST). In this study, we carry out ensemble atmospheric simulations driven by observed or climatological SST in which the LSH is either interactive or nudged towards a global monthly re-analysis. The main objective is to evaluate the impact of soil moisture or snow mass anomalies on seasonal climate variability and predictability over the 1986–1995 period. We first analyse the annual cycle of zonal mean potential (perfect model approach) and effective (simulated vs. observed climate) predictability in order to identify the seasons and latitudes where land surface initialization is potentially relevant. Results highlight the influence of soil moisture boundary conditions in the summer mid-latitudes and the role of snow boundary conditions in the northern high latitudes. Then, we focus on the Eurasian continent and we contrast seasons with opposite land surface anomalies. In addition to the nudged experiments, we conduct ensembles of seasonal hindcasts in which the relaxation is switched off at the end of spring or winter in order to evaluate the impact of soil moisture or snow mass initialization. LSH appears as an effective source of surface air temperature and precipitation predictability over Eurasia (as well as North America), at least as important as SST in spring and summer. Cloud feedbacks and large-scale dynamics contribute to amplify the regional temperature response, which is however, mainly found at the lowest model levels and only represents a small fraction of the observed variability in the upper troposphere.     

Sensitivity of an ecosystem model to hydrology and temperature

We tested the sensitivity of a dynamic ecosystem model (LPJ-GUESS) to the representation of soil moisture and soil temperature and to uncertainties in the prediction of precipitation and air temperature. We linked the ecosystem model with an advanced hydrological model (JULES) and used its soil moisture and soil temperature as input into the ecosystem model. We analysed these sensitivities along a latitudinal gradient in northern Russia. Differences in soil temperature and soil moisture had only little influence on the vegetation carbon fluxes, whereas the soil carbon fluxes were very sensitive to the JULES soil estimations. The sensitivity changed with latitude, showing stronger influence in the more northern grid cell. The sensitivity of modelled responses of both soil carbon fluxes and vegetation carbon fluxes to uncertainties in soil temperature were high, as both soil and vegetation carbon fluxes were strongly impacted. In contrast, uncertainties in the estimation of the amount of precipitation had little influence on the soil or vegetation carbon fluxes. The high sensitivity of soil respiration to soil temperature and moisture suggests that we should strive for a better understanding and representation of soil processes in ecosystem models to improve the reliability of predictions of future ecosystem changes.     

A scaling analysis of soil moisture–precipitation interactions in a regional climate model

The University of Oklahoma’s Advanced Regional Prediction System (ARPS) was used to examine the impacts of varying mean soil moisture and model resolution on the magnitude and frequency of precipitation events in the U.S. Central Plains and to determine whether modeled soil moisture and precipitation fields exhibit scale invariance using the statistical moments. It was found that high soil moisture resulted in greater precipitation amounts and a higher frequency of events, suggesting the occurrence of a positive soil moisture–precipitation feedback. The scaling analysis performed on cumulative precipitation determined that these fields did not exhibit signs of self-similarity and, therefore, statistical properties cannot be predicted at other resolutions. The scaling properties of soil moisture were highly variable in time which has important implications for the use of remotely sensed data, as scaling properties from 1 day cannot necessarily be applied to subsequent days.     

江苏省自动土壤水分观测与人工观测对比分析及应用

利用2010年江苏省20个土壤水分站的自动站与人工观测资料,分析了自动站与人工观测的对比差值、相关系数和各自的方差等.结果表明:人工观测值平均高于自动站观测值,两者在浅层的平均差值最小,相关性最好.随着土壤深度的加深,人工与自动观测对比差值增大,相关性减小,在出现强降水时尤为明显.在有效降水较少时,各层人工观测方差均明显大于自动站观测.自动站观测方差在浅层为最大,随深度的加深而明显降低,因为受降水影响很小,而表现比较稳定.人工观测却受降水影响相对较大,方差平均值在各层表现波动均较大,在较深层波动更明显.最后通过多元线性回归方法,以六合站为例初步建立了土壤干旱预报模型并检验其预报能力.     

云物理初始化对一次强对流天气数值预报的影响研究

基于第二代华东快速更新循环同化预报模式系统,针对2015年4月28日华东强对流天气,分析了云初始化对强对流数值预报的作用和影响。有无云初始化试验对比结果表明,在循环系统中使用云初始化,能够显著提高0~6 h的降水预报评分,强降水的位置预报更接近实况。云初始化能较好地改善初始场水凝物的质量分布,提供较准确的相关对流系统的初始信息,改进强对流区域内水凝物的预报效果,有效避免了模式初始阶段的降水滞后现象,缩短了模式由于初始微物理信息缺失引起的“spin-up”时间。而积分6 h以后的结果与无云初始化的结果差别不大。      

南阳市土壤湿度与气候变化的关系分析

根据1981 2005年的气象观测资料和土壤湿度测定资料,利用统计学方法,分析了南阳市土壤湿度变化规律及与温度、降水的关系,结果表明:土壤湿度无论是年均值或最小值都呈明显下降趋势,年平均相对湿度下降约0.4%;浅层湿度变化幅度小,深层变化幅度大。影响土壤湿度的气象因子中,气温与浅层土壤湿度呈明显的负相关,降水量与深层土壤湿度呈明显正相关;各季土壤湿度与气温和降水量的二元回归方程都通过了F检验,其中春秋冬季通过0.01的显著性检验,夏季通过0.05的显著性检验。     

Impact of moisture flux convergence and soil moisture on precipitation: a case study for the southern United States with implications for the globe

Interactions between soil moisture, evapotranspiration (ET), atmospheric moisture fluxes and precipitation are complex. It is difficult to attribute the variations of one variable to another. In this study, we investigate the influence of atmospheric moisture fluxes and land surface soil moisture on local precipitation, with a focus on the southern United States (U.S.), a region with a strong humidity gradient and intense moisture fluxes. Experiments with the Weather Research and Forecasting model show that the variation of moisture flux convergence (MFC) is more important than that of soil moisture for precipitation variation over the southern U.S. Further analyses decompose the precipitation change into several contributing factors and show that MFC affects precipitation both directly through changing moisture inflow (wet areas) and indirectly by changing the precipitation efficiency (transitional zones). Soil moisture affects precipitation mainly by changing the precipitation efficiency, and secondly through direct surface ET contribution. The greatest soil moisture effects are over transitional zones. MFC is more important for the probability of heavier rainfall; soil moisture has much weaker impact on rainfall probability and its roles are similar for the probability of intermediate-to-heavy rainfall (>10 mm day^?1). Although MFC is more important than soil moisture for precipitation over most regions, the impact of soil moisture could be large over certain transitional regions. At the submonthly time scale, the African Sahel appears to be the only major region where soil moisture has a greater impact than MFC on precipitation. This study provides guidance to understanding and further investigation of the roles of local land surface processes and large-scale circulations on precipitation.     

利用GLDAS资料分析黄土高原半干旱区土壤湿度对气候变化的响应

利用GLDAS资料分析了1948~2010年黄土高原半干旱区气温、降水和土壤湿度的变化趋势,并重点讨论了气温和降水对土壤湿度的影响和相对贡献。结果表明:近60 a来黄土高原半干旱区整体呈现暖干化趋势,增温速率明显高于全球平均增温速率;不同深度的土壤湿度的长期变化均呈减小趋势,且年际间变化明显。不同深度的土壤湿度和气温呈负相关关系,并随着土壤加深,两者的相关性加强;土壤湿度和降水则呈正相关关系,相关关系最大出现在表层土壤。通过分析气温和降水在不同季节对土壤湿度的相对贡献发现,春季和冬季气温对土壤湿度的相对贡献较降水显著,秋季恰好相反,夏季气温和降水对土壤湿度的相对贡献大小相当。对比不同深度层降水、气温对土壤湿度的相对贡献得出,降水对浅层土壤湿度有显著作用,而气温对深层土壤湿度的作用更明显。