Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe

Soil moisture exhibits outstanding memory characteristics and plays a key role within the climate system. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy balance and therefore surface temperature. These attributes make soil moisture an important variable in the context of weather and climate forecasting. In this study we investigate the value of (initial) soil moisture information for sub-seasonal temperature forecasts. For this purpose we employ a simple water balance model to infer soil moisture from streamflow observations in 400 catchments across Europe. Running this model with forecasted atmospheric forcing, we derive soil moisture forecasts, which we then translate into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2 weeks in most of the considered catchments. Even if forecasting skills are rather small at longer lead times with significant skill only in some catchments at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly European Centre for Medium Range Weather Forecasting (ECMWF) temperature forecasts at these lead times. For both products (soil moisture-only forecast and ECMWF forecast), we find comparable or better forecast performance in the case of extreme events, especially at long lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill. Investigating the underlying soil moisture of the ECMWF forecasts we find good agreement with the simple model forecasts, especially at longer lead times. Analyzing the drivers of the temperature forecast skills we find that they are mainly controlled by the strengths of (1) the soil moisture-temperature coupling and (2) the soil moisture memory. We find a negative relationship between these controls that weakens the forecast skills, nevertheless there is a middle ground between both controls in several catchments, as shown by our results.     

土壤热异常对地表能量平衡影响初探

将来自土壤深部的热通量引入off line的陆面过程模式 (NCAR—LSM ) ,通过长达 2a的数值试验对比分析了它对各层次土壤温度和地表能量平衡的影响。　　在土壤底部引入 5W /m2 的热通量使底层土壤显著升温 ,但升温随着接近表层而迅速衰减。积分 3个月后 ,由地下进入地表的热流量增幅可达 1W/m2 以上 ,并持续增大到 5W /m2 ,地表最大升温约 0 .5K ,同时地表感热、蒸发潜热及长波辐射通量均有 1W /m2 左右的正异常 ;若将土壤热传导系数放大一个量级以加速热量交换 ,则地表升温提高到 1K以上 ,长波辐射增加 3W /m2 以上 ,超过了气溶胶全球平均的辐射效应。结果表明 :一定量值的土壤热异常对地表能量平衡和短期气候变化 (10 -1～ 10 1a)有着不可忽略的影响。同时 ,深入的资料分析、完善的陆面过程模式以及它与大气模式的耦合试验也是亟待进行的相关工作。     

CLDAS土壤湿度模拟结果及评估

中国气象局陆面数据同化系统（CLDAS V1.0）由陆面驱动数据融合和陆面模式模拟两部分组成。基于驱动数据,选取Canmunity Land Model 3.5（CLM3.5）作为CLDAS V1.0系统的陆面模式进行模拟试验,并对土壤模拟结果进行评估。利用2013年经过质量控制的中国气象局业务化自动土壤水分观测站实况数据、青藏高原试验观测数据及国际同类产品对模拟结果进行评估,结果表明:从各省以及全国平均结果看,相关系数普遍在0.8以上,偏差基本为-0.04~0.04 mm3·mm-3,平均均方根误差为0.04~0.05 mm3·mm-3,在青藏高原地区与国际同类产品相比,精度也有一定提高。总体而言,模拟结果已达到较高精度,数据集产品对中国区域干旱监测等具有重要意义。     

黑河地区近地面层辐射和温度的适用性模拟研究

为了检验中尺度区域大气模式在中国高原复杂下垫面区域气候模拟中的适用性,文中采用该模式在40余种不同的初始参数条件下模拟了1991年6月20日至7月20日黑河区域的近地面辐射收支平衡和空气温度。并分析了中尺度区域大气模式应用于中国西北部大起伏地形和高原地区复杂下垫面(HEIFE)的模拟能力。结果表明,在仅使用NCEP再分析资料、探空资料和常规地面观测资料(RAMS标准输入),而不根据当地特征调整区域大气模式初始参数的情况下,对近地面层的辐射收支和空气温度具有一定的模拟能力,但可能引发较大的误差;特别是地面向上长波辐射通量和2 m空气温度,其模拟结果与实测结果相差甚远。只有合理地调整模式的初始参数,主要是初始土壤层的温度和湿度,才能得到与实测资料符合良好的结果;而要进一步地模拟出这些物理量在复杂天气情况下的细致变化,则需要把土壤深度扩大到4 m左右,并使用较为可靠的数据初始化垂直非均匀的土壤湿度。     

Near-surface air temperature retrieval from satellite images and influence by wetlands in urban region

Near-surface air temperature (NSAT) directly reflects the thermal conditions above the ground and has been considered as a relevant indicator of resident health in urban regions. The rapid retrieval of NSAT data is necessary to assess urban environments. In this paper, a method of NSAT retrieval is developed that employs Landsat Thematic Mapper images using an Energy Balance Bowen Ratio model. This model is established based on the energy balance over land and the Bowen ratio. The degree of retrieval error obtained when using this model is determined on the basis of a comparison with the observed values obtained from weather stations; the mean error is approximately 2.21 °C. Moreover, the spatial relationship between NSAT and urban wetlands is analyzed using Geographical Information System technology. The results show that wetlands have an obvious influence on atmospheric temperature and that this influence decreases as the distance from the wetland increases. When that distance is less than 300 m, its influence on the NSAT is significant.     

土壤热异常影响地表能量平衡的个例分析和数值模拟

The statistical relationship between soil thermal anomaly and short-term climate change is presented based on a typical case study. Furthermore, possible physical mechanisms behind the relationship are revealed through using an off-line land surface model with a reasonable soil thermal forcing at the bottom of the soil layer.In the first experiment, the given heat flux is 5 W m-2 at the bottom of the soil layer (in depth of 6.3 m)for 3 months, while only a positive ground temperature anomaly of 0.06℃ can be found compared to the control run. The anomaly, however, could reach 0.65℃ if the soil thermal conductivity was one order of magnitude larger. It could be even as large as 0.81℃ assuming the heat flux at bottom is 10 W m-2. Meanwhile, an increase of about 10 W m-2 was detected both for heat flux in soil and sensible heat on land surface, which is not neglectable to the short-term climate change. The results show that considerable response in land surface energy budget could be expected when the soil thermal forcing reaches a certain spatial-tem poral scale. Therefore, land surface models should not ignore the upward heat flux from the bottom of the soil layer. Moreover, integration for a longer period of time and coupled land-atmosphere model are also necessary for the better understanding of this issue.     

Simulation of daily energy budget and mean soil temperatures at an arid site

Summary Soil temperature is often inadequately based upon relatively few measurements at widely dispersed locations. Within arid regions, such as the desert southwestern United States, soils, microclimates, and thus soil temperature may be markedly heterogeneous. Because extensive measurement of soil temperature is often not feasible, models are needed that simulate soil temperature based on readily available soil survey and above-ground weather information. This paper describes a simple energy-budget based model for simulating daily mean temperatures within a bare arid land soil. The model requires basic information on soil physical properties, and daily weather data including air temperature, windspeed, rainfall, and solar radiation to calculate daily surface energy budget components and surface temperature. One of two alternative numerical methods is then used to calculated subsurface temperatures. Tests of the model using 1987 daily temperature data from an arid site at Yuma, Arizona resulted in root mean square deviations within 1.4°C between daily modeled and measured temperatures at both 0.05 and 0.10 m depths. Sensitivity analysis showed modeled temperatures at 0.05 m depth to be most sensitive to parameters affecting the surface energy balance such as air temperature and solar radiation. Modeled temperatures at 1.0m depth were relatively more sensitive to initial temperature conditions and to parameters affecting distribution of energy within the profile such as thermal conductivity.With 3 Figures     

Simulation of the Bare Soil Surface Energy Balance at the Tongyu Reference Site in Semiarid Area of North China

The performance of a 1-D soil model in a semiarid area of North China was investigated using observational data from a cropland station at the Tongyu reference site of the Coordinated Enhanced Observing Period (CEOP) during the non-growing period, when the ground surface was covered with bare soil. Comparisons between simulated and observed soil surface energy balance components as well as soil temperatures and water contents were conducted to validate the soil model. Results show that the soil model could produce good simulations of soil surface temperature, net radiation flux and sensible heat flux against observed values with the RMSE of 1.54oC, 7.71 W m-2 and 27.79 W m-2, respectively. The simulated volumetric soil water content is close to the observed values at various depths with the maximal difference between them being 0.03. Simulated latent heat and ground heat fluxes have relatively lower errors in relative to net radiation and sensible heat flux. In conclusion, the soil model has good capacity to simulate the bare soil surface energy balance at the Tongyu cropland station and needs to be further tested in longer period and at more sites in semiarid areas.     

Simulation of surface energy fluxes using high-resolution non-hydrostatic simulations and comparisons with measurements for the LITFASS-2003 experiment

Land-surface heterogeneity effects on the subgrid scale of regional climate and numerical weather prediction models are of vital interest for the energy and mass exchange between the surface and the atmospheric boundary layer. High-resolution numerical model simulations can be used to quantify these effects, and are a tool used to obtain area-averaged surface fluxes over heterogeneous land surfaces. We present high-resolution model simulations for the LITFASS area near Berlin during the LITFASS-2003 experiment, which were carried out using the non-hydrostatic model FOOT3DK of the University of Köln with horizontal resolutions of 1 km and 250 m. The LITFASS-2003 experimental dataset is used for comparison. The screen level quantities show good quality for the simulated pressure, temperature, humidity and wind speed and direction. Averaged over the four week experimental period, simulated surface energy fluxes at land stations show a small bias for the turbulent heat fluxes and an underestimation of the net radiation caused by excessive cloudiness in the simulations. For eight selected days with low cloud amounts, the net radiation bias is close to zero, but the sensible heat flux shows a strong positive bias. Large differences are found for latent heat fluxes over a lake, which are partly due to local effects on the measurements, but an additional problem seems to be the overestimation of the turbulent exchange under stable conditions in the daytime internal boundary layer over the lake. In the area average over the LITFASS area of 20 ×  20 km², again a strong positive bias of 70 W m^?2 for the sensible heat is present. For the low soil moisture conditions during June 2003, the simulation of the turbulent heat fluxes is sensitive to variations in the soil type and its hydrological properties. Under these conditions, the supply of ground water to the lowest soil layer should be accounted for. Different area-averaging methods are tested. The experimental set-up of the LITFASS-2003 experiment is found to be well suited for the computation of area-averaged turbulent heat fluxes.     

利用气象卫星资料对春季土壤水分进行监测的地面响应模型的研究

根据卫星遥感中利用热惯量法监测土壤水分的原理,考虑辐射平衡和潜热交换,分析了土壤热通量与地面辐射的关系及显热交换和潜热交换对土壤热通量的影响,建立土壤水分模型,为农业气象服务提供科学依据,也为利用卫星资料监测春季裸地土壤水分提供地面响应模型。     

Thermal bioclimate in idealized urban street canyons in Campinas, Brazil

Among several urban design parameters, the height-to-width ratio (H/W) and orientation are important parameters strongly affecting thermal conditions in cities. This paper quantifies changes in thermal comfort due to typical urban canyon configurations in Campinas, Brazil, and presents urban guidelines concerning H/W ratios and green spaces to adapt urban climate change. The study focuses on thermal comfort issues of humans in urban areas and performs evaluation in terms of physiologically equivalent temperature (PET), based on long-term data. Meteorological data of air temperature, relative humidity, wind speed and solar radiation over a 7-year period (2003–2010) were used. A 3D street canyon model was designed with RayMan Pro software to simulate the influence of urban configuration on urban thermal climate. The following configurations and setups were used. The model canyon was 500 m in length, with widths 9, 21, and 44 m. Its height varied in steps of 2.5 m, from 5 to 40 m. The canyon could be rotated in steps of 15°. The results show that urban design parameters such as width, height, and orientation modify thermal conditions within street canyons. A northeast–southwest orientation can reduce PET during daytime more than other scenarios. Forestry management and green areas are recommended to promote shade on pedestrian areas and on façades, and to improve bioclimate thermal stress, in particular for H/W ratio less than 0.5. The method and results can be applied by architects and urban planners interested in developing responsive guidelines for urban climate issues.     

高分辨率WRF模式中土壤湿度扰动对短期高温天气模拟影响的个例研究

本文利用WRFV3.6中尺度预报模式就土壤湿度扰动对2003年7月22~23日和29~30日短期高温天气过程的影响进行了高分辨率模拟研究。结果表明:(1)WRF模式地表气温对土壤湿度扰动有较强的敏感性,且随着土壤湿度的增加(减小)而降低(升高)。同时,模式中土壤湿度对地面气温影响的强度对模式分辨率具有较高的依赖性。(2)不同模式分辨率下气温随土壤湿度变化的规律一致;由于更高分辨率的地形资料的应用,提高分辨率可在较大程度上改善模拟效果。(3)不同土壤湿度试验模拟的地表感热、潜热通量可直接影响气温变化;(4)土壤湿度扰动通过间接影响高温发展的近地层各物理过程使得地表气温发生变化。这些过程中,对流(平流)过程在全天表现为增温(冷却)的作用,强度在白天均随土壤湿度的减小而增加。在较干的土壤条件下,非绝热增温在白天的主导地位加强;在夜间,非绝热冷却的强度减弱,且小于占据主导的对流绝热增温的强度。以上结果表明,在模拟和预报高温天气时土壤湿度非常重要,也意味着通过土壤湿度扰动的集合预报方法来改进模式高温模拟预报具有较大的潜力。     

A non-hydrostatic modeling study of surface moisture effects on mesoscale convection induced by sea breeze circulation

Summary Convection and subsequent precipitation induced by the sea breeze circulations are often observed in the Florida peninsula during summer. In this study, the mechanisms of initiation and maintenance of the convective clouds and precipitation are investigated. A fully-compressible fine resolution non-hydrostatic mesoscale numerical model is used in this study. Surface energy and moisture budget were included in this model to simulate the diurnal cycle of ground surface temperature and wetness. The model also has a sophisticated boundary layer and explicit cloud physics. A sounding obtained from Orlando, Florida at 1110 UTC 17 July 1991 as part of the Convection and Precipitation Electrification (CaPE) experiment is used for initialization. The initial data for the model is kept in geostrophic and thermal wind balance. Several sensitivity tests were conducted to investigate the effects of different treatments of ground surface moisture and temperature on the model forecast of the convection and precipitation induced by the sea breeze circulations. The simulations agree reasonably well with the observations when both surface energy and moisture budget were included in the model to predict ground surface temperature and wetness. The surface moisture has a significant impact on the formation, strength, sustenance, and the location of convection and precipitation induced by the sea breezes.With 17 Figures     

The role of surface energy balance complexity in land surface models' sensitivity to increasing carbon dioxide

Global simulations with the Bureau of Meteorology Research Centre climate model coupled to the CHAmeleon Surface Model (CHASM) are used to explore the sensitivity of simulated changes in evaporation, precipitation, air temperature and soil moisture resulting from a doubling of carbon dioxide in the atmosphere. Five simulations, using prescribed sea surface temperatures, are conducted which are identical except in the level of complexity used to represent the surface energy balance. The simulation of air temperature, precipitation, evaporation and soil moisture at 1 2 CO₂ and at 2 2 CO₂ are generally sensitive at statistically significant levels to the complexity of the surface energy balance representation (i.e. the level of complexity used to represent these processes affects the simulated climate). However, changes in mean quantities, resulting from a doubling of atmospheric CO₂, are generally insensitive to the surface energy balance complexity. Conversely, changes in the spatial and temporal variance of evaporation and soil moisture are sensitive to the surface energy balance complexity. The addition of explicit canopy interception to the simplest model examined here enables that model to capture the change in the variance of evaporation simulated by the more complex models. In order to simulate changes in the variability of soil moisture, an explicit parameterization of bare soil evaporation is required. Overall, our results increase confidence that the simulation by climate models of the mean impact of increasing CO₂ on climate are reliable. Changes in the variability resulting from increased CO₂ on air temperature, precipitation or evaporation are also likely to be reliable since climate models typically use sufficiently complex land surface schemes. However, if the impact of increased CO₂ on soil moisture is required, then a more complex surface energy balance representation may be needed in order to capture changes in variability. Overall, our results imply that the level of complexity used by most climate models to represent the surface energy balance is appropriate and does not contribute significant uncertainty in the simulation of changes resulting from increasing CO₂. Our results only relate to surface energy balance complexity, and major uncertainties remain in how to model the surface hydrology and changes in the physiology, structural characteristics and distribution of vegetation. Future developments of land surface models should therefore focus on improving the representation of these processes.     

A Model to Predict Surface Temperatures

A model to predict the surface temperature of a variety of surfaces is described. The model solves the surface energy balance equation iteratively, using only standard meteorological data. Since surface and soil temperature information is not required for initialisation, the model is portable and, in theory, could be used for any surface and location. It is shown that, in order to obtain the correct cooling rates for vegetation during the night, the direct influence of the ground flux must be removed from the energy balance equation for the layer of vegetation. A scheme that couples a vegetation canopy to the ground solely by radiation is described, giving satisfactory cooling rates when compared with observations. Observations from a field site at Cardington, near Bedford, UK, are used to test the accuracy of the model for road and grass surfaces. When compared against these data, the model predicts surface temperatures with a root mean square error of about 1 °C for the road and 2 °C for the grass. Data from other sources not only give similar results to the Cardington data, but also demonstrate that the model can reproduce the characteristics of wet and partially dry soils and also dry desert sand. A study of the sensitivity of the model to errors in the forcing data indicates that inaccuracies in the air temperature data lead to similar sized errors in the predicted surface temperatures. Fluctuations in the forcing data that are not resolved by the model will affect a grass surface much more than a road surface, due to the relatively small thermal inertia of the grass.     

The Wave Train Characteristics of Teleconnection Caused by the Thermal Anomaly of the Underlying Surface of the Tibetan Plateau. Part Ⅰ: Data Analysis

探讨了前期青藏高原下垫面热力结构异常对后期长江中下游地区降水的影响。通过资料分析揭示出长江中下游地区夏季降水异常前期冬、春季青藏高原下垫面三维热力结构强信号特征,即长江中下游夏季旱涝前期高原南部和北部各层次的地温距平呈反位相分布。从地面0cm到地下320 cm的地温距平分布为:涝年高原偏南部(30°N以南)为正,中部和北部(30°N以北)为负,旱年时相反。其中地温距平的大值区在 40 cm到160 cm层之间。同时揭示了北半球环流型对青藏高原下垫面热力异常可能产生遥响应,并形成季尺度低频波的传播,从而影响长江中下游地区后期的降水,反映了遥相关是区域性旱涝形成的一个动力机制。资料分析结果表明前期青藏高原下垫面三维热力结构异常是后期长江中下游地区降水异常的重要原因之     

Modeling the climatic effects of urbanization in the Beijing–Tianjin–Hebei metropolitan area

In this analysis, the weather research and forecasting model coupled with a single-layer urban canopy model is used to simulate the climatic impacts of urbanization in the Beijing–Tianjin–Hebei metropolitan area, which has experienced significant expansion in its urban areas. Two cases examining current landscapes and the sensitivity test of urban areas replaced by cropland have been carried out to explore the changes in the surface air and atmospheric boundary structure. The impact of urbanization on annual mean surface air temperature has been found to be more than 1 °C in urban areas, and the maximum difference is almost 2 °C. The change in near-surface level temperature is most pronounced in winter, but the area influenced by urbanization is slightly larger in summer. The annual mean water vapor mixing ratio and wind speed are both reduced in the urban area. The effect of urbanization can only heat the temperature inside the urban boundary layer, below 850 hPa. The modeling results also indicate that the underlying surface thermal forces induced by the “urban heat island” effect enhance vertical air movement and engenders a convergence zone over urban areas. The convergence at low level together with the moisture increases in the layer between 850 and 700 hPa triggered the increase of convective precipitation.     

The impact of climatic and non-climatic factors on land surface temperature in southwestern Romania

Land surface temperature is one of the most important parameters related to global warming. It depends mainly on soil type, discontinuous vegetation cover, or lack of precipitation. The main purpose of this paper is to investigate the relationship between high LST, synoptic conditions and air masses trajectories, vegetation cover, and soil type in one of the driest region in Romania. In order to calculate the land surface temperature and normalized difference vegetation index, five satellite images of LANDSAT missions 5 and 7, covering a period of 26 years (1986–2011), were selected, all of them collected in the month of June. The areas with low vegetation density were derived from normalized difference vegetation index, while soil types have been extracted from Corine Land Cover database. HYSPLIT application was employed to identify the air masses origin based on their backward trajectories for each of the five study cases. Pearson, logarithmic, and quadratic correlations were used to detect the relationships between land surface temperature and observed ground temperatures, as well as between land surface temperature and normalized difference vegetation index. The most important findings are: strong correlation between land surface temperature derived from satellite images and maximum ground temperature recorded in a weather station located in the area, as well as between areas with land surface temperature equal to or higher than 40.0 °C and those with lack of vegetation; the sandy soils are the most prone to high land surface temperature and lack of vegetation, followed by the chernozems and brown soils; extremely severe drought events may occur in the region.     

土壤湿度初始异常对东亚区域气候模拟影响的敏感性试验

利用耦合了CLM3.5陆面模式的区域气候模式RegCM4.0,通过敏感性试验,探讨了人为减小春季初始土壤体积水含量对短期时间尺度东亚夏季气候模拟的可能影响。结果表明:较低的初始土壤湿度场能够明显改变区域的地表能量平衡,引起地表净长波辐射和感热通量的显著增加,进而加强了地表对大气的加热,因而引起东亚大范围地区特别是中国东部、印度北部和中亚地区地表温度、气温的升高。与气温不同,初始土壤湿度场对降水的影响很小而且有较大的不确定性,同时偏暖的下垫面使得对流层中高层出现暖高压异常,但这些影响均不显著。综合来看,土壤湿度初始场的初始异常,对RegCM4.0 模式东亚气候模拟的结果有一定影响,特别是在地表温度、气温和能量平衡方面,应在以后的模拟中加以考虑。     

利用任意时刻AVHRR资料近似估计区域地表温度日较差的试验

根据表征土壤温度日变化的土温方程一阶近似解，提出一种利用一日中任意时刻NOAA－AVHRR图像数据估计地表温度日较差的简易推算方法。该方法尤其可用于反演土壤含水量的计算，当图像数据的时次与热惯量法所要求的最高、最低温度时次配不准的情况下，近似地估计地表温度日较差，进而计算地表热惯量及相应的土壤含水量。用实例验证了该方法的可行性，为进一步推广应用奠定基础。