Land response to atmosphere at different resolutions in the common land model over East Asia

Towards a better understanding of hydrological interactions between the land surface and atmosphere, land surface models are routinely used to simulate hydro-meteorological fluxes. However, there is a lack of observations available for model forcing, to estimate the hydro-meteorological fluxes in East Asia. In this study, Common Land Model (CLM) was used in offline-mode during the summer monsoon period of 2006 in East Asia, with different forcings from Asiaflux, Korea Land Data Assimilation System (KLDAS), and Global Land Data Assimilation System (GLDAS), at point and regional scales, separately. The CLM results were compared with observations from Asiaflux sites. The estimated net radiation showed good agreement, with r =0.99 for the point scale and 0.85 for the regional scale. The estimated sensible and latent heat fluxes using Asiaflux and KLDAS data indicated reasonable agreement, with r = 0.70. The estimated soil moisture and soil temperature showed similar patterns to observations, although the estimated water fluxes using KLDAS showed larger discrepancies than those of Asiaflux because of scale mismatch. The spatial distribution of hydro-meteorological fluxes according to KLDAS for East Asia were compared to the CLM results with GLDAS, and the GLDAS provided online. The spatial distributions of CLM with KLDAS were analogous to CLM with GLDAS, and the standalone GLDAS data. The results indicate that KLDAS is a good potential source of high spatial resolution forcing data. Therefore, the KLDAS is a promising alternative product, capable of compensating for the lack of observations and low resolution grid data for East Asia.     

A 10-Yr Global Land Surface Reanalysis Interim Dataset (CRA-Interim/Land): Implementation and Preliminary Evaluation

A land surface reanalysis dataset covering the most recent decades is able to provide temporally consistent initial conditions for weather and climate models, and thus is crucial to verifying/improving numerical weather/climate forecasts/predictions. In this paper, we report the development of a 10-yr China Meteorological Administration (CMA) global Land surface ReAnalysis Interim dataset (CRA-Interim/Land; 2007–2016, 6-h intervals, approximately 34-km horizontal resolution). The dataset was produced and evaluated by using the Global Land Data Assimilation System (GLDAS) and NCEP Climate Forecast System Reanalysis (CFSR) global land surface reanalysis datasets, as well as in situ observations in China. The results show that the global spatial patterns and monthly variations of the CRA-Interim/Land, GLDAS, and CFSR climatology are highly consistent, while the soil moisture and temperature values of the CRA-Interim/Land dataset are in between those of the GLDAS and CFSR datasets. Compared with ground observations in China, CRA-Interim/Land soil moisture is comparable to or better than that of GLDAS and CFSR datasets for the 0-10-cm soil layer and has higher correlations and slightly lower root mean square errors (RMSE) for the 10-40-cm soil layer. However, CRA-Interim/Land shows negative biases in 10-40-cm soil moisture in Northeast China and north of central China. For ground temperature and the soil temperature in different layers, CRA-Interim/Land behaves better than the CFSR, especially in East and central China. CRA-Interim/Land has added value over the land components of CRA-Interim due to the introduction of global precipitation observations and improved soil/vegetation parameters. Therefore, this dataset is potentially a critical supplement to the CRA-Interim. Further evaluation of the CRA-Interim/Land, assimilation of near-surface atmospheric forcing variables, and extension of the current dataset to 40 yr (1979–2018) are in progress.     

Simulation of location-specific severe thunderstorm events using high resolution land data assimilation

In this study, the impact of different land initial conditions on the simulation of thunderstorms and monsoon depressions is investigated using the Weather Research and Forecasting (WRF) model. A control run (CNTL) and a simulation with an improved land state (soil moisture and temperature) using the High Resolution Land Data Assimilation System (HRLDAS, experiment name: EHRLDAS) are compared for three different rainfall cases in order to examine the robustness of the assimilation system. The study comprises two thunderstorm cases (one in the pre-monsoon and one during the monsoon) and one monsoon depression case that occurred during the Interaction of Convective Organisation, Atmosphere, Surface and Sea (INCOMPASS) field campaign of the 2016 Indian monsoon. EHRLDAS is shown to yield improvements in the representation of location-specific rainfall, particularly over land. Further, it is found that surface fluxes as well as convective indices are better captured for the pre-monsoon thunderstorm case in EHRLDAS. By analysing components of the vorticity tendency equation, it is found that the vertical advection term is the major contributor towards the positive vorticity tendency in EHRLDAS compared to CNTL, hence improving localised convection and consequently facilitating rainfall. Significant improvements in the simulation of the pre-monsoon thunderstorm are noted, as seen using Automatic Weather Station (AWS) validation, whereas improvements in the monsoon depression are minimal. Further, it is found that vertical advection (moisture flux convergence) is the major driver modulating the convective circulation in localised thunderstorm (monsoon depression) cases and these dynamics are better represented by EHRLDAS compared to CNTL. These findings underline the importance of accurate and high resolution land-state conditions in model initial conditions for forecasting severe weather systems, particularly the simulation of localised thunderstorms over India.     

Land surface sensitivity of monsoon depressions formed over Bay of Bengal using improved high-resolution land state

Monsoon depressions (MDs) constitute a large fraction of the total rainfall during the Indian summer monsoon season. In this study, the impact of high-resolution land state is addressed by assessing the evolution of inland moving depressions formed over the Bay of Bengal using a mesoscale modeling system. Improved land state is generated using High Resolution Land Data Assimilation System employing Noah-MP land-surface model. Verification of soil moisture using Soil Moisture and Ocean Salinity (SMOS) and soil temperature using tower observations demonstrate promising results. Incorporating high-resolution land state yielded least root mean squared errors with higher correlation coefficient in the surface and mid tropospheric parameters. Rainfall forecasts reveal that simulations are spatially and quantitatively in accordance with observations and provide better skill scores. The improved land surface characteristics have brought about the realistic evolution of surface, mid-tropospheric parameters, vorticity and moist static energy that facilitates the accurate MDs dynamics in the model. Composite moisture budget analysis reveals that the surface evaporation is negligible compared to moisture flux convergence of water vapor, which supplies moisture into the MDs over land. The temporal relationship between rainfall and moisture convergence show high correlation, suggesting a realistic representation of land state help restructure the moisture inflow into the system through rainfall-moisture convergence feedback.     

Satellite Monitoring of the Surface Water and Energy Budget in the Central Tibetan Plateau

The water and energy cycle in the Tibetan Plateau is an important component of Monsoon Asia and the global energy and water cycle. Using data at a CEOP （Coordinated Enhanced Observing Period）-Tibet site, this study presents a first-order evaluation on the skill of weather forecasting from GCMs and satellites in producing precipitation and radiation estimates. The satellite data, together with the satellite leaf area index, are then integrated into a land data assimilation system （LDAS-UT） to estimate the soil moisture and surface energy budget on the Plateau. The system directly assimilates the satellite microwave brightness temperature, which is strongly affected by soil moisture but not by cloud layers, into a simple biosphere model. A major feature of this system is a dual-pass assimilation technique, which can auto-calibrate model parameters in one pass and estimate the soil moisture and energy budget in the other pass. The system outputs, including soil moisture, surface temperature, surface energy partition, and the Bowen ratio, are compared with observations, land surface models, the Global Land Data Assimilation System, and four general circulation models. The results show that this satellite data-based system has a high potential for a reliable estimation of the regional surface energy budget on the Plateau.     

Climate response to introduction of the ESA CCI land cover data to the NCAR CESM

The European Space Agency Climate Change Initiative Land Cover data (ESA CCI-LC, from 1992 to 2015) is introduced to the National Center for Atmospheric Research Community Earth System Model version 1.2.1 (NCAR CESM1.2.1). In comparison with the original land surface data in the Community Land Model version 4 (ORG), the new data features notable land use and land cover change (LULCC) with increased forests over northeastern Asia and Alaska by decreasing shrublands and grasslands. Overestimated bare land cover over the Tibetan Plateau (TP) and the Rocky Mountains in the ORG are corrected with the replacements by grasslands and shrublands respectively in the new data. The model simulation results show that with the introduction of the ESA CCI-LC, the simulated surface albedo, surface net radiation flux, sensible and latent heat fluxes are relatively improved over the regions where significant LULCC exists, such as northeastern Asia, Alaska, the TP, and Australia. Surface air temperature, precipitation, and atmospheric circulation are improved in boreal winter but degraded in summer. The winter warming over northeastern Asia results from increased longwave downwelling flux and adiabatic heating while the notable winter cooling over Alaska is attributed to strong cold advection followed by reduced longwave downwelling flux. LULCC alters precipitation by influencing water vapor content. In winter, LULCC affects atmospheric circulation via modulating baroclinicity while in summer, it influences land-sea thermal contrast, thus affecting the intensity of East Asian summer monsoon. LULCC also alters the simulated dust burden.

     

Soil moisture influence on summertime surface air temperature over East Asia

Soil moisture influence on surface air temperature in summer is statistically quantified across East Asia using the Global Land Data Assimilation System soil moisture and observational temperature. The analysis uses a soil moisture feedback parameter computed based on lagged covariance ratios. It is found that significant negative soil moisture feedbacks on temperature mainly appear over the transition zones between dry and wet climates of northern China and Mongolia. Over these areas, the feedbacks account for typically 5–20% of the total temperature variance, with the feedback parameter of ?0.2°C to ?0.5°C (standardized soil moisture)^?1. Meanwhile, positive feedbacks may exist over some areas of Northeast Asia but are much less significant. These findings emphasize the importance of soil moisture-temperature feedbacks in influencing summer climate variability and have implications for seasonal temperature forecasting.     

The effects of land surface process perturbations in a global ensemble forecast system

Atmospheric variability is driven not only by internal dynamics, but also by external forcing, such as soil states, SST, snow, sea-ice cover, and so on. To investigate the forecast uncertainties and effects of land surface processes on numerical weather prediction, we added modules to perturb soil moisture and soil temperature into NCEP’s Global Ensemble Forecast System (GEFS), and compared the results of a set of experiments involving different configurations of land surface and atmospheric perturbation. It was found that uncertainties in different soil layers varied due to the multiple timescales of interactions between land surface and atmospheric processes. Perturbations of the soil moisture and soil temperature at the land surface changed sensible and latent heat flux obviously, as compared to the less or indirect land surface perturbation experiment from the day-to-day forecasts. Soil state perturbations led to greater variation in surface heat fluxes that transferred to the upper troposphere, thus reflecting interactions and the response to atmospheric external forcing. Various verification scores were calculated in this study. The results indicated that taking the uncertainties of land surface processes into account in GEFS could contribute a slight improvement in forecast skill in terms of resolution and reliability, a noticeable reduction in forecast error, as well as an increase in ensemble spread in an under-dispersive system. This paper provides a preliminary evaluation of the effects of land surface processes on predictability. Further research using more complex and suitable methods is needed to fully explore our understanding in this area.     

Spin-up behavior of soil moisture content over East Asia in a land surface model

This study presents an investigation of the spin-up behavior of soil moisture content (SMC) and evapotranspiration (ET) in an offline Noah land surface model (LSM) for East Asia, focusing on its interplay with the Asian monsoon. The set of 5-year recursive runs is conducted to properly assess the spin-up behavior of land surface processes and consists of simulations initialized with (1) a spatially uniform soil moisture, (2) NCEP GDAS soil moisture data, and (3) ECMWF ERA-Interim soil moisture data. Each run starts either after or before the summer monsoon. Initial SMCs from GDAS and ERA-Interim data significantly deviate from the equilibrium state (spin-up state) with the given input forcing even though the same equilibrium is reached within 3-year spin-up time, indicating that spin-up of land surface process is necessary. SMC reaches the equilibrium much quickly when (1) the consistent LSMs have been used in the prediction and analysis systems and (2) the spin-up simulation starts before the onset of heavy rainfall events during summer monsoon. For an area with heavy monsoon rainfall, the total column SMC and ET spin up quickly. The spin-up time over dry land is about 2–3?years, but for monsoon rainfall area decreases dramatically to about 3?months if the spin-up run starts just before the onset of monsoon. Further scrutiny shows that the spin-up time is well correlated with evaporative fraction given by the ratio between the latent heat flux and the available energy at the land surface.     

内蒙古地区下垫面变化对土壤湿度数值模拟的影响

利用第二次全国土壤调查土壤质地数据（SNSS）和中国区域陆地覆盖资料（CLCV）将陆面过程模式CLM3.5（Community Land Model version 3.5）中基于联合国粮食农业组织发展的土壤质地数据（FAO）和MODIS卫星反演的陆地覆盖数据（MODIS）进行了替换,使用中国气象局陆面数据同化系统（CMA Land Data Assimilation System,CLDAS）大气强迫场资料,分别驱动基于同时改进土壤质地和陆地覆盖数据的CLM3.5（CLM-new）、基于只改进陆地覆盖数据的CLM3.5（CLM-clcv）、基于只改进土壤质地数据的CLM3.5（CLM-snss）和基于原始下垫面数据的CLM3.5（CLM-ctl）,对内蒙古地区2011～2013年土壤湿度的时空变化进行模拟试验,研究下垫面改进对CLM3.5模拟土壤湿度的影响。将四组模拟结果与46个土壤水分站点观测数据进行对比分析,结果表明:相对于控制试验,CLM-clcv、CLM-snss和CLM-new都能不同程度地改进土壤湿度模拟,其中CLM-clcv主要在呼伦贝尔改进明显,CLM-snss则在除呼伦贝尔以外的大部地区改进显著,CLM-ctl模拟的土壤湿度在各层上均系统性偏大,而CLM-new模拟土壤湿度最好地反映出内蒙古地区观测的土壤湿度的时空变化特征,显著改善了土壤湿度的模拟,体现在与观测值有着更高的相关系数和更小的平均偏差与均方根误差。     

Testing a GCM land surface scheme against catchment-scale runoff data

A GCM land surface scheme was used, in off-line mode, to simulate the runoff, latent and sensible heat fluxes for two distinct Australian catchments using observed atmospheric forcing. The tropical Jardine River catchment is 2500 km² and has an annual rainfall of 1700 mm y^–1 while the Canning River catchment is 540 km², has a Mediterranean climate (annual rainfall of 800 mm y^–1) and is ephemeral for half the year. It was found that the standard version of a land surface scheme developed for a GCM, and initialised as for incorporation into a GCM, simulated similar latent and sensible heat fluxes compared to a basin-scale hydrological model (MODHYDROLOG) which was calibrated for each catchment. However, the standard version of the land surface scheme grossly overestimated the observed peak runoff in the wet Jardine River catchment at the expense of runoff later in the season. Increasing the soil water storage permitted the land surface scheme to simulate observed runoff quite well, but led to a different simulation of latent and sensible heat compared to MODHYDROLOG. It is concluded that this 2-layer land surface scheme was unable to simulate both catchments realistically. The land surface scheme was then extended to a three-layer model. In terms of runoff, the resulting control simulations with soil depths chosen as for the GCM were better than the best simulations obtained with the two-layer model. The three-layer model simulated similar latent and sensible heat for both catchments compared to MODHYDROLOG. Unfortunately, for the ephemeral Canning River catchment, the land surface scheme was unable to time the observed runoff peak correctly. A tentative conclusion would be that this GCM land surface scheme may be able to simulate the present day state of some larger and wetter catchments but not catchments with peaky hydrographs and zero flows for part of the year. This conclusion requires examination with a range of GCM land surface schemes against a range of catchments. Received: 9 June 1995 / Accepted: 4 April 1996     

东亚中纬度夏季陆面增暖与土壤湿度异常的联系

利用1979—2015年ERA-Interim再分析土壤湿度、云量资料,NCEP/NCAR再分析环流资料和CPC土壤湿度资料,分析了东亚中纬度夏季陆面热力异常的时空分布特征及其与前期春季土壤湿度异常的联系,探讨了前期春季土壤湿度影响东亚中纬度夏季陆面增暖的可能途径。结果表明,东亚中纬度夏季土壤表层温度呈全区一致增暖趋势,其中贝加尔湖及以南地区温度变化最剧烈、增暖最迅速,且1990年代中期前后存在一个明显由冷向暖的年代际转变。进一步分析发现,春、夏季西西伯利亚到贝加尔湖北部地区的土壤湿度与夏季贝加尔湖及以南地区的土壤表层温度在年代际和年际尺度上均存在紧密联系:西西伯利亚到贝加尔湖北部地区土壤湿度异常偏高,通常对应贝加尔湖及南部地区夏季土壤表层温度偏高。西西伯利亚到贝加尔湖北部地区春、夏土壤湿度异常可以引起夏季大气环流异常,从而对东亚夏季中纬度陆面热力异常产生影响:春、夏土壤湿度偏高时,贝加尔湖及其南部地区上空位势高度为正异常,对应为反气旋性异常环流,云量减少,有利于东亚中纬度陆面增暖;反之,则对应为气旋性异常环流,不利于陆面增暖。     

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。     

两种陆面模式对中国区域土壤温度模拟的对比分析

为研究不同陆面模式对中国区域土壤温度的模拟效果,基于中国气象局陆面数据同化系统（CMA Land Data Assimilation System,CLDAS）大气驱动数据分别驱动Noah和Noah-MP陆面模式进行中国区域土壤温度的模拟（简称:CLDAS_Noah和CLDAS_Noah-MP试验）,使用2010—2018年中国气象局2380个土壤温度观测站点10和40 cm观测数据以及美国全球陆面数据同化系统（The Global Land Data Assimilation System,GLDAS）驱动的Noah模式（GLDAS_Noah试验）模拟的土壤温度结果,从空间分布、季节、分区等角度进行了评估,实现了不同驱动数据相同陆面模式和相同驱动数据不同陆面模式的对比分析。结果表明: GLDAS_Noah、CLDAS_Noah和CLDAS_Noah-MP试验均能合理模拟出中国区域土壤温度空间分布,但在量级上有一定差异,主要表现在中国东北、新疆、青藏高原等积雪区。对于相同陆面模式不同驱动数据,均方根误差显示CLDAS_Noah试验在季节与分区上均优于GLDAS_Noah试验,间接表明CLDAS大气驱动数据优于GLDAS大气驱动数据,且大气驱动数据是提高土壤温度模拟精度的重要因素之一;对于相同驱动数据不同陆面模式,总体上CLDAS_Noah-MP试验棋拟效果优于CLDAS_Noah试验,其中CLDAS_Noah试验模拟的10和40 cm深度土壤温度在冬季积雪区误差明显大于CLDAS_Noah-MP试验,可能与Noah-MP模式改进了积雪方案有关,但10和40 cm深度下CLDAS_Noah-MP试验在东北、华北、青藏高原地区对春季土壤温度模拟误差明显大于CLDAS_Noah试验,可能与Noah-MP模式融雪方案有关。总之,本研究对于后续开展土壤温度多模式集成、土壤温度站点资料同化,最终研制中国区域高质量土壤温度数据集具有一定的参考意义。      

东亚夏季风降水年代际变异模态及其与太平洋年代际振荡的关系

利用全球陆地月平均降水资料、英国气象局哈德莱中心的月平均海表温度距平(SSTA)资料及NCEP/NCAR再分析大气环流资料,探讨东亚夏季风降水年代际变率及其与太平洋年代际振荡(PDO)的联系。研究指出:东亚夏季风降水年代际变异模态以及PDO均在1976年前后呈现显著的年代际转折,并且东亚夏季风降水与PDO在年代际尺度上具有较好的相关关系。PDO能够在对流层低层激发出与年代际东亚夏季风环流较为相似的大气环流异常特征,表明东亚夏季风环流的年代际变化可能受大气外强迫因子PDO在对流层低层的外源强迫作用影响,最终导致东亚夏季风降水发生年代际变化。     

Evaluation of a Photosynthesis-Based Canopy Resistance Formulation in the Noah Land-Surface Model

Accurately representing complex land-surface processes balancing complexity and realism remains one challenge that the weather modelling community is facing nowadays. In this study, a photosynthesis-based Gas-exchange Evapotranspiration Model (GEM) is integrated into the Noah land-surface model replacing the traditional Jarvis scheme for estimating the canopy resistance and transpiration. Using 18-month simulations from the High Resolution Land Data Assimilation System (HRLDAS), the impact of the photosynthesis-based approach on the simulated canopy resistance, surface heat fluxes, soil moisture, and soil temperature over different vegetation types is evaluated using data from the Atmospheric Radiation Measurement (ARM) site, Oklahoma Mesonet, 2002 International H₂O Project (IHOP_2002), and three Ameriflux sites. Incorporation of GEM into Noah improves the surface energy fluxes as well as the associated diurnal cycle of soil moisture and soil temperature during both wet and dry periods. An analysis of midday, average canopy resistance shows similar day-to-day trends in the model fields as seen in observed patterns. Bias and standard deviation analyses for soil temperature and surface fluxes show that GEM responds somewhat better than the Jarvis scheme, mainly because the Jarvis approach relies on a parametrised minimum canopy resistance and meteorological variables such as air temperature and incident radiation. The analyses suggest that adding a photosynthesis-based transpiration scheme such as GEM improves the ability of the land-data assimilation system to simulate evaporation and transpiration under a range of soil and vegetation conditions.     

陆面过程模型CoLM与区域气候模式RegCM3的耦合及初步评估

陆面过程通过影响陆面和大气之间物质（如,水分）和能量的交换影响气候, 其参数化方案对数值天气预报、全球及区域气候模拟有重要影响。本研究利用对生物物理、生物化学过程考虑更全面的陆面模式Common Land Model(CoLM) 替代区域气候模式RegCM3原有的陆面模式BATS, 发展了耦合区域气候模式C－RegCM3; 将其应用于东亚地区典型洪涝年份夏季气候模拟以进行评估, 结果表明新耦合的模式C－RegCM3能合理模拟大尺度环流场、近地表气温和降水的分布特征, 对西北半干旱地区降水模拟比RegCM3有所改进。通过利用区域气候模式C－RegCM3及RegCM3对地表能量和水文过程模拟结果的比较, 发现在半干旱、半湿润过渡区C－RegCM3模拟的潜热增大、感热减小; 模拟的地表吸收太阳辐射差异较明显的地区位于模式模拟的主要雨区; C-RegCM3在上述过渡区模拟的夏季地表土壤湿度比RegCM3偏干, 这与它在过渡区降水模拟偏少、蒸散发模拟偏大相对应, 体现了该模式在半干旱、半湿润过渡带模拟出比RegCM3更明显的局地土壤湿度－降水－蒸散发之间的正反馈作用。     

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.     

土壤湿度对卫星辐射率资料直接同化的影响

本研究利用WRF模式及其三维变分同化系统实现了对NOAA-16 AMSU-A微波资料的直接同化,针对2010年6月19日江西地区的一次强降水过程开展模拟与同化试验,并利用中国区域土壤湿度同化系统(CLSMDAS—China Land Soil Moisture Data Assimilation System)输出的土壤湿度值替换NCEP(National Centers for Environmental Prediction)资料中的土壤湿度,研究土壤湿度初值对辐射率资料直接同化中观测场与背景场偏差调整的影响。结果表明:采用CLSMDAS输出土壤湿度初值条件下模拟的亮温值与实际观测值更为接近,经过质量控制和偏差订正后更多的观测资料能够进入到同化系统中,说明改进的土壤湿度初值条件下观测算子的计算值得到正的调整,对低层地表通道的改进效果明显,尤其以50.3 GHz的窗区通道3的结果最为理想;针对此次强降水过程中24 h累积降水分布的模拟结果,CLSMDAS输出土壤湿度初值条件下同化AMSU-A资料,能够较为准确的把握整个雨带的走向、大雨以上级别降水的落区范围、降水中心落区及强度等。说明准确的土壤湿度初值能够改进卫星辐射率资料的同化结果,进而提高数值模式的模拟预报能力。     

Sensitivity study and validation of a land surface parameterization using the HAPEX-MOBILHY data set

A simple parameterization of land surface processes, amenable to the structure of a two-layer soil model, including a representation of the vegetation, has been designed for use in meteorological models. Prior to implementation in a mesoscale model, it is necessary to check the components and to verify the good working order of the parameterization as a whole. The aims of this paper then are: (i) evaluation and a sensitivity study of the various components of the model, specifying the needed accuracy for the parameters; (ii) micrometeorological validation of the model against the HAPEX-MOBILHY data set.First, we present the basic scheme. The focus is on the parameterization of surface resistance, and especially on its relationship with soil moisture.A sensitivity study is then performed through a set of one-dimensional simulations which allow a full interaction between the ground and the atmosphere. Above bare ground, it is shown that both soil texture and initial moisture greatly influence the outcome of the simulation. Latent heat flux ranges from that associated with potential evaporation through a switch-like behavior to that of dry soil. Next, the effects of transpiring vegetation canopies on the physical processes involved and the surface energy balance are examined. The sensitivity of the latent heat flux to changes in the soil and canopy parameters is emphazised; the major influence of the initial mean soil moisture and of the vegetation cover is pointed out. Finally, the evolution of the boundary layer in response to various surface conditions is studied.A validation of the land surface scheme is conducted through daily cycles during cloudless days. Simulated turbulent fluxes are successfully compared to micrometeorological measurements over a maize field at different growth stages. Over a pine forest, the correct simulation of the turbulent fluxes is obtained with an adequate parameterization of the surface resistance accounting for the atmospheric moisture deficit.