Coordinated Enhanced Observing Period Research Articles

The evaluation of AMSR-E soil moisture data in atmospheric modeling using a suitable time series iteration to derive land surface fluxes over the Tibetan Plateau.

In this study, the initial soil moisture in an atmospheric model was varied by assimilating AMSR-E (The Advanced Microwave Scanning Radiometer for EOS) products, and the results were compared with the default model scenario and in-situ data based on long-term CAMP/Tibet (Coordinated Enhanced Observing Period (CEOP) Asia-Australia Monsoon Project (CAMP) Tibet) observations. The differences between the obtained results (i.e., the new simulation, default model configuration and in-situ data) showed an apparent inconsistency in the model-simulated land surface heat fluxes. The results showed that the soil moisture was sensitive to the specific model simulation. To evaluate and verify the model stability, a long-term modeling study with AMSR-E soil moisture data assimilation was performed. Based on test simulations, AMSR-E data were assimilated into an atmospheric model for July and August 2007. The results showed that the land surface fluxes agreed well with both the in-situ data and the results of the default model configuration. Assimilating the AMSR-E SM products was important for determining the land surface heat fluxes in the WRF model. All the assimilation work substantially improved the modeling of land surface heat fluxes. Land surface heat fluxes are related to atmospheric interactions. Therefore, land surface heat fluxes are very important land surface parameters during these processes. Therefore, the simulation can be used to retrieve land surface heat fluxes from an atmospheric model. It is important to study the surface heating sources that are related to both the water and energy cycles over the Tibetan Plateau.

Estimation of Land Surface Heat Fluxes Based on Landsat 7 ETM+ Data and Field Measurements over the Northern Tibetan Plateau

Land surface heat fluxes consist of the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux. The estimation of these fluxes is essential to the study of energy transfer in land–atmosphere systems. In this paper, Landsat 7 ETM+ SLC-on data were applied to estimate the land surface heat fluxes on the northern Tibetan Plateau using the SEBS (surface energy balance system) model, in combination with the calculation of field measurements at CAMP/Tibet (Coordinated Enhanced Observing Period (CEOP) Asia–Australia Monsoon Project on the Tibetan Plateau) automatic weather stations based on the combinatory method (CM) for comparison. The root mean square errors between the satellite estimations and the CM calculations for the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux were 49.2 W/m2, 46.3 W/m2, 68.2 W/m2, and 54.9 W/m2, respectively. The results reveal that land surface heat fluxes all present significant seasonal variability. Apart from the sensible heat flux, the satellite-estimated net radiation flux, soil heat flux, and latent heat flux exhibited a trend of summer > spring > autumn > winter. In summer, spring, autumn, and winter, respectively, the median values of the net radiation flux (631.8 W/m2, 583.0 W/m2, 404.4 W/m2, 314.3 W/m2), soil heat flux (40.9 W/m2, 37.9 W/m2, 26.1 W/m2, 20.5 W/m2), sensible heat flux (252.7 W/m2, 219.5 W/m2, 221.4 W/m2, 204.8 W/m2), and latent heat flux (320.1 W/m2, 298.3 W/m2, 142.3 W/m2, 75.5 W/m2) exhibited distinct seasonal diversity. From November to April, the in situ sensible heat flux is higher than the latent heat flux; the opposite is true between June and September, leaving May and October as transitional months. For water bodies, alpine meadows and other main underlying surface types, sensible and latent heat flux generally present contrasting and complementary spatial distributions. Due to the 15–60 m resolution of the Landsat 7 ETM+ data, the distribution of land surface heat fluxes can be used as an indicator of complex underlying surface types over the northern Tibetan Plateau.

Estimation of actual evapotranspiration in the Nagqu river basin of the Tibetan Plateau

As a critical component of the energy and water cycle, terrestrial actual evapotranspiration (ET) can be influenced by many factors. This study was mainly devoted to providing accurate and continuous estimations of actual ET for the Tibetan Plateau (TP) and analyzing the effects of its impact factors. In this study, summer observational data from the Coordinated Enhanced Observing Period (CEOP) Asia–Australia Monsoon Project (CAMP) on the Tibetan Plateau (CAMP/Tibet) for 2003 to 2004 was selected to determine actual ET and investigate its relationship with energy, hydrological, and dynamical parameters. Multiple-layer air temperature, relative humidity, net radiation flux, wind speed, precipitation, and soil moisture were used to estimate actual ET. The regression model simulation results were validated with independent data retrieved using the combinatory method. The results suggested that significant correlations exist between actual ET and hydro-meteorological parameters in the surface layer of the Nagqu river basin, among which the most important factors are energy-related elements (net radiation flux and air temperature). The results also suggested that how ET is eventually affected by precipitation and two-layer wind speed difference depends on whether their positive or negative feedback processes have a more important role. The multivariate linear regression method provided reliable estimations of actual ET; thus, 6-parameter simplified schemes and 14-parameter regular schemes were established.

Combining MODIS, AVHRR and in situ data for evapotranspiration estimation over heterogeneous landscape of the Tibetan Plateau

Abstract. In this study, a parameterization method based on MODIS (Moderate Resolution Imaging Spectroradiometer) data, AVHRR (Advanced Very High-Resolution Radiometer) data and in situ data is introduced and tested for estimating the regional evaporative fraction Λ over a heterogeneous landscape. As a case study, the algorithm was applied to the Tibetan Plateau (TP) area. Eight MODIS data images (17 January, 14 April, 23 July and 16 October in 2003; 30 January, 15 April, 1 August and 25 October in 2007) and four AVHRR data images (17 January, 14 April, 23 July and 16 October in 2003) were used in this study to compare winter, spring, summer and autumn values and for annual variation analysis. The results were validated using the "ground truth" measured at Tibetan Observation and Research Platform (TORP) and the CAMP/Tibet (CEOP (Coordinated Enhanced Observing Period) Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau) meteorological stations. The results show that the estimated evaporative fraction Λ in the four different seasons over the TP is in clear accordance with the land surface status. The Λ fractions show a wide range due to the strongly contrasting surface features found on the TP. Also, the estimated Λ values are in good agreement with "ground truth" measurements, and their absolute percentage difference (APD) is less than 10.0% at the validation sites. The AVHRR data were also in agreement with the MODIS data, with the latter usually displaying a higher level of accuracy. It was therefore concluded that the proposed algorithm was successful in retrieving the evaporative fraction Λ using MODIS, AVHRR and in situ data over the TP. MODIS data are the most accurate and should be used widely in evapotranspiration (ET) research in this region.

Using MODIS and AVHRR data to determine regional surface heating field and heat flux distributions over the heterogeneous landscape of the Tibetan Plateau

In this study, a parameterization methodology based on Advanced Very High-Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and in situ data is proposed and tested for deriving the regional surface heating field, sensible heat flux, and latent heat flux over a heterogeneous landscape. In this case study, this method is applied to the whole Tibetan Plateau (TP) area. Four sets of AVHRR data and four sets of MODIS data (collected on 17 January 2003, 14 April 2003, 23 July 2003, and 16 October 2003) were used in this study to make comparisons between winter, spring, summer, and autumn values. The satellite-derived results were also validated using the “ground truth” as measured in the stations of CAMP/Tibet (Coordinated Enhanced Observing Period (CEOP) and Asia–Australia Monsoon Project on the Tibetan Plateau). The results show that the surface heating field, sensible heat flux, and latent heat flux in the four seasons across the TP are in close accordance with its land surface status. These parameters range widely due to the strongly contrasting surface features found within the TP region. Also, the estimated surface heating field, sensible heat flux, and latent heat flux all agree with the ground truth data, and usually, the absolute percentage difference between the two sets of data is less than 10 % at the validation stations. The AVHRR results were also in agreement with the MODIS data, with the latter usually displaying a higher level of accuracy. We have thus concluded that the proposed method was successful in retrieving surface heating field, sensible heat flux, and latent heat flux values using AVHRR, MODIS, and in situ data over the heterogeneous land surface of the TP. Shortcomings and possible further improvements in the method are also discussed.

Evaluating CEOP model performance in semi-arid region of China

This study systematically evaluates simulations of near-surface temperature and precipitation using the station observations collected in the semi-arid region of China during the Coordinated Enhanced Observing Period (CEOP) from October 2002 to December 2004 (EOP3 and EOP4). The outputs being evaluated are from eight general circulation models (GCMs) archived by the Coordinated Energy and Water Cycle Observations Project (CEOP), as well as a multi-model ensemble based on these eight models. We find that the multi-model ensemble has a better performance than most of the individual models. Our results show that all individual models and the Model Analysis Comparison (MAC) ensemble mean perform much better when simulating regionally averaged temperature than precipitation. For most models, a systematically low bias is identified in the regionally averaged simulated temperatures, while a high bias exists in the simulated precipitation except in summer. For the simulated temperatures, the lowest and largest rRMSE are found in JMA and BMRC, respectively. Furthermore, temperature is always overestimated when it is between − 18 and − 10 °C, while the temperature is underestimated when it is greater than 6 °C; the best performance lies between − 10 and 2 °C for all the models except BMRC. For the simulated precipitation, excessive rainfall is reproduced at all intervals except in ECPC-SFM, and the largest deviation is identified at the interval of 2–5 mm with a bias of 18.3%. With respect to sub-regions, the simulated temperatures are better in eastern China, but the simulated precipitation is better in the transition zone from the semi-arid region to the arid region. However, the simulation bias increases west of 100°E, which may be associated with the complex and steep topography there. We want to stress that the MAC ensemble mean is superior to any individual models.

Modeling the Spatial Distribution of Snow Cover in the Dudhkoshi Region of the Nepal Himalayas

Abstract In this study, a distributed biosphere hydrological model with three-layer energy-balance snow physics [an improved version of the Water and Energy Budget–based Distributed Hydrological Model (WEB-DHM-S)] is applied to the Dudhkoshi region of the eastern Nepal Himalayas to estimate the spatial distribution of snow cover. Simulations are performed at hourly time steps and 1-km spatial resolution for the 2002/03 snow season during the Coordinated Enhanced Observing Period (CEOP) third Enhanced Observing Period (EOP-3). Point evaluations (snow depth and upward short- and longwave radiation) at Pyramid (a station of the CEOP Himalayan reference site) confirm the vertical-process representations of WEB-DHM-S in this region. The simulated spatial distribution of snow cover is evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day maximum snow-cover extent (MOD10A2), demonstrating the model’s capability to accurately capture the spatiotemporal variations in snow cover across the study area. The qualitative pixel-to-pixel comparisons for the snow-free and snow-covered grids reveal that the simulations agree well with the MODIS data to an accuracy of 90%. Simulated nighttime land surface temperatures (LST) are comparable to the MODIS LST (MOD11A2) with mean absolute error of 2.42°C and mean relative error of 0.77°C during the study period. The effects of uncertainty in air temperature lapse rate, initial snow depth, and snow albedo on the snow-cover area (SCA) and LST simulations are determined through sensitivity runs. In addition, it is found that ignoring the spatial variability of remotely sensed cloud coverage greatly increases bias in the LST and SCA simulations. To the authors’ knowledge, this work is the first to adopt a distributed hydrological model with a physically based multilayer snow module to estimate the spatial distribution of snow cover in the Himalayan region.

A China-Japan Cooperative JICA Atmospheric Observing Network over the Tibetan Plateau (JICA/Tibet Project): An Overviews

A China-Japan Cooperative JICA Atmospheric Observing Network over the Tibetan Plateau (JICA/Tibet Project): An Overviews

The coupling of cloud base height and surface fluxes: a transferability intercomparison

This paper presents an evaluation of the simulated coupling between cloud base height (CBH) and surface fluxes over selected Coordinated Enhanced Observing Period (CEOP) reference stations by five regional climate models as part of a transferability intercomparison experiment. The model results are compared with station data obtained during the first phase of the CEOP measuring campaigns. The models gave a credible simulation of both diurnal and seasonal cycles of cloud base height and surface variables over the stations. However, the models exhibited some difficulty in reproducing the diurnal and seasonal temperatures over the tropical stations. The study used principal component analysis to show that three factors account for most of the variability in the observed and simulated data and to investigate the coupling between cloud base height and surface fluxes in the data. In the observations, CBH is well coupled with the surface fluxes over Cabauw, Bondville, Lamont, and Berms, but coupled only with temperature over Lindenberg and Tongyu. All models but GEMLAM simulate substantial coupling between CBH and surface fluxes at all stations; GEMLAM does not couple CBH with surface fluxes, but with surface temperature and specific humidity.

A coupled Land Atmosphere Radiative-Transfer Model (LA-RTM) for multi-frequency passive microwave remote sensing: development and application over Wakasa Bay and the Tibetan Plateau

Multi-frequency passive microwave sensors herald a new dawn for combined land and atmosphere observations. Past efforts to utilize microwave remote sensing of atmosphere and land surface have proceeded by treating these two areas in a parallel fashion. In this research, a unified approach is presented that can be used to improve both quantitative and qualitative understanding of land and atmosphere constituents. A coupled Land Atmosphere Radiative-Transfer Model (LA-RTM) that can be used as a forward model in retrieval algorithms, or as an observation operator in data-assimilation schemes is developed. This model is validated using data collected during the 2003 Advanced Microwave Scanning Radiometer on board the Earth Observing Satellite (AMSR/AMSR-E) validation experiment over Wakasa Bay in Japan and the Coordinated Enhanced Observing Period (CEOP) dataset for the Tibetan Plateau collected in April and August 2004. These datasets comprise satellite (AMSR-R) observations, ground-based microwave radiometers (GBMRs) and radiosonde atmosphere soundings. In both sites, good agreement between simulated and observed brightness temperatures is demonstrated. To facilitate fast retrievals, a retrieval scheme is proposed that uses LA-RTM as a forward model to generate a look-up table (LUT) for varying land-surface conditions. This LUT is used to retrieve soil-moisture and surface-roughness conditions for the target site. Using this scheme, retrieved soil moisture at in situ stations was shown to have fairly good agreement with observations.

Evaluating CEOP model performance with the observational data from Tongyu reference site, semi-arid region of China

Using data archived in the Coordinated Enhanced Observing Period (CEOP) project, comparisons between field observations undertaken at Tongyu CEOP reference site in China and model output from year 2003 to 2004 have been implemented, and in particular, the time series and diurnal cycles of precipitation, near-surface temperature, air temperature, and latent and sensible heat fluxes are presented. The results show that the ability of the model simulations on the temperatures, such as air temperature and the surface temperature, is satisfactory compared with the simulations on the land surface heat fluxes and the precipitation at Tongyu site. In addition, the multi-model ensemble exhibits better results over all items in comparison with the observations. The differences of the precipitation at the interannual and the seasonal time scales between the model results and observations indicate that some of the models are able to reproduce the larger amount of precipitation in 2003 than that in 2004, which is consistent with the trend of the observations at Tongyu site even though the mean square errors of models output calculated from daily precipitation during year 2003 and 2004 are even greater than the daily amount of the precipitation. The poor skill in the quantitative simulation of the precipitation indicates that the deficiency of the models in simulating the surface heat fluxes may be closely related to the biases of the precipitation simulations. In terms of the seasonal time series of the precipitation, there is an increase during summer, accompanied by the same increased trend of the latent heat flux and the decreased trend of the sensible heat flux from the insitu observations.

Estimation of land surface temperature over the Tibetan Plateau using AVHRR and MODIS data

Estimation of large-scale land surface temperature from satellite images is of great importance for the study of climate change. This is especially true for the most challenging areas, such as the Tibetan Plateau (TP). In this paper, two split window algorithms (SWAs), one for the NOAA’s Advanced Very High Resolution Radiometer (AVHRR), and the other for the Moderate Resolution Imaging Spectroradiometer (MODIS), were applied to retrieve land surface temperature (LST) over the TP simultaneously. AVHRR and MODIS data from 17 January, 14 April, 23 July, and 16 October 2003 were selected as the cases for winter, spring, summer, and autumn, respectively. Firstly, two key parameters (emissivity and water vapor content) were calculated at the pixel scale. Then, the derived LST was compared with in situ measurements from the Coordinated Enhanced Observing Period (CEOP) Asia-Australia Monsoon Project (CAMP) on the TP (CAMP/Tibet) area. They were in good accordance with each other, with an average percentage error (PE) of 10.5% for AVHRR data and 8.3% for MODIS data, meaning the adopted SWAs were applicable in the TP area. The derived LST also showed a wide range and a clear seasonal difference. The results from AVHRR were also in agreement with MODIS, with the latter usually displaying a higher level of accuracy.

Modeling of surface flux in Tongyu using the Simple Biosphere Model 2 (SiB2)

The modeling ability of a stand-alone version of the Simple Biosphere Model 2 (SiB2) was tested mainly through diagnosing the simulated latent heat (LE), sensible heat (H), CO2 flux, and air temperature at the Tongyu field observation station (44°25′N, 122°52′E, 184 m elevation) of Coordinated Enhanced Observing Period (CEOP), where the land cover is cropland and grassland. In the whole year of 2003, the canopy height and the leaf area index was variable. During non-growth period, the surface would become bare, while during the growth period, the canopy height could reach 2.0 m high over cropland and 0.8 m high over grassland, respectively, and max leaf area index could reach 4.2 and 2.4, respectively. The model was initialized with measurement and driven by half-hourly atmospheric observations. The simulation values for 2003 were compared against measurements. Results show that the model is of a good ability of simulating the hourly latent heat (LE), sensible heat (H), CO2 flux and temperature during the growth period. Moreover, the daily LE, H and CO2 flux simulated by SiB2 could reflect their yearly change reasonably. However, the model may overestimate the H generally.

Parameterization of heat fluxes at heterogeneous surfaces by integrating satellite measurements with surface layer and atmospheric boundary layer observations

The regional heat flux exchange between heterogeneous landscapes and the nearby surface layer (SL) is a key issue in the study of land-atmosphere interactions over arid areas such as the Heihe River basin in northwestern China and in high elevation areas such as the Tibetan Plateau. Based on analysis of the land surface heterogeneity and its effects on the overlying air flow, the use of SL observations, atmospheric boundary layer (ABL) observations, and satellite remote sensing (RS) measurements along with three parameterization methodologies (here, termed as the RS, tile, and blending approaches) have been proposed to estimate the surface heat flux densities over heterogeneous landscapes. The tile and blending approaches have also been implemented during HEIhe basin Field Experiment (HEIFE), the Coordinated Enhanced Observing Period (CEOP) Asia-Australia Monsoon Project on the Tibetan Plateau (CAMP/Tibet), the Arid Environment Comprehensive Monitoring Plan’ 95 (AECMP′95), and the DunHuang Experiment (DHEX). The results showed that these two proposed parameterization methodologies can be accurately used over heterogeneous land surfaces.

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 simu-lations of soil surface temperature,net radiation flux,and sensible heat flux against observed values with the RMSE of 1.54°C,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 larger 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.

A Multimodel Analysis for the Coordinated Enhanced Observing Period (CEOP)

Abstract A collection of eight operational global analyses over a 27-month period have been processed to common data structures to facilitate comparisons among the analyses and global observational datasets. The present study evaluated the global precipitation, outgoing longwave radiation (OLR) at the top of the atmosphere, and basin-scale precipitation over the United States. In addition, a multimodel ensemble was created from a linear average of the available data, as close to the analysis time as each system permitted. The results show that the monthly global precipitation and OLR from the multimodel ensemble compares generally better to the observations than any single analysis. Likewise, the daily precipitation from the ensemble exhibits better statistical comparison (in space and time) to gauge observations over the Mississippi River basin. However, the comparisons have seasonality, when the members of the ensemble exhibit generally more skill, during winter. There is notably higher skill of the summertime basin precipitation by the ensemble. Using the global precipitation and OLR, the sensitivity was tested to selectively choose the members with the best statistical comparisons to the reference data. Only small improvements in the statistics were found when comparing a selective ensemble to the full ensemble. Additionally, terms of the global energy budget were compared among the ensemble and to other estimates. The ensemble data and the variance of the ensemble should make a useful point of comparison for the development of model and assimilation components of global analyses.

Estimating surface fluxes over the north Tibetan Plateau area with ASTER imagery

Abstract. Surface fluxes are important boundary conditions for climatological modeling and Asian monsoon system. The recent availability of high-resolution, multi-band imagery from the ASTER (Advanced Space-borne Thermal Emission and Reflection radiometer) sensor has enabled us to estimate surface fluxes to bridge the gap between local scale flux measurements using micrometeorological instruments and regional scale land-atmosphere exchanges of water and heat fluxes that are fundamental for the understanding of the water cycle in the Asian monsoon system. A parameterization method based on ASTER data and field observations has been proposed and tested for deriving surface albedo, surface temperature, Normalized Difference Vegetation Index (NDVI), Modified Soil Adjusted Vegetation Index (MSAVI), vegetation coverage, Leaf Area Index (LAI), net radiation flux, soil heat flux, sensible heat flux and latent heat flux over heterogeneous land surface in this paper. As a case study, the methodology was applied to the experimental area of the Coordinated Enhanced Observing Period (CEOP) Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau (CAMP/Tibet), located at the north Tibetan Plateau. The ASTER data of 24 July 2001, 29 November 2001 and 12 March 2002 was used in this paper for the case of summer, winter and spring. To validate the proposed methodology, the ground-measured surface variables (surface albedo and surface temperature) and land surface heat fluxes (net radiation flux, soil heat flux, sensible heat flux and latent heat flux) were compared to the ASTER derived values. The results show that the derived surface variables and land surface heat fluxes in three different months over the study area are in good accordance with the land surface status. Also, the estimated land surface variables and land surface heat fluxes are in good accordance with ground measurements, and all their absolute percentage difference (APD) is less than 10% in the validation sites. It is therefore concluded that the proposed methodology is successful for the retrieval of land surface variables and land surface heat fluxes using the ASTER data and filed observation over the study area.

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.

Use of a land surface model to evaluate the observed soil moisture of grassland at the Tongyu reference site

A land surface model driven by the continuous three-year observed meteorological data with a time interval of 30 minutes at the Tongyu station, a reference site of the Coordinated Enhanced Observing Period (CEOP), was used to evaluate the observation bias of soil moisture (SM) data and analyze the variation of SM at different time scales. The saline-alkaline soil of the grassland at the Tongyu site makes the measured SM too high, especially in boreal summer of 2003–05. The simulated annual mean SM has the lowest value in 2004 and its three-year variation corresponds to the change of precipitation, whereas the observation shows the increasing trend from 2003 to 2005. Compared to the variation range between −60% and 40% for the anomaly percentage of the simulated daily mean SM during May–October of 2004, the measured data show the higher values more than 40%. The magnitude of the variation trend of the observed daily mean SM in 2003 and 2005 is generally consistent with the simulation. The largest deficiency for the soil moisture observation of the grassland is the overestimated value in the drought year with less precipitation. The simulated monthly mean SM has the lowest value in March due to the large contribution of evaporation relative to precipitation and this phenomenon can not be reproduced in the observation.

An Advanced Quality Control System for the CEOP/CAMP In-Situ Data Management

The Coordinated Enhanced Observing Period (CEOP) was proposed in 1997 as an initial step for establishing an integrated observation system for the global water cycle. The Enhanced Observing Period was conducted from October 2002 to December 2004, with satellite data, in-situ data, and model output data collected and available for integrated analysis. Under the framework of CEOP, the CEOP Asia-Australia Monsoon Project (CAMP) was organized and provided the in-situ dataset in the Asian region. CAMP included 13 different reference sites in the Asian monsoon region during Phase 1 (October 2002 to December 2004). These reference sites were operated by individual researchers for their own research objectives. Therefore, the various sites' data had important differences in observational elements, data formats, recording intervals, etc. This usually requires substantial manual data processing to use these data for scientific research which consumes a great deal of researcher time and energy. To reduce the time and effort for data quality checking and format conversion, the CAMP Data Center (CDC) established a Web-based quality control (QC) system. This paper introduces this in-situ data management and quality control system for the Asian region data under the framework of CEOP.