First six months quality assessment of HY-2A SCAT wind products using in situ measurements

The first Chinese microwave ocean environment satellite HY-2A, carrying a Ku-band scatteromenter （SCAT）, was successfully launched in August 2011. The first quality assessment of HY-2A SCAT wind products is presented through the comparison of the first 6 months operationally released SCAT products with in situ data. The in situ winds from the National Data Buoy Center （NDBC） buoys, R/V Polarstern, Aurora Australis, Roger Revelle and PY30-1 oil platform, were converted to the 10 m equivalent neutral winds. The temporal and spatial differences between the HY-2A SCAT and the in situ observations were limited to less than 5 min and 12.5 km. For HY-2A SCAT wind speed products, the comparison and analysis using the NDBC buoys yield a bias of-0.49 m/s, a root mean square error （RMSE） of 1.3 m/s and an increase negative bias with increasing wind speed observation above 3 m/s. Although less accurate of HY-2A SCAT wind direction at low winds, the RMSE of 19.19° with a bias of 0.92° is found for wind speeds higher than 3 m/s. These results are found consistent with those from R/Vs and oil platform comparisons. Moreover, the NDBC buoy comparison results also suggest that the accuracy of HY-2A SCAT winds is consistent over the first half year of 2012. The encouraging assessment results over the first 6 months show that wind products from HY-2A SCAT will be useful for scientific community.     

台湾海峡海表面温度的遥感反演及精度检验

海表面温度(SST)是海洋-大气系统中一个十分关键的物理量。SST为海洋学课题的研究提供了一种直观的指示量[1],在海洋捕捞中SST是寻找中心渔场的指标之一,可为渔业部门提供鱼类的回游路线和渔场的位置信息[2]。SST制约着海面和大气的热量、动量和水汽交换,是研究大气环流和气候变化[3]甚至台风移动路径[4]等气象学课题的一个重要因子。因此,SST在海洋学和气象学研究中占有非常重要的地位,此外SST对海洋运输、海洋污染、海上油气资源开发、海滨核电站建设等方面的影响近年来也倍受关注。     

空间变异对海洋叶绿素a质量浓度遥感产品精度验证的影响

海洋叶绿素a质量浓度遥感产品是海洋初级生产力与海洋生态系统固碳能力研究的重要数据源,为了保证数据的可靠性,对遥感产品进行精度验证以及验证误差的成因分析尤为重要.遥感产品的验证过程中,由于空间变异的存在,使得遥感像元尺度内的实测数据具有不同的离散程度和统计分布特征,并由此产生了不同的误差统计结果.本文选择MODIS-Aq...     

不同插值方法在海域气象参数估算中的可靠性评价

海域条件下的气象观测具有数据稀少、变化大且观测站点分布不均的特点,其插值精度受插值方法影响较大。首先对常规插值方法进行理论分析,进而选取了反距离加权法、克里金法和样条函数法三种插值方法进行了插值实验和精度分析。根据渤海湾某区域的气象历史数据,采用不同方法绘制了温度、压强和湿度的插值平面图,并基于交叉验证的方式对各插值方法进行了对比,给出了不同方法的插值估算可靠性评价。结果表明:温度、压强和湿度的插值精度均是基于反距离加权法的插值结果最优(MAE_(温度)=2.42,RMSE_(温度)=1.92,MAE_(压强)=2.05,RMSE_(压强)=1.30,MAE_(湿度)=11.394, RMSE_(压强)=6.43),同时基于反距离加权法的图形绘制可视化效果也要优于其他两种方法。研究结果可为海域气象参数估算提供理论和实践依据。     

Global Statistical Assessment and Cross-Calibration with Jason-2 for Reprocessed HY-2 A Altimeter Data

HY-2 A (Haiyang-2 A) satellite was launched on August 16, 2011 and radar altimeter is one of its main payloads. We reprocessed two years of HY-2 A altimeter sensor geophysical dataset records (SGDR) data. This paper presents the main results in terms of reprocessed HY-2 A altimeter data quality: verification of data availability and validity, monitoring several relevant altimeter parameters, and assessment of the HY-2 A altimeter system performances. A cross-calibration analysis of reprocessed HY-2 A altimeter data with Jason-2 was conducted. The reprocessed HY-2 A altimeter data show good quality and have a low level of noise with respect to Jason-2. The same geophysical correction methods were used to calculate the sea surface height (SSH) for the two missions. The mean standard deviations of the crossover differences for HY-2 A and Jason-2 are 5.24 cm and 5.34 cm, respectively. The mean standard deviation of the crossover differences between HY-2 A and Jason-2 is 5.37 cm. These show that HY-2 A can provide SSH measurements at almost the same level of accuracy as Jason-2. The relative SSH bias between HY-2 A and Jason-2 due to the Ultra Stable Oscillator (USO) drift is obviously observed, and it can affect the calculation of mean sea level and should be further studied and corrected.     

A New Retracking Technique for Brown Peaky Altimetric Waveforms

A new Brown-Peaky (BP) retracker has been developed for peaky waveforms that usually appear within ～10 km to the coastline. The main feature of the BP is that it fits peaky waveforms using the Brown model without introducing a peak function. The retracking strategy first detects the peak location and width of a waveform using an adaptive peak detection method, and then estimates retracking parameters using a weighted least squares (WLS) estimator. The WLS assigns a downsized weight to corrupted waveform gates, but an equal weight to other normal waveform gates. The BP retracker has been applied to 4-year Jason-1 waveform (2002–2006) in two Australian coastal zones. The results retracked by BP, MLE4 and ALES retrackers have been validated against tide-gauge observations located at Burnie, Lorne and Broome. The comparison results show that three retrackers have similar performance over open oceans with the correlation coefficient (～0.7) and RMSE (～13 cm) between altimetric and tide-gauge sea levels for distance >7 km offshore. The main improvement of BP retracker occurs for distance ≤7 km to the coastline, where validation results indicate that data retracked by BP are more accurate (15–21 cm) than those by ALES (16–24 cm) and MLE4 (19–37 cm).     

北斗混合星座分层约束下的精密定轨方法

针对北斗导航卫星系统首创的GEO+IGSO+MEO混合星座设计,本文研究了根据不同星座,采取不同约束条件和数据处理策略的北斗卫星精密定轨方法,提出了一种针对北斗系统混合星座的分层约束精密定轨方案.该方案首先将北斗卫星分为非GEO(IGSO/MEO)和GEO两部分进行解算,利用GPS解算的公共参数对北斗IGSO/MEO精...     

Validation of a soil water balance model using soil water content and pressure head data

The validation of soil water balance models and the evaluation of the quality of the model predictions at field‐scale require time‐series of in situ measured model outputs. In our study, we have validated such a model using a 6‐year period with time‐series of automatically recorded, daily volumetric soil water contents measured with the time‐domain reflectometry with intelligent microelements (TRIME) method and daily pressure heads measured with tensiometers. The comparisons of simulated with measured soil water contents and pressure heads were analysed using the modelling efficiency index (IA) and the square root of the mean square error (RMSE) in order to evaluate the prediction quality of the model. In our study, IA and RMSE, obtained either from the comparison of simulated with measured soil water contents or the comparison of calculated with observed pressure heads, in some cases lead to different results regarding the evaluation of the simulation quality of the soil water balance model. For example, a good fit between simulated and observed soil water contents does not necessarily result in a comparably good fit between the corresponding calculated and measured pressure heads. Therefore, a combined use of both measurement techniques, which takes into account their respective advantages and disadvantages, gives a more complete overview on the simulation quality of the soil water balance model than the single use of one of those techniques. Copyright © 2004 John Wiley & Sons, Ltd.     

Identifying linear and non-linear behaviour in reduced complexity modelling output using surrogate data methods

Validation of model output is an important issue in the environmental sciences. This is particularly the case for reduced complexity modelling approaches where verification of the underlying equations is often problematic. Hence, methods that go beyond validation based on average values or the histogram of model output, are clearly advantageous. In this paper we show that a validation method based on the serial properties of time–space data, and developed in geomorphology, is a useful alternative but is nevertheless still insensitive to certain asymmetric characteristics of the signal. Hence, use of this method for validation may be enhanced by the adoption of an accompanying test for asymmetry in the model output.     

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, Kain-Fritsch and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, root-mean-squares error (RMSE), and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation. Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the CPSs for different synoptic situations.