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1.
利用时空匹配的15个海岛站的探空资料对WindSat 2007—2015年的海洋大气可降水量产品(total precipitable water,TPW)进行了检验,并分析了造成两者差异的原因。结果表明:WindSat反演的海洋大气可降水量产品与探空比对的一致性较好,两者平均偏差为-0.43mm,均方根误差为3.14mm,标准偏差为3.11mm,相关系数达到了0.98;WindSat在中高纬度地区反演效果较好,均方根误差在各个站点均小于3mm;在低纬度地区WindSat反演精度较差,均方根误差大于5mm。低风速对WindSat可降水反演精度影响较大;海面温度和云中液态水含量与大气可降水量产品之间无明显相关关系;WindSat反演精度随纬度降低下降明显;利用白天探空释放所得到的水汽数据存在干性偏差。 相似文献
2.
海表温度产品是研究全球海洋大气系统的重要数据源,在海洋相关领域的研究和应用方面具有重要价值。以西北太平洋海域为研究区域,本文对2013年和2014年3个微波辐射计海表温度产品(AMSR-2,TMI和WindSat)的产品特性和Argo浮标进行了真实性检验,并对3个传感器数据进行了交叉比对分析,具体涉及海表温度分布、温度梯度分布、观测点分布、匹配点分布、平均偏差分布、均方根误差分布、统计分析结果的逐月演变和海表温度误差棒分析。结果表明,3个微波辐射计在空间尺度上都能比较一致地反映西北太平洋海域的海表温度变化趋势。但遥感数据与浮标数据却存在季节性变化和昼夜差异,其中冬季微波数据与浮标数据的平均偏差和均方根误差较小,降轨数据与浮标数据的结果更接近。AMSR-2的海表温度数据质量比TMI和WindSat的海表温度数据更接近Argo数据。相比于WindSat和TMI,AMSR-2和TMI的海表温度数据质量更为接近,但是由于受到近岸陆地信号干扰,AMSR-2和TMI离岸100 km以内海域的数据应当慎用。 相似文献
3.
2010-2018年北极夏季中国北极科学考察航行期间被动微波遥感海冰密集度与船基目视观测资料的比较 总被引：2，自引：0，他引：2
为了更有效地将卫星数据应用于北极航行导航，被动微波（PM）产品的海冰密集度（SIC）与从中国北极科学考察中收集到的船基目视观测（OBS）资料进行了比较。在2010、2012、2014、2016和2018年的北极夏季总共收集了3667组目测数据。PM SIC取自基于SSMIS传感器的NASA-Team（NT）、Bootstrap（BT）以及Climate Data Record（CDR）算法和基于AMSR-E/AMSR-2传感器的BT、enhanced NT（NT2）以及ARTIST Sea Ice（ASI）算法。使用PM SIC的日算术平均值和OBS SIC的日加权平均值进行比较。比较了PM SIC和OBS SIC之间的相关系数，偏差和均方根偏差，包括总体趋势以及在轻度/普通/严重冰况下的情况。使用OBS数据，浮冰尺寸和冰厚对不同PM产品SIC反演的影响可以通过计算浮冰尺寸编码和冰厚的日加权平均值来评估。我们的结果显示相关系数的范围为0.89（AMSR-E/AMSR-2 NT2）到0.95（SSMIS NT），偏差的范围为-3.96%（SSMIS NT）到12.05%（AMSR-E/AMSR-2），均方根偏差的范围为10.81%（SSMIS NT）到20.15%（AMSR-E/AMSR-2 NT2）。浮冰尺寸对PM产品的SIC反演有显著的影响，大多数PM产品倾向于在小浮冰尺寸情况下低估SIC，而在大浮冰尺寸情况下高估SIC。超过30 cm的冰厚对于PM产品的SIC反演没有明显影响。总体来看，在北极夏季，SSMIS NT SIC与OBS SIC之间有着最好的一致性，而AMSR-E/AMSR-2 NT2 SIC与OBS SIC的一致性最差。 相似文献
4.
国内外对海上阵风的研究并不多,且大多集中在阵风预报和应用研究方面,对于海洋阵风数据的获取技术未见文献系统论述。本文利用HY-2B卫星雷达高度计观测的后向散射系数,结合校正微波辐射计观测的亮度温度信息,提出联合反演阵风风速的方法。两个遥感载荷联合反演得到的阵风风速与2019–2021年美国国家浮标数据中心（NDBC）浮标数据进行真实性检验,结果显示:阵风风速均方根误差（RMSE）为0.98 m/s,相关系数为0.82;基于本方法利用国外同类卫星Jason-3得到的阵风风速与2016–2018年NDBC浮标数据的RMSE为0.96 m/s,相关系数为0.88。本文在HY-2B卫星雷达高度计海面风速观测的基础上,纳入同一卫星平台校正微波辐射计的同步观测信息联合实现了海面阵风的观测,数据的比对结果证明文中方法具有较高的观测精度。同时,该方法对于具有相同观测体制的国内外卫星也适用。 相似文献
5.
本研究利用国际在轨SSMIS、WindSat、AMSR-E、ASMR2和国产HY-2A微波辐射计多源遥感大气柱水汽含量观测数据,基于最优插值算法,生成了2003－2015年的全球海洋每日0.25°高分辨率大气柱水汽含量多源遥感融合产品,以及2012－2015年未使用HY-2A微波辐射计数据的全球海洋每日0.25°遥感融合产品。利用无线电探空仪水汽含量观测数据,对生成的全部全球海洋大气柱水汽含量融合产品进行精度检验,结果表明,总体上,13年间均方根误差和标准差优于3 mm,平均偏差优于0.6 mm,平均绝对偏差优于2 mm,相关系数优于0.98;使用HY-2A微波辐射计数据产品会使融合结果的精度出现微小的降低;AMSR2和HY-2A微波辐射计数据的联合使用对于替代AMSR-E数据具有积极意义。 相似文献
6.
通过卫星遥感获取的海表温度（SST）产品已经成为海洋和大气研究中的重要数据源，我国海洋水色遥感卫星（HY1C和HY1D）的海洋水色水温扫描仪（COCTS）具有两个热红外通道，可反演全球SST遥感产品。对比Terra和Aqua卫星的中分辨率成像光谱仪（MODIS）的SST产品，分析COCTS海表温度产品对MODIS相应产品的可替代性。比较了两种卫星的全球SST单日和月平均融合产品的图像空间结构，分析了匹配像元SST值的离散度，统计了HY1C/1D的误差结果，讨论了HY1C与HY1D产品的一致性、不同质量控制方案对SST产品影响以及遥感产品质量对昼夜SST变化研究影响等问题。结果表明，以2020年6月SST(Terra)为真值，HY1C白天SST的单日全球遥感产品的平均偏差、绝对偏差、均方根误差和相关系数分别为0.04℃、0.60℃、0.78℃和0.98，夜晚SST的单日全球遥感产品的平均偏差、绝对偏差、均方根误差和相关系数分别为-0.16℃、0.78℃、0.95℃和0.86。以2020年6月SST(Aqua)为真值，HY1D白天SST的单日全球遥感产品的平均偏差、绝对偏差、均方根误差和相... 相似文献
7.
本文基于2016年11月8日—2019年6月29日大沽河入海口水深观测数据分析了大沽河河口水位变化特征,并结合风场、降水量、卫星高度计融合产品资料对其影响因素展开了讨论。结果表明:1)大沽河口水位变化由潮汐过程主导,潮汐类型为正规半日潮,M2分潮占主导;2)余水位在2017年7月—2019年1月存在周期约为110—150天的显著季节内变化,主要受到纬向风的影响,监测系统处在大沽河入海口西岸,东向(西向)风将驱动水体向东(西)输运,导致西岸监测系统处水量减少(增加),从而观测到余水位下降(上升);3)观测期间,余水位存在显著下降趋势,约为–0.53×10–2 m/月,主要受到大沽河流域降水量减少的影响。 相似文献
8.
一次渤海强对流天气系统监测与大风成因探讨 总被引：1，自引：0，他引：1
利用FY-2E卫星云图、天气雷达、雷电、海上平台、海岛站及海洋模式产品等资料,对2011年9月1日01—06时出现在渤海湾强对流天气成因进行综合分析。结果表明:位于燕山南麓较弱中β尺度云团,在500 hPa西风急流出口处、低层925 hPa切变线及层结不稳定条件下,触发多单体风暴重新发展,造成西岸区短时强降水天气及冰雹天气;中尺度系统主体入海后南压强度少变,在多单体风暴后部下沉气流与后部冷空气动量下传共同作用下,迅速加大渤海湾海区东北大风的分量,在同时具备天文大潮的条件下导致了南岸局部风暴潮灾害的发生。同步监测显示:云图中尺度象元TBB为-25°—-65℃,对流云团强弱交替变化时间为3—6 h,减弱后迅速转向东北岸区;三部天气雷达径向速度图先后监测到NE向低空急流"牛眼"时空尺度特征,同步垂直风廓线(VWP)反演出NE向低空急流由1000 m下降至300 m动量下传过程,与海岛站、平台监测值接近一致,中部与南部海区转为东北大风时间差为3—4 h;20时探空海岸带与风场垂直和水平切变明显,K指数为33℃,SI指数为-3.8℃,对流有效位能Cape为1555 J/kg;海洋中尺度数值产品3—6 h的K指数及海区辐合线的动态模拟与云图TBB中尺度象元、雷达回波移向相对一致,但风速明显偏小10—12 m/s。 相似文献
9.
海表二氧化碳分压(pCO2)是指海洋表层水和大气之间的二氧化碳(CO2)交换处于动态平衡时CO2的含量, 是描述海-气CO2交换的一个主要因子。本文利用2008—2014年覆盖南海大部分海域的海表pCO2观测资料, 结合现场海表温度和海表盐度以及卫星观测的叶绿素a数据, 构建了基于多元线性回归方法的分区域反演模型。模型在水深浅于30m的区域均方根误差为5.3μatm, 其余海区均方根误差为10.8μatm, 与前人基于个别航次的有限区域反演结果的均方根误差相当。利用该模型公式和HYbrid Coordinate Ocean Model(HYCOM)再分析海表温、盐数据及MODIS-Aqua卫星观测的叶绿素a数据进行反演, 得到了时空分辨率为5'×5'的2004—2016年的逐月南海海表pCO2数据。该数据能较好地反映南海海表pCO2在海表温度影响下, 春夏高、秋冬低的季节变化特征, 与前人基于航次观测的研究结果相似, 表明反演模型具有较高的可信度。进一步分析发现, 南海及邻近海域平均海表pCO2具有显著的准十年振荡特征: 2012年附近出现了极小值, 之前表现为降低的趋势, 之后略有升高的趋势。受海表pCO2的影响, 南海海盆平均海-气CO2通量在2012年之前出现了显著降低的趋势, 表明南海释放到大气中的CO2减少, 并在2007年之后的冬季出现了负值(从碳源变为碳汇), 2012年之后变化较为平缓。热带太平洋年代际振荡引起的南海区域海表盐度变化是造成海表pCO2及海-气CO2通量准十年变化的主要原因。分区分析的结果表明, 南海北部海表pCO2变化最为显著, 在南海海表pCO2的季节和准十年变化中都起到非常重要的作用。 相似文献
10.
为评价“海洋二号”卫星（HaiYang-2A, HY-2A）校正微波辐射计（Calibration Microwave Radiometer, CMR）近海水汽产品精度,以中国沿海全球导航卫星系统（Global Navigation Satellite System, GNSS）业务观测站数据和欧洲中期天气预报中心（European Centre for Medium-Range Weather Forecasts,ECMWF)发布的第五代大气再分析资料（ECMWF Reanalysis 5, ERA5）作为验证数据。首先对选取的GNSS业务观测站数据和CMR水汽含量数据进行时空匹配,两者的观测时间一致、空间范围取为100 km;然后利用精密单点定位方法反演GNSS业务观测站上空的大气可降水量（Precipitable Water Vapor, PWV）,同时对1 h分辨率的ERA5再分析资料内插计算,得到CMR水汽数据点处的ERA5 PWV;最后以GNSS PWV和ERA5 PWV为参考,分析2015年CMR水汽产品精度和偏差时空分布。结果表明,CMR水汽含量和GNSS PWV、ERA5 PWV之间的相关系数r均高于0.96,平均均方根误差分别为3.17 mm和1.58 mm,具有较高的精度;CMR水汽含量相对于GNSS PWV和ERA5 PWV的偏差不随季节变化而变化,但CMR水汽含量数据精度随纬度的增加而有所提高。 相似文献
11.
基于星载微波辐射计的海洋大气参数反演算法研究 总被引：4，自引：0，他引：4
利用3个辐射传输模式对无冰无降水情况下的星载微波辐射计亮温测量进行仿真研究,通过模拟计算结果与同步卫星数据之间的比较分析,确定了用于反演算法研究的前向模式;利用该模式,提出了基于物理的星载微波辐射计海洋大气参数(包括海面风速、海表温度、大气垂直积分水汽量以及积分液态水量)多重线性回归算法。 相似文献
12.
我们发展了一种用19．35GHz星载微波辐射计(SSM／I)亮温反演海面风速的模式，并利用同步的卫星亮温和海面浮标数据反演出海面风速，并且和浮标风速进行比较。为了说明反演算法的可用性，我们分别与目前国际上的通用反演算法的反演结果进行了比较。文章提供了一种新的、用单一波段亮温反演海面风速的方法。 相似文献
13.
Akira Shibata 《Journal of Oceanography》2006,62(3):351-359
A wind speed retrieval algorithm was developed using 6 and 10 GHz h-pol (6H and 10H) data of the Advanced Microwave Scanning
Radiometer (AMSR) aboard the Advanced Earth Observation Satellite-II (ADEOS-II) and AMSR-E aboard AQUA, for the purpose of
retrieving wind speed inside rainstorms, primarily hurricanes and typhoons. The h-pol was used rather than the v-pol, because
the brightness temperature sensitivity to the ocean wind at h-pol is larger than v-pol. The microwave emission change of 6H
and 10H corresponding to ocean wind was evaluated in no-rain areas by combining AMSR and SeaWinds data aboard the ADEOS-II
(SeaWinds was NASA’s scatterometer), and it was found that the ratio of the two 6H to 10H increments due to ocean wind is
0.9. Assuming that this result also holds with higher wind speeds and under rainy conditions, the brightness temperatures
at 6H and 10H were simulated using a microwave radiative transfer model. A parameter W6 (unit; Kelvin) was then defined, representing
an increment at 6H due to ocean wind. W6 is applicable to rainy areas, and to all ranges of sea surface temperature. W6 was
compared with wind speed reported by the National Hurricanes Center for several hurricanes in the Western Atlantic Ocean during
three years (2002 to 2004). W6 averaged around centers of hurricanes was found to exhibit a sensitivity to wind speed, such
as increasing from 22 K to 65 K as the wind speed rose from 65 to 140 knots (33 to 72 m/s), and an empirical relationship
relating the averaged W6 to wind speed in hurricanes was derived. 相似文献
14.
Kohtaro Hosoda Hiroshi Murakami Akira Shibata Futoki Sakaida Hiroshi Kawamura 《Journal of Oceanography》2006,62(3):339-350
This study compares infrared and microwave measurements of sea surface temperature (SST) obtained by a single satellite. The
simultaneous observation from the Global Imager (GLI: infrared) and the Advanced Microwave Scanning Radiometer (AMSR: microwave)
aboard the Advanced Earth Observing Satellite-II (ADEOS-II) provided an opportunity for the intercomparison. The GLI-and AMSR-derived
SSTs from April to October 2003 are analyzed with other ancillary data including surface wind speed and water vapor retrieved
by AMSR and SeaWinds on ADEOS-II. We found no measurable bias (defined as GLI minus AMSR), while the standard deviation of
difference is less than 1°C. In low water vapor conditions, the GLI SST has a positive bias less than 0.2°C, and in high water
vapor conditions, it has a negative (positive) bias during the daytime (nighttime). The low spatial resolution of AMSR is
another factor underlying the geographical distribution of the differences. The cloud detection problem in the GLI algorithm
also affects the difference. The large differences in high-latitude region during the nighttime might be due to the GLI cloud-detection
algorithm. AMSR SST has a negative bias during the daytime with low wind speed (less than 7 ms−1), which might be related to the correction for surface wind effects in the AMSR SST algorithm. 相似文献
15.
The Jason microwave radiometer (JMR) provides a crucial correction due to water vapor in the troposphere, and a much smaller correction due to liquid water, to the travel time of the Jason-1 altimeter radar pulse. An error of any size in the radiometer's measurement of wet path delay translates as an error of equal size in the measurement of sea surface height, the ultimate quantity that the altimetric system should yield. The estimate of globally-averaged sea surface height change associated with climate change, requires that uncertainties in the trends in such a global average be accurate to much better than the signal of 1–2 mm/yr. We first compare the JMR observations to those from the TOPEX/Poseidon radiometer (TMR) over approximately six months, since the intent of Jason is to continue the 10-year time series of precision ocean surface topography initiated by T/P. We then assess the stability of the JMR measurement by comparing its wet path delay to those of other orbiting radiometers over 22 months, specifically the Special Sensor Microwave Imager aboard the Defense Meteorological Satellite Program (DMSP-SSM/I) series of satellites, and the Tropical Rainfall Mapping Mission's Microwave Imager (TMI), as well as the European Center for Medium Range Weather Forecasting's (ECMWF) atmospheric numerical model estimate of water vapor. From the combined set, we obtain a robust assessment of the stability of JMR measurements. We find, that JMR is in remarkable agreement with TMR, only 2.5 mm longer, and 6–7 mm standard deviation on their difference in 0.5 degree averages; that JMR has experienced a globally-averaged step-function change, yielding an apparent shortening in wet path delay estimates of 4–5 mm around October 2002 (Jason cycles 28–32); that this step-function is visible only in the 23.8 GHz channel; and that the 34 GHz channel appears to drift at a rate of ?0.4K/year. In addition, we find that, while in 2002 there was no evidence of sensitivity to the Jason satellite's attitude (a correlation of the wet path delay with yaw state), in 2003 there are strong (2–3 mm, up to 7 mm globally averaged) changes associated with such yaw state. These JMR issues were all found in the first 22 months of Jason's geophysical data records (GDR) data, and thus they apply to any investigations that use such data without further corrections. 相似文献
16.
The Jason microwave radiometer (JMR) provides a crucial correction due to water vapor in the troposphere, and a much smaller correction due to liquid water, to the travel time of the Jason-1 altimeter radar pulse. An error of any size in the radiometer's measurement of wet path delay translates as an error of equal size in the measurement of sea surface height, the ultimate quantity that the altimetric system should yield. The estimate of globally-averaged sea surface height change associated with climate change, requires that uncertainties in the trends in such a global average be accurate to much better than the signal of 1-2 mm/yr. We first compare the JMR observations to those from the TOPEX/Poseidon radiometer (TMR) over approximately six months, since the intent of Jason is to continue the 10-year time series of precision ocean surface topography initiated by T/P. We then assess the stability of the JMR measurement by comparing its wet path delay to those of other orbiting radiometers over 22 months, specifically the Special Sensor Microwave Imager aboard the Defense Meteorological Satellite Program (DMSP-SSM/I) series of satellites, and the Tropical Rainfall Mapping Mission's Microwave Imager (TMI), as well as the European Center for Medium Range Weather Forecasting's (ECMWF) atmospheric numerical model estimate of water vapor. From the combined set, we obtain a robust assessment of the stability of JMR measurements. We find, that JMR is in remarkable agreement with TMR, only 2.5 mm longer, and 6-7 mm standard deviation on their difference in 0.5 degree averages; that JMR has experienced a globally-averaged step-function change, yielding an apparent shortening in wet path delay estimates of 4-5 mm around October 2002 (Jason cycles 28-32); that this step-function is visible only in the 23.8 GHz channel; and that the 34 GHz channel appears to drift at a rate of -0.4K/year. In addition, we find that, while in 2002 there was no evidence of sensitivity to the Jason satellite's attitude (a correlation of the wet path delay with yaw state), in 2003 there are strong (2-3 mm, up to 7 mm globally averaged) changes associated with such yaw state. These JMR issues were all found in the first 22 months of Jason's geophysical data records (GDR) data, and thus they apply to any investigations that use such data without further corrections. 相似文献
17.
Merging satellite infrared and microwave SSTs: Methodology and evaluation of the new SST 总被引：3，自引：0，他引：3
The Global Ocean Data Assimilation Experiment (GODAE) requires the availability of a global analyzed SST field with high-resolution
in space (at least 10 km) and time (at least 24 hours). The new generation SST products would be based on the merging of SSTs
from various satellites data and in situ measurements. The merging of satellite infrared and microwave SST data is investigated in this paper. After pre-processing
of the individual satellite data, objective analysis was applied to merge the SST data from NOAA AVHRR (National Oceanic and
Atmospheric Administration, Advanced Very High Resolution Radiometer), GMS S-VISSR (Geostationary Meteorological Satellite,
Stretched-Visible Infrared Spin Scan Radiometer), TRMM MI (Tropical Rainfall Measuring Mission, Microwave Imager: TMI) and
VIRS (Visible and Infrared Scanner). The 0.05° daily cloud-free SST products were generated in three regions, viz., the Kuroshio
region, the Asia-Pacific Region and the Pacific, during one-year period of October 1999 to September 2000. Comparisons of
the merged SSTs with Japan Meteorological Agency (JMA) buoy SSTs show that, with considerable error sources from individual
satellite data and merging procedure, an accuracy of 0.95 K is achieved. The results demonstrate the practicality and advantages
of merging SST measurements from various satellite sensors. 相似文献
18.
介绍了红外辐射计和微波辐射计测量海表面温度的原理，分析了它们各自在反演海表面温度时的差异。在全球范围的海表面温度的遥感蛉测中，红外辐射计和微波辐射计的遥感精度受到多种因素影响。传感器本身的噪音、算法反演精度、传感器分辨率、搭载卫星的全球覆盖率等自身因素使辐射计的探测资料产生差别：大气状况、海面风速、测量海洋不同深度海水的表征温度等外界因子也同时影响着红外辐射计和微波辐射计的遥感精度。了解红外波段和微波波段的辐射计在各方面的优劣，有助于发挥各自特长，有效提高卫星监测海表面温度的精度。 相似文献
19.
The accuracy and drift of atmospheric path delay due to water vapor as derived from satellite microwave radiometers (MWR) is vital to altimetric measures of sea-level change. In this study a continuous time series of dual frequency GPS data from a number of offshore sites is used to examine the long term stability of the TOPEX/Poseidon radiometer and investigate initial performance of that of Jason-1. The location offshore eliminates the problems associated with land based/coastal locations where extrapolation of the GPS tropospheric correction to subsatellite points offshore are required to avoid background surface heat emissions contaminating the MWR delay measurement. 相似文献
20.
Monitoring Measurements from the Jason-1 Microwave Radiometer and Independent Validation with GPS 总被引：1，自引：0，他引：1
The Jason-1 Microwave Radiometer (JMR) provides measurements of the wet troposphere content to correct the altimetric range measurement for the associated path delay. Various techniques are used to monitor the JMR wet troposphere path delays, with measurements of zenith troposphere content from terrestrial GPS sites used as an independent verification technique. Results indicate that an unexpected offset of approximately +4.1 ± 1.2 mm (drier) emerged in the JMR measurements of wet path delay between cycles 28-32 of the Jason-1 mission, and that the measurements may be drifting at a rate of approximately -0.5 mm/year. These anomalies are shown to be caused by a -0.7 K offset in 23.8 GHz brightness temperatures between cycles 28-32, and a 0.16 ± 0.04 and -0.45 ± 0.08 K/year drift in the 18.7 and 34.0 GHz brightness temperatures, respectively. Intercomparison of the 3-Hz JMR brightness temperature measurements show that they have been drifting with respect to each other, and that a dependence on yaw-steering regime is present in these measurements. An offset of 0.5 m/s between cycles 28-32 and a drift of approximately 0.5 m/s/year in the JMR wind speed measurements is also associated with these anomalies in the 1-Hz brightness temperatures. These errors in JMR wind speeds presently have a negligible impact on the retrieved JMR path delays. 相似文献