联合地基GPS和MODIS研究成都地区大气可降水量变化
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摘要
成都的热力和动力作用对四川地区的气候变化有重要的影响,而成都地区大气可降水量变化是揭示成都平原热力、动力作用及区域水循环机制的重要信息。为进一步提高成都地区大气可降水量变化研究结果的空间分辨率和精度,本文利用近年发展起来的地基GPS大气探测技术,联合高空间分辨率卫星遥感数据(MODIS),定量反演了成都地区大气可降水量变化。
本文的研究内容主要分为以下四个部分:
1、通过解算成都地区成都(CHDU)、简阳(JYAN)、郫县(PIXI)、邛崃(QLAI)、人寿(RENS)、中江(ZHJI)共6个站的地基GPS大气可降水量探测资料,获得了这些站的大气可降水量;分析了成都站的大气可降水量的变化特征、地基GPS探测结果的精度及大气可降水量与地面气象要素之间的关系。结果表明:①成都站2005年7月大气可降水量变化为31.6～62.3mm,8月36.9～62.5mm,9月23.1～58.2mm;②成都站地基GPS探测与同一时刻无线电探空结果的平均差值为0.45mm,均方根误差为2.82mm,相关系数为98.27%,二者的线性关系式为:GPS=1.018×SONDE-0.328;③大气可降水量变化与降水密切相关,降水往往发生在大气可降水量发生跳跃递增、持续递增或者出现骤变时刻。
2、探讨利用MODIS近红外波段反演大气可降水量的方法,得到了两通道比值加权法和三通道比值加权法的MODIS大气可降水量产品。对该两种方法结果进行统计,并与成都站SONDE大气可降水量进行比较分析,结果显示,三通道比值加权法可靠性更高。
3、将成都站地基GPS大气可降水量与MODIS大气可降水量进行了比较分析。研究发现地基GPS大气可降水量与MODIS大气可降水量的变化趋势较一致(相关系数为85.4%),但均方根误差却达2.98mm,且MODIS大气可降水量明显偏低,有些几乎相差一半。因此,需要对MODIS大气可降水量进行订正。经订正得到的MODIS大气可降水量的精度明显提高,两者在数值上很接近,相关系数达到89.8%,均方根误差也减到了2.15mm。
4、由于MODIS的空间分辨率较高,其大气可降水量结果更能较为详细地反映大气可降水量变化。因此,将地基GPS大气可降水量面与MODIS大气可降水量进行联合分析,不仅能增强成都地区大气可降水量变化研究的可靠性,还可以有效提高成都地区大气可降水量变化的空间分辨率。
综上所述,与利用少量的地基GPS站点获得的成都地区大气可降水量变化结果相比,将地基GPS和MODIS联合进行大气可降水量变化研究,可有效提高大气可降水量的时间分辨率、空间分辨率及可靠性,且具有全天候、长期、稳定、成本低等优点。
The thermal and dynamical effect of Chengdu is very important for the weather and climate change in Sichuan. Studying atmospheric precipital water vapor (PWV) variability over Chengdu region is one of the most important ways to realize the thermal and dynamical effect, weather and climate change, as well as regional water cycle over Chengdu plain. In order to improve spatial resolution and precision of PWV over Chengdu region, in this paper, using ground-based GPS, associated with MODIS image of high spatial resolution, retrieval the PWV variability over Chengdu region.
Contents of this paper including the following four aspects:
Firstly, the ground-based GPS data in Chengdu (CHDU), Jianyang (JYAN), Pixian (PIXI), Qionglai (QLAI), Renshou (RENS) and Zhongjiang (ZHJI) are processed to obtain the PWV of the six stations; the PWV variability of CHDU stations covered area are analysed and compared with the Radiosonde (SONDE) data. The relationships between PWV and ground meteorology factors are studied. It shows that: the change scope of PWV in station CHDU is about 31.6mm to 62.3mm in July, 36.9mm to 62.5mm in August, and 23.1mm to 58.2mm in September; average difference between the results of ground-based GPS and the Radiosonde data on CHDU station is 045mm, with the RMS of 2.82mm, correlation coefficient of 98.27 % , a model can be fitted between ground-based GPS and SONDE, i.e.GPS = 1.018×SONDE-0.328; ground actual precipitation is well related with the change of PWV, and an abrupt increase, durative increase and abrupt change of PWV is companied with precipitation.
Secondly, discussed the means of retrieving PWV using MODIS image, we procured the PWV of two-channel ratio weighted method and three-channel ratio weighted method of Chengdu region in the end. Compared the results of the two kinds weighted method to the PWV of SONDE over CHDU station, and compared the results of the two kinds weighted method, it shows that the PWV of three-channel ratio weighted method have higher dependability.
Thirdly, compared the PWV of the ground-based GPS with PWV of MODIS in CHDU station. It shows that the changing trend between them are consistent with a correlation coefficient of 85.4%, but the RMS is 2.98mm, and the PWV of MODIS are low obviously, almost half of ground-based GPS results sometimes. Obviously the PWV of MODIS needs to correct, the precision of corrected PWV of MODIS increased obviously. The two are adjacent at numerical value, its relativity coefficient is 89.8%, and RMS reduce to 2.15mm.
Fourthly, due to the PWV of MODIS has higher spatial resolution, its results can reflect PWV variability more detailedly. So we can associate with the PWV of ground-based GPS and MODIS to research the Chengdu region, not only increase the dependability of PWV variability, but also enhance the spatial resolution of PWV variability.
In conclusion, compared with the PWV of observations data based on a few ground-based GPS stations, associate with ground-based GPS and MODIS research PWV variability, it can enhance the temporal resolution, spatial resolution, dependability, and have many excellence, such as all-weather, permanent, stabilization, low cost, and so on.
本文的研究内容主要分为以下四个部分:
1、通过解算成都地区成都(CHDU)、简阳(JYAN)、郫县(PIXI)、邛崃(QLAI)、人寿(RENS)、中江(ZHJI)共6个站的地基GPS大气可降水量探测资料,获得了这些站的大气可降水量;分析了成都站的大气可降水量的变化特征、地基GPS探测结果的精度及大气可降水量与地面气象要素之间的关系。结果表明:①成都站2005年7月大气可降水量变化为31.6～62.3mm,8月36.9～62.5mm,9月23.1～58.2mm;②成都站地基GPS探测与同一时刻无线电探空结果的平均差值为0.45mm,均方根误差为2.82mm,相关系数为98.27%,二者的线性关系式为:GPS=1.018×SONDE-0.328;③大气可降水量变化与降水密切相关,降水往往发生在大气可降水量发生跳跃递增、持续递增或者出现骤变时刻。
2、探讨利用MODIS近红外波段反演大气可降水量的方法,得到了两通道比值加权法和三通道比值加权法的MODIS大气可降水量产品。对该两种方法结果进行统计,并与成都站SONDE大气可降水量进行比较分析,结果显示,三通道比值加权法可靠性更高。
3、将成都站地基GPS大气可降水量与MODIS大气可降水量进行了比较分析。研究发现地基GPS大气可降水量与MODIS大气可降水量的变化趋势较一致(相关系数为85.4%),但均方根误差却达2.98mm,且MODIS大气可降水量明显偏低,有些几乎相差一半。因此,需要对MODIS大气可降水量进行订正。经订正得到的MODIS大气可降水量的精度明显提高,两者在数值上很接近,相关系数达到89.8%,均方根误差也减到了2.15mm。
4、由于MODIS的空间分辨率较高,其大气可降水量结果更能较为详细地反映大气可降水量变化。因此,将地基GPS大气可降水量面与MODIS大气可降水量进行联合分析,不仅能增强成都地区大气可降水量变化研究的可靠性,还可以有效提高成都地区大气可降水量变化的空间分辨率。
综上所述,与利用少量的地基GPS站点获得的成都地区大气可降水量变化结果相比,将地基GPS和MODIS联合进行大气可降水量变化研究,可有效提高大气可降水量的时间分辨率、空间分辨率及可靠性,且具有全天候、长期、稳定、成本低等优点。
The thermal and dynamical effect of Chengdu is very important for the weather and climate change in Sichuan. Studying atmospheric precipital water vapor (PWV) variability over Chengdu region is one of the most important ways to realize the thermal and dynamical effect, weather and climate change, as well as regional water cycle over Chengdu plain. In order to improve spatial resolution and precision of PWV over Chengdu region, in this paper, using ground-based GPS, associated with MODIS image of high spatial resolution, retrieval the PWV variability over Chengdu region.
Contents of this paper including the following four aspects:
Firstly, the ground-based GPS data in Chengdu (CHDU), Jianyang (JYAN), Pixian (PIXI), Qionglai (QLAI), Renshou (RENS) and Zhongjiang (ZHJI) are processed to obtain the PWV of the six stations; the PWV variability of CHDU stations covered area are analysed and compared with the Radiosonde (SONDE) data. The relationships between PWV and ground meteorology factors are studied. It shows that: the change scope of PWV in station CHDU is about 31.6mm to 62.3mm in July, 36.9mm to 62.5mm in August, and 23.1mm to 58.2mm in September; average difference between the results of ground-based GPS and the Radiosonde data on CHDU station is 045mm, with the RMS of 2.82mm, correlation coefficient of 98.27 % , a model can be fitted between ground-based GPS and SONDE, i.e.GPS = 1.018×SONDE-0.328; ground actual precipitation is well related with the change of PWV, and an abrupt increase, durative increase and abrupt change of PWV is companied with precipitation.
Secondly, discussed the means of retrieving PWV using MODIS image, we procured the PWV of two-channel ratio weighted method and three-channel ratio weighted method of Chengdu region in the end. Compared the results of the two kinds weighted method to the PWV of SONDE over CHDU station, and compared the results of the two kinds weighted method, it shows that the PWV of three-channel ratio weighted method have higher dependability.
Thirdly, compared the PWV of the ground-based GPS with PWV of MODIS in CHDU station. It shows that the changing trend between them are consistent with a correlation coefficient of 85.4%, but the RMS is 2.98mm, and the PWV of MODIS are low obviously, almost half of ground-based GPS results sometimes. Obviously the PWV of MODIS needs to correct, the precision of corrected PWV of MODIS increased obviously. The two are adjacent at numerical value, its relativity coefficient is 89.8%, and RMS reduce to 2.15mm.
Fourthly, due to the PWV of MODIS has higher spatial resolution, its results can reflect PWV variability more detailedly. So we can associate with the PWV of ground-based GPS and MODIS to research the Chengdu region, not only increase the dependability of PWV variability, but also enhance the spatial resolution of PWV variability.
In conclusion, compared with the PWV of observations data based on a few ground-based GPS stations, associate with ground-based GPS and MODIS research PWV variability, it can enhance the temporal resolution, spatial resolution, dependability, and have many excellence, such as all-weather, permanent, stabilization, low cost, and so on.
引文
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