scholarly journals Evaluation of MODIS Water Vapour Products over ALGERIA using Radiosonde Data

Author(s):  
Houaria Namaoui ◽  
Salem Kahlouche ◽  
Ahmed Hafidh Belbachir

Remote sensing of atmospheric water vapour using GNSS and Satellite data has become an efficient tool in meteorology and climate research. Many satellite data have been increasingly used to measure the content of water vapour in the atmosphere and to characterize its temporal and spatial variations. In this paper, we have used observations from radiosonde data collected from three stations (Algiers, Bechar and Tamanrasset) in Algeria from January to December 2012 to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) total precipitable water vapour (PWV) products. Results show strong agreement between the total precipitable water contents estimated based on radiosondes observations and the ones measured by the sensor MODIS with the correlation coefficients in the range 0.69 to 0.95 and a mean bias, which does not exceed 1.5.  

MAUSAM ◽  
2021 ◽  
Vol 67 (3) ◽  
pp. 571-576
Author(s):  
ZHANG JINYE ◽  
CHENG CHUNFU ◽  
ZHU JINRONG ◽  
YU XIULI

Column-integrated water vapour also called Precipitable Water Vapour (PWV), is one of the main parameters influencing the global climate change. Due to its high spatial and temporal variability PWV has been found to be a good tracer of atmospheric motions. Retrieving PWV from Moderate Resolution Imaging Spectroradiometer (MODIS) data has the merits of high spatial resolution and low cost. In this paper, an algorithm for retrieving PWV using several MODIS near-IR channels data is first presented. Six typical cities in China with different climate are selected for study. These are Beijing, Shanghai, Guangzhou, Chengdu, Wuhan and Lanzhou. The variations of PWV in recent13 years (2001-2013) over six cities have been analyzed. The study brings out an increasing trend of annual average of water vapour over these cities in recent 13 years. The results also indicate that PWV reaches the highest value in summer, decreases in autumn, further decrease in spring, and is lowest in winter. PWV in summer over the six cities have been increasing in recent 13 years, but PWV in autumn and winter have been decreasing over inland cities, such as Wuhan and Beijing. Possible reasons for such observed trends are given in this paper.  


Author(s):  
Parwati Sofan ◽  
Totok Sugiharto ◽  
Hasnaeni

This research is performed to derive weather property, i.e. relative humidity, based on precipitable water from MODIS (Moderate Resolution Imaging Spectroradiometer) data which on board of TERRA/AQUA satellites. As one of dynamic atmospheric parameters, the precipitable water has ability to indicate the dryness or wetness of a certain area. It can be derived by MODIS at 0.865, 1.24, 0.905, 0.936 and 0.940 um of its wavelength ranges. Verification of MODIS precipitatble water is made using radiosonde data at 2 climatological stations in Java island (Jakarta and Surabaya). The result shows that the standard deviation between precipitable water which is derived by MODIS and radiosonde data (August-October 2004), is 1.6 cm, Meanwhile, through the statistical analysis, they have significant correlation of about 0.82. In adition, the relationship between the MODIS precipitable water and the altitude has a negative correlation (r= -0.98). It means that the precipitable water tends to decrease along with the increase of altitude, According to the climate condition in West Java which is mostly wetter rather than of East Java, we knew that the precipitable water in West Java is higher than East Java. Related to related to relative humidity, the mODIS precipitable water can be used to estimate relative humidity, based on topography area, the correlation coeficient between 0.84-0.92. Keywords: MODIS Precipitable water, Radiosonde, Relative humidity, Verification.


2019 ◽  
Author(s):  
Juan Huo ◽  
Daren Lu ◽  
Shu Duan ◽  
Yongheng Bi ◽  
Bo Liu

Abstract. To better understand the accuracy of cloud top heights (CTHs) derived from passive satellite data, ground-based Ka-band radar measurements from 2016 and 2017 in Beijing were compared with CTH data inferred from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Himawari Imager (AHI). Relative to the radar CTHs, the MODIS CTHs were found to be underestimated by −1.10 ± 2.53 km and 49 % of CTH differences were within 1.0 km. Like the MODIS results, the AHI CTHs were underestimated by −1.10 ± 2.27 km and 42 % were within 1.0 km. Both the MODIS and AHI retrieval accuracy depended strongly on the cloud depth (CD). Large differences were mainly occurring for the retrieval of thin clouds of CD  1 km, the CTH difference decreased to −0.48 ± 1.70 km for MODIS and to −0.76 ± 1.63 km for AHI. MODIS CTHs greater than 6 km showed better agreement with the radar data than those less than 4 km. Statistical analysis showed that the average AHI CTHs were lower than the average MODIS CTHs by −0.64 ± 2.36 km. The monthly accuracy of both retrieval algorithms was studied and it was found that the AHI retrieval algorithm had the largest bias in winter while the MODIS retrieval algorithm had the lowest accuracy in spring.


2020 ◽  
Vol 64 (04) ◽  
pp. 562-577
Author(s):  
Shaoqi Gong ◽  
Wenqin Chen ◽  
Cunjie Zhang ◽  
Ping Wu ◽  
Jing Han

The atmospheric precipitable water vapour (PWV) plays a crucial role in the hydrological cycle and energy transfer on a global scale. Radiosonde (RS), sunphotometer (SP) and GPS (as well as broader GNSS) receivers have gradually been the principal instruments for ground-based PWV observation. This study first co-locates the observation stations configured the three instruments in the globe and in three typical latitudinal climatic regions respectively, then the PWV data from the three instruments are matched each other according to the observing times. After the outliers are removed from the matched data pairs, the PWV intercomparisons for any two instruments are performed. The results show that the PWV estimates from any two instruments have a good agreement with very high correlation coefficients. The latitude and climate have no significant influence on the PWV measurements from the three instruments, indicating that the instruments are very stable and depend on their performance. The PWV differences of any two instruments display the normal distribution, indicating non-systematic biases among the two PWV datasets. The relative differences between SP and GPS are the smallest, the middle between SP and RS, and those between GPS and RS are the largest. This study will be useful to promote GPS (GNSS) and SP PWV to be a substitute for RS PWV as a benchmark because of their high temporal resolutions.


2020 ◽  
Vol 12 (12) ◽  
pp. 1985 ◽  
Author(s):  
Sundar Christopher ◽  
Pawan Gupta

Using a combined Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) mid-visible aerosol optical depth (AOD) product at 0.1 × 0.1-degree spatial resolution and collocated surface PM2.5 (particulate matter with aerodynamic diameter smaller than 2.5 μm) monitors, we provide a global five-year (2015–2019) assessment of the spatial and seasonal AOD–PM2.5 relationships of slope, intercepts, and correlation coefficients. Only data from ground monitors accessible through an open air-quality portal that are available to the worldwide community for air quality research and decision making are used in this study. These statistics that are reported 1 × 1-degree resolution are important since satellite AOD is often used in conjunction with spatially limited surface PM2.5 monitors to estimate global distributions of surface particulate matter concentrations. Results indicate that more than 3000 ground monitors are now available for PM2.5 studies. While there is a large spread in correlation coefficients between AOD and PM2.5, globally, averaged over all seasons, the correlation coefficient is 0.55 with a unit AOD producing 54 μgm−3 of PM2.5 (Slope) with an intercept of 8 μgm−3. While the number of surface PM2.5 measurements has increased by a factor of 10 over the last decade, a concerted effort is still needed to continue to increase these monitors in areas that have no surface monitors, especially in large population centers that will further leverage the strengths of satellite data.


2018 ◽  
Vol 11 (11) ◽  
pp. 6003-6012 ◽  
Author(s):  
Shailesh Parihar ◽  
Ashim Kumar Mitra ◽  
Mrutyunjay Mohapatra ◽  
Rajjev Bhatla

Abstract. The objectives of the INSAT-3D satellite are to enhance the meteorological observations and to monitor the Earth's surface for weather forecasting and disaster warning. One of the weather-monitoring capabilities of the INSAT-3D sounder is the estimation of water vapour in the atmosphere. The amount of water vapour present in the atmospheric column is derived as the total precipitable water (TPW) product from the infrared radiances measured by the INSAT-3D sounder. The present study is based on TPW derived from INSAT-3D sounder, radiosonde (RS) observations and the corresponding National Oceanic and Atmospheric Administration (NOAA) satellite. To assess retrieval performances of INSAT-3D sounder-derived TPW, RS TPW observations are considered for the validation from May to September 2016 from 34 stations belonging to the India Meteorological Department (IMD). The analysis is performed on daily, monthly, and subdivisional bases over the Indian region. The comparison of INSAT-3D TPW with RS TPW on daily and monthly bases shows that the root mean square error (RMSE) and correlation coefficients (CC) are ∼8 mm and 0.8, respectively. However, on subdivisional and overall scales, the RMSE found to be in the range of 1 to 2 mm and CC was around 0.9 in comparison with RS and NOAA. The spatial distribution of INSAT-3D TPW with actual rainfall observation is also investigated. In general, INSAT-3D TPW corresponds well with rainfall observation; however, it has found that heavy rainfall events occur in the presence of high TPW values. In addition, the cases of thunderstorm events were assessed using TPW from INSAT-3D and network of Global Navigation Satellite System (GNSS) receiver. This shows the good agreement between TPW from INSAT-3D and GNSS during the mesoscale activity. The improvement in the estimation of TPW is carried out by applying the GSICS calibration corrections (Global Space-based Inter-Calibration System) to the radiances from infrared (IR) channels of the sounder, which is used by IMDPS (INSAT Meteorological Data Processing System). The current TPW from INSAT-3D satellite can be utilized operationally for weather monitoring and forecast purposes. It can also offer substantial opportunities for improvement in nowcasting studies.


2015 ◽  
Vol 54 (5) ◽  
pp. 1009-1020 ◽  
Author(s):  
Ning An ◽  
Kaicun Wang

AbstractClouds determine the amount of solar radiation incident to the surface. Accurately quantifying cloud fraction is of great importance but is difficult to accomplish. Satellite and surface cloud observations have different fields of view (FOVs); the lack of conformity of different FOVs may cause large discrepancies when comparing satellite- and surface-derived cloud fractions. From the viewpoint of surface-incident solar radiation, this paper compares Moderate Resolution Imaging Spectroradiometer (MODIS) level-2 cloud-fraction data with three surface cloud-fraction datasets at five Surface Radiation Network (SURFRAD) sites. The correlation coefficients between MODIS and the surface cloud fractions are in the 0.80–0.91 range and vary at different SURFRAD sites. In a number of cases, MODIS observations show a large cloud-fraction bias when compared with surface data. The variances between MODIS and the surface cloud-fraction datasets are more apparent when small convective or broken clouds exist in the FOVs. The magnitude of the discrepancy between MODIS and surface-derived cloud fractions depends on the satellite’s view zenith angle (VZA). On average, relative to surface cloud-fraction data, MODIS observes a larger cloud fraction at VZA > 40° and a smaller cloud fraction at VZA < 20°. When comparing long-term MODIS averages with surface datasets, Aqua MODIS observes a higher annual mean cloud fraction, likely because convective clouds are better developed in the afternoon when Aqua is observing.


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