scholarly journals Comparison of the cloud top heights retrieved from MODIS and AHI satellite data with ground-based Ka-band radar

2019 ◽  
Author(s):  
Juan Huo ◽  
Daren Lu ◽  
Shu Duan ◽  
Yongheng Bi ◽  
Bo Liu
Keyword(s):  
Satellite Data ◽  
Radar Data ◽  
Retrieval Algorithm ◽  
Ka Band ◽  
Retrieval Accuracy ◽  
Retrieval Algorithms ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Radar Measurements ◽  
Moderate Resolution Imaging Spectroradiometer

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.

scholarly journals Comparison of the cloud top heights retrieved from MODIS and AHI satellite data with ground-based Ka-band radar

2020 ◽  
Vol 13 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Juan Huo ◽  
Daren Lu ◽  
Shu Duan ◽  
Yongheng Bi ◽  
Bo Liu
Keyword(s):  
Satellite Data ◽  
Cloud Base ◽  
Ka Band ◽  
Retrieval Accuracy ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Radar Measurements ◽  
The Mean ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference

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 are 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 are found to be underestimated by−1.10 ± 2.53 km on average and 49 % of CTH differences are within 1.0 km. The AHI CTHs are underestimated by −1.10 ± 2.27 km and 42 % are within 1.0 km. Both the MODIS and AHI CTH retrieval accuracy depends strongly on the cloud depth (CD). Large differences are mainly due to the retrieval of thin clouds of CD <1 km, especially when the cloud base height is higher than 4 km. For clouds with CD >1 km, the mean CTH difference decreases to -0.48±1.70 km for MODIS and to -0.76±1.63 km for AHI. It is found that MODIS CTHs with higher values (i.e. >6 km) show smaller discrepancy with radar CTH than those MODIS CTHs with lower values (i.e. <4 km). Statistical analysis illustrate that the CTH difference between the two satellite instruments is lower than the difference between the satellite instrument and the ground-based Ka-band radar. The monthly accuracy of both CTH retrieval algorithms is investigated and it is found that summer has the smallest retrieval difference.

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

2021 ◽  
Vol 44 ◽  
Author(s):  
Houaria Namaoui ◽  
Salem Kahlouche ◽  
Ahmed Hafidh Belbachir
Keyword(s):  
Water Vapour ◽  
Satellite Data ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Radiosonde Data ◽  
Precipitable Water Vapour ◽  
Total Precipitable Water ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

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.  

scholarly journals A Global Multilayer Cloud Identification with POLDER/PARASOL

2017 ◽  
Vol 56 (4) ◽  
pp. 1121-1139 ◽  
Author(s):  
M. Desmons ◽  
N. Ferlay ◽  
F. Parol ◽  
J. Riédi ◽  
F. Thieuleux
Keyword(s):  
Threshold Level ◽  
Satellite Retrieval ◽  
Retrieval Algorithms ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Confidence Index ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Discrete Values ◽  
Level 2 ◽  
Risk Of Misclassification

AbstractThe detection of multilayer cloud situations is important for satellite retrieval algorithms and for many climate-related applications. In this paper, the authors describe an algorithm based on the exploitation of the Polarization and Directionality of the Earth’s Reflectance (POLDER) observations to identify monolayered and multilayered cloudy situations along with a confidence index. The authors’ reference comes from the synergy of the active instruments of the A-Train satellite constellation. The algorithm is based upon a decision tree that uses a metric from information theory and a series of tests on POLDER level-2 products. The authors obtain a multilayer flag as the final result of a tree classification, which takes discrete values between 0 and 100. Values closest to 0 (100) indicate a higher confidence in the monolayer (multilayer) character. This indicator can be used as it is or with a threshold level that minimizes the risk of misclassification, as a binary index to distinguish between monolayer and multilayer clouds. For almost fully covered and optically thick enough cloud scenes, the risk of misclassification ranges from 29% to 34% over the period 2006–10, and the average confidences in the estimated monolayer and multilayer characters of the cloud scenes are 74.0% and 58.2%, respectively. With the binary distinction, POLDER provides a climatology of the mono–multilayer cloud character that exhibits some interesting features. Comparisons with the performance of the Moderate Resolution Imaging Spectroradiometer (MODIS) multilayer flag are given.

scholarly journals Indirect Assessment of Sedimentation in Hydropower Dams Using MODIS Remote Sensing Images

2019 ◽  
Vol 11 (3) ◽  
pp. 314 ◽  
Author(s):  
Rita Condé ◽  
Jean-Michel Martinez ◽  
Marco Pessotto ◽  
Raúl Villar ◽  
Gérard Cochonneau ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Trapping Efficiency ◽  
Retrieval Algorithm ◽  
Independent Field ◽  
Hydropower Dams ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sedimentation Processes

In this study, we used moderate resolution imaging spectroradiometer (MODIS) satellite images to quantify the sedimentation processes in a cascade of six hydropower dams along a 700-km transect in the Paranapanema River in Brazil. Turbidity field measurement acquired over 10 years were used to calibrate a turbidity retrieval algorithm based on MODIS surface reflectance products. An independent field dataset was used to validate the remote sensing estimates showing fine accuracy (RMSE of 9.5 NTU, r = 0.75, N = 138). By processing 13 years of MODIS images since 2000, we showed that satellite data can provide robust turbidity monitoring over the entire transect and can identify extreme sediment discharge events occurring on daily to annual scales. We retrieved the decrease in the water turbidity as a function of distance within each reservoir that is related to sedimentation processes. The remote sensing-retrieved turbidity decrease within the reservoirs ranged from 2 to 62% making possible to infer the reservoir type and operation (storage versus run-of-river reservoirs). The reduction in turbidity assessed from space presented a good relationship with conventional sediment trapping efficiency calculations, demonstrating the potential use of this technology for monitoring the intensity of sedimentation processes within reservoirs and at large scale.

scholarly journals Adaption of the MODIS aerosol retrieval algorithm using airborne spectral surface reflectance measurements over urban areas: a case study

2015 ◽  
Vol 8 (12) ◽  
pp. 5237-5249 ◽  
Author(s):  
E. Jäkel ◽  
B. Mey ◽  
R. Levy ◽  
X. Gu ◽  
T. Yu ◽  
...  
Keyword(s):  
Urban Areas ◽  
Retrieval Algorithm ◽  
Surface Reflectance ◽  
Airborne Measurements ◽  
Modis Aod ◽  
Urban Sample ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. MODIS (MOderate-resolution Imaging Spectroradiometer) retrievals of aerosol optical depth (AOD) are biased over urban areas, primarily because the reflectance characteristics of urban surfaces are different than that assumed by the retrieval algorithm. Specifically, the operational "dark-target" retrieval is tuned towards vegetated (dark) surfaces and assumes a spectral relationship to estimate the surface reflectance in blue and red wavelengths. From airborne measurements of surface reflectance over the city of Zhongshan, China, were collected that could replace the assumptions within the MODIS retrieval algorithm. The subsequent impact was tested upon two versions of the operational algorithm, Collections 5 and 6 (C5 and C6). AOD retrieval results of the operational and modified algorithms were compared for a specific case study over Zhongshan to show minor differences between them all. However, the Zhongshan-based spectral surface relationship was applied to a much larger urban sample, specifically to the MODIS data taken over Beijing between 2010 and 2014. These results were compared directly to ground-based AERONET (AErosol RObotic NETwork) measurements of AOD. A significant reduction of the differences between the AOD retrieved by the modified algorithms and AERONET was found, whereby the mean difference decreased from 0.27±0.14 for the operational C5 and 0.19±0.12 for the operational C6 to 0.10±0.15 and -0.02±0.17 by using the modified C5 and C6 retrievals. Since the modified algorithms assume a higher contribution by the surface to the total measured reflectance from MODIS, consequently the overestimation of AOD by the operational methods is reduced. Furthermore, the sensitivity of the MODIS AOD retrieval with respect to different surface types was investigated. Radiative transfer simulations were performed to model reflectances at top of atmosphere for predefined aerosol properties. The reflectance data were used as input for the retrieval methods. It was shown that the operational MODIS AOD retrieval over land reproduces the AOD reference input of 0.85 for dark surface types (retrieved AOD = 0.87 (C5)). An overestimation of AOD = 0.99 is found for urban surfaces, whereas the modified C5 algorithm shows a good performance with a retrieved value of AOD = 0.86.

scholarly journals Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

2012 ◽  
Vol 51 (10) ◽  
pp. 1811-1822 ◽  
Author(s):  
Kristopher M. Bedka ◽  
Richard Dworak ◽  
Jason Brunner ◽  
Wayne Feltz
Keyword(s):  
Weather Prediction ◽  
Convective Cloud ◽  
Radar Data ◽  
Numerical Weather Prediction Model ◽  
Detection Methods ◽  
Spatial Gradients ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractTwo satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-μm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD > 0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

scholarly journals Validation of MODIS 3 km Land Aerosol Optical Depth from NASA's EOS Terra and Aqua Missions

2018 ◽  
Author(s):  
Pawan Gupta ◽  
Lorraine A. Remer ◽  
Robert C. Levy ◽  
Shana Mattoo
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Aerosol Retrieval ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sensor Degradation ◽  
Over Time

Abstract. The two MODerate Resolution Imaging Spectroradiometer (MODIS) sensors, aboard Earth Observing Satellites (EOS) Terra and Aqua, have been making aerosol observations for more than 15 years. From these observations, the MODIS dark target (DT) aerosol retrieval algorithm provides aerosol optical depth (AOD) products, globally over both land and ocean. In addition to the standard resolution product (10 × 10 km2), the MODIS collection 6 (C006) data release included a higher resolution (3 × 3 km2). Other than accommodations for the two different resolutions, the 10 km, and 3 km DT algorithms are basically the same. In this study, we perform global validation of the higher resolution AOD over global land by comparing against AERONET measurements. The MODIS-AERONET collocated data sets consist of 161,410 high-confidence AOD pairs from 2000 to 2015 for MODIS Terra and 2003 to 2015 for MODIS-Aqua. We find that 62.5 % and 68.4 % of AODs retrieved from MODIS-Terra and MODIS-Aqua, respectively, fall within previously published expected error bounds of ±(0.05 + 0.2*AOD), with a high correlation (R = 0.87). The scatter is not random but exhibits a mean positive bias of ~ 0.06 for Terra and ~ 0.03 for Aqua. These biases for the 3 km product are approximately 0.03 larger than the biases found in similar validations of the 10 km product. The validation results for the 3 km product did not have a relationship to aerosol loading (i.e. true AOD) but did exhibit dependence on quality flags, region, viewing geometry, and aerosol spatial variability. Time series of global MODIS-AERONET differences show that validation is not static, but has changed over the course of both sensors' lifetimes, with MODIS-Terra showing more change over time. The likely cause of the change of validation over time is sensor degradation, but changes in the distribution of AERONET stations and differences in the global aerosol system itself could be contributing to the temporal variability of validation.

scholarly journals Retrieval of aerosol fine-mode fraction over China from satellite multiangle polarized observations: validation and comparison

2021 ◽  
Vol 14 (2) ◽  
pp. 1655-1672
Author(s):  
Yang Zhang ◽  
Zhengqiang Li ◽  
Zhihong Liu ◽  
Yongqian Wang ◽  
Lili Qie ◽  
...  
Keyword(s):  
Optical Parameter ◽  
Absolute Error ◽  
Retrieval Algorithm ◽  
Polarization Data ◽  
Moderate Resolution ◽  
Fine Mode ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Remote Sensing Methods ◽  
Observation Results

Abstract. The aerosol fine-mode fraction (FMF) is an important optical parameter of aerosols, and the FMF is difficult to accurately retrieve by traditional satellite remote sensing methods. In this study, FMF retrieval was carried out based on the multiangle polarization data of Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from Lidar (PARASOL), which overcame the shortcomings of the FMF retrieval algorithm in our previous research. In this research, FMF retrieval was carried out in China and compared with the AErosol RObotic NETwork (AERONET) ground-based observation results, Moderate Resolution Imaging Spectroradiometer (MODIS) FMF products, and Generalized Retrieval of Aerosol and Surface Properties (GRASP) FMF results. In addition, the FMF retrieval algorithm was applied, a new FMF dataset was produced, and the annual and quarterly average FMF results from 2006 to 2013 were obtained for all of China. The research results show that the FMF retrieval results of this study are comparable with the AERONET ground-based observation results in China and the correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), and the proportion of results that fall within the expected error (Within EE) are 0.770, 0.143, 0.170, and 65.01 %, respectively. Compared with the MODIS FMF products, the FMF results of this study are closer to the AERONET ground-based observations. Compared with the FMF results of GRASP, the FMF results of this study are closer to the spatial variation in the ratio of PM2.5 to PM10 near the ground.

scholarly journals Evaluation of JAXA Himawari-8-AHI Level-3 Aerosol Products over Eastern China

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 215 ◽  
Author(s):  
Ding Li ◽  
Kai Qin ◽  
Lixin Wu ◽  
Jian Xu ◽  
Husi Letu ◽  
...  
Keyword(s):  
Eastern China ◽  
Retrieval Algorithm ◽  
High Temporal Resolution ◽  
Aerosol Model ◽  
Significant Difference ◽  
Moderate Resolution ◽  
Level 3 ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces

A novel geostationary satellite, the H8/AHI (Himawari-8/Advanced Himawari Imager), greatly improved the scan times per day covering East Asia, and the operational products have been stably provided for a period of time. Currently, atmospheric aerosol pollution is a major concern in China. H8/AHI aerosol products with a high temporal resolution are helpful for real-time monitoring of subtle aerosol variation. However, the H8/AHI aerosol optical thickness (AOT) product has been updated three times since its launch, and the evaluation of this dataset is currently rare. In order to validate its accuracy, this study compared the H8/AHI Level-3 (L3) hourly AOT products of all versions with measurements obtained from eleven sunphotometer sites located in eastern China from 2015 to 2018. Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 AOT products from the same period were also used for inter-comparison. Although the H8/AHI AOT retrievals in version 010 show a moderate agreement with ground-based observations (correlation coefficient (R): 0.66–0.85), and the time series analysis shows that it can effectively monitor hourly variation, it suffers from an obvious underestimation of 0.3 compared to ground-based and MODIS observations. After the retrieval algorithm updated the predefined aerosol model, the overall underestimation of AHI AOTs was solved (version 010 slope: 0.43–0.62, version 030 slope: 0.75–1.02), and the AOTs in version 030 show a high agreement with observations from ten sites (R: 0.73–0.91). In addition, the surface reflectance dataset derived from the minimum reflectivity model in version 010 is inaccurate in parts of eastern China, for both “bright” and “dark” land surfaces, which leads to the overestimation of the AOT values under low aerosol loads at the Beijing and Xianghe sites. After the update of the surface dataset in version 030, this phenomenon was alleviated, resulting in no significant difference in scatterplots under different surface conditions. The AOTs of H8/AHI version 030 show a significant improvement compared to the previous two versions, but the spatial distribution of AHI is still different from MODIS AOT products due to the differences in sensors and algorithms. Therefore, although the evaluation in this study demonstrates the effectiveness of H8/AHI AOT products for aerosol monitoring at fine temporal resolutions, the performance of H8/AHI AOT products needs further study by considering more conditions.

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