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

Huo, Juan; Lü, Daren; Duan, Suqing; Bi, Yanfeng; Liu, Bo

doi:10.5194/amt-2019-276

Cited by 3 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Clouds are the major factor that controls water balance and energy in the Earth. Also, the cloud condition is characterized by often uncertain sources and components, [1]. A cloud can be defined, according to the American Meteorological Society's Glossary of Meteorology, as a visible aggregate of minute water droplets and/or ice particles in the atmosphere above the Earth's surface, [2].…”

Section: Introductionmentioning

confidence: 99%

The Digital Change Detection for Low Resolution Satellite Images in Weathering Estimation

Mahdi

2023

Iraqi Journal of Science

View full text Add to dashboard Cite

The detection and estimation of weathering conditions have become a very important daily necessity in our life. For this purpose, several satellites of low resolution imagery were launched by the weathering and environmental agencies. The important weather paremeters are temperuter, wind direction, velocity, clould and humidity, etc. The low resolution images often deal with large-scale phenomena and the interpretation and projection of the produced data requires continuous development of tools and criteria. In this paper, the low spatial resolution data generated by the moderate resolution imaging spectroradiometer (MODIS) were used to monitor the cloud density and direction above Iraq and its neighboring countries for the period from 14-12-2021 to 23-12-2021. The MODIS reflectance and surface temperature (HDF format) data were used and processed to achieve the purpose of this research. The reflectance data were projected according to a sinusoidal system due to the presence of three Earth zones distributions (37, 38, and 39, N). The cloud density was estimated from the digital values and the wind direction was estimated from the bands animation. The direction of wind for the cloudy condition was from the North-East. The digital data processing included data preparation and selection, georeference (adding a projection system), features extraction, and displaying the final results. All data were evaluated using ENVI (Environment for Visualizing Images, ver. 4.5.)

show abstract

Section: Introductionmentioning

confidence: 99%

The Digital Change Detection for Low Resolution Satellite Images in Weathering Estimation

Mahdi

2023

Iraqi Journal of Science

View full text Add to dashboard Cite

show abstract

“…Ground‐based detection techniques include millimetre‐wave cloud radar (MMCR), laser ceilometer, etc. The MMCR and laser ceilometer can accurately obtain the cloud vertical structure with high temporal and spatial resolution and can achieve continuous observation, which are very effective detection tools (Huo et al, 2020; Kollias et al, 2007; Zhou et al, 2019). In particular, MMCR, whose wavelength is closer to the scale of small particles, utilizes the scattering characteristics of electromagnetic waves by cloud particles (Liu et al, 2015, 2017).…”

Section: Introductionmentioning

confidence: 99%

Fine vertical structures of cloud from a ground‐based cloud radar over the western Tianshan mountains

Chen

Yang

Zeng

et al. 2022

Meteorological Applications

View full text Add to dashboard Cite

In this study, the grounded‐based Ka‐band millimetre‐wave cloud radar (MMCR) is used to analyse the cloud characteristics over the western Tianshan mountains. The cloud top height (CTH) obtained by MMCR is verified by comparing it with the Fengyun‐4A (FY‐4A) observations. Overall, the MMCR‐obtained CTHs are attenuated and lower than the FY‐4A‐obtained CTHs under precipitation conditions. Thus, the FY‐4A data is used to complement MMCR data when there is rainfall. The diurnal, seasonal variation and vertical structures of the cloud are further examined using the combination of MMCR and FY‐4A. The result indicates that the CTH and cloud base height (CBH) are highest in summer and lowest in winter. Also, clouds tend to form frequently at night in spring, summer, and winter. Although in autumn, clouds tend to form most frequently in the morning. This may be related to the diurnal variation of temperature, humidity, wind speed, and wind direction. Moreover, the CTHs occur most frequently at heights of 8–9 km in spring and autumn, 9–10 km in summer, and 7–8 km in winter. The high CTHs caused by the strong convective activities in summer may be related to sufficient water vapour transport. These corrected CTH data are also used to classify cloud types, the results indicate that the proportion of high clouds is highest in summer, while the proportion of medium clouds is lower than in the other three seasons. Also, the average CTH of the low, medium, and high clouds is highest in summer and lowest in winter.

show abstract

“…The primary objective of this study was to assess the performance of cloud retrievals from AHI onboard Himawari‐8 (Himawari‐8/AHI) observation by using CSPP‐GEO. Although similar studies had been conducted (e.g., Huo et al, 2020; Lai et al, 2019; Letu et al, 2019; Tan et al, 2019), the cloud properties have not been comprehensively evaluated with either active or passive instrument (e.g., CPR, CALIOP, or MODIS) in an unstable atmospheric condition. In particular, the variability and bias of AHI cloud properties will be quantified as a function of cloud phases, CTH, and COT, which will lead to improved utilization of AHI radiances such as the assimilation of cloudy radiances in numerical weather prediction models.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Cloud‐Top Property Retrievals From Advanced Himawari Imager, MODIS, CloudSat/CPR, CALIPSO/CALIOP, and Radiosonde

et al. 2020

View full text Add to dashboard Cite

The information on cloud properties and microphysical characteristics is critical for environmental research and application, such as that on weather, climate, hydrology, and green energy and Earth energy budget. The launch of the new‐generation geostationary satellite, for example, the Japanese Himawari‐8, enables retrieval of cloud information through multichannel observation. To confirm the retrievals from the Advanced Himawari Imager (AHI) onboard Himawari‐8 (Himawari‐8/AHI), this study accessed the cloud retrievals from AHI and compare them against those obtained from spaceborne passive and active sensors on the low Earth orbit satellites, such as NASA's CloudSat, Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The atmospheric thermodynamic state from in situ radiosonde provides another dimension for evaluating the retrieved cloud‐top temperature and height, which were obtained and analyzed during two research cruises over the South China Sea during monsoon onset season with large cloud variability to ensure the comprehensive intercomparisons. The findings show that the cloud‐top altitude, cloud optical thickness, and cloud effective particle radius retrieved from AHI are consistent with passive Moderate Resolution Imaging Spectroradiometer (MODIS) data. Furthermore, both spaceborne active Cloud Priofiling Radar (CPR) and Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) data confirm the low uncertainty of cloud‐top altitude, particularly when the cloud is optically thick. Large cloud‐top altitude discrepancy among these data in the optically thin cloud might be due to the limited AHI spectral channels or instrumental spatial resolutions. The cloud‐top temperature and altitudes in either liquid or ice phase cloud agree well with collocated sounding profiles, with low difference of 1 K and 170 m, respectively.

show abstract

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

Cited by 3 publications

References 12 publications

The Digital Change Detection for Low Resolution Satellite Images in Weathering Estimation

The Digital Change Detection for Low Resolution Satellite Images in Weathering Estimation

Fine vertical structures of cloud from a ground‐based cloud radar over the western Tianshan mountains

Comparison of Cloud‐Top Property Retrievals From Advanced Himawari Imager, MODIS, CloudSat/CPR, CALIPSO/CALIOP, and Radiosonde

Contact Info

Product

Resources

About