Intercomparison of Vertical Structure of Storms Revealed by Ground-Based (NMQ) and Spaceborne Radars (CloudSat-CPR and TRMM-PR)

Fall, Veronica; Cao, Qing; Hong, Yang

doi:10.1155/2013/270726

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…At approximately UTC 15:33:45, a region with enhanced reflectivity at 3 km (maximum ∼12 dbZ) decreases in altitude as the satellite moves northwest along its track (Figure 2b). The slight reduction in reflectivity around 2 km altitude, along with the coincident increase in temperature, likely indicates melting and disintegration of snowflakes [49,50]. The region with a sharp reduction in reflectivity centered at UTC 15:33:55 is associated with an area of non-precipitation.…”

Section: Detection Of Precipitation Occurrence and Phasementioning

confidence: 95%

Validation of CloudSat-CPR Derived Precipitation Occurrence and Phase Estimates across Canada

Kodamana

Fletcher

2021

Atmosphere

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Snowfall affects the terrestrial climate system at high latitudes through its impacts on local meteorology, freshwater resources and energy balance. Precise snowfall monitoring is essential for cold countries such as Canada, and particularly in temperature-sensitive regions such as the Arctic; however, its size and remote location means the precipitation gauge network there is sparse. While satellite remote sensing of snowfall from instruments such as CloudSat-CPR offers a potential solution, satellite detection of precipitation phase has not been systematically evaluated across Canada. In this study, CloudSat-based precipitation occurrence and phase retrievals were validated at 26 stations across Canada maintained by Environment and Climate Change Canada (ECCC). Probability of Detection (POD), defined as the percentage agreement between coincident CloudSat and human-observed present weather information for precipitation (solid, liquid or no precipitation), and False Alarm Ratio (FAR) were used as the primary metrics for validation. The mean POD (FAR) for precipitation occurrence across Canada is 65.5% ± 4.3 (31.4% ± 5.1) and for no precipitation is 90.6% ± 1.4 (11% ± 2.5). The results show lower rates of detection under cloudier skies, in the presence of (freezing) drizzle and for lighter snowfall, which may be explained by a large number of false-positives due to CloudSat-CPR’s high instrumental sensitivity. When CloudSat correctly detects the occurrence of precipitation, it shows uniformly high POD (>80%) and low FAR (<10%) for classifying the phase of precipitation. Large databases of coincident ground and satellite measurements allow us to provide a new estimate of around 9% for the frequency of virga events, a factor of two smaller than a previous estimate for the Arctic. The results from this study show that CloudSat has useful accuracy in detecting precipitation occurrence and very high accuracy at classifying precipitation phase, over diverse climate zones across Canada. As such, there is significant potential for satellite monitoring of snowfall in remote, cold regions.

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Section: Detection Of Precipitation Occurrence and Phasementioning

confidence: 95%

Validation of CloudSat-CPR Derived Precipitation Occurrence and Phase Estimates across Canada

Kodamana

Fletcher

2021

Atmosphere

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“…The results demonstrated that the reflectivity from CloudSat CPR was approximately 10 dBZ lower than that of TRMM PR below a height of 4 km. Fall et al (2013) analyzed the vertical structure of storms utilizing data from CloudSat CPR, TRMM PR, and ground-based radar [10]. They further conducted multi-frequency measurements of microphysical quantities within different regions of the melting layer and carried out comparisons among them.…”

Section: Introductionmentioning

confidence: 99%

Comparison and Synthesis of Precipitation Data from CloudSat CPR and GPM KaPR

Liang,

Kou,

Huang

et al. 2024

Remote Sensing

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Employing different bands of radar to detect precipitation information in identical regions enables the acquisition of a more comprehensive precipitation cloud structure, thereby refining the continuity and completeness of precipitation measurements. This study first compared the coincident data from CloudSat W-band cloud profiling radar (CPR) and Global Precipitation Measurement Mission (GPM) Ka-band precipitation radar (KaPR) from 2014 to 2017, and then a synthesis of the radar reflectivity from CPR and KaPR was attempted to obtain a complete cloud and precipitation structure. The findings of the reflectivity comparisons indicated that the echo-top height identified by CPR is on average 3.6 to 4.2 km higher than that from KaPR, due to the higher sensitivity. Because of strong attenuation of CPR by liquid-phase particles, the reflectivity below the height of the melting layer usually shows an opposite gradient to KaPR with decreasing altitude. The difference in the near-surface rain rates of CPR and KaPR was found to be related to reflectivity gradients in the vertical direction, and the larger the reflectivity gradients, the greater the differences in near-surface rain rates. For better representing the complete vertical structure of precipitation clouds and improving the consistency of the reflectivity and precipitation rate, the radar reflectivity was weighted, synthesized from CPR and KaPR based on the gradient difference of the reflectivity from the two radars. We presented the synthesis results for a stratiform cloud and a deep convective case, and Spearman’s rank correlation coefficient (rs) between the GPM combined radiometer precipitation rate and the radar reflectivity was utilized to analyze the performance of the synthesis. The consistency between synthesized reflectivity and precipitation rate in the non-liquid phase was improved compared with KaPR, and the rs of the ice and mixed phases was increased by about 12% and 10%, respectively.

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Intercomparison of Vertical Structure of Storms Revealed by Ground-Based (NMQ) and Spaceborne Radars (CloudSat-CPR and TRMM-PR)

Cited by 2 publications

References 6 publications

Validation of CloudSat-CPR Derived Precipitation Occurrence and Phase Estimates across Canada

Validation of CloudSat-CPR Derived Precipitation Occurrence and Phase Estimates across Canada

Comparison and Synthesis of Precipitation Data from CloudSat CPR and GPM KaPR

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