4.7 Article

CloudSat-Based Assessment of GPM Microwave Imager Snowfall Observation Capabilities

期刊

REMOTE SENSING
卷 9, 期 12, 页码 -

出版社

MDPI AG
DOI: 10.3390/rs9121263

关键词

snowfall detection; GPM; CloudSat; CPR; CALIPSO; high latitudes; passive microwave; remote sensing of precipitation

资金

  1. EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF) Federated Activity [H_SAF_FA15_01]
  2. EUMETSAT H SAF [H_SAF_FA15_01, CDOP-2]
  3. EU DG Research 7th Framework Programme [17]
  4. EUMETSAT H-SAF
  5. CNR Short Term Mobility Program
  6. Italian Research Project of National Interest (PRIN) [4WX5NA]
  7. NASA [NNX16AE21G, NNX14AB22G]
  8. PMM Research Program
  9. EUMETSAT
  10. NASA [686877, NNX14AB22G, 906451, NNX16AE21G] Funding Source: Federal RePORTER

向作者/读者索取更多资源

The sensitivity of Global Precipitation Measurement (GPM) Microwave Imager (GMI) high-frequency channels to snowfall at higher latitudes (around 60 degrees N/S) is investigated using coincident CloudSat observations. The 166 GHz channel is highlighted throughout the study due to its ice scattering sensitivity and polarization information. The analysis of three case studies evidences the important combined role of total precipitable water (TPW), supercooled cloud water, and background surface composition on the brightness temperature (TB) behavior for different snow-producing clouds. A regression tree statistical analysis applied to the entire GMI-CloudSat snowfall dataset indicates which variables influence the 166 GHz polarization difference (166 TB) and its relation to snowfall. Critical thresholds of various parameters (sea ice concentration (SIC), TPW, ice water path (IWP)) are established for optimal snowfall detection capabilities. The 166 TB can identify snowfall events over land and sea when critical thresholds are exceeded (TPW > 3.6 kgm-2, IWP > 0.24 kgm-2 over land, and SIC > 57%, TPW > 5.1 kgm-2 over sea). The complex combined 166 TB-TB relationship at higher latitudes and the impact of supercooled water vertical distribution are also investigated. The findings presented in this study can be exploited to improve passive microwave snowfall detection algorithms.

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