Impacts of Shape Assumptions on Z–R Relationship and Satellite Remote Sensing Clouds Based on Model Simulations and GPM Observations
In this study, the spherical particle model and ten nonspherical particle models describing the scattering properties of snow are evaluated for potential use in precipitation estimation from spaceborne dual-frequency precipitation radar. The single scattering properties of nonspherical snow particle...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/6/1556 |
| _version_ | 1827747773884137472 |
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| author | Liting Mai Shuping Yang Yu Wang Rui Li |
| author_facet | Liting Mai Shuping Yang Yu Wang Rui Li |
| author_sort | Liting Mai |
| collection | DOAJ |
| description | In this study, the spherical particle model and ten nonspherical particle models describing the scattering properties of snow are evaluated for potential use in precipitation estimation from spaceborne dual-frequency precipitation radar. The single scattering properties of nonspherical snow particles are computed using discrete dipole approximation (DDA), while those of spherical particles are determined using Mie theory. The precipitation profiles from WRF output are then input to a forward radiative transfer model to simulate the radar reflectivity at Ka-band and Ku-band. The results are validated with Global Precipitation Mission Dual-Frequency Precipitation Radar measurements. Greater consistency between the simulated and observed reflectivity is obtained when using the sector- and dendrite-shape assumptions. For the case in this study, when using the spherical-shape assumption, radar underestimates the error of the cloud’s top by about 300 m and underestimates the error of the cloud’s area by about 15%. As snowflake shapes change with temperature, we use the range between −40 °C and −5 °C to define three temperature layers. The relationships between reflectivity (Z) and precipitation rate (R) are fitted separately for the three layers, resulting in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="normal">Z</mi><mo>=</mo><mn>134.59</mn><mo>·</mo><msup><mi mathvariant="normal">R</mi><mrow><mn>1.184</mn></mrow></msup></mrow></semantics></math></inline-formula> (sector) and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="normal">Z</mi><mo>=</mo><mn>127.35</mn><mo>·</mo><msup><mi mathvariant="normal">R</mi><mn>1.221</mn></msup></mrow></semantics></math></inline-formula> (dendrite) below −40 °C. |
| first_indexed | 2024-03-11T05:57:01Z |
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| id | doaj.art-25f623e995a44984aa8c569d60c61b9e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T05:57:01Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-25f623e995a44984aa8c569d60c61b9e2023-11-17T13:38:42ZengMDPI AGRemote Sensing2072-42922023-03-01156155610.3390/rs15061556Impacts of Shape Assumptions on Z–R Relationship and Satellite Remote Sensing Clouds Based on Model Simulations and GPM ObservationsLiting Mai0Shuping Yang1Yu Wang2Rui Li3School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, ChinaSchool of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, ChinaSchool of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, ChinaSchool of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, ChinaIn this study, the spherical particle model and ten nonspherical particle models describing the scattering properties of snow are evaluated for potential use in precipitation estimation from spaceborne dual-frequency precipitation radar. The single scattering properties of nonspherical snow particles are computed using discrete dipole approximation (DDA), while those of spherical particles are determined using Mie theory. The precipitation profiles from WRF output are then input to a forward radiative transfer model to simulate the radar reflectivity at Ka-band and Ku-band. The results are validated with Global Precipitation Mission Dual-Frequency Precipitation Radar measurements. Greater consistency between the simulated and observed reflectivity is obtained when using the sector- and dendrite-shape assumptions. For the case in this study, when using the spherical-shape assumption, radar underestimates the error of the cloud’s top by about 300 m and underestimates the error of the cloud’s area by about 15%. As snowflake shapes change with temperature, we use the range between −40 °C and −5 °C to define three temperature layers. The relationships between reflectivity (Z) and precipitation rate (R) are fitted separately for the three layers, resulting in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="normal">Z</mi><mo>=</mo><mn>134.59</mn><mo>·</mo><msup><mi mathvariant="normal">R</mi><mrow><mn>1.184</mn></mrow></msup></mrow></semantics></math></inline-formula> (sector) and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="normal">Z</mi><mo>=</mo><mn>127.35</mn><mo>·</mo><msup><mi mathvariant="normal">R</mi><mn>1.221</mn></msup></mrow></semantics></math></inline-formula> (dendrite) below −40 °C.https://www.mdpi.com/2072-4292/15/6/1556shape of snowflakesradiative transferZ–R relationshipDPRdetection threshold |
| spellingShingle | Liting Mai Shuping Yang Yu Wang Rui Li Impacts of Shape Assumptions on Z–R Relationship and Satellite Remote Sensing Clouds Based on Model Simulations and GPM Observations Remote Sensing shape of snowflakes radiative transfer Z–R relationship DPR detection threshold |
| title | Impacts of Shape Assumptions on Z–R Relationship and Satellite Remote Sensing Clouds Based on Model Simulations and GPM Observations |
| title_full | Impacts of Shape Assumptions on Z–R Relationship and Satellite Remote Sensing Clouds Based on Model Simulations and GPM Observations |
| title_fullStr | Impacts of Shape Assumptions on Z–R Relationship and Satellite Remote Sensing Clouds Based on Model Simulations and GPM Observations |
| title_full_unstemmed | Impacts of Shape Assumptions on Z–R Relationship and Satellite Remote Sensing Clouds Based on Model Simulations and GPM Observations |
| title_short | Impacts of Shape Assumptions on Z–R Relationship and Satellite Remote Sensing Clouds Based on Model Simulations and GPM Observations |
| title_sort | impacts of shape assumptions on z r relationship and satellite remote sensing clouds based on model simulations and gpm observations |
| topic | shape of snowflakes radiative transfer Z–R relationship DPR detection threshold |
| url | https://www.mdpi.com/2072-4292/15/6/1556 |
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