Combining Satellite High Frequency Microwave Radiometer & Surface Cloud Radar Data for Determination of Large Scale 3 D Cloud IWC 서은경

Transcription

1 11/21/2008 제9회 기상레이더 워크숍 Combining Satellite High Frequency Microwave Radiometer & Surface Cloud Radar Data for Determination of Large Scale 3 D Cloud IWC 서은경 공주대학교 지구과학교육과 Objective: To retrieve large scale 3 D cloud IWC by combining data from NOAA satellite Advanced Microwave Sounding Unit B TBs and ground based cloud radar

2 Outline Motivation Objectives and Approach How to construct a supporting database from radar for satellite retrieval? Importance of database: manifolds problem How to make a consistent framework btw Radar and Satellite? From point to area measurement in a consistent framework Ice particle Design Radar Reflectivity IWC Relation Construction of vertical Ice Clouds TB IWP Relations at AMSU B channels TB IWP Relations on TB EOF domain Comparison of MMCR and AMSU B IWC profiles Conclusions

3 Motivation Single Column Models (supported by the Atmospheric Radiation Measurement) are used to test physical parameterizations. As forcing terms, SCMs need advection tendency of condensates besides advections of T, q, Point measurements of cloud water alone are not sufficient to derive these advection terms MMCR Satellite data provide areal coverage of water condensates es can potentially be used to derive these terms (together with other data)

4 Objectives and Approach Objectives By combining i surface radar and satellite data, Ice water path over a large area Vertical ice water content distribution over a large area 3 D ice water content distribution can be utilized to calculate ice water advection terms for single column model inputs Approach Surface radar (MMCR) provides detailed, high quality characteristics of vertical ice water content distribution Satellite (NOAA AMSU B) provides broad horizontal coverage Use surface radar data to generate database for satellite retrievals, and then use satellite data to broaden the area coverage From point measurement to area measurement in a consistent framework

5 How to construct a supporting database for satellite retrieval? observation NOAA AMSU B TB Supporting Database Linkage btw TB Ice Model Simulations? Cloud Observations? No ice Ice Retrieval Algorithm Consistency check btw TB and TB? Ice Retrieval To overcome the lack of in situ observations of IWC profiles, we take the advantage of surface radar observations

6 Importance of database: manifolds problem TB observations TB simulations i Ch 1 Ch 1 Ch 5 Ch 5 Representativeness? Ch 2 Ch 2 Ch 3 Ch 4 Ch 3 Ch 4

7 How to make a consistent framework btw Radar and Satellite? (1) Both instruments are looking at the same clouds. share the same microphysical and radiative properties. Radar MMCR At the SGP site 35 GHz (8.6 mm) Zenith pointing (90 m) Reflectivity & Doppler Data from surface to 20 km ALT Continuous observation in time (9 second) * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ** *** * * * * * * * * * * * * * * * * Satellite AMSU B 89, 150, 183.3±1, 183.3±3, 183.3±7 GHz 16 km resolution at nadir, ~2000 km swath width, cross scan Twice daily coverage per satellite (currently 3 NOAA satellites + SSMIS)

8 How to make a consistent framework btw Radar and Satellite? (2) MMCR reflectivity profile Find Z IWC relation ice microphysics single scattering MMCR Radar reflectivity IWC profile Database TB IWC profile relation Radiative transfer model

9 From point to area measurement in a consistent framework Ice particle il types Including various Ice Particle Shapes instead of solid ice particle (Liu 2004) A sector and a dendrite type for snowflakes rosettes with 3 to 6 hexagonal columns Hyemsfield et al. (2002) 100 μm: bullet rosettes and aggregates

10 From point to area measurement in a consistent framework Particle size distribution ib ti & density Particle Size Distributions based on in situ measurements of synoptically generated midlatitude ice clouds (Heymsfield et al. 2003a,b) density a gamma distribution of order μ, slope λ

11 From point to area measurement in a consistent framework Slope of the particle size distribution ib ti

12 From point to area measurement in a consistent framework Backscattering cross section To calculate backscattering cross section for the defined nonspherical ice particles, the Discrete Dipole Approximation (DDA) model is used (Liu 2004). At 35 GHz (MMCR frequency)

13 From point to area measurement in a consistent framework Radar Reflectivity tiit IWC relation From the backscattering cross section (s), the radar reflectivity can obtained from and. Frame B 10 0 By using the DDA model for the six types of cloud ice particle shapes, the Z IWC relation is derived as: IWC = Z where IWC is in g m 3 and Z in mm 6 m 3. Frame A: this study s Z IWC relations DDA calculations Frame B: Liu & Illingworth(2000) Z IWC Lorenz Mie calculations IWC (g m -3 ) 10-1 Frame A 10-2 type-a snowflakes type-b snowflakes 3-bulltet rosettes Z (dbz) 4-bullet rosettes 5-bullet rosettes 6-bullet rosettes mean for the six ice types Liu and Illingworth [2000] Mace et al. [2002] Figure. The relationships between Z and IWC.

14 From point to area measurement in a consistent framework Construction of vertical ice clouds (a) mean radar reflectivity 14 To overcome the lack of in situ 12 observations of vertical IWC 8 6 structure, we take the advantage 4 2 of surface radar observations Based on the major EOFs of MMCR radar reflectivity profiles, synthetic radar reflectivity profiles are constructed into IWC profiles. These IWC profiles serve as the inputs to a radiative transfer model dl that links TBs and IWC profiles. height(km) heig eight(km) height(km) ) (b) standard deviation 14 ) dbze dbze (c) the first EOF eigenvalues: 49% 56% (e) the third EOF eigenvalues: 11% 8% MMCR radar reflectivity height(km) heig eight(km) height(km) (d) the second EOF eigenvalues: 22% 35% (f) the fourth EOF eigenvalues: 5% 1% synthetic radar reflectivity Figure. (a) Mean, (b) standard deviation, (c-f) major EOF profiles for the observed MMCR profiles (solid lines) and the generated radar reflectivity profiles (dotted lines). The first and second numbers in the bottom of (c-f) denote the eigenvalues for the observed and generated radar reflectivity profiles.

15 From point to area measurement in a consistent framework TB IWP Relations on TB EOF domain Figure. Large circles denote AMSU B TB's at the ARM SGP site. Small circles and crosses represent AMSU B TB's, whose departure from clear sky background brightness temperatures at 89 GHz are between 25 K and 50 K and greater than 50 K, respectively, over a 10 deg x 10 deg box centered at the SGP site during March 2003.

16 Comparison of MMCR and AMSU B IWC profiles Satellite retrievals MMCR retrievals

17 Conclusions A framework to retrieve ice water path over a broad area is presented by combining observations of a surface cloud radar and satellite microwave measurements in a physically consistent way. For construction ti of model database, this study adapted d newly available ice microphysical properties from recent in situ observations and treated the single scattering properties based on DDA simulations of realistic nonspherical ice particles A new radar reflectivity ice water content relation ( IWC = 0.078Z ) was derived.