Microphysics Schemes W.-K. Tao S. Lang , J. Chern, T. Matsui, X. Li, - PowerPoint PPT Presentation

Microphysics Schemes W.-K. Tao S. Lang , J. Chern, T. Matsui, X. Li, T. Iguchi, D. Wu NASA Goddard Space Flight Center All microphysical schemes have their own set of unique assumptions and capabilities. It is critical therefore to sample and evaluate model performance over a comprehensive range of cloud and precipitation systems. There is “no measurements” on cloud and microphysical processes! There is no “ perfect ” microphysical scheme (parameterization!) Goddard Cloud Library http://cloud.gsfc.nasa.gov/ 1/30 + 1

2 Tao and Moncrieff (2009)

Issues for Microphysics Schemes What are the main characteristics and differences / similarities of these microphysics schemes? One-moment, two-moment, three-moment, spectral bin microphysics Assumed or pre-determined parameters and transfer processes between cloud species What is the sensitivity of model resolution on the performance of the microphysics schemes? (1, 2, 3.5, or 7 km) What are the main methods to evaluate the performance of these microphysics schemes? Ground, Aircraft and Satellite observations What are the main issues for inter-comparison studies on different microphysics schemes? What are the main uncertainties of microphysics (processes) schemes? 3

120 Papers Ice Microphysics Developments 4

Tao, W.-K., D. Wu, S. Lang, J. Chern, C. Peters-Lidard, A. Fridlind, and T. Matsui, 2016: High-resolution NU-WRF model simulations of MC3E, deep convective-precipitation systems: Comparisons between Goddard microphysics 5 schemes and observations , J. Geophys. Res ., 121, 1278-1306. doi:10.1002/2015JD023986.

Fifteen 1-M or 2-M 3-Ice schemes Two 3-M schemes Three 4-Ice schemes One P3 scheme Bin microphysical scheme explicitly resolves hydrometeor size distributions using 43 mass double size bins. There is no need to assume any pre-defined particle size distributions. Eight different species, i.e., the aerosols serving as CCN, liquid drops, three types of pristine ice crystals (column, plate, and dendrite), snow aggregates, graupel, as well as hail are included. Riming fractions explicitly for aggregates and graupel, and melting fractions are tracked for all ice-phase are solved species. 6

Improving Bulk Microphysics in GCE Using Bin Spectral Scheme (Li, Tao et al., JAS, 2009) By assuming exp. rain Radar Observation DSD, bulk scheme artificially increases #s of small drops observation bin Bin Scheme Simulation Bin Scheme is used to correct the overestimation of rain evaporation in bulk scheme and the density and fall speed of graupel in bulk scheme Bulk Scheme (original) Bulk Scheme (Red Evap) 7

Improving spectral bin scheme using TRMM satellite Ground-based Radar Space-based Radar Microwave (TB) Ice particle collection efficiency observations simulation Bin model improvements : 1. Reduce temperature dependent ice particles collection efficiencies ; improvements 2. Adjust graupel production terms when snow aggregates or ice crystals collect cloud droplets. Li, X., W.-K. Tao, T. Matsui, C. Liu and H. Masunaga, 2010: Improving spectral bin microphysical scheme using TRMM satellite observations. Quart. J. Roy. Meteor. Soc . 136, 382–399 . 8

WRF-SBM and Polarimetric Radar Observations in MC3E 1. Hydrometeor distributions from WRF- SBM simulations were evaluated for the first time against the CSU Polarimetric HID retrievals. 2. WRF-SBM closely generated 9 different hydrometeor species vs the polariemtric retrievals including heavily rimed particles. 3. Distributions are highly sensitive to the ice- formulating nuclei. Dolan, B., T. Matsui, A. A. Matthews, S. A. Rutledge , W. Xu, W.-K. Tao, T. Iguchi, V. Chandrasekar , 2016: Multi-sensor Radar Observations and Size-Resolving Cloud Modeling Analysis of the 25 April 2011 MC3E Convective Case, (to be submitted to MWR) 9

S-band echo top height simulated by 3 different Models Same Microphysics Scheme (Morrison) – Li et al. (2017) WRF GCE SAM 10

S-band echo top height simulated by three different Models Same microphysics scheme (Morrison) – Li et al. (2017) WRF GCE SAM SAM 11

S-band echo top height simulated by GCE with different microphysics (Morrison vs Goddard 3ICE) Morrison Goddard 12

Contoured Frequency Altitude Diagrams (CFADs) Observation 4ICE 3ICE ( Graupel ) Morrison (Graupel) WDM6 - 7 Morrison (Hail) Thompson WSM6 4ICE simulated CFAD agrees very well with observations Wu/Tao et al. (2015) Morrison 3ICE-Hail simulated CFAD agrees better with observations than the 3ICE-Graupel schemes (Goddard, Morrison, and WSM6) 13

4ICE Morrison WSM6 IMERG 2015-12-03 00:00 UTC 2015-12-03 15:00 UTC 4ICE Morrison WSM6 14

No measurement : Microphysics Processes! What are the uncertainties of cloud/microphysical processes? The vertical profiles of the cloud/precipitation properties in convective and stratiform regions, mixed phase (melting, riming, ice processes), life cycle Need to have the following measurements of cloud properties • 3D vertical velocity structures; • High temporal resolution aerosol/CCN measurements; • Vertical (ice, liquid) hydrometeor particles (droplet spectrum, condensation, size, density) measurements; • Comprehensive polarmetric radar measurements (i.e., S/C- band ground-based for convective cores and air/space borne or vertically pointing X/K-band for anvil/stratiform characteristics) 15

Implemented in GCE and MMF GCE: 4-ICE Scheme RAMS 2-M Morrison 2-M JP Chen 2-M 2-M 4ICE Scheme CaPPM Major characteristics of Goddard 4-ICE scheme and three two-moment schemes (RAMS, JP Chen and Morrison). The similarities and differences between these schemes are shown. 16

Tropical MCS Identify the important microphysics processes in the CRM Also used for improve GCM performance (next 2 slices) Larger letter -> more important Numerical number -> where is occurred Tao, W.-K., J. Simpson, S. Lang, M. McCumber, R. Adler and R. Penc, 1990: An algorithm to estimate the 17/30 heating budget from vertical hydrometeor profiles. J. Appl. Meteor., 29 , 1232-1244.

TRMM and GPM Latent Heating Wei-Kuo TAO Y. N. Takayabu, S. Lang, S. Shige, and D. Wu What are the TRMM LH products? What are the TRMM LH applications? How can TRMM LH be validated? What are GPM LH products? (Sept 2017) Tao, W.-K., Y. N. Takayabu, S. E. Lang, W. Olson, S. Shige, A. Hou, G. M. Skofronick-Jackson, X. Jiang, K.-M. Lau, T. Krishnamurti, D. Waliser, C. Zhang, R. Johnson, R. Houze, P. Ciesielski, M. Grecu, S. Hagos, R. Kakar, N. Nakamura, S. Braun, and A. Bhardwaj, 2016: TRMM Latent Heating Retrieval: Applications and Comparisons with Field Campaigns and Large-Scale Analyses, Amer. Meteor. Soc. Meteorological Monographs - Multi-scale Convection-Coupled Systems in the Tropics, 56, Chapter 2, doi: 10.1175/AMSMONOGRAPHS-D-15-0013.1 TRMM Diabatic Heating Special Collection (J. Climate, 2009, 2010) 18

CRM Simulated Q 1 Budget LH: Latent Heat - phase change of water Eddy - heat transport by cloud dynamics Purple: Simulated Q 1 Green: Observed Q 1 LH Rainfall + Sensible heat fluxes Q R Edd Sounding Estimated Q 1 Budget y (Yanai et al. 1973) Q 1 Q R : Radiation • Role of convection in tropical intraseasonal variability and quasi-stationary circulation/ITCZ/MJO • Improvement/Validation of Cumulus parameterization in GCMs/Climate Models 19

Similarities and Differences between SLH and CSH Algorithm Convective – Stratiform Separation Method GCE vs PR Look-Up Table GCE simulated cases Domain (256-512 km) vs sub-domain (64 km) averaged Horizontal and vertical eddy fluxes Radiation 20

TRMM Standard LH Products GPM L80 Pixel Gridded (0.5 o ) Orbital Monthly Gridded (0.5 o ) research standard standard LH 21

Array, 2011 D. Johnson and P. Ciesielski DYNAMO AMMA CSH (PR): 6.56 mm/day, 43% Northern stratiform Array TRMM 3B42: 6.6 mm/day Q2 budget: 5.5 mm/day NAME CSH (PR): 8.43 mm/day. Southern 45% stratiform Array TRMM 3B42: 6.3 mm/day Gauge network: 7.2 mm/day SLH derived LH also agree with sounding estimated for DYNAMO 22

TRMM Derived Rainfall CSH Performance (Lang et al 2017) 7-km LH 2-km LH 1 ∫ ∫ P − ∆ ∆ = + base ( Q Q ) p x LP S 1 R o o g Lx Ptop P o is surface rainfall S o is surface sensitive flux 23

SLH L2/L3 V04 Evaluations (TRMM/ GPM ) Horizontal distributions of three-month mean Q1R [K/day] TRMM PR V7A GPM DPR ITE057 7km 2km Good agreements in horizontal distributions between PR-SLH and DPR- 02/23/2016 JPST SLH are found in the TRMM region 24

4ICE: Cloud ice, snow, graupel and hail CSH and SLH team will use the same cases for GPM! 25

Winter Storm (3) Cases NEXRAD NU-WRF NEXRAD NU-WRF 03/16/2014 18:00 UTC NEXRAD NU-WRF 02/17/2015 03:00 UTC NEXRAD NU-WRF 02/21/2015 18:00 UTC 26

Goddard GPM LH LUTs • Model simulations (dx=1 km, 60 vertical layers) • Derive variables corresponding to GPM combined product – Freezing level height – Storm top height – 3D reflectivity • Anvil region • Height of maximum dBZ • Composited dBZ • Construct bins (e.g. every 2 km in altitude) • Create heating table for categorized regions 27

Evaluation: Consistency Check 28

Maximum LH [20140316 22:00 UTC] NU-WRF GPM with threshold NU-WRF CSH with threshold Threshold: GPM reflectivity > 13 dBZ 29

CSH NU-WRF GPM GPM without threshold <-> 30/30