Title: Remote sensing and modeling of cloud contents and precipitation efficiency
1Remote sensing and modeling of cloud contents and
precipitation efficiency
Chung-Hsiung Sui Institute of Hydrological
Sciences National Central University Xiaofan
Li Joint Center for Satellite Data Assimilation
and NOAA/NESDIS/Office of Research and
Applications
On-going collaborations Ming-Dah Chou
(National Taiwan Univ.) Ming-Jen Yang (IHS,
NCU) Radar and regional modeling groups, IAP,
NCU Chang-Hoi Ho (Seoul National Univ.)
2Link of cloud contents to microphysicsthrough
satellite measurements and cloud models
Cloud ratio IWP LWP Rate ratio (PDEPPSDEPPGDEP) PCND CMPE Ps (PDEPPSDEPPGDEPPCND)
QPE Climate feedback processes? A 2D
version of the Goddard Cumulus Ensemble Model
TOGA COARE experiments? 3D non-hydrostatic
regional models, MM5 and WRF Typhoon
simulations
3Satellite measured and simulated cloud contents
- global oceanic tropics on March 2003
- Microwave Surface and Precipitation
NCEP/Global Forecast System (GFS) - Products System (MSPPS)
4MSPPS C
- 6-hourly data from three satellites (NOAA-15,
16, 17) are used in the MSPPS data whereas hourly
data are analyzed in C.
5Cloud and rate ratios
Cloud ratio IWP LWP Rate ratio (PDEPPSDEPPGDEP) PCND
A 2D version of the Goddard Cumulus Ensemble
Model is forced by the vertical velocity derived
from the Tropical Ocean Global Atmosphere Coupled
OceanAtmosphere Response Experiment (TOGA
COARE).
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7rate ratio 1
S
M
rate ratio approaches 0
rate ratio 0.1
rate ratio gt1
C
S
M
cloud ratio gt1
cloud ratio 1
cloud ratio 0.4
cloud ratio approaches 0
C
8 Cloud ratio IWP LWP Rate ratio (PDEPPSDEPPGDEP) PCND CMPE Ps (PDEPPSDEPPGDEPPCND)
Stratiform 2.10 2.10 0.48
Convective 0.13 0.03 0.72
Mixed 0.60 0.30 1.01
Cloud microphysical budgets in stratiform and
convective regimes
Stratiform (cloud ratio gt1 or rate ratiogt1)
Convective (cloud ratiolt0.4 or rate ratiolt0.1)
9Cloud ratio and microphysics
10rain rates lt 0.3 mm h-1 rain rates gt
0.3 mm h-1
melting of graupel and accretion of cloud water
by precipitation ice vapor deposition
and condensation Rainfall and evaporation of
rain Unit is h-1.
11Column averaged water budgets
Precipitation efficiency
,
SIqv PCND PDEP PSDEP PGDEP
SOqv PREVP PMLTG PMLTS
LSPE
CMPE
1
?
12Short-term averaged budgets(hourly)
What processes determine CMPE ?CONVc , vertical
velocity, wind shear
13Long-term averaged budgets(longer than daily)
What factors determine CMPE ?Temperature,
humidity (land vs ocean surface),CCN
concentration, etc.
14processes
Realistic simulations2D GCE COARE
experimentThe 3D cloud-resolving modeling is
based on the MM5 simulation of Typhoon Nari
(2001).
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16Simulated Track
Simulated Intensity
17 (a) surface rainrate (mm h-1) (b) LSPE
18 (c) CMPE (d) SOqv/SIqv
19 (e) positive CONVc/SIqv (f) negative
CONVc/SIqv
20118 km2
96 km
59 km2
48 km
30 km2
24 km
21118 km2
96 km
59 km2
48 km
30 km2
24 km
22118 km2
96 km
59 km2
48 km
30 km2
24 km
23FactorsIdealized experiments
24Summary
- Cloud ratio is statistically related to rate
ratio? Time rate of change of rate ratio is
derived as a function of three groups of
microphysics processes Precipitation
efficiency (short-term average)? Es CONVqv
SIqv regardless of the average area ? LSPE
CMPE. ? Function of (CONVC , PS) (other
processes ?) Precipitation efficiency (long-term
average)? Function of Ts (other factors ?)
25Further research TRMM/GPM application
? Statistic analysis (like probability
distributions) of LWP, IWP, CR, CR tendency, and
Ps in different large-scale disturbances and
environments using satellite data. ? Evaluation
of simulated LWP, IWP, CR, CR tendency, Ps , and
precipitation efficiency in different models
using explicit cloud micro-physics schemes
against satellite derived quantities. ?
Investigations of responses of water vapor and
clouds (LWP, IWP, CR, and CR tendency) to climate
forcing anomalies.
26FDDA
MOTHER DOMAIN (90 km)
NESTED DOMAIN (30 km)
OBS(NRA1)
27Next steps
- 1. Further refinements better spectral
constraints (Aref), - reduce model physical and computational
errors - 2. Finer resolution in the cyclogenesis region
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29Improve the prognostic cloud microphysics scheme
in the atmosphere regional model to predict the
formation and transport of hydrometeors.
Combine radar and satellite measurements with
the cloud (microphysics) model for cloud and
rainfall estimate in severe weather
30Remote sensing and modeling of cloud contents and
precipitation efficiency
Effect on weather and climate Cloud microphysics
and cloud dynamics Mesoscale and large-scale
circulation Parameterization and
prediction Quantitative rainfall estimate ? rain
gauges (bucket, optical, acoustic) spatial
resolution ? radar Z-R relations
(microphysics), localized ? satellite (IR,
microwave) space and time sampling,
micro-physics, cloud optical properties,
radiative transfer ? validation