Impact of microphysics on cloud-system resolving model simulations of deep convection and SpCAM
Hugh Morrison and Wojciech Grabowski NCAR* (MMM Division, NESL)
Marat Khairoutdinov Stony Brook University
*NCAR is sponsored by the National Science Foundation
Outline
1. Motivation
- Indirect aerosol effects
2. CSRM simulations of convective radiative quasi- equilibrium
3. CSRM simulations of real case study (TWP-ICE)
4. SpCAM simulations with new microphysics scheme
Microphysics plays a key role in cloud, climate and weather models
Stephens (2005)
- Latent heating/cooling
(condensation, evaporation, deposition, sublimation, freezing, melting)
- Condensate loading
(mass of the condensate carried by the flow)
- Precipitation
(fallout of larger particles)
- Coupling with surface processes
(moist downdrafts leading to surface-wind gustiness, cloud shading)
- Radiative transfer
(mostly mass for absorption/emission of LW, particle size also important for SW)
- Cloud-aerosol-precipitation interactions
(aerosol affect clouds: indirect aerosol effects, but clouds process aerosols as well)
maritime (“clean”) continental (“polluted”) cloud
base cloud
updraft
Ship tracks: spectacular example of indirect effects caused by ship exhausts acting as CCN
(long-lasting, feedback on cloud dynamics?)
IPCC 2007; Synthesis Report
Issues:
- Difficulty of current observational techniques in untangling relationship between aerosols and
clouds on spatial and temporal scales relevant to climate:
correlation versus causality
- Traditional general circulation models cannot resolve the cloud dynamics that are critical to cloud-aerosol-precipitation interactions
parameterized microphysics in
parameterized clouds parameterization
2- Aerosol indirect effects are especially uncertain for deep convective clouds because of the complexity of microphysical processes (both liquid and ice) and close coupling between cloud-scale dynamics and
microphysics.
- High resolution cloud models (GCRMs and MMF) can resolve deep-convective and mesoscale motion and
therefore are better suited to the problem.
-
Rosenfeld et al.
Science, 2008
Example of hypothesized aerosol-
microphysics- dynamics
interactions in deep convection
Koren et al. (2010)
single-cloud reasoning versus
cloud-ensemble reasoning
Arguably, the cloud-ensemble reasoning is more appropriate for climate.
Another way to think about the problem: single-process reasoning (e.g.,
microphysics) versus the system-dynamics approach. Only the latter includes all the feedbacks and forcings in the system.
Convective-radiative quasi-equilibrium is the simplest system that includes interactions
between clouds and their environment
(“system-dynamics approach”).
Convective-radiative quasi-equilibrium mimicking planetary energy budget using a 2D cloud-system resolving model
61 levels 100 columns (200 columns)
Surface temperature = 15° C Surface relative humidity = 85%
Surface albedo = 0.15 solar input
342 Wm-2
horizontal distance
height
Grabowski J. Climate 2006, Grabowski and Morrison J. Climate 2010 (submitted)
Numerical model:
Dynamics: 2D super-parameterization model (Grabowski 2001)
Radiation: NCAR’s Community Climate System Model (CCSM) (Kiehl et al 1994) in the Independent Column Approximation (ICA) mode
100-200 columns (Δx=1-2km) and 61 levels (stretched; 12 levels below 2 km; top at 18-24 km)
Grabowski 2006; Grabowski and Morrison 2010
Simulations with the new two-moment bulk microphysics:
Warm-rain scheme of Morrison and Grabowski (JAS 2007,
2008a) predicts concentrations and mixing ratios of cloud water and rain water; relatively sophisticated CCN activation scheme, contrasting pristine and polluted CCN spectra, and better
representation of the homogeneity of subgrid-scale mixing.
Ice scheme of Morrison and Grabowski (JAS 2008b; 2010)
predicts concentrations and two mixing ratios of ice particles to keep track of mass grown by diffusion and by riming;
heterogeneous and homogeneous ice nucleation with the same IN
characteristics for pristine and polluted conditions.
Cloud water and drizzle/rain fields
Ice field Solid: polluted Dashed: pristine
Grabowski
J. Climate 2006 (G06)
Grabowski and Morrison
J. Climate 2010 (submitted) (GM10)
Solid: polluted Dashed: pristine
Horizontal bars: standard deviation of temporal evolution (measure of statistical significance of the difference)
Cloud fraction profiles
G06 – 1-moment microphysics
GM10 – 2-moment microphysics
Pot. temperature profiles in the lower troposphere:
Dashed: domain-averaged
Solid: within raining regions only
Mean of rainy grids
Domain mean
G06 GM10 GM10: 1-moment rain
Deviation from surface temperature
• Idealized convective-radiative quasi-equilibrium simulations using the two-moment bulk microphysics result in the mean
atmospheric state similar to previous simulations with one-moment microphysics.
• Bowen ratio: two-moment microphysics has a different impact on cold-pool temperature and moisture due to smaller rate of rain
evaporation.
• Precipitation: Little difference in atm. radiative cooling between PRISTINE and POLLUTED little impact of aerosol on surface precipitation
• TOA net shortwave: between PRISTINE and POLLUTED is down to about 9 Wm
-2from about 20 Wm
-2in one-moment
simulations.
Next we move to a less idealized, time-evolving framework…
less stringent constraints relative to CRE
16-day, 2D simulations of TWP-ICE, using observed large-scale forcing
• similar setup to other GCSS case studies
97 levels 200 columns
Surface temperature = 29° C
Prescribed large-scale forcing of T, qv, 6 hr nudging of u to observations
horizontal distance
height
Tropical Western Pacific – International
Cloud Experiment (TWP-ICE)
-
Question: how does parameterization of
microphysics and model resolution in a CSRM impact simulation of aerosol effects on clouds and
precipitation for tropical deep convection?
-
• BASE Baseline configuration (Morrison and Grabowski 2007; 2008a,b)
• FRZ Heterogeneous droplet freezing of Bigg (1953) replaced by Barklie and Gokhale (1959), ~ factor of 100 reduction in freezing rate
• GRPL Graupel density decreased by ~ factor of 3
• Resolution Horizontal grid spacing varied from 2 km to 500 m
Aerosol
specification, similar to
Fridlind et al.
(2010, in prep)
PRISTINE (SOLID LINES)
POLLUTED (DOTTED LINES)
• Impact on surface precipitation
ACTIVE MONSOON SUPPRESSED MONSOON BASE FRZ GRP OBS
PRISTINE (SOLID LINES)
POLLUTED (DOTTED LINES) ACTIVE MONSOON
SUPPRESSED MONSOON
PRISTINE (SOLID LINES)
POLLUTED (DOTTED LINES)\
OBSERVED
IMPACT ON
MICROPHYSICS
PRISTINE (SOLID)
POLLUTED (DOTTED)
DROPLET CONCENTRATION ICE CONCENTRATION
ICE WATER CONTENT LIQUID WATER CONTENT
DROPLET EFF RADIUS ICE EFF RADIUS
PRISTINE (SOLID LINES) POLLUTED (DOTTED LINES)
• Impact on TOA radiative fluxes
TOA upwelling SW
BASE FRZ GRP OBS
What is the role of internal variability in explaining these differences?
• Run 5-member ensemble of simulations (pristine and polluted) with different initial seed for random noise
ACTIVE MONSOON SUPPRESSED MONSOON
W m-2 /µm hr-1 ENSEMBLE
SPREAD
Given a standard deviation of 10 W m
-2in aerosol indirect effect, statistical significance at 95% level
roughly requires:
3 W m
-2 50 ensemble members 2 W m
-2 100 ensemble members 1 W m
-2 400 ensemble members Size of
indirect
effect
• Precipitation: little impact of aerosol over timescales longer than a few days, consistent with “systems dynamics” reasoning and
results for CRE
• Radiation: impact of aerosol difficult to discern from large internal variability ensemble approach
Caution is needed when quantifying indirect effects in GCSS- type modeling frameworks as used here, less problematic for 3D??
• Sensitivity to microphysics and resolution: nearly all tests lie within the ensemble spread
Summary of TWP-ICE results
Microphysics and aerosol indirect effects in MMF
• Recent effort to incorporate 2-moment microphysics scheme (Morrison et al. 2009) into SpCAM that predicts cloud particle number concentration and allows coupling with aerosol
• Parallel effort underway (led by PNNL) to incorporate cloud-aerosol interaction in SpCAM using a more
complicated framework (Explicit Clouds-Parameterized Pollutants)
• Preliminary results using 2-moment scheme and comparison with default SpCAM microphysics
2-moment scheme is out of the box, no tuning…
DJF Precipitation Rate (mm hr
-1)
From M. Khairoutdinov
DJF Outgoing Longwave Radiation, OLR (W m
-2)
From M. Khairoutdinov
DJF Absorbed Solar Radiation (W m
-2)
From M. Khairoutdinov