Transcript Parameterizations in NWP Models

Parameterizations in NWP
Models
Clouds
And
Precipitation
Rich Cianflone, NOAA/NWS
RFC/HPC Hydromet 01-2
THU, 7 December 2000
1
What is Parameterization?
• How the effects of physical processes are
included implicitly when when the processes
themselves cannot be included explicitly
• Can be thought of as emulation rather than
simulation
• Method of accounting for such effects without
directly forecasting them is called
parameterization.
2
Why Parameterize?
• NWP models cannot
resolve features/processes
occurring within a single
grid box
• Models must account for
the aggregate effects of
features/processes
• Computers are not
powerful enough
• Some processes are not
sufficiently understood
3
What is Parameterized in
NWP Models
• Atmospheric radiation
processes
• Convection
• Precipitation
• Clouds
• Surface characteristics
• PBL/free atmosphere
processes
4
Sub-Grid Scale
Parameterizations
• Parameterization of
sub grid-scale
processes is
necessary in order to
account for their
effects on the largerscale forecast
variables
5
How Parameterizations Account
for Physical Processes
Parameterization schemes are based on:
• Physical or Statistical representations
• ASSUMPTIONS: used to "create" information
– Empirical/statistical assumptions
– Dynamic/thermodynamic constraining
assumptions
– Model within a model
• CLOSURE: the link between the assumptions
in the scheme and the forecast variables
– Closes the loop between the parameterization and
forecast equations.
6
Parameterization Impacts
• Largest impact of parameterization is usually on forecasts
of sensible weather at the surface
• Problems with using parameterizations can result from:
– Interactions between parameterization schemes
– Increasing complexity and interconnectedness of
parameterizations
7
Primary NWP
Parameterizations affecting
Model QPF
• Precipitation and Cloud Parameterizations (PCP) :
Model emulation of cloud and precipitation processes
– PCP schemes have commonly been referred to as
grid-scale precipitation schemes
• Convective Parameterizations (CP): Methods by
which models account for convective effects
• Neither type of scheme is designed to produce
precipitation!!
8
Role of PCP Schemes
• Grid-scale motions
determine the forcing
but additional cloud and
precipitation processes
occur at sub-grid scales
• PCP plays a direct role
in the parameterization
of these sub grid-scale
processes
9
Types of PCP Schemes
• Inferred Cloud
Schemes: ‘infer’
clouds from RH
• Predicted Cloud Water
Schemes: actually
include cloud water
and cloud ice
(Simple and Complex)
10
Inferred Cloud Schemes
Currently used in AVN/MRF, NGM and NOGAPS
Excess moisture or supersaturation must be present to diagnose precip.
Infers precip. to remove excess moisture and infer clouds, based on RH
** Note that order is not physically correct!!
11
Inferred Cloud Schemes
Temps warm from latent heat release- specific humidity/dewpoint
decrease as water vapor condenses until they are equal
Precip falls out instantaneously. Sub-saturated areas beneath the
precip production layers are cooled and moistened
All water in the atmosphere remains in vapor form. The resulting
RH is too high, because no water is held in cloud
12
Implementation in AVN/MRF
Impacts on model precipitation forecasts
Precipitation formation
• Precipitation created directly from water vapor in all supersaturated
layers (RH > 100%)
Treatment of falling precipitation
• Evaporation if a layer is subsaturated; added to precipitation if lower
layers are supersaturated
• Evaporation rate based on assumed drop-size distribution estimated
from precipitation rate
Treatment of precipitation at the earth's surface
• Snow diagnosed if 850-hPa temperature is < 0ºC, otherwise rain
Interaction with convective parameterization
• If the Pan/Grell CP scheme is not active enough, produces too much
grid-scale precipitation, with resulting excessive cyclonic
development
13
Impacts on AVN/MRF Precip.
Forecasts
• Leaves out almost all details of cloud and precip.
microphysics and hydrometeor advection
– Cannot emulate snow/ice processes
– Cannot emulate mixed phase processes (cloud ice seeding
of supercooled water)
• Precipitation is not advected from one column to the
next before reaching the ground
– Cannot create or advect lake-effect snow or advect
orographic snow downwind from peaks
– Particularly problematic where advected snow is important,
such as regions of strong orographic forcing or significant
lake-effect snow
14
Impacts on AVN/MRF Precip.
Forecasts (con’t)
• Has no explicit clouds, data assimilation cannot
incorporate cloud data in initial conditions
– Less accurate description of initial moisture state
• Because all precipitation falls through a column in
one time step, effects of dry air advection on
suspended hydrometeors are completely ignored
– Dry layers near surface may become saturated prematurely
– Model may predict onset of precipitation too quickly
• The precipitation rate is an average for a grid box, which can
lead to over or under forecasts of precipitation by the model
15
Implementation of the Inferred
Scheme in AVN/MRF
• For detailed information on the
implementation of the inferred cloud
scheme in the AVN/MRF see:
http://deved.meted.ucar.edu/nwp/pcu2/avncpmp1.htm
16
Simple Predicted Cloud Scheme
Implemented in the Eta model
Uses critical RH level (generally below 100%) to account for sub
grid-scale moisture variability
Supersaturation is not required to create cloud liquid and ice
Accounts for partial cloudiness through overcast cloud cover as RH
increases above the critical value
17
Simple Predicted Cloud Scheme
Follows a physically based sequence of forming clouds prior to precip.
Precip falls out instantaneously & sub-saturated areas beneath the
precip production layers are cooled and moistened
Resulting RH is more realistic because some water and ice is
condensed in clouds
18
Improvement of Simple Over
Inferred Schemes
• Improvement in precipitation amount/location over
schemes with inferred cloud because:
– Clouds can be advected
– Includes effects of cloud ice
– RH fields are more realistic
– The PCP scheme may have direct interaction with
the CP scheme through input of convective cloud
water
• Allows direct comparisons of model initial/forecast
cloud fields with satellite imagery
19
Implementation of Simple
Scheme in Eta
Treatment of cloud liquid and cloud ice
20
Limitations of Simple in Eta
Model
• Improvements in precip. forecast are not complete because
– Precip. is still a byproduct, rather than predicted directly, and
falls to the ground in one time step
– Important microphysical parameterizations are crude
– Precip. hydrometeors are not explicitly predicted
• Precip. rate is an avg. for a grid box which can lead to
– Over/under forecasts of precip. depending upon the actual
extent and rate of the precip.
• Microphysics are too simple to predict convective processes,
such as the creation of cold pools and gust fronts
• Details on precip. process in Eta found at:
http://www.meted.ucar.edu/nwp/pcu2/etapcp2.htm
21
Implementation of Simple
Cloud Scheme in Eta
For detailed information on the
implementation of the Simple Cloud
Scheme in the current version of the Eta
model see:
http://deved.meted.ucar.edu/nwp/pcu2/etapcp1.htm
22
Complex Cloud Schemes
Implemented in RUC and some versions of the MM5
As precip. starts to fall within the cloud, cooling and moistening occur
near the freezing level from melting and occur in the sub-cloud layer
from evaporation
Mixed phase hydrometeor interactions/phase changes are
accounted for
23
Complex Cloud Schemes
As precipitation falls from the cloud
Precip. is tracked as it falls to the ground, rather than falling
to the ground instantaneously
Hydrometeors have more complex interactions as precip. falls
Some water or ice remains held in clouds
24
Improvement of Complex over
Simple Schemes
Inclusion of multiple hydrometeor types/interactions leads to ability to:
• Directly predict precip. type
• Improve forecasts of precip. location/amount
• Directly predict cooling from both evaporating and melting precip.
• Predict snow to blow far downwind from regions where it is
generated
• Depict convective system anvil extent and stratiform rain region
• Development and areal coverage of cirrus anvils
• Improve areal coverage/duration of precip. from a convective
system
• Better assimilate remote sensing data using different hydrometeor
types
• Directly forecast aircraft icing based
• Improve the radiation scheme (water, ice and graupel)
25
Implementation of Complex
Scheme in RUC
• Many microphysical processes accounted for
• Has to "spin up" until equilibrium is reached between
the hydrometeors and the forecast moisture, temp.,
and wind fields
– Results in the under prediction of clouds and precipitation
early in the forecast
• Can advect both cloud and precip. downstream
– Useful in location downstream of steep topography and in
lake-effect situations
• Can begin to resolve and generate convective
features such as cold pools and gust fronts
– Results in better depiction of generation of new convection
26
Implementation of Complex
Scheme in RUC and MM5
For details on the implementation of
Complex cloud schemes in the RUC and
MM5 see:
RUC:
http://deved.meted.ucar.edu/nwp/pcu2/rucpcp1.htm
MM5:
http://deved.meted.ucar.edu/nwp/pcu2/afgrid1.htm
27
Convective Parameterization
Given the scale at which convective processes occur,
current operational models cannot predict them explicitly
and must do so via parameterization
28
Role of CP in Models
29
BMJ Scheme
• Adjusts the sounding toward a pre-determined, postconvective reference profile derived from climatology
• BMJ scheme is used in the operational NCEP Eta
Model
• Trigger: Three conditions are required to trigger
convection:
– At least some CAPE
– Convective cloud depth exceeding a threshold value
– Moist soundings to activate
30
BMJ Scheme Process
• Starts with a reference profile, then adjusts the
original sounding toward it.
31
BMJ Scheme Process
• Rain produced from a reduction in precipitable water
going from the original sounding to the reference
sounding
32
BMJ Trigger in Operational
Eta
Deep and shallow convection occur with deep convective potential
evaluated first
If neg. Precip. is produced by adjustment to reference profile then
shallow scheme is called
For the deep scheme to trigger
• There must be an unstable parcel
• The convective cloud depth must exceed 200 hPa (les if terrain
is elevated)
• The adjusted reference profile must produce net warming and
drying
• Pre-convective sounding must have more precipitable water in
the cloud layer than the adjusted reference profile, otherwise
deep convection is not triggered
33
BMJ Trigger Issues in
Operational Eta
• Dry mid-level soundings do not trigger the scheme
– Classic severe weather soundings may yield no model
precip.
• The scheme convects even if a cap is present
• Allows elevated convection, but only originating within around
200 hPa of the surface
• The influence of potentially resolvable outflow boundaries and
their cold pools is insufficient because the scheme does not
directly change the sounding below cloud base
– Results in often missing convective redevelopment, echo
training, and stalling of warm fronts
34
BMJ Precip Issues in Eta
• Insufficient precipitation falls when the scheme fails to trigger
and in locations where moisture is concentrated below cloudbase level
• When the scheme triggers in a deep moist environment, it tends
to rain out too much
• Overall, the scheme underestimates very heavy precipitation
• Excellent at preventing unrealistic grid-scale convection
• For more details on the implementation in the Eta see:
http://deved.meted.ucar.edu/nwp/pcu2/etacp1.htm
35
Arakawa/Schubert
• Complex scheme
• Variations are used in the AVN/MRF, the NCEP
Regional Spectral Model, and the RUC
• To trigger convection, the scheme requires some
boundary-layer CAPE.
• Requires the presence of large-scale atmospheric
destabilization with time.
• Some versions include clouds of various heights with
various entrainment rates (more realistic)
36
AS Scheme Process
• Changes result from cloud processes rather than adjustments
toward a particular state.
• Sounding changes result from the total effect over time of clouds
detraining at their tops, of environmental subsidence, and of
boundary-layer stabilization from convective downdrafts.
37
AS Scheme in AVN/MRF
• “Simplified Arakawa-Schubert" (SAS) scheme is used
• Assumes one cloud type with detrainment only from its top
– Results in drying through the entire cloud layer
• Responds to differences between model CAPE and a
climatological CAPE (from tropical oceans) that varies with
cloud height
• Triggering and strength of convection are modulated by the
large-scale vertical velocity at the parcel LFC
• Has a pronounced tendency to result in excessive PCP
precipitation resulting from grid-scale convection. This is a
significant failure of this scheme
• Is not designed for elevated convection
38
Overactive CP Scheme Effects
• When a CP scheme removes too much moisture and instability
• Can occur even when the large-scale fields are well predicted
and convection is triggered at the correct location and time
39
Underactive CP Scheme Effects
• When a CP scheme fails to remove enough moisture and
instability
40
Important Points
CP Schemes
• Convective precip. is created as a by-product of the CP
scheme rearranging heat and moisture
• Do not use precip. forecasts at face value!!!!
• Model convective precip. forecasts have notoriously poor skill
• Incorrect timing, placement, and amount of precip. can cause
errors in the simulation of many forecast variable
• Model soundings are affected where model convection occurs,
and effects are advected downstream
• Forecast impacts of CP schemes depend heavily upon where
and when convection occurs in the model
• Scheme trigger functions are often sensitive to sounding
differences that are within the range of observational error
41
Important Points
PCP Schemes
• Primary purpose is to redistribute heat and moisture and remove
excess moisture
• Precipitation is only a by-product
• If the CP scheme does not sufficiently remove instability the
PCP scheme will attempt to remove it
• Results in grid-scale convection with over forecast of precip. in
overrunning region and too little precip. in moist, warm air mass
• Excessive lowering of sfc pressure due to latent heat release at
lower level and larger scale (actual cause of “convective
feedback”
• If CP Scheme removes too much instability and moisture the
pcp scheme will likely produce too little overrunning precip.
42