25.09.12
Clouds, Precipitation and their
Remote Sensing
Prof. Susanne Crewell
AG Integrated Remote Sensing
Institute for Geophysics and Meteorology
University of Cologne
Susanne Crewell, Kompaktkurs, Jülich
September 2012
24.25September
2012
Intergovernmental Panel on
Climate Change (IPCC) www.ipcc.ch
Nobel price 2007
IPCC Fourth Assessment Report (FAR), 2007:
"Warming of the climate system is unequivocal", and
"Most of the observed increase in global average temperatures since
the mid-20th century is very likely due to the observed increase in
anthropogenic greenhouse gas concentrations".
Aerosols, clouds and their interaction with climate
is still the most uncertain area of climate change and
require multidisciplinary coordinated research efforts.
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25.09.12
Why are clouds so complex?
  Cloud microphysical processes occur on small spatial scales and need to
be parametrized in atmospheric models
  Cloud microphysics is strongly connected to other sub-grid scale
processes (turbulence, radiation)
Cloud droplets
0.01 mm diameter
100-1000 per cm3
Drizzle droplets
0.1 mm diameter
1 per cm3
Condensation nuclei
0.001 mm diameter
1000 per cm3
Rain drops ca. 1 mm diameter, 1 drops per liter
Susanne
sa
a
Crewell, Kompaktkurs, Jülich 25 September 2012
Why are clouds so complex?
From hydrometeors
to single clouds to
Einzelwolken
and cloud fields
to the global
system
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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25.09.12
What are important cloud parameter?
Macro-physical Parameter
Radiative Quantities
  cloud fraction
  extinction coefficient ε [m-1]
  cloud height
  optical thickness τ
  cloud contours
τλ =
  3D-structure
z=∞
∫ε
λ
(z') d z'
z=0
  transmission t = exp(-τ)
Micro-physical Parameter
Ice- and mixed
phase clouds
  number concentration N
  effective radius reff
  liquid water content LWC
  radar reflectivity Z
moments of
the droplet
spectrum
 phase
 shape
 density
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
Droplet spectra
Hawaii
orographic
observations
modelling
Hawaii
stratus
Passat
moments of drop spectra
∞
m(n) = ∫ r n N (r)dr
0
Australia
continental
cloud liquid water density [kg m-3]
LWC =
4π ∞ 3
ρ w ∫ r N (r)dr
0
3
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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25.09.12
Ice and mixed phase clouds
Bergeron-Findeisen
While everywhere sufficient cloud condensation nuclei for forming water droplets
are available, much fewer ice nuclei exist
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
From small to large particles ....
0.1 μm
aerosols
1.0 μm
10 μm
cloud droplets
ice crystals
100 μm
1.0 mm
rain drops
10 mm
snow
turbulence
microphysical models ~100 m
numerical weather prediction (NWP) models ~10 km
Susanne
Crewell,
Jülich 25 September 2012
climate
models
~100Kompaktkurs,
km
4
25.09.12
Jülich ObservatorY for Cloud Evolution
•  JOYCE aims at investigating the processes of cloud formation and
cloud evolution (precipitation)
•  Various instruments set up at the Research Centre Jülich continuously monitor winds, temperature, water vapor, clouds, and
precipitation over many years
geomet.uni-koeln.de/joyce
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
JOYCE: Scientific goals
Goals
  to disentangle water vapor variations due to advection and to
local surface influence
validate coupled models
  to better understand the development of boundary layer clouds
including cloud radiation interaction
  to observe precipitation formation and improve parametrization
schemes
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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25.09.12
JOYCE: Instrumente (24/7)
Scanning cloud
radar MIRA-36s
Micro Rain
Radar
Lidar Ceilometer
Pulsed Doppler
Lidar
Scanning MWR
HATPRO
Infrared
spectrometer
AERI
Doppler Sodar
Total sky imager
Sun photometer
Radiation sensors
Auxilliary instruments: 120-m meteorological mast, MAX-DOAS, GPS,
polarimetric weather radar
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
How to remotely sense cloud parameters?
Active and passive techniques in different spectral regions use
extinktion, absorption and scattering of electromagnetic radiation to
indirectly sense cloud properties
Clouds are best „visible“ in atmospheric windows
  Microwaves (radiometry, radar & GNSS)
  Thermal infrared (satellite radiometry and spectrometry)
  Visible (reflected sun light, lidar, sun photometer)
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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25.09.12
How to determine cloud occurrence?
Total Sky Imager (Yes Inc.)
Specifications:
  Camera looks from above on
spherical mirror
  Sun is blocked by black tape on
mirror
  Temporal resolution 20 s
Products & retrievals:
  Cloud classification based on RGB
components for each pixel (in-house
algorithm):
sky, thin- and opaque clouds
(blue, light blue and white)
  Cloud fraction
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
Total Sky Imager
  Advantages: very reliable, intuitive, spatio-temporal structure
  Disadvantage: difficult to interprete due to geometry effects
18
UTC
12
UTC
10
1
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une
2
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2011
06
UTC
N E S W
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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At which height do clouds occur?
Lidar Ceilometer CT25K
Specifications:
  pulses at 905 nm
  temporal resolution 15 s
  range resolution ~15m,
range 0-7 km
Products & retrievals:
  senitive to small particles
  cloud base height
  optical extinction assuming
constant lidar ratio (in-house
algorithm)
  aerosol layer height
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
Lidar ceilometer
Altitude (m above ground)
  Advantages: very reliable, vertical structure
  Disadvantage: does not penetrate liquid water (cloud!)
Ice clouds
Rising PBL
Rain
Aerosol
Fog
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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Remote sensing and sensor synergy
  Lidar
- backscatter coefficient prop. r2
- depolarisation information (phase!)
- strong extinktion by water clouds
  Cloud radar
Radar
Lidar
- radar reflectivity factor
∫D
6
Radar
N (D)dD
- Doppler-spectrum
- linear depolarisation ratio LDR
Lidar
Height
Z=
LWC -liquid water content
- influence by insects and drizzle
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
Cloud radar
  Sends (active!) out pulses of microwave
radiation
  Measures backscattered radiation
(Z @ 35 GHz)
  Time between emitted and received pulse
information on the distance to
backscatterer
Cloud radar @ JOYCE
  Sensitive towards cloud droplets, ice particles & precipitation
  Doppler radar
radial velocity component can be measured
Doppler spectrum can help to distinguish different targets
  Polarized receiver
target discrimination constraint
information on particle shape
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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Cloud radar
radar reflectivity factor
7.8.2001 13:30 - 14:30
95 GHz GKSS
cloud radar
MIRACLE
Doppler velocity
Lineare depolarisation ratio
backscatter proportional r6
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
Doppler Cloud Radar MIRA-36
Elevation scan from 90° to 15°
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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Sensor Synergy: target categorization
Bit0: small liquid cloud drops (SCD)
Bit1: falling hydrometeors
Bit2: wet-bulb temperature < 0°C
Bit3: melting ice
Bit4: aerosol
Bit5: insects
  Only mean to derive complex vertical
structure of multi-level, multi-phase clouds
  Provides assumptions for radiative transfer
and retrieval algorithms
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
Why is cloud liquid water so important?
Liquid water path (LWP)
2007
2012
observations
Jiang et al, 2012
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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MicroWave Radiometer (MWR)
HATPRO
TOPHAT:
  Measures thermal emission of atmospheric gases
and liquid water
  Brightness temperatures (TB) in 14 channels
measurements
  Azimuth and elevation scanning
  Complete hemispheric scans during 7 min
Products:
  Temperature and
humidity profiles
  Integrated Water
Vapor (IWV)
  Liquid Water Path
(LWP)
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
Microwave radiometry
Standard atmosphere
temperature profile
water vapour profile
liquid water path
liquid water path
LWP=250 gm-2
scattering at cloud droplets
is negligle in microwave
spectral region
extinction ≈l absorption α
TB = TB cos exp(−τ ) +
∫
∞
0
s
T (s) α (s) exp(− ∫ α (s')ds') ds
0
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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25.09.12
Cloud radar and microwave
Interruption
for scanning
radar reflectivity factor
doppler velocity
But how to get the liquid water content profile ?
spectral width
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
The inverse problem
  Remote sensing instruments measure
indirect information, e.g. the
measurement vector y includes radiances
TB at different frequencies
  Forward problem (radiative transfer)
for a given atmospheric state x
(temperature, humidity, cloud parameter)
is well constrained y = F(x)
Microwave spectrum
Atmosperic profile
  Inverse problem (retrieval algorithm), i.e.
the determination of the atmospheric state
is often ill-conditioned and requires the
inclusion of empirical information
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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25.09.12
Integrated Profiling Technique
a variational approach towards multiinstrument retrieval
measurement 1
+ error
measurement 2
+ error
atmospheric state:
temperature, humidity,
hydrometeors
+ errors
measurement 3
+ error
Inversion
a priori information
+ error
OPTIMAL
ESTIMATION
Löhnert et al., 2004 and 2008
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
Liqud Water Content (LWC)
Application of LWC retrieved by IPT for evaluating regional
climate models
Models show different liquid water paths and
different peak altitudes
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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Further developments in synergy
•  Combination of ground-based and satellite information
spatial representation of supersites
•  Development of a “quasi-real-time” variational algorithm based on
optimal estimation theory
Meteosat
Seviri
RSW
TBIR
Z
Cloud
radar
TBMW TBIR
MRW
IRR
IIR
Integration &
minimization Profiles
Pro
of cost
of
function
T,
q,
LW
LWC,
reff
AERI
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
Challenges in sensor synergy
Goall: synchroneous scans radar – microwave radiometer
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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25.09.12
Summary and conclusions
Clouds
  clouds have a strong effect on the
Earths energy and water budget
  cloud processes are rather complex
and involve scales from nm to km
  cloud feedbacks related to aerosols
and changes in temperature and
humidty are not well understood
Observations
  better observations of clouds
are urgently required
sensor synergy
  observations and modelling need
to be linked closely for further progress
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
How to sense the various cloud
parameters?
Macro-physical Parameter
Radiative Quantities
  cloud fraction
  extinction coefficient ε [m-1]
  cloud height
  optical thickness τ
  cloud contours
  3D-structure
τλ =
z =∞
∫ ε λ ( z' ) d z'
z =0
  transmission t = exp(-τ)
Micro-physical Parameter
  number concentration N
  effective radius reff
  liquid water content LWC
  radar reflectivity Z
Ice- and mixed
phase clouds
 phase
 shape
 density
Susanne Crewell, Kompaktkurs, Jülich 25 September 2012
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