A First Look at the CloudSat Precipitation Dataset

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A First Look at the CloudSat Precipitation Dataset

• Tristan LEcuyer
• S. Miller, C. Mitrescu, J. Haynes, C. Kummerow,
  and J. Turk

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The CloudSat Mission
Primary Objective To provide, from space, the
first global survey of cloud profiles and cloud
physical properties, with seasonal and
geographical variations needed to evaluate the
way clouds are parameterized in global models,
thereby contributing to weather predictions,
climate and the cloud-climate feedback problem.
The Cloud Profiling Radar

• Nadir pointing, 94 GHz radar
• 3.3?s pulse ? 500m vertical res.
• 1.4 km horizontal res.
• Sensitivity -28 dBZ
• Dynamic Range 80 dB
• Antenna Diameter 1.85 m
• Mass 250 kg
• Power 322 W

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but can it measure precipitation?
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CloudSats First Image
25 km
1300 km
http//cloudsat.cira.colostate.edu/index.php Click
CURRENT STATUS
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Applications

• A few examples from other talks
• Testing rainfall detection capabilities of PMW
  sensors
• Calibrating high temporal resolution global
  rainfall datasets
• Evaluating PMW rainfall estimates over land
  surface
• Comparisons with global rainfall statistics from
  other sensors (particularly at higher latitudes)
• Global statistics of frozen precipitation
• Other science applications
• Evaluating physical assumptions in PMW algorithms
  (eg. beamfilling/vertical structure/freezing
  level)
• Assessing the significance of light rainfall and
  snowfall in the global energy and water cycles
• Aerosol indirect effects on precipitation

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Probabilistic Philosophy

• Algorithm
• infer vertical profile of precipitating LWC/IWC
  and surface rainrate from the observed
  reflectivity profile and an integral constraint
  (eg. PIA or precipitation water path)
• Strengths
• Probabilistic retrieval framework adopted
• Allows formal inclusion of multiple forms of
  information including a priori knowledge and
  additional measurements and/or constraints
• Explicitly accounts for uncertainties in all
  unknown parameters
• Provides quantitative measures of uncertainties
  including relative contributions of all forms of
  assumed knowledge and measurement error
• CPR offers higher spatial resolution than other
  sensors that directly measure precipitation
• Sensitivity to continuum of clouds, drizzle,
  rainfall, and snowfall facilitates studying
  transition regions
• Weaknesses
• Strong attenuation at 94 GHz can lead to
  retrieval instability
• Single-frequency method limits information
  regarding the dielectric properties of the
  melting layer and restricts DSD assumptions
• CPR is nadir-pointing providing only a 2D slice
  of the real world

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First Attempt at a Retrieval
South Carolina
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Sanity Check
NEXRAD and CPR Rainfall
Default M-P Tropical CloudSat
Rainrate (mm h-1)
CPR Reflectivity (09/07/2006 1843 UTC)
B
A
Distance (km)
A
B
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Tropical Storm Ernesto
http//www.nrlmry.navy.mil/nexsat_pages/nexsat_hom
e.html Click CloudSat
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Applications

• A few examples from other talks
• Testing rainfall detection capabilities of PMW
  sensors
• Calibrating high temporal resolution global
  rainfall datasets
• Evaluating PMW rainfall estimates over land
  surface
• Comparisons with global rainfall statistics from
  other sensors (particularly at higher latitudes)
• Global statistics of frozen precipitation
• Other science applications
• Evaluating physical assumptions in PMW algorithms
  (eg. beamfilling/vertical structure/freezing
  level)
• Assessing the significance of light rainfall and
  snowfall in the global energy and water cycles
• Aerosol indirect effects on precipitation

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The A-Train Constellation
Formation flying provides opportunities for
product inter-comparisons and the development of
multi-sensor algorithms.
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Comparison with AMSR-E
16 days of direct pixel match-ups during August
2006
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Global Rainfall Statistics
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Tropics
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Higher Latitudes
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Pixel-Level Comparisons
157.7ºW
157.8ºW
17.95ºS
8.0 6.0 4.0 2.0 0.0
Rainrate (mm h-1)
Z (dBZ)
Zsfc (Black) PIA (green)
CloudSat
Rainrate (mm h-1)
18.42ºS
AMSR-E 37 GHz FOV (approximate)
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Frozen Precipitation
15ºN
15ºS

• CloudSats sensitivity makes it ideal for
  detecting snowfall.
• The region poleward of 60º is sampled 4 times
  more frequently than an equal area region at the
  equator!

60ºS
90ºS
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A First Look at Snowfall fromCloudSats
Perspective
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Radar-Only Retrieval

• Very preliminary inversion of CPR reflectivities
  to infer snowfall rate
• Assumes exponential distribution of snow
  particles
• Similar probabilistic retrieval framework as
  rainfall retrieval
• First goal is detection and discrimination from
  light rainfall

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Final Thoughts

• Early results from CloudSat confirm its
  potential for detecting and quantifying light
  rainfall and snow toward answering the question
  How important are light rainfall and snow in the
  global hydrologic cycle and energy budget?
• Two development streams (a) PIA-based detection
  and column-mean rainrate, (b) full probabilistic
  vertical structure retrieval. Ultimately merged
  into a single product.
• First products from both algorithms for the
  first 6 months of operation may be available as
  early as years end.
• More comprehensive validation of products is
  underway.

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Outline

• Applications highlight the need for these
  observations with particular emphasis on PMW and
  science apps. use the global distribution as a
  specific example
• Briefly re-iterate CloudSats purpose and lead
  into What about rain?
• First image confirms what sensitivity studies
  showed years earlier CloudSat CAN see rainfall
• Algorithm VERY briefly point out measurements,
  retrieved parameters, and philosophy for getting
  from one to the other
• Example point out that results are reasonable
  (only) not validation
• Ernesto CloudSat even capable of seeing heavier
  precipitation
• Point out advantage of A-Train co-located obs.
  from AMSR-E/CloudSat like a TRMM PR/TMI
• Show two types of comparisons (a) Initial
  statistical comparisons over a 16 day period
  using a stripped-down PIA-based version of the
  algorithm, (b) more detailed pixel-level
  comparison (shows relative footprint sizes and
  demonstrates testing of detection, freezing
  level, vertical distribution, beamfilling, etc.).
• Conclude with snowfall not many talks on this
  so far but CloudSat sampling sensitivity makes
  it a very useful snowfall sensor.
• Results are VERY preliminary but demonstrate
  detection capability

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Significance
CloudSats contribution to global precipitation
observations may be to assess the importance of
light rainfall and snow in the global energy
budget and hydrologic cycle.
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Can Rainfall be MeasuredWith A Cloud Radar?
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Global Light Rainfall Statistics
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Science Applications
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Aerosol Impacts?
GOCART Sulfate Aerosol (Feb. 01, 2000)
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Implementation (NRL)
Level-0
Level-1B
Downlink Raw Telemetry
Kirtland AFB
CIRA/DPC
NRL Monterey
New CPR L1B File
MODIS, AMSR-E
CRON
NOGAPS T/Q
Sigma_0 Database
UPDATE s0 Database
Gas Extinction
IGBP Database
Particle Scattering
Linux Processing Cluster
N
LOOP OVER ALL SHOTS
ZgtZthresh?
Driver Defines Input Metadata
Read Ancillary Databases
Read CPR Data Cloud Mask/Class
Y
DO RETRIEVAL!
Calculate Error Stats Store All Data
Interpolate T/Q Profile
Determine Gas Extinction
Define Constraints (e.g., PIA, LWP)
First Guess (Z/R)
RETRIEVAL LOOP
N
Optimal Estimation
Y
Converged?
Compute Forward Model Sensitivity
Compute Sx and Increment R