global precipitation measurement (gpm) for...
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Global Precipitation Measurement (GPM) for Science and Society
Gail Skofronick-JacksonGPM Project Scientist
NASA Goddard Space Flight Center
Radar Observation of Rain
from Space
Tokyo, Japan
29 November 2017
GPM: A Science Mission with Integrated Application Goals
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Unified Precipitation MeasurementsFloods/Landslides
Agriculture/Famine Warning
Freshwater Availability
Land surface & climate modeling
World Health
Extreme EventsGPM Science Objectives:
New reference standards for precipitation measurements from space
Improved knowledge of water cycle variability and freshwater availability
Improved numerical weather prediction capabilities
Improved climate prediction skills
Improved predictions for floods, landslides, and freshwater resources
GPM Core Observatory & Constellation
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GPM Microwave Imager (GMI) 13 Channels,
NASA– Passive radiometer with excellent calibration
– Provides measurements of precipitation (rain and
snow) intensity and distribution over 885 km
– High spatial resolution (down to ~5km footprints)
– 166 Kg, 162 W, 34.9 Kbs Science,1.2 m reflector
Dual-frequency Precipitation Radar (DPR),
JAXA– KuPR similar to TRMM, KaPR added for GPM
– Provides 3D measurements of precipitation
structure, precipitation particle size distribution and
precipitation intensity and distribution
– High spatial resolution (5km horiz.; 250m vertical)
GPM Core Observatory:
407 km; 65 deg inclin.; 3-
year design life, extra fuel,
0.2-110 mm/hr & snow• New precip. ref. standards
• Improved NWP & climate
prediction skills
GPM Constellation:• Improved knowledge of water
cycle variability
• Improved prediction of floods,
landslides & freshwater
resources
Launched
Feb 2014
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GPM Core Observatory & Data Summary
Spacecraft and Instrument Status: Green: All Functioning
Data Products:•GPM Version 05 algorithms released in May 2017•TRMM+GPM long-term data record to be released in 2018
Data Latency (Data Available To Users)GMI (1 hr requirement, avg 23 min)DPR (3 hr, avg 76 min)Combined GMI+DPR (3 hr, avg 83 min)NASA multi-satellite estimates(avg 5 hrs)This near-real-time data is important for application and operational users. More accurate data later for science.
Fuel Predictions (with controlled re-entry):
Prediction Date Plus/Early Mean/Nominal Minus/Late
Nov-2017 08/2027 (13 yrs) 07/2032 (18 yrs) 08/2035 (21 yrs)
Fuel estimates change with solar cycle. Instruments are hoped to work as long as fuel.
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GPM Core Observatory Rain & Snow Estimates: 1 April 2017
0.2
11
0D
PR
MS
Pro
du
ct
(mm
/hr)
GV (mm/hr)
0.2 110
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GPM’s Data are Highly Accurate and Informative
Solid: Bias
Dash: NMAE (Random Error)
1.0 10.0
50%
25%
25%
50%
GV Dm (mm)
DP
R M
S D
mP
rod
uct
(mm
)
DPR: quantify rain rates between 0.2 and 110 mm/hrand demonstrate the detection of snowfall.
Estimate the Dm of precipitation particle size distribution to within +/- 0.5 mm.
The instantaneous rain rate bias and random error estimates are <50% at 1 mm hr-1 and <25% at 10 mm/hr.
DPR Retrievals
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GPM’s Radar Data Inform us about Particle Drop Sizes
Integrated Multi-satellitE Retrievals for GPM (IMERG)
8IMERG provides precipitation estimates every 30 min at a 0.1° x 0.1° grid box and
with a 4-5 hour latency (for applications) and ~3 month latency (for science users)
21-2
8 N
ovem
be
r 2017
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Applications: FloodsFlood Susceptibility (Oroville Dam,
California USA; Feb 2017)
X Oroville
IMERG Rainfall (7-day accum.) 21 Feb 2017
Flood Detection/Intensity (depth above threshold
[mm]) Forecast for 22 Feb 2017
21
Fe
b 2
01
7
Fo
reca
st E
ve
nt
Estimated Water Volume into
Oroville Dam
flood.umd.edu
View of Oroville Dam's
main spillway (center)
and emergency
spillway (top),
11 February 2017.
11 Feb 2017
Spillway
release
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Applications: Landslides Associated with Hurricane MariaData was routinely used by the US National Guard for situational awareness for Hurricane Maria, the city of Rio de Janeiro, Pacific Disaster Center, FEMA and others
1-day rain accumulation – 20 Sept 2017 Landslide nowcast – 20 Sept 2017
https://pmm.nasa.gov/precip-apps
Applications: Fire Weather Data and Forecasting
The Fire Weather Index System is the most widely used fire danger rating system in the world. The Global Fire WEather Database (GFWED) developed at NASA integrates different weather factors influencing the likelihood of a vegetation fire starting and spreading. [https://data.giss.nasa.gov/impacts/gfwed/]
Higher
chance
of fire
More
rain
Fire Weather Index 28 Aug 2015 Fine Fuel Moisture Code 14 Feb 2017
Drier
conditions
Dots=fires
Pacific
Northwest
USA
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Application: Agriculture & Crop IrrigationSatellite data used to empower National Water
Agencies of Pakistan and Nepal
Over 10,000 farmers in the Indus basin receive information on water resources in their area on their cell phone. Reference: Hossain et al. EOS Earth and Space News, 2017
Banana farmer checking his IMERG-
based irrigation advisory
“Dear farmer
friend, we would
like to inform
you that your
banana crop
does not need
irrigation due to
sufficient rainfall
the past week”
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GPM Science Team
• 60 NASA funded Principal Investigators, 25 no-cost international teams
• Next NASA 3-year funded proposal cycle renewal in 2018
• Reference paper:Skofronick-Jackson, Petersen, Berg, Kidd, Stocker, Kirschbaum, Kakar, Braun,
Huffman, Iguchi, Kirstetter, Kummerow, Meneghini, Oki, Olson, Takayabu,
Furukawa, Wilheit, The Global Precipitation Measurement (GPM) Mission for
Science and Society. Bull. Amer. Meteor. Soc., August 2017.
NASA Precipitation Measurement Mission Science Team Meeting,
San Diego, CA USA October 2017
14Educational Comic Book
gpm
.nas
a.go
v/e
du
cati
on
/co
mic
s
Applications/Education & Public Outreach
NASA Social Media Twitter: NASARain (> 21K followers)Facebook: NASARain (> 52K followers)Website: gpm.nasa.govMovies: svs.gsfc.nasa.gov
gpm.nasa.gov/education
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Cloud and Precipitation Processes Measurement (CaPPM)(Submitted to 2017 NASA Earth Science Decadal Survey, Decisions in 2018)
Image: Science News magazine article March 22, 2014
• As models achieve reduced grid scales, the
microphysical states and processes become
important and implementable in climate and
earth system models
• Key instruments being considered include radars
at Ku, Ka, W-band (some with Doppler), and a
wideband radiometer (potentially from 10-874
GHz); Intl. collaborations are being encouraged.
It is essential to know where, when and how clouds form,
whether they precipitate or not, and how patterns may
change in a future climate. Science questions include:
How can the ice species be parameterized?
What is the connection between vertical velocities
and resulting ice hydrometeor species?
What is the partitioning between liquid and ice?
What dynamics can be measured and modeled?