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

2

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

3

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

4

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

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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?