A Microwave Retrieval Algorithm of Above-Cloud Electric Fields

Michael J. PetersonThe University of Utah

Chuntao LiuTexas A & M University – Corpus Christi

Douglas MachGlobal Hydrology and Climate Center

Wiebke Deierling Christina Kalb

National Center for Atmospheric Research

The Global Electric Circuit (GEC)

Ionosphere

FairWeatherCurrents

WilsonCurrents

250 kV

0 VGround

How is the GEC Studied?

• Direct E field observations

• Limited domain and sample size

• Continuous global observations

• Thunderstorms only

Goal

• To create an algorithm that can estimate above-cloud electric fields that uses commonly-available global satellite productso Passive microwave

- SSMI

- TMI

- GMI

o Radar- TRMM PR

- GPM DPR

Objectives

• To provide a unique tool for examining:o Individual cases and global electricityo Long-term variations in global electricityo Relative contributions of different cloud types to the

GEC

• To provide validation for the FESD:ECCWES effort

Theoretical Basis

Ice Particle Collisions

Hydrometeor Charging

Charge Separatio

n

Wilson Currents

GEC

Theoretical Basis

Ice Particle Collisions

Hydrometeor Charging

Charge Separatio

n

Wilson Currents

Collision Frequency

Ice Concentration

. . .

GEC

Theoretical Basis

Ice Particle Collisions

Hydrometeor Charging

Charge Separatio

n

Wilson Currents

GEC

Collision Frequency

Ice Concentration

37 GHz and 85 GHz Passive Microwave

Observations

. . .

High Altitude Aircraft Version

• NASA ER-2o Advanced Microwave Precipitation Radiometer

(AMPR)o Lightning Instrument Package (LIP)

- 3D electric field vector

• 4 field campaigns: CAMEX-3, CAMEX-4, TCSP, TRMM-LBA

• AMPR and LIP observations are used to construct the algorithm and assess its validity

How the Algorithm Works

10 km

5 km

0 km

20 km

200 K

qi

Coulomb’s law:

How the Algorithm Works

10 km

5 km

0 km

20 km

260 K 200 K 150 K 200 K 250 K 270 K 290 K 280 K250 K250 K270 K300 K300 K 300 K 300 K

How the Algorithm Works

10 km

5 km

0 km

20 km

qnet i

260 K 200 K 150 K 200 K 250 K 270 K 290 K 280 K250 K250 K270 K300 K300 K 300 K 300 K

How the Algorithm Works

10 km

5 km

0 km

qnet i hi

260 K 200 K 150 K 200 K 250 K 270 K 290 K 280 K250 K250 K270 K

|qnet i| = f (Tb i)

20 km

hi = f (Tb i)

How the Algorithm Works

10 km

5 km

0 km

ri

260 K 200 K 150 K 200 K 250 K 270 K 290 K 280 K250 K250 K270 K

20 km

|qnet i| = f (Tb i)hi = f (Tb i)

hi

qnet i

Coulomb’s law:

How the Algorithm Works

10 km

5 km

0 km

ri

260 K 200 K 150 K 200 K 250 K 270 K 290 K 280 K250 K250 K270 K

20 km

|qnet i| = f (Tb i)hi = f (Tb i)

hi

qnet i

Coulomb’s law:

How the Algorithm Works

10 km

5 km

0 km

ri

260 K 200 K 150 K 200 K 250 K 270 K 290 K 280 K250 K250 K270 K

20 km

|qnet i| = f (Tb i)hi = f (Tb i)

hi

qnet i

Coulomb’s law:

Algorithm Performance Over Land

Algorithm Performance over Land

Miss

ed Eve

nts

False

Ala

rms M

issed E

vents

False

Ala

rms

Example Case

Missed Event Case

False Alarm Case

Overall Performance over Land

|Error|< 100%

Missed Events

False Alarms

37 GHzShower clouds

> 100 V/m40.3 % 53.2 % 6.4 %

Storm clouds> 100 V/m 41.7 % 47.1 % 11.2 %

85 GHZShower clouds

> 100 V/m68.2 % 17.5 % 14.4 %

Storm clouds> 100 V/m 69.5 % 7.4 % 23.2 %

Satellite Version

• Tropical Rainfall Measuring Mission (TRMM)o TRMM Microwave Imager (TMI)o Precipitation Radar (PR)o Lightning Imaging Sensor (LIS)

• Designed to take advantage of unique sensor packageo Radar-based estimate of charge heighto Radar-based stratiform/convective partitioning

Satellite Version

10 km

5 km

0 km

hi

260 K 200 K 150 K 200 K 250 K 280 K250 K250 K270 K

|qnet i| = f (Tb i)

20 km

hi = max ht of 30 dBZ

qnet i

1998 Distribution of LIS Lightning Flashes

1998 Distribution of Total Proxy E (stratiform scaling: 10%)

Comparison with LIS Lightning

Comparison with LIS Lightning

1998 Diurnal LIS Lightning Distribution

1998 Diurnal Proxy E Distribution over Land (stratiform scaling: 10%)

Comparison with LIS Lightning

1998 Diurnal LIS Lightning Distribution

1998 Diurnal Proxy E Distribution over Land (stratiform scaling: 10%)

Comparison with LIS Lightning

1998 Diurnal LIS Lightning Distribution

1998 Diurnal Proxy E Distribution over Land (stratiform scaling: 10%)

Conclusions

• The high altitude aircraft version can produce reasonable estimates of electric fields above convective clouds and clouds with significant electric fields

• The algorithm in its present form cannot adequately characterize electric fields above stratiform clouds and convection near large stratiform regionso Particularly a problem for oceanic regions and mature

MCS’s over land

• Passive microwave estimates of global electricity over land lead to similar spatial and temporal distributions compared to LIS lightning frequency

Next Steps

• Apply new dynamic stratiform scaling factor to prevent stratiform bias in convective pixel calculations (6,000 TRMM orbits processed)

• Incorporate ground-based radar observations into the high-altitude aircraft dataset

• Explore the feasibility of using a microwave-based convective/stratiform partitioning scheme

• Determine whether a combined 85 GHz/37 GHz charge proxy would have more skill than considering each frequency independently

• Apply algorithm to entire 16-year TRMM dataset

Proxy E E Transfer Functions

Stratiform Scaling1998 Distribution of Total Proxy E (stratiform scaling: 100%)

1998 Distribution of Total Proxy E (stratiform scaling: 0%)