Climate Applications of ground-based Global

Navigation Satellite Systems (GNSS) measurements

Junhong (June) WangDept. of Atmospheric and Environmental

SciencesUniversity at Albany, SUNY, Albany, NY

Earth Observing Laboratory, NCAR, Boulder, CO

Outline

1. Motivation

2.GNSS precipitable water (PW) data

3.Climate applications:

• Validations of radiosonde and other data

• PW Variabilities: Diurnal cycle, annual anomaly, inter-annual variability, long-term trends and extremes

4. Other water cycle products from GNSS & other geodetic techniques

5. Summary

2

Gaffen et al. (1995)

Challenge: Large variability

3

How does GNSS estimate precipitable water?

4

Total delay = Ionosphere + dry + wet

Meteorological data (Ps, Ts) & estimated Tm

Dual-frequency GNSS mea.:GNSS EphemerisStation position

Timing

Atmospheric delay (ZTD = ZHD+ZWD)

Precipitable Water (PW)

ZWD = ZTD - ZHDZHD = f(Ps)

PW = * ZWD = f (Tm)

Forward modelGeodetic Noise to Meteorological signals

5

GNSS Radiosonde Satellite

Availability all weather Difficulty in thunderstorms

IR: clearMW: ocean

Temporal resolution

High (5 min-2 hourly)

1-2/daily >12-hourly

Temporal coverage

<~20 years >50 years ~30 years

Spatial coverage

~1000 stations ~1000 stations globe

Accuracy High (< 3mm) Low, various, bias Low, depending on radiosonde

Long-term stability

Stable Significant temporal inhomogeneity

Significant temporal inhomogeneity

Why GNSS for Climate Research?

• Diurnal variation• Climate extremes

Validations of other measurements

Climate trends

6

GNSS Networks

7

GNSS Satellites & Network Expansion

Number of GNSS Satellites

How good are GNSS measurements?

Orbit Accuracy of GPS Satellites: ~2 cm

1994

2012

NCAR global, 2-hourly GNSS-PW data (1995-present) • Jan. 1995 to Dec. 2012• 2 hourly (0100, 0300, …, 2300 UTC)• 380 IGS, 169 SuomiNet, 1223 GEONET

• Accuracy: < 3 mm• Ps, Tm, ZHD and ZWD also available• http://dss.ucar.edu/datasets/ds721.1/

Wang et al. (2007)

9

GNSS-PW Data Highlights

10

Hurricane Ernesto (Miami, 8/28-8/31/2006)

35

40

45

50

55

60

65

70

75

240 241 242 243 244

Julian days

PW

(m

m)

1005

1006

1007

1008

1009

1010

1011

1012

1013

1014

1015

Su

rfac

e p

ress

ure

(h

Pa)

PW

Ps

8/28 8/318/308/29

Hurricane Ernesto (24 Aug – 1 Sep. 2006)

11

12

Radiosonde validation: Systematic errors

Comparisons of PW (IGRA-GPS 1997-2006 106 stations)(only significant ones)

-11-10

-9-8-7-6-5-4-3-2-10123456789

10

PW

(m

m IG

RA

-GP

S)

RS80A RS80H RS90 RS92Modem Meisei VIZ-type IM-MK3MSS Shang MRZ/Mars

CapacitiveCarbon Hygristor

Goldbeater's skin

1.934.151.72S.D.0.811.97-1.67median

Goldbeater’s skinCarbon hygristorCapacitive

Wang and Zhang (2008a)

13

Temporal inhomogeneity of radiosonde PW data

Wang and Zhang (2008)

Miami, U.S.A

Suwon-Shi, Korea

Beijing, China

carbon hygristor

carbon hygristor

Goldbeater’s skin Carbon

hygristor

capacitive

capacitive with cover

Rela

tive

PW

diff

ere

nces

(% R

ad

ioso

nd

e-

GP

S)

Diurnal Variations (Lindenberg)

Radiosonde before corr.GNSS

Vaisala RS92

14

Radiosonde after corr.

ERA-Interim Japanese Reanalysis

Wang et al. (2013)

Global PW diurnal anomaly from GNSS

• The diurnal cycle is less than 5% of annual mean PW

• Larger magnitude in summer than in winter

• Peak around late afternoon to early evening

• An order of magnitude smaller than seasonal variation

GlobeS. H.N. H.

15

PW Anomaly in 2010 (GPS v.s. Microwave satellite)

Mears et al. (2010)Mears et al. (2011)

Mears et al. (2011)

16

Inter-annual and Long-Term PW Variability

El NinoLa Nina

Land

Ocean

Mears et al. (2012) 17

18

Land: X Radiosonde; O GPS Ocean: MWR satellites

19

Comparisons of Day & Night Trends (GPS)

20

Correlation between monthly anomaly PW and Ts

21

Variations of PW with Ts, Tmax and Tmin

Clausius-Clapeyron

PLATTEVILLE (PLTC)

Akronarpt

(P044)

ALTERNATE MASTER (AMC2)

SA62

2013 CO Flooding

25

Tropical Strom Fay, Aug 17-29, 2008

• Fatalities: 13 dir./23 indirect• $560 million• Area affected: Puerto Rico, Dominican Republic, Haiti, Jamaica, Cuba, Bahamas, South Eastern USFay Dumps Record-Breaking Rain; Flood Victims Warned Of Alligator Swimming In Streets Homeowners Forced To Use Canoes POSTED: August 20, 2008

27

Tropical Strom Fay, Aug 17-29, 2008

http://xenon.colorado.edu/spotlight/index.php?product=spotlight&station=sg05

Reflected GPS Signals

http://xenon.colorado.edu/portal/

2012 AnomalyNMRI: Vegetation Water Content

NDVI: photosynthesis

NLDAS: precipitation PW: Water Vapor

http://xenon.colorado.edu/portal/index.php

Soil Moisture Variability at Marshall, CO

31

DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite)

32

Very Long Baseline Interferometry (VLBI)

Summary1. The ground-based GNSS PW data have been approved very

useful for studying water vapor diurnal, inter-annual and long-term variations, and extreme events, and play an important role in various climate studies.

2. Other potential applications and other techniques of GNSS measurements to climate should be explored, GPS-RO, 3-D water vapor retrieval, other geodetic techniques.

33

http://www.eol.ucar.edu/homes/junhong/homepage.htm

http://xenon.colorado.edu/portal/