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Use of GOES, SSM/I, TRMM Satellite Measurements for Estimating Water Budget Variations in Gulf of Mexico -- Caribbean Sea Basins

E.A. Smith (NASA/GSFC -- Greenbelt, MD) & P. Santos (NOAA/NWS -- Miami, FL)

Global Precipitation Measurement (GPM) Mission

An International Partnership &Precipitation Satellite Constellation

for Researchon Global Water & Energy Cycle

The 2nd TRMM International Science Conference Eric A. Smith; NASA/Goddard Space Flight Center, Greenbelt, MD 20771 [tel: 301-286-5770; [email protected]; fax: 301-286-1626; http://gpmscience.gsfc.nasa.gov] 6-10 September 2004; Nara, JAPAN


Motivation & Background Water cycle and climate research Limited success due to lack of global

data networks -- particularly over world oceans

Satellite global networks Several research programs designed to

develop comprehensive datasets of atmospheric processes in order to gain better understanding of climate and its variability

GCRP (TRMM) GEWEX (GPM) But rainfall is not only component of

atmospheric water cycle today recognized as foremost control on Earth’s climate

Therefore, understanding of water budget processes, their interplay and natural variability would be a valuable contribution

From this perspective, and examining problem first raised by Peixöto (1973) and put in climatic context by Peixöto and Oort (1992) -- main goal of research is:

“to determine how water balance is achieved for oceanic basin at regional- seasonal scales, focusing on degree to which water vapor and cloud condensate storage terms contribute to water balance within convective ocean regime”Specifically, variability of atmospheric water budget of Gulf of Mexico – Caribbean Sea basin is investigated for six sample months over 16-month period, consisting of:

Oct’97, Jan’98, Apr’98, Jul’98, Oct’98, and Jan’99.


Past Research• 1958 - International Geophysical Year.• Global Studies: Starr et al. (1958, 1969), Peixöto

(1970, 1972), Starr and Peixöto (1971), Peixöto et al. (1976, 1978), Peixöto and Oort (1983), & Chen and Pfaendtner (1993).

• Studied elements of atmospheric water budget such as PW, qV, , and compared these to independent estimates of E - P.

• Zonal and meridional components of qV.• In terms of yearly means, observed PW maintained

by qV with E - P > 0 across subtropical belts and < 0 across the ITCZ and subpolar lows.

• Maximum water vapor transport in PBL.• Standing eddies account for most of zonal transport

except in mid-latitudes where transient eddies play greater role.

• Transient eddies principal mechanism responsible for meridional transport of water vapor in mid-latitudes while Hadley cell is main mechanism across tropics.

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• Regional Studies: Benton and Estoque (1954), Hastenrath (1966), Rasmusson (1966a-b, 1967, 1968, 1971), Etter (1983), Etter et al. (1987), Yoo and Carton (1990), and Rabin et al. (1993).

• Monthly/Seasonal Scales: Convergence of qV related to P distribution. Basins transport easterly and southerly in summer -- during winter, easterly across southern Caribbean and westerly across northern Gulf. Southerly from SE Caribbean to northerly across northern Gulf.

• E - P > 0 across Gulf during winter and summer but strongest during Winter. Caribbean E - P > 0 throughout year but weaker than Gulf.

• Large diurnal variations of qV and based on twice a day radiosonde observations.

• Above normal P across eastern US eastern associated with >0 departures across Gulf and Caribbean.

• Daily Scale: Rasmusson: stated storage significant on daily scale but did not quantify;. Rabin et al. (1993) found storage term increases by factor of 3 or more following cold frontal passages across Gulf.

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In Summary: Local tendencies ignored -- therefore, complete analysis of hydrological cycle within context of atmospheric water balance equation has not yet been published.


Study Area & GOES/SSM-I/TRMM/ECMWF Coverage


Hypothesis/Scientific ObjectivesHypothesis:

Local rate changes of storage of water vapor and cloud condensate within convectively active regions are significant and should be considered in space- time restricted water budget calculations. Thus, conventional time-averaged form of water balance equation used in previous studies, which consists of balance between E - P and may not retain its validity when budget calculations are obtained diurnally and/or regionally.

Scientific Objectives: Develop purely satellite-based retrieval methodology, based principally

on multispectral measurements from GOES and SSM/I observations to calculate atmospheric water budget over Gulf of Mexico - Caribbean Sea basin, including retrieval of water vapor / cloud water contents and their time derivatives, as well as divergence of vertically integrated water vapor transport, surface rainfall, and surface evaporation. Quantify uncertainty in convectively active ocean basin stemming from

assumption that water vapor & cloud water storage terms are negligible insofar as atmospheric water balance at regional-seasonal scales.

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Mathematical Framework

Regional time-averaged form of atmospheric water balance equation given by:

where:

[ ] [ ]PEQt

LWPPW−=•∇+⎥⎦

⎤⎢⎣

⎡∂

+∂ )(

,/)(0∫ +=+op

l gdpqqLWPPW ,/0

gdpVqQop

∫=r [ ] [ ] ΩΩ= ∫ d)/1(

PW is precipitable water ; LWP is cloud liquid water path is water vapor plus cloud

condensate storage term are water vapor and liquid water mixing ratios are horizontal water vapor transport &

vertically-integrated horizontal water vapor transport E , P are surface evaporation and precipitation is divergence of

vertically integrated horizontal water vapor transport

tLWPPW ∂+∂ /)(lqq,QVq ,

r

[ ] ∫ −Ω=•∇ )()/1( qvdxqudyQ


Climatic Regime During Study Period

Study period was influenced by strong El Niño that developed in spring of 1997 and lasted into late winter of 1997-98 -- followed by strong La Niña that developed in late spring/early summer 1998 and lasted through reminder of study period.

El Niño is characteristic of above normal cyclonic activity, and hence precipitation, across northern Gulf of Mexico during fall and winter seasons while Caribbean undergoes drier than normal summer conditions -- converse is true with La Niña.

Also, tropical storm activity is below normal during El Niño years and above normal during La Niña years across Atlantic.

1997 Atlantic season was below normal with no storms across Caribbean and only one across Gulf -- although not during study period.

1998 Atlantic season was above normal with 5 tropical storms affecting Gulf (during Aug and Sep) and intense category 5 hurricane (Mitch) moving across southwestern Caribbean during last 10 days of October.


Data Sets

Budget methodology uses data from six sources:

GOES-8• Used to retrieve directly or indirectly P, PW, LWP,

cloud cover, SST, Ta, , , and ESSM/I

• Used to retrieve directly P, PW, LWP, , and TRMM 2a12 V5 P retrievals for Determining P

UncertaintyECMWF Gridded Global Analysis Data (2.5 deg

resolution)Upper Air Sounding DataBuoy Data

sq aq

sU aq


Multi-Algorithm Water Budget Retrieval &

Validation-Verification Methodology

AlgorithmCross-

Validation

AlgorithmDirect

Validation

FinalAlgorithm

PWprecipitable water

LWPliquid water path

Pprecipitation

Eevaporation

1. CldCov i. NESDIS-NRL

2. SST i. Legeckis & Zhu ii. NESDIS-LSSTiii. NESDIS-NLSST iv. Schlüssel

3. Us i. Schlüssel ii. Batesiii. Clayson & Curry

4-5. Ta & qs i. Clayson ii. Fairall

6. qa i. Schlüssel ii. Schulz

MODELClayson & Curry (1996)

Clayson et al. (1996)with GOES-SSM/I Inputs

1. Santos & Smith

Sondes

Combined GOES-SSM/I1. Chesters2. Crosson & Smith3. Santos & Smith

MethodologyVerification

GOES CldCov

Combined GOES-SSM/I1. Santos & Smith

1. Spencer2. Adler3. Ferraro 4. Olson5. Smith

TRMM

Line Integral Qfrom Sounding Data

ECMWF Qfrom Global Analyses

Qvapor

divergence

ResidueTerm

€

∂(PW + LWP )∂t

⎡

⎣⎢⎢

⎤

⎦⎥⎥+ ∇• Q[ ] = E −P[ ]

1. Alishouse2. Greenwald3. Lojou4. Weng & Grody

1. Wentz2. Greenwald 3. Lojou4. Petty

Sondes & Buoys

GOESSSM/I

Combined

CombinedGOES-SSM/I

1. Grose & Smith2. Turk

3. Santos & Smith


|)||||||/||/(|

||

PEQtLWPtPW

TCTWB ++•∇+∂∂+∂∂

=

Definition ofContribution to Total Water Budget

(TWB)


Calculation of Time-Dependent

Water Budget at Various Scales

•Retrievals are made on GOES-8 2 x 4 km grid and averaged to 0.25 x 0.25 degree grid for water budget analysis.

•Spatial-temporal characteristics of regional water budget are mainly analyzed on two scales:1. regional fully-averaged monthly scale2. regional diurnally-averaged monthly scale

•Noise reduction:

⎟⎟⎠

⎞⎜⎜⎝

⎛

Δ

+−+−−=•∇ −+

t

LWPPWLWPPWjiPjiEjiQ njijinjiji

2

)()(,,,)( 1,,1,,

E = 1.9 10-4 kg m-2 s-1

P = 3.7 “

/ t = 4.1 “

LP/ t = 0.2 “

where: 110-4 kg m-2 s-1 = 0.36 mm hr-1


SSMIGOES / SSMI matchTRMMGOES / TRMM match

SSMIGOES / SSMI matchTRMMGOES / TRMM match

TRMM vs SSMI and GOESR

ain

rate

(m

m h

r-1)

TRMM [2-month set] 1.02 mm hr-1

(SSMI - TRMM) / TRMM -3%(GOES - TRMM) / TRMM[for TRMM-match-ups]

-0.1%

(GOES - SSMI) / SSMI[for SSMI match-ups on TRMM days]

+12%

SSMI [6-month set] 0.98 mm hr-1

(GOES - SSMI) / SSMI[for SSMI match-ups]

+2.0%


E Model Sensitivity Analysis


Monthly Mean Budget Distribution Maps

Oct’97 Apr’98

Jan’98 Jul’98


Monthly Mean Budget Distribution Maps

Jan’99Oct’98


Methodology Verification (Line Integral)


Methodology Verification (ECMWF)


Monthly Mean Budget Time Series


“Termwise” Contribution to TWB


Comparisons to Previous Studies

This Study

This Study


Hour

Hour

QuickTime™ and aPNG decompressor

are needed to see this picture.

Gulf Region

0

10

20

30

40

50

DqV

P

E

Gulf of Mexico Basin TWB Contributions Caribbean Region

0

10

20

30

40

50

DqV

P

E

Caribbean Sea Basin TWB Contributions

∇•Q ∇•Q

P

E

P

E

Fully-Averaged Monthly Framework

€

CTWB=⟨T ⟩/ [⟨∂PW / ∂t⟩+ ⟨∂LWP / ∂t⟩+ ⟨P ⟩+ ⟨E ⟩]

€

⟨⟩≡absolutevalue

Q = (E - P)

Ocean

Atmosphere

Vapor Transport toSurroundings

Vapor-CondensateStorage

P = 36%E = 50%

∂(PW + LWP)/∂t = 0%Q = 14%


Diurnally-Averaged Monthly Budget Cycle (mass fluxes) & TWB Contributions

Oct’97


Illustration of Diurnal Fluctuations

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Month 00Z 12Z Monthly AVG 00Z 12Z Monthly AVG 00Z 12Z Monthly AVG

Oct-97 -14 -15 1 -17 -23 2 -11 -10 -0.2

Jan-98 -26 -5 1 -31 -16 -3 -24 2 4Apr-98 4 12 3 8 -2 2 1 20 3

Jul-98 -6 17 0.4 3 19 2 -12 16 -1Oct-98 -5 15 -2 -8 26 2 -4 8 -4

Jan-99 -20 -2 3 -18 -11 1 -22 4 4

Entire Gulf Caribbean


E - P

DqV0

10

20

30

40

50

Hour

Gulf Basin

E - P d(PW+LWP)/dt DqV

E - P

DqV0

10

20

30

40

50

Hour

Caribbean Basin

E - P d(PW+LWP)/dt DqVE - P

Gulf of Mexico Basin TWB Contributions E - P

Hour Hour

Caribbean Sea Basin TWB Contributions

Hour

Hour

Hour

Hour

δ( + )/PW LWP δt δ( + )/PW LWP δt∇•Q ∇•Q

™ QuickTime and aPNG decompressor

.are needed to see this picture

& Gulf of Mexico Basin E P Mass Fluxes

0.00

1.00

.00

3.00

4.00

5.00

Hour

EP

& Caribbean Sea Basin E P Mass Fluxes

0.00

1.00

.00

3.00

4.00

5.00

Hour

EP

E P E P Gulf of MexicoE&P Mass Fluxes

0-3-56-89-111-1415-1718-01-3

Caribbean SeaE&P Mass Fluxes

0-3-56-89-111-1415-1718-01-3

Diurnally-Averaged Monthly Framework

P = 14%E = 22%

∂(PW + LWP)/∂t = 32%Q = 32%

Ocean

Atmosphere

Vapor Transport toSurroundings

Vapor-CondensateStorage

∇•Q = (E - P)

- ∂(PW + LWP)/∂t

P


Summary and Detailed Conclusions• Emphasis placed on regional-seasonal

water balance storage processes. • Satellite algorithm retrieval methodology.• Regional Fully-Averaged Monthly Scale:

Rain maximum in Winter-Spring across Gulf, Summer-Fall in Caribbean -- with divergence term compensating.

• Results reflect expected weather patterns associated with El Niño / La Niña conditions.

• E exhibits weak seasonal variability but overall larger winter versus summer.

• In fully-averaged monthly framework: • Gulf: E main contributing term to TWB 80%

of time.• Caribbean: E and P main contributing

terms 50% of time.• Combined basins: P dominant process

only during Oct’98 -- highlighting Mitch’s impact on regional budget.

• Study period means: E = 50%, P = 36 %, = 14%.

PEQ −=•∇

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• Regional Diurnally-Averaged Monthly Scale: Balance between four terms:E, P, with divergence & storage revealing large amplitude diurnal oscillations, as noted earlier (qualitatively) by Rasmusson. Diurnal modulations largely driven by strong synoptic scale forcing mechanism.

• Diurnal TWB contributions: , , , & .• Assumptions: LWP derived from daily

mean SSM/I modulated by GOES-8 cloud cover and SSM/I daily mean wind speed used in water budget retrievals.

• Verification: Comparisons to line integral calculations (direct) & ECMWF global analyses (indirect) give guarded confidence in satellite retrievals when considering weather patterns.

• Hypothesis: True at diurnally-averaged monthly scale, confirming suspicions of Peixöto and Rasmusson.

• Objectives: Ignoring storages can lead to 30% error in estimating diurnally-averaged monthly water budget.

• Satellite approach is viable.

,,/ QtPW •∇∂∂

%32=•∇ Q %32/ =∂ dtPW %22=E %14=P


General Conclusions Fully-Averaged Monthly Scale

•Balance between and E - P , confirming findings of previous studies (e.g., E. Rasmusson) -- but through complete rendition of water budget -- not through simple balance assumption.

•Results agree with number of previous studies over Caribbean basin -- do NOT agree with single study over Gulf basin possibly due to

climatic differences.

Diurnally-Averaged Monthly Scale

•Balance between , E - P, and Storage.

•Budget mechanisms within both basins on this scale select synoptically-driven diurnal storage mode to achieve climatic adjustments.

•Results bear out Peixöto and Oort’s suspicions concerning role of storage.

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Future Research Improvements to multi-algorithm retrieval methodology are possible as satellite technology improves, e.g., multifrequency rain radars and better sampling frequency by microwave radiometers, i.e., main promise of GPM.

Better retrievals of various surface meteorological variables needed in ocean evaporation models. For example, Ta would be better retrieved using advanced infrared interferometer technology -- to be deployed around mid-decade by NASA/NAVY GIFTS mission.

Other improved retrieval products are becoming available on routine basis when considering scatterometer-retrieved surface winds, space radar-retrieved precipitation, and ever evolving constellation of microwave radiometer-bearing satellites.

Satellite approach becomes even more compelling when lidar-measured wind profiles become available from space, so that in combination with satellite-retrieved water vapor mixing ratio profiles, divergence term can be retrieved independently. This circumvents need for residue calculations, as well as enabling comprehensive testing of how well actual water budget closure can be achieved.

Essential point is to bring water budget analysis, budget closure, and scale resolution to degree of accuracy and precision, such that weather, climate, and hydrometeorological modelers are compelled to upgrade their model’s physics so as to reproduce important details in observed water cycle.


Satellite-based Water Budget of Gulf of Mexico & Caribbean Basins

Design of Algorithm System

Combined TRMM-SSM/I

& GOES

€

∂(PW + LWP )∂t

⎡

⎣⎢⎢

⎤

⎦⎥⎥+ ∇• Q[ ] = E −P[ ]

(∇• )Q , ,i j t=( - )E P, ,i j t-{[( + )PW LWP, , +i j t Δt-( + )PW LWP, , -i j t Δt]/ }Dt

Gulf RegionJul 98 - 12Z

-80

-60

-40

-20

0

20

40

60

80

6 8 10 12 14 16 18 20 22 24Days

Divergence

ECMWF Satellite

Caribbean RegionJul 98 - 12Z

-80

-60

-40

-20

0

20

40

60

80

6 8 10 12 14 16 18 20 22 24Days

Divergence

ECMWF Satellite

ECMWF Validation

Gulf-Caribbean Basins &Upper Air/Buoy Validation Data Sites

Study Area, GOES-SSM/I-TRMMSectors, & ECMWF Grid

Sounding, Satellite, and ECMWF Divergence Term Estimates July - 12Z

-60

-40

-20

0

20

40

60

6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Days

Divergence

Sounding (7) Sounding (9) Satellite ECMWF Sounding-Int (9)

Line Integral ValidationQ Uncertainty (%)vs Sample Count (N)

Gulf BasinJul’98 - 12Z

Caribbean Basin

GOES

GOES

GOES

GOES

SSM/I

SSM/I


Backup Slides


Study Region


Surface Map valid Oct 24, 1998 at 00Z


SST, Ta, Us, & qa Algorithm

Validation


E Response to Variations in Us

Month U-50 E-50 Us E U+50 E+50 Oct’97 2.77 2.33 5.55 3.72 8.32 5.21 Jan’98 3.13 2.16 6.26 3.51 9.39 5.03 Apr’98 2.85 2.11 5.71 3.38 8.57 4.76 Jul’98 2.75 1.54 5.49 2.46 8.24 3.44 Oct’98 3.02 2.33 6.04 3.76 9.05 5.35 Jan’99 3.33 2.41 6.66 3.95 9.99 5.73

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