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Transcript of Http://gpmscience.gsfc.nasa.gov [email protected] 1 Use of GOES, SSM/I, TRMM Satellite...
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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
2http://[email protected] CRLGHCC
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.
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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.
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Study Area & GOES/SSM-I/TRMM/ECMWF Coverage
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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
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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.
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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
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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
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|)||||||/||/(|
||
PEQtLWPtPW
TCTWB ++•∇+∂∂+∂∂
=
Definition ofContribution to Total Water Budget
(TWB)
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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
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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%
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E Model Sensitivity Analysis
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Monthly Mean Budget Distribution Maps
Oct’97 Apr’98
Jan’98 Jul’98
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Methodology Verification (Line Integral)
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Methodology Verification (ECMWF)
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Methodology Verification (ECMWF)
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Monthly Mean Budget Time Series
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Monthly Mean Budget Time Series
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“Termwise” Contribution to TWB
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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%
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Diurnally-Averaged Monthly Budget Cycle (mass fluxes) & TWB Contributions
Oct’97
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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
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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
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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 −=•∇
Q•∇
• 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
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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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Q•∇
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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.
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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
31http://[email protected] CRLGHCC
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
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Backup Slides
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Study Region
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Surface Map valid Oct 24, 1998 at 00Z
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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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Methodology Verification (Line Integral)
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Methodology Verification (Line Integral)