NASA Technical Reports Server (NTRS) 20070034010: Correlations Between Sea-Surface Salinity Tendencies and Freshwater Fluxes in the Pacific Ocean

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Correlations Between Sea-Surface Salinity Tendencies and
Freshwater Fluxes i n the Pacific Ocean
Zhen Li and David Adamee
Abstract
Temporal changes in sea-surface salinity (SSS) from 21
years of a high resolution model integration of the Pacific
Ocean are correlated with the freshwater flux that was used
to force the integration. The correlations are calculated
on a 1°x10 grid, and on a monthly scale to assess the
possibility of deducing evaporation minus precipitation (E-
P) fields from the salinity measurements to be taken by the
upcoming Aquarius/SAC-D mission. Correlations between the
monthly mean E-P fields and monthly mean SSS temporal
tendencies are mainly zonally-oriented, and are highest
where the local precipitation is relatively high.
Nonseasonal (deviations from the monthly mean) correlations
are highest along mid-latitude storm tracks and are
relatively small in the tropics. The response of the
model's surface salinity to surface forcing is very
complex, and retrievals of freshwater fluxes from SSS
measurements alone will require consideration of other
processes, including horizontal advection and vertical
mixing, rather than a simple balance between the two.
POPULAR SUMMARY
Title: Correlations Between Sea-Surface Salinity Tendencies and Fresl-rwater Fluxes in
the Pacific Ocean
Authors: Z. Li and D. Adamec/614.2
Summary: One of the goals of NASA's new mission to measure the global sea-surface
salinity will be to determine how much of the temporal changes in sea-surface salinity is
directly due to the additions and subtractions of fresh water to and from the ocean.
Addition of freshwater is accomplished through precipitation, and subtraction through
evaporation. Whereas precipitation can be measured from satellites, there is no current
available technology for a direct measurement of evaporation from space. It is hoped that
salinity changes would provide a useful proxy for these important freshwater fluxes, that
among other things, determines the long climate-scale flows in the ocean known as the
thermohaline circulation and the global ocean conveyor belt.
A sophisticated and realistic ocean computer model is forced with prescribed
evaporation and precipitation fields. The computer-generated salinity fields are then used
to determine how much of the changes in salinity are due to that forcing and how much
of the changes are due to other processes such as movement of salt by ocean currents, or
stirring of the surface waters by the wind. It turns out that the ocean computer model's
response to the prescribed inputs is very complex, and simple balances between salinity
changes and precipitation and evaporation fields are the exception as opposed to the rule.
Retrieving freshwater additions and subtractions to the ocean will require careful
consideration of the ocean currents, and how easily surface waters are stirred by the
atmosphere.
GEOPHYSICAL RESERlXC'II LETTERS, VOL J t, XXXX DO1 10 1020/
Correlations Between Sea-Surface Salinity Tendencies
and freshwater Fluxes in the Pacific Ocean
Zhen Lj
Science Applications International Corporation, Beltsville, Maryland, USA
David Adamec
Oceans Sciences Branch, NASA Goddard Space Flight Center, Greenbelt,
Maryland, USA.
D. Adamec, Oceans Sciences Branch, Code 614.2, NASA Goddard Space Flight Center, Green-
belt, MD 20771, USA
Z. Li, Global Modeling and Assimilation Office (GMAO), Code 610.1, NASA Goddard Space
Flight Center, Greenbelt, MD 20771, USA. ([email protected])
April 26, 2007, 3:18pm D R A F T
x
- 2 LI ET AL E-P FROM SALINITY TENDENCIES
Teniporal changes in sea-snrface saIinity (SSSJ from 21 years of a high res-
olution model integration of the Pacific Ocean are correlated with the fresh-
I
water flux used to force the integration. The correlations are calculated on
a 1°x10 grid, and on a monthly scale to assess the possibility of deducing evap-
oration minus precipitation (EP) fields from the salinity measurements to
be taken by the upcoming Aquarius/SAC-D mission. Correlations between
lI
the monthly mean E-P fields and monthly mean SSS temporal tendencies
are mainly zonally-oriented, and are highest where the local precipitation is
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relatively high. Nonseasonal (deviations from the monthly mean) correlations
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are highest along mid-latitude storm tracks and are relatively small in the
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tropics. The response of the model's surface salinity to surface forcing is very
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complex, and retrievals of freshwater fluxes from SSS measurements will re-
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quire consideration of other processes, including horizontal advection and ver-
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tical mixing.
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D R A F T April 26, 2007: 3:18pm D R A F T
LI ET AL E-P FROM SALINITY TENDENCIES
1. Ir~trodaaction
The science goals of the joint United States-Argentina sea-surface salinity (SSS) observ-
ing mission, Aquarius/SAC-D, are to understand the role of salinity variations in climatic
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processes, and to understand how salinity variations influence the ocean's general circula-
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tion (Lagerloef et al., 2002; Koblinsky et al., 2003). To attain these goals, it is envisioned
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that accurate maps of the flux of freshwater between the ocean and atmosphere, usu-
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ally represented as the difference between evaporation and precipitation (EP), will be
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derivable from the temporal changes in SSS observed by AquariusISAC-D.
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The mission science requirement of Aquarius/SAC-D is to deliver measurements of the
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global SSS at a spatial resolution of 100 km every month. The nominal accuracy of those
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SSS measurements is to be no worse than 0.2 - 0.3 practical salinity units (psu). The
2P
approximate 30-day temporal resolution is too long to capture fast ocean processes such
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as entrainment and detrainment in the mixed layer, and possibly too long for determin-
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ing the effects of horizontal advection when the advecting velocities exceed 4cm/s (N
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1001tm/30days). Thus, obtaining reliable E P e stimates from surface salinity changes will
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rely on the effects of fast, i.e., faster than 30 days (e.g., tropical instability waves or wind
stirring), ocean processes acting randomly that do not introduce their own relatively large
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time-integrated tendencies in the SSS.
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Delcroix et al. (1996) examine the relationship between temporal changes in the ob-
served SSS provided by ships of opportunity and rainfall estimates derived from satellite
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outgoing longwave radiation, and find a good correspondence between the two in areas
3P
with the heaviest precipitation, i.e., the Intertropical and South Pacific convergence zones
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D R A F T April 26, 2007, 3:68pm
X - 4 LI ET AL.: E-P FROM SALINI'TY 'I'ENDENCIES
(ITCZ and SPCZ). That study averaged data into 10' zonal by 2.5" rneridional boxes
and temporally smootl~edt he lnolithly input data. Though not forilially calculated, the
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Delcroix et al. study estimates the effect of evaporation would be 30-50% of precipitation
.+3
a changes in the convergence zones, and the effect of advection is responsible for 25% of the
local salinity balance near strong currents.
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Wijffels (2001) compares 13 different climatological estimates of E P and finds that
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differences between products can have a global standard deviation as large as 250mm/yr,
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and regional differences as large as 50Omm/yr. The largest deviations occur predominantly
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over the tropics and the mid-latitude storm tracks. The deviations between the E-P
4P
estimates in that study are mainly due to differing estirnates of precipitation over the
ocean. The estimates of evaporation, a derived quantity, vary much less than precipitation
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estimates. The Wijffels study clearly identifies a need for consistent estimates of E-P, even
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for an annual mean temporal scale.
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In this study, a state-of-the-art numerical model is used to simulate variability in the
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Pacific Ocean. Model surface salinities from a 21-year (1984-2004) period are used to in-
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vestigate the viability of deriving E P f ields from surface salinity at temporal and spatial
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resolutions commensurate with Aquarius/SAC-D. The viability is determined by calcu-
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lating the correlation coefficient between the local temporal changes in the upper most
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layer salinity and the E-P fields used to force the model. Results for both the seasonal
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and nonseasonal correlations are presented.
I,I ET AL 13-P Fl2OAI SA1,INITY TENDENCIFJS X-5
2. Model Setup
The ocean integration utilizes the klodulm Ocean Model (MOM) version 4.0 (Griffies
el nl., 2005). The domain extends 45*S to 50°N and 120"E to 70°W. For simplicity,
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all lateral boundaries are closed, even though the exchange of salt that occurs in reality
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between the Indian and Pacific oceans may be locally relevant and affects conclusions of
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this study there. The horizontal resolution is 1/4O, and the model has 43 vertical levels.
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The vertical resolution is 10 m in the upper 220m, and increases to a maximum of ~500m
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in the deepest ocean. Bottom topography derives from Smith and Sandwell's (1997) 2.5'
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product. The minimum water depth is 100m.
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The model initializes with the Levitus 1998 (Levitus et al., 1998) annual mean clima-
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tology of temperature and salinity and spins-up for 30 years forced by the NCEP-STR
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air-sea flux climatology (Doney et al., 1998). The integration then runs for 41 years
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(1964-2004) using monthly average wind forcing, surface heat and freshwater fluxes from
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the NCEPINCAR Reanalysis 1 Data (Kalnay et al., 1996). To avoid possible transient
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effects after switching to NCEP/NCAR monthly forcing, only model output from last 21
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years (19842004) of the integration is used in this investigation. The integration uses the
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standard default settings for mixing parameters (Griffies et al., 2005), including a KPP
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option for the surface mixed layer parameterization. To avoid drift in the model climatol-
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ogy, a tendency based on the difference between the modeled and observed monthly mean
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salinity and temperature fields is included. The model surface temperature is relaxed to
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monthly mean climatology with a 30-day-' damping scale. The surface salinity employs a
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D R A F T April 26, 2007, 3:18pm D R A F T
X-6 LI ET AL E-P FROM SALINrTY TENDENCIES
weaker 240-day-' damping scale that allows for realistic variability at ani~xiala nt1 longer
time scales.
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3. Forced Surface Layer Salinity Variability
The simulated SSS at the model's 1/4'x1/4' resolution is averaged to a 1°x10 grid to
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match the nominal Aquarius/SAC-D resolution. Evaporation is computed from the latent
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heat flux data from the NCEP/NCAR reanalysis. Evaporation and precipitation fields
are interpolated from their original 1.875' x 1.9047' resolution to the coincident 1°x10 SSS
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grid.
Two calculations of correlations are presented. The first calculation uses monthly mean
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values for input, and those inputs and correlations are referred to here as "seasonal". The
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second correlation uses deviations from monthly mean values and is referred here to as
"nonseasonal". For seasonal correlations, values above 0.53 are significant at the 95%
9l
confidence level, and for nonseasonal correlations, values above 0.125 axe significant at
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the 95% level.
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The standard deviation of seasonal E P (Figure la) has variability that is mainly
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zonally-oriented. The largest standard deviations occur off the west coast of Central
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America where precipitation has a marked stimmertime peak due to convection. This
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area is also a genesis area for hurricane formation in the east Pacific. There are local
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maxima in the standard deviations at about 18" latitude in each hemisphere extending
9s
out from the western boundary. Off the east coast of Australia, the larger standard devia-
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tions are due to large values of summertime precipitation and activity associated with the
lw
SPCZ. Near the Philippines, the larger standard deviations are more associated with the
lol
D R A F T April 26, 2007, 3:18pm D R A F T
LI ET AL FP FROM SALINITY TENDENCIES X-'9
seasonal meritlional migration of a local maxiniuin in precipitation. East of the dateline,
there are local maxima at about 5" latitude associated with precipitation along a north-
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ern and southern branch of the ITCZ. There are also local nlaxirna in the North Pacific
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along the winter time storm track. The equator and warm pool are areas of low seasonal
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variability.
The nonseasonal E Ps tandard deviations (Figure lb) have maximum variability that is
lo7
located almost entirely in the tropics west of 160°W. Variability associated with El Nino
lw Southern Oscillation (ENSO) events is responsible for the larger standard deviations in
the warm pool. The effects of ENS0 reach into the SPCZ and the high variability of
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precipitation area off the east coast of the Philippines. The warm and cold sea surface
temperatures caused by ENS0 in the east Pacific affect the local convective activity and
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hurricane generation off the west coast of Panama, and South America, and that variability
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is also evident in the non-seasonal standard deviations of EP.
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The standard deviations of the seasonal SSS temporal tendencies (Figure lc) are mainly
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zonally oriented as were the seasonal standard deviations in E-P. The largest values are in
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the eastern equatorial Pacific and near the Korean peninsula that is a natural response to
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strong E P f orcing from local monsoonal variability. Curiously, this area was not an area
lls
of relatively large E P f orcing. The nearby Kuroshio plays an important role for SSS in
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this area. The nonseasonal standard deviations (Figure Id) are of larger spatial scale than
1M
the seasonal variability. The largest standard deviations are in the eastern and western
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tropics and are related to ENS0 variability. The minimum in the tropics near 150°W is
consistent with the area being a pivot point of the normal see saw pattern of variability
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>; - 8 LI ET AL E-P FROM SALINITY TENDENCIES
in the eastern and western tropical Pacific during an ENS0 event. The maxirnum in
the western tropical Pacific is consistent with model calculations performed by Wang and
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Chao (2004) who showed a maximum in interannual variability of SSS there with RMS
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values approaching 0.5 psu.
The correlations between the seasonal SSS temporal tendencies and seasonal E P ( Fig-
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ure 2a) are, not surprisingly, zonally-oriented as were the seasonal signals of the individual
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fields of standard deviations. What is surprising is that some of the correlations are neg-
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ative indicating processes that lead, for example, to surface water becoming more saline
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during periods of less evaporation and more precipitation. It is much easier to compre-
132
hend and justify positive correlations when considering the local effect of E-P on salinity
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tendencies.
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In areas of greater seasonal variability of EP, specifically off the Central American
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coast, and near 18' latitude in the western Pacific, the seasonal correlations are strongly
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positive. These correlations are consistent with the Delcroix et al. (1996) study who show
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consistency on large spatial scales between areas of higher precipitation and negative
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salinity tendencies. Here, the correlations are also strongly positive along the northern
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and southern branches of the ITCZ, and along the southern edge of the wintertime Pacific
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storm track, again in areas of higher precipitation. The southern edge of the storm track
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is an area of greater precipitation as the synoptic systems are able to tap into moisture
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provide by the subtropical jet. This explanation provides a rationalization of why the
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highest correlations are south of the high E-P variability, but does not explain why higher
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E P variability is located further to the north. More detailed analyses that involve the
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D R A F T April 26, 2007, 3:18prn D R A F T