Verification of the geographical origin of modeled air-mass trajectories by means of the isotope...

17
Environ Fluid Mech (2009) 9:409–425 DOI 10.1007/s10652-009-9121-z ORIGINAL ARTICLE Verification of the geographical origin of modeled air-mass trajectories by means of the isotope composition of rainwater during the SALLJEX experiment Marcela González · Cristina Dapeña · Bibiana Cerne · Odon Sánchez-Ccoyllo · Saulo Freitas · Pedro L. Silva Dias · Héctor Panarello Received: 3 September 2008 / Accepted: 5 February 2009 / Published online: 22 February 2009 © Springer Science+Business Media B.V. 2009 Abstract The SALLJEX experiment was held during the summer 2002–2003. It consisted of three-dimensional observation of the atmosphere to study the structure of the low level jet along the eastern slopes of the Andes. Daily precipitation water samples were collected at two stations (Resistencia and Salta) in northern Argentina and isotope content was analyzed. M. González · B. Cerne Centro de Investigaciones del Mar y la Atmósfera, UBA-CONICET, Buenos Aires, Argentina M. González (B ) · B. Cerne Departamento de Ciencias de la Atmósfera y los Océanos, FCEN-UBA, Buenos Aires, Argentina e-mail: [email protected] B. Cerne e-mail: [email protected] C. Dapeña · H. Panarello Instituto de Geocronología y Geología Isotópica, INGEIS-CONICET-UBA, Buenos Aires, Argentina e-mail: [email protected] H. Panarello e-mail: [email protected] O. Sánchez-Ccoyllo · S. Freitas · P. L. Silva Dias Department of Atmospheric Sciences, Institute of Astronomy, Geophysics and Atmospheric Sciences, University of São Paulo, São Paulo, SP, Brazil e-mail: [email protected] P. L. Silva Dias e-mail: [email protected] S. Freitas Center for Weather Forecasting and Climate Studies - INPE, Cachoeira Paulista, SP, Brazil e-mail: [email protected] O. Sánchez-Ccoyllo Departamento de Ingeniería Ambiental, Física y Meteorología, Universidad Nacional Agraria La Molina, Av. La Molina s/n, La Molina, Lima, Peru e-mail: [email protected] 123

Transcript of Verification of the geographical origin of modeled air-mass trajectories by means of the isotope...

  • Environ Fluid Mech (2009) 9:409425DOI 10.1007/s10652-009-9121-z

    ORIGINAL ARTICLE

    Verification of the geographical origin of modeledair-mass trajectories by means of the isotope compositionof rainwater during the SALLJEX experiment

    Marcela Gonzlez Cristina Dapea Bibiana Cerne Odon Snchez-Ccoyllo Saulo Freitas Pedro L. Silva Dias Hctor Panarello

    Received: 3 September 2008 / Accepted: 5 February 2009 / Published online: 22 February 2009 Springer Science+Business Media B.V. 2009

    Abstract The SALLJEX experiment was held during the summer 20022003. It consistedof three-dimensional observation of the atmosphere to study the structure of the low level jetalong the eastern slopes of the Andes. Daily precipitation water samples were collected attwo stations (Resistencia and Salta) in northern Argentina and isotope content was analyzed.

    M. Gonzlez B. CerneCentro de Investigaciones del Mar y la Atmsfera, UBA-CONICET, Buenos Aires, Argentina

    M. Gonzlez (B) B. CerneDepartamento de Ciencias de la Atmsfera y los Ocanos, FCEN-UBA, Buenos Aires, Argentinae-mail: [email protected]

    B. Cernee-mail: [email protected]

    C. Dapea H. PanarelloInstituto de Geocronologa y Geologa Isotpica, INGEIS-CONICET-UBA, Buenos Aires, Argentinae-mail: [email protected]

    H. Panarelloe-mail: [email protected]

    O. Snchez-Ccoyllo S. Freitas P. L. Silva DiasDepartment of Atmospheric Sciences, Institute of Astronomy, Geophysics and Atmospheric Sciences,University of So Paulo, So Paulo, SP, Brazile-mail: [email protected]

    P. L. Silva Diase-mail: [email protected]

    S. FreitasCenter for Weather Forecasting and Climate Studies - INPE, Cachoeira Paulista, SP, Brazile-mail: [email protected]

    O. Snchez-CcoylloDepartamento de Ingeniera Ambiental, Fsica y Meteorologa, Universidad Nacional Agraria La Molina,Av. La Molina s/n, La Molina, Lima, Perue-mail: [email protected]

    123

  • 410 Environ Fluid Mech (2009) 9:409425

    The isotope data were used in conjunction with air parcel trajectories obtained from a 3-Dkinematic model (3D-MTC) developed by the University of Sao Paulo, Brazil. Values ofdeuterium excess were related with air masses of continental origin, whilst low values wereassociated with air masses with longer oceanic trajectories. Furthermore, although data arescarce, results show that oxygen-18 and deuterium excess in rainwater are related with theoccurrence of the low level jet.

    Keywords Isotope content Rainfall Air mass trajectories Low level jet

    1 Introduction

    Studies analyzing possible water vapor sources in subtropical Argentina are scarce, but it isclear that circulation is dominated by two main factors. The first one is the oceanic trajectoryof air induced by the South Atlantic anticyclone, which carries water vapor into the continent.The second is the summer dominance of humid winds from the north, with a long trajectoryover the Amazon forest associated to the low level jet (LLJ) along the eastern slopes of theAndes [17]. Knowledge of this jet is limited, as it develops over a region with scarce meteo-rological observations. The study of the low level jet was considered of worldwide interest bythe Climate Variability and Predictability Program (CLIVAR) of the World MeteorologicalOrganization (WMO). In this context, the CLIVAR regional program on American Monsoons(VAMOS) supported a field experiment to study this phenomenon in South America. TheSALLJEX (South American Low Level Jet Experiment) was carried out from 15 November2002 to 15 February 2003. The experiment consisted of the three-dimensional observationsof the atmosphere to describe the structure of the LLJ and the associated precipitation sys-tems. To this effect, precipitation measurements were made, as well as radio-soundings, pilotballoons and missions of an instrumented aircraft WP-3D. Furthermore, the isotope contentwas analyzed in daily rainwater samples at two stations in the region.

    Many natural processes cause variations in isotope compositions of natural waters. Themost important are evaporation and condensation. Therefore, the isotope composition ofrainwater is a good indicator of the origin of water vapor [8,29,30]. The first approach tounderstand the isotope composition of atmospheric water is to consider the system as aglobal distillation column fed by evaporation from the oceans. During evaporation, the vaporpressure of the light molecule of water, 1H1H16O, is greater (more volatile) than that of theheavy molecules, 1H2H16O or 1H1H18O (less volatile). Consequently, the content of 2H and18O in atmospheric water vapor is lower than in oceanic water vapor. When the atmosphericwater vapor cools and condenses, forming clouds and subsequent rain, the heavy molecules1H1H18O and 1H2H16O condense first, progressively depleting the amount of these speciesin the residual water vapor. As a result, the proportion of heavy isotopes in precipitationwater from the initial water vapor mass will decrease progressively. This process is definedand quantified by the Rayleigh equation [3,7,8].

    Dansgaard [8] carried out the first investigations with information of the world precipi-tation isotope composition, and laid the foundations for the application of isotope methodsin hydrogeological studies. He explained isotope content variations through the so-calledeffects, in terms of empiric relationships involving meteorological parameters. These alti-tude, latitude, seasonal, continental and amount effects produce variations in theisotope content of rainwater. The meteorological analysis of long precipitation worldwiderecords suggests that the long-term meteorological history of air masses is the main factorgoverning the variability of isotope content in rain water, as well as seasonal variation in

    123

  • Environ Fluid Mech (2009) 9:409425 411

    middle and high latitudes and the amount of precipitation in tropical regions [1,8,11,30]. Inareas like the Amazon basin, evapotranspiration is substantially higher. A large percentage ofprecipitation in such humid regions is caused by re-condensation of the vapor introduced inthe atmosphere by evapotranspiration, a process known as recycling and it has a charac-teristic isotope composition (normally with high deuterium excesses) [22,31].

    Albero and Panarello [1] studied the relationship between the mean monthly content ofstable isotopes in meteoric water in the Southern Hemisphere and temperature and precip-itation. They found that there is a large correlation with temperature at high and middlelatitudes as well as with the amount of precipitation at low latitudes. Treble et al. [38] exam-ined the interrelation between the synoptic patterns and 18O content based on 5-year dailyrecords in Tasmania. In this case, they observed the correlation with temperature and withthe length of the precipitation event were weak, but they found a major relationship withsynoptic conditionssuch as northerly wind and the location of cyclones.

    The aim of this paper is to use the isotope information from the rainwater samples takenduring the SALLJEX experiment to verify the geographic origin of the trajectories esti-mated with the three-dimensional model 3D-MTC [13,14,33], developed at the Universityof Sao Paulo, Brazil. In addition, a relationship with the occurrence of the low level jet (LLJ)was identified. Section 2 describes the information and the methodology used. Section 3.1presents the analysis of the data; Sect. 3.2 verifies the air mass modeled trajectories using theisotope data of the SALLJEX experiment; and Sect. 3.3 analyzes the relationship betweenthe isotope content of rainwater and the occurrence of the LLJ.

    2 Data and methodology

    An intensive observation period was held during the SALLJEX from January 11 to February15 2003, where daily rain samples were taken at two stations located in the region under inves-tigation -Resistencia (2727S, 5903W, 52 masl) and Salta (2451S, 6529W, 1,220 masl)(Fig. 1). These stations are part of the National Collector Network (RNC) established by theInstituto de Geocronologa y Geologa Isotpica (INGEIS) [9,10,12] in the framework ofthe International Atomic Energy Agency/WMO project launched in 1961. This internationalproject for the measurement of isotope content of precipitation water throughout the worldis called GNIP (Global Network for Isotopes in Precipitation).

    Since the publication of the first data on isotope composition of natural water [8,15], aclear correlation became evident between the content of 2H and 18O. This relationship formeteoric waters not affected by evaporation was established by Craig [6]. This author notedthat the data formed a linear band when the isotope composition of global precipitation wasrepresented in a 2H versus 18O scatter plot. Craig [6] named this coupling as Global Mete-oric Water Line (GMWL) and it is described by 2H = 818O + 100/00. Moreover, throughlong-term observations, made within the GNIP framework, this linear correlation between2H and 18O in precipitation samples collected from a world-wide network of stations wasconfirmed [30]. Additionally, Dansgaard [8] used this linear correlation to relate isotopecomposition of any water sample with meteoric water line and defined the parameter knownas deuterium excess (d)

    d = 2H 8 18O (1)where d is the ordinate, a parameter dependent on the original vapor and the most use-ful property to differentiate vapor origin. In addition, it allows discriminating balance andnon-balance processes. In most of the continental precipitation, d = +100/00.

    123

  • 412 Environ Fluid Mech (2009) 9:409425

    Fig. 1 Stations where rainsamples were collected toperform the isotopic analysis

    -80 -70 -60 -50 -40

    -50

    -40

    -30

    -20

    -10

    0

    10

    ResistenciaSalta

    The isotope analyzes were made at INGEIS laboratories. 2H in water samples wasprocessed by Coleman et al. [4] technique and for the measurement of 18O was used themethodology modified by Panarello and Parica [26]. Isotope ratios were measured with atriple collector, multiport inlet system, mass spectrometer, Finnigan MAT Delta S. Resultsare expressed in the usual way as [0/00], which is defined by the following equation:

    = 1,000(RS RP)/RP0/00 (2)where , isotope deviation in 0/00; S, sample; P, international reference; R, isotope ratios(2H/1H, 18O/16O). Values are referred to Vienna Standard Mean Ocean Water (V-SMOW)[16]. The analytic uncertainties are 0.10/00 and 1.00/00 for 18O and 2H, respectively.Positive values of 18O or 2H indicate that the content of 18O or 2H in a sample are abovethe pattern (enriched sample); negative values indicate the opposite (depleted sample).

    Deuterium excess (d) was calculated as mentioned above. Cases with precipitationbelow 2 mm were not taken into consideration, as isotope composition in too small sam-ples is modified by evaporation in raindrops during precipitation [20]. To analyze the type ofclouds and amounts of precipitation, meteorological records of Salta and Resistencia stationswere used. These stations are part of the synoptic network of the National MeteorologicalService of Argentina.

    A three-dimensional kinematic trajectory model (3D-MTC) developed by the Universityof Sao Paulo, Brazil [13,14,33] was used to estimate backward trajectories of air masses thatcaused precipitation events from which water samples were taken for isotope analysis, as willbe described in Sect. 3. The 3D-MTC model is computed using all three wind component(zonal wind, meridional wind and vertical wind). The wind fields needed for the trajec-tory model were derived from the Regional Atmospheric Modeling SystemRAMS [5,28],available at the University of Sao Paulo (Brazil). A detailed description of the 3D-MTC andRAMS models can be found in Snchez-Ccoyllo et al. [33].

    The RAMS application utilizes an Arakawa C-grid on an oblique polar stereographicprojection and employs a terrain-following coordinate system that determines the vertical

    123

  • Environ Fluid Mech (2009) 9:409425 413

    coordinate [5]. The RAMS simulations were performed for the period from 5 January to 14February 2003 with horizontal grid resolutions of 64 km. Thirty-two vertical layers with ver-tical grid spacing ranging from 60 to 1,000 m and a vertical grid stretch ratio of 1.2 were usedin simulations. The model used 72-s time steps. The numbers of grid cells in eastwest andnorthsouth directions were 8246. The RAMS model was initialized and updated in lateralboundaries every 6 h by using the National Centers for Environmental Prediction/NCAR(NCEP/NCAR) reanalysis at 2.5 latitude by 2.5 longitude and 17 vertical pressure levels(1,000, 925, 850, 700, 600, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 20, 10 hPa). Theassimilated variables were zonal and meridional wind velocity, absolute temperature, relativehumidity, geopotential and atmospheric sea level pressure. The four-dimensional data assim-ilation of coarse-resolution analyzed fields in the RAMS was performed through Newtonianrelaxation [36] within five nudging points at lateral boundary.

    Parameterization of horizontal diffusion coefficients was performed using the K-theoryaccording to Smagorinski [35]. The vertical diffusion was parameterized [23], which employsa prognostic equation for turbulent kinetic energy. The soil model used included equationsfor heat and moisture diffusion [40]. The bulk cloud microphysics parameterization (i.e.,level 3) was activated for cloud water and rain. The amount of precipitation was computedand removed from saturated layer by applying precipitation efficiency estimation [24]. Kuosconvection parameterization [19,39] was also used. For shortwave and longwave radiationparameterizations, the technique developed by [18] was used. Sea surface temperature datawas obtained from the Comprehensive Ocean-Atmosphere Data Set-COADS [41]. Topogra-phy and vegetation data set were taken from standard products in the RAMS model package.RAMS simulated wind fields are stored at every hours of simulation and they are the inputto trajectory computation.

    The 3D-MTC was based on the trajectory equation:drdt

    = v(r(t)) (3)

    where t is time, r is the position vector and v the wind velocity vector. To compute trajectories,the iterative scheme [27] was used. The position at a future time was calculated from thestarting position of wind vector. Then it was recalculated from an interpolated wind vector,between initial and future positions calculated in the previous iteration. This recursive methodends when convergence is achieved [34,37]. The trajectory equation (3) was integrated usinga time-step (dt) of 180 s. The horizontal components of wind vector were bilinear interpo-lated meanwhile for the vertical component, a 3-linear interpolation was used. For the timeintegration, a linear interpolation between two RAMS analysis intervals (3 h) was applied.

    3 Results

    3.1 Data analysis

    Tables 1 and 2 show the precipitation in 24 h-periods, the mean daily temperature and theisotope values obtained in Salta and Resistencia, respectively. Isotope data are representedin conventional 2H versus 18O diagrams (Fig. 2a, b) jointly with the global meteoric waterline as reference.

    Figure 2a and b present a scatter plot 2H versus 18O with daily and monthly rain sam-ples values in JanuaryFebruary and the global meteoric water line in Salta station and inResistencia station respectively.

    123

  • 414 Environ Fluid Mech (2009) 9:409425

    Table 1 Daily precipitation, temperature, 18O, 2H and deuterium excess in Salta

    Date Precipitation (mm) T (C) 18O (0/00) 0.1 2H (0/00) 1 d (0/00) 211 Jan 03 12.6 21.1 1.9 3 1212 Jan 03 7.3 18.1 2.3 1 1914 Jan 03 14.7 22.6 4.4 15 2017 Jan 03 40.8 22.7 6.4 35 1618 Jan 03 16.8 20.8 7.2 39 1920 Jan 03 12.6 24.6 5.4 33 1021 Jan 03 16.2 23.6 7.1 41 1622 Jan 03 16.0 21.8 4.8 22 1624 Jan 03() 1.0 18.0 0.2 7 928 Jan 03 2.8 22.7 1.0 4 1229 Jan 03 3.2 17.8 0.3 13 1104 Feb 03 3.0 23.9 7.0 45 1105 Feb 03 27.1 21.7 7.4 45 1407 Feb 03 5.2 21.3 7.1 43 1409 Feb 03() 1.0 23.1 4.0 23 910 Feb 03 25.3 24.2 5.3 30 12The cases () were not taken into consideration because of the low precipitation amounts

    Table 2 Daily precipitation, temperature, 18O, 2H and deuterium excess in Resistencia

    Date Precipitation (mm) T (C) 18O (0/00) 0.1 2H (0/00) 1 d (0/00) 211 Jan 03 10.8 26.9 2.6 10 111718 Jan 03 7.6 31.6 (17) 28 (18) 0.5 1 520 Jan 03 16.4 29.3 3.4 17 102223 Jan 03 15.8 27.7 (22) 24.85 (23) 6.5 38 1401 Feb 03() 0.6 31.8 5.1 9 3205 Feb 03() 1.9 29.8 0.5 17 1307 Feb 03 11.0 27.7 6.3 42 808 Feb 03 50.0 26.7 5.8 36 1009 Feb 03 8.0 28.0 6.0 39 910 Feb 03 41.4 26.7 8.8 66 412 Feb 03() 0.4 26.7 0.3 16 14The cases () were not taken into consideration because of the low precipitation amounts

    On January 11, there was intense convection and 10.8 and 12.6 mm fell intermittentlyin Resistencia and Salta respectively. Water vapor at both stations has the same origin, asobserved from d values (Tables 1, 2, Fig. 2a, b). On 12 and 14 January, rain was observedonly in Salta. In those days, rain samples were depleted of 18O. Furthermore, the values ofd are high in all cases, indicating that rain water came from recycled vapor [31].

    During January 17 and 18 convection developed over the north of Argentina and southernBolivia. Cumulonimbus clouds were observed in Salta, associated with strong convection,which is consistent with the increasing depletion in 18O along the days, as a consequence

    123

  • Environ Fluid Mech (2009) 9:409425 415

    Fig. 2 a 2H versus 18O of daily and monthly precipitation for the experiment period and global meteoricwater line in Salta. b 2H versus 18O of daily and monthly precipitation for the experiment period and globalmeteoric water line in Resistencia

    of amount effect [8,38]. In Resistencia, on January 17 and 18, the temperature was high;precipitation and relative humidity were low, reflecting the enriched isotope composition andthe low value of d (50/00). This fact might suggest that evaporation process were present(Fig. 2a, b). The isotope composition of precipitation in Salta reflects the characteristics ofprevious cases.

    On January 20 and 21 very strong northerly winds prevailed at low levels, fulfilling Bonnercriterion [2] (LLJ) [21,32]. The d values at both stations are equal or close to 10, indicatingthat water vapor has the same origin. On January 22, organized convection was observed in

    123

  • 416 Environ Fluid Mech (2009) 9:409425

    the northern part of Argentina and precipitation was detected in Salta and Resistencia. On the23rd, it continued to rain only in Resistencia and isotope composition was depleted in 18O.The high value of d at both stations indicates vapor recycling. There was a gradual deple-tion of 18O in Resistencia due to water discharge. In Salta, depletion might be to rainouton January 2021 [3,8], and the different isotope content observed on January 22 appears toindicate that the water samples corresponds to a different air mass (Fig. 2a, b). On the 24th,a cold air outbreak caused a temperature drop. Rain was scarce in Salta and no precipitationwas recorded in Resistencia.

    On January 28 and 29, little precipitation was observed in Salta and LLJ was not present.The 18O values corresponded to enriched rain and d indicates that the origin of precipitatingair mass was different from that causing precipitation on the previous days (Fig. 2a).

    As from February 3, a strong northerly flow was observed peaking in Bolivia. On thefollowing day, wind at 850 hPa reached 50 kt between Bolivia and Paraguay and organizedconvection was observed at the exit of LLJ in central-eastern Argentina. On February 5 and6, LLJ intensified, and there was a cold front advancing from the south. On the 7th, the frontwas located in Central Argentina, favoring strong winds in the warm air mass and the Bonnercriterion [2] was fulfilled over Bolivia and Paraguay, characterizing a LLJ episode. The 18Ovalues corresponded to depleted precipitation in Salta and d suggest than rain was fromrecycled vapor (Fig. 2a).

    On February 8, convection developed ahead the cold front, which moved towards the northcausing precipitation at both stations the following day. On February 9, the maximum dailyrainfall for this study period was recorded in Resistencia. The 18O values and d indicatedthat precipitation on the 8th and 9th February was caused by the same event (Fig. 2b). North-erly wind became stronger on February 10, increasing humidity and thermal contrast betweenthe air masses and leading to deep convection over Central Argentina. Precipitation amountswere 41.4 mm in Resistencia and 25.3 mm in Salta. 18O values decreased substantially inResistencia, which might be related to the amount effect and recycling within clouds. Isotopecontent in Salta was quite different, indicating that the origin of vapor and/or the trajectoryof the air mass that originated such precipitation was different from that of Resistencia.

    3.2 Confirmation of air-mass trajectories from the 3D-MTC model

    For each precipitation event that occurred in Salta and Resistencia for the period under study(Tables 1, 2) the trajectories of the air masses were modeled during the 4 days preceding therain event. The levels at which trajectories were estimated are 1,000, 1,500, 2,000, 2,500,3,000, 3,500 and 4,000 m above the surface. It is worth mentioning that northward of 38Sthe Andes are considerably higher and compact. This produces a distortion of air flow thatin many cases is not exactly represented by models. This structure forces the air from thePacific Ocean to cross the Andes only to the south of this latitude at low levels. This mustbe taken into account, especially for the trajectories corresponding to precipitation in Salta,due to its proximity to the Andes.

    The trajectories of air masses identified by isotope analysis at both stations, were studiedin the cases when precipitation was above 2 mm. Figure 3 shows the trajectories calculatedat 1,000 masl for the events in Resistencia and 1,500 or 2,000 masl for the events in Salta,as they are representative of the low level flow, with highest vapor content. In general, whenair comes from the north with a long section over the Amazon, the values of d are greaterthan 100/00 whilst when a mixture is detected with air from the Atlantic Ocean, with shortercontinental trajectories, the value of d is lower, approaching 100/00 and in some cases evenlower values.

    123

  • Environ Fluid Mech (2009) 9:409425 417

    Fig. 3 Trajectories from the 3D-MTC model corresponding to the precipitation events recorded in Salta(am) at 2,000 or 1,500 masl and in Resistencia (nu) at 1,000 masl, where isotope analyses of rainwater weremade during the SALLJEX experiment

    Precipitation recorded in Salta showed in all cases, except for January 28 and 29, atrajectory typically from the north with a substantial continental section. In all cases, dwas higher than 100/00 (Table 1, Fig. 2a). Salta also had d values lower than 100/00, butwithin the error of the variable (20/00). These values were consistent with the model for a

    123

  • 418 Environ Fluid Mech (2009) 9:409425

    Fig. 3 continued

    continental trajectory from the north. On the other hand, in January 28 and 29 rain events,precipitation amounts were small and the trajectories were consistent with a cold front com-ing from the south. Therefore, a lower d value can be expected, as the air may have partlytraveled over the Pacific Ocean, crossing the lower Andes southward of 38S and moving overArgentina, representing a mixture of oceanic and continental air. Quite higher values of d

    123

  • Environ Fluid Mech (2009) 9:409425 419

    Fig. 3 continued

    were observed in the cases of rain on January 12 and 14, when the trajectories were from thenorth but farther to the Andes than that observed in the other cases in January.

    The air mass trajectories that originated the precipitation event on 10th February werefrom the north at 1,500 m in Salta, crossing Bolivia and entering the Argentine territory ataround 65W and d was slightly above 100/00 (120/00) (Table 1, Fig. 2a). The upper level air

    123

  • 420 Environ Fluid Mech (2009) 9:409425

    Fig. 3 continued

    (3500 m) came from the Pacific Ocean and it is therefore probable that some kind of mixtureoccurred, which partly reduced the expected value of d.

    In the case of precipitation events that occurred in Resistencia (Table 1, Fig. 2a), rain waterwas from continental origin in some cases and others had an important oceanic component,shown by low values of d. Precipitation recorded on January 11 and 2223, had valuesof d higher than 100/00, with typically continental trajectories in both cases. The event of1718 January had a d of 50/00, the air trajectory being clearly oceanic with a short path overUruguay and southern Brazil. Also in the case of February 7 (d = 80/00), 8 (d = 100/00)and 9 (d = 90/00) the air entered from the Atlantic, although farther to the north, with asubstantially shorter continental trajectory as compared with the trajectories of January 11and 2223.

    The only case where the isotope analysis was not consistent with the type of trajectory wasFebruary 10, when the model showed air at lower and upper levels moving from the north,closer to the Andes but with d = 40/00, which is not representative of a continental trajectory.To verify whether precipitation on that day could have originated from non-continental vapor,the trajectories at 9 points close to Resistencia, with horizontal displacement of 0.25 and500 m in the vertical at the final position of the air parcels (Fig. 4a), were determined. The

    123

  • Environ Fluid Mech (2009) 9:409425 421

    spread of these trajectories confirm the large variability in this particular case. Some trajec-tories indicated a more oceanic air origin, which suggest that precipitation water collected inResistencia on that particular day may have different vapor sourcescontinental and oce-anic. Figure 4b shows the same situation for Salta, where trajectories are homogeneouslycontinental, contrary to the case of Resistencia. This result is consistent with the analysismade in Sect. 3.1 (Tables 1, 2, Fig. 2a, b).

    Although only 14 precipitation water samples could be studied in Salta, and 8 inResistencia, during SALLJEX, there is evidence that d is a good parameter to verifytrajectories derived from models, and it provides an additional element to measure theirefficiency.

    3.3 Relationship between isotope composition of rainwater and the low level jet (LLJ)

    Figure 5 shows a diagram (d, 18O) in Salta (5a) and Resistencia (5b). As isotope content ofrainwater is related with the origin of water vapor, in a first approach these values are relatedto the occurrence of the LLJ (L cases) or its absence (N cases). The LLJ is related withhumid air coming from the north, with a long trajectory over the Amazon. The L situationswere defined using the Bonner criterion [2]. LLJ events reaching 25S are called Chaco[25,32]C in the figures. These cases are related with a humidity flux and convergencein middle and low atmospheric levels over the northern part of Argentina and Paraguay thatit is 10 times higher than the normal summer values [32].

    There was a tendency for C cases to occur in Salta (Fig. 5a), originating precipitationdepleted in 18O and with d values between 110/00 and 170/00. On the other hand, L casesappeared in the transition phase between the cases with and without LLJ. It is noticeable inFig. 5a that N cases occur for 18O values greater than (5)0/00 with d values near 200/00

    Fig. 4 Trajectories from 3D-MTC at 9 points, corresponding to precipitation events recorded in Salta andResistencia on 10 February 2003

    123

  • 422 Environ Fluid Mech (2009) 9:409425

    (b)

    (a)

    L

    NN

    C

    L

    C

    CC

    NNC

    C CC

    -8 -7 -6 -5 -4 -3 -2 -1 0 118O (o/oo)

    8

    10

    12

    14

    16

    18

    20

    22

    d (o/oo)d (o/oo)

    L

    N

    C

    C- L

    C

    C

    C

    C-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1

    18 O (o/oo)4

    6

    8

    10

    12

    14

    16

    Fig. 5 Salta (a) and Resistencia (b). Rain-days and occurrence of LLJ Chaco (C, blue), LLJ non-Chaco(L, green) or absence of LLJ (N, red)

    for cases with trajectories from the north meanwhile, d were less than 120/00 for southernones, as shown in Fig. 3.

    The same methodology was applied for precipitation events in Resistencia (Fig. 5b),where most cases were L and C in this period and there was only one N case. Thisindicates that precipitation in Resistencia was mainly generated by humid air carried by LLJ.Only on 1718 January the water vapor was originated in the Atlantic Ocean (see Fig. 3o),characterized by 18O value near zero and d of 50/00, approximately.

    It is worth mentioning that, although in the presence of LLJ, different values of 18Oand d were observed in Salta and Resistencia on February 10, according to the analysisdescribed in the previous section (Fig. 4).

    4 Conclusions

    During the summer of 20022003, SALLJEX (South American Low Level Jet Experiment)was carried out, taking samples of rainwater at two stations located in the study region (Salta

    123

  • Environ Fluid Mech (2009) 9:409425 423

    and Resistencia). The INGEIS determined isotope composition of the samples (2H and 18O).This was the first time in the region that the isotope content was measured in samples ofdaily precipitation. The results of the analysis showed a good correspondence with the globalmeteoric water line and allowed establishing the origin of the air masses from the precip-itation recorded at both stations. The synoptic situations that caused precipitation duringthe sampling period were described in order to establish the probable relationship betweenisotope content and atmospheric circulation.

    The results showed that rainwater isotope composition is a useful tool to establish theorigin and transformation processes during the trajectory of the air masses associated withprecipitation. The analysis of the trajectories obtained from the 3D-MTC model allowedestimating the trajectory of the air masses 4 days previous to each precipitation event. It alsoleads to the evidences that the deuterium excess d is a good parameter to validate thekinematic trajectories, as values above 100/00 (with an error of 20/00) represent continentaltrajectories whilst the opposite occurs with the mostly oceanic trajectories.

    In addition, the isotope content of precipitation water was related to the occurrence ofLLJ. Water samples in Salta showed lower values of 18O for LLJ cases, especially thoseclassified as C with d values between 110/00 and 170/00. The cases classified as L werepositioned in the transition band between the precipitation events generated by LLJ-Chaco(C) and those that were not (N). The cases N had samples enriched in 18O, with smaller dvalues in the cases of trajectories from the south than, in those cases when the air came fromthe north.

    In Resistencia, the most part of the precipitation events during the sampling period corre-sponded to LLJ situations, indicating a continental source of humid air.

    This investigation shows that series of daily measurements of isotope contents were usefulto achieve more knowledge about the relation between the LLJ situations and the moisturetransport. Furthermore, these measurements result an important tool to validate daily fore-casts supplied by numerical models.

    Acknowledgements We wish to thank Dr. Paola Salio for the classification of the LLJ events. The paperwas financed by ANPCyT/PICT-2004 25269, NOAA/CPPA GC07-134. UBACYT X444, UBACYT X160,NOAA-CLIVAR/PACS Proposal GC03-011, IAI-CRN55, NOAA/GC03-011, and CONICET/PEI-6391. Theauthor P. L. Silva Dias acknowledges the CNPq support in the development of this work.

    References

    1. Albero MC, Panarello HO (1981) Tritium and stable isotopes in precipitation water in South America.In: Interamerican symposium of isotope hydrology, IAEA, Columbia, pp 91109

    2. Bonner W (1968) Climatology of the low level jet. Mon Weather Rev 94:167178. doi:10.1175/1520-0493(1966)0942.3.CO;2

    3. Clark ID, Fritz P (1997) Environmental isotopes in hydrogeology. Lewis Publishers/CRC Press.New York, 328 pp

    4. Coleman ML, Sheperd TJ, Durham JJ, Rouse JE, Moore FR (1982) A rapid and precise techniquefor reduction of water with zinc for hydrogen isotope analysis. Anal Chem 54:993995. doi:10.1021/ac00243a035

    5. Cotton WR, Pielke RA, Walko RL, Liston GE, Tremback C, Jiang H, McAnelly RL, Harrington JY,Nicholls ME, Carrio GG, McFadden JP (2003) RAMS 2001: current status and future directions. Mete-orol Atmos Phys 82:529. doi:10.1007/s00703-001-0584-9

    6. Craig H (1961) Isotope variations in meteoric waters. Science 133:17021703. doi:10.1126/science.133.3465.1702

    7. Craig H, Gordon L (1965) Deuterium and oxygen-18 in the ocean and the marine atmosphere. In:Tongiorgi E (ed) Stable isotopes in oceanographic studies and paleotemperatures. Spoleto, ConsiglioNazionale delle Ricerche, Pisa, Italy, pp 9130

    123

  • 424 Environ Fluid Mech (2009) 9:409425

    8. Dansgaard W (1964) Stable isotopes in precipitation. Tellus 16:4364689. Dapea C, Panarello HO (1999) Development of the national network for isotopes in precipitation of

    Argentina. In: II South American Symposium on Isotope Geology, pp 50350810. Dapea C, Panarello HO (2002) Red Nacional de Colectores de Istopos en precipitation en Argentina: su

    importancia en estudios hidrogeolgicos. Congreso Agua Subterrnea y Desarrollo Humano, Bocanegra,Martnez, Massone (Editores), pp 10531060

    11. Dapea C, Panarello HO (2004) Composicin isotpica de la lluvia de Buenos Aires. Su importanciapara el estudio de los sistemas hidrolgicos pampeanos. Rev Latino-Americana Hidrogeologia 4:1725

    12. Dapea C, Panarello HO (2005) Evolucin y estado actual de la Red Nacional de Colectores de Istoposen Precipitacin de la Repblica Argentina. Actas del XVI Congreso Geolgico Argentino, La Plata, II,pp 635642

    13. Freitas SR, Longo KM, Silva Dias MAF, Artaxo P (1996) Numerical modeling of air mass trajectoriesfrom the biomass burning areas of the Amazon basin. Ann Acad Bras Sci 68(Supplement 1):193206

    14. Freitas SR, Silva Dias MAF, Dias PLS, Longo KM, Artaxo P, Andreae MO, Fischer HS (2000) A convec-tive kinematic trajectory calculation for low resolution atmospheric models. J Geophys Res 105:375386.doi:10.1029/2000JD900217

    15. Friedman I (1953) Deuterium content of natural water and other substances. Geochim Cosmochim 4:89103. doi:10.1016/0016-7037(53)90066-0

    16. Gonfiantini R (1978) Standards for stable isotope measurements in natural compounds. Nature 271:534.doi:10.1038/271534a0

    17. Gonzlez MH, Barros V (1998) The relation between tropical convection in South America andthe end of the dry period in subtropical Argentina. Int J Climatol 18(15):16711687. doi:10.1002/(SICI)1097-0088(199812)18:153.0.CO;2-1

    18. Harrington JY (1997) The effects of radiative and microphysical processes on simulated warm andtransition season Arctic stratus. PhD Dissertation, Atmospheric Science Paper No. 637, Department ofAtmospheric Science, Colorado Sate University, Fort Collins, CO 80523, 289 pp

    19. Kuo HL (1974) Further studies of the parameterization of the influence of cumulus convection on large-scale flow. J Atmos Sci 31:12321240. doi:10.1175/1520-0469(1974)0312.0.CO;2

    20. Leguy C, Rindsberger M, Zwangwil A, Issar A, Gat JR (1983) The relation between the 18O and deute-rium contents of rain water in the Negev Desert and air-mass trajectories. Chem Geol (Isot Geosci Sect)1:205218

    21. Marengo JA, Douglas MW, Silva Dias PL (2002) The South American low-level jet east of the Andesduring the 1999 LBA-TRMM and LBA-WET AMC campaign. J Geophys Res 107(D20):47.147.11

    22. Martinelli L, Victoria R, Lobo Stemberg L, Ribeiro A, Moreira M (1996) Using stable isotopes to deter-mine source of evaporated water to the atmosphere in the Amazon basin. J Hydrol (Amst) 183:191204.doi:10.1016/0022-1694(95)02974-5

    23. Mellor GL, Yamada T (1982) Development of a turbulence closure model for geophysical fluid problems.Rev Geophys 20:851875. doi:10.1029/RG020i004p00851

    24. Meyers MP, Walko RL, Harrington JY, Cotton WR (1997) New RAMS cloud microphysics parameteri-zation. Part II: the two moment scheme. Atmos Res 45:339. doi:10.1016/S0169-8095(97)00018-5

    25. Nicolini M, Salio P, Paegle J (2004) Diurnal wind cycle of the South American Low-Level Jet. In: 1stinternational CLIVAR science conference: monsoon systems, Baltimore, Maryland, USA. DIALOG,http://www.clivar2004.electronic%20posters/monsoon_table.html

    26. Panarello HO, Parica CA (1984) Istopos del oxgeno en hidrogeologa e hidrologa. Primeros valoresen aguas de lluvia de Buenos Aires. Rev Asoc Geol Argent 39(12):311

    27. Pettersen S (1940) Weather analysis and forecasting. McGraw-Hill, New York28. Pielke RA, Cotton WR, Walko RL, Tremback CJ, Lyons WA, Grasso LD, Nicholls ME, Moran MD,

    Wesley DA, Lee TJ, Copeland JH (1992) A comprehensive meteorological modeling systemRAMS.Meteorol Atmos Phys 49(14):6991. doi:10.1007/BF01025401

    29. Rozanski K, Araguas L (1995) Spatial and temporal variability of stable isotope composition of precipi-tation over the South American continent. Bull Inst Fr Etudes Andines 24(3):379390

    30. Rozanski K, Araguas L, Gonfiantini R (1993) Isotope patterns in modern global precipitation.Climate change in continental isotope records. Geophysical Monograph 78, American Geophysical Union,pp 136

    31. Salati E, DallOlio A, Matsui E, Gat JR (1979) Recycling of water in the Amazon basin: an isotope study.Water Resour Res 15:12501258. doi:10.1029/WR015i005p01250

    32. Salio P, Nicolini M, Saulo A (2002) Chaco low level jet events characterization during the austral summerseason by ERA reanalysis. J Geophys Res 107(D24) 4816:ACL 32-1ACL 32-17

    123

  • Environ Fluid Mech (2009) 9:409425 425

    33. Snchez-Ccoyllo OR, Silva Dias PL, Andrade MF, Freitas SF (2006) Determination of O3, CO and PM10transport in the metropolitan area of So Paulo, Brazil through synoptic-scale analysis of back trajectories.Meteorol Atmos Phys 92:8393. doi:10.1007/s00703-005-0139-6

    34. Seibert P (1993) Convergence and accuracy of numerical methods for trajectory calculations. J ApplMeteorol 32:558566. doi:10.1175/1520-0450(1993)0322.0.CO;2

    35. Smagorinski J (1963) General circulation experiments with the primitive equations. Part I, thebasic experiment. Mon Weather Rev 91:99164. doi:10.1175/1520-0493(1963)0912.3.CO;2

    36. Stauffer DR, Seaman NL (1994) Multiscale four-dimensional data assimilation. J Appl Meteorol 33:416434. doi:10.1175/1520-0450(1994)0332.0.CO;2

    37. Stohl A (1998) Computation, accurancy and applications of trajectories. A review and bibliography.Atmos Environ 32(6):947966. doi:10.1016/S1352-2310(97)00457-3

    38. Treble PC, Budd WF, Hope PK, Rustomji PK (2005) Synoptic-scale climate patterns associated withprecipitation in Southern Australia. J Hydrol 302(14):270282

    39. Tremback CJ (1990) Numerical simulation of a mesoscale convective complex: model development andnumerical results. PhD Dissertation, Atmospheric Science Paper No. 465, Colorado State University,Department of Atmospheric Science, Fort Collins, CO 80523

    40. Tremback CJ, Kessler R (1985) A surface temperature and moisture parametrization for use in mesoscalenumerical models. In: Preprints seventh conference on numerical weather prediction, Montreal, AMS

    41. Woodruff SD, Diaz HF, Elms JD, Worley SJ (1998) COADS release 2 data and metadata enhance-ments for improvements of marine surface flux fields. Phys Chem Earth 23:517527. doi:10.1016/S0079-1946(98)00064-0. http://www.cdc.noaa.gov/coads/egs_paper.html

    123

    Verification of the geographical origin of modeled air-mass trajectories by means of the isotope composition of rainwater during the SALLJEX experimentAbstract1 Introduction2 Data and methodology3 Results3.1 Data analysis3.2 Confirmation of air-mass trajectories from the 3D-MTC model3.3 Relationship between isotope composition of rainwater and the low level jet (LLJ)

    4 ConclusionsAcknowledgementsReferences

    /ColorImageDict > /JPEG2000ColorACSImageDict > /JPEG2000ColorImageDict > /AntiAliasGrayImages false /DownsampleGrayImages true /GrayImageDownsampleType /Bicubic /GrayImageResolution 150 /GrayImageDepth -1 /GrayImageDownsampleThreshold 1.50000 /EncodeGrayImages true /GrayImageFilter /DCTEncode /AutoFilterGrayImages true /GrayImageAutoFilterStrategy /JPEG /GrayACSImageDict > /GrayImageDict > /JPEG2000GrayACSImageDict > /JPEG2000GrayImageDict > /AntiAliasMonoImages false /DownsampleMonoImages true /MonoImageDownsampleType /Bicubic /MonoImageResolution 600 /MonoImageDepth -1 /MonoImageDownsampleThreshold 1.50000 /EncodeMonoImages true /MonoImageFilter /CCITTFaxEncode /MonoImageDict > /AllowPSXObjects false /PDFX1aCheck false /PDFX3Check false /PDFXCompliantPDFOnly false /PDFXNoTrimBoxError true /PDFXTrimBoxToMediaBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXSetBleedBoxToMediaBox true /PDFXBleedBoxToTrimBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXOutputIntentProfile (None) /PDFXOutputCondition () /PDFXRegistryName (http://www.color.org?) /PDFXTrapped /False

    /Description >>> setdistillerparams> setpagedevice