Relationship between atmospheric circulation and winter precipitation δ18O in central New York State

Authors


Abstract

[1] Oxygen isotope values of meteoric precipitation (δ18O) are strongly influenced by water vapor source and trajectory history, and can therefore be used as a tool for the reconstruction of atmospheric circulation. However, this approach requires an understanding of how differing patterns of atmospheric circulation influence precipitation δ18O. This study examines the relationship between atmospheric circulation and winter precipitation δ18O in central New York State. Circulation back trajectories, weather maps, and δ18O values for 132 precipitation samples were examined to determine the circulation type for each event. Lake-effect precipitation, which generated the lowest δ18O values, featured low pressure over New England and northwesterly flow over the Great Lakes. Events with the highest δ18O values were associated with low pressure north of New York and strong southerly flow within the warm sector. Less frequent were the Atlantic coastal and warm frontal overrunning events, both of which yielded relatively depleted precipitation.

1. Introduction

[2] δ18O values of carbonates, ice cores, and plant cellulose represent an important archive that can serve as valuable tools in paleoclimate studies. Among other things, these records provide insight on the oxygen isotope value of meteoric precipitation contemporaneous with their development [Anderson et al., 2002; Vinther et al., 2003]. Factors that control δ18O values of meteoric precipitation involve fractionation processes associated with the evaporation and condensation history of the precipitating water vapor. These factors include the temperature at which condensation occurs, the amount of precipitation, the isotope value of the water vapor source, and the degree to which the water vapor has traveled over land [Dansgaard, 1964; Rozanski et al., 1993; Araguás-Araguás et al., 2000]. Because these processes are tied to the storm system dynamics associated with the precipitation, records of isotopic variability can be used to study paleo-atmospheric circulation. Many recent paleoclimate studies using δ18O values of lacustrine carbonates have interpreted isotopic variability as a function of changing atmospheric circulation, rather than a simple air or lake water temperature signal [Edwards and Wolfe, 1996; Teranes and McKenzie, 2001; Kirby et al., 2002]. Furthermore, recent modeling efforts have shown that the interpretation of isotopic data using only local meteorological conditions, such as temperature, can lead to incorrect paleoclimate reconstructions [Noone and Simmonds, 2002].

[3] Developing an atmospheric circulation history using δ18O archives, however, requires an understanding of the ways in which circulation influences the isotope value of the meteoric precipitation at the site in which the archives are developed. One approach is to use modern precipitation isotope and circulation records to develop statistical relationships that can be used to interpret the paleorecords. Unfortunately, modern records of precipitation δ18O are limited, with the most extensive records contained in the International Atomic and Energy Agency (IAEA) Global Network of Isotopes in Precipitation (GNIP) dataset. The coarse spatial distribution and short period of record for many sites in the GNIP dataset limit their use in circulation study. The monthly resolution of the GNIP data also masks the influence of individual storms on the δ18O record.

[4] This study presents the initial findings of an ongoing effort to understand the relationship between winter atmospheric circulation and δ18O of individual precipitation events for central New York State, which is an area in which little work of this type has been performed. This region is interesting because of its location near several lakes in which paleoenvironmental records have been, and are being, developed [Mullins, 1998; Mullins et al., 2003]. Also, this is a region that receives significant winter precipitation in the form of Great Lake-effect snowfall. The impact of Great Lake derived moisture on precipitation isotopic variability and the associated sedimentary records of this region are undocumented.

2. Data and Methods

[5] This study uses δ18O and δD values derived from 132 winter (November–March) precipitation samples collected daily near Colgate University (42.8°N, 75.6°W) between 1999 and 2003. These samples are part of an effort to develop a precipitation isotope record of sufficient length and resolution to study the impact of individual storm types on precipitation isotopic variability and aid in the interpretation of paleo-isotopic records. Samples were collected using a funnel attached to a 500 ml bottle mounted on a 1.5 m post in an open setting. The bottles were replaced daily at 7:30 am local time. Our goal was to collect all winter precipitation; however, some days were missed because bottles were not deployed properly. These cases were limited and not linked to weather-related conditions that might bias the isotope data. Each sample represented the precipitation that had fallen over the previous 24-hours.

[6] Liquid samples were poured into a 60 ml bottle and sealed tightly to prevent evaporation. Snow samples, most of which collected within the funnel, were covered in plastic wrap, melted at room temperature, and stored in a sealed container. Samples were analyzed at the University of Saskatchewan Isotope Laboratory using a GC Pal Liquid Autosampler mounted on a Thermo Finnigan TC/EA coupled to a Thermo Finnigan Delta Plus XL mass spectrometer via a Conflo III interface. Stable isotopes are measured relative to VSMOW using internal standards calibrated with international standards. Sample precision is determined to be ±0.39‰ for δ18O and ±3‰ for δD (1σ, n = 45).

[7] The atmospheric circulation during each precipitation event was evaluated using a 48-hour back trajectory approach originating near Colgate University. This technique has been used to a limited extent by others and can provide insight into the source and meteorological history of the precipitating water vapor [Lee et al., 2003]. Back trajectories were calculated using the HYSPLIT model provided by the National Oceanographic and Atmospheric Administration's Air Resource Laboratory. Each trajectory was initiated at 500 meters above ground level using archived data from the ETA 80 km data assimilation system. Vertical motions were modeled dynamically within HYSPLIT. Trajectory data were coupled with a qualitative assessment of weather conditions for each precipitation event using synoptic-scale surface and middle-tropospheric weather maps. A circulation classification was constructed in which each precipitation event was assigned to a particular synoptic weather pattern.

3. Results

[8] The circulation analysis produced four dominant precipitation weather types, which were associated with 115 (87%) of the events. The remaining 17 days represented less frequent weather types and were bundled into an “other” category. The most common precipitating weather type was the lake-effect pattern (42%). These events, which average 0.16 cm (σ = 0.20 cm) of liquid precipitation, as measured using hourly records from nearby Syracuse, NY, are associated with high pressure over the central and Midwestern states, lower pressure over New England and northwesterly surface winds over the Great Lakes (Figure 1a). The northwesterly flow associated with these events can be seen in the trajectory summary (Figure 2a). Aloft, lake-effect events feature deep troughing over New England, which provides the cold air necessary for lake-effect instability.

Figure 1.

Surface circulation composites associated with: (a) lake-effect, (b) warm sector, (c) Atlantic coastal, and (d) warm frontal overrunning precipitation.

Figure 2.

48-hour back trajectories associated with: (a) lake-effect, (b) warm sector, (c) Atlantic coastal, and (d) warm frontal overrunning precipitation.

[9] Nearly 25% of the weather types were classified as warm sector events and are characterized by an average of 0.56 cm (σ = 0.61 cm) of liquid precipitation and surface low pressure north of the study region. Conditions aloft feature southwest flow along a ridged pattern over the Atlantic Coast. This pattern places the study region within an open warm sector dominated by southerly wind flow (Figures 1b and 2b). Precipitation is driven by cold frontal lifting operating on the relatively humid warm sector air originating from the Gulf of Mexico and nearby Atlantic.

[10] Atlantic coastal systems, which produce the largest average liquid precipitation amounts (ave = 0.86 cm, σ = 0.56 cm), comprised 15% of the events and feature a deep surface low moving northward along the coast (Figure 1c). These events are largely associated with easterly trajectories (Figure 2c), although many trajectories begin over the Great Lakes before entering central New York from the east. Aloft, coastal systems feature deep troughing over the Mid-Atlantic and riding over the west. The least common weather type (6%) was the warm frontal overrunning condition. These events are driven by troughing over the Midwest, which carries surface low pressure south of the study region. These events yield an average liquid precipitation of 0.80 cm (σ = 0.50 cm) and are associated with southerly surface flow and broad lifting over a warm frontal boundary south of the region (Figure 1d). Although some of the warm frontal overrunning trajectories originate from the west, most eventually flow into central New York from the south (Figure 2d).

[11] A scatter plot showing the δ18O and δD values for each sample, coded by weather type, is shown in Figure 3. Also shown in Figure 3 is the local meteoric water line (LMWL), which was calculated as the best fit regression line through the sample data, and the global meteoric water (GMWL) line as reported by Rozanski et al. [1993]. A comparison of the water lines shows that the LMWL is most different from the GMWL in the most negative sector, but converges as the sample values increase.

Figure 3.

Scatterplot showing δ18O and δD values for each precipitation event coded by circulation type. The local meteoric water line is based on a linear regression through the observations, whereas the equation for the global meteoric water line comes from Rozanski et al. [1993].

[12] The δ18O of lake-effect precipitation is most negative, with an average of −17.9‰ (σ = 4.3‰). Coastal and warm frontal overrunning events had slightly higher values, with average δ18O of −16.1‰ (σ = 3.0‰) and −16.6‰ (σ = 3.9‰) respectively. Highest δ18O values are associated with the warm sector events (ave = −8.2‰, σ = 3.1‰). Mean δ18O for the “other” weather type category, which captures a wide range of less frequent types, falls between the warm sector and coastal events (ave = −12.5‰, σ = 4.3‰). A statistical comparison of the mean δ18O values among the weather types was performed using a t-test. Among the types associated with low δ18O precipitation, lake-effect values are significantly more negative than coastal precipitation (P-value = 0.043). By contrast, the mean δ18O of the warm frontal overrunning weather type is not statistically different from the lake-effect or coastal δ18O values (P-values = 0.409 and 0.765 respectively). This lack of statistical difference may be influenced by the small number of warm frontal overrunning events in the dataset. The mean δ18O for warm sector events is significantly different from all other weather types, with P-values of 0.001 or less.

[13] An examination of the weather types associated with each precipitation day showed that 14 samples represented single storm systems lasting multiple days. Using a paired t-test, we assessed the possibility that system longevity might alter isotope values. Results showed that the precipitation δ18O did not differ significantly from the previous day's value in these 14 cases (P-value = 0.671). We also assessed the degree to which each weather type occurred equally throughout all months of the winter season. Events that occur more frequently within different parts of the winter season may carry a temperature related δ18O bias. Using a Chi-squared test, we compared the observed monthly distribution of events to an equal distribution. In all cases, the observed monthly distribution did not differ significantly from the equal distribution.

[14] A comparison of δ18O values and the mean surface temperature recorded at Syracuse, NY yielded a statistically significant positive relationship. However, an r2 value of 0.25 indicates that 75% of the precipitation δ18O variability cannot be explained by surface air temperature alone. Using the derived temperature-δ18O equation, (δ18O = 0.285T − 23.46), the average residual δ18O value was calculated for each circulation type. The most extreme average residual values were associated with the lake-effect (−3.3‰) and warm sector (+3.3‰) events, indicating that these events yield precipitation that is more negative and positive respectively than would be expected through surface temperature alone. The coastal and warm frontal overrunning events exhibited slightly more negative values (−1.5‰ and −0.7‰) than predicted by temperature.

4. Discussion

[15] This study provides a first step toward an understanding of how different winter circulation types in the northeastern United States influence precipitation δ18O and underscores the importance of circulation when interpreting δ18O archives. Lake-effect events are especially interesting in that they represent the impact of water recycling on precipitation δ18O. The northwesterly trajectories that are associated with lake-effect precipitation bring cold, dry air across the relatively warm lake surfaces [Burnett et al., 2003]. The δ18O of the Great Lakes surface water, as reported by Gat et al. [1994], is in the −6.8‰ to −8.8‰ range. Vertical fluxes of heat and recycled moisture destabilizes the overlying atmosphere, thus producing the lake-effect precipitation. The degree to which lake-effect precipitation records Great Lake moisture recycling was examined in isotope terms by Gat et al. [1994] using the deuterium excess (d = δD − 8 · δ18O). For the data presented in this study, deuterium excess can be visually assessed through a comparison of the LMWL and GMWL in Figure 3. The larger differences between the LMWL and the GMWL for the lake-effect samples reflect larger deuterium excess and recycled moisture. By contrast, the warm sector events, with their strong Gulf of Mexico and Atlantic moisture inflow, yield an enriched precipitation with little continental rainout and moisture recycling. These conclusions are consistent with findings reported by Gedzelman and Lawrence [1982] for warm sector precipitation.

[16] Coastal and warm frontal overrunning systems exhibit relatively low δ18O values that we associate with broad-scale frontal lifting and an associated altitude effect. This condition is especially pronounced in the warm frontal overrunning events where warm, humid air is transported northward and gradually lifted over a warm frontal boundary. As this air rises, cools, and condenses, the resulting precipitation δ18O decrease. Lawrence et al. [1982] present a similar argument for δD variability at Mohonk Lake, in southeastern New York State, in which they associate negative δD value events with more southerly and easterly storm tracks. The coastal systems, with their low δ18O, may also reflect warm frontal overrunning along the easterly flow on the north side of the low. Gedzelman and Lawrence [1990] preformed an isotopic analysis of two coastal storms and found the lowest δ18O from stratiform precipitation within the cold sectors of each storm. This low δ18O value stratiform precipitation is consistent with the easterly overrunning and depleted Atlantic coastal precipitation observed in the current study. As the coastal systems move north and east, they can create northwesterly flow and lake-effect precipitation over the study area, adding to lower δ18O values. Gedzelman and Lawrence [1990] also found a significant amount effect with coastal systems, in which δ18O values decreased as precipitation totals increased. On average, the coastal events in this study exhibit the largest average liquid precipitation and may be influenced by an amount effect.

5. Conclusions

[17] The distinctiveness of precipitation δ18O derived from different winter storm types supports the idea that δ18O records, such as those stored in lacustrine carbonates, can be used to reconstruct regional-scale patterns of paleo-circulation. However, the results of this study remain limited. In the case of many lake systems, lacustrine carbonate δ18O values are influenced by factors other than winter circulation and precipitation. The degree to which a particular lake system derives its water from winter and summer precipitation, the lake residence time, and summer evaporation all influence the lake water δ18O. Furthermore, one must understand the significance of lake water temperature on the δ18O values, which may serve to conflate the lake water δ18O-atmospheric circulation signal. Recognizing these constraints, we hope that this ongoing effort to document circulation-isotope relations in central New York State for all seasons will provide an important tool for paleoclimate interpretation throughout this region and others.

Acknowledgments

[18] This research was supported by funding from the Colgate University Research Council and by NSF grant BCS-0418012.

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