1JULY 2020 M A E T A L . 5371

Impacts of Storm Track Variations on Wintertime Extreme and Moisture Budgets over the Ohio Valley and Northwestern United States

CHEN-GENG MA AND EDMUND K. M. CHANG School of Marine and Atmospheric Sciences, Stony Brook University, State University of New York, Stony Brook, New York

SUN WONG Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California

RUI ZHANG AND MINGHUA ZHANG School of Marine and Atmospheric Sciences, Stony Brook University, State University of New York, Stony Brook, New York

ANTHONY DEL GENIO NASA Goddard Institute for Space Studies, New York, New York

(Manuscript received 18 July 2019, in final form 23 March 2020)

ABSTRACT

Previous studies have shown that variations in extratropical cyclone activity significantly affect the fre- quency of extreme precipitation events over the Ohio Valley and northwestern United States. In this study, we examine the similarities and differences between the dynamics governing these events in these two re- gions. In the Ohio Valley, extreme precipitation events are associated with midlatitude synoptic-scale con- vergence northeast of cyclones and a southwestward oriented ridge near the Atlantic coast that drives strong transport from the Gulf of Mexico into the Ohio Valley. In the northwestern United States, extreme precipitation events are associated with a cyclonic and anticyclonic circulation pair aligned northwest to southeast, which together drive a long and strong moisture transport corridor from the lower latitude of the central Pacific Ocean toward the northwestern United States. Moisture budget analysis shows that moisture convergence due to dynamical convergence dominates in the Ohio Valley, whereas moisture advection dominates over the Pacific Northwest. Differences between the cases in the same region are examined by an empirical orthogonal function (EOF) analysis conducted on the vertically integrated moisture flux. Different EOFs highlight shifts in spatial location, orientation, and intensity of the moisture flux but demonstrate consistent roles of dynamics in the two regions. Composites based on these EOFs highlight the range of likely synoptic scenarios that can give rise to precipitation extremes over these two regions.

1. Introduction heavy precipitation and floods associated with them can cause tremendous loss to human society (Easterling Extratropical cyclones are a dominant driver for et al. 2000; Rappaport 2000; Pall et al. 2011). Kunkel wintertime (December to February) extreme et al. (2012) subjectively assigned each daily extreme events over the midlatitudes (Ashley and Black 2008; precipitation event a meteorological cause and showed Frankoski and DeGaetano 2011; Colle et al. 2013). The that about 54% of extremes are near the fronts of ex- tratropical cyclones, and about 24% are near the ex- Supplemental information related to this paper is available at tratropical cyclone low pressure center. In northeastern the Journals Online website: https://doi.org/10.1175/JCLI-D-19- United States, 60%–80% of 6-hourly precipitation ex- 0543.s1. tremes occur within the circulation of a cyclone in winter (Pfahl and Wernli 2012). Numerous case studies of Corresponding author: Edmund K. M. Chang, kar.chang@ hazardous weather for the winter over the United States stonybrook.edu demonstrate that these are mostly related to the passage

DOI: 10.1175/JCLI-D-19-0543.1 Ó 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Unauthenticated | Downloaded 10/09/21 08:48 PM UTC 5372 JOURNAL OF CLIMATE VOLUME 33

2 FIG. 1. (a) The difference in storm track activity {in terms of filtered SLP variance statistics, i.e., ECApp [see Eq. (6)]; hPa } between the 10 high ECApp winters and the 10 low ECApp winters based on the MERRA-2 product. (b) Difference in the frequency of 99th-percentile extreme precipitation events (%; based on CPC daily gauge-based precipitation data) between high ECApp and low ECApp winters. We highlight the precipitation in two regions by superposing two boxes: the Great Lakes and Ohio Valley (368–508N, 958–808W) and the northwestern United States (448–508N, 1258–1118W). The dotted regions in (a) and the cross-hatched regions in (b) show significant difference at the 5% level based on the t test. of deep cyclones (e.g., Bosart 1981; Zhang et al. 2002; moisture convergence being largely responsible across Cardone et al. 1996). Detailed statistical composites of the west but intensified transient eddy moisture con- extratropical cyclones have related the extreme precip- vergence wetting the northeast (Seager et al. 2014). itation to cyclone depths (Polly and Rossow 2016)or Over the southwestern United States, the models’ pro- cyclone intensification (Rudeva and Gulev 2011). Over jected spring drying is mainly caused by decreased mean the U.S. west coast, many such events have been linked moisture convergence, partially compensated by the to atmospheric rivers (Ralph et al. 2006; Guan et al. increase in transient eddy moisture convergence (Ting 2010), which are also related to cyclones (Zhu and et al. 2018). Hence future changes in precipitation de- Newell 1994; Ralph et al. 2004). These extreme precip- pend on how the changes in the mean flow or the tran- itation events not only are important for their weather sient moisture convergence dominates one another. impacts, but also provide for much of the winter snow- Most previous studies focused on the meteorological pack that is critical for water resource (e.g., Eldardiry cause for each extreme precipitation event. Ma and et al. 2019). Chang (2017) quantified the response of extreme pre- Apart from the strength of cyclones, modeling studies cipitation frequency against cyclone activity variations have shown that changes in moisture flux convergence over the continental United States winter by winter. are also important for modulating extreme precipitation Associated with an overall increase in cyclone activity, (Meehl et al. 2005). Wong et al. (2018) studied the this response mostly focuses on the Ohio Valley–Great precipitation structure inside extratropical cyclones by Lakes region, showing much enhanced extreme precip- decomposing the large-scale moisture flux convergence itation rate in high cyclone activity winters, together into two moisture tendency terms: moisture advection with some signal in the northwestern United States and moisture change due to dynamical convergence. Figure 1 shows that during winter with enhanced storm Precipitation type and amount in different sectors of the track activity, the frequency of extreme precipitation cyclones are related to the relative contribution of the events is strongly enhanced over the aforementioned two terms to the total moisture flux convergence (Wong two regions (Fig. 1b). The apparent difference in spatial et al. 2018). scales of the extreme precipitation regions associated Besides the decomposition according to moisture with cyclone activity over these two regions is consistent transport mechanisms, the moisture budget can also be with the findings of Touma et al. (2018). separated into contributions from different time scales. While Ma and Chang (2017) found these associations, Based on the European Centre for Medium-Range they did not explore the dynamics behind these rela- Weather Forecasts interim reanalysis (ERA-Interim), tionships. This study extends the work of Ma and Chang during the cool season transient eddies converge mois- (2017) and examines the physical mechanisms in terms ture across much of the United States while the mean of large-scale circulation patterns and the associated flow provides moisture to the northwest and dries the moisture transport that support the relationships be- southwest (Seager et al. 2014). Under global warming, tween extreme precipitation and cyclone events, and the CMIP5 models project drying for the southwest and whether the mechanisms that drive the Ohio Valley and wetting to the north, with changes in the mean flow northwestern U.S extreme precipitation are different.

Unauthenticated | Downloaded 10/09/21 08:48 PM UTC 1JULY 2020 M A E T A L . 5373 ð ps To systematically understand the difference between 5 1 1 V r qw dp, (3) the two regions, we examine both the seasonal scale and Q g w 0 daily scale. At the seasonal scale, we examine the fol- lowing questions: How does the moisture budget look as mentioned in Wong et al. (2016), precipitation minus like in high cyclone activity winters and low cyclone evaporation (P 2 E) plus the tendency of total precip- activity winters? Which moisture transport mechanism, itable water (›Q/›t) is balanced by moisture flux con- advection or dynamical convergence, contributes most vergence, which can be further decomposed into two to the total moisture flux convergence in different pla- terms: the tendency related to large-scale dynamical ces? Are there changes in the moisture sources that are convergence (2Q= V) and the tendency related to related to the precipitation extremes in the highlighted moisture advection (2V =Q). The two-dimensional regions? At the daily scale, we investigate the follow- vector V is the vertically integrated velocity of hori- ings: How frequent are the extreme precipitation events zontal w, weighted by the profile in each associated with cyclones? What does the circulation column [Eq. (3)]. To further analyze the strength of pattern look like and how is the moisture transported anomalies at high and low frequency, we compute the during extreme precipitation events? Our results sug- monthly mean and 10-day high-pass transient compo- gest that there are significant differences between these nents for both Q and V using a fast Fourier transform: two regions. The synoptic situations giving rise to indi- 0 vidual extreme precipitation events are not the same. 2V =Q ’2V =Q 2 V =Q0 and (4) Variations among all these extreme precipitation days in 0 both regions are examined through empirical orthogo- 2Q= V ’2Q= V 2 Q0= V , (5) nal function (EOF) analysis of the moisture flux to provide a likely range of synoptic conditions associated where overbarred variables represent monthly mean with these extremes. and primed variables are 10-day high-pass transient components. Similarly, the transient products are first computed on the original grid and then interpolated to 2. Data and methods the 1.5831.58 resolution for each month. a. Data To directly compare with the above moisture budget terms, we use the 3-hourly sea level pressure (SLP) and The Modern-Era Retrospective Analysis for Research hourly precipitation products (both at 0.5830.6258) and Applications, version 2 (MERRA-2), data are used from MERRA-2 to compute the storm track activity, to compute monthly mean moisture tendencies related to seasonal mean precipitation and extreme precipitation large-scale advection and dynamical convergence for di- counts. Here we use the ‘‘PRECTOT’’ precipitation agnostics of the sources of precipitation. MERRA-2 is the output from the GMAO atmospheric model, which is latest of the modern satellite era consistent with the assimilation results for more basic produced by NASA’s Global Modeling and Assimilation variables (like SLP, , etc.) and can close the model Office (GMAO; Gelaro et al. 2017). It aims to provide moisture budget when the analysis increment for water improved accuracy in global variability vapor is taken into account. Since our previous study (Bosilovich et al. 2017). (Ma and Chang 2017) used daily precipitation for ex- The moisture tendency terms are described in Wong treme events, here we transform the hourly data into et al. (2016), and are calculated from the hourly MERRA-2 daily. To close the moisture budget [Eq. (1)], we also use products of vertically integrated moisture flux and total the monthly mean surface evaporation flux (0.583 precipitable water on a 0.625830.58 grid. Finite differ- 0.6258) from MERRA-2. The period for this analysis is encing is used for horizontal gradients and convergence. between 1980 and 2011. The final products are then interpolated onto 1.5831.58 We have also compared GMAO precipitation and resolution by local area averaging. Based on the water evaporation products with the ERA-Interim reanalysis vapor budget equation (e.g., Peixoto and Oort 1992) precipitation and evaporation, and Climate Prediction ›Q Center (CPC) gauge-based precipitation data for many P 2 E 1 52= (QV) 52Q= V 2 V =Q, (1) ›t of the analyses presented in our previous study (Ma and Chang 2017) and made sure that they are highly con- where sistent. For example, the extreme precipitation fre- ð quencies derived from MERRA-2 products are largely ps 5 1 consistent with those derived from CPC data (cf. Fig. 2b Q r qdp and (2) g w 0 with Fig. 1b), and the 10 high and 10 low storm track

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FIG. 2. Composite difference between 10 high ECApp winters and 10 low ECApp winters for the MERRA-2 data for (a) precipitation 2 2 (mm day 1), (b) 99th-percentile extreme precipitation frequency, (c) evaporation (mm day 1), (d) moisture advection 2V =Q 2 2 (mm day 1), (e) moisture convergence 2Q= V (mm day 1), and (f) total moisture budget, which is the sum of (d) and (e). Also shown are the product of monthly mean terms: (g) 2V =Q, (h) 2Q= V, and (i) sum of (g) and (h), along with the covariance of 10-day high- 0 0 pass transient terms: (j) 2V =Q0, (k) 2Q0= V , and (l) sum of (j) and (k). The cross-hatched regions are significant at the level of 5%. years calculated from MERRA-2 data (3-hourly SLP; 1979 to 2010. Figures 3–12 (described in detail below) 0.5830.6258) are exactly the same set of years as se- are based on ERA-Interim data. lected by using ERA-Interim data (6-hourly SLP; 2.583 To calculate the cyclone frequency in winter, we use 2.58 or 0.75830.758). Note that CPC (and not reanalysis) the cyclone track product as described in Chang and data are used to quantify extreme precipitation and se- Yau (2016). The tracking is performed based on ERA- lect the extreme precipitation days. To further study the Interim’s 6-hourly SLP product (2.5832.58) for each monthly mean tendency associated with large-scale dy- winter, using the objective tracking algorithm of Hodges namical divergence, we use the monthly mean dynami- (1994). Here we use the filtered product, where the cal divergence and specific humidity (0.75830.758)at32 seasonal mean is first removed for each winter, and high- pressure levels from ERA-Interim. pass filtering is performed over the spatial anomalies For the extreme events, we define the extreme with only wavenumbers 5–70 retained. Hence the large precipitation days based on the CPC gauge-based spatial scale and low-frequency temporal scale back- daily precipitation data (0.25830.258). To examine ground is removed before the tracking algorithm is run. the circulation patterns on these extreme days, we use While previous studies (e.g., Neu et al. 2013; Raible et al. the 6-hourly SLP, 500-hPa geopotential height, ver- 2008) have suggested that cyclone tracks may be de- tically integrated divergence of moisture flux, and pendent on the tracking algorithm, statistics for strong vertically integrated water vapor flux from ERA- cyclones are more robust. Here we are mainly con- Interim, all at a resolution of 0.75830.758,from cerned with the presence (or not) of significant cyclones

Unauthenticated | Downloaded 10/09/21 08:48 PM UTC 1JULY 2020 M A E T A L . 5375 during extreme precipitation events. All negative SLP cyclone or storm track activity (Lau 1988; Feser et al. anomaly centers are tracked, with tracks lasting less than 2015; Alexander et al. 2005; Chang et al. 2012, 2016;etc.). 2 days or traveling less than 1000 km removed. Our results are mainly shown through composite analyses. We summarize each composite by averaging b. Methods or by counting extreme events and test their differ- There are two families of methods that are widely ence through a t test to compare their means or used to study cyclone activity. The first directly studies proportions. cyclone trajectories using objective tracking algorithms According to Ma and Chang (2017),therearetwo (Hodges 1994, 1999; Hoskins and Hodges 2002), as regions that show strong variability of extreme pre- mentioned in the last section. The second, on the other cipitation frequency (99th percentile) associated with hand, studies the synoptic time scale variability using variations of ECApp over the continental United variance statistics (Blackmon et al. 1977, 1984a,b; Lau States: the Great Lakes–Ohio Valley (368–508N, 958– 1988; Wallace et al. 1988). The passage of a cyclone close 808W) and northwestern United States (448–508N, to any location generates rapid pressure perturbations, 1258–1118W) (marked by the rectangles in Fig. 1b). circulation anomalies, and advection. Thus, These two regions are also favored by teleconnections the use of temporal variance or covariance is an alternative in winter, such as ENSO and PNA (e.g., Kunkel and way to represent cyclone activity. These statistics generally Angel 1999; Montroy et al. 1998; Ning and Bradley display two maxima spanning the North Pacific and North 2015; Leathers et al. 1991). The extreme precipitation Atlantic Oceans (e.g., Chang et al. 2002). These centers days (based on CPC precipitation data) for each re- coincide with the ‘‘storm track’’ region, introduced by gion are selected in the following way: we put a box earlier surveys of cyclone trajectories of individual cyclone over each of the region mentioned above. Within centers (e.g., Petterssen 1956, 267–276). One should keep each box, we only consider the grid points at which in mind that by using the filtered variance metrics to variations in extreme precipitation frequency are measure the storm track activity, the variance related to foundtobesignificantlycorrelatedwiththosein anticyclones is also included. However, anticyclones are cyclone activity by Ma and Chang (2017).Thereare usually slow moving and have pressure anomalies weaker two reasons for only selecting the significant points: than the cyclones (Hoskins and Hodges 2002), hence the 1) The regions we are interested in and also high- variance is likely to be dominated by cyclones. In addition, lighted by previous studies are not necessarily rect- our results will show that anticyclones are also important angles. 2) In certain locations, the precipitation is for generating extreme precipitation. generated by orographic lifting, and hence only the In this study, we use both methods but for different grid points close to the mountains will have significant purposes. To validate the relationship between cyclone response. This can be important for the northwestern and extreme precipitation, during the extreme precipi- U.S. box, since the significant points in that box do tation days, we count the number of times a tracked low not cover much of the area and occur mainly in two pressure center is within 500 km of a grid point, which clusters: one being the coastal part of Washington is equivalent to assuming that a cyclone has a radius State, and the other in western Montana and northern of about 500 km, a threshold widely used in previous Idaho (Fig. 1b). studies (e.g., Sinclair 1997; Grise et al. 2013). The total The daily accumulated precipitation amount of these count for all composited events will be normalized as the selected grid points is averaged as a single time series. average count per day. Since the temporal variance From this time series, we pick the days with the largest method has been shown to be a good representation 5% of values and define them as the extreme precipi- that captures the essence of midlatitude cyclone ac- tation days for this region. Since the daily data cover tivity, we also use it to show the interannual variability 32 years, about 90 winter days per year, the top 5% of cyclone activity. To be consistent with our previous provides 145 extreme precipitation days, which are study (Ma and Chang 2017), we use the 24-h difference shown in Tables S1 and S2 in the online supplemental filtered variance of SLP to measure extratropical cy- material for the Great Lakes–Ohio Valley region and clone activity (ECA; Wallace et al. 1988), referred to northwesternUnitedStates, respectively. as ECApp: To examine the variations among these 145 extreme precipitation days, we perform an EOF analysis on the ECApp 5 [SLP(t 1 24 h) 2 SLP(t)]2 , (6) column-integrated water vapor flux, concatenating the zonal and meridional component into a single where the variance is taken for each winter. Similar field. The water vapor flux is chosen for the EOF metrics are widely used in previous work to quantify analysis because it contains information regarding

Unauthenticated | Downloaded 10/09/21 08:48 PM UTC 5376 JOURNAL OF CLIMATE VOLUME 33 the moisture sources and sinks as well as transport of Florida. Differences in extreme precipitation fre- pathways. quency from MERRA-2 (Fig. 2b) have patterns that are similar to those from CPC precipitation (Fig. 1b), with MERRA-2 having a weaker signal over the Ohio Valley 3. Moisture budget anomalies over seasonal that is more concentrated around the Great Lakes, and a time scale weaker signal over the northwestern United States. In Ma and Chang (2017), ECApp is averaged over the Near the Gulf of Mexico coast, MERRA-2 shows a continental part of the domain (608–1408W, 258–558N) more pronounced negative signal. Figure 2a shows the and the highest and lowest 1/3 (10 winters) are selected difference in seasonal mean precipitation between the to form the high and low composites from the 32 years high and low composites. Similar to the response in ex- of data (1979–2010). Within each composite, we count treme precipitation frequency (Fig. 2b), Fig. 2a shows a the 99th-percentile precipitation events, which are de- significantly positive signal over the Great Lakes and fined over gridded daily precipitation data when the Ohio Valley, and a strongly negative signal over the daily precipitation amount exceeds the local top first- Gulf of Mexico and subtropical Atlantic. A significantly percentile threshold. In the rare cases that the threshold positive signal can be seen in southwestern Canada is not meaningful (e.g., in very dry regions where the top spreading into northwestern United States. In summary, first percentile of precipitation might be zero), the points the response in extreme precipitation frequency is con- are masked as missing. For any grid point, the non- sistent between MERRA-2 and CPC, and the response missing part is used if the fraction of missing data is less in extreme precipitation frequency is consistent with the than 10% of its length; otherwise the point is not in- response in seasonal mean precipitation. cluded in the analysis. Figures 2d and 2e show the response of the mois- Figure 1 reproduces part of Fig. 4 of Ma and Chang ture advection (2V =Q) and dynamical convergence (2017). Figure 1a shows the composite difference in (2Q= V) contributions to the moisture budget, and ECApp, which is highly consistent with Fig. 1c of Fig. 2f shows the sum of these two terms. The advection Ma and Chang (2017), except that MERRA-2 shows and convergence terms show opposite signs in many a slightly larger difference (by 5–10 hPa2) over the cen- places: the coastal region of Washington and Oregon tral United States. Figure 1b shows the difference in receives strong moisture advection from the Pacific, the frequency of 99th-percentile extreme precipitation while there is strong divergence in these regions and the events between the high and low composite based on eastern Pacific. The sum is still positive for the coastal CPC precipitation data, which highlights the Ohio regions of Washington and Oregon, implying the ad- Valley and the Pacific Northwest, where the absolute vection is slightly stronger. From the central United value of the difference is between 0.6% and 1.5%. States (Texas, Oklahoma, Kansas) to the Ohio Valley, Statistically, the probability of a 99th-percentile event there is strong convergence; the advection there is neg- happening is 1%. Thus, the response mentioned above ative but much weaker. Close to the north shore of the is very strong, showing the significant impacts of storm Great Lakes, there is a small region where the advection track variations. Note that while we base our compos- is significantly positive while the convergence is much ites on the magnitude of ECApp, Ma and Chang (2017) smaller. Along the coastal southeastern United States, showed that this ‘‘mode’’ is identical to the leading the advection is negative while the moisture conver- mode of covariability between ECApp and extreme gence is positive; there is significant cancellation be- precipitation frequency as found from a singular value tween the two and their sum is a much weaker residual. decomposition analysis of the covariance between To close the moisture budget, we also show the com- ECApp and extreme precipitation frequency over the posite difference for evaporation in Fig. 2c using the continental United States. MERRA-2 product. Based on Eq. (1), for precipitation, Figure 2 shows the differences in MERRA-2 precip- the variability of remote evaporative source might also itation statistics and moisture budgets between high and have significant contribution to our studied regions. In low ECApp years. Results based on ERA-Interim data Fig. 2c, there is significantly more evaporation east of 2 corresponding to Figs. 2d–i are qualitatively consistent Cuba and equatorward of 288N (0.6–0.9 mm day 1) and and are shown in Fig. S1 of the online supplemental less evaporation along the eastern U.S. coast into the 2 material for reference. Figure 2b shows the difference in central Atlantic Ocean (from 20.6 to 21.2 mm day 1)in 99th-percentile extreme precipitation frequency based the high ECApp winters than the low ECApp winters. on MERRA-2 precipitation, which highlights the posi- In the Gulf of Mexico, the evaporation is significantly tive response around the Great Lakes and the negative reduced along the Texas coast and the south end of response over the Gulf of Mexico and the Atlantic east Texas, and not significantly changed in the remaining

Unauthenticated | Downloaded 10/09/21 08:48 PM UTC 1JULY 2020 M A E T A L . 5377 area. Along the coast of northwestern United States and As discussed in section 2 [Eqs. (4) and (5)], the western Canada, the difference in evaporation is sig- monthly mean advection and convergence terms are 2 nificantly positive (0.3– 0.6 mm day 1). Over the conti- decomposed into the products of seasonal means nental United States, the difference is much smaller. (Figs. 2g,h) and mean of transient covariance terms The correlation coefficients between evaporation and (Figs. 2j,k). Figures 2g and 2h show the response of area averaged ECApp over the United States are also mean moisture advection (2V =Q) and mean con- significantly positive to the east of Cuba and near the vergence (2Q= V), with Fig. 2i as the sum of them. west coast of Canada and northwestern United States, Similarly, Figs. 2j and 2k show the response of tran- 0 and not significant in the Gulf of Mexico (see Fig. S2c in sient moisture advection (2V =Q0) and transient 0 the online supplemental material). The positive evapo- convergence (2Q0= V ), with Fig. 2l as the sum of ration anomalies east of Cuba is in the path of the them. Over much of the United States and the eastern clockwise circulation of moisture transport anomalies Pacific, the transient terms are much weaker than the (see discussions below), and hence it might have some mean terms, even though they are still significant. But positive contribution to the precipitation in Ohio Valley. over the Gulf of Mexico and along the coastal states Along the coast of the northwestern United States, the nearby, the transient moisture advection (Fig. 2j)is positive anomaly of evaporation is also in the path of the dominant over the mean advection term (Fig. 2g), composite mean moisture transport (see discussions since the total advection’s response (Fig. 2d)shares below), but the evaporation difference is only one-half the same sign as the transient advection’s response. of the values in subtropical Atlantic. Results based on Comparing with the transient advection, the transient ERA-Interim are consistent and are shown in supple- convergence (Fig. 2k)ismuchweakeroverthedo- mental Fig. S2. Over these regions, SST anomalies are main. The negative transient advection’s response in negative [not shown, but see Fig. 13c of Ma and Chang the southeastern United States (Fig. 2j) is largely (2017)], and thus enhanced evaporation is likely due to cancelled by the positive response of mean advection increase in surface wind. These results suggest that (Fig. 2g) and mean convergence (Fig. 2h), leaving only changes in evaporation may contribute, but further an- the coastal region of Alabama and Georgia with alyses using backward trajectories from the extreme negative values (Fig. 2f). Except for the southeastern precipitation regions will be needed to quantify the United States, much of the United States is still contributions from increased evaporation. dominated by the mean moisture budget terms. The sum of the advection and convergence terms Since we are showing the response to storm track (Fig. 2f) is consistent with the response of seasonal variations, and the cyclone activity mostly involves dis- mean precipitation (Fig. 2a), especially after evapora- turbances with a period of 2–10 days, we might wonder tion changes are taken into account (Fig. S3 in the on- why the mean terms dominate in many places. Our hy- line supplemental material). Over southwestern Canada pothesis is that even though cyclones are by themselves and the northwestern United States, there are two parallel a high-frequency phenomenon, it is not necessary that bow-shaped lines of enhanced values, both for the re- their contribution to the moisture budget must stay in sponse of seasonal mean precipitation (Fig. 2a)andforthe the corresponding high-frequency range. Stronger cy- sum of moisture budgets’ response (Fig. 2f), one over clone activity usually increases the seasonal mean dy- Washington and Oregon and the other in northern Idaho namical convergence (given anticyclones are usually and western Montana. These bow-shaped signals corre- weaker than their nearby cyclones), hence enhancing spond to the two local maxima of extreme precipitation the seasonal mean moisture convergence. Similarly, rate based on CPC’s results (Fig. 1c). From a topographic variations of cyclone activity contribute to the seasonal map (not shown), it can be seen that these two parallel mean flow due to eddy momentum transports, thus bands correspond to the Cascade Range and the Rocky affecting the mean moisture advection. On the other Mountains, respectively. With strong advection from the hand, cyclone activity is also affected by variations in Pacific (Fig. 2d), air is forced to climb over the mountains the mean flow, with stronger flow (indicating stronger resulting in orographic precipitation. This is probably why baroclinicity) and convergence east of quasi-stationary the northwestern United States can get extreme pre- troughs being favorable conditions for enhanced cy- cipitation without positive convergence. Based on clone activity (e.g., Chang et al. 2002). Consequently, conservation of Ertel’s PV and mass, such upward detailed explanation of what determines whether the motion is associated with divergence instead of conver- mean response or the transient response should dom- gence. Stronger airflow is expected to give rise to stronger inate still needs further investigation. divergence, which is consistent with strong moisture di- Since in the Ohio Valley it is the response of the mean vergence seen in the northwestern United States (Fig. 2e). convergence term (2Q= V) that dominates, we further

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FIG. 3. The interannual variations of mean moisture convergence 2d(Q= V) is decomposed and approxi- mated by two terms: (a) the product between the variations of precipitable water dQ and the averaged mean 2 dynamical convergence 2= V (mm day 1) and (b) the product between the variations of mean dynamical 2 convergence 2d(= V) and the averaged precipitable water Q (mm day 1). (c) Composite difference for precipitable water between the 10 high ECApp winters and 10 low ECApp winters (mm). The stippled regions show significant difference at the 5% level. (d) Averaged precipitable water between both composites (mm). 2 (e),(f)Asin(c)and(d),butforthemean dynamical convergence (day 1). The regions where the surface pressure has ever been below 850 hPa has been masked out for the dynamical convergence and associated products. investigate whether it is the variations of seasonal mean the subtropical Atlantic, and the eastern Pacific, the precipitable water Q or the variations of seasonal mean 2Qd(= V) term (Fig. 3b) is much larger than the convergence (2= V) that is more important between 2dQ(= V) term (Fig. 3a), which is close to zero almost the high and low storm track winters. We use the everywhere. So, it is the variations of mean dynamical monthly mean divergence and specific humidity from convergence 2d(= V) instead of the variations of mean ERA-Interim and integrated through 32 pressure levels precipitable water dQ that dominates this term. This to calculate 2= V and Q for each winter. Then we result further implies that the contribution of evapora- decompose the variations of 2Q= V in the follow- tion variations over the moisture source region might ing way: not be the dominant term for the precipitation in Ohio Valley. We have also shown the anomalies and average 2d(Q= V) ’2dQ(= V) 2 Qd(= V), (7) of precipitable water in Figs. 3c and 3d, separately. The anomalies in the precipitable water shows its maximum where the dX means the high composite average of X in southeastern United States (Fig. 3c), but the value minus the low composite average of X, and the non- represents only about a few percent of the mean pre- d term is approximated by the average of high and low cipitable water (Fig. 3d). On the other hand, in the Ohio composite. Valley and the Great Lakes, the anomalies in the con- 2 Figures 3a and 3b compare these two terms. In most vergence is about 0.04 day 1 (Fig. 3e), but the averaged places including the Ohio Valley, the Gulf of Mexico, mean convergence is of the same order of magnitude.

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Thus the 2Qd(= V) term (Fig. 3b) dominates over the contrast is also captured by MERRA-2 at the seasonal 2dQ(= V) term (Fig. 3a) over these regions. scale (Fig. 2f). In addition, MERRA-2 also shows that the drying in Texas is mostly because of the negative advection (Fig. 2d), even though the moisture conver- 4. Conditions on extreme precipitation days gence is positive there (Fig. 2e). Finally, Figs. 4i and 4j We have examined the response of extreme precipi- show the moisture flux in the extreme composite and its tation frequency and moisture budget to the variations anomalies. Most of the water vapor flux comes from the of storm track activity at the seasonal time scale. Now Gulf of Mexico, which is the main source of moisture for we will examine how these extreme precipitation events the eastern United States, but part of the flux also comes are related to cyclones in the Ohio Valley and north- from Texas. In the extreme composite, the vapor flux western United States. is much stronger and more poleward than the climatol- ogy (not shown), but quickly turns into pure eastward a. Large-scale conditions transport in the North Atlantic, creating clockwise cir- culation anomalies in Fig. 4j, which is consistent with 1) OHIO VALLEY the higher SLP, positive 500-hPa geopotential height As described in section 2, we select 145 extreme pre- anomalies, and smaller cyclone count in the North cipitation days for the Ohio Valley and Great Lakes Atlantic, shown in Figs. 4b, 4d, and 4f. In summary, a region. Figure 4 shows the composite average (Fig. 4, left cyclone in the Ohio Valley, accompanied by an anticy- column) and the composite anomalies which is the de- clone to its east, provides a strong pressure gradient and viation from the (Fig. 4, right column) for southwesterly flow that give rise to strong moisture these days. During this extreme precipitation composite, transport into the Ohio Valley, fueling these extreme the SLP is about 6–10 hPa lower than climatology within precipitation events. the box, and about 10 hPa higher over the North To further investigate the conditions favorable for Atlantic (Figs. 4a,b). The 500-hPa geopotential height producing extreme precipitation, we stratified the ex- shows clearly Rossby wave–like troughs and ridges for treme precipitation days into days in which a cyclone the composite (Fig. 4c), with the box locating east of a center can be located within the high cyclone density trough and west of a ridge, a region that favors cyclo- region in Fig. 4e (area covered by the 0.2 contour; 99 genesis and upward motion. In particular, the anoma- cases or about 2/3 of the cases) and those in which a cy- lous height field shows a zonally oriented synoptic-scale clone is not identified by the tracker over this region. wave train pattern with amplitude over 100 m (Fig. 4d; The composite SLP and moisture flux anomalies for the see Wallace et al. 1988; Chang 1993). We have also ex- cyclone cases are shown in Figs. 5a and 5b. These com- amined the composite average for 1 day before and posites resemble Figs. 4b and 4j, except that the cyclonic 1 day after the extreme precipitation days (not shown). anomaly is even slightly stronger. For the cases when Together they show clear eastward wave propagation. extreme precipitation occurred but a cyclone is not The cyclone count per day is strongly enhanced within identified by the tracker, the composites (Figs. 5c,d) still much of the box extending southwestward and is sig- show a weak cyclonic anomaly resembling a trough nificantly reduced over the North Atlantic (Figs. 4e,f). (likely the location of a diffuse cyclone or a cold front) The cyclone count, SLP, and 500-hPa geopotential over the same region, but a much stronger and south- height pattern together confirm the relationship be- westward extended ridge over the western Atlantic. tween the extreme precipitation events and midlatitude The ridge–trough couplet gives rise to a strong mois- cyclones. Clearly, this relationship can be explained by ture flux anomaly over the southeastern United States, typical midlatitude synoptic (Rossby) wave dynamics. again providing very strong moisture transport into the Figures 4g and 4h show the convergence of moisture Ohio Valley. flux in the extreme composite and its anomalies from the How are these conditions different from regular cy- climatology. The maximum of moisture flux conver- clone days? We have also examined cases in which a gence is located near the maximum of cyclone count cyclone is located within the same region but no extreme except displaced slightly eastward. In a typical cyclone, precipitation occurred. It turns out that the intensity the poleward airstream of warm and moist air [the warm of the cyclones associated with extreme precipitation conveyor belt (WCB)], which runs ahead of the cold (median intensity 18 hPa) is higher than those that do front and climbs over the warm front, is usually east of not produce extreme precipitation (median intensity the low pressure center of the cyclone. Apart from 12 hPa). Nevertheless, there are cases in which there is a the moisture convergence in the Ohio Valley, there is strong cyclone without causing extreme precipitation. also a region of moisture flux divergence in Texas. This Composites based on such cases in which cyclones with

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FIG. 4. (a) SLP averaged within the 145 extreme precipitation days (based on CPC gauge-based daily precipi- tation data) defined for the box around the Great Lakes and Ohio Valley (hPa). (b) Difference between (a) and the climatology (hPa), where the stippled regions show significant difference at the 5% level. The remaining panels are presented in the same way as (a) and (b), but for (c),(d) 500-hPa geopotential height (m); (e),(f) cyclone density 2 using 500-km radius (day 1); (g),(h) convergence of moisture flux, which is the sum of moisture convergence and 2 2 2 advection (mm day 1); and (i),(j) column-integrated water vapor flux (kg m 1 s 1). All of the variables except precipitation are based on 6-hourly ERA-Interim data.

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FIG. 5. Anomalies of SLP and moisture flux averaged for the composite that are (a),(b) extreme precipitation days for the box and have at least one cyclone located within the 0.2 contour of Fig. 4e on that day (99 days); (c),(d) extreme precipitation days for the box but have no cyclone located within the 0.2 contour of Fig. 4e on that day (46 days); and (e),(f) nonextreme precipitation days but have at least one cyclone located within the 0.3 contour of Fig. 4e on that day with a daily maximum intensity at least 17 hPa (26 days). In this figure, for counting cyclones and finding the daily maximum intensity, we represent a cyclone as all of the grid points’ values 100 km from the tracked cyclone center. intensity stronger than 17 hPa occurring within the mentioned before, the grid points considered are only 0.3 contour in Fig. 4e are shown in Figs. 5e and 5f. For the significant ones shown in Fig. 1c, so the extreme these cases, a deep cyclone is found over the Ohio precipitation mostly happens in two regions: the coastal Valley, but the ridge to its east is much weaker and re- region of Washington and Oregon, and northern Idaho treated northward. The absence of the southwestward and western Montana. This can be directly observed in ridge extension along the Atlantic coast means that the Fig. 6g, which shows the convergence of moisture flux in pressure gradient over the southeastern United States is the extreme composite, and Fig. 6h, which shows the much weaker despite there being a strong cyclone, thus difference from climatology. This feature is also cap- the moisture flux anomaly over that region is also much tured by MERRA-2 in the seasonal mean precipitation’s weaker (Fig. 5f). These results show that apart from the response (Fig. 2a) and the response of the total moisture existence of a cyclone over the Ohio Valley, the south- budgets (Fig. 2f). westward extended ridge near the Atlantic coast is also Instead of a synoptic wave-like pattern, the north- critical for the occurrence of extreme precipitation over western U.S. composites show a pair of cyclonic and the Ohio Valley. anticyclonic anomalies aligned northwest to southeast, regardless of SLP (Figs. 6a,b), 500-hPa geopotential 2) NORTHWESTERN UNITED STATES height (Fig. 6d), and cyclone count (Fig. 6f). Comparing For the northwestern United States (448–508N, 1258– with the Ohio Valley, the SLP shows much larger spatial 1118W), composites for the extreme precipitation days scale (Fig. 6a) and the 500-hPa geopotential height also and anomalies from climatology are shown in Fig. 6.As shows much longer wavelength (Fig. 6c). The structure

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FIG.6.AsinFig. 4, but for the extreme precipitation days defined for the box over the northwestern United States. of the height anomalies (Fig. 6d) is distinctly different aforementioned dipole structures over the eastern Pacific from those associated with zonally oriented synoptic- resembling an atmospheric river. The composite vertically 2 2 scale Rossby wave trains (see Wallace et al. 1988; Fig. 4). integrated water vapor flux value (over 400 kg m 1 s 1 Unlike their Ohio Valley counterparts, cyclones associated over the eastern Pacific) is also consistent with the exis- with precipitation extremes in this region are located tence of an atmospheric river (e.g., Guan and Waliser mostly to the north and northwest of the region with ex- 2015). Comparing Figs. 6a and 6b, it is clear that the long treme precipitation. The most important feature is a long corridor for enhanced moisture transport is due to the corridor of moisture transport (Figs. 6i,j) between the superposition of the cyclonic and anticyclonic anomalies

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21 FIG. 7. Composite of moisture budget anomalies for 145 extreme precipitation days (mm day ): (a),(b) moisture advection; (c),(d) dynamical moisture convergence; and (e),(f) change in storage for (left) the Ohio Valley and (right) the northwestern United States. on top of the climatological Aleutian low and east Pacific activity, we found that variations in moisture convergence subtropical high, giving rise to a long corridor of strong dominate over the Ohio Valley, while changes in mois- pressure gradient that provides the strong low-level flow ture advection dominate over the northwestern United for the enhanced moisture transport. When this strong States. Here we will examine whether similar differences moisture transport reaches the Cascade Range and the can be found for the extreme precipitation days. Rocky Mountains, it is forced to go upward by the The interpretation of the moisture budget for individual mountains, producing heavy orographic precipitation. days is not as straightforward as that for the seasonal mean. Thus, in this region, rising motion is not directly forced by Over a season, the change in storage [third term on the left- the cyclones themselves, but is mostly due to the fixed hand side of Eq. (1)] averages out to be much smaller than orography. This explains the very different cyclone dis- all the other terms and can be neglected. However, over tributions relative to the location of the precipitation one day, the change in storage can be as large as the other extremes in these two regions. Comparing with the pre- terms and must be taken into account. Figure 7e shows the ceding subsection, we see that from the moisture budget composite of this term for the extreme precipitation days to weather patterns, the northwestern United States for Ohio Valley. Between the beginning and end of the shows very different physical mechanisms from the Ohio day, there is significant reduction in precipitable water to Valley. These results also indicate that anticyclones are the southwest of the region, and significant increase to the not always associated with sunny days. They do have east of the region, consistent with the northeastward positive influence on extreme , perhaps not propagation of the synoptic-scale system bringing warm locally but on the larger scale. and moist air northeastward toward the east coast of the United States, with cold dry air moving into the southern b. Moisture budget part of the United States behind a cold front. In section 3, when we examined the winter mean The decomposition of the convergence of moisture moisture budget modulated by the strength of cyclone flux anomaly (Fig. 4h) into moisture advection and

Unauthenticated | Downloaded 10/09/21 08:48 PM UTC 5384 JOURNAL OF CLIMATE VOLUME 33 dynamical moisture convergence is shown in Figs. 7a explain 7% or less of the variance each and will not be and 7c, respectively. Both exhibit positive contribution discussed. The value of the principal component for over the Ohio Valley. The contribution from the ad- each day quantifies how strongly the moisture transport vection term appears to be larger than that from the pattern on that particular extreme day resembles the convergence term. However, in comparing Figs. 7a and sum of that EOF and the mean pattern. High and low 7e, it is clear that a significant part of moisture advection composites shown in these figures are based on the top is associated with the aforementioned northeastward and bottom thirds of the principal component values. displacement of the warm moist air and does not nec- These composites provide a range of likely synoptic essarily contribute to the heavy precipitation. Note that scenarios associated with the extreme precipitation Figs. 7a,c and 4h appear to be much noisier than Fig. 7e. days, and may be useful for identifying the potential for This could partly be due to the noisy distribution of the occurrence of heavy precipitation. The differences precipitation, but it should be noted that the moisture between high and low composites that show the struc- flux terms are averaged over four 6-hourly instanta- ture of the EOFs (as well as SLP composites) are shown neous reanalysis snapshots, whereas the change in in Figs. S4–S8 of the online supplemental material. precipitation represents the integral of ›Q/›t over a The composites for EOF1 generally show a Rossby 24-h period and is thus expected to be smoother. wave phase shift between the high and low composites Nevertheless, Fig. 7c shows that dynamical conver- (Figs. 8a,b). In the high composite, the trough is located gence clearly significantly contributes to the moisture at about 1108W and the ridge at about 808W, whereas in budget for extreme precipitation events over the the low composite the trough is at around 978W and the Ohio Valley. ridge at about 728W. In the high composite, more cy- Similar decomposition for northwestern United States clones occur toward the southwest of the box (Fig. 8a, is shown in the right panels of Fig. 7. Clearly, consistent shading) with the low pressure center located in Texas with the monthly mean budget (Fig. 2), over this region (online supplemental Fig. S4a), hence the warm con- advection (Fig. 7b) dominates, with the contribution veyor belt (WCB) carries more moisture into the from dynamical convergence (Fig. 7d) being opposite to southern part of the box (Fig. 8c); in the low composite, the sign of the moisture flux convergence (Fig. 6f), cyclones are located farther northeast (Fig. 8b and similar to the seasonal moisture budget discussed above. Fig. S4b), resulting in more moisture convergence over In addition, in this region advection does not lead to the northeastern United States (Fig. 8d). The moisture northeastward movement of the warm and moist air fluxes for both cases are oriented southwest to north- 2 2 mass, with little change in storage found (Fig. 7f). This east and are rather strong (over 500 kg m 1 s 1), with is likely due to the moisture being largely exhausted the main difference being an east–west shift in their by orographic precipitation after uplift by the moun- location (Figs. 8e,f). tains. Thus Fig. 7 confirms that for individual extreme EOF2 contrasts stronger and weaker moisture flux, precipitation events, moisture advection dominates as can be seen from the 500-hPa geopotential height over the northwestern United States, while dynamical (Figs. 9a,b) and the norm of the moisture flux (Figs. 9e,f). moisture convergence contributes significantly over In the low composite both the height gradient and wave the Ohio Valley, qualitatively consistent with the amplitude at 500 hPa are stronger, implying stronger conclusion reached above. winds, which is consistent with stronger moisture flux, while the wave amplitude is weaker in the high com- c. Variations in moisture transport posite. Even though the moisture flux flowing into the box is weaker in the high composite, the outgoing 1) OHIO VALLEY flux is even weaker (Fig. 9e), resulting in strong Figures 4 and 6 summarize the mean synoptic situa- moisture convergence within the box (Fig. 9c). On the tion of the extreme precipitation cases and compare other hand, even though the low composite shows them with climatology. However, not all cases are the much stronger moisture flux, much of the moisture is same, and we will examine some differences between carried through the Ohio Valley toward the Northeast these cases. For the Ohio Valley, an EOF analysis is (Fig. 9d). Thus, stronger incoming moisture flux does conducted on the column-integrated water vapor flux not necessarily imply stronger moisture convergence from the 145 extreme days for the continental part of the within the region. United States by concatenating the zonal and meridio- EOF3 highlights the orientation of weather patterns nal components of each case into a single vector. The (more meridional or more zonal). In the high com- leading three EOFs explain 28.0%, 16.4%, and 13.4% of posite, the wave amplitude is stronger, the wavelength the variance, respectively. EOF4 and higher modes only is shorter (Fig. 10a), and the moisture flux is more

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FIG. 8. (left) High and (right) low composites for the EOF1 of vapor flux within the 145 extreme precipitation days defined for the box over the Great Lakes and Ohio Valley for (a),(b) 500-hPa geopotential height (contours; 2 contour interval 100 m) and cyclone density (shading; day 1); (c),(d) convergence of moisture flux, which is the sum 2 of moisture convergence and advection (mm day 1); and (e),(f) column-integrated water vapor flux (vectors; 2 2 2 2 kg m 1 s 1) and the norm of the vectors (shading; kg m 1 s 1). poleward (Fig. 10e), whereas in the low composite the coast, and strong moisture flux flowing poleward across wave amplitude is weaker and the moisture flux is the Gulf Coast. more zonal (Figs. 10b,f). Cyclones also expand more 2) NORTHWESTERN UNITED STATES poleward in the high composite and spread eastward in the low composite (Figs. 10a,b). The moisture An EOF analysis has also been conducted for the convergence is also affected by the different spatial northwestern U.S. extreme precipitation days, using a orientations: in the high composite, it is concentrated domain covering both the land and ocean (258–608N, within the box (Fig. 10c) whereas in the low composite 1408–1008W). For this case, the leading EOFs are even it extends farther eastward (Fig. 10d). better separated: EOF1 explains 44.1% of the variance, In summary, Figs. 8–10 show that there is a range of and EOF2 19.3%. EOF3 and higher modes explain only synoptic situations that can lead to heavy precipitation 7.4% or less and are not discussed here. The EOF pat- over the Ohio Valley. The trough/ridge axes can occur terns are robust if we expand the domain farther (by 108) over a range of longitudes (EOF1), the magnitude of into the Pacific. moisture flux can vary (EOF2), and the orientation of EOF1 highlights the spatial orientation of the mois- the moisture transport can be more meridional or zonal ture transport. In the high composite, the 500-hPa geo- (EOF3). Nevertheless, while there are differences be- potential height suggests strong southwesterly wind over tween the cases, all groups display a Rossby wave train the eastern Pacific (Fig. 11a). The strong moisture flux at 500 hPa with an amplified ridge near the U.S. Atlantic flows from the low latitudes of central Pacific into the

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FIG.9.AsinFig. 8, but for the EOF2 mode. box (Fig. 11e). Cyclones are located to the west of the strong moisture flux flowing northeastward from the box off the Washington–Oregon coast (Fig. 11a). In the lower latitudes of the central Pacific. However, in the low low composite, the geopotential height contours are composite (Fig. 12f), the Pacific moisture transport cor- much more zonal, and the gradient is weaker over the ridor is much shorter in distance and the magnitude of the 2 2 Pacific (Fig. 11b). The comparatively weaker moisture flux is much lower (only up to about 400 kg m 1 s 1), and flux flows eastward into the box at a higher latitude is associated with partially inland weak cyclones located compared to the high composite (Figs. 11e,f). The cy- north of the moisture transport without an enhanced clone density shows two local maxima, indicating a main anticyclone to the south (Fig. 12b and Fig. S8b). Unlike occluded low in the Gulf of Alaska and a weak sec- the Ohio Valley cases, here stronger incoming moisture ondary cyclone near the U.S.–Canada border (Fig. 11b transport gives rise to stronger moisture convergence and online supplemental Fig. S7b). Both the high and (Figs. 12c,d), likely related to the impacts of the mountain low composites give rise to strong moisture convergence ranges in this region. In summary, Figs. 11 and 12 high- in the Northwest, with that in the high composite being light the fact that there is also a range of synoptic sce- slightly stronger (Figs. 11c,d and Fig. S7l); however, in narios that can give rise to heavy precipitation over the high composite strong moisture convergence ex- northwestern United States. tends southward into Northern California. EOF2 highlights the strength of the moisture transport. 5. Discussion and conclusions The high composite shows strong moisture transport of 2 2 over 600 kg m 1 s 1 similartothatofanatmospheric Our previous study showed the significant impacts of river (Fig. 12e), with strong cyclonic circulation to the storm track variations on extreme precipitation fre- northwest and anticyclonic circulation to the southeast of quency in the Ohio Valley and the Pacific Northwest. the moisture transport corridor (Fig. S8a), giving rise to Here we compare the physical mechanisms generating

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FIG. 10. As in Fig. 8, but for the EOF3 mode. extreme precipitation within these two regions. By ex- arises between such a dipole structure. As the flux from amining the extreme precipitation days and moisture the Pacific meets the Cascade Range and the Rocky budgets in those two regions, we find that the extreme Mountains in the northwestern United States, the precipitation days in the Ohio Valley display typical moisture is forced upward to form heavy orographic zonally oriented midlatitude synoptic (Rossby) wave precipitation. train patterns at 500-hPa level and classic cyclone At the seasonal scale, to understand the moisture source structure on the ground. Moisture mainly comes from for seasons with frequent extreme precipitation events, we the Gulf of Mexico between the cyclonic circulation decompose the total moisture flux convergence into two over the central United States and the anticyclonic terms: moisture advection and moisture tendency due to circulation close to the Atlantic coast. The low pressure dynamical convergence. We find that the dynamical con- center and fronts on the ground lead to convergence of vergence dominates the moisture budget in the Ohio air and upward motion to the northeast of the cyclone Valley, whereas in the northwestern United States both center. Our results also show that the existence of a are important but mostly cancel each other out, with the southwestward extended ridge close to the Atlantic advection being slightly stronger. Evaporation is found to coast is a crucial ingredient leading to enhanced north- be enhanced over subtropical Atlantic east of Cuba and ward moisture transport from the Gulf. On the other along the coast of northwestern United States, along the hand, the extreme precipitation days in the northwest- path of the enhanced moisture transport into the extreme ern United States show a cyclonic and anticyclonic precipitation regions. Future work will be needed to circulation pair aligned northwest to southeast that is quantify the contribution from enhanced evaporation by different from the signature of a zonally oriented directly computing moisture source following backward synoptic-scale Rossby wave train. Strong northeast- Lagrangian trajectories from regions of enhanced moisture ward moisture flux resembling an atmospheric river convergence.

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FIG. 11. As in Fig. 8, but for the box over the northwestern United States.

We further decompose each term into the mean and precipitation days described above clearly demonstrate transient components. Within most of the domain, the the importance of cyclone (and anticyclone) activity mean terms dominate over the transient terms. The during these events. Nevertheless, what factors control exceptions are over the Gulf of Mexico and nearby whether mean or transient moisture transport domi- coastal states, where the transient advection term is nates over a region should be further investigated. comparable with the mean advection term and they Seasonal mean budgets and composites made from all mostly cancel each other. Over the Ohio Valley, we find extreme precipitation days highlight the average con- that it is the variations of the mean dynamical con- ditions for these events, but not all events are the same. vergence instead of the variations of precipitable water We examine the differences between these events by that contribute most to variations in mean moisture conducting EOF analyses on the column-integrated convergence. vapor flux data. All three leading EOFs in the Ohio Even though a cyclone is by itself a high-frequency Valley show variations of midlatitude synoptic waves, transient phenomenon, it is not necessary that its con- with different wave phases and amplitudes, giving rise to tribution to the moisture budget must stay within the different longitudinal location, orientation, and strength corresponding high-frequency range. Stronger and more of the moisture flux. Nevertheless, all EOFs display a frequent cyclones can increase the seasonal mean dy- Rossby wave train at 500 hPa with an amplified ridge namical convergence, hence enhancing the seasonal near the U.S. Atlantic coast, and strong moisture flux mean moisture convergence. Similarly, variations in flowing poleward across the Gulf Coast. One interesting cyclone activity also contribute to changes in the sea- observation is that over this region, stronger incoming sonal mean flow, affecting the mean moisture advec- moisture flux may not necessarily give rise to stronger tion. Our composites of the circulation during extreme moisture flux convergence, since the latter depends also

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FIG. 12. As in Fig. 11, but for the EOF2 mode. on the location of the synoptic weather system including detail, and found that even though in both regions these the cyclone center and the fronts. For the northwestern events are due to cyclone and anticyclone activity, the United States, the two leading EOFs also highlight shifts detailed dynamics giving rise to these events are quite in spatial location, orientation, and strength of moisture different. It would be of interest to examine similar transport. But in this region, stronger incoming moisture events in other regions that may exhibit potentially flux generally leads to stronger moisture flux conver- different dynamics, for example the U.S. east coast and gence, given the flux is met with the spatially fixed western Europe. In addition, given the importance of mountain ranges that force the incoming airstream to this topic, it will be of interest to see how well climate ascend and cool. models simulate the different relationships between While some of our results are largely consistent with cyclone activity and precipitation extremes in the dif- those of previous studies, this work extends previous ferent regions, and whether there will be a significant studies by directly contrasting the differences between change of these relationships between the current and the dynamics governing extreme precipitation events in future climates. two different regions. Our results also highlight the im- portance of the southwestward extended ridge near the Acknowledgments. The authors thank three anony- Atlantic coast for the Ohio Valley cases, and show that mous reviewers for comments that helped to improve not only are the cyclones important, but the accompa- the paper. We acknowledge the European Centre for nying anticyclones are also important in channeling a Medium-Range Weather Forecasts (ECMWF), NASA strong moisture flux toward both regions. Global Modeling and Assimilation Office (GMAO), In this study, we have examined conditions giving rise and the Climate Prediction Center (CPC) for making to winter extreme precipitation events in two regions in the ERA-Interim (https://www.ecmwf.int/en/forecasts/

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