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Jun 13, 2016 - 1 Jackson School of Geosciences, University of Texas at Austin, ... 2 Center for Global Change Science, Massachusetts Institute of Technology, ...
Role of ocean evaporation in California droughts and floods

Jiangfeng Wei1, Qinjian Jin1,2, Zong-Liang Yang1, Paul A. Dirmeyer3 1

2

Jackson School of Geosciences, University of Texas at Austin, Austin, Texas 78712, USA Center for Global Change Science, Massachusetts Institute of Technology, Cambridge,

Massachusetts 02139, USA 3

Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, Virginia 22030,

USA

Corresponding author: Jiangfeng Wei, CIESS, Jackson School of Geosciences, University of Texas at Austin, 2275 Speedway C9000, Austin, TX 78712. E-mail: [email protected].

First revision: May 21, 2016 Second revision: June 6, 2016 Third revision: June 13, 2016

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/grl.54627 © 2016 American Geophysical Union. All rights reserved.

Abstract Since winter 2011, a record-breaking drought has occurred in California. Studies found that the drought is mainly caused by a persistent high-pressure system off the U.S. West Coast, which is linked to Pacific sea surface temperature anomalies. The water cycles associated with the droughts and floods are still not clearly understood. Here we show that the atmospheric circulation off the West Coast not only controls the atmospheric convergence and formation of precipitation but also largely determines surface wind speed, which further affects the evaporation over the eastern North Pacific, the major evaporative moisture source for California precipitation. Because of this mechanism, the ocean evaporation over the eastern North Pacific has been reduced during the recent drought. However, the ocean evaporation anomalies have little direct influence on California precipitation, especially during dry years, mainly because of their weak amplitudes. The California droughts cannot be readily attributed to the reduced ocean evaporation. The association between increased Pacific evaporation and floods over California is somewhat stronger.

Key points: 

Atmospheric circulation off U.S. West Coast controls surface wind speed and ocean evaporation



Ocean evaporation has little direct influence on California precipitation because of its weak variability



Ocean evaporation has stronger influence on California precipitation in wet years than in dry years

© 2016 American Geophysical Union. All rights reserved.

1. Introduction During the winters of 2011–2014, California has experienced one of the most severe multiyear droughts in its history [Griffin and Anchukaitis, 2014; Swain et al., 2014; Robeson, 2015; Seager et al., 2015]. The drought has just been mitigated in winter 2015/16 by a strong El Niño, but most of California is still in a severe drought. The precipitation deficit during the drought has mainly been caused by a persistent high-pressure system off the U.S. West Coast that suppressed the moisture convergence and precipitation in California. Studies have found that the high-pressure system is linked to Pacific sea surface temperature anomalies [Wang et al., 2014; Hartmann, 2015; Seager et al., 2015]. Although this is a very rare event, the probability of this kind of high-pressure system is likely increasing with global warming [Swain et al., 2014; Wang et al., 2014; Diffenbaugh et al., 2015; Wang et al., 2015; Yoon et al., 2015]. The drought was exacerbated by the high evaporative demand over land associated with high temperature [Shukla et al., 2015], part of which has been attributed to global warming [Williams et al., 2015]. Climatologically, the California winter precipitation is mainly a result of the inland moisture transfer from the eastern North Pacific, and heavy precipitation occurs when the moisture flow encounters the Sierra Nevada mountain range. Much of the moisture transport is contributed by the so-called atmospheric rivers [Zhu and Newell, 1998; Ralph et al., 2006; Ralph and Dettinger, 2011; Dettinger, 2013], and they produce 30–50% of the total precipitation in the West Coast. Based on the water balance, the moisture transport to California should be lower (higher) during drought (flood). The amount of transported moisture is affected by atmospheric circulation and available moisture in the atmospheric. Previous studies have identified the important effect of atmospheric circulation on precipitation in California, but the respective roles of the water cycle components are still not clear. Specifically, we are interested in the roles of atmospheric circulation, evaporation in the moisture sources, and their interactions in California precipitation variability. We first identified the major moisture sources for California precipitation, which is the eastern North Pacific, and then investigate the role of ocean evaporation over these moisture sources in California droughts and floods. We performed data analysis, moisture tracking, and model simulations to investigate these issues.

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2. Data and Methods Precipitation data. Two precipitation dataset are used: the Climate Prediction Center (CPC) Unified Gauge-Based Analysis of precipitation [Xie et al., 2007; Chen et al., 2008] at 0.25° resolution and the Parameter elevation Regression on Independent Slopes Model (PRISM) precipitation [Daly et al., 2008] at about 4 km resolution. We used monthly data for 1979– 2015.

OAFlux data. The Objectively Analyzed Air-sea Fluxes (OAFlux) products [Yu and Weller, 2007] are constructed using the best possible estimates of flux-related surface meteorology from an optimal blending of satellite retrievals and atmospheric reanalyses and the state-ofthe-art bulk flux parameterizations. OAFlux project used an advanced objective analysis to combine the advantages of the existing data sources and produced synthesized datasets, especially ocean surface fluxes, with improved accuracy. Monthly products (1979-2015) of ocean

evaporation, surface (10 m) wind speed, and SST at 1° resolution are used for analysis.

Reanalysis data. 1979-2015 monthly ocean evaporation, 500 hPa geopotential height (GPH), and surface (10 m) wind speed from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim; 0.75° resolution) [Dee et al., 2011] and the Modern Era Retrospective-analysis for Research and Applications (MERRA; 2/3°×1/2° resolution) [Rienecker et al., 2011] are used.

Back-trajectory analysis. The Quasi-isentropic back-trajectory (QIBT) method [Dirmeyer and Brubaker, 1999; 2007] is used to track the water vapor for each precipitation event during 1985-2015 backward in time. The method has been used to study various water cycle problems [Dirmeyer and Kinter, 2010; Wei et al., 2012; Wei et al., 2013]. It is a post hoc Lagrangian method that traces the advection of moisture back in time from precipitation events. It uses upstream evaporation and precipitable water to determine the probabilistic distribution of surface evaporation supplying the precipitated water vapor. Traces start from the grid box that has precipitation and the time step when precipitation occurs, backward in space and time until all of its original precipitation is attributed to ET. The datasets used to drive the scheme include atmospheric temperature, humidity, winds, surface pressure, (all from MERRA), surface ET (ET over land is from MERRA-Land [Reichle et al., 2011], evaporation over ocean is from MERRA but corrected by OAFlux evaporation at daily

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timescale, evaporation over ice is from MERRA), and precipitation (from MERRA and corrected by CPC Unified product at daily timescale), all at 6-hourly timescale. 3. Results 3.1. Water cycle associated with California precipitation The precipitation in California has a distinct seasonal cycle with the winter months (November to April) accounting for about 84% of annual total, and the recent precipitation deficit mainly occurred during this period (Fig. S1). Therefore, we focus on the winter months in the following analysis. We first look at the general relationship between California precipitation and atmospheric circulation. Fig. 1 shows the regression of the winter GPH onto the California precipitation. Associated with high California precipitation is a consistent lowpressure center from upper to lower troposphere off the northwest coast of the U.S. Deep pressure centers like this one are mostly associated with wave patterns forced by sea surface temperature (SST) anomalies [Lau, 1997; Hartmann, 2015]. Precipitation anomalies are associated with the water cycle anomalies. Using a backtrajectory method that tracks the moisture supplying California winter precipitation (see Section 2), we found that most of the moisture comes from the ocean evaporation near the West Coast (Fig. 2a), and the land evapotranspiration (ET) only contributes a small portion (~5%). The ocean evaporation near the West Coast shows a significant positive correlation with the California precipitation, and the surface wind pattern associated with high precipitation shows a cyclonic flow, transporting moisture from the ocean to California (Fig. 2b). Also, the ocean evaporation near the West Coast has stronger correlation with the precipitation in California than that in any other regions of the Contiguous U.S. (Fig. 2c). The significant correlations with precipitation in the southeast U.S. are a result of teleconnection of large-scale wave patterns (Fig. 1). We selected a region (26°–47°N, 162°–114°W; green box in Fig. 2a,b) where evaporation supplies the most moisture for, and also shows the highest correlation with, California precipitation. The evaporation in this region, mostly over the ocean, contributed about 85% of the total moisture for California winter precipitation (Figs. 2a,d), and there is a high correlation between California precipitation and total moisture from this region (Fig. 2d). However, this hydrological connection does not guarantee a causal relationship, i.e., the anomalies in moisture contribution and precipitation may be both controlled by the atmospheric circulation [Wei et al., 2012]. A circulation pattern like that in Fig. 2b can transport a large amount of moisture from ocean evaporation to California and produce

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precipitation. Prein et al. [2016] found that the frequency of this weather pattern was decreasing in the past decades, which is the main reason for the drying of the U.S. Southwest. Note that although the atmospheric rivers for the U.S. West Coast usually have a tropical origin, they only provide 30-50% of total precipitation [Dettinger, 2013] and have various shapes and sizes, so the mean moisture source for California (Fig. 2a) does not extend deep into the tropics as the individual extreme cases do.

3.2. Relationships among water cycle components To investigate the relationship between California precipitation and its controlling factors, we plotted the time series of California precipitation (P) and ocean evaporation (E), surface wind speed (WS), and 500 hPa GPH near the West Coast (Fig. 3a), all from observation-based datasets. As summarized in Fig. 3b, the mutual correlations between the time series of the four variables are very high; their correlations are all significant at 99% conference level. P shows a higher correlation with GPH than with E, and may be affected by both. WS is a term in the calculation of E and is an important factor affecting variations of E [Yu, 2007]. As expected, WS shows a highly significant correlation with E. In the midlatitudes, SST over most regions does not have a strong correlation with ocean evaporation, but the relationship between WS and E is strong almost everywhere over the ocean (Fig. S2 and Wu et al. [2006]). On the other hand, the correlations between GPH and WS are also very significant (≈−0.87). This is because high surface pressure (or high GPH) is usually associated with a stable atmosphere, small pressure gradients and calm winds, and the opposite is true for low surface pressure. Through WS change, GPH change affects E, so it is reasonable that the correlation between GPH and E is a little weaker than that of WS and E. Thus, GPH can possibly affect P both directly by controlling the convergence of moisture and indirectly by changing WS and E and thus the available moisture in the atmosphere. The P deficits in past four winters (2011–2014) are associated with increased GPH and reduced WS and E (Figs. 3a,S3). To disentangle the respective effects of GPH and E on P, we calculated the partial correlation between P and E while excluding the effect of GPH ( partial correlation between P and GPH while excluding the effect of E ( shows that

is much smaller than

) and the ). Figure 3b

, the original correlation between P and E,

indicating that GPH plays a dominant role in the correlation between P and E. While compared with the original correlation between P and GPH (

,

is a little

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weaker but still very significant. This demonstrates the dominant role of circulation effect on P, and E may only have a secondary effect. We found that although wet events are usually associated with increased evaporation over the eastern North Pacific, past droughts are not always associated with reduced evaporation (Figs. S4a, S3). The strong correlation between P and E is mainly contributed by the wet years; after removing the wettest years their correlation becomes very low (Fig. S4). This could be because extreme wet events in California are usually supplied by additional moisture from enhanced evaporation, in addition to favorable circulation patterns, while California droughts are mainly caused by circulation anomalies and are less associated with reduced evaporation in moisture sources. The importance of intense remote evaporation for extreme precipitation has also been found in some other regions [Dirmeyer and Kinter, 2010; Winschall et al., 2014]. This issue is further investigated by a moisture flux analysis in the next section.

3.3. Vertical profiles of moisture flux components The zonal moisture transfer at a certain time and location is humidity

and zonal wind speed . If

and

, a product of specific

are each expressed as a sum of its mean value

and anomaly, then (1) The difference between zonal moisture transfer and its mean value is (2) The three terms on the right size of Eq. (2) are changes in moisture transfer contributed by zonal wind change (

), humidity change (

covariation of humidity and zonal wind (

), and a residual term that represents the ).

We choose the four wettest winters of California after 1979 (1981/82, 1982/83, 1994/95, and 1997/98) and recent four dry winters (2011/12–2014/15). Although only one of the four recent dry winters belongs to the four driest winters since 1979, they are all dry and have negative ocean evaporation anomalies in the eastern North Pacific (Figs. 3,S3). It is of interest to examine their water cycle. Figure 4 shows the mean changes of the specific humidity, zonal wind, and the three terms on the right-hand side of Eq. (2) in the four wet winters (1981/82,1982/83,1994/95, and 1997/98) and recent four dry winters (2011/12– 2014/15). It can be seen that the specific humidity in the wet winters and dry winters are similar (Fig. 4a,b), although the wet winters have stronger ocean evaporation. The dry

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winters even show a little higher humidity over the ocean but a little lower humidity over California, probably because of the influence of wind patterns on moisture transport. The zonal wind from Pacific to California is much stronger in wet years (Fig. 4c,d), which is the main reason for the differences in moisture transfer toward California (Fig. 4e,f). The difference in moisture content in the air plays little role (Fig. 4g,h). If evaporation changes in wet and dry year lead to similar amplitudes of (different signs), the moisture transfer anomaly

change

is larger in wet years because of the

stronger zonal wind . This should be the main reason for the greater influence of ocean evaporation changes on California precipitation in wet years than in dry years.

3.4. Model simulations We performed ensemble simulations with the Weather Research and Forecast (WRF) model [Skamarock et al., 2008] (version 3.5) to corroborate the findings from data analysis. The model resolution was 36 km with 30 vertical levels. The spatial domain of the simulations is shown in Fig. S5a. Two experiments are performed for each of the four wet winters (1981/82, 1982/83, 1994/95, and 1997/98) and recent four dry winters (2011/12– 2014/15). The first contains control simulations for each of the eight winters. The second are for the same years but at each time step the ocean evaporation in the model domain is replaced by a medium value from the eight winters of control simulations. The four wet years have consistently higher ocean evaporation than the four dry years. For simplicity, we used the average ocean evaporation in 1994/95 and 2011/12 (ranked 4th and 5th among the eight winters) from the control simulations to replace the ocean evaporation in the model at each time step. Thus, in the second experiment the ocean evaporations passed to the atmosphere are the same for the eight winters. The initial and boundary conditions (including SST) were from ERA-Interim reanalysis [Dee et al., 2011] 6-hourly data. Each experiment has 16 ensemble members that are different in their combination of physical parameterizations (see Supporting Information). The model satisfactorily reproduces the observed spatial patterns and variabilities of precipitation and circulation (Fig. S5). Fig. 5 shows the model results. Although the model slightly overestimates ocean evaporation, the control simulations simulated higher ocean evaporations in the four wet years than in the four dry years, consistent with observations (Fig. 5a). However, their differences are small compared to their amplitudes, indicating a weak interannual variability of ocean evaporation. When moderate ocean evaporation is prescribed, the simulated

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precipitation in the four wet years remains much higher than for the four dry years (Fig. 5b). For all years, the simulated California precipitation from the two experiments are not significantly different, indicating that the ocean evaporation change has a minimal effect. The average precipitation is slightly diminished in wet years when ocean evaporation is reduced, but precipitation also declines in dry years when ocean evaporation is increased. Note that the prescribed ocean evaporation does not have a uniform difference from those in the control, and ocean evaporation changes may secondarily change atmosphere circulations. These are the possible reasons why the dry years do not have higher precipitation when ocean evaporation is increased. Experiments show that if the ocean evaporation is further increased, the dry years respond with higher precipitation, but they are still far drier than the wet years (not shown). These results support the relationships suggested in Fig. S4 that the dry years are less sensitive to the evaporation changes than the wet years.

4. Conclusions We conclude that California precipitation is more strongly related to the atmospheric circulation off the U.S. West Coast than ocean evaporation or moisture content in the atmosphere. The circulation anomaly can lead to surface wind speed anomalies, which further affect ocean evaporation. Although the ocean evaporation in the eastern North Pacific provides most of the moisture for California precipitation, its variations have little influence on California precipitation, mainly because the evaporation anomalies are small compared to the mean. The extreme precipitation anomalies are mainly caused by the convergence and divergence of the moisture in the atmosphere, which is little disturbed by the changes in ocean evaporation. The California drought during the past four years is mainly a result of the persistence of the high-pressure system, and is little affected by the reduced ocean evaporation. For extreme floods in California, increased ocean evaporation is more of a factor. The roles of evaporation over other ocean regions (e.g., tropics) and land surface [Wei et al., 2016] may be different and need further investigation.

Acknowledgements We thank three anomalous reviewers for their constructive comments, which helped to improve the paper. This study was supported by a seed fund granted to the first author from the Jackson School of Geosciences at the University of Texas at Austin. The data used in this study are available upon request to the corresponding author.

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Figure 1. The regression of 1979/80–2014/5 interannual winter (November–April) GPH onto the California precipitation. (a),(c),(e) MERRA; (b),(d)(f) ERA-Interim; (a),(b) 200 hPa; (c),(d) 500 hPa; (e)(f) 850 hPa. The green box (30°–55°N, 160°–120°W) encloses the core region of GPH change. Missing values are shown as grey.

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Figure 2. Relationship between California precipitation and its moisture supply from evaporation during winter (November–April) 1985/86–2014/15. (a) Climatologically mean percentage moisture contribution for California winter precipitation from the source regions. Stippling highlights the major moisture sources that contribute 95% of moisture for California winter precipitation (b) Regression of winter ocean surface evaporation (shading; from OAFlux) and 50 m wind (arrows; from MERRA; 95% confident) onto the California precipitation. (c) Regression of the Contiguous U.S. precipitation (CPC unified) at each grid cell onto the ocean evaporation in the green box. Stippling in (b) and (c) highlights the regions that are 95% confident. (d) Time series of 1986–2015 water year annual (October of previous year to September of current year) and winter California precipitation and the winter contribution from ocean evaporation within the green box.

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Figure 3. Relationships between California precipitation (P), ocean evaporation (E), ocean surface wind speed (WS), and 500 hPa GPH. (a) Their anomalies time series during winter 1979/80–2014/15. All from different observation-based datasets. Ocean evaporation and surface wind speed are the averages over the ocean in the box in Fig. 2, and GPH is the average over its core anomaly area (box in Fig. 1). Note the scale for GPH is inverted. The gray bar highlights the recent four winters. (b) Temporal correlation coefficients between the time series. is the correlation between X and Y (blue bars), and is the partial correlation between X and Y while removing the effect of Z (red bars). The bars show the average correlations while the whiskers show the maximum and minimum correlations. The correlations are calculated for all possible combinations. For example, there are two precipitation datasets, three evaporation datasets, and two GPH datasets, so there are 12 possible combinations for . Note the correlations with GPH have reversed signs. 90% and 99% confidence levels are for single correlations (not the means); the confidence thresholds for mean correlations would be lower than for single correlations.

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Figure 4. Pressure-longitude plots (30°–40°N average) of average specific humidity ( ), zonal wind ( ), and moisture transfer components (see Eq. (2)) for (left) four wettest winters (1981/82,1982/83,1994/95, and 1997/98) and (right) recent four dry winters (2011/12– 2014/15). The region is at around the west coast of California, and California is at around 120°W. Data are from MERRA.

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Figure 5. WRF experiment results and observations. (a) Ocean evaporation (over the ocean in the box in Fig. 2) and (b) Winter California precipitation for the four wet and four dry years from observations and two WRF experiments. The bars show the average values while the whiskers show the maximum and minimum values from different observational datasets (for observations) or different ensemble members (for WRF simulations). Observations are from the same datasets as in Fig. 3

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