Atmospheric rivers induced heavy precipitation and flooding in the western U.S. simulated by the WRF regional climate model

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1 GEOPHYSICAL RESEARCH LETTERS, VOL. 36, L03820, doi: /2008gl036445, 2009 Atmospheric rivers induced heavy precipitation and flooding in the western U.S. simulated by the WRF regional climate model L. Ruby Leung 1 and Yun Qian 1 Received 24 October 2008; revised 7 January 2009; accepted 9 January 2009; published 12 February [1] A 20-year regional climate simulated by the Weather Research and Forecasting model has been analyzed to study the influence of the atmospheric rivers and land surface conditions on heavy precipitation and flooding in the western U.S. The simulation realistically captured the mean and extreme precipitation, and the precipitation/temperature anomalies of all the atmospheric river events between Contrasting the 1986 President Day and 1997 New Year Day events, differences in atmospheric stability have an influence on the spatial distribution of precipitation. Although both cases yielded similar precipitation, the 1997 case produced more runoff. Antecedent soil moisture, rainfall versus snowfall, and existing snowpack all seem to play a role, leading to a higher runoff to precipitation ratio for the 1997 case. This study underscores the importance of the atmospheric rivers and land surface conditions for predicting heavy precipitation and floods in the current and future climate of the western U.S. Citation: Leung, L. R., and Y. Qian (2009), Atmospheric rivers induced heavy precipitation and flooding in the western U.S. simulated by the WRF regional climate model, Geophys. Res. Lett., 36, L03820, doi: /2008gl Introduction [2] The western U.S. receives precipitation predominantly during the cold season when storms approach from the Pacific Ocean. The snowpack that accumulates during winter storms provide about 70 90% of water supply for hydropower generation, irrigation, and other uses. However, not all winter storms result in water that can be captured and utilized. Heavy precipitation can lead to floods that are damaging, with little net water gain in reservoirs. [3] Several studies in recent years have clarified the role of atmospheric rivers (AR) in producing heavy precipitation and floods in the mountainous regions of the West. Atmospheric rivers are narrow bands of enhanced water vapor associated with the warm sector of extratropical cyclones over the Pacific and Atlantic oceans [Zhu and Newell, 1998; Ralph et al., 2004; Bao et al., 2006]. Although ARs can be found in both winter and summer, Neiman et al. [2008] found that only the winter ones originate directly from the tropics; they are associated with higher water vapor fluxes because of the much stronger atmospheric flows, and the resulting precipitation shows larger orographic enhancement during landfall on the U.S. West Coast. Ralph et al. [2006] studied 7 floods between the winters of 1997 and 2006 in the California Russian River and found that AR 1 Pacific Northwest National Laboratory, Richland, Washington, USA. Copyright 2009 by the American Geophysical Union /09/2008GL conditions were present in all cases, though not all ARs produce floods. [4] To investigate how global warming may affect heavy precipitation and flooding in the western U.S., it is important to understand how ARs and the associated heavy precipitation and floods may change in a warmer climate. If atmospheric circulation remains unchanged, the frequency of AR may not change, but the atmospheric water vapor transported by ARs will likely increase because the atmospheric water holding capacity increases by about 7% for each 1-K increase in temperature. Although this may lead to increased heavy precipitation, whether flooding will increase is more complicated, as land surface conditions should also play an important role. For example, previous studies have projected large reduction in mountain snowpack that may have implications to flooding, as rain-on-snow is an important mechanism for flood generation in the mountainous West [Leung et al., 2004]. [5] Motivated by the need to understand how global warming may affect AR and the associated heavy precipitation and flooding, the goals of this study are to evaluate how well heavy precipitation and floods associated with AR may be simulated by a regional climate model that better resolves the narrow, elongated AR, and the complex orography of the western U.S. compared to global climate models, and to examine the role of land surface conditions on flooding through comparison of two AR cases. 2. Model and Data [6] As part of the North American Regional Climate Change Assessment Program (NARCCAP) ( narccap.ucar.edu), the Weather Research and Forecasting (WRF) model [Skamarock et al., 2005] has been used to simulate the regional climate of North America. In this study, we analyzed the simulation driven by the NCEP/DOE global reanalysis [Kanamitsu et al., 2002] for We used the standard NARCCAP domain that covers North America and the adjacent oceans at 50 km grid resolution. Atmospheric circulation, including temperature, winds, relative humidity, and sea level pressure, from the global reanalysis was used to provide initial and lateral boundary conditions for the simulation. For the lower boundary, sea surface temperature and sea ice from the AMIP monthly data were used. The lateral and lower boundary conditions were updated every 6 hours. A simple nudging scheme was used to blend the lateral boundary conditions with the WRF simulation in a 10-grid point wide buffer zone, with nudging coefficients following a linear-exponential function. [7] The WRF simulation was performed using physics options including the Community Atmospheric Model (CAM3) radiative transfer scheme for shortwave and long- L of6

2 Figure 1. (left) Observed and (right) simulated (top) 95th percentile daily precipitation and (bottom) mean daily precipitation intensity for December January February (DJF) of in mm/day. wave [Collins et al., 2004], the Noah LSM [Chen and Dudhia, 2001] for land surface processes, the Kain-Fritsch cumulus and shallow convection scheme [Kain, 2004], the Yonsei University counter-gradient boundary layer turbulence transfer scheme [Hong and Pan, 1996], and the 5-class mixed phase cloud microphysics scheme [Hong et al., 2004]. The simulation was initialized on September 1, 1979, with atmospheric and land surface conditions from the global reanalysis. Vegetation cover and background surface albedo are updated each day based on temporal interpolation from a climatological monthly vegetation cover data and summer/winter vegetation-type dependent surface albedo parameters, respectively. [8] This paper focuses on analysis of surface temperature, precipitation, and land surface variables. We used the 1/8- degree gridded daily maximum and minimum temperature and precipitation data prepared by the Land Surface Modeling group at the University of Washington to evaluate our simulation. The gridded data were produced using surface meteorological station data, with topographic adjustment based on the PRISM monthly climatology [Maurer et al., 2002]. 3. Results [9] Atmospheric rivers have large impacts on heavy precipitation and flooding along the west coasts where the complex terrains effectively extract the low-level moisture from the ARs. Figure 1 compares the 95th percentile daily precipitation and the mean daily precipitation intensity based on observations and the WRF model simulation for December-February averaged over During the cold season, the western U.S. receives a large amount of precipitation along the coastal mountain ranges. The 95th percentile or extreme precipitation is generally 3 5 times higher than the mean precipitation intensity. The same is true for large areas over the southeastern U.S., except this region generally receives less precipitation compared to the western U.S. The WRF simulation realistically captured the amount and spatial distribution of both precipitation intensity and extremes, suggesting that the probability density function of precipitation rate is likely well simulated. [10] We compared the mean observed and simulated precipitation anomaly (not shown) associated with all the AR events between identified by Dettinger [2004] based on back trajectory analysis of the vertically integrated atmospheric moisture transport from a global reanalysis. Precipitation amounts for days associated with AR and one day that follows are summed up as the total amount of precipitation affected by AR. The AR precipitation anomaly is calculated by subtracting the mean monthly precipitation corresponding to the month of each AR event from the total amount of precipitation affected by AR. The AR surface temperature anomaly is calculated similarly and compared between the observations and simulation. On average, the AR produces large precipitation anomaly, particularly along the mountain ranges, and warmer temperature over most of the western U.S. 2of6

3 Figure 2. (left) Observed and (right) simulated (top) precipitation and (bottom) surface temperature anomalies for the 1986 President Day (PD) event. Precipitation and temperature anomalies are in mm/day and C respectively. [11] To examine the hydrologic impacts of AR, we selected two specific AR events, the 1986 President Day (PD) event and the 1997 New Year Day (ND) event, to contrast the precipitation and flooding conditions. Figures 2 and 3 show the precipitation and surface temperature anomalies associated with the two AR events. Dettinger [2004] noted that the 1986 PD and 1997 ND are associated with AR west coast crossings between N and 42 N, respectively. The precipitation and temperature anomalies simulated by WRF reflect the different locations of the west coast crossing, showing more precipitation and warmer temperature covering the entire west coast during the 1997 ND compared to the more localized influence associated with the 1986 PD over California. [12] Comparing the atmospheric conditions simulated by WRF at the location of the west coast crossing (not shown), the 1986 PD is associated with larger atmospheric moisture content than the 1997 ND (a maximum of 10 g/kg versus 8 g/kg near the surface). With similar lower level wind speed between m/s, the AR of the 1986 PD has a higher vertically integrated water vapor transport compared to the AR of the 1997 ND. However, the latter is associated with weaker atmospheric stability or stronger vertical motion. As a result, the total amounts of precipitation produced by the AR of the two events are similar (Figures 4a and 4b), except the 1997 ND precipitation is more widespread to the north, and the AR produces more precipitation in the Coastal Range of northern California than the 1986 PD. [13] Figures 4c and 4d compares the ratio of runoff to total precipitation (R/P ratio) simulated for the two cases. Although the precipitation amounts produced by the AR are comparable, the AR of the 1997 ND leads to more runoff than the 1986 PD. This is more clearly seen by comparing the R/P ratio, which is mostly above 80% in the west coast during the 1997 ND, as compared to below 50% during the 1986 PD. [14] Clearly the land surface plays an important role in producing the contrasting runoff or flood conditions. Comparing the antecedent soil moisture, Figures 4e and 4f shows that the total soil column is much wetter before the 1997 ND than the 1986 PD. Indeed, Dettinger [2004] identified another AR event on December 28 29, 1996, that precedes the 1997 ND event. In contrast, the AR that precedes the 1986 PD occurred about 15 days earlier, with little precip- 3of6

4 Figure 3. Same as Figure 2, but for the 1997 New Year Day (ND) event. itation in between, hence the large difference between the antecedent soil moisture and runoff. [15] In addition to antecedent soil moisture, we also compared the existing snowpack and the ratio of snowfall to total precipitation between the two cases (not shown). Based on hydrologic simulations, White et al. [2002] noted large increases in runoff with increasing altitude of the snow level in some watersheds in California. In our simulation, generally less than 20% of the precipitation falls as snow during the 1997 ND compared to 60% or higher during the 1986 PD because of the warmer temperature associated with the 1997 event (Figure 3). Hence, larger runoff can result from the higher snow level or larger fraction of rainfall that directly contributes to runoff in the 1997 ND case. Furthermore, consistent with the proximity of the two AR events that occurred 2 days before and on the 1997 New Year Day, the existing snowpack is larger in the Sierra Nevada and Cascades during the 1997 ND than the 1986 PD. This is supported by observed snow water equivalent data measured at snow telemetry (snotel) sites along the Cascades and Sierra Nevada, which show that snowpack is 10 30% higher preceding the 1997 event than the 1986 event. With higher rainfall and more existing snowpack, rain-on-snow could also play a role in generating the higher R/P ratio shown in Figures 4c and 4d. 4. Conclusion [16] A 20-year regional climate simulation by the WRF model has been analyzed and compared with observed precipitation and temperature. Focusing on the topographically diverse western U.S., the simulation realistically captured the amount and spatial distribution of mean precipitation intensity and extreme (95th percentile) precipitation. Both the mean precipitation and temperature anomalies associated with atmospheric rivers are also well simulated. [17] This study highlights the role of both atmospheric and land surface conditions in flooding associated with AR. Although ARs are often characterized by moist neutral static stability [Ralph et al., 2005], atmospheric stability plays a role in determining the spatial distribution of precipitation of the 1986 PD and 1997 ND events, as atmospheric stability can modify the orographic precipitation signature through changes in low level flow over terrain. Consistent with previous studies [e.g., Leung and Ghan, 1995, 1998; Neiman et al., 2002; Kim and Kang, 2007; Hughes et al., 4of6

5 Figure 4. (a and b) Simulated precipitation (mm/day), (c and d) runoff to precipitation (R/P) ratio, and (e and f) total column soil moisture (mm) simulated for the (left) 1997 ND and (right) 1986 PD events. 2009], this study suggests that the Froude number, defined by atmospheric stability and low level wind speed, can be a useful parameter for predicting or diagnosing orographic precipitation pattern. This may also be true for heavy precipitation such as those associated with AR, as even small deviations from moist neutral stability can lead to important differences in both precipitation amounts and spatial distributions. [18] For precipitation to generate floods, our results underscore the important role of antecedent soil moisture, as well as precipitation phase (or snow level), which depends on temperature, and possibly melting of existing snowpack due to rain-on-snow. For a climate simulation to 5of6

6 realistically characterize extreme precipitation and flood in the western U.S., the model must be able to simulate AR and its atmospheric structures, as well as the land surface conditions. The latter requires realistic simulation of both temporal and spatial variability of precipitation. In a follow on study using the NARCCAP downscaled climate change scenarios, we will examine how AR, the associated precipitation, and land surface conditions may be affected by climate change to alter extreme precipitation and flooding in the western U.S. [19] Acknowledgments. This study was supported by the Department of Energy Office of Science Climate Change Prediction Program (CCPP) as part of the multi-agency funded North American Regional Climate Change Assessment Program (NARCCAP), and by the National Oceanic and Atmospheric Administration Climate Prediction Program for the Americas (CPPA). The WRF simulation was performed using supercomputing resources from the National Center for Atmospheric Research. Pacific Northwest National Laboratory is operated for the U.S. Department of Energy by Battelle Memorial Institute under contract DE-AC06-76RLO References Bao, J.-W., S. A. Michelson, P. J. Neiman, F. M. Ralph, and J. M. Wilczak (2006), Interpretation of enhanced integrated water-vapor bands associated with extratropical cyclones: Their formation and connection to tropical moisture, Mon. Weather Rev., 134, Chen, F., and J. Dudhia (2001), Coupling an advanced land-surface/ hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model description and implementation, Mon. Weather Rev., 129, Collins, W. D., et al. (2004), Description of the NCAR Community Atmosphere Model (CAM 3.0), NCAR Tech. Note NCAR/TN- 464+STR, 214 pp., Natl. Cent. for Atmos. Res., Boulder, Colo. Dettinger, M. 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