scholarly journals Atmospheric River–Induced Precipitation and Snowpack during the Western United States Cold Season

2019 ◽  
Vol 20 (4) ◽  
pp. 613-630 ◽  
Author(s):  
Hisham Eldardiry ◽  
Asif Mahmood ◽  
Xiaodong Chen ◽  
Faisal Hossain ◽  
Bart Nijssen ◽  
...  

Abstract Atmospheric rivers (ARs) are narrow, elongated corridors of high water vapor content transported from tropical and/or extratropical cyclones. We characterize precipitation and snow water equivalent associated with ARs intersecting the western U.S. coast during the cold season (November– March) of water years 1949–2015. For each AR landfalling date, we retrieved the precipitation and relevant hydrometeorological variables from dynamically downscaled atmospheric reanalyses (NCEP–NCAR) using the WRF mesoscale numerical weather prediction model. Landfalling ARs resulted in higher precipitation amounts throughout the domain than did non-AR storms. ARs contributed the most extreme precipitation events during January and February. Daily snow water equivalent (SWE) changes during ARs indicate that high positive net snow accumulation conditions accompany ARs in December, January, and February. We also assess the historical impact of AR storm duration and precipitation frequency by considering the precipitation depth estimated during a 72-h window bounding the AR landfall date. More extreme precipitation amounts are produced by ARs in the South Cascades and Sierra Nevada ranges compared with ARs with landfall farther north. Most AR extreme precipitation events (and lower SWE accumulations) are produced during warm AR dates, especially toward the northern end of our domain. Analysis of ARs during dry and wet years reveals that ARs during wet years are more frequent and produce heavier precipitation and snow accumulation as compared with dry years. Such conditions are evident in drought events that are associated with a reduced frequency of ARs.

2019 ◽  
Vol 147 (4) ◽  
pp. 1415-1428 ◽  
Author(s):  
Imme Benedict ◽  
Karianne Ødemark ◽  
Thomas Nipen ◽  
Richard Moore

Abstract A climatology of extreme cold season precipitation events in Norway from 1979 to 2014 is presented, based on the 99th percentile of the 24-h accumulated precipitation. Three regions, termed north, west, and south are identified, each exhibiting a unique seasonal distribution. There is a proclivity for events to occur during the positive phase of the NAO. The result is statistically significant at the 95th percentile for the north and west regions. An overarching hypothesis of this work is that anomalous moisture flux, or so-called atmospheric rivers (ARs), are integral to extreme precipitation events during the Norwegian cold season. An objective analysis of the integrated vapor transport illustrates that more than 85% of the events are associated with ARs. An empirical orthogonal function and fuzzy cluster technique is used to identify the large-scale weather patterns conducive to the moisture flux and extreme precipitation. Five days before the event and for each of the three regions, two patterns are found. The first represents an intense, southward-shifted jet with a southwest–northeast orientation. The second identifies a weak, northward-shifted, zonal jet. As the event approaches, regional differences become more apparent. The distinctive flow pattern conducive to orographically enhanced precipitation emerges in the two clusters for each region. For the north and west regions, this entails primarily zonal flow impinging upon the south–north-orientated topography, the difference being the latitude of the strong flow. In contrast, the south region exhibits a significant southerly component to the flow.


2015 ◽  
Vol 16 (5) ◽  
pp. 2065-2085 ◽  
Author(s):  
Allan Frei ◽  
Kenneth E. Kunkel ◽  
Adao Matonse

Abstract Recent analyses of extreme hydrological events across the United States, including those summarized in the recent U.S. Third National Climate Assessment (May 2014), show that extremely large (extreme) precipitation and streamflow events are increasing over much of the country, with particularly steep trends over the northeastern United States. The authors demonstrate that the increase in extreme hydrological events over the northeastern United States is primarily a warm season phenomenon and is caused more by an increase in frequency than magnitude. The frequency of extreme warm season events peaked during the 2000s; a secondary peak occurred during the 1970s; and the calmest decade was the 1960s. Cold season trends during the last 30–50 yr are weaker. Since extreme precipitation events in this region tend to be larger during the warm season than during the cold season, trend analyses based on annual precipitation values are influenced more by warm season than by cold season trends. In contrast, the magnitude of extreme streamflow events at stations used for climatological analyses tends to be larger during the cold season: therefore, extreme event analyses based on annual streamflow values are overwhelmingly influenced by cold season, and therefore weaker, trends. These results help to explain an apparent discrepancy in the literature, whereby increasing trends in extreme precipitation events appear to be significant and ubiquitous across the region, while trends in streamflow appear less dramatic and less spatially coherent.


2020 ◽  
Vol 21 (9) ◽  
pp. 2003-2021 ◽  
Author(s):  
Trine J. Hegdahl ◽  
Kolbjørn Engeland ◽  
Malte Müller ◽  
Jana Sillmann

AbstractThe aim of this study is to investigate extreme precipitation events caused by atmospheric rivers and compare their flood impact in a warmer climate to current climate using an event-based storyline approach. The study was set up by selecting four high-precipitation events from 30 years of present and future climate simulations of the high-resolution global climate model EC-Earth. The two most extreme precipitation events within the selection area for the present and future climate were identified, and EC-Earth was rerun creating 10 perturbed realizations for each event. All realizations were further downscaled with the regional weather prediction model, AROME-MetCoOp. The events were thereafter used as input to the operational Norwegian flood-forecasting model for 37 selected catchments in western Norway, and the magnitude and the spatial pattern of floods were analyzed. The role of the hydrological initial conditions, which are important for the total flooding, were analyzed with a special emphasis on snow and soil moisture excess. The results show that the selected future extreme precipitation events affected more catchments with larger floods, compared to the events from present climate. In addition, multiple realizations of the meteorological forcing and four different hydrological initial conditions, for example, soil saturation and snow storage, were important for the estimation of the maximum flood level. The meteorological forcing (e.g., the internal variability/perturbed output) accounts for the highest contribution to the spread in flood magnitude; however, for some events and catchments the hydrological initial conditions affected the magnitudes of floods more than the meteorological forcing.


2016 ◽  
Vol 16 (1) ◽  
pp. 269-285 ◽  
Author(s):  
S. O. Krichak ◽  
S. B. Feldstein ◽  
P. Alpert ◽  
S. Gualdi ◽  
E. Scoccimarro ◽  
...  

Abstract. This paper presents a review of a large number of research studies performed during the last few decades that focused on the investigation of cold season extreme precipitation events (EPEs) in the Mediterranean region (MR). The publications demonstrate the important role of anomalously intense transports of moist air from the tropical and subtropical Atlantic in the occurrence of EPEs in the MR. EPEs in the MR are directly or indirectly connected to narrow bands with a high concentration of moisture in the lower troposphere, i.e., atmospheric rivers, along which a large amount of moisture is transported from the tropics to midlatitudes. Whereas in a significant fraction of the EPEs in the western MR moisture is transported to the MR from the tropical Atlantic, EPEs in the central, and especially the eastern, MR are more often associated with intense tropical moisture transports over North Africa and the Red Sea. The moist air for the EPEs in the latter part of the MR also mainly originates from the tropical Atlantic and Indian oceans, and in many cases it serves as a temporary moisture reservoir for future development. The paper is supplemented by the results of a test for a possible connection between declining Arctic sea ice and the climatology of intense precipitation in the eastern MR. Based on the results of the evaluation supporting those from the earlier climate change analyses and modeling studies, it is concluded that a further anthropogenic global warming may lead a greater risk of higher rainfall totals and therefore larger winter floods in western and central parts of the MR as a consequence of stronger and more numerous Atlantic atmospheric rivers, possibly accompanied by a decline in the number of EPEs in the eastern part of the MR.


2020 ◽  
Author(s):  
Carmelo Cammalleri ◽  
Paulo Barbosa ◽  
Jürgen Vogt

<p>Winter droughts, defined as periods of reduced precipitation and snow accumulation during the cold season, can have significant impacts on the subsequent summer season, especially over areas that strongly rely on stored water resources released during the spring melting.</p><p>The Snow Water Equivalent, SWE, represents a reliable means to quantify the amount of liquid water in the snowpack, and its anomalies can be used to evaluate deviations from the amount usually stored. Unfortunately, the use of SWE for operational monitoring of winter droughts is constrained by the limited availability of long time series of ground observations, and the lack of coordinated measuring networks at European continental scale.</p><p>Remote sensing data from microwave sensors, therefore, represent a valuable source of continuously-updated SWE data. Products such as the H-SAF (EUMETSAT Hydrology Satellite Application Facility, http://hsaf.meteoam.it/) SNOBS4-H13 are updated in almost near-real time, providing daily maps covering continental Europe and northern Africa. Limitations include data gaps, difficult retrievals over impervious terrain, coarse spatial resolution and a reduced length of the time series.</p><p>In this study, we tested the potential inclusion of a drought indicator based on the H-SAF SWE product in the European Drought Observatory (EDO, http://edo.jrc.ec.europa.eu), with the aim to fill the current gap faced over mountainous basins in terms of early warning of spring water deficits.</p><p>An analysis of the full dataset collected between 2013 and 2019 highlights how, currently, the main drawback of the product seems to be represented by the limited length of the time series, as well as by the difficulties to capture snow accumulation over some mountainous areas (e.g., Pyrenees) likely due to the coarse spatial resolution. Spatial aggregation at water basin scale was also tested, in order to evaluate the possibility to reduce the effects of some of these limitations.     </p>


2021 ◽  
Author(s):  
Nikolaos Mastrantonas ◽  
Linus Magnusson ◽  
Florian Pappenberger ◽  
Jörg Matschullat

<p>The Mediterranean region frequently experiences extreme precipitation events with devastating consequences for the affected societies, economies, and environment. Being able to provide reliable and skillful predictions of such events is crucial for mitigating their adverse impacts and related risks. One important part of the risk mitigation chain is the sub-seasonal predictability of such extremes, with information provided at such timescales supporting a range of actions, as for example warn decision-makers, and preposition materials and equipment.</p><p>This work focuses on the predictability of large-scale atmospheric flow patterns connected to extreme precipitation events in the Mediterranean. Previous research has identified strong connections between localized extremes and large-scale patterns. This is promising to provide useful information at sub-seasonal timescales. For such lead times, the Numerical Weather Prediction models are more skillful in predicting large-scale patterns than localized extremes. Here, we analyze the usefulness of these connections at sub-seasonal timescales by using the ECMWF extended-range forecasts. We aim at quantifying related benefits for the different areas in the Mediterranean region and providing insights that are of interest to the operational community.</p><p>Initial results suggest that the ECMWF forecasts provide skillful information in the predictability of large-scale patterns up to about 15 days lead time.</p><p> </p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.3687c29b370068376801161/sdaolpUECMynit/12UGE&app=m&a=0&c=49e65b5908090e0787f0f7f4f8930219&ct=x&pn=gnp.elif&d=1" alt=""></p><p>Large-scale patterns over the Mediterranean based on anomalies of sea level pressure (color shades) and geopotential at 500 hPa (contours) (Figure adapted from Mastrantonas et al, 2020)</p>


2017 ◽  
Vol 18 (4) ◽  
pp. 1101-1119 ◽  
Author(s):  
Melissa L. Wrzesien ◽  
Michael T. Durand ◽  
Tamlin M. Pavelsky ◽  
Ian M. Howat ◽  
Steven A. Margulis ◽  
...  

Abstract Despite the importance of snow in global water and energy budgets, estimates of global mountain snow water equivalent (SWE) are not well constrained. Two approaches for estimating total range-wide SWE over Sierra Nevada, California, are assessed: 1) global/hemispherical models and remote sensing and models available for continental United States (CONUS) plus southern Canada (CONUS+) available to the scientific community and 2) regional climate model simulations via the Weather Research and Forecasting (WRF) Model run at 3, 9, and 27 km. As no truth dataset provides total mountain range SWE, these two approaches are compared to a “reference” SWE consisting of three published, independent datasets that utilize/validate against in situ SWE measurements. Model outputs are compared with the reference datasets for three water years: 2005 (high snow accumulation), 2009 (average), and 2014 (low). There is a distinctive difference between the reference/WRF datasets and the global/CONUS+ daily estimates of SWE, with the former suggesting up to an order of magnitude more snow. Results are qualitatively similar for peak SWE and 1 April SWE for all three years. Analysis of SWE time series indicates that lower SWE for global and CONUS+ datasets is likely due to precipitation, rain/snow partitioning, and ablation parameterization differences. It is found that WRF produces reasonable (within 50%) estimates of total mountain range SWE in the Sierra Nevada, while the global and CONUS+ datasets underestimate SWE.


2013 ◽  
Vol 26 (12) ◽  
pp. 4231-4243 ◽  
Author(s):  
Michael J. DeFlorio ◽  
David W. Pierce ◽  
Daniel R. Cayan ◽  
Arthur J. Miller

Abstract Water resources and management over the western United States are heavily impacted by both local climate variability and the teleconnected responses of precipitation to the El Niño–Southern Oscillation (ENSO) and Pacific decadal oscillation (PDO). In this work, regional precipitation patterns over the western United States and linkages to ENSO and the PDO are analyzed using output from a Community Climate System Model version 4 (CCSM4) preindustrial control run and observations, with emphasis on extreme precipitation events. CCSM4 produces realistic zonal gradients in precipitation intensity and duration over the western United States, with higher values on the windward side of the Cascade Mountains and Sierra Nevada and lower values on the leeward. Compared to its predecessor CCSM3, CCSM4 shows an improved teleconnected signal of both ENSO and the PDO to large-scale circulation patterns over the Pacific–North America region and also to the spatial pattern and other aspects of western U.S. precipitation. The so-called drizzle problem persists in CCSM4 but is significantly improved compared to CCSM3. In particular, it is found that CCSM4 has substantially less precipitation duration bias than is present in CCSM3. Both the overall and extreme intensity of wintertime precipitation over the western United States show statistically significant linkages with ENSO and PDO in CCSM4. This analysis provides a basis for future studies using greenhouse gas (GHG)-forced CCSM4 runs.


Author(s):  
Haleakala K. ◽  
Gebremichael M. ◽  
Dozier J. ◽  
Lettenmaier D.P.

AbstractSeasonal snow water equivalent (SWE) accumulation in California’s Sierra Nevada is primarily governed by a few orographically enhanced snowstorms. However, as air temperatures gradually rise, resulting in a shift from snow to rain, the governing processes determining SWE accumulation versus ablation become ambiguous. Using a network of 28 snow pillow measurements to represent an elevational and latitudinal gradient across the Sierra Nevada, we identify distributions of critical temperatures and corresponding storm and snowpack properties that describe how SWE accumulation varies across the range at an hourly timescale for water years 2010 through 2019. We also describe antecedent and prevailing conditions governing whether SWE accumulates or ablates during warm storms. Results show that atmospheric moisture regulates a temperature dependence of SWE accumulation. Conditions balancing precipitable water and snow formation requirements produce the most seasonal SWE, which was observed in the (low-elevation) northern and (middle-elevation) central Sierra Nevada. The high southern Sierra Nevada conservatively accumulates SWE with colder, drier air, resulting in less midwinter ablation. These differences explain a tendency for deep, low-density snowpacks to accumulate rather than ablate SWE during warm storms (having median temperatures exceeding 1.0°C), reflecting counteracting liquid storage and internal energy deficits. The storm events themselves in these cases are brief with modest moisture supplies or are otherwise followed immediately by ablation.


2020 ◽  
Vol 163 ◽  
pp. 01011
Author(s):  
Andrey Shikhov ◽  
Evgenii Churiulin

More recently, snow accumulation and snowmelt models for their calculations are forced to apply data from numerical weather prediction (NWP) models. This approach allows improvement the accuracy of calculating snow water equivalent (SWE) values especially in remote and mountain regions. In this study, we compared the numerical results of SWE calculations performed by two independent models. The first one is the SnoWE model and the second one is the ICON NWP model. During the period from November 2018 to May 2019, the simulation results of SWE compared with in-situ data from 64 snow surveys, which are located in the Kama river basin. We found that both models (SnoWE and ICON) allow getting satisfactory estimates of the maximum values of SWE (the accuracy of data is sufficient for their practical using). The root mean square error was equal 14-18% from the average measured SWE. Moreover, we got reliable maximum values of SWE for forested areas. At the same time, both models underestimate SWE values during spring snowmelt season. Probably, this underestimation is due to the shortcomings of the models and a sparse snow course-measuring network.


Sign in / Sign up

Export Citation Format

Share Document