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At least 37 records · Page 2Linked to original sources
USGS2008

Meteorological characteristics and overland precipitation impacts of atmospheric rivers affecting the West coast of North America based on eight years of SSM/I satellite observations

The pre-cold-frontal low-level jet within oceanic extratropical cyclones represents the lower-tropospheric component of a deeper corridor of concentrated water vapor transport in the cyclone warm sector. These corridors are referred to as atmospheric rivers (ARs) because they are narrow relative to their length scale and are responsible for most of the poleward water vapor transport at midlatitudes. This paper investigates landfalling ARs along adjacent north- and south-coast regions of western North America. Special Sensor Microwave Imager (SSM/ I) satellite observations of long, narrow plumes of enhanced integrated water vapor (IWV) were used to detect ARs just offshore over the eastern Pacific from 1997 to 2005. The north coast experienced 301 AR days, while the south coast had only 115. Most ARs occurred during the warm season in the north and cool season in the south, despite the fact that the cool season is climatologically wettest for both regions. Composite SSM/I IWV analyses showed landfalling wintertime ARs extending northeastward from the tropical eastern Pacific, whereas the summertime composites were zonally oriented and, thus, did not originate from this region of the tropics. Companion SSM/I composites of daily rainfall showed significant orographic enhancement during the landfall of winter (but not summer) ARs. The NCEP-NCAR global reanalysis dataset and regional precipitation networks were used to assess composite synoptic characteristics and overland impacts of landfalling ARs. The ARs possess strong vertically integrated horizontal water vapor fluxes that, on average, impinge on the West Coast in the pre-cold-frontal environment in winter and post-cold-frontal environment in summer. Even though the IWV in the ARs is greater in summer, the vapor flux is stronger in winter due to much stronger flows associated with more intense storms. The landfall of ARs in winter and north-coast summer coincides with anomalous warmth, a trough offshore, and ridging over the Intermountain West, whereas the south-coast summer ARs coincide with relatively cold conditions and a near-coast trough. ARs have a much more profound impact on near-coast precipitation in winter than summer, because the terrain-normal vapor flux is stronger and the air more nearly saturated in winter. During winter, ARs produce roughly twice as much precipitation as all storms. In addition, wintertime ARs with the largest SSM/I IWV are tied to more intense storms with stronger flows and vapor fluxes, and more precipitation. ARs generally increase snow water equivalent (SWE) in autumn/winter and decrease SWE in spring. On average, wintertime SWE exhibits normal gains during north-coast AR storms and above-normal gains during the south-coast AR storms. The north-coast sites are mostly lower in altitude, where warmer-than-normal conditions more frequently yield rain. During those events when heavy rain from a warm AR storm falls on a preexisting snowpack, flooding is more likely to occur. ?? 2008 American Meteorological Society.

Journal of Hydrometeorology↗
USGS2008

Characterization of errors in a coupled snow hydrology-microwave emission model

Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (TB) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while TB model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (GBMR), air-craft [Polarimetric Scanning Radiometer (PSR)], and satellite [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E)] TB measurements. Limitations of the model at the point scale were not as evident when comparing areal estimates. The coupled model was able to reproduce the TB spatial patterns observed by PSR in two of three sites. However, this was mostly due to the presence of relatively dense forest cover. An interesting result occurs when examining the spatial scaling behavior of the higher-resolution errors; the satellite-scale error is well approximated by the mode of the (spatial) histogram of errors at the smaller scale. In addition, TB prediction errors were almost invariant when aggregated to the satellite scale, while forest-cover fractions greater than 30% had a significant effect on TB predictions. ?? 2008 American Meteorological Society.

Journal of Hydrometeorology↗
USGS2008

Joint variability of global runoff and global sea surface temperatures

Global land surface runoff and sea surface temperatures (SST) are analyzed to identify the primary modes of variability of these hydroclimatic data for the period 1905-2002. A monthly water-balance model first is used with global monthly temperature and precipitation data to compute time series of annual gridded runoff for the analysis period. The annual runoff time series data are combined with gridded annual sea surface temperature data, and the combined dataset is subjected to a principal components analysis (PCA) to identify the primary modes of variability. The first three components from the PCA explain 29% of the total variability in the combined runoff/SST dataset. The first component explains 15% of the total variance and primarily represents long-term trends in the data. The long-term trends in SSTs are evident as warming in all of the oceans. The associated long-term trends in runoff suggest increasing flows for parts of North America, South America, Eurasia, and Australia; decreasing runoff is most notable in western Africa. The second principal component explains 9% of the total variance and reflects variability of the El Ni??o-Southern Oscillation (ENSO) and its associated influence on global annual runoff patterns. The third component explains 5% of the total variance and indicates a response of global annual runoff to variability in North Aflantic SSTs. The association between runoff and North Atlantic SSTs may explain an apparent steplike change in runoff that occurred around 1970 for a number of continental regions.

Journal of Hydrometeorology↗
USGS2009

Recent declines in western U.S. snowpack in the context of twentieth-century climate variability

A monthly snow accumulation and melt model was used with monthly Precipitation-elevation Regressions on Independent Slopes Model (PRISM) temperature and precipitation data to generate time series of 1 April snow water equivalent (SWE) for 1900 through 2008 in the western United States. Averaged across the western United States, SWE generally was higher than long-term (1900–2008) average conditions during the periods 1900–25, 1944–55, and 1966–82; SWE was lower than long-term average conditions during the periods 1926–43, 1957–65, and 1984–2008. During the period 1900–2008, the temporal pattern in winter precipitation exhibited wetter-than-average and drier-than-average decadal-scale periods with no long-term increasing or decreasing trend. Winter temperature generally was below average from 1900 to the mid-1950s, close to average from the mid-1950s to the mid-1980s, and above average from the mid-1980s to 2008. In general, periods of higher-than-average SWE have been associated with higher precipitation and lower temperature. Since about 1980, western U.S. winter temperatures have been consistently higher than long-term average values, and the resultant lower-than-average SWE values have been only partially offset by periods of higher-than-average precipitation. The post-1980 lower-than-average SWE conditions in the western United States are unprecedented within the context of twentieth-century climate and estimated SWE.

Arizona, California, Idaho, Montana, New Mexico, N↗
USGS2004

Winter orographic precipitation ratios in the Sierra Nevada: Large-scale atmospheric circulations and hydrologic consequences

The extent to which winter precipitation is orographically enhanced within the Sierra Nevada of California varies from storm to storm, and season to season, from occasions when precipitation rates at low and high altitudes are almost the same to instances when precipitation rates at middle elevations (considered here) can be as much as 30 times more than at the base of the range. Analyses of large-scale conditions associated with orographic precipitation variations during storms and seasons from 1954 to 1999 show that strongly orographic storms most commonly have winds that transport water vapor across the range from a more nearly westerly direction than during less orographic storms and than during the largest overall storms, and generally the strongly orographic storms are less convectively stable. Strongly orographic conditions often follow heavy precipitation events because both of these wind conditions are present in midlatitude cyclones that form the cores of many Sierra Nevada storms. Storms during La Niña winters tend to yield larger orographic ratios (ORs) than do those during El Niños. A simple experiment with a model of streamflows from a river basin draining the central Sierra Nevada indicates that, for a fixed overall basin-precipitation amount, a decrease in OR contributes to larger winter flood peaks and smaller springtime flows, and thus to an overall hastening of the runoff season.

Sierra Nevada↗
USGS2005

Sources of variability of evapotranspiration in California

The variability (1990–2002) of potential evapotranspiration estimates (ETo) and related meteorological variables from a set of stations from the California Irrigation Management System (CIMIS) is studied. Data from the National Climatic Data Center (NCDC) and from the Department of Energy from 1950 to 2001 were used to validate the results. The objective is to determine the characteristics of climatological ETo and to identify factors controlling its variability (including associated atmospheric circulations). Daily ETo anomalies are strongly correlated with net radiation ( R n ) anomalies, relative humidity (RH), and cloud cover, and less with average daily temperature ( T avg ). The highest intraseasonal variability of ETo daily anomalies occurs during the spring, mainly caused by anomalies below the high ETo seasonal values during cloudy days. A characteristic circulation pattern is associated with anomalies of ETo and its driving meteorological inputs, R n , RH, and T avg , at daily to seasonal time scales. This circulation pattern is dominated by 700-hPa geopotential height ( Z 700 ) anomalies over a region off the west coast of North America, approximately between 32° and 44° latitude, referred to as the California Pressure Anomaly (CPA). High cloudiness and lower than normal ETo are associated with the low-height (pressure) phase of the CPA pattern. Higher than normal ETo anomalies are associated with clear skies maintained through anomalously high Z 700 anomalies offshore of the North American coast. Spring CPA, cloudiness, maximum temperature ( T max ), pan evaporation ( E pan ), and ETo conditions have not trended significantly or consistently during the second half of the twentieth century in California. Because it is not known how cloud cover and humidity will respond to climate change, the response of ETo in California to increased greenhouse-gas concentrations is essentially unknown; however, to retain the levels of ETo in the current climate, a decline of R n by about 6% would be required to compensate for a warming of +3°C.

Journal of Hydrometeorology↗
USGS2005

Analysis of ground-measured and passive-microwave-derived snow depth variations in midwinter across the Northern Great Plains

Accurate estimation of snow mass is important for the characterization of the hydrological cycle at different space and time scales. For effective water resources management, accurate estimation of snow storage is needed. Conventionally, snow depth is measured at a point, and in order to monitor snow depth in a temporally and spatially comprehensive manner, optimum interpolation of the points is undertaken. Yet the spatial representation of point measurements at a basin or on a larger distance scale is uncertain. Spaceborne scanning sensors, which cover a wide swath and can provide rapid repeat global coverage, are ideally suited to augment the global snow information. Satellite-borne passive microwave sensors have been used to derive snow depth (SD) with some success. The uncertainties in point SD and areal SD of natural snowpacks need to be understood if comparisons are to be made between a point SD measurement and satellite SD. In this paper three issues are addressed relating satellite derivation of SD and ground measurements of SD in the northern Great Plains of the United States from 1988 to 1997. First, it is shown that in comparing samples of ground-measured point SD data with satellite-derived 25 ?? 25 km2 pixels of SD from the Defense Meteorological Satellite Program Special Sensor Microwave Imager, there are significant differences in yearly SD values even though the accumulated datasets showed similarities. Second, from variogram analysis, the spatial variability of SD from each dataset was comparable. Third, for a sampling grid cell domain of 1?? ?? 1?? in the study terrain, 10 distributed snow depth measurements per cell are required to produce a sampling error of 5 cm or better. This study has important implications for validating SD derivations from satellite microwave observations. ?? 2005 American Meteorological Society.

Journal of Hydrometeorology↗
USGS2011

Value of a dual-polarized gap-filling radar in support of southern California post-fire debris-flow warnings

A portable truck-mounted C-band Doppler weather radar was deployed to observe rainfall over the Station Fire burn area near Los Angeles, California, during the winter of 2009/10 to assist with debris-flow warning decisions. The deployments were a component of a joint NOAA–U.S. Geological Survey (USGS) research effort to improve definition of the rainfall conditions that trigger debris flows from steep topography within recent wildfire burn areas. A procedure was implemented to blend various dual-polarized estimators of precipitation (for radar observations taken below the freezing level) using threshold values for differential reflectivity and specific differential phase shift that improves the accuracy of the rainfall estimates over a specific burn area sited with terrestrial tipping-bucket rain gauges. The portable radar outperformed local Weather Surveillance Radar-1988 Doppler (WSR-88D) National Weather Service network radars in detecting rainfall capable of initiating post-fire runoff-generated debris flows. The network radars underestimated hourly precipitation totals by about 50%. Consistent with intensity–duration threshold curves determined from past debris-flow events in burned areas in Southern California, the portable radar-derived rainfall rates exceeded the empirical thresholds over a wider range of storm durations with a higher spatial resolution than local National Weather Service operational radars. Moreover, the truck-mounted C-band radar dual-polarimetric-derived estimates of rainfall intensity provided a better guide to the expected severity of debris-flow events, based on criteria derived from previous events using rain gauge data, than traditional radar-derived rainfall approaches using reflectivity–rainfall relationships for either the portable or operational network WSR-88D radars. Part of the reason for the improvement was due to siting the radar closer to the burn zone than the WSR-88Ds, but use of the dual-polarimetric variables improved the rainfall estimation by ~12% over the use of traditional Z – R relationships.

Journal of Hydrometeorology↗
USGS2014

An enhanced model of land water and energy for global hydrologic and earth-system studies

LM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial stepwise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (≫300 yr) model spinup times.

Journal of Hydrometeorology↗
USGS2014

Trends in precipitation, runoff, and evapotranspiration for rivers draining to the Gulf of Maine in the United States

Climate warming is projected to result in increases in total annual precipitation in northeastern North America. The response of runoff to increases in precipitation is likely to be more complex because increasing evapotranspiration (ET) could counteract increasing precipitation. This study was conducted to examine these competing trends in the historical record for 22 rivers having >70 yr of runoff data. Annual (water year) average precipitation increased in all basins, with increases ranging from 0.9 to 3.12 mm yr −1 . Runoff increased in all basins with increases ranging from 0.67 to 2.58 mm yr −1 . The ET was calculated by using a water balance approach in which changes in terrestrial water storage were considered negligible. ET increased in 16 basins and decreased in 6 basins. Temporal trends in temperature, precipitation, runoff, and ET were also calculated for each basin over their respective periods of record for runoff and for the consistent period (1927–2011) for the area-weighted average of the nine largest non-nested basins. From 1927 through 2011, precipitation and runoff increased at average rates of 1.6 and 1.7 mm yr −1 , respectively, and ET increased slightly at a rate of 0.18 mm yr −1 . For the more recent period (1970–2011), there was a positive trend in ET of 1.9 mm yr −1 . The lack of a more consistent increase in ET, compared with the increases in precipitation and runoff, for the full periods of record, was unexpected, but may be explained by various factors including decreasing wind speed, increasing cloudiness, decreasing vapor pressure deficit, and patterns of forest growth.

Journal of Hydrometeorology↗
USGS2013

Atmospheric rivers as drought busters on the U.S. west coast

Atmospheric rivers (ARs) have, in recent years, been recognized as the cause of the large majority of major floods in rivers all along the U.S. West Coast and as the source of 30%–50% of all precipitation in the same region. The present study surveys the frequency with which ARs have played a critical role as a common cause of the end of droughts on the West Coast. This question was based on the observation that, in most cases, droughts end abruptly as a result of the arrival of an especially wet month or, more exactly, a few very large storms. This observation is documented using both Palmer Drought Severity Index and 6-month Standardized Precipitation Index measures of drought occurrence for climate divisions across the conterminous United States from 1895 to 2010. When the individual storm sequences that contributed most to the wet months that broke historical West Coast droughts from 1950 to 2010 were evaluated, 33%–74% of droughts were broken by the arrival of landfalling AR storms. In the Pacific Northwest, 60%–74% of all persistent drought endings have been brought about by the arrival of AR storms. In California, about 33%–40% of all persistent drought endings have been brought about by landfalling AR storms, with more localized low pressure systems responsible for many of the remaining drought breaks.

California;Oregon;Washington↗
USGS2014

Variability common to global sea surface temperatures and runoff in the conterminous United States

Singular value decomposition (SVD) is used to identify the variability common to global sea surface temperatures (SSTs) and water-balance-modeled water-year (WY) runoff in the conterminous United States (CONUS) for the 1900–2012 period. Two modes were identified from the SVD analysis; the two modes explain 25% of the variability in WY runoff and 33% of the variability in WY SSTs. The first SVD mode reflects the variability of the El Niño–Southern Oscillation (ENSO) in the SST data and the hydroclimatic effects of ENSO on WY runoff in the CONUS. The second SVD mode is related to variability of the Atlantic multidecadal oscillation (AMO). An interesting aspect of these results is that both ENSO and AMO appear to have nearly equivalent effects on runoff variability in the CONUS. However, the relatively small amount of variance explained by the SVD analysis indicates that there is little covariation between runoff and SSTs, suggesting that SSTs may not be a viable predictor of runoff variability for most of the conterminous United States.

Journal of Hydrometeorology↗
USGS2015

Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture

The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.

Journal of Hydrometeorology↗
USGS2015

Climatology of extreme daily precipitation in Colorado and its diverse spatial and seasonal variability

The climatology of Colorado’s historical extreme precipitation events shows a remarkable degree of seasonal and regional variability. Analysis of the largest historical daily precipitation totals at COOP stations across Colorado by season indicates that the largest recorded daily precipitation totals have ranged from less than 60 mm day −1 in some areas to more than 250 mm day −1 in others. East of the Continental Divide, winter events are rarely among the top 10 events at a given site, but spring events dominate in and near the foothills; summer events are most common across the lower-elevation eastern plains, while fall events are most typical for the lower elevations west of the Divide. The seasonal signal in Colorado’s central mountains is complex; high-elevation intense precipitation events have occurred in all months of the year, including summer, when precipitation is more likely to be liquid (as opposed to snow), which poses more of an instantaneous flood risk. Notably, the historic Colorado Front Range daily rainfall totals that contributed to the damaging floods in September 2013 occurred outside of that region’s typical season for most extreme precipitation (spring–summer). That event and many others highlight the fact that extreme precipitation in Colorado has occurred historically during all seasons and at all elevations, emphasizing a year-round statewide risk.

Journal of Hydrometeorology↗
USGS2015

Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

Journal of Hydrometeorology↗
USGS2015

Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products

There is a high demand for agrohydrologic models to use gridded near-surface air temperature data as the model input for estimating regional and global water budgets and cycles. The Global Land Data Assimilation System (GLDAS) developed by combining simulation models with observations provides a long-term gridded meteorological dataset at the global scale. However, the GLDAS air temperature products have not been comprehensively evaluated, although the accuracy of the products was assessed in limited areas. In this study, the daily 0.25° resolution GLDAS air temperature data are compared with two reference datasets: 1) 1-km-resolution gridded Daymet data (2002 and 2010) for the conterminous United States and 2) global meteorological observations (2000–11) archived from the Global Historical Climatology Network (GHCN). The comparison of the GLDAS datasets with the GHCN datasets, including 13 511 weather stations, indicates a fairly high accuracy of the GLDAS data for daily temperature. The quality of the GLDAS air temperature data, however, is not always consistent in different regions of the world; for example, some areas in Africa and South America show relatively low accuracy. Spatial and temporal analyses reveal a high agreement between GLDAS and Daymet daily air temperature datasets, although spatial details in high mountainous areas are not sufficiently estimated by the GLDAS data. The evaluation of the GLDAS data demonstrates that the air temperature estimates are generally accurate, but caution should be taken when the data are used in mountainous areas or places with sparse weather stations.

Journal of Hydrometeorology↗
USGS2015

Hydroclimatic conditions preceding the March 2014 Oso landslide

The 22 March 2014 Oso landslide was one of the deadliest in U.S. history, resulting in 43 fatalities and the destruction of more than 40 structures. We examine synoptic conditions, precipitation records and soil moisture reconstructions in the days, months, and years preceding the landslide. Atmospheric reanalysis shows a period of enhanced moisture transport to the Pacific Northwest beginning on 11 February 2014. The 21- to 42-day periods prior to the landslide had anomalously high precipitation; we estimate that 300-400 mm of precipitation fell at Oso in the 21 days prior to the landslide. Relative only to historical periods ending on 22 March, the return periods of these precipitation accumulations are large (25-88 years). However, relative to the largest accumulations from any time of the year (annual maxima), return periods are more modest (2-6 years). In addition to the 21-42 days prior to the landslide, there is a secondary maximum in the precipitation return periods for the 4 years preceding the landslide. Reconstructed soil moisture was anomalously high prior to the landslide, with a return period that exceeded 40 years about a week before the event.

Washington↗
USGS2018

Hydroclimatology of the Missouri River basin

Despite the importance of the Missouri River for navigation, recreation, habitat, hydroelectric power, and agriculture, relatively little is known about the basic hydroclimatology of the Missouri River basin (MRB). This is of particular concern given the droughts and floods that have occurred over the past several decades and the potential future exacerbation of these extremes by climate change. Here, observed and modeled hydroclimatic data and estimated natural flow records in the MRB are used to 1) assess the major source regions of MRB flow, 2) describe the climatic controls on streamflow in the upper and lower basins , and 3) investigate trends over the instrumental period. Analyses indicate that 72% of MRB runoff is generated by the headwaters in the upper basin and by the lowest portion of the basin near the mouth. Spring precipitation and temperature and winter precipitation impacted by changes in zonal versus meridional flow from the Pacific Ocean play key roles in surface water supply variability in the upper basin. Lower basin flow is significantly correlated with precipitation in late spring and early summer, indicative of Atlantic-influenced circulation variability affecting the flow of moisture from the Gulf of Mexico. Although increases in precipitation in the lower basin are currently overriding the effects of warming temperatures on total MRB flow, the upper basin’s long-term trend toward decreasing flows, reduction in snow versus rain fraction, and warming spring temperatures suggest that the upper basin may less often provide important flow supplements to the lower basin in the future.

Missouri River basin↗