Geology topics

G.J. McCabe

Publications and source records attributed to G.J. McCabe.

At least 19 recordsLinked to original sources

USGS2018

Variability in winter mass balance of Northern Hemisphere glaciers and relations with atmospheric circulation

An analysis of variability in the winter mass balance (WMB) of 22 glaciers in the Northern Hemisphere indicates two primary modes of variability that explain 46% of the variability among all glaciers. The first mode of variability characterizes WMB variability in Northern and Central Europe and the second mode primarily represents WMB variability in northwestern North America, but also is related to variability in WMB of one glacier in Europe and one in Central Asia. These two modes of WMB variability are explained by variations in mesoscale atmospheric circulation which are driving forces of variations in surface temperature and precipitation. The first mode is highly correlated with the Arctic Oscillation Index, whereas the second mode is highly correlated with the Southern Oscillation Index. In addition, the second mode of WMB variability is highly correlated with variability in global winter temperatures. This result suggests some connection between global temperature trends and WMB for some glaciers.

Arctic, Antarctic, and Alpine Research↗

USGS2009

Reducing streamflow forecast uncertainty: Application and qualitative assessment of the upper klamath river Basin, Oregon

The accuracy of streamflow forecasts depends on the uncertainty associated with future weather and the accuracy of the hydrologic model that is used to produce the forecasts. We present a method for streamflow forecasting where hydrologic model parameters are selected based on the climate state. Parameter sets for a hydrologic model are conditioned on an atmospheric pressure index defined using mean November through February (NDJF) 700-hectoPascal geopotential heights over northwestern North America [Pressure Index from Geopotential heights (PIG)]. The hydrologic model is applied in the Sprague River basin (SRB), a snowmelt-dominated basin located in the Upper Klamath basin in Oregon. In the SRB, the majority of streamflow occurs during March through May (MAM). Water years (WYs) 1980-2004 were divided into three groups based on their respective PIG values (high, medium, and low PIG). Low (high) PIG years tend to have higher (lower) than average MAM streamflow. Four parameter sets were calibrated for the SRB, each using a different set of WYs. The initial set used WYs 1995-2004 and the remaining three used WYs defined as high-, medium-, and low-PIG years. Two sets of March, April, and May streamflow volume forecasts were made using Ensemble Streamflow Prediction (ESP). The first set of ESP simulations used the initial parameter set. Because the PIG is defined using NDJF pressure heights, forecasts starting in March can be made using the PIG parameter set that corresponds with the year being forecasted. The second set of ESP simulations used the parameter set associated with the given PIG year. Comparison of the ESP sets indicates that more accuracy and less variability in volume forecasts may be possible when the ESP is conditioned using the PIG. This is especially true during the high-PIG years (low-flow years). ?? 2009 American Water Resources Association.

Journal of the American Water Resources Associatio↗

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↗

USGS2008

Associations of multi-decadal sea-surface temperature variability with US drought

Recent research suggests a link between drought occurrence in the conterminous United States (US) and sea surface temperature (SST) variability in both the tropical Pacific and North Atlantic Oceans on decadal to multidecadal (D2M) time scales. Results show that the Atlantic Multidecadal Oscillation (AMO) is the most consistent indicator of D2M drought variability in the conterminous US during the 20th century, but during the 19th century the tropical Pacific is a more consistent indicator of D2 M drought. The interaction between El Nin??o-Southern Oscillation (ENSO) and the AMO explain a large part of the D2M drought variability in the conterminous US. More modeling studies are needed to reveal possible mechanisms linking low-frequency ENSO variability and the AMO with drought in the conterminous US. ?? 2007 Elsevier Ltd and INQUA.

Quaternary International↗

USGS2007

Warming may create substantial water supply shortages in the Colorado River basin

The high demand for water, the recent multiyear drought (1999-2007), and projections of global warming have raised questions about the long-term sustainability of water supply in the southwestern United States. In this study, the potential effects of specific levels of atmospheric warming on water-year streamflow in the Colorado River basin are evaluated using a water-balance model, and the results are analyzed within the context of a multi-century tree-ring reconstruction (1490-1998) of streamflow for the basin. The results indicate that if future warming occurs in the basin and is not accompanied by increased precipitation, then the basin is likely to experience periods of water supply shortages more severe than those inferred from the longterm historical tree-ring reconstruction. Furthermore, the modeling results suggest that future warming would increase the likelihood of failure to meet the water allocation requirements of the Colorado River Compact.

Geophysical Research Letters↗

USGS2007

Verification of the Rhea-orographic-precipitation model

ABSTRACT: Observed April 1 snowpack accumulations within and near the Gunnison River basin in southwestern Colorado are compared with simulations from the Rhea-orographic-precipitation model to determine if the model simulates reliable magnitudes and temporal and spatial variability in winter precipitation for the basin. Twenty simulations of the Rhea model were performed using‘optimal’parameter sets determined for 10-kilometer (km) grids (10-km by 10-km grid cells) through stochastic calibration. Comparisons of Rhea-model simulations of winter precipitation with April 1 snowpack accumulations at 32 snowcourse stations were performed for the years 1972–1990. For most stations and most years the Rhea model reliably simulates the temporal and spatial variability in April 1 snowpack accumulations. However, in general, the Rhea-model underestimates April 1 snowpack accumulations in the Gunnison River basin area, and the underestimation is greatest for locations that receive the largest amount of snow. A significant portion of the error in Rhea-model simulations is due to the calibration of the Rhea model using gauge-catch precipitation measurements which can be as much as 50 percent below actual snowfall accumulations. Additional error in the Rhea-model simulations is a result of the comparison of gridded precipitation values to observed values measured at points.

Journal of the American Water Resources Associatio↗

USGS2007

Rain-on-snow events in the western United States

Rain-on-snow events pose a significant flood hazard in the western United States. This study provides a description of the spatial and temporal variability of the frequency of rain-on-snow events for 4318 sites in the western United States during water years (October through September) 1949-2003. Rain-on-snow events are found to be most common during the months of October through May; however, at sites in the interior western United States, rain-on-snow events can occur in substantial numbers as late as June and as early as September. An examination of the temporal variability of October through May rain-on-snow events indicates a mixture of increasing and decreasing trends in rain-on-snow events across the western United States. Decreasing trends in rain-on-snow events are most pronounced at lower elevations and are associated with trends toward fewer snowfall days and fewer precipitation days with snow on the ground. Rain-on-snow events are more (less) frequent in the northwestern (southwestern) United States during La Nin??a (El Nin??o) conditions. Additionally, increases in temperature in the western United States appear to be contributing to decreases in the number of rain-on-snow events for many sites through effects on the number of days with snowfall and the number of days with snow on the ground. ?? 2007 American Meteorological Society.

Bulletin of the American Meteorological Society↗

USGS2007

Associations of decadal to multidecadal sea-surface temperature variability with Upper Colorado River flow

The relations of decadal to multidecadal (D2M) variability in global sea-surface temperatures (SSTs) with D2M variability in the flow of the Upper Colorado River Basin (UCRB) are examined for the years 1906-2003. Results indicate that D2M variability of SSTs in the North Atlantic, North Pacific, tropical Pacific, and Indian Oceans is associated with D2M variability of the UCRB. A principal components analysis (with varimax rotation) of detrended and 11-year smoothed global SSTs indicates that the two leading rotated principal components (RPCs) explain 56% of the variability in the transformed SST data. The first RPC (RPC1) strongly reflects variability associated with the Atlantic Multidecadal Oscillation and the second RPC (RPC2) represents variability of the Pacific Decadal Oscillation, the tropical Pacific Ocean, and Indian Ocean SSTs. Results indicate that SSTs in the North Atlantic Ocean (RPC1) explain as much of the D2M variability in global SSTs as does the combination of Indian and Pacific Ocean variability (RPC2). These results suggest that SSTs in all of the oceans have some relation with flow of the UCRB, but the North Atlantic may have the strongest and most consistent association on D2M time scales. Hydroclimatic persistence on these time scales introduces significant nonstationarity in mean annual streamflow, with critical implications for UCRB water resource management. ?? 2007 American Water Resources Association.

Journal of the American Water Resources Associatio↗

USGS2006

Multidecadal climate variability of global lands and oceans

Principal components analysis (PCA) and singular value decomposition (SVD) are used to identify the primary modes of decadal and multidecadal variability in annual global Palmer Drought Severity Index (PDSI) values and sea-surface temperature (SSTs). The PDSI and SST data for 1925-2003 were detrended and smoothed (with a 10-year moving average) to isolate the decadal and multidecadal variability. The first two principal components (PCs) of the PDSI PCA explained almost 38% of the decadal and multidecadal variance in the detrended and smoothed global annual PDSI data. The first two PCs of detrended and smoothed global annual SSTs explained nearly 56% of the decadal variability in global SSTs. The PDSI PCs and the SST PCs are directly correlated in a pairwise fashion. The first PDSI and SST PCs reflect variability of the detrended and smoothed annual Pacific Decadal Oscillation (PDO), as well as detrended and smoothed annual Indian Ocean SSTs. The second set of PCs is strongly associated with the Atlantic Multidecadal Oscillation (AMO). The SVD analysis of the cross-covariance of the PDSI and SST data confirmed the close link between the PDSI and SST modes of decadal and multidecadal variation and provided a verification of the PCA results. These findings indicate that the major modes of multidecadal variations in SSTs and land-surface climate conditions are highly interrelated through a small number of spatially complex but slowly varying teleconnections. Therefore, these relations may be adaptable to providing improved baseline conditions for seasonal climate forecasting. Published in 2006 by John Wiley & Sons, Ltd.

International Journal of Climatology↗

USGS2006

Assimilation of snow covered area information into hydrologic and land-surface models

This paper describes a data assimilation method that uses observations of snow covered area (SCA) to update hydrologic model states in a mountainous catchment in Colorado. The assimilation method uses SCA information as part of an ensemble Kalman filter to alter the sub-basin distribution of snow as well as the basin water balance. This method permits an optimal combination of model simulations and observations, as well as propagation of information across model states. Sensitivity experiments are conducted with a fairly simple snowpack/water-balance model to evaluate effects of the data assimilation scheme on simulations of streamflow. The assimilation of SCA information results in minor improvements in the accuracy of streamflow simulations near the end of the snowmelt season. The small effect from SCA assimilation is initially surprising. It can be explained both because a substantial portion of snowmelts before any bare ground is exposed, and because the transition from 100% to 0% snow coverage occurs fairly quickly. Both of these factors are basin-dependent. Satellite SCA information is expected to be most useful in basins where snow cover is ephemeral. The data assimilation strategy presented in this study improved the accuracy of the streamflow simulation, indicating that SCA is a useful source of independent information that can be used as part of an integrated data assimilation strategy. ?? 2005 Elsevier Ltd. All rights reserved.

Advances in Water Resources↗

USGS2004

Precipitation and the occurrence of lyme disease in the Northeastern United States

The occurrence of Lyme disease is a growing concern in the United States, and various studies have been performed to understand the factors related to Lyme disease occurrence. In the United States, Lyme disease has occurred most frequently in the northeastern United States. Positive correlations between the number of cases of Lyme disease reported in the northeastern United States during the 1992-2002 period indicate that late spring/early summer precipitation was a significant climate factor affecting the occurrence of Lyme disease. When late spring/early summer precipitation was greater than average, the occurrence of Lyme disease was above average, possibly due to increased tick activity and survival rate during wet conditions. Temperature did not seem to explain the variability in Lyme disease reports for the northeastern United States. ?? Mary Ann Liebert, Inc.

Vector-Borne and Zoonotic Diseases↗

USGS2003

The health of glaciers: Recent changes in glacier regime

Glacier wastage has been pervasive during the last century; small glaciers and those in marginal environments are disappearing, large mid-latitude glaciers are shrinking slightly, and arctic glaciers are warming. Net mass balances during the last 40 years are predominately negative and both winter and summer balances (accumulation and ablation) and mass turnover are increasing, especially after 1988. Two principal components of winter balance time-series explain about 50% of the variability in the data. Glacier winter balances in north and central Europe correlate with the Arctic Oscillation, and glaciers in western North America correlate with the Southern Oscillation and Northern Hemisphere air temperature. The degree of synchronization for distant glaciers relates to changes in time of atmospheric circulation patterns as well as differing dynamic responses.

Conference Paper↗

USGS2002

Primary modes and predictability of year-to-year snowpack variations in the Western United States from teleconnections with Pacific Ocean climate

Snowpack, as measured on 1 April, is the primary source of warm-season streamflow for most of the western United States and thus represents an important source of water supply. An understanding of climate factors that influence the variability of this water supply and thus its predictability is important for water resource management. In this study, principal component analysis is used to identify the primary modes of 1 April snowpack variability in the western United States. Two components account for 61% of the total snowpack variability in the western United States. Relations between these modes of variability and indices of Pacific Ocean climate [e.g., the Pacific decadal oscillation (PDO) and Nin??o-3 sea surface temperatures (SSTs)] are examined. The first mode of snowpack variability is closely associated with the PDO, whereas the second mode varies in concert with both the PDO and Nin??o-3 SSTs. Because these atmospheric-oceanic conditions change slowly from season to season, the observed teleconnections between the Pacific Ocean climate and 1 April snowpack may be useful to forecast 1 April snowpack using data that describe the Pacific Ocean climate in the previous summer and autumn seasons, especially for the northwestern United States.

Journal of Hydrometeorology↗

USGS2002

Trends and temperature sensitivity of moisture conditions in the conterminous United States

Observed (1895-1999) trends in climatic moisture conditions in the conterminous United States (US) characterized by (1) annual precipitation minus annual potential evapotranspiration (PMPE), (2) annual surplus (water that eventually becomes streamflow), and (3) annual deficit (the amount of water that must be supplied by irrigation to grow vegetation at an optimum rate) are examined. The sensitivity of moisture conditions across the conterminous US to increases in temperature also are examined. Results indicate that there have been statistically significant trends in PMPE, annual surplus, and annual deficit for some parts of the conterminous US. Most of the significant trends in PMPE have been increasing trends primarily in the eastern US. Annual surplus also has increased over the eastern US, whereas the magnitudes of annual deficit have decreased. For the conterminous US as a whole, there has been a statistically significant increase in PMPE and annual surplus; however, there is no significant trend in annual deficit. Results also indicate that PMPE and annual deficit in the warmest regions of the conterminous US are most sensitive to increase in temperature. The high sensitivity of PMPE and annual deficit in these regions to increases in temperature is related to the relation between temperature and the saturation vapor pressure of air. The increases in potential evapotranspiration for a given change in temperature are larger for high temperatures than for low temperatures. The regions with the highest sensitivity of annual surplus to increases in temperature are the humid regions of the country. In these regions, annual surplus is large and increased potential evapotranspiration, resulting from increased temperature, has a significant effect on reducing annual surplus. In the dry regions of the country, annual surplus is so low that increases in potential evapotranspiration only result in small decreases in annual surplus.

Climate Research↗

USGS2002

Effects of ENSO on weather-type frequencies and properties at New Orleans, Louisiana, USA

Examination of historical climate records indicates a significant relation between the El Nino/Southern Oscillation (ENSO) and seasonal temperature and precipitation in Louisiana. In this study, a 40 yr record of twice daily (06:00 and 15:00 h local time) weather types are used to study the effects of ENSO variability on the local climate at New Orleans, Louisiana. Tropical Pacific sea-surface temperatures (SSTs) for the NINO3.4 region are used to define ENSO events (i.e. El Nino and La Nina events), and daily precipitation and temperature data for New Orleans are used to define weather-type precipitation and temperature properties. Data for winters (December through February) 1962-2000 are analyzed. The 39 winters are divided into 3 categories; winters with NINO3.4 SST anomalies < -1degreesC (La Nina events), winters with NINO3.4 anomalies > 1degreesC (El Nino events), and neutral conditions (all other years). For each category, weather-type frequencies and properties (i.e. precipitation and temperature) are determined and analyzed. Results indicate that El Nino events primarily affect precipitation characteristics of weather types at New Orleans, whereas the effects of La Nina events are most apparent in weather-type frequencies. During El Nino events, precipitation for some of the weather types is greater than during neutral and La Nina conditions and is related to increased water vapor transport from the Tropics to the Gulf of Mexico. The changes in weather-type frequencies during La Nina events are indicative of a northward shift in storm tracks and/or a decrease in storm frequency in southern Louisiana.

Louisiana↗

USGS2001

Trends in Northern Hemisphere surface cyclone frequency and intensity

One of the hypothesized effects of global warming from increasing concentrations of greenhouse gases is a change in the frequency and/or intensity of extratropical cyclones. In this study, winter frequencies and intensities of extratropical cyclones in the Northern Hemisphere for the period 1959-97 are examined to determine if identifiable trends are occurring. Results indicate a statistically significant decrease in midlatitude cyclone frequency and a significant increase in high-latitude cyclone frequency. In addition, storm intensity has increased in both the high and midlatitudes. The changes in storm frequency correlate with changes in winter Northern Hemisphere temperature and support hypotheses that global warming may result in a northward shift of storm tracks in the Northern Hemisphere.

Journal of Climate↗

USGS2000

Differences in topographic characteristics computed from 100- and 1000-m resolution digital elevation model data

Topographic characteristics computed from 100- and 1000-m resolution digital elevation model (DEM) data are compared for 50 locations representing varied terrain in the conterminous USA. The topographic characteristics are three parameters used extensively in hydrological research and modelling - slope (S), specific catchment area (A(s)) and a wetness index computed as the logarithm of the specific catchment area divided by slope [ln(A(s)/S)]. Slope values computed from 1000-m DEMs are smaller than those computed from 100-m DEMs; specific catchment area and the wetness index are larger for the 1000-m DEMs compared with the 100-m DEMs. Most of the differences between the 100- and 1000-m resolution DEMs can be attributed to terrain-discretization effects in the computation of the topographic characteristics and are not the result of smoothing or loss of terrain detail in the coarse data. In general, the terrain-discretization effects are greatest on flat terrain with long length-scale features, and the smoothing effects are greatest on steep terrain with short length-scale features. For the most part, the differences in the average values of the topographic characteristics computed from 100- and 1000-m resolution DEMs are predictable; that is, biases in the mean values for the characteristics computed from a 1000-m DEM can be corrected with simple linear equations. Copyright (C) 2000 John Wiley and Sons, Ltd.Topographic characteristics computed from 100- and 1000-m resolution digital elevation model (DEM) data are compared for 50 locations representing varied terrain in the conterminous USA. The topographic characteristics are three parameters used extensively in hydrological research and modelling - slope (S), specific catchment area (As) and a wetness index computed as the logarithm of the specific catchment area divided by slope [In(As/S)]. Slope values computed from 1000-m DEMs are smaller than those computed from 100-m DEMs; specific catchment area and the wetness index are larger for the 1000-m DEMs compared with the 100-m DEMs. Most of the differences between the 100- and 1000-m resolution DEMs can be attributed to terrain-discretization effects in the computation of the topographic characteristics and are not the result of smoothing or loss of terrain detail in the coarse data. In general, the terrain-discretization effects are greatest on flat terrain with long length-scale features, and the smoothing effects are greatest on steep terrain with short length-scale features. For the most part, the differences in the average values of the topographic characteristics computed from 100- and 1000-m resolution DEMs are predictable; that is, biases in the mean values for the characteristics computed from a 1000-m DEM can be corrected with simple linear equations.

Hydrological Processes↗

USGS1999

General-circulation-model simulations of future snowpack in the western United States

April 1 snowpack accumulations measured at 311 snow courses in the western United States (U.S.) are grouped using a correlation-based cluster analysis. A conceptual snow accumulation and melt model and monthly temperature and precipitation for each cluster are used to estimate cluster-average April 1 snowpack. The conceptual snow model is subsequently used to estimate future snowpack by using changes in monthly temperature and precipitation simulated by the Canadian Centre for Climate Modeling and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HADLEY) general circulation models (GCMs). Results for the CCC model indicate that although winter precipitation is estimated to increase in the future, increases in temperatures will result in large decreases in April 1 snowpack for the entire western US. Results for the HADLEY model also indicate large decreases in April 1 snowpack for most of the western US, but the decreases are not as severe as those estimated using the CCC simulations. Although snowpack conditions are estimated to decrease for most areas of the western US, both GCMs estimate a general increase in winter precipitation toward the latter half of the next century. Thus, water quantity may be increased in the western US; however, the timing of runoff will be altered because precipitation will more frequently occur as rain rather than as snow.

Conference Paper↗