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- Author or Editor: John A. Dracup x
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Indices for objectively quantifying the severity of meteorological, agricultural, and hydrological forms of drought are discussed. Indices for each drought form are judged according to six weighted evaluation criteria: robustness, tractability, transparency, sophistication, extendability, and dimensionality. The indices considered most promising for succinctly summarizing drought severity are computed for two climate divisions in Oregon for 24 water years, 1976–99. The assessment determined that the most valuable indices for characterizing meteorological, hydrological, and agricultural droughts are rainfall deciles, total water deficit, and computed soil moisture, respectively.
Indices for objectively quantifying the severity of meteorological, agricultural, and hydrological forms of drought are discussed. Indices for each drought form are judged according to six weighted evaluation criteria: robustness, tractability, transparency, sophistication, extendability, and dimensionality. The indices considered most promising for succinctly summarizing drought severity are computed for two climate divisions in Oregon for 24 water years, 1976–99. The assessment determined that the most valuable indices for characterizing meteorological, hydrological, and agricultural droughts are rainfall deciles, total water deficit, and computed soil moisture, respectively.
Abstract
Streamflows in the Pacific Southwest of the United States in relation to the tropical Type 1 El Niño-Southern Oscillation (T1ENSO) and La Niña events are examined using composite and harmonic analyses for each event during a 24-month evolution period. The hydroclimatic signals associated with either extreme phase of the Southern Oscillation (SO) are explored based on data from 50 streamflow stations in California, Arizona, New Mexico, Colorado, and Utah. A significant level for the results is assessed by the use of a hypergeometric distribution. Highly significant, coherent signals are demonstrated to exist for both events, with opposite sign and almost identical timing. Pacific Southwest streamflow responses to the T1ENSO thermal forcing are characterized by a wet December-July season in the subsequent year of the event. Similarly, a dry February-July season is detected as a period at which the La Niña-streamflow relationship is strong and spatially coherent. An index time series is plotted to determine the temporal consistency of the signal. It was found that the respective seasonal signal for each event was confirmed by all episodes. Amplification (suppression) of the regional annual streamflow cycle is noticed during the subsequent year of the typical T1ENSO (La Niña) event.
A lag cross-correlation analysis is conducted between the time series of the seasonal December-July streamflow index and the SO index. The March-May season in the previous year of the seasonal T1ENSO signal was determined to be the logical period in which the SO index can be averaged to obtain the highest correlation and the maximum time lag. A Mann-Whitney U test reveals statistically significant differences in the means of seasonal streamflows associated with T1ENSO and La Niña events. Plausible explanations for the observed teleconnections are presented.
Abstract
Streamflows in the Pacific Southwest of the United States in relation to the tropical Type 1 El Niño-Southern Oscillation (T1ENSO) and La Niña events are examined using composite and harmonic analyses for each event during a 24-month evolution period. The hydroclimatic signals associated with either extreme phase of the Southern Oscillation (SO) are explored based on data from 50 streamflow stations in California, Arizona, New Mexico, Colorado, and Utah. A significant level for the results is assessed by the use of a hypergeometric distribution. Highly significant, coherent signals are demonstrated to exist for both events, with opposite sign and almost identical timing. Pacific Southwest streamflow responses to the T1ENSO thermal forcing are characterized by a wet December-July season in the subsequent year of the event. Similarly, a dry February-July season is detected as a period at which the La Niña-streamflow relationship is strong and spatially coherent. An index time series is plotted to determine the temporal consistency of the signal. It was found that the respective seasonal signal for each event was confirmed by all episodes. Amplification (suppression) of the regional annual streamflow cycle is noticed during the subsequent year of the typical T1ENSO (La Niña) event.
A lag cross-correlation analysis is conducted between the time series of the seasonal December-July streamflow index and the SO index. The March-May season in the previous year of the seasonal T1ENSO signal was determined to be the logical period in which the SO index can be averaged to obtain the highest correlation and the maximum time lag. A Mann-Whitney U test reveals statistically significant differences in the means of seasonal streamflows associated with T1ENSO and La Niña events. Plausible explanations for the observed teleconnections are presented.
Abstract
Artificial neural networks (ANNs), which are modeled on the operating behavior of the brain, are tolerant of some imprecision and are especially useful for classification and function approximation/mapping problems, to which hard and fast rules cannot be applied easily. Using ANNs, this study maps a 1-yr monthly (January–December) time series of the 700-hPa teleconnection indices and ENSO indicators onto the water year (October–September) total precipitation of California’s seven climatic zones, with different lag times between the inputs and outputs. It was found that the pattern of rainfall predicted by the ANN model matched closely the observed rainfall with a 1-yr time lag for most California climate zones and for most years. This research shows the possibility of making long-range predictions using ANNs and large-scale climatological parameters. This research also extends the use of neural networks to determine important parameters in long-range precipitation prediction by comparing results gained using all the inputs with results from leaving an individual index out of the network training. This comparison gives insight into the physical meteorological factors that influence California’s rainfall.
Abstract
Artificial neural networks (ANNs), which are modeled on the operating behavior of the brain, are tolerant of some imprecision and are especially useful for classification and function approximation/mapping problems, to which hard and fast rules cannot be applied easily. Using ANNs, this study maps a 1-yr monthly (January–December) time series of the 700-hPa teleconnection indices and ENSO indicators onto the water year (October–September) total precipitation of California’s seven climatic zones, with different lag times between the inputs and outputs. It was found that the pattern of rainfall predicted by the ANN model matched closely the observed rainfall with a 1-yr time lag for most California climate zones and for most years. This research shows the possibility of making long-range predictions using ANNs and large-scale climatological parameters. This research also extends the use of neural networks to determine important parameters in long-range precipitation prediction by comparing results gained using all the inputs with results from leaving an individual index out of the network training. This comparison gives insight into the physical meteorological factors that influence California’s rainfall.
Abstract
Linkages between tropical Pacific Ocean monthly climatic variables and the Upper Colorado River basin (UCRB) hydroclimatic variations from 1909 to 1998 are analyzed at interseasonal timescales. A study of the changes in these linkages through the years and their relationship to the Pacific Decadal Oscillation (PDO) is also investigated. Tropical Pacific climate variations were represented by atmospheric/oceanic ENSO indicators. For the UCRB, warm season (April–September) streamflow totals at Lee's Ferry, Arizona, and precipitation averages at different periods (cold season: October–March; warm season: April–September; and annual: October–September) were used to study the UCRB's response to tropical Pacific climatic forcing. A basinwide ENSO signature was found in the significant correlations between warm season precipitation in the UCRB and warm season SST averages from the Niño-3 region in most of the stations around the UCRB. This link is more evident during the warm phase of ENSO (El Niño), which is associated with an increase in warm season precipitation. The analysis also showed a link between June to November ENSO conditions and cold season precipitation variations contained in a principal component representing the high-elevation precipitation stations, which are the main source of streamflow. However, the amplitude and coherence of the cold season ENSO signal is significantly smaller compared to the general precipitation variations found in stations around the UCRB. Only when very few stations in the high elevations are considered is the ENSO signal in cold season precipitation in the basin revealed. Interdecadal hydroclimatic variations in the UCRB related to possible PDO influences were also investigated. There are significant shifts in the mean of UCRB's moisture-controlled variables (precipitation and streamflow) coincident with the PDO shifts, suggesting a connection between the two processes. It has been suggested in other studies that this connection could be expressed as a modulation on the predominance of each ENSO phase; that is, strong and consistent winter El Niño (La Niña) patterns are associated with the positive (negative) phase of the PDO. In the UCRB this apparent modulation seems to be accompanied by a general change in the sign of the correlation between ENSO indicators and cold season precipitation in most stations of the basin around 1932/33. From 1909 to 1932 the basin has a predominantly cold season ENSO response characteristic of the northwestern United States (drier than normal associated with tropical SST warming and vice versa); from 1933 to 1998 the response of the basin is predominantly typical of the southwestern United States during winter (wetter than normal associated with tropical SST warming and vice versa). This apparent correlation sign reversal is suggested to be related to interdecadal changes in the boundary of the north–south bipolar response characteristic of the ENSO signal in the western United States during winter.
Abstract
Linkages between tropical Pacific Ocean monthly climatic variables and the Upper Colorado River basin (UCRB) hydroclimatic variations from 1909 to 1998 are analyzed at interseasonal timescales. A study of the changes in these linkages through the years and their relationship to the Pacific Decadal Oscillation (PDO) is also investigated. Tropical Pacific climate variations were represented by atmospheric/oceanic ENSO indicators. For the UCRB, warm season (April–September) streamflow totals at Lee's Ferry, Arizona, and precipitation averages at different periods (cold season: October–March; warm season: April–September; and annual: October–September) were used to study the UCRB's response to tropical Pacific climatic forcing. A basinwide ENSO signature was found in the significant correlations between warm season precipitation in the UCRB and warm season SST averages from the Niño-3 region in most of the stations around the UCRB. This link is more evident during the warm phase of ENSO (El Niño), which is associated with an increase in warm season precipitation. The analysis also showed a link between June to November ENSO conditions and cold season precipitation variations contained in a principal component representing the high-elevation precipitation stations, which are the main source of streamflow. However, the amplitude and coherence of the cold season ENSO signal is significantly smaller compared to the general precipitation variations found in stations around the UCRB. Only when very few stations in the high elevations are considered is the ENSO signal in cold season precipitation in the basin revealed. Interdecadal hydroclimatic variations in the UCRB related to possible PDO influences were also investigated. There are significant shifts in the mean of UCRB's moisture-controlled variables (precipitation and streamflow) coincident with the PDO shifts, suggesting a connection between the two processes. It has been suggested in other studies that this connection could be expressed as a modulation on the predominance of each ENSO phase; that is, strong and consistent winter El Niño (La Niña) patterns are associated with the positive (negative) phase of the PDO. In the UCRB this apparent modulation seems to be accompanied by a general change in the sign of the correlation between ENSO indicators and cold season precipitation in most stations of the basin around 1932/33. From 1909 to 1932 the basin has a predominantly cold season ENSO response characteristic of the northwestern United States (drier than normal associated with tropical SST warming and vice versa); from 1933 to 1998 the response of the basin is predominantly typical of the southwestern United States during winter (wetter than normal associated with tropical SST warming and vice versa). This apparent correlation sign reversal is suggested to be related to interdecadal changes in the boundary of the north–south bipolar response characteristic of the ENSO signal in the western United States during winter.
Abstract
Recent studies demonstrate that ocean–atmosphere forcing by persistent sea surface temperature (SST) anomalies is a primary driver of seasonal-to-interannual hydroclimatic variability, including drought events. Other studies, however, conclude that although SST anomalies influence the timing of drought events, their duration and magnitude over continental regions is largely governed by land–atmosphere feedbacks. Here the authors evaluate the direct influence of SST anomalies on the stochastic characteristics of precipitation and drought in two ensembles of AGCM simulations forced with observed (interannually varying) monthly SST and their climatological annual cycle, respectively. Results demonstrate that ocean–atmosphere forcing contributes to the magnitude and persistence of simulated seasonal precipitation anomalies throughout the tropics but over few mid- and high-latitude regions. Significant autocorrelation of simulated seasonal anomalies over oceans is directly forced by persistent SST anomalies; over land, SST anomalies are shown to enhance autocorrelation associated with land–atmosphere feedbacks. SST anomalies are shown to have no significant influence on simulated drought frequency, duration, or magnitude over most midlatitude land regions. Results suggest that severe and sustained drought events may occur in the absence of persistent SST forcing and support recent conclusions that ocean–atmosphere forcing primarily influences the timing of drought events, while duration and magnitude are governed by other mechanisms such as land–atmosphere feedbacks. Further analysis is needed to assess the potential model dependence of results and to quantify the relative contribution of land–atmosphere feedbacks to the long-term stochastic characteristics of precipitation and drought.
Abstract
Recent studies demonstrate that ocean–atmosphere forcing by persistent sea surface temperature (SST) anomalies is a primary driver of seasonal-to-interannual hydroclimatic variability, including drought events. Other studies, however, conclude that although SST anomalies influence the timing of drought events, their duration and magnitude over continental regions is largely governed by land–atmosphere feedbacks. Here the authors evaluate the direct influence of SST anomalies on the stochastic characteristics of precipitation and drought in two ensembles of AGCM simulations forced with observed (interannually varying) monthly SST and their climatological annual cycle, respectively. Results demonstrate that ocean–atmosphere forcing contributes to the magnitude and persistence of simulated seasonal precipitation anomalies throughout the tropics but over few mid- and high-latitude regions. Significant autocorrelation of simulated seasonal anomalies over oceans is directly forced by persistent SST anomalies; over land, SST anomalies are shown to enhance autocorrelation associated with land–atmosphere feedbacks. SST anomalies are shown to have no significant influence on simulated drought frequency, duration, or magnitude over most midlatitude land regions. Results suggest that severe and sustained drought events may occur in the absence of persistent SST forcing and support recent conclusions that ocean–atmosphere forcing primarily influences the timing of drought events, while duration and magnitude are governed by other mechanisms such as land–atmosphere feedbacks. Further analysis is needed to assess the potential model dependence of results and to quantify the relative contribution of land–atmosphere feedbacks to the long-term stochastic characteristics of precipitation and drought.
The flooding in the lower basin of the Colorado River during the spring and summer of 1983 led to discussion of the management of the heavy spring runoff from the upper basin. This analysis stresses that the reasons for the flooding go beyond the climatic events of the year and the U.S. Bureau of Reclamation's response to them. It is argued that the flooding is the result of the convergence of three factors: 1) the 17-year period of filling Lake Powell (Glen Canyon Dam) has ended and the system of water storage reservoirs on the river now considered full; 2) during the filling period, physical encroachment into the lower basin flood plain accelerated; and 3) the climatic variability experienced in the Colorado River Basin.
The flooding in the lower basin of the Colorado River during the spring and summer of 1983 led to discussion of the management of the heavy spring runoff from the upper basin. This analysis stresses that the reasons for the flooding go beyond the climatic events of the year and the U.S. Bureau of Reclamation's response to them. It is argued that the flooding is the result of the convergence of three factors: 1) the 17-year period of filling Lake Powell (Glen Canyon Dam) has ended and the system of water storage reservoirs on the river now considered full; 2) during the filling period, physical encroachment into the lower basin flood plain accelerated; and 3) the climatic variability experienced in the Colorado River Basin.
