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- Author or Editor: D. Cayan x
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Abstract
The diurnal cycle in streamflow constitutes a significant part of the variability in many rivers in the western United States and can be used to understand some of the dominant processes affecting the water balance of a given river basin. Rivers in which water is added diurnally, as in snowmelt, and rivers in which water is removed diurnally, as in evapotranspiration and infiltration, exhibit substantial differences in the timing, relative magnitude, and shape of their diurnal flow variations. Snowmelt-dominated rivers achieve their highest sustained flow and largest diurnal fluctuations during the spring melt season. These fluctuations are characterized by sharp rises and gradual declines in discharge each day. In large snowmelt-dominated basins, at the end of the melt season, the hour of maximum discharge shifts to later in the day as the snow line retreats to higher elevations. Many evapotranspiration/infiltration-dominated rivers in the western states achieve their highest sustained flows during the winter rainy season but exhibit their strongest diurnal cycles during summer months, when discharge is low, and the diurnal fluctuations compose a large percentage of the total flow. In contrast to snowmelt-dominated rivers, the maximum discharge in evapotranspiration/infiltration-dominated rivers occurs consistently in the morning throughout the summer. In these rivers, diurnal changes are characterized by a gradual rise and sharp decline each day.
Abstract
The diurnal cycle in streamflow constitutes a significant part of the variability in many rivers in the western United States and can be used to understand some of the dominant processes affecting the water balance of a given river basin. Rivers in which water is added diurnally, as in snowmelt, and rivers in which water is removed diurnally, as in evapotranspiration and infiltration, exhibit substantial differences in the timing, relative magnitude, and shape of their diurnal flow variations. Snowmelt-dominated rivers achieve their highest sustained flow and largest diurnal fluctuations during the spring melt season. These fluctuations are characterized by sharp rises and gradual declines in discharge each day. In large snowmelt-dominated basins, at the end of the melt season, the hour of maximum discharge shifts to later in the day as the snow line retreats to higher elevations. Many evapotranspiration/infiltration-dominated rivers in the western states achieve their highest sustained flows during the winter rainy season but exhibit their strongest diurnal cycles during summer months, when discharge is low, and the diurnal fluctuations compose a large percentage of the total flow. In contrast to snowmelt-dominated rivers, the maximum discharge in evapotranspiration/infiltration-dominated rivers occurs consistently in the morning throughout the summer. In these rivers, diurnal changes are characterized by a gradual rise and sharp decline each day.
Abstract
Short-term climate and weather systems can have a strong influence on mountain snowmelt, sometimes overwhelming the effects of elevation and aspect. Although most years exhibit a spring onset that starts first at lowest and moves to highest elevations, in spring 2002, flow in a variety of streams within the Tuolumne and Merced River basins of the southern Sierra Nevada all rose synchronously on 29 March. Flow in streams draining small high-altitude glacial subcatchments rose at the same time as that draining much larger basins gauged at lower altitudes, and streams from north- and south-facing cirques rose and fell together. Historical analysis demonstrates that 2002 was one among only 8 yr with such synchronous flow onsets during the past 87 yr, recognized by having simultaneous onsets of snowmelt at over 70% of snow pillow sites, having discharge in over 70% of monitored streams increase simultaneously, and having temperatures increase over 12°C within a 5-day period. Synchronous springs tend to begin with a low pressure trough over California during late winter, followed by the onset of a strong ridge and unusually warm temperatures. Synchronous springs are characterized by warmer than average winters and cooler than average March temperatures in California. In the most elevation-dependent, nonsynchronous years, periods of little or no storm activity, with warmer than average March temperatures, precede the onset of spring snowmelt, allowing elevation and aspect to influence snowmelt as spring arrives gradually.
Abstract
Short-term climate and weather systems can have a strong influence on mountain snowmelt, sometimes overwhelming the effects of elevation and aspect. Although most years exhibit a spring onset that starts first at lowest and moves to highest elevations, in spring 2002, flow in a variety of streams within the Tuolumne and Merced River basins of the southern Sierra Nevada all rose synchronously on 29 March. Flow in streams draining small high-altitude glacial subcatchments rose at the same time as that draining much larger basins gauged at lower altitudes, and streams from north- and south-facing cirques rose and fell together. Historical analysis demonstrates that 2002 was one among only 8 yr with such synchronous flow onsets during the past 87 yr, recognized by having simultaneous onsets of snowmelt at over 70% of snow pillow sites, having discharge in over 70% of monitored streams increase simultaneously, and having temperatures increase over 12°C within a 5-day period. Synchronous springs tend to begin with a low pressure trough over California during late winter, followed by the onset of a strong ridge and unusually warm temperatures. Synchronous springs are characterized by warmer than average winters and cooler than average March temperatures in California. In the most elevation-dependent, nonsynchronous years, periods of little or no storm activity, with warmer than average March temperatures, precede the onset of spring snowmelt, allowing elevation and aspect to influence snowmelt as spring arrives gradually.
Abstract
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.
Abstract
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.
Abstract
A new set of CMIP6 data downscaled using the localized constructed analogs (LOCA) statistical method has been produced, covering central Mexico through southern Canada at 6-km resolution. Output from 27 CMIP6 Earth system models is included, with up to 10 ensemble members per model and 3 SSPs (245, 370, and 585). Improvements from the previous CMIP5 downscaled data result in higher daily precipitation extremes, which have significant societal and economic implications. The improvements are accomplished by using a precipitation training dataset that better represents daily extremes and by implementing an ensemble bias correction that allows a more realistic representation of extreme high daily precipitation values in models with numerous ensemble members. Over southern Canada and the CONUS exclusive of Arizona (AZ) and New Mexico (NM), seasonal increases in daily precipitation extremes are largest in winter (∼25% in SSP370). Over Mexico, AZ, and NM, seasonal increases are largest in autumn (∼15%). Summer is the outlier season, with low model agreement except in New England and little changes in 5-yr return values, but substantial increases in the CONUS and Canada in the 500-yr return value. One-in-100-yr historical daily precipitation events become substantially more frequent in the future, as often as once in 30–40 years in the southeastern United States and Pacific Northwest by the end of the century under SSP 370. Impacts of the higher precipitation extremes in the LOCA version 2 downscaled CMIP6 product relative to the LOCA downscaled CMIP5 product, even for similar anthropogenic emissions, may need to be considered by end-users.
Abstract
A new set of CMIP6 data downscaled using the localized constructed analogs (LOCA) statistical method has been produced, covering central Mexico through southern Canada at 6-km resolution. Output from 27 CMIP6 Earth system models is included, with up to 10 ensemble members per model and 3 SSPs (245, 370, and 585). Improvements from the previous CMIP5 downscaled data result in higher daily precipitation extremes, which have significant societal and economic implications. The improvements are accomplished by using a precipitation training dataset that better represents daily extremes and by implementing an ensemble bias correction that allows a more realistic representation of extreme high daily precipitation values in models with numerous ensemble members. Over southern Canada and the CONUS exclusive of Arizona (AZ) and New Mexico (NM), seasonal increases in daily precipitation extremes are largest in winter (∼25% in SSP370). Over Mexico, AZ, and NM, seasonal increases are largest in autumn (∼15%). Summer is the outlier season, with low model agreement except in New England and little changes in 5-yr return values, but substantial increases in the CONUS and Canada in the 500-yr return value. One-in-100-yr historical daily precipitation events become substantially more frequent in the future, as often as once in 30–40 years in the southeastern United States and Pacific Northwest by the end of the century under SSP 370. Impacts of the higher precipitation extremes in the LOCA version 2 downscaled CMIP6 product relative to the LOCA downscaled CMIP5 product, even for similar anthropogenic emissions, may need to be considered by end-users.
Abstract
A hybrid (physical–statistical) scheme is developed to resolve the finescale distribution of daily precipitation over complex terrain. The scheme generates precipitation by combining information from the upper-air conditions and from sparsely distributed station measurements; thus, it proceeds in two steps. First, an initial estimate of the precipitation is made using a simplified orographic precipitation model. It is a steady-state, multilayer, and two-dimensional model following the concepts of Rhea. The model is driven by the 2.5° × 2.5° gridded National Oceanic and Atmospheric Administration–National Centers for Environmental Prediction upper-air profiles, and its parameters are tuned using the observed precipitation structure of the region. Precipitation is generated assuming a forced lifting of the air parcels as they cross the mountain barrier following a straight trajectory. Second, the precipitation is adjusted using errors between derived precipitation and observations from nearby sites. The study area covers the northern half of California, including coastal mountains, central valley, and the Sierra Nevada. The model is run for a 5-km rendition of terrain for days of January–March over the period of 1988–95. A jackknife analysis demonstrates the validity of the approach. The spatial and temporal distributions of the simulated precipitation field agree well with the observed precipitation. Further, a mapping of model performance indices (correlation coefficients, model bias, root-mean-square error, and threat scores) from an array of stations from the region indicates that the model performs satisfactorily in resolving daily precipitation at 5-km resolution.
Abstract
A hybrid (physical–statistical) scheme is developed to resolve the finescale distribution of daily precipitation over complex terrain. The scheme generates precipitation by combining information from the upper-air conditions and from sparsely distributed station measurements; thus, it proceeds in two steps. First, an initial estimate of the precipitation is made using a simplified orographic precipitation model. It is a steady-state, multilayer, and two-dimensional model following the concepts of Rhea. The model is driven by the 2.5° × 2.5° gridded National Oceanic and Atmospheric Administration–National Centers for Environmental Prediction upper-air profiles, and its parameters are tuned using the observed precipitation structure of the region. Precipitation is generated assuming a forced lifting of the air parcels as they cross the mountain barrier following a straight trajectory. Second, the precipitation is adjusted using errors between derived precipitation and observations from nearby sites. The study area covers the northern half of California, including coastal mountains, central valley, and the Sierra Nevada. The model is run for a 5-km rendition of terrain for days of January–March over the period of 1988–95. A jackknife analysis demonstrates the validity of the approach. The spatial and temporal distributions of the simulated precipitation field agree well with the observed precipitation. Further, a mapping of model performance indices (correlation coefficients, model bias, root-mean-square error, and threat scores) from an array of stations from the region indicates that the model performs satisfactorily in resolving daily precipitation at 5-km resolution.
Abstract
This study examines the geographic structure of observed trends in key hydrologically relevant variables across the western United States at ⅛° spatial resolution during the period 1950–99. Geographical regions, latitude bands, and elevation classes where these trends are statistically significantly different from trends associated with natural climate variations are identified. Variables analyzed include late-winter and spring temperature, winter-total snowy days as a fraction of winter-total wet days, 1 April snow water equivalent (SWE) as a fraction of October–March (ONDJFM) precipitation total [precip(ONDJFM)], and seasonal [JFM] accumulated runoff as a fraction of water-year accumulated runoff. Observed changes were compared to natural internal climate variability simulated by an 850-yr control run of the finite volume version of the Community Climate System Model, version 3 (CCSM3-FV), statistically downscaled to a ⅛° grid using the method of constructed analogs. Both observed and downscaled model temperature and precipitation data were then used to drive the Variable Infiltration Capacity (VIC) hydrological model to obtain the hydrological variables analyzed in this study. Large trends (magnitudes found less than 5% of the time in the long control run) are common in the observations and occupy a substantial part (37%–42%) of the mountainous western United States. These trends are strongly related to the large-scale warming that appears over 89% of the domain. The strongest changes in the hydrologic variables, unlikely to be associated with natural variability alone, have occurred at medium elevations [750–2500 m for JFM runoff fractions and 500–3000 m for SWE/Precip(ONDJFM)] where warming has pushed temperatures from slightly below to slightly above freezing. Further analysis using the data on selected catchments indicates that hydroclimatic variables must have changed significantly (at 95% confidence level) over at least 45% of the total catchment area to achieve a detectable trend in measures accumulated to the catchment scale.
Abstract
This study examines the geographic structure of observed trends in key hydrologically relevant variables across the western United States at ⅛° spatial resolution during the period 1950–99. Geographical regions, latitude bands, and elevation classes where these trends are statistically significantly different from trends associated with natural climate variations are identified. Variables analyzed include late-winter and spring temperature, winter-total snowy days as a fraction of winter-total wet days, 1 April snow water equivalent (SWE) as a fraction of October–March (ONDJFM) precipitation total [precip(ONDJFM)], and seasonal [JFM] accumulated runoff as a fraction of water-year accumulated runoff. Observed changes were compared to natural internal climate variability simulated by an 850-yr control run of the finite volume version of the Community Climate System Model, version 3 (CCSM3-FV), statistically downscaled to a ⅛° grid using the method of constructed analogs. Both observed and downscaled model temperature and precipitation data were then used to drive the Variable Infiltration Capacity (VIC) hydrological model to obtain the hydrological variables analyzed in this study. Large trends (magnitudes found less than 5% of the time in the long control run) are common in the observations and occupy a substantial part (37%–42%) of the mountainous western United States. These trends are strongly related to the large-scale warming that appears over 89% of the domain. The strongest changes in the hydrologic variables, unlikely to be associated with natural variability alone, have occurred at medium elevations [750–2500 m for JFM runoff fractions and 500–3000 m for SWE/Precip(ONDJFM)] where warming has pushed temperatures from slightly below to slightly above freezing. Further analysis using the data on selected catchments indicates that hydroclimatic variables must have changed significantly (at 95% confidence level) over at least 45% of the total catchment area to achieve a detectable trend in measures accumulated to the catchment scale.
Abstract
Extreme daily precipitation contributes to flooding that can cause significant economic damages, and so is important to properly capture in gridded meteorological datasets. This work examines precipitation extremes, the mean precipitation on wet days, and fraction of wet days in two widely used gridded datasets over the conterminous United States. Compared to the underlying station observations, the gridded data show a 27% reduction in annual 1-day maximum precipitation, 25% increase in wet day fraction, 1.5–2.5 day increase in mean wet spell length, 30% low bias in 20-yr return values of daily precipitation, and 25% decrease in mean precipitation on wet days. It is shown these changes arise primarily from the time adjustment applied to put the precipitation gauge observations into a uniform time frame, with the gridding process playing a lesser role. A new daily precipitation dataset is developed that omits the time adjustment (as well as extending the gridded data by 7 years) and is shown to perform significantly better in reproducing extreme precipitation metrics. When the new dataset is used to force a land surface model, annually averaged 1-day maximum runoff increases 38% compared to the original data, annual mean runoff increases 17%, evapotranspiration drops 2.3%, and fewer wet days leads to a 3.3% increase in estimated solar insolation. These changes are large enough to affect portrayals of flood risk and water balance components important for ecological and climate change applications across the CONUS.
Abstract
Extreme daily precipitation contributes to flooding that can cause significant economic damages, and so is important to properly capture in gridded meteorological datasets. This work examines precipitation extremes, the mean precipitation on wet days, and fraction of wet days in two widely used gridded datasets over the conterminous United States. Compared to the underlying station observations, the gridded data show a 27% reduction in annual 1-day maximum precipitation, 25% increase in wet day fraction, 1.5–2.5 day increase in mean wet spell length, 30% low bias in 20-yr return values of daily precipitation, and 25% decrease in mean precipitation on wet days. It is shown these changes arise primarily from the time adjustment applied to put the precipitation gauge observations into a uniform time frame, with the gridding process playing a lesser role. A new daily precipitation dataset is developed that omits the time adjustment (as well as extending the gridded data by 7 years) and is shown to perform significantly better in reproducing extreme precipitation metrics. When the new dataset is used to force a land surface model, annually averaged 1-day maximum runoff increases 38% compared to the original data, annual mean runoff increases 17%, evapotranspiration drops 2.3%, and fewer wet days leads to a 3.3% increase in estimated solar insolation. These changes are large enough to affect portrayals of flood risk and water balance components important for ecological and climate change applications across the CONUS.