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- Author or Editor: Kelly Redmond x
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Abstract
A parameterization of the infrared clear-sky emissivity of the atmosphere at monthly to annual time scales and local to zonal space scales is developed. The total emissivity is the sum of contributions from ozone, assigned a constant value, and from water vapor and carbon dioxide, corrected for their spectral overlap. Emissivity can be adequately estimated from mean annual surface air temperature, annual range of monthly mean temperature and surface station pressure. Over most of the world, emissivity can be determined solely from surface temperature. Longwave counterradiation from the atmosphere to the surface is estimated from the parameterized emissivity and the surface temperature, and compared with fluxes calculated from soundings. This formulation is adaptable to any climate model which produces surface temperature as an output.
Abstract
A parameterization of the infrared clear-sky emissivity of the atmosphere at monthly to annual time scales and local to zonal space scales is developed. The total emissivity is the sum of contributions from ozone, assigned a constant value, and from water vapor and carbon dioxide, corrected for their spectral overlap. Emissivity can be adequately estimated from mean annual surface air temperature, annual range of monthly mean temperature and surface station pressure. Over most of the world, emissivity can be determined solely from surface temperature. Longwave counterradiation from the atmosphere to the surface is estimated from the parameterized emissivity and the surface temperature, and compared with fluxes calculated from soundings. This formulation is adaptable to any climate model which produces surface temperature as an output.
Abstract
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.
Abstract
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.
Abstract
The northeastern Pacific Ocean is a preferential location for the formation of closed low pressure systems. These slow-moving, quasi-barotropic systems influence vertical stability and sustain a moist environment, giving them the potential to produce or affect sustained precipitation episodes along the west coast of the United States. They can remain motionless or change direction and speed more than once and thus often pose difficult forecast challenges. This study creates an objective climatological description of 500-hPa closed lows to assess their impacts on precipitation in the western United States and to explore interannual variability and preferred tracks. Geopotential height at 500 hPa from the NCEP–NCAR global reanalysis dataset was used at 6-h and 2.5° × 2.5° resolution for the period 1948–2011. Closed lows displayed seasonality and preferential durations. Time series for seasonal and annual event counts were found to exhibit strong interannual variability. Composites of the tracks of landfalling closed lows revealed preferential tracks as the features move inland over the western United States. Correlations of seasonal event totals for closed lows with ENSO indices, the Pacific decadal oscillation (PDO), and the Pacific–North American (PNA) pattern suggested an above-average number of events during the warm phase of ENSO and positive PDO and PNA phases. Precipitation at 30 U.S. Cooperative Observer stations was attributed to closed-low events, suggesting 20%–60% of annual precipitation along the West Coast may be associated with closed lows.
Abstract
The northeastern Pacific Ocean is a preferential location for the formation of closed low pressure systems. These slow-moving, quasi-barotropic systems influence vertical stability and sustain a moist environment, giving them the potential to produce or affect sustained precipitation episodes along the west coast of the United States. They can remain motionless or change direction and speed more than once and thus often pose difficult forecast challenges. This study creates an objective climatological description of 500-hPa closed lows to assess their impacts on precipitation in the western United States and to explore interannual variability and preferred tracks. Geopotential height at 500 hPa from the NCEP–NCAR global reanalysis dataset was used at 6-h and 2.5° × 2.5° resolution for the period 1948–2011. Closed lows displayed seasonality and preferential durations. Time series for seasonal and annual event counts were found to exhibit strong interannual variability. Composites of the tracks of landfalling closed lows revealed preferential tracks as the features move inland over the western United States. Correlations of seasonal event totals for closed lows with ENSO indices, the Pacific decadal oscillation (PDO), and the Pacific–North American (PNA) pattern suggested an above-average number of events during the warm phase of ENSO and positive PDO and PNA phases. Precipitation at 30 U.S. Cooperative Observer stations was attributed to closed-low events, suggesting 20%–60% of annual precipitation along the West Coast may be associated with closed lows.
The Pacific Northwest is dependent on the vast and complex Columbia River system for power production, irrigation, navigation, flood control, recreation, municipal and industrial water supplies, and fish and wildlife habitat. In recent years Pacific salmon populations in this region, a highly valued cultural and economic resource, have declined precipitously. Since 1980, regional entities have embarked on the largest effort at ecosystem management undertaken to date in the United States, primarily aimed at balancing hydropower demands with salmon restoration activities. It has become increasingly clear that climatically driven fluctuations in the freshwater and marine environments occupied by these fish are an important influence on population variability. It is also clear that there are significant prospects of climate predictability that may prove advantageous in managing the water resources shared by the long cast of regional interests. The main thrusts of this study are 1) to describe the climate and management environments of the Columbia River basin, 2) to assess the present degree of use and benefits of available climate information, 3) to identify new roles and applications made possible by recent advances in climate forecasting, and 4) to understand, from the point of view of present and potential users in specific contexts of salmon management, what information might be needed, for what uses, and when, where, and how it should be provided. Interviews were carried out with 32 individuals in 19 organizations involved in salmon management decisions. Primary needs were in forecasting runoff volume and timing, river transit times, and stream temperatures, as much as a year or more in advance. Most respondents desired an accuracy of 75% for a seasonal forecast. Despite the significant influence of precipitation and its subsequent hydrologic impacts on the regional economy, no specific use of the present climate forecasts was uncovered. Understanding the limitations to information use forms a major component of this study. The complexity of the management environment, the lack of well-defined linkages among potential users and forecasters, and the lack of supplementary background information relating to the forecasts pose substantial barriers to future use of forecasts. Recommendations to address these problems are offered. The use of climate information and forecasts to reduce the uncertainty inherent in managing large systems for diverse needs bears significant promise. The Pacific Northwest is dependent on the vast and complex Columbia River system for power production, irrigation, navigation, flood control, recreation, municipal and industrial water supplies, and fish and wildlife habitat. In recent years Pacific salmon populations in this region, a highly valued cultural and economic resource, have declined precipitously. Since 1980, regional entities have embarked on the largest effort at ecosystem management undertaken to date in the United States, primarily aimed at balancing hydropower demands with salmon restoration activities. It has become increasingly clear that climatically driven fluctuations in the freshwater and marine environments occupied by these fish are an important influence on population variability. It is also clear that there are significant prospects of climate predictability that may prove advantageous in managing the water resources shared by the long cast of regional interests. The main thrusts of this study are 1) to describe the climate and management environments of the Columbia River basin, 2) to assess the present degree of use and benefits of available climate information, 3) to identify new roles and applications made possible by recent advances in climate forecasting, and 4) to understand, from the point of view of present and potential users in specific contexts of salmon management, what information might be needed, for what uses, and when, where, and how it should be provided. Interviews were carried out with 32 individuals in 19 organizations involved in salmon management decisions. Primary needs were in forecasting runoff volume and timing, river transit times, and stream temperatures, as much as a year or more in advance. Most respondents desired an accuracy of 75% for a seasonal forecast. Despite the significant influence of precipitation and its subsequent hydrologic impacts on the regional economy, no specific use of the present climate forecasts was uncovered. Understanding the limitations to information use forms a major component of this study. The complexity of the management environment, the lack of well-defined linkages among potential users and forecasters, and the lack of supplementary background information relating to the forecasts pose substantial barriers to future use of forecasts. Recommendations to address these problems are offered. The use of climate information and forecasts to reduce the uncertainty inherent in managing large systems for diverse needs bears significant promise.
The Pacific Northwest is dependent on the vast and complex Columbia River system for power production, irrigation, navigation, flood control, recreation, municipal and industrial water supplies, and fish and wildlife habitat. In recent years Pacific salmon populations in this region, a highly valued cultural and economic resource, have declined precipitously. Since 1980, regional entities have embarked on the largest effort at ecosystem management undertaken to date in the United States, primarily aimed at balancing hydropower demands with salmon restoration activities. It has become increasingly clear that climatically driven fluctuations in the freshwater and marine environments occupied by these fish are an important influence on population variability. It is also clear that there are significant prospects of climate predictability that may prove advantageous in managing the water resources shared by the long cast of regional interests. The main thrusts of this study are 1) to describe the climate and management environments of the Columbia River basin, 2) to assess the present degree of use and benefits of available climate information, 3) to identify new roles and applications made possible by recent advances in climate forecasting, and 4) to understand, from the point of view of present and potential users in specific contexts of salmon management, what information might be needed, for what uses, and when, where, and how it should be provided. Interviews were carried out with 32 individuals in 19 organizations involved in salmon management decisions. Primary needs were in forecasting runoff volume and timing, river transit times, and stream temperatures, as much as a year or more in advance. Most respondents desired an accuracy of 75% for a seasonal forecast. Despite the significant influence of precipitation and its subsequent hydrologic impacts on the regional economy, no specific use of the present climate forecasts was uncovered. Understanding the limitations to information use forms a major component of this study. The complexity of the management environment, the lack of well-defined linkages among potential users and forecasters, and the lack of supplementary background information relating to the forecasts pose substantial barriers to future use of forecasts. Recommendations to address these problems are offered. The use of climate information and forecasts to reduce the uncertainty inherent in managing large systems for diverse needs bears significant promise. The Pacific Northwest is dependent on the vast and complex Columbia River system for power production, irrigation, navigation, flood control, recreation, municipal and industrial water supplies, and fish and wildlife habitat. In recent years Pacific salmon populations in this region, a highly valued cultural and economic resource, have declined precipitously. Since 1980, regional entities have embarked on the largest effort at ecosystem management undertaken to date in the United States, primarily aimed at balancing hydropower demands with salmon restoration activities. It has become increasingly clear that climatically driven fluctuations in the freshwater and marine environments occupied by these fish are an important influence on population variability. It is also clear that there are significant prospects of climate predictability that may prove advantageous in managing the water resources shared by the long cast of regional interests. The main thrusts of this study are 1) to describe the climate and management environments of the Columbia River basin, 2) to assess the present degree of use and benefits of available climate information, 3) to identify new roles and applications made possible by recent advances in climate forecasting, and 4) to understand, from the point of view of present and potential users in specific contexts of salmon management, what information might be needed, for what uses, and when, where, and how it should be provided. Interviews were carried out with 32 individuals in 19 organizations involved in salmon management decisions. Primary needs were in forecasting runoff volume and timing, river transit times, and stream temperatures, as much as a year or more in advance. Most respondents desired an accuracy of 75% for a seasonal forecast. Despite the significant influence of precipitation and its subsequent hydrologic impacts on the regional economy, no specific use of the present climate forecasts was uncovered. Understanding the limitations to information use forms a major component of this study. The complexity of the management environment, the lack of well-defined linkages among potential users and forecasters, and the lack of supplementary background information relating to the forecasts pose substantial barriers to future use of forecasts. Recommendations to address these problems are offered. The use of climate information and forecasts to reduce the uncertainty inherent in managing large systems for diverse needs bears significant promise.
Abstract
The National Oceanic and Atmospheric Administration is establishing the U.S. Climate Reference Network (CRN) to improve the capacity for observing climatic change and variability. A goal of this network is to provide homogeneous observations of temperature and precipitation from benchmark stations that can be coupled with historical observations for detection and attribution of climatic change. The purpose of this study was to estimate the number and distribution of U.S. CRN observing sites. The analysis was conducted by forming hypothetical networks from representative subsamples of stations in an existing higher-density baseline network. The objective was to have the differences between the annual temperature and precipitation trends computed from reduced-size networks and the full-size networks not greater than predetermined error limits. This analysis was performed on a grid cell basis to incorporate the expectation that a greater station density would be required to achieve the monitoring goals in areas with greater spatial gradients in trends. Monte Carlo resampling techniques were applied to stations within 2.5° latitude × 3.5° longitude grid cells to successively lower the resolution compared to that in the reference or baseline network. Differences between 30-yr trends from lower-resolution networks and full-resolution networks were generated for each grid cell. Grid cell densities were determined separately for temperature and precipitation trends. In practice densities can be derived for any parameter and monitoring goal. A network of 327 stations for the contiguous United States satisfied a combined temperature-trend goal of 0.10°C decade−1 and a precipitation-trend goal of 2.0% of median precipitation per decade.
Abstract
The National Oceanic and Atmospheric Administration is establishing the U.S. Climate Reference Network (CRN) to improve the capacity for observing climatic change and variability. A goal of this network is to provide homogeneous observations of temperature and precipitation from benchmark stations that can be coupled with historical observations for detection and attribution of climatic change. The purpose of this study was to estimate the number and distribution of U.S. CRN observing sites. The analysis was conducted by forming hypothetical networks from representative subsamples of stations in an existing higher-density baseline network. The objective was to have the differences between the annual temperature and precipitation trends computed from reduced-size networks and the full-size networks not greater than predetermined error limits. This analysis was performed on a grid cell basis to incorporate the expectation that a greater station density would be required to achieve the monitoring goals in areas with greater spatial gradients in trends. Monte Carlo resampling techniques were applied to stations within 2.5° latitude × 3.5° longitude grid cells to successively lower the resolution compared to that in the reference or baseline network. Differences between 30-yr trends from lower-resolution networks and full-resolution networks were generated for each grid cell. Grid cell densities were determined separately for temperature and precipitation trends. In practice densities can be derived for any parameter and monitoring goal. A network of 327 stations for the contiguous United States satisfied a combined temperature-trend goal of 0.10°C decade−1 and a precipitation-trend goal of 2.0% of median precipitation per decade.
Abstract
A novel approach is presented to objectively identify regional patterns of climate variability within the state of California using principal component analysis on monthly precipitation and temperature data from a network of 195 climate stations statewide and an ancillary gridded database. The confluence of large-scale circulation patterns and the complex geography of the state result in 11 regional modes of climate variability within the state. A comparison between the station and gridded analyses reveals that finescale spatial resolution is needed to adequately capture regional modes in complex orographic and coastal settings. Objectively identified regions can be employed not only in tracking regional climate signatures, but also in improving the understanding of mechanisms behind regional climate variability and climate change. The analysis has been incorporated into an operational tool called the California Climate Tracker.
Abstract
A novel approach is presented to objectively identify regional patterns of climate variability within the state of California using principal component analysis on monthly precipitation and temperature data from a network of 195 climate stations statewide and an ancillary gridded database. The confluence of large-scale circulation patterns and the complex geography of the state result in 11 regional modes of climate variability within the state. A comparison between the station and gridded analyses reveals that finescale spatial resolution is needed to adequately capture regional modes in complex orographic and coastal settings. Objectively identified regions can be employed not only in tracking regional climate signatures, but also in improving the understanding of mechanisms behind regional climate variability and climate change. The analysis has been incorporated into an operational tool called the California Climate Tracker.
Abstract
Frequency distributions of daily precipitation in winter and daily stream flow from late winter to early summer, at several hundred sites in the western United States, exhibit strong and systematic responses to the two phases of ENSO. Most of the stream flows considered are driven by snowmelt. The Southern Oscillation index (SOI) is used as the ENSO phase indicator. Both modest (median) and larger (90th percentile) events were considered. In years with negative SOI values (El Niño), days with high daily precipitation and stream flow are more frequent than average over the Southwest and less frequent over the Northwest. During years with positive SOI values (La Niña), a nearly opposite pattern is seen. A more pronounced increase is seen in the number of days exceeding climatological 90th percentile values than in the number exceeding climatological 50th percentile values, for both precipitation and stream flow. Stream flow responses to ENSO extremes are accentuated over precipitation responses. Evidence suggests that the mechanism for this amplification involves ENSO-phase differences in the persistence and duration of wet episodes, affecting the efficiency of the process by which precipitation is converted to runoff. The SOI leads the precipitation events by several months, and hydrologic lags (mostly through snowmelt) delay the stream flow response by several more months. The combined 6–12-month predictive aspect of this relationship should be of significant benefit in responding to flood (or drought) risk and in improving overall water management in the western states.
Abstract
Frequency distributions of daily precipitation in winter and daily stream flow from late winter to early summer, at several hundred sites in the western United States, exhibit strong and systematic responses to the two phases of ENSO. Most of the stream flows considered are driven by snowmelt. The Southern Oscillation index (SOI) is used as the ENSO phase indicator. Both modest (median) and larger (90th percentile) events were considered. In years with negative SOI values (El Niño), days with high daily precipitation and stream flow are more frequent than average over the Southwest and less frequent over the Northwest. During years with positive SOI values (La Niña), a nearly opposite pattern is seen. A more pronounced increase is seen in the number of days exceeding climatological 90th percentile values than in the number exceeding climatological 50th percentile values, for both precipitation and stream flow. Stream flow responses to ENSO extremes are accentuated over precipitation responses. Evidence suggests that the mechanism for this amplification involves ENSO-phase differences in the persistence and duration of wet episodes, affecting the efficiency of the process by which precipitation is converted to runoff. The SOI leads the precipitation events by several months, and hydrologic lags (mostly through snowmelt) delay the stream flow response by several more months. The combined 6–12-month predictive aspect of this relationship should be of significant benefit in responding to flood (or drought) risk and in improving overall water management in the western states.
Abstract
A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this “homogeneous segments” of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910–2003. Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (> +0.25°C decade−1). The Valley trend of annual mean temperatures is +0.07° ± 0.07°C decade−1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable −0.02° ± 0.10°C decade−1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (>0.4°C decade−1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain.
Abstract
A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this “homogeneous segments” of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910–2003. Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (> +0.25°C decade−1). The Valley trend of annual mean temperatures is +0.07° ± 0.07°C decade−1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable −0.02° ± 0.10°C decade−1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (>0.4°C decade−1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain.
