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Abstract
The estimation of ultraviolet-A (UV-A) radiation across the earth’s surface is needed to model plant productivity and future impacts of ultraviolet-B radiation on plant productivity. We have developed two models to estimate the UV-A irradiance from measurements of the diffuse and global spectral irradiance at 368 nm. The models were developed from 30-min-interval measurements made throughout 2000 at three locations across the United States and evaluated from 30-min measurements made throughout 2000 at three additional locations and throughout 2001 and 2002 at seven locations. UV-A irradiance was best estimated from measured global 368-nm irradiance and empirical functions defining the UV-A and 368-nm irradiance values estimated from a theoretical pseudospherical two-stream discrete-ordinates radiative transfer model. The radiative transfer model provided baseline irradiance relationships between UV-A irradiance and 368-nm spectral irradiance. The semiempirical model estimated the UV-A irradiance at seven locations across the United States with a mean bias error of 0.5 W m−2 and a root-mean-square error of 2 W m−2, corresponding to approximately ±4% of a clear-sky irradiance of 50 W m−2 for a solar zenith angle of 30°. This model error was comparable to the combined effect of previously estimated UV-A and 368-nm irradiance measurement errors.
Abstract
The estimation of ultraviolet-A (UV-A) radiation across the earth’s surface is needed to model plant productivity and future impacts of ultraviolet-B radiation on plant productivity. We have developed two models to estimate the UV-A irradiance from measurements of the diffuse and global spectral irradiance at 368 nm. The models were developed from 30-min-interval measurements made throughout 2000 at three locations across the United States and evaluated from 30-min measurements made throughout 2000 at three additional locations and throughout 2001 and 2002 at seven locations. UV-A irradiance was best estimated from measured global 368-nm irradiance and empirical functions defining the UV-A and 368-nm irradiance values estimated from a theoretical pseudospherical two-stream discrete-ordinates radiative transfer model. The radiative transfer model provided baseline irradiance relationships between UV-A irradiance and 368-nm spectral irradiance. The semiempirical model estimated the UV-A irradiance at seven locations across the United States with a mean bias error of 0.5 W m−2 and a root-mean-square error of 2 W m−2, corresponding to approximately ±4% of a clear-sky irradiance of 50 W m−2 for a solar zenith angle of 30°. This model error was comparable to the combined effect of previously estimated UV-A and 368-nm irradiance measurement errors.
Abstract
The stabilities of two model tropospheric jets are compared. The first jet is a simple, smooth, idealized profile governed by a single scale length of tropospheric dimensions. The second jet takes the first model flow and superimposes on it a localized deformation of much smaller scale. In this second model, the shears deriving from the small-scale structure provide the subcritical Richardson numbers that support instability. The two-scale model produces a much wider range of wave instabilities. Its Kelvin-Helmholtz waves span a wavenumber domain that is nearly two orders of magnitude wider than the domain of the one-scale model, while the gravity shear waves fill out into the small wavenumber areas of the stability diagrams. However, the growth rates of the instabilities displace significantly toward smaller scales in the two-scale model.
It is suggested that the two-scale model is probably geophysically more realistic, and removes the necessity for deep layers of subcritical Richardson numbers, making it more in agreement with radiosonde observations than are smooth one-scale models.
Abstract
The stabilities of two model tropospheric jets are compared. The first jet is a simple, smooth, idealized profile governed by a single scale length of tropospheric dimensions. The second jet takes the first model flow and superimposes on it a localized deformation of much smaller scale. In this second model, the shears deriving from the small-scale structure provide the subcritical Richardson numbers that support instability. The two-scale model produces a much wider range of wave instabilities. Its Kelvin-Helmholtz waves span a wavenumber domain that is nearly two orders of magnitude wider than the domain of the one-scale model, while the gravity shear waves fill out into the small wavenumber areas of the stability diagrams. However, the growth rates of the instabilities displace significantly toward smaller scales in the two-scale model.
It is suggested that the two-scale model is probably geophysically more realistic, and removes the necessity for deep layers of subcritical Richardson numbers, making it more in agreement with radiosonde observations than are smooth one-scale models.
Abstract
Upscale scattering of Kelvin-Helmholtz waves to gravity shear waves involves the nonlinear interaction of two Kelvin-Helmholtz waves with wavenumbers k and k′ to produce a wave with wavenumber k−k′. Calculations show that the process produces long-wavelength radiating gravity waves in atmospheric conditions that favor the Kelvin-Helmholtz instabilities. Both line and continuum evaluations are presented in the context of the unstable tropospheric jet. It is shown that even when the unstable shear in the jet is confined to a shallow sublayer, producing markedly small-scale Kelvin-Helmholtz instabilities, upscale scattering to the large-scale waves is an efficient process.
Abstract
Upscale scattering of Kelvin-Helmholtz waves to gravity shear waves involves the nonlinear interaction of two Kelvin-Helmholtz waves with wavenumbers k and k′ to produce a wave with wavenumber k−k′. Calculations show that the process produces long-wavelength radiating gravity waves in atmospheric conditions that favor the Kelvin-Helmholtz instabilities. Both line and continuum evaluations are presented in the context of the unstable tropospheric jet. It is shown that even when the unstable shear in the jet is confined to a shallow sublayer, producing markedly small-scale Kelvin-Helmholtz instabilities, upscale scattering to the large-scale waves is an efficient process.
Abstract
The correction of a land surface albedo estimate made at one solar zenith angle (SZA) from a polar-orbiting satellite to a standard SZA or to a daily mean albedo requires knowledge of the dependence of the albedo on SZA. This paper uses ground-based measurements of the clear-sky albedo at a uniform grassland site at Uardry (34.39°S, 145.30°E) in southeastern Australia to investigate the accuracy to which the daily mean albedo can be inferred from the albedo at 1030 LST, given knowledge of the SZA dependence of albedo to various levels of detail. During nine months in which the daily mean albedo varied from 0.20 to 0.27, the albedo always had the expected minimum near noon but the strength of the albedo’s SZA dependence varied greatly. For a few months, albedos were up to 0.04 higher in the afternoon than in the morning, and variations on finer timescales of up to 0.02 also appeared in the diurnal albedo cycle for days or weeks. These features of the diurnal variation were all seen at two or three surface points separated by up to 750 m and so are expected to appear at the ∼1-km resolution of many satellite sensors. For the Uardry grassland site, the error in estimating the daily mean albedo from the 1030 LST, albedo can be up to 0.03, which is 15% of an albedo of 0.20, if the albedo is assumed to be constant through the day. The maximum error is reduced to about 0.02 if a simple model of the SZA dependence is used with even an approximate value for the parameter that controls the strength of the dependence, and to 0.01 or less if the strength of the dependence is appropriate to the state of the vegetation on the day. Afternoon–morning asymmetry in the albedo can contribute almost 0.01 to the error in inferring a daily albedo from a morning measurement.
Abstract
The correction of a land surface albedo estimate made at one solar zenith angle (SZA) from a polar-orbiting satellite to a standard SZA or to a daily mean albedo requires knowledge of the dependence of the albedo on SZA. This paper uses ground-based measurements of the clear-sky albedo at a uniform grassland site at Uardry (34.39°S, 145.30°E) in southeastern Australia to investigate the accuracy to which the daily mean albedo can be inferred from the albedo at 1030 LST, given knowledge of the SZA dependence of albedo to various levels of detail. During nine months in which the daily mean albedo varied from 0.20 to 0.27, the albedo always had the expected minimum near noon but the strength of the albedo’s SZA dependence varied greatly. For a few months, albedos were up to 0.04 higher in the afternoon than in the morning, and variations on finer timescales of up to 0.02 also appeared in the diurnal albedo cycle for days or weeks. These features of the diurnal variation were all seen at two or three surface points separated by up to 750 m and so are expected to appear at the ∼1-km resolution of many satellite sensors. For the Uardry grassland site, the error in estimating the daily mean albedo from the 1030 LST, albedo can be up to 0.03, which is 15% of an albedo of 0.20, if the albedo is assumed to be constant through the day. The maximum error is reduced to about 0.02 if a simple model of the SZA dependence is used with even an approximate value for the parameter that controls the strength of the dependence, and to 0.01 or less if the strength of the dependence is appropriate to the state of the vegetation on the day. Afternoon–morning asymmetry in the albedo can contribute almost 0.01 to the error in inferring a daily albedo from a morning measurement.
Abstract
Temperature time series for stations in western North Carolina are used to evaluate the potential for an urban signal in the local temperature trend, and to compare a homogeneous temperature record from a mountain-top station to two versions of the lower-tropospheric, satellite-derived temperatures from the Microwave Sounding Unit (MSU). Results regarding the urban signal are in agreement with the conclusion from previous investigations that after a location is urbanized, the local temperature trend is consistent with trends derived from surrounding, more rural stations. With respect to the mountain top and lower-tropospheric temperature comparison, the magnitudes of the two MSU-derived trends for the western North Carolina area are closer to the average annual minimum temperature trend than to the annual average maximum temperature trend.
Abstract
Temperature time series for stations in western North Carolina are used to evaluate the potential for an urban signal in the local temperature trend, and to compare a homogeneous temperature record from a mountain-top station to two versions of the lower-tropospheric, satellite-derived temperatures from the Microwave Sounding Unit (MSU). Results regarding the urban signal are in agreement with the conclusion from previous investigations that after a location is urbanized, the local temperature trend is consistent with trends derived from surrounding, more rural stations. With respect to the mountain top and lower-tropospheric temperature comparison, the magnitudes of the two MSU-derived trends for the western North Carolina area are closer to the average annual minimum temperature trend than to the annual average maximum temperature trend.
Abstract
Sea level anomaly extremes impact tropical Pacific Ocean islands, often with too little warning to mitigate risks. With El Niño, such as the strong 2015/16 event, comes weaker trade winds and mean sea level drops exceeding 30 cm in the western Pacific that expose shallow-water ecosystems at low tides. Nearly opposite climate conditions accompany La Niña events, which cause sea level high stands (10–20 cm) and result in more frequent tide- and storm-related inundations that threaten coastlines. In the past, these effects have been exacerbated by decadal sea level variability, as well as continuing global sea level rise. Climate models, which are increasingly better able to simulate past and future evolutions of phenomena responsible for these extremes (i.e., El Niño–Southern Oscillation, Pacific decadal oscillation, and greenhouse warming), are also able to describe, or even directly simulate, associated sea level fluctuations. By compiling monthly sea level anomaly predictions from multiple statistical and dynamical (coupled ocean–atmosphere) models, which are typically skillful out to at least six months in the tropical Pacific, improved future outlooks are achieved. From this multimodel ensemble comes forecasts that are less prone to individual model errors and also uncertainty measurements achieved by comparing retrospective forecasts with the observed sea level. This framework delivers online a new real-time forecasting product of monthly mean sea level anomalies and will provide to the Pacific island community information that can be used to reduce impacts associated with sea level extremes.
Abstract
Sea level anomaly extremes impact tropical Pacific Ocean islands, often with too little warning to mitigate risks. With El Niño, such as the strong 2015/16 event, comes weaker trade winds and mean sea level drops exceeding 30 cm in the western Pacific that expose shallow-water ecosystems at low tides. Nearly opposite climate conditions accompany La Niña events, which cause sea level high stands (10–20 cm) and result in more frequent tide- and storm-related inundations that threaten coastlines. In the past, these effects have been exacerbated by decadal sea level variability, as well as continuing global sea level rise. Climate models, which are increasingly better able to simulate past and future evolutions of phenomena responsible for these extremes (i.e., El Niño–Southern Oscillation, Pacific decadal oscillation, and greenhouse warming), are also able to describe, or even directly simulate, associated sea level fluctuations. By compiling monthly sea level anomaly predictions from multiple statistical and dynamical (coupled ocean–atmosphere) models, which are typically skillful out to at least six months in the tropical Pacific, improved future outlooks are achieved. From this multimodel ensemble comes forecasts that are less prone to individual model errors and also uncertainty measurements achieved by comparing retrospective forecasts with the observed sea level. This framework delivers online a new real-time forecasting product of monthly mean sea level anomalies and will provide to the Pacific island community information that can be used to reduce impacts associated with sea level extremes.
Abstract
Observations from the Clouds and the Earth’s Radiant Energy System (CERES), Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) between 2000 and 2005 are analyzed in order to determine if these data are meeting climate accuracy goals recently established by the climate community. The focus is primarily on top-of-atmosphere (TOA) reflected solar radiances and radiative fluxes. Direct comparisons of nadir radiances from CERES, MODIS, and MISR aboard the Terra satellite reveal that the measurements from these instruments exhibit a year-to-year relative stability of better than 1%, with no systematic change with time. By comparison, the climate requirement for the stability of visible radiometer measurements is 1% decade−1. When tropical ocean monthly anomalies in shortwave (SW) TOA radiative fluxes from CERES on Terra are compared with anomalies in Photosynthetically Active Radiation (PAR) from SeaWiFS—an instrument whose radiance stability is better than 0.07% during its first six years in orbit—the two are strongly anticorrelated. After scaling the SeaWiFS anomalies by a constant factor given by the slope of the regression line fit between CERES and SeaWiFS anomalies, the standard deviation in the difference between monthly anomalies from the two records is only 0.2 W m−2, and the difference in their trend lines is only 0.02 ± 0.3 W m−2 decade−1, approximately within the 0.3 W m−2 decade−1 stability requirement for climate accuracy. For both the Tropics and globe, CERES Terra SW TOA fluxes show no trend between March 2000 and June 2005. Significant differences are found between SW TOA flux trends from CERES Terra and CERES Aqua between August 2002 and March 2005. This discrepancy is due to uncertainties in the adjustment factors used to account for degradation of the CERES Aqua optics during hemispheric scan mode operations. Comparisons of SW TOA flux between CERES Terra and the International Satellite Cloud Climatology Project (ISCCP) radiative flux profile dataset (FD) RadFlux product show good agreement in monthly anomalies between January 2002 and December 2004, and poor agreement prior to this period. Commonly used statistical tools applied to the CERES Terra data reveal that in order to detect a statistically significant trend of magnitude 0.3 W m−2 decade−1 in global SW TOA flux, approximately 10 to 15 yr of data are needed. This assumes that CERES Terra instrument calibration remains highly stable, long-term climate variability remains constant, and the Terra spacecraft has enough fuel to last 15 yr.
Abstract
Observations from the Clouds and the Earth’s Radiant Energy System (CERES), Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) between 2000 and 2005 are analyzed in order to determine if these data are meeting climate accuracy goals recently established by the climate community. The focus is primarily on top-of-atmosphere (TOA) reflected solar radiances and radiative fluxes. Direct comparisons of nadir radiances from CERES, MODIS, and MISR aboard the Terra satellite reveal that the measurements from these instruments exhibit a year-to-year relative stability of better than 1%, with no systematic change with time. By comparison, the climate requirement for the stability of visible radiometer measurements is 1% decade−1. When tropical ocean monthly anomalies in shortwave (SW) TOA radiative fluxes from CERES on Terra are compared with anomalies in Photosynthetically Active Radiation (PAR) from SeaWiFS—an instrument whose radiance stability is better than 0.07% during its first six years in orbit—the two are strongly anticorrelated. After scaling the SeaWiFS anomalies by a constant factor given by the slope of the regression line fit between CERES and SeaWiFS anomalies, the standard deviation in the difference between monthly anomalies from the two records is only 0.2 W m−2, and the difference in their trend lines is only 0.02 ± 0.3 W m−2 decade−1, approximately within the 0.3 W m−2 decade−1 stability requirement for climate accuracy. For both the Tropics and globe, CERES Terra SW TOA fluxes show no trend between March 2000 and June 2005. Significant differences are found between SW TOA flux trends from CERES Terra and CERES Aqua between August 2002 and March 2005. This discrepancy is due to uncertainties in the adjustment factors used to account for degradation of the CERES Aqua optics during hemispheric scan mode operations. Comparisons of SW TOA flux between CERES Terra and the International Satellite Cloud Climatology Project (ISCCP) radiative flux profile dataset (FD) RadFlux product show good agreement in monthly anomalies between January 2002 and December 2004, and poor agreement prior to this period. Commonly used statistical tools applied to the CERES Terra data reveal that in order to detect a statistically significant trend of magnitude 0.3 W m−2 decade−1 in global SW TOA flux, approximately 10 to 15 yr of data are needed. This assumes that CERES Terra instrument calibration remains highly stable, long-term climate variability remains constant, and the Terra spacecraft has enough fuel to last 15 yr.
Abstract
No abstract available.
Abstract
No abstract available.
Abstract
A vertical array of acoustic current meters measures the vector flow field in the lowest 5 m of the oceanic boundary layer. By resolving the velocity to 0.03 cm s−1 over 15 cm paths, it samples the dominant turbulent eddies responsible for Reynolds stress to within 50 cm of the bottom. Profiles through the inner boundary layer, from six sensor pods, of velocity, turbulent kinetic energy, and Reynolds stress can be recorded for up 10 four months with a 2 Hz sample rate and 20 min averaging interval. We can study flow structure and spectra from as many as four event-triggered recordings of unaveraged samples, each lasting one hour, during periods of intense sediment transport. Acoustic transducer multiplexing permits 24 axes to be interfaced to a single receiving circuit. Electrical reversal of transducers in each axis eliminates zero drift. A deep-sea tripod supports the sensor array rigidly with minimum flow disturbance, yet releases on command for free vehicle recovery.
Abstract
A vertical array of acoustic current meters measures the vector flow field in the lowest 5 m of the oceanic boundary layer. By resolving the velocity to 0.03 cm s−1 over 15 cm paths, it samples the dominant turbulent eddies responsible for Reynolds stress to within 50 cm of the bottom. Profiles through the inner boundary layer, from six sensor pods, of velocity, turbulent kinetic energy, and Reynolds stress can be recorded for up 10 four months with a 2 Hz sample rate and 20 min averaging interval. We can study flow structure and spectra from as many as four event-triggered recordings of unaveraged samples, each lasting one hour, during periods of intense sediment transport. Acoustic transducer multiplexing permits 24 axes to be interfaced to a single receiving circuit. Electrical reversal of transducers in each axis eliminates zero drift. A deep-sea tripod supports the sensor array rigidly with minimum flow disturbance, yet releases on command for free vehicle recovery.
The year 2012 marks a decade of observations undertaken by the U.S. Climate Reference Network (USCRN) under the auspices of NOAA's National Climatic Data Center and Atmospheric Turbulence and Diffusion Division. The network consists of 114 sites across the conterminous 48 states, with additional sites in Alaska and Hawaii. Stations are installed in open (where possible), rural sites very likely to have stable land-cover/use conditions for several decades to come. At each site a suite of meteorological parameters are monitored, including triple redundancy for the primary air temperature and precipitation variables and for soil moisture/temperature. Instrumentation is regularly calibrated to National Institute for Standards and Technology (NIST) standards and maintained by a staff of expert engineers. This attention to detail in USCRN is intended to ensure the creation of an unimpeachable record of changes in surface climate over the United States for decades to come. Data are made available without restriction for all public, private, and government use. This article describes the rationale for the USCRN, its implementation, and some of the highlights of the first decade of operations. One critical use of these observations is as an independent data source to verify the existing U.S. temperature record derived from networks corrected for nonhomogenous histories. Future directions for the network are also discussed, including the applicability of USCRN approaches for networks monitoring climate at scales from regional to global. Constructive feedback from end users will allow for continued improvement of USCRN in the future and ensure that it continues to meet stakeholder requirements for precise climate measurements.
The year 2012 marks a decade of observations undertaken by the U.S. Climate Reference Network (USCRN) under the auspices of NOAA's National Climatic Data Center and Atmospheric Turbulence and Diffusion Division. The network consists of 114 sites across the conterminous 48 states, with additional sites in Alaska and Hawaii. Stations are installed in open (where possible), rural sites very likely to have stable land-cover/use conditions for several decades to come. At each site a suite of meteorological parameters are monitored, including triple redundancy for the primary air temperature and precipitation variables and for soil moisture/temperature. Instrumentation is regularly calibrated to National Institute for Standards and Technology (NIST) standards and maintained by a staff of expert engineers. This attention to detail in USCRN is intended to ensure the creation of an unimpeachable record of changes in surface climate over the United States for decades to come. Data are made available without restriction for all public, private, and government use. This article describes the rationale for the USCRN, its implementation, and some of the highlights of the first decade of operations. One critical use of these observations is as an independent data source to verify the existing U.S. temperature record derived from networks corrected for nonhomogenous histories. Future directions for the network are also discussed, including the applicability of USCRN approaches for networks monitoring climate at scales from regional to global. Constructive feedback from end users will allow for continued improvement of USCRN in the future and ensure that it continues to meet stakeholder requirements for precise climate measurements.