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Estimating Profiles of Dissipation Rate in the Upper Ocean Using Acoustic Doppler Measurements Made from Surface-Following PlatformsAbstract
High-resolution profiles of vertical velocity obtained from two different surface-following autonomous platforms, Surface Wave Instrument Floats with Tracking (SWIFTs) and a Liquid Robotics SV3 Wave Glider, are used to compute dissipation rate profiles ϵ(z) between 0.5 and 5 m depth via the structure function method. The main contribution of this work is to update previous SWIFT methods to account for bias due to surface gravity waves, which are ubiquitous in the near-surface region. We present a technique where the data are prefiltered by removing profiles of wave orbital velocities obtained via empirical orthogonal function (EOF) analysis of the data prior to computing the structure function. Our analysis builds on previous work to remove wave bias in which analytic modifications are made to the structure function model. However, we find the analytic approach less able to resolve the strong vertical gradients in ϵ(z) near the surface. The strength of the EOF filtering technique is that it does not require any assumptions about the structure of nonturbulent shear, and does not add any additional degrees of freedom in the least squares fit to the model of the structure function. In comparison to the analytic method, ϵ(z) estimates obtained via empirical filtering have substantially reduced noise and a clearer dependence on near-surface wind speed.
Abstract
High-resolution profiles of vertical velocity obtained from two different surface-following autonomous platforms, Surface Wave Instrument Floats with Tracking (SWIFTs) and a Liquid Robotics SV3 Wave Glider, are used to compute dissipation rate profiles ϵ(z) between 0.5 and 5 m depth via the structure function method. The main contribution of this work is to update previous SWIFT methods to account for bias due to surface gravity waves, which are ubiquitous in the near-surface region. We present a technique where the data are prefiltered by removing profiles of wave orbital velocities obtained via empirical orthogonal function (EOF) analysis of the data prior to computing the structure function. Our analysis builds on previous work to remove wave bias in which analytic modifications are made to the structure function model. However, we find the analytic approach less able to resolve the strong vertical gradients in ϵ(z) near the surface. The strength of the EOF filtering technique is that it does not require any assumptions about the structure of nonturbulent shear, and does not add any additional degrees of freedom in the least squares fit to the model of the structure function. In comparison to the analytic method, ϵ(z) estimates obtained via empirical filtering have substantially reduced noise and a clearer dependence on near-surface wind speed.
Abstract
The Pacific Equatorial Undercurrent (EUC) flows eastward across the Pacific at the equator in the thermocline. Its variability is related to El Niño. Moored acoustic Doppler current profiler (ADCP) measurements recorded at four widely separated sites along the equator in the EUC were compared to currents generated by version 4 release 4 of the Estimating the Circulation and Climate of the Ocean (ECCOv4r4) global model–data synthesis product. We are interested to learn how well ECCOv4r4 currents could complement sparse in situ current measurements. ADCP measurements were not assimilated in ECCOv4r4. Comparisons occurred at 5-m depth intervals at 165°E, 170°W, 140°W, and 110°W over time intervals of 10–14 years from 1995 to 2010. Hourly values of ECCOv4r4 and ADCP EUC core speeds were strongly correlated, similar for the EUC transport per unit width (TPUW). Correlations were substantially weaker at 110°W. Although we expected means and standard deviations of ECCOv4r4 currents to be smaller than ADCP values because of ECCOv4r4’s grid representation error, the large differences were unforeseen. The appearance of ECCOv4r4 diurnal-period current oscillations was surprising. As the EUC moved eastward from 170° to 140°W, the ECCOv4r4 TPUW exhibited a much smaller increase compared to the ADCP TPUW. A consequence of smaller ECCOv4r4 EUC core speeds was significantly fewer instances of gradient Richardson number (Ri) less than 1/4 above and below the depth of the core speed compared to Ri computed with ADCP observations. We present linear regression analyses to use monthly-mean ECCOv4r4 EUC core speeds and TPUWs as proxies for ADCP measurements.
Significance Statement
Hundreds of scientific papers have used ECCO data products generated with a continually evolving state-of-the-art ocean-model–data synthesis system. We ask, How representative is the latest version of ECCO equatorial ocean currents? We use independent in situ current measurements as the reference dataset to establish the accuracy of ECCO currents in the tropical Pacific. Attention is focused on the Pacific Equatorial Undercurrent (EUC) because it contributes to the formation of El Niño and La Niña events. ECCO EUC core speeds were smaller in magnitude and less variable in time compared to observations. As a consequence, ECCO currents generated smaller vertical mixing in the EUC compared to that inferred from current measurements. We developed a linear regression model to improve representation of monthly-mean ECCO currents.
Abstract
The Pacific Equatorial Undercurrent (EUC) flows eastward across the Pacific at the equator in the thermocline. Its variability is related to El Niño. Moored acoustic Doppler current profiler (ADCP) measurements recorded at four widely separated sites along the equator in the EUC were compared to currents generated by version 4 release 4 of the Estimating the Circulation and Climate of the Ocean (ECCOv4r4) global model–data synthesis product. We are interested to learn how well ECCOv4r4 currents could complement sparse in situ current measurements. ADCP measurements were not assimilated in ECCOv4r4. Comparisons occurred at 5-m depth intervals at 165°E, 170°W, 140°W, and 110°W over time intervals of 10–14 years from 1995 to 2010. Hourly values of ECCOv4r4 and ADCP EUC core speeds were strongly correlated, similar for the EUC transport per unit width (TPUW). Correlations were substantially weaker at 110°W. Although we expected means and standard deviations of ECCOv4r4 currents to be smaller than ADCP values because of ECCOv4r4’s grid representation error, the large differences were unforeseen. The appearance of ECCOv4r4 diurnal-period current oscillations was surprising. As the EUC moved eastward from 170° to 140°W, the ECCOv4r4 TPUW exhibited a much smaller increase compared to the ADCP TPUW. A consequence of smaller ECCOv4r4 EUC core speeds was significantly fewer instances of gradient Richardson number (Ri) less than 1/4 above and below the depth of the core speed compared to Ri computed with ADCP observations. We present linear regression analyses to use monthly-mean ECCOv4r4 EUC core speeds and TPUWs as proxies for ADCP measurements.
Significance Statement
Hundreds of scientific papers have used ECCO data products generated with a continually evolving state-of-the-art ocean-model–data synthesis system. We ask, How representative is the latest version of ECCO equatorial ocean currents? We use independent in situ current measurements as the reference dataset to establish the accuracy of ECCO currents in the tropical Pacific. Attention is focused on the Pacific Equatorial Undercurrent (EUC) because it contributes to the formation of El Niño and La Niña events. ECCO EUC core speeds were smaller in magnitude and less variable in time compared to observations. As a consequence, ECCO currents generated smaller vertical mixing in the EUC compared to that inferred from current measurements. We developed a linear regression model to improve representation of monthly-mean ECCO currents.
Airborne Radar Doppler Spectrum Width as a Scale-Dependent Turbulence MetricAbstract
High-resolution airborne cloud Doppler radars such as the W-band Wyoming Cloud Radar (WCR) have, since the 1990s, investigated cloud microphysical, kinematic, and precipitation structures down to 30-m resolution. These measurements revolutionized our understanding of fine-scale cloud structure and the scales at which cloud processes occur. Airborne cloud Doppler radars may also resolve cloud turbulent eddy structure directly at 10-m scales. To date, cloud turbulence has been examined as variances and dissipation rates at coarser resolution than individual pulse volumes. The present work advances the potential of near-vertical pulse-pair Doppler spectrum width as a metric for turbulent air motion. Doppler spectrum width has long been used to investigate turbulent motions from ground-based remote sensors. However, complexities of airborne Doppler radar and spectral broadening resulting from platform and hydrometeor motions have limited airborne radar spectrum width measurements to qualitative interpretation only. Here we present the first quantitative validation of spectrum width from an airborne cloud radar. Echoes with signal-to-noise ratio greater than 10 dB yield spectrum width values that strongly correlate with retrieved mean Doppler variance for a range of nonconvective cloud conditions. Further, Doppler spectrum width within turbulent regions of cloud also shows good agreement with in situ eddy dissipation rate (EDR) and gust probe variance. However, the use of pulse-pair estimated spectrum width as a metric for turbulent air motion intensity is only suitable for turbulent air motions more energetic than the magnitude of spectral broadening, estimated to be <0.4 m s−1 for the WCR in these cases.
Significance Statement
Doppler spectrum width is a widely available airborne radar measurement previously considered too uncertain to attribute to atmospheric turbulence. We validate, for the first time, the response of spectrum width to turbulence at and away from research aircraft flight level and demonstrate that under certain conditions, spectrum width can be used to diagnose atmospheric turbulence down to scales of tens of meters. These high-resolution turbulent air motion intensity measurements may better connect to cloud hydrometeor process and growth response seen in coincident radar reflectivity structures proximate to turbulent eddies.
Abstract
High-resolution airborne cloud Doppler radars such as the W-band Wyoming Cloud Radar (WCR) have, since the 1990s, investigated cloud microphysical, kinematic, and precipitation structures down to 30-m resolution. These measurements revolutionized our understanding of fine-scale cloud structure and the scales at which cloud processes occur. Airborne cloud Doppler radars may also resolve cloud turbulent eddy structure directly at 10-m scales. To date, cloud turbulence has been examined as variances and dissipation rates at coarser resolution than individual pulse volumes. The present work advances the potential of near-vertical pulse-pair Doppler spectrum width as a metric for turbulent air motion. Doppler spectrum width has long been used to investigate turbulent motions from ground-based remote sensors. However, complexities of airborne Doppler radar and spectral broadening resulting from platform and hydrometeor motions have limited airborne radar spectrum width measurements to qualitative interpretation only. Here we present the first quantitative validation of spectrum width from an airborne cloud radar. Echoes with signal-to-noise ratio greater than 10 dB yield spectrum width values that strongly correlate with retrieved mean Doppler variance for a range of nonconvective cloud conditions. Further, Doppler spectrum width within turbulent regions of cloud also shows good agreement with in situ eddy dissipation rate (EDR) and gust probe variance. However, the use of pulse-pair estimated spectrum width as a metric for turbulent air motion intensity is only suitable for turbulent air motions more energetic than the magnitude of spectral broadening, estimated to be <0.4 m s−1 for the WCR in these cases.
Significance Statement
Doppler spectrum width is a widely available airborne radar measurement previously considered too uncertain to attribute to atmospheric turbulence. We validate, for the first time, the response of spectrum width to turbulence at and away from research aircraft flight level and demonstrate that under certain conditions, spectrum width can be used to diagnose atmospheric turbulence down to scales of tens of meters. These high-resolution turbulent air motion intensity measurements may better connect to cloud hydrometeor process and growth response seen in coincident radar reflectivity structures proximate to turbulent eddies.
Multisensor Agile Adaptive Sampling (MAAS): A Methodology to Collect Radar Observations of Convective Cell Life CycleAbstract
Multisensor Agile Adaptive Sampling (MAAS), a smart sensing framework, was adapted to increase the likelihood of observing the vertical structure (with little to no gaps), spatial variability (at subkilometer scale), and temporal evolution (at ∼2-min resolution) of convective cells. This adaptation of MAAS guided two mechanically scanning C-band radars (CSAPR2 and CHIVO) by automatically analyzing the latest NEXRAD data to identify, characterize, track, and nowcast the location of all convective cells forming in the Houston domain. MAAS used either a list of predetermined rules or real-time user input to select a convective cell to be tracked and sampled by the C-band radars. The CSAPR2 tracking radar was first tasked to collect three sector plan position indicator (PPI) scans toward the selected cell. Edge computer processing of the PPI scans was used to identify additional targets within the selected cell. In less than 2 min, both the CSAPR2 and CHIVO radars were able to collect bundles of three to six range–height indicator (RHI) scans toward different targets of interest within the selected cell. Bundles were successively collected along the path of cell advection for as long as the cell met a predetermined set of criteria. Between 1 June and 30 September 2022 over 315 000 vertical cross-section observations were collected by the C-band radars through ∼1300 unique isolated convective cells, most of which were observed for over 15 min of their life cycle. To the best of our knowledge, this dataset, collected primarily through automatic means, constitutes the largest dataset of its kind.
Abstract
Multisensor Agile Adaptive Sampling (MAAS), a smart sensing framework, was adapted to increase the likelihood of observing the vertical structure (with little to no gaps), spatial variability (at subkilometer scale), and temporal evolution (at ∼2-min resolution) of convective cells. This adaptation of MAAS guided two mechanically scanning C-band radars (CSAPR2 and CHIVO) by automatically analyzing the latest NEXRAD data to identify, characterize, track, and nowcast the location of all convective cells forming in the Houston domain. MAAS used either a list of predetermined rules or real-time user input to select a convective cell to be tracked and sampled by the C-band radars. The CSAPR2 tracking radar was first tasked to collect three sector plan position indicator (PPI) scans toward the selected cell. Edge computer processing of the PPI scans was used to identify additional targets within the selected cell. In less than 2 min, both the CSAPR2 and CHIVO radars were able to collect bundles of three to six range–height indicator (RHI) scans toward different targets of interest within the selected cell. Bundles were successively collected along the path of cell advection for as long as the cell met a predetermined set of criteria. Between 1 June and 30 September 2022 over 315 000 vertical cross-section observations were collected by the C-band radars through ∼1300 unique isolated convective cells, most of which were observed for over 15 min of their life cycle. To the best of our knowledge, this dataset, collected primarily through automatic means, constitutes the largest dataset of its kind.
Abstract
The third edition of the CM SAF Cloud, Albedo and Surface Radiation dataset from AVHRR data (CLARA-A3) contains for the first time the top-of-atmosphere products reflected solar flux (RSF) and outgoing longwave radiation (OLR), which are presented and validated using CERES, HIRS, and ERA5 reference data. The products feature an unprecedented resolution (0.25°) and time span (4 decades) and offer synergy and compatibility with other CLARA-A3 products. The RSF is relatively stable; its bias with respect to (w.r.t.) ERA5 remains mostly within ±2 W m−2. Deviations are predominantly caused by absence of either morning or afternoon satellite, mostly during the first decade. The radiative impact of the Pinatubo volcanic eruption is estimated at 3 W m−2. The OLR is stable w.r.t. ERA5 and HIRS, except during 1979–80. OLR regional uncertainty w.r.t. HIRS is quantified by the mean absolute bias (MAB) and correlates with observation density and time (satellite orbital configuration), which is optimal during 2002–16, with monthly and daily MAB of approximately 1.5 and 3.5 W m−2, respectively. Daily OLR uncertainty is higher (MAB +40%) during periods with only morning or only afternoon observations (1979–87). During the CERES era (2000–20), the OLR uncertainties w.r.t. CERES-EBAF, CERES-SYN, and HIRS are very similar. The RSF uncertainty achieves optimal results during 2002–16 with a monthly MAB w.r.t. CERES-EBAF of ∼2 W m−2 and a daily MAB w.r.t. CERES-SYN of ∼5 W m−2, and it is more sensitive to orbital configuration than is OLR. Overall, validation results are satisfactory for this first release of TOA flux products in the CLARA-A3 portfolio.
Abstract
The third edition of the CM SAF Cloud, Albedo and Surface Radiation dataset from AVHRR data (CLARA-A3) contains for the first time the top-of-atmosphere products reflected solar flux (RSF) and outgoing longwave radiation (OLR), which are presented and validated using CERES, HIRS, and ERA5 reference data. The products feature an unprecedented resolution (0.25°) and time span (4 decades) and offer synergy and compatibility with other CLARA-A3 products. The RSF is relatively stable; its bias with respect to (w.r.t.) ERA5 remains mostly within ±2 W m−2. Deviations are predominantly caused by absence of either morning or afternoon satellite, mostly during the first decade. The radiative impact of the Pinatubo volcanic eruption is estimated at 3 W m−2. The OLR is stable w.r.t. ERA5 and HIRS, except during 1979–80. OLR regional uncertainty w.r.t. HIRS is quantified by the mean absolute bias (MAB) and correlates with observation density and time (satellite orbital configuration), which is optimal during 2002–16, with monthly and daily MAB of approximately 1.5 and 3.5 W m−2, respectively. Daily OLR uncertainty is higher (MAB +40%) during periods with only morning or only afternoon observations (1979–87). During the CERES era (2000–20), the OLR uncertainties w.r.t. CERES-EBAF, CERES-SYN, and HIRS are very similar. The RSF uncertainty achieves optimal results during 2002–16 with a monthly MAB w.r.t. CERES-EBAF of ∼2 W m−2 and a daily MAB w.r.t. CERES-SYN of ∼5 W m−2, and it is more sensitive to orbital configuration than is OLR. Overall, validation results are satisfactory for this first release of TOA flux products in the CLARA-A3 portfolio.
Swish Floats: An Inexpensive Neutrally Buoyant Float to Monitor Dispersion in Coastal SeasAbstract
Neutrally buoyant floats have been widely used to measure flows in the ocean, but deploying them in large numbers can be costly and impractical. This is particularly true near coastlines due to the elevated risk of instrument grounding or vessel collisions, resulting in a lack of subsurface Lagrangian measurements in coastal regions. Here, we describe an inexpensive neutrally buoyant satellite-tracked float (named “Swallow-ish,” or “Swish” floats) that has been designed and tested as a cost-effective strategy to measure subsurface dispersion in coastal areas on time scales up to a month. These autonomous instruments are inexpensive, constructed at a material cost of CAD $300 per unit; lightweight, with a mass of 5.4 kg; isopycnal; and constructed from commercially available components, using recently available global navigation satellite system technology to provide the user with a point-to-point measure of subsurface transport. We describe the float design, ballasting techniques, and the governing equations that determine their behavior. Further, through 29 deployments in two coastal seas, we calculate an uncertainty budget and determine a ballasting error of ±1.6 g, corresponding to a local depth targeting error of 16–30 m, analyze the float resurfacing data to calculate subsurface dispersion coefficients, and examine the float depth records to quantify the local internal wave field. Finally, we evaluate surface dispersion using the postresurfacing trajectories. Our findings indicate that Swish floats offer a cost-effective alternative for Lagrangian measurements of subsurface flows in coastal regions.
Abstract
Neutrally buoyant floats have been widely used to measure flows in the ocean, but deploying them in large numbers can be costly and impractical. This is particularly true near coastlines due to the elevated risk of instrument grounding or vessel collisions, resulting in a lack of subsurface Lagrangian measurements in coastal regions. Here, we describe an inexpensive neutrally buoyant satellite-tracked float (named “Swallow-ish,” or “Swish” floats) that has been designed and tested as a cost-effective strategy to measure subsurface dispersion in coastal areas on time scales up to a month. These autonomous instruments are inexpensive, constructed at a material cost of CAD $300 per unit; lightweight, with a mass of 5.4 kg; isopycnal; and constructed from commercially available components, using recently available global navigation satellite system technology to provide the user with a point-to-point measure of subsurface transport. We describe the float design, ballasting techniques, and the governing equations that determine their behavior. Further, through 29 deployments in two coastal seas, we calculate an uncertainty budget and determine a ballasting error of ±1.6 g, corresponding to a local depth targeting error of 16–30 m, analyze the float resurfacing data to calculate subsurface dispersion coefficients, and examine the float depth records to quantify the local internal wave field. Finally, we evaluate surface dispersion using the postresurfacing trajectories. Our findings indicate that Swish floats offer a cost-effective alternative for Lagrangian measurements of subsurface flows in coastal regions.
Abstract
Small uncrewed aircraft systems (sUAS) are regularly being used to conduct atmospheric research and are starting to be used as a data source for informing weather models through data assimilation. However, only a limited number of studies have been conducted to evaluate the performance of these systems and assess their ability to replicate measurements from more traditional sensors such as radiosondes and towers. In the current work, we use data collected in central Oklahoma over a 2-week period to offer insight into the performance of five different sUAS platforms and associated sensors in measuring key weather data. This includes data from three rotary-wing and two fixed-wing sUAS and included two commercially-available systems and three university-developed research systems. Flight data were compared to regular radiosondes launched at the flight location, tower observations, and intercompared with data from other sUAS platforms. All platforms were shown to measure atmospheric state with reasonable accuracy, though there were some consistent biases detected for individual platforms. This information can be used to inform future studies using these platforms and is currently being used to provide estimated error covariances as required in support of assimilation of sUAS data into weather forecasting systems.
Abstract
Small uncrewed aircraft systems (sUAS) are regularly being used to conduct atmospheric research and are starting to be used as a data source for informing weather models through data assimilation. However, only a limited number of studies have been conducted to evaluate the performance of these systems and assess their ability to replicate measurements from more traditional sensors such as radiosondes and towers. In the current work, we use data collected in central Oklahoma over a 2-week period to offer insight into the performance of five different sUAS platforms and associated sensors in measuring key weather data. This includes data from three rotary-wing and two fixed-wing sUAS and included two commercially-available systems and three university-developed research systems. Flight data were compared to regular radiosondes launched at the flight location, tower observations, and intercompared with data from other sUAS platforms. All platforms were shown to measure atmospheric state with reasonable accuracy, though there were some consistent biases detected for individual platforms. This information can be used to inform future studies using these platforms and is currently being used to provide estimated error covariances as required in support of assimilation of sUAS data into weather forecasting systems.
Abstract
We present a new global oxygen atlas. This atlas uses all of the available full water column profiles of oxygen, salinity, and temperature available as part of the World Ocean Database released in 2018. Instead of optimal interpolation, we use the Data Interpolating Variational Analysis (DIVA) approach to map the available profiles onto 108 depth levels between the surface and 6800 m, covering more than 99% of ocean volume. This 1/2° × 1/2° atlas covers the period 1955–2018 in 1-yr intervals. The DIVA method has significant benefits over traditional optimal interpolation. It allows the explicit inclusion of advection and boundary constraints, thus offering improvements in the representations of oxygen, salinity, and temperature in regions of strong flow and near coastal boundaries. We demonstrate these benefits of this mapping approach with some examples from this atlas. We can explore the regional and temporal variations of oxygen in the global oceans. Preliminary analyses confirm earlier analyses that the oxygen minimum zone in the eastern Pacific Ocean has expanded and intensified. Oxygen inventory changes between 1970 and 2010 are assessed and compared against prior studies. We find that the full ocean oxygen inventory decreased by 0.84% ± 0.42%. For this period, temperature-driven solubility changes explain about 21% of the oxygen decline over the full water column; in the upper 100 m, solubility changes can explain all of the oxygen decrease; for the 100–600 m depth range, it can explain only 29%, 19% between 600 and 1000 m, and just 11% in the deep ocean.
Significance Statement
The purpose of this study is to create a new oxygen atlas of the world’s oceans using a technique that better represents the effects of ocean currents and topographic boundaries, and to investigate how oxygen in the ocean has changed over recent decades. We find the total quantity of oxygen in the world’s oceans has decreased by 0.84% since 1970, similar to previous studies. We also examine how much of this change can be explained by changes in water temperature; we find that this can explain all the changes in the upper 100 m but only 21% of the oxygen decline over the whole water column.
Abstract
We present a new global oxygen atlas. This atlas uses all of the available full water column profiles of oxygen, salinity, and temperature available as part of the World Ocean Database released in 2018. Instead of optimal interpolation, we use the Data Interpolating Variational Analysis (DIVA) approach to map the available profiles onto 108 depth levels between the surface and 6800 m, covering more than 99% of ocean volume. This 1/2° × 1/2° atlas covers the period 1955–2018 in 1-yr intervals. The DIVA method has significant benefits over traditional optimal interpolation. It allows the explicit inclusion of advection and boundary constraints, thus offering improvements in the representations of oxygen, salinity, and temperature in regions of strong flow and near coastal boundaries. We demonstrate these benefits of this mapping approach with some examples from this atlas. We can explore the regional and temporal variations of oxygen in the global oceans. Preliminary analyses confirm earlier analyses that the oxygen minimum zone in the eastern Pacific Ocean has expanded and intensified. Oxygen inventory changes between 1970 and 2010 are assessed and compared against prior studies. We find that the full ocean oxygen inventory decreased by 0.84% ± 0.42%. For this period, temperature-driven solubility changes explain about 21% of the oxygen decline over the full water column; in the upper 100 m, solubility changes can explain all of the oxygen decrease; for the 100–600 m depth range, it can explain only 29%, 19% between 600 and 1000 m, and just 11% in the deep ocean.
Significance Statement
The purpose of this study is to create a new oxygen atlas of the world’s oceans using a technique that better represents the effects of ocean currents and topographic boundaries, and to investigate how oxygen in the ocean has changed over recent decades. We find the total quantity of oxygen in the world’s oceans has decreased by 0.84% since 1970, similar to previous studies. We also examine how much of this change can be explained by changes in water temperature; we find that this can explain all the changes in the upper 100 m but only 21% of the oxygen decline over the whole water column.
Abstract
Estimation of uncertainties (random error statistics) of radio occultation (RO) observations is important for their effective assimilation in numerical weather prediction (NWP) models. Average uncertainties can be estimated for large samples of RO observations and these statistics may be used for specifying the observation errors in NWP data assimilation. However, the uncertainties of individual RO observations vary, and so using average uncertainty estimates will overestimate the uncertainties of some observations and underestimate those of others, reducing their overall effectiveness in the assimilation. Several parameters associated with RO observations or their atmospheric environments have been proposed to estimate individual RO errors. These include the standard deviation of bending angle (BA) departures from either climatology in the upper stratosphere and lower mesosphere (STDV) or the sample mean between 40 and 60 km (STD4060), the local spectral width (LSW), and the magnitude of the horizontal gradient of refractivity (|∇ HN|). In this paper we show how the uncertainties of two RO datasets, COSMIC-2 and Spire BA, as well as their combination, vary with these parameters. We find that the uncertainties are highly correlated with STDV and STD4060 in the stratosphere, and with LSW and |∇ HN| in the lower troposphere. These results suggest a hybrid error model for individual BA observations that uses an average statistical model of RO errors modified by STDV or STD4060 above 30 km, and LSW or |∇ HN| below 8 km.
Significance Statement
These results contribute to the understanding of the sources of uncertainties in radio occultation observations. They could be used to improve the effectiveness of these observations in their assimilation into numerical weather prediction and reanalysis models by improving the estimation of their observational errors.
Abstract
Estimation of uncertainties (random error statistics) of radio occultation (RO) observations is important for their effective assimilation in numerical weather prediction (NWP) models. Average uncertainties can be estimated for large samples of RO observations and these statistics may be used for specifying the observation errors in NWP data assimilation. However, the uncertainties of individual RO observations vary, and so using average uncertainty estimates will overestimate the uncertainties of some observations and underestimate those of others, reducing their overall effectiveness in the assimilation. Several parameters associated with RO observations or their atmospheric environments have been proposed to estimate individual RO errors. These include the standard deviation of bending angle (BA) departures from either climatology in the upper stratosphere and lower mesosphere (STDV) or the sample mean between 40 and 60 km (STD4060), the local spectral width (LSW), and the magnitude of the horizontal gradient of refractivity (|∇ HN|). In this paper we show how the uncertainties of two RO datasets, COSMIC-2 and Spire BA, as well as their combination, vary with these parameters. We find that the uncertainties are highly correlated with STDV and STD4060 in the stratosphere, and with LSW and |∇ HN| in the lower troposphere. These results suggest a hybrid error model for individual BA observations that uses an average statistical model of RO errors modified by STDV or STD4060 above 30 km, and LSW or |∇ HN| below 8 km.
Significance Statement
These results contribute to the understanding of the sources of uncertainties in radio occultation observations. They could be used to improve the effectiveness of these observations in their assimilation into numerical weather prediction and reanalysis models by improving the estimation of their observational errors.
