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Abstract
Use of horizontal diffusion of temperature and salinity in numerical ocean models causes spurious diapycnal transfers—the “Veronis effect”—leading to erosion of the thermocline and reduced poleward heat transports. The authors derive a relation between these diapycnal transfers and the dissipation of vorticity gradients. An increase in model resolution does not significantly reduce the diapycnal transfers since vorticity gradients cascade to smaller scales and must ultimately be dissipated to maintain numerical stability. This is confirmed in an idealized primitive equation ocean model at a variety of resolutions between 1° and 1/8°.
Thus, the authors conclude that adiabatic dissipation schemes are required, even in eddy-resolving ocean models. The authors propose and implement a new biharmonic form of the Gent and McWilliams scheme, which adiabatically dissipates at the grid scale while preserving larger-scale features.
Abstract
Use of horizontal diffusion of temperature and salinity in numerical ocean models causes spurious diapycnal transfers—the “Veronis effect”—leading to erosion of the thermocline and reduced poleward heat transports. The authors derive a relation between these diapycnal transfers and the dissipation of vorticity gradients. An increase in model resolution does not significantly reduce the diapycnal transfers since vorticity gradients cascade to smaller scales and must ultimately be dissipated to maintain numerical stability. This is confirmed in an idealized primitive equation ocean model at a variety of resolutions between 1° and 1/8°.
Thus, the authors conclude that adiabatic dissipation schemes are required, even in eddy-resolving ocean models. The authors propose and implement a new biharmonic form of the Gent and McWilliams scheme, which adiabatically dissipates at the grid scale while preserving larger-scale features.
Vertical Atmospheric Structures Associated with Positive Biases in COSMIC-2 Refractivity RetrievalsAbstract
Representation of complex vertical structures observed in the troposphere can vary depending on data sources. The radio occultation (RO) technique offers great advantages for sensing the atmosphere down to its lowermost layers using high-resolution measurements collected by satellites on low-Earth orbit (LEO). The structures are generally smoother in vertical when reproduced from atmospheric models. We evaluate the quality of troposphere retrievals from the COSMIC-2 mission and demonstrate that systematic effects in fractional refractivity deviations with respect to European Centre for Medium-Range Weather Forecasts (ECMWF) background fields are spatially correlated with positive refractivity gradients characterized as subrefraction. The magnitude of refractivity biases observed mostly over the equatorial regions can exceed 1% within altitudes of 3–5 km. Respective zonal means reveal seasonal trends linked with the distribution of atmospheric inversion layers and signal-to-noise ratio values in RO data. The positive biases are vertically collocated with significant refractivity gradients in COSMIC-2 retrievals that are not reflected in the corresponding ECMWF profiles. The analysis of gradients based on COSMIC-2 data, further supported by radiosonde observations, suggests that most of subrefractions is identified in the middle troposphere at around 4 km. While the altitudes of maximum refractivity gradients from COSMIC-2 and ECMWF data are in fairly good agreement, the magnitude of ECMWF gradients is significantly smaller and rarely exceeds positive values.
Abstract
Representation of complex vertical structures observed in the troposphere can vary depending on data sources. The radio occultation (RO) technique offers great advantages for sensing the atmosphere down to its lowermost layers using high-resolution measurements collected by satellites on low-Earth orbit (LEO). The structures are generally smoother in vertical when reproduced from atmospheric models. We evaluate the quality of troposphere retrievals from the COSMIC-2 mission and demonstrate that systematic effects in fractional refractivity deviations with respect to European Centre for Medium-Range Weather Forecasts (ECMWF) background fields are spatially correlated with positive refractivity gradients characterized as subrefraction. The magnitude of refractivity biases observed mostly over the equatorial regions can exceed 1% within altitudes of 3–5 km. Respective zonal means reveal seasonal trends linked with the distribution of atmospheric inversion layers and signal-to-noise ratio values in RO data. The positive biases are vertically collocated with significant refractivity gradients in COSMIC-2 retrievals that are not reflected in the corresponding ECMWF profiles. The analysis of gradients based on COSMIC-2 data, further supported by radiosonde observations, suggests that most of subrefractions is identified in the middle troposphere at around 4 km. While the altitudes of maximum refractivity gradients from COSMIC-2 and ECMWF data are in fairly good agreement, the magnitude of ECMWF gradients is significantly smaller and rarely exceeds positive values.
WHOI SDSL Data-Link Project—Ethernet Telemetry through Sea CablesAbstract
A data telemetry technique for communicating over standard oceanographic sea cables that achieves a nearly 100-fold increase in bandwidth as compared to traditional systems has been recently developed and successfully used at sea on board two Research Vessel (R/V) Atlantis cruises with an 8.5-km, 0.322-in.-diameter three-conductor sea cable. The system uses commercially available modules to provide Ethernet connectivity through existing sea cables, linking serial and video underwater instrumentation to the shipboard user. The new method applies Synchronous Digital Subscriber Line (SDSL) communications technology to undersea applications, greatly increasing the opportunities to use scientific instrumentation from existing ships and sea cables at minimal cost and without modification.
Abstract
A data telemetry technique for communicating over standard oceanographic sea cables that achieves a nearly 100-fold increase in bandwidth as compared to traditional systems has been recently developed and successfully used at sea on board two Research Vessel (R/V) Atlantis cruises with an 8.5-km, 0.322-in.-diameter three-conductor sea cable. The system uses commercially available modules to provide Ethernet connectivity through existing sea cables, linking serial and video underwater instrumentation to the shipboard user. The new method applies Synchronous Digital Subscriber Line (SDSL) communications technology to undersea applications, greatly increasing the opportunities to use scientific instrumentation from existing ships and sea cables at minimal cost and without modification.
Abstract
Observations of air and ground temperatures collected between 1993 and 2004 from Emigrant Pass Geothermal Climate Observatory in northwestern Utah are analyzed to understand the relationship between these two quantities. The influence of surface air temperature (SAT), incident solar radiation, and snow cover on surface ground temperature (SGT) variations are explored. SAT variations explain 94% of the variance in SGT. Incident solar radiation is the primary variable governing the remaining variance misfit and is significantly more important during summer months than winter months. A linear relationship between the ground–air temperature difference (ΔT sgt-sat) and solar radiation exists with a trend of 1.21 K/(100 W m−2); solar radiation accounts for 1.3% of the variance in SGT. The effects of incident solar radiation also account for the 2.47-K average offset in ΔT sgt-sat. During the winter, snow cover plays a role in governing SGT variability, but exerts only a minor influence on the annual tracking of ground and air temperatures at the site, accounting for 0.5% of the variance in SGT. These observations of the tracking of SGT and SAT confirm that borehole temperature changes mimic changes in SAT at frequencies appropriate for climatic reconstructions.
Abstract
Observations of air and ground temperatures collected between 1993 and 2004 from Emigrant Pass Geothermal Climate Observatory in northwestern Utah are analyzed to understand the relationship between these two quantities. The influence of surface air temperature (SAT), incident solar radiation, and snow cover on surface ground temperature (SGT) variations are explored. SAT variations explain 94% of the variance in SGT. Incident solar radiation is the primary variable governing the remaining variance misfit and is significantly more important during summer months than winter months. A linear relationship between the ground–air temperature difference (ΔT sgt-sat) and solar radiation exists with a trend of 1.21 K/(100 W m−2); solar radiation accounts for 1.3% of the variance in SGT. The effects of incident solar radiation also account for the 2.47-K average offset in ΔT sgt-sat. During the winter, snow cover plays a role in governing SGT variability, but exerts only a minor influence on the annual tracking of ground and air temperatures at the site, accounting for 0.5% of the variance in SGT. These observations of the tracking of SGT and SAT confirm that borehole temperature changes mimic changes in SAT at frequencies appropriate for climatic reconstructions.
Abstract
Recent drop size distribution data from four advection fog sites are reanalyzed for the purpose of predicting millimeter-wave and infrared to visible wavelength reflectivity and attenuation coefficients in such fogs. A gamma drop size distribution model is shown to be an adequate fit to measured distributions of typical fog drop diameters. Conclusions are drawn with respect to the relationships between the reflectivity and the attenuation to the liquid water content. A possible method is outlined for using ground-based measurement of liquid water content for the purpose of predicting arbitrary slant-path reflectivity and attenuation at the smaller wavelengths.
Abstract
Recent drop size distribution data from four advection fog sites are reanalyzed for the purpose of predicting millimeter-wave and infrared to visible wavelength reflectivity and attenuation coefficients in such fogs. A gamma drop size distribution model is shown to be an adequate fit to measured distributions of typical fog drop diameters. Conclusions are drawn with respect to the relationships between the reflectivity and the attenuation to the liquid water content. A possible method is outlined for using ground-based measurement of liquid water content for the purpose of predicting arbitrary slant-path reflectivity and attenuation at the smaller wavelengths.
Abstract
A set of model runs was made with the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3 (CCM3) to investigate and help assess the relative roles of snow cover anomalies and initial atmospheric states on the subsequent accumulation and ablation seasons. In order to elucidate the physical mechanisms responsible for the large impact in one case but small impact in the other, two experiments with CCM3 were made that imposed an exaggerated initial snow cover [1-m snow water equivalent (SWE)] over the western U.S. domain. One run was started on 1 December, the other on 1 February. These runs made it clear that the high albedo of snow was the dominant physical process. An additional set of runs with realistic yearly snow anomalies was also made. Results suggest that for runs starting in February (late winter), the initial prescription of snow cover is more important than the initial atmospheric state in determining the subsequent evolution of snow cover. For runs starting in December (early winter), the results are less clear, with neither the initial snow cover nor the initial state of the atmosphere appearing to be the dominant factor. In February, when the sun is relatively high in the sky and days are longer, the albedo effect is a dominant factor; while in December the sun was too low in the sky and days too short for the albedo effect to be important. As the winter season progressed, the subsequent accumulation of snow eliminated the effects of the initial December anomalies.
Abstract
A set of model runs was made with the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3 (CCM3) to investigate and help assess the relative roles of snow cover anomalies and initial atmospheric states on the subsequent accumulation and ablation seasons. In order to elucidate the physical mechanisms responsible for the large impact in one case but small impact in the other, two experiments with CCM3 were made that imposed an exaggerated initial snow cover [1-m snow water equivalent (SWE)] over the western U.S. domain. One run was started on 1 December, the other on 1 February. These runs made it clear that the high albedo of snow was the dominant physical process. An additional set of runs with realistic yearly snow anomalies was also made. Results suggest that for runs starting in February (late winter), the initial prescription of snow cover is more important than the initial atmospheric state in determining the subsequent evolution of snow cover. For runs starting in December (early winter), the results are less clear, with neither the initial snow cover nor the initial state of the atmosphere appearing to be the dominant factor. In February, when the sun is relatively high in the sky and days are longer, the albedo effect is a dominant factor; while in December the sun was too low in the sky and days too short for the albedo effect to be important. As the winter season progressed, the subsequent accumulation of snow eliminated the effects of the initial December anomalies.
Abstract
Radar ducting is caused by sharp vertical changes in temperature and, especially, water vapor at the top of the atmospheric boundary layer, both of which are sensitive to variations in the underlying surface conditions, local mesoscale weather, and synoptic weather patterns. High-resolution numerical weather prediction (NWP) models offer an alternative to observation to determine boundary layer (BL) structure and to assess the spatial variability of radar ducts. The benefit of using NWP models for simulating ducting conditions very much depends on the initial state of sea surface temperature (SST) and the model spinup time, both of which have a great impact on BL structure. This study investigates the effects of variation of NWP-model initial conditions and simulation length on the accuracy of simulating the atmosphere’s refractive index over the Wallops Island, Virginia, region, which has pronounced SST variability and complex BL structure. The Met Office Unified Model (MetUM) with horizontal resolution of 4 km (4-km model) was used to simulate the atmospheric environment when observations were made during the Wallops-2000 experiment. Sensitivity tests were conducted in terms of the variability of SST and model spinup time. The evaluation of the model results was focused on low-level moisture, temperature, and surface ducting characteristics including the frequency, strength, and the height of the ducting layer. When provided with more accurate SST and adequate simulation length, the MetUM 4-km model demonstrated an improved ability to predict the observed ducting.
Abstract
Radar ducting is caused by sharp vertical changes in temperature and, especially, water vapor at the top of the atmospheric boundary layer, both of which are sensitive to variations in the underlying surface conditions, local mesoscale weather, and synoptic weather patterns. High-resolution numerical weather prediction (NWP) models offer an alternative to observation to determine boundary layer (BL) structure and to assess the spatial variability of radar ducts. The benefit of using NWP models for simulating ducting conditions very much depends on the initial state of sea surface temperature (SST) and the model spinup time, both of which have a great impact on BL structure. This study investigates the effects of variation of NWP-model initial conditions and simulation length on the accuracy of simulating the atmosphere’s refractive index over the Wallops Island, Virginia, region, which has pronounced SST variability and complex BL structure. The Met Office Unified Model (MetUM) with horizontal resolution of 4 km (4-km model) was used to simulate the atmospheric environment when observations were made during the Wallops-2000 experiment. Sensitivity tests were conducted in terms of the variability of SST and model spinup time. The evaluation of the model results was focused on low-level moisture, temperature, and surface ducting characteristics including the frequency, strength, and the height of the ducting layer. When provided with more accurate SST and adequate simulation length, the MetUM 4-km model demonstrated an improved ability to predict the observed ducting.
Abstract
In this study four mesoscale forecasting systems were used to investigate the four-dimensional structure of atmospheric refractivity and ducting layers that occur within evolving synoptic conditions over the eastern seaboard of the United States. The aim of this study was to identify the most important components of forecasting systems that contribute to refractive structures simulated in a littoral environment. Over a 7-day period in April–May of 2000 near Wallops Island, Virginia, meteorological parameters at the ocean surface and within the marine atmospheric boundary layer (MABL) were measured to characterize the spatiotemporal variability contributing to ducting. By using traditional statistical metrics to gauge performance, the models were found to generally overpredict MABL moisture, resulting in fewer and weaker ducts than were diagnosed from vertical profile observations. Mesoscale features in ducting were linked to highly resolved sea surface temperature forcing and associated changes in surface stability and to local variations in internal boundary layers that developed during periods of offshore flow. Sensitivity tests that permit greater mesoscale detail to develop on the model grids revealed that initialization of the simulations and the resolution of sea surface temperature analyses were critical factors for accurate predictions of coastal refractivity.
Abstract
In this study four mesoscale forecasting systems were used to investigate the four-dimensional structure of atmospheric refractivity and ducting layers that occur within evolving synoptic conditions over the eastern seaboard of the United States. The aim of this study was to identify the most important components of forecasting systems that contribute to refractive structures simulated in a littoral environment. Over a 7-day period in April–May of 2000 near Wallops Island, Virginia, meteorological parameters at the ocean surface and within the marine atmospheric boundary layer (MABL) were measured to characterize the spatiotemporal variability contributing to ducting. By using traditional statistical metrics to gauge performance, the models were found to generally overpredict MABL moisture, resulting in fewer and weaker ducts than were diagnosed from vertical profile observations. Mesoscale features in ducting were linked to highly resolved sea surface temperature forcing and associated changes in surface stability and to local variations in internal boundary layers that developed during periods of offshore flow. Sensitivity tests that permit greater mesoscale detail to develop on the model grids revealed that initialization of the simulations and the resolution of sea surface temperature analyses were critical factors for accurate predictions of coastal refractivity.
Abstract
The local scale observation site (LSOS) is the smallest study site (0.8 ha) of the 2002/03 Cold Land Processes Experiment (CLPX) and is located within the Fraser mesocell study area. It was the most intensively measured site of the CLPX, and measurements here had the greatest temporal component of all CLPX sites. Measurements made at the LSOS were designed to produce a comprehensive assessment of the snow, soil, and vegetation characteristics viewed by the ground-based remote sensing instruments. The objective of the ground-based microwave remote sensing was to collect time series of active and passive microwave spectral signatures over snow, soil, and forest, which is coincident with the intensive physical characterization of these features. Ground-based remote sensing instruments included frequency modulated continuous wave (FMCW) radars operating over multiple microwave bandwidths; the Ground-Based Microwave Radiometer (GBMR-7) operating at channels 18.7, 23.8, 36.5, and 89 GHz; and in 2003, an L-, C-, X- and Ku-band scatterometer radar system. Snow and soil measurements included standard snow physical properties, snow wetness, snow depth transects, and soil moisture. The stem and canopy temperature and xylem sap flux of several trees were monitored continuously. Five micrometeorological towers monitored ambient conditions and provided forcing datasets for 1D snow and soil models. Arrays of pyranometers (0.3–3 μm) and a scanning thermal radiometer (8–12 μm) characterized the variability of radiative receipt in the forests. A field spectroradiometer measured the hyperspectral hemispherical-directional reflectance of the snow surface. These measurements, together with the ground-based remote sensing, provide the framework for evaluating and improving microwave radiative transfer models and coupling them to land surface models. The dataset is archived at the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado.
Abstract
The local scale observation site (LSOS) is the smallest study site (0.8 ha) of the 2002/03 Cold Land Processes Experiment (CLPX) and is located within the Fraser mesocell study area. It was the most intensively measured site of the CLPX, and measurements here had the greatest temporal component of all CLPX sites. Measurements made at the LSOS were designed to produce a comprehensive assessment of the snow, soil, and vegetation characteristics viewed by the ground-based remote sensing instruments. The objective of the ground-based microwave remote sensing was to collect time series of active and passive microwave spectral signatures over snow, soil, and forest, which is coincident with the intensive physical characterization of these features. Ground-based remote sensing instruments included frequency modulated continuous wave (FMCW) radars operating over multiple microwave bandwidths; the Ground-Based Microwave Radiometer (GBMR-7) operating at channels 18.7, 23.8, 36.5, and 89 GHz; and in 2003, an L-, C-, X- and Ku-band scatterometer radar system. Snow and soil measurements included standard snow physical properties, snow wetness, snow depth transects, and soil moisture. The stem and canopy temperature and xylem sap flux of several trees were monitored continuously. Five micrometeorological towers monitored ambient conditions and provided forcing datasets for 1D snow and soil models. Arrays of pyranometers (0.3–3 μm) and a scanning thermal radiometer (8–12 μm) characterized the variability of radiative receipt in the forests. A field spectroradiometer measured the hyperspectral hemispherical-directional reflectance of the snow surface. These measurements, together with the ground-based remote sensing, provide the framework for evaluating and improving microwave radiative transfer models and coupling them to land surface models. The dataset is archived at the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado.
Abstract
The boundary layer plays a critical role in regulating energy and moisture exchange between the surface and the free atmosphere. However, the boundary layer and lower atmosphere (including shallow flow features and horizontal gradients that influence local weather) are not sampled at time and space scales needed to improve mesoscale analyses that are used to drive short-term model predictions of impactful weather. These data gaps are exasperated in remote and less developed parts of the world where relatively cheap observational capabilities could help immensely. The continued development of small, weather-sensing uncrewed aircraft systems (UAS), coupled with the emergence of an entirely new commercial sector focused on UAS applications, has created novel opportunities for partially filling this observational gap. This article provides an overview of the current level of readiness of small UAS for routinely sensing the lower atmosphere in support of national meteorological and hydrological services (NMHS) around the world. The potential benefits of UAS observations in operational weather forecasting and numerical weather prediction are discussed, as are key considerations that will need to be addressed before their widespread adoption. Finally, potential pathways for implementation of weather-sensing UAS into operations, which hinge on their successful demonstration within collaborative, multi-agency-sponsored testbeds, are suggested.
Abstract
The boundary layer plays a critical role in regulating energy and moisture exchange between the surface and the free atmosphere. However, the boundary layer and lower atmosphere (including shallow flow features and horizontal gradients that influence local weather) are not sampled at time and space scales needed to improve mesoscale analyses that are used to drive short-term model predictions of impactful weather. These data gaps are exasperated in remote and less developed parts of the world where relatively cheap observational capabilities could help immensely. The continued development of small, weather-sensing uncrewed aircraft systems (UAS), coupled with the emergence of an entirely new commercial sector focused on UAS applications, has created novel opportunities for partially filling this observational gap. This article provides an overview of the current level of readiness of small UAS for routinely sensing the lower atmosphere in support of national meteorological and hydrological services (NMHS) around the world. The potential benefits of UAS observations in operational weather forecasting and numerical weather prediction are discussed, as are key considerations that will need to be addressed before their widespread adoption. Finally, potential pathways for implementation of weather-sensing UAS into operations, which hinge on their successful demonstration within collaborative, multi-agency-sponsored testbeds, are suggested.
