Browse
Abstract
A lack of routine environmental observations located near deepening cumulus congestus clouds limits verification of important theorized and simulated updraft–environment interaction processes occurring during deep convection initiation (CI). We analyze radiosonde profiles collected during several hundred CI events near a mountain range in central Argentina during the CACTI field campaign. Statistical analyses illustrate environmental conditions supporting radar-observed CI outcomes that span a spectrum of convective cell depths, widths, and durations, as well as events lacking precipitating convection. Tested environmental factors include a large variety of sounding-derived measurements of CAPE, CIN, moisture, terrain-relative winds, vertical shear, and lifted parcel properties, with supplemental model reanalysis of background larger-scale vertical motion. CAPE and CIN metrics do not consistently differentiate CI success from failure. Only a few environmental factors contain consistent monotonic relationships among the spectrum of cloud depths achieved during CI: (i) the depth and strength of background ascent, and (ii) the component of low-level flow oriented parallel to the ridgeline. These metrics suggest that the ability of the surrounding flow to lift parcels to their LFC and terrain-modified flow are consistently relevant processes for CI. Low- to midlevel relative humidity strongly discriminated between CI and non-CI events, likely reflecting entrainment-driven dilution processes. However, we could not confidently conclude that relative humidity similarly discriminated robust from marginal CI events. Circumstantial evidence was found linking cell width, an important cloud property governing the probability of CI, to LCL height, boundary layer depth, depth and magnitude of the CIN layer, and ambient wind shear.
Abstract
A lack of routine environmental observations located near deepening cumulus congestus clouds limits verification of important theorized and simulated updraft–environment interaction processes occurring during deep convection initiation (CI). We analyze radiosonde profiles collected during several hundred CI events near a mountain range in central Argentina during the CACTI field campaign. Statistical analyses illustrate environmental conditions supporting radar-observed CI outcomes that span a spectrum of convective cell depths, widths, and durations, as well as events lacking precipitating convection. Tested environmental factors include a large variety of sounding-derived measurements of CAPE, CIN, moisture, terrain-relative winds, vertical shear, and lifted parcel properties, with supplemental model reanalysis of background larger-scale vertical motion. CAPE and CIN metrics do not consistently differentiate CI success from failure. Only a few environmental factors contain consistent monotonic relationships among the spectrum of cloud depths achieved during CI: (i) the depth and strength of background ascent, and (ii) the component of low-level flow oriented parallel to the ridgeline. These metrics suggest that the ability of the surrounding flow to lift parcels to their LFC and terrain-modified flow are consistently relevant processes for CI. Low- to midlevel relative humidity strongly discriminated between CI and non-CI events, likely reflecting entrainment-driven dilution processes. However, we could not confidently conclude that relative humidity similarly discriminated robust from marginal CI events. Circumstantial evidence was found linking cell width, an important cloud property governing the probability of CI, to LCL height, boundary layer depth, depth and magnitude of the CIN layer, and ambient wind shear.
Abstract
This study describes a real-time implementation of valid time shifting (VTS) within the Gridpoint Statistical Interpolation–based ensemble-variational (EnVar) data assimilation system, developed at the Multi-Scale Data Assimilation and Predictability Laboratory. This system, featuring data assimilation of mesoscale conventional observations and storm-scale radar reflectivity observations and interfaced with the next-generation Finite Volume Cubed Sphere Dynamical Core limited-area model (FV3-LAM), was run in real-time during the 2021 Hazardous Weather Testbed Spring Forecast Experiment. The VTS method efficiently increases ensemble size by incorporating ensemble forecast output before and after the central analysis. Two configurations were examined to systematically evaluate VTS: a baseline 36-member system with hourly data assimilation (NOVTS), and an experiment testing VTS for the radar analysis step. Verification across 22 cases shows statistically significant benefits of VTS to increase ensemble spread and better fit first guesses to observations. Control member forecasts launched at 0000 UTC have consistently higher skill, lower bias, and higher reliability in VTS than in NOVTS throughout the 18-h forecast evaluation period, especially from severe cases often featuring upscale growth into mesoscale convective systems. Verification of updraft helicity-based ensemble surrogate severe probabilistic forecasts against observed storm reports shows higher skill of VTS when verifying on finer scales, with benefits to constraining higher probabilities over report locations and reducing probabilities over no-report locations. This study is a first step toward the next-generation Rapid Refresh Forecast System (RRFS), demonstrating the feasibility of such a real-time system and the potential benefits of VTS implementation.
Abstract
This study describes a real-time implementation of valid time shifting (VTS) within the Gridpoint Statistical Interpolation–based ensemble-variational (EnVar) data assimilation system, developed at the Multi-Scale Data Assimilation and Predictability Laboratory. This system, featuring data assimilation of mesoscale conventional observations and storm-scale radar reflectivity observations and interfaced with the next-generation Finite Volume Cubed Sphere Dynamical Core limited-area model (FV3-LAM), was run in real-time during the 2021 Hazardous Weather Testbed Spring Forecast Experiment. The VTS method efficiently increases ensemble size by incorporating ensemble forecast output before and after the central analysis. Two configurations were examined to systematically evaluate VTS: a baseline 36-member system with hourly data assimilation (NOVTS), and an experiment testing VTS for the radar analysis step. Verification across 22 cases shows statistically significant benefits of VTS to increase ensemble spread and better fit first guesses to observations. Control member forecasts launched at 0000 UTC have consistently higher skill, lower bias, and higher reliability in VTS than in NOVTS throughout the 18-h forecast evaluation period, especially from severe cases often featuring upscale growth into mesoscale convective systems. Verification of updraft helicity-based ensemble surrogate severe probabilistic forecasts against observed storm reports shows higher skill of VTS when verifying on finer scales, with benefits to constraining higher probabilities over report locations and reducing probabilities over no-report locations. This study is a first step toward the next-generation Rapid Refresh Forecast System (RRFS), demonstrating the feasibility of such a real-time system and the potential benefits of VTS implementation.
Abstract
Convection initiation (CI) has remained a major challenge in weather forecasting worldwide. The Hetao area in North China, the location of Asia’s largest irrigation area, contains highly heterogeneous vegetation where near-surface convergence lines (boundaries) parallel to the oasis–desert border often emerge over the desert and initiate convection. This study investigated the evolution of such a boundary and its influence on the CI process where a series of cells were successively initiated along the boundary on 4 June 2013. Our results indicated that uneven surface heating across the oasis–desert border produced mesoscale thermal circulation. The westerly oasis breeze in the thermal circulation converged with the southerly background wind and formed a boundary over the desert along the high-temperature contrast line. A middle-hemisphere westerly trough further enhanced uplift and facilitated CI. Our simulation revealed that the first 30-dBZ parcels in each cell originated from either the desert side at a low level or the oasis side at a middle level, rather than from the oasis at a low level, as indicated by previous idealized studies. Southerly low-level parcels veered above the boundary and experienced a longer lifting time over the desert, while western parcels originating from the oasis experienced a shorter lifting time and smaller vertical displacement, resulting in middle-level parcels instead of low-level parcels that reached their level of free convection. Even though CI occurred over a surface boundary without a near-surface stable layer, the inflow may have originated from middle levels rather than in contact with the surface.
Significance Statement
The purpose of this study is to understand the evolution of a real-world near-surface convergence line and the associated deep convection initiation (CI) along the border of Asia’s largest irrigation area and the desert in northern China. Notably, previous works have mainly focused on shallow convection over uneven vegetation distributions based on idealized simulations, which may be quite different from real-world interactions between thermal circulation and background flow. Our results highlight different parcel sources in different convections initiated by the same convergence line, which is different from the idealized situation where parcels mainly originate from the low-level oasis side.
Abstract
Convection initiation (CI) has remained a major challenge in weather forecasting worldwide. The Hetao area in North China, the location of Asia’s largest irrigation area, contains highly heterogeneous vegetation where near-surface convergence lines (boundaries) parallel to the oasis–desert border often emerge over the desert and initiate convection. This study investigated the evolution of such a boundary and its influence on the CI process where a series of cells were successively initiated along the boundary on 4 June 2013. Our results indicated that uneven surface heating across the oasis–desert border produced mesoscale thermal circulation. The westerly oasis breeze in the thermal circulation converged with the southerly background wind and formed a boundary over the desert along the high-temperature contrast line. A middle-hemisphere westerly trough further enhanced uplift and facilitated CI. Our simulation revealed that the first 30-dBZ parcels in each cell originated from either the desert side at a low level or the oasis side at a middle level, rather than from the oasis at a low level, as indicated by previous idealized studies. Southerly low-level parcels veered above the boundary and experienced a longer lifting time over the desert, while western parcels originating from the oasis experienced a shorter lifting time and smaller vertical displacement, resulting in middle-level parcels instead of low-level parcels that reached their level of free convection. Even though CI occurred over a surface boundary without a near-surface stable layer, the inflow may have originated from middle levels rather than in contact with the surface.
Significance Statement
The purpose of this study is to understand the evolution of a real-world near-surface convergence line and the associated deep convection initiation (CI) along the border of Asia’s largest irrigation area and the desert in northern China. Notably, previous works have mainly focused on shallow convection over uneven vegetation distributions based on idealized simulations, which may be quite different from real-world interactions between thermal circulation and background flow. Our results highlight different parcel sources in different convections initiated by the same convergence line, which is different from the idealized situation where parcels mainly originate from the low-level oasis side.
Abstract
The Advanced Geostationary Radiation Imager (AGRI) on board the Fengyun-4A (FY-4A) satellite provides visible radiances that contain critical information on clouds and precipitation. In this study, the impact of assimilating FY-4A/AGRI all-sky visible radiances on the simulation of a convective system was evaluated with an observing system simulation experiment (OSSE) using a localized particle filter (PF). The localized PF was implemented into the Data Assimilation Research Testbed (DART) coupled with the Weather Research and Forecasting (WRF) Model. The results of a 2-day data assimilation (DA) experiment generated encouraging outcome at a synoptic scale. Assimilating FY-4A/AGRI visible radiances with the localized PF significantly improved the analysis and forecast of cloud water path (CWP), cloud coverage, rain rate, and rainfall areas. In addition, some positive impacts were produced on the temperature and water vapor mixing ratio in the vicinity of cloudy regions. Sensitivity studies indicated that the best results were achieved by the localized PF configured with a localization distance that is equivalent to the model grid spacing (20 km) and with an adequately short cycling interval (30 min). However, the localized PF could not improve cloud vertical structures and cloud phases due to a lack of related information in the visible radiances. Moreover, the localized PF was compared with the ensemble adjustment Kalman filter (EAKF) and it was indicated that the localized PF outperformed EAKF even when the number of ensemble members was doubled for the latter, indicating a great potential of the localized PF in assimilating visible radiances.
Abstract
The Advanced Geostationary Radiation Imager (AGRI) on board the Fengyun-4A (FY-4A) satellite provides visible radiances that contain critical information on clouds and precipitation. In this study, the impact of assimilating FY-4A/AGRI all-sky visible radiances on the simulation of a convective system was evaluated with an observing system simulation experiment (OSSE) using a localized particle filter (PF). The localized PF was implemented into the Data Assimilation Research Testbed (DART) coupled with the Weather Research and Forecasting (WRF) Model. The results of a 2-day data assimilation (DA) experiment generated encouraging outcome at a synoptic scale. Assimilating FY-4A/AGRI visible radiances with the localized PF significantly improved the analysis and forecast of cloud water path (CWP), cloud coverage, rain rate, and rainfall areas. In addition, some positive impacts were produced on the temperature and water vapor mixing ratio in the vicinity of cloudy regions. Sensitivity studies indicated that the best results were achieved by the localized PF configured with a localization distance that is equivalent to the model grid spacing (20 km) and with an adequately short cycling interval (30 min). However, the localized PF could not improve cloud vertical structures and cloud phases due to a lack of related information in the visible radiances. Moreover, the localized PF was compared with the ensemble adjustment Kalman filter (EAKF) and it was indicated that the localized PF outperformed EAKF even when the number of ensemble members was doubled for the latter, indicating a great potential of the localized PF in assimilating visible radiances.
Abstract
During late June 2021, a record-breaking heatwave impacted western North America, with all-time high temperatures reported across Washington, Oregon, British Columbia, and Alberta. The heatwave was forced by a highly anomalous upper-level ridge, strong synoptic-scale subsidence, and downslope flow resulting in lower-tropospheric adiabatic warming. This study examines the impact of antecedent soil moisture on this extreme heat event. During the cool season of 2020/21, precipitation over the Pacific Northwest was above or near normal, followed by a dry spring that desiccated soils to 50%–75% of normal moisture content by early June. Low surface soil moisture affects the surface energy balance by altering the partitioning between sensible and latent heat fluxes, resulting in warmer temperatures. Using numerical model simulations of the heatwave, this study demonstrates that surface air temperatures were warmed by an average of 0.48°C as a result of dry soil moisture conditions, compared to a high-temperature anomaly of 10°–20°C during the event. Air temperatures over eastern Washington and southern British Columbia were most sensitive to soil moisture anomalies, with 0000 UTC temperature anomalies ranging from 1.2° to 2.2°C. Trajectory analysis indicated that rapid subsidence of elevated parcels prevented air parcels from being affected by surface heat fluxes over a prolonged period of time, resulting in a relatively small temperature sensitivity to soil moisture. Changes to soil moisture also altered regional pressure, low-level wind, and geopotential heights, as well as modified the marine air intrusion along the Pacific coast of Washington and Oregon.
Significance Statement
The record-breaking western North American heatwave of late June 2021 was preceded by below-normal soil moisture over the region. This study evaluates the role of soil moisture on the 2021 heatwave, demonstrating that the anomalous temperatures during this extreme event were not significantly increased by below-normal soil moisture.
Abstract
During late June 2021, a record-breaking heatwave impacted western North America, with all-time high temperatures reported across Washington, Oregon, British Columbia, and Alberta. The heatwave was forced by a highly anomalous upper-level ridge, strong synoptic-scale subsidence, and downslope flow resulting in lower-tropospheric adiabatic warming. This study examines the impact of antecedent soil moisture on this extreme heat event. During the cool season of 2020/21, precipitation over the Pacific Northwest was above or near normal, followed by a dry spring that desiccated soils to 50%–75% of normal moisture content by early June. Low surface soil moisture affects the surface energy balance by altering the partitioning between sensible and latent heat fluxes, resulting in warmer temperatures. Using numerical model simulations of the heatwave, this study demonstrates that surface air temperatures were warmed by an average of 0.48°C as a result of dry soil moisture conditions, compared to a high-temperature anomaly of 10°–20°C during the event. Air temperatures over eastern Washington and southern British Columbia were most sensitive to soil moisture anomalies, with 0000 UTC temperature anomalies ranging from 1.2° to 2.2°C. Trajectory analysis indicated that rapid subsidence of elevated parcels prevented air parcels from being affected by surface heat fluxes over a prolonged period of time, resulting in a relatively small temperature sensitivity to soil moisture. Changes to soil moisture also altered regional pressure, low-level wind, and geopotential heights, as well as modified the marine air intrusion along the Pacific coast of Washington and Oregon.
Significance Statement
The record-breaking western North American heatwave of late June 2021 was preceded by below-normal soil moisture over the region. This study evaluates the role of soil moisture on the 2021 heatwave, demonstrating that the anomalous temperatures during this extreme event were not significantly increased by below-normal soil moisture.
Abstract
The current global operational four-dimensional ensemble-variational (4DEnVar) data assimilation (DA) system at NCEP adopts a background ensemble at a reduced resolution, which restricts the range of spatial scales that the ensemble background error covariance can resolve. A prior study developed a multiresolution ensemble 4DEnVar method and determined that this approach can provide a comparable forecast to an approach using solely high-resolution members, while substantially reducing the computational cost. This study further develops the multiresolution ensemble 4DEnVar approach to allow for a flexible number of low- and high-resolution ensemble members as well as varying localization length scales between the high- and low-resolution ensembles. Three 4DEnVar experiments with the same computational costs are compared. The first experiment has an 80-member high-resolution background ensemble with single-scale optimally tuned localization (SR-High). The second and third experiments utilize the multiresolution background ensembles. One has 130 low-resolution and 40 high-resolution members (MR170) while the other has 180 low-resolution members and 24 high-resolution members (MR204). Both multiresolution ensemble experiments utilize differing localization radii with ensemble resolution. Despite having the same costs, both MR170 and MR204 improves global forecasts and decreases tropical cyclone track errors for up to 5 days’ lead time compared to SR-High. Improvements are most apparent in larger-scale features, such as jet streams and the environmental steering flow of tropical cyclones. Additionally, MR170 outperforms MR204 in terms of global and tropical cyclone track forecasts, demonstrating the value of both increasing sampling at large scales and retaining substantial information at small scales.
Abstract
The current global operational four-dimensional ensemble-variational (4DEnVar) data assimilation (DA) system at NCEP adopts a background ensemble at a reduced resolution, which restricts the range of spatial scales that the ensemble background error covariance can resolve. A prior study developed a multiresolution ensemble 4DEnVar method and determined that this approach can provide a comparable forecast to an approach using solely high-resolution members, while substantially reducing the computational cost. This study further develops the multiresolution ensemble 4DEnVar approach to allow for a flexible number of low- and high-resolution ensemble members as well as varying localization length scales between the high- and low-resolution ensembles. Three 4DEnVar experiments with the same computational costs are compared. The first experiment has an 80-member high-resolution background ensemble with single-scale optimally tuned localization (SR-High). The second and third experiments utilize the multiresolution background ensembles. One has 130 low-resolution and 40 high-resolution members (MR170) while the other has 180 low-resolution members and 24 high-resolution members (MR204). Both multiresolution ensemble experiments utilize differing localization radii with ensemble resolution. Despite having the same costs, both MR170 and MR204 improves global forecasts and decreases tropical cyclone track errors for up to 5 days’ lead time compared to SR-High. Improvements are most apparent in larger-scale features, such as jet streams and the environmental steering flow of tropical cyclones. Additionally, MR170 outperforms MR204 in terms of global and tropical cyclone track forecasts, demonstrating the value of both increasing sampling at large scales and retaining substantial information at small scales.
Abstract
To provide global coverage for the hyperspectral infrared (IR) and microwave (MW) sounders, the low-Earth-orbiting (LEO) satellite constellation is in operation in three temporally well-spaced sun-synchronous orbits. However, the satellite program can be altered as a result of aging satellites needing to deorbit and/or termination of the legacy program, resulting in less spatiotemporal coverage. In this study, to stress the contribution of IR and MW sounder observations from the LEO satellite constellation on numerical weather prediction (NWP) system performance, the change of the analysis impact is assessed under two assumptions: 1) the loss of the IR and MW sounder observations in each of three sun-synchronous orbits and 2) the loss of the secondary LEO satellite in two orbits, using a 2017 version of the National Centers for Environmental Prediction Global Forecast System (GFS). In the analysis verification, it is found that the analysis field is degraded due to the loss of the IR and MW sounders in each of the three primary orbits. In particular, the satellites in the afternoon orbit significantly contribute to improving the analysis as compared with the satellites in the other two orbits. In addition, the loss of the secondary satellite results in significant degradation of the analysis, resulting from reduced spatial coverage by the IR and MW sounders. These results suggest that the LEO satellite constellation, consisting of the LEO satellites in three primary sun-synchronous orbits, should be maintained in terms of the contribution to the NWP.
Significance Statement
Hyperspectral infrared (IR) and microwave (MW) sounders from low-Earth-orbiting (LEO) satellites significantly contribute to improving numerical weather forecasting. Nevertheless, the resiliency of the LEO satellite programs, operating in three sun-synchronous orbits, can be compromised by aging satellites needing to deorbit and/or termination of legacy satellite systems. Thus, to highlight the importance of the IR and MW sounder observations from LEO satellites in terms of numerical weather forecasting, we assessed the analysis impact of these observations with diverse satellite data availability scenarios. In the trial experiments, it is demonstrated that analysis performance is significantly degraded if the IR and MW sounders are lost, suggesting that the satellite programs carrying the IR and MW sounders should be maintained seamlessly in the future.
Abstract
To provide global coverage for the hyperspectral infrared (IR) and microwave (MW) sounders, the low-Earth-orbiting (LEO) satellite constellation is in operation in three temporally well-spaced sun-synchronous orbits. However, the satellite program can be altered as a result of aging satellites needing to deorbit and/or termination of the legacy program, resulting in less spatiotemporal coverage. In this study, to stress the contribution of IR and MW sounder observations from the LEO satellite constellation on numerical weather prediction (NWP) system performance, the change of the analysis impact is assessed under two assumptions: 1) the loss of the IR and MW sounder observations in each of three sun-synchronous orbits and 2) the loss of the secondary LEO satellite in two orbits, using a 2017 version of the National Centers for Environmental Prediction Global Forecast System (GFS). In the analysis verification, it is found that the analysis field is degraded due to the loss of the IR and MW sounders in each of the three primary orbits. In particular, the satellites in the afternoon orbit significantly contribute to improving the analysis as compared with the satellites in the other two orbits. In addition, the loss of the secondary satellite results in significant degradation of the analysis, resulting from reduced spatial coverage by the IR and MW sounders. These results suggest that the LEO satellite constellation, consisting of the LEO satellites in three primary sun-synchronous orbits, should be maintained in terms of the contribution to the NWP.
Significance Statement
Hyperspectral infrared (IR) and microwave (MW) sounders from low-Earth-orbiting (LEO) satellites significantly contribute to improving numerical weather forecasting. Nevertheless, the resiliency of the LEO satellite programs, operating in three sun-synchronous orbits, can be compromised by aging satellites needing to deorbit and/or termination of legacy satellite systems. Thus, to highlight the importance of the IR and MW sounder observations from LEO satellites in terms of numerical weather forecasting, we assessed the analysis impact of these observations with diverse satellite data availability scenarios. In the trial experiments, it is demonstrated that analysis performance is significantly degraded if the IR and MW sounders are lost, suggesting that the satellite programs carrying the IR and MW sounders should be maintained seamlessly in the future.
Abstract
Traditional atmospheric surface layer theory assumes homogeneous surface conditions. Regardless, nearly all surface layer parameterization schemes employed within numerical weather prediction models utilize the same techniques within highly heterogeneous coastal regimes as for homogeneous environments. We compare predicted surface weather and fluxes of momentum, heat, and moisture—focusing mainly on momentum—from regional simulations using the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model to observations collected from offshore buoys, inland flux towers, and radiosonde profiles during the Coastal Land-Air-Sea Interaction (CLASI) project throughout the summer of 2021 around Monterey Bay, California. Results reveal that modeled cross-coastal surface flux gradients are spuriously discontinuous, leading to systematically overestimated fluxes and weak winds inland of the coastline during onshore flow periods. Additionally, contrary to observations, modeled surface exchange coefficients are insensitive to wind direction on both sides of the coast, which degrades predictive skill downstream from the coastline. Over the central bay, prediction degrades when near-surface wind directions deviate from the prevailing flow direction as the parameterized stress–wind relationship fails during these cases. Predictive skill over the bay is therefore linked to variations in wind direction. Offshore of the geographically complex peninsula, systematic biases are less clear; however, bifurcations in drag coefficients based on wind direction were measured here as well. Last, increasing the horizontal grid spacing from 333 m to 3 km does not significantly affect surface layer prediction. This work highlights the need to reevaluate surface layer parameterization methods for modeling within coastal regions.
Significance Statement
Understanding surface layer weather is critical for many purposes, such as infrastructure design and weather forecasting. Within the context of numerical modeling and weather prediction, skillful forecasts of surface winds and temperature rely on accurate portrayal of the surface layer. By comparing observations collected during the Coastal Land-Air-Sea Interaction field program to numerical model solutions, we show that prediction of the surface layer fluxes of momentum, heat, and moisture break down near the coastline, which leads to biases in the predicted surface layer weather both inland and over the water. As surface layer parameterization methods across nearly all numerical models are rooted in the same practices, our results call into question the use of traditional methods near the coastline.
Abstract
Traditional atmospheric surface layer theory assumes homogeneous surface conditions. Regardless, nearly all surface layer parameterization schemes employed within numerical weather prediction models utilize the same techniques within highly heterogeneous coastal regimes as for homogeneous environments. We compare predicted surface weather and fluxes of momentum, heat, and moisture—focusing mainly on momentum—from regional simulations using the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model to observations collected from offshore buoys, inland flux towers, and radiosonde profiles during the Coastal Land-Air-Sea Interaction (CLASI) project throughout the summer of 2021 around Monterey Bay, California. Results reveal that modeled cross-coastal surface flux gradients are spuriously discontinuous, leading to systematically overestimated fluxes and weak winds inland of the coastline during onshore flow periods. Additionally, contrary to observations, modeled surface exchange coefficients are insensitive to wind direction on both sides of the coast, which degrades predictive skill downstream from the coastline. Over the central bay, prediction degrades when near-surface wind directions deviate from the prevailing flow direction as the parameterized stress–wind relationship fails during these cases. Predictive skill over the bay is therefore linked to variations in wind direction. Offshore of the geographically complex peninsula, systematic biases are less clear; however, bifurcations in drag coefficients based on wind direction were measured here as well. Last, increasing the horizontal grid spacing from 333 m to 3 km does not significantly affect surface layer prediction. This work highlights the need to reevaluate surface layer parameterization methods for modeling within coastal regions.
Significance Statement
Understanding surface layer weather is critical for many purposes, such as infrastructure design and weather forecasting. Within the context of numerical modeling and weather prediction, skillful forecasts of surface winds and temperature rely on accurate portrayal of the surface layer. By comparing observations collected during the Coastal Land-Air-Sea Interaction field program to numerical model solutions, we show that prediction of the surface layer fluxes of momentum, heat, and moisture break down near the coastline, which leads to biases in the predicted surface layer weather both inland and over the water. As surface layer parameterization methods across nearly all numerical models are rooted in the same practices, our results call into question the use of traditional methods near the coastline.
Abstract
This study investigates mixed-phase cloud (MPC) processes along the warm conveyor belts (WCBs) of two extratropical cyclones observed during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX). The aim is to investigate the effect of two radically distinct parameterizations for MPCs on the WCB and the ridge building downstream: the first one (REF) drastically limits the formation of liquid clouds, while the second one (T40) forces the liquid clouds to exist. REF exhibits a stronger heating below 6-km height and a more important cooling above 6-km height than T40. The stronger heating at lower levels is due to more important water vapor depositional processes while the larger cooling at upper levels is due to differences in radiative cooling. The consequence is a more efficient potential vorticity destruction in the WCB outflow region and a more rapid ridge building in REF than T40. A comparison with airborne remote sensing measurements is performed. REF does not form any MPCs whereas T40 does, in particular in regions detected by the radar–lidar platform like below the dry intrusion. Comparison of both ice water content and reflectivity shows there may be too much pristine ice and not enough snow in REF and not enough cold hydrometeors in general in T40. The lower ice-to-snow ratio in T40 likely explains its better distribution of hydrometeors with respect to height compared to REF. These results underline the influence of MPC processes on the upper-tropospheric circulation and the need for more MPC observations in midlatitudes.
Significance Statement
The diabatic processes occurring in the warm conveyor belt (WCB) of extratropical cyclones impact the jet stream structure at midlatitudes. This study highlights some sensitivity of upper-level dynamics to mixed-phase-cloud-related processes. Comparisons of two different microphysical schemes for mixed-phase clouds shows that the ratio of liquid to solid clouds along the WCB ascents impacts the latent heat release and the radiation. Data from the NAWDEX campaign helps to determine room for improvement for both schemes and point out the need of a better understanding of these processes for an improved prediction of upper-level dynamics.
Abstract
This study investigates mixed-phase cloud (MPC) processes along the warm conveyor belts (WCBs) of two extratropical cyclones observed during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX). The aim is to investigate the effect of two radically distinct parameterizations for MPCs on the WCB and the ridge building downstream: the first one (REF) drastically limits the formation of liquid clouds, while the second one (T40) forces the liquid clouds to exist. REF exhibits a stronger heating below 6-km height and a more important cooling above 6-km height than T40. The stronger heating at lower levels is due to more important water vapor depositional processes while the larger cooling at upper levels is due to differences in radiative cooling. The consequence is a more efficient potential vorticity destruction in the WCB outflow region and a more rapid ridge building in REF than T40. A comparison with airborne remote sensing measurements is performed. REF does not form any MPCs whereas T40 does, in particular in regions detected by the radar–lidar platform like below the dry intrusion. Comparison of both ice water content and reflectivity shows there may be too much pristine ice and not enough snow in REF and not enough cold hydrometeors in general in T40. The lower ice-to-snow ratio in T40 likely explains its better distribution of hydrometeors with respect to height compared to REF. These results underline the influence of MPC processes on the upper-tropospheric circulation and the need for more MPC observations in midlatitudes.
Significance Statement
The diabatic processes occurring in the warm conveyor belt (WCB) of extratropical cyclones impact the jet stream structure at midlatitudes. This study highlights some sensitivity of upper-level dynamics to mixed-phase-cloud-related processes. Comparisons of two different microphysical schemes for mixed-phase clouds shows that the ratio of liquid to solid clouds along the WCB ascents impacts the latent heat release and the radiation. Data from the NAWDEX campaign helps to determine room for improvement for both schemes and point out the need of a better understanding of these processes for an improved prediction of upper-level dynamics.
Abstract
Under very large vertical gradients of atmospheric refractivity, which are typical at the height of the planetary boundary layer, the assimilation of radio occultation (RO) observations into numerical weather prediction (NWP) models presents several serious challenges. In such conditions, the assimilation of RO bending angle profiles is an ill-posed problem, the uncertainty associated with the RO observations is higher, and the one-dimensional forward operator used to assimilate these observations has several theoretical deficiencies. As a result, a larger percentage of these RO observations are rejected at the NWP centers by existing quality control procedures, potentially limiting the benefits of this data type to improve weather forecasting in the lower troposphere. To address these problems, a new methodology that enables the assimilation of RO data to be extended to the lower moist troposphere has been developed. Challenges associated with larger atmospheric gradients of refractivity are partially overcome by a reformulation that has minimal effect at higher altitudes. As a first step toward this effort, this study presents both the theoretical development of this new methodology and a forecast impact assessment of it using the NCEP NWP system. Though using a conservative approach, benefits in the lower tropical troposphere are already noticeable. The encouraging results of this work open the potential for further exploitation and optimization of RO assimilation.
Abstract
Under very large vertical gradients of atmospheric refractivity, which are typical at the height of the planetary boundary layer, the assimilation of radio occultation (RO) observations into numerical weather prediction (NWP) models presents several serious challenges. In such conditions, the assimilation of RO bending angle profiles is an ill-posed problem, the uncertainty associated with the RO observations is higher, and the one-dimensional forward operator used to assimilate these observations has several theoretical deficiencies. As a result, a larger percentage of these RO observations are rejected at the NWP centers by existing quality control procedures, potentially limiting the benefits of this data type to improve weather forecasting in the lower troposphere. To address these problems, a new methodology that enables the assimilation of RO data to be extended to the lower moist troposphere has been developed. Challenges associated with larger atmospheric gradients of refractivity are partially overcome by a reformulation that has minimal effect at higher altitudes. As a first step toward this effort, this study presents both the theoretical development of this new methodology and a forecast impact assessment of it using the NCEP NWP system. Though using a conservative approach, benefits in the lower tropical troposphere are already noticeable. The encouraging results of this work open the potential for further exploitation and optimization of RO assimilation.
