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Abstract
Application of random sampling techniques to composite differences between 18 El Niño and 14 La Niña events observed since 1920 reveals considerable uncertainty in both the pattern and amplitude of the Northern Hemisphere extratropical winter sea level pressure (SLP) response to ENSO. While the SLP responses over the North Pacific and North America are robust to sampling variability, their magnitudes can vary by a factor of 2; other regions, such as the Arctic, North Atlantic, and Europe are less robust in their SLP patterns, amplitudes, and statistical significance. The uncertainties on the observed ENSO composite are shown to arise mainly from atmospheric internal variability as opposed to ENSO diversity. These observational findings pose considerable challenges for the evaluation of ENSO teleconnections in models. An approach is proposed that incorporates both pattern and amplitude uncertainty in the observational target, allowing for discrimination between true model biases in the forced ENSO response and apparent model biases that arise from limited sampling of non-ENSO-related internal variability. Large initial-condition coupled model ensembles with realistic tropical Pacific sea surface temperature anomaly evolution during 1920–2013 show similar levels of uncertainty in their ENSO teleconnections as found in observations. Because the set of ENSO events in each of the model composites is the same (and identical to that in observations), these uncertainties are entirely attributable to sampling fluctuations arising from internal variability, which is shown to originate from atmospheric processes. The initial-condition model ensembles thus inform the interpretation of the single observed ENSO composite and vice versa.
Abstract
Application of random sampling techniques to composite differences between 18 El Niño and 14 La Niña events observed since 1920 reveals considerable uncertainty in both the pattern and amplitude of the Northern Hemisphere extratropical winter sea level pressure (SLP) response to ENSO. While the SLP responses over the North Pacific and North America are robust to sampling variability, their magnitudes can vary by a factor of 2; other regions, such as the Arctic, North Atlantic, and Europe are less robust in their SLP patterns, amplitudes, and statistical significance. The uncertainties on the observed ENSO composite are shown to arise mainly from atmospheric internal variability as opposed to ENSO diversity. These observational findings pose considerable challenges for the evaluation of ENSO teleconnections in models. An approach is proposed that incorporates both pattern and amplitude uncertainty in the observational target, allowing for discrimination between true model biases in the forced ENSO response and apparent model biases that arise from limited sampling of non-ENSO-related internal variability. Large initial-condition coupled model ensembles with realistic tropical Pacific sea surface temperature anomaly evolution during 1920–2013 show similar levels of uncertainty in their ENSO teleconnections as found in observations. Because the set of ENSO events in each of the model composites is the same (and identical to that in observations), these uncertainties are entirely attributable to sampling fluctuations arising from internal variability, which is shown to originate from atmospheric processes. The initial-condition model ensembles thus inform the interpretation of the single observed ENSO composite and vice versa.
Abstract
Reanalysis output for 1948–99 is used to evaluate the temporal distributions, the geographical origins, and the atmospheric teleconnections associated with major cold outbreaks affecting heavily populated areas of middle latitudes. The study focuses on three subregions of the United States and two subregions of Europe. The cold outbreaks affecting the United States are more extreme than those affecting Europe, in terms of both the regionally averaged and the local minimum air temperatures. There is no apparent trend toward fewer extreme cold events on either continent over the 1948–99 period, although a long station history suggests that such events may have been more frequent in the United States during the late 1800s and early 1900s. The trajectories of the coldest air masses are southward or southeastward over North America, but westward over Europe. Subsidence of several hundred millibars is typical of the trajectories of the coldest air to reach the surface in the affected regions. Sea level pressure anomalies evolve consistently with the trajectories over the 1–2 weeks prior to the extreme outbreaks, and precursors of the cold events are apparent in coherent antecedent anomaly patterns. Negative values of the North Atlantic oscillation index and positive anomalies of Arctic sea level pressure are features common to North American as well as European outbreaks. However, the strongest associated antecedent anomalies of sea level pressure are generally shifted geographically relative to the nodal locations of the North Atlantic and Arctic oscillations.
Abstract
Reanalysis output for 1948–99 is used to evaluate the temporal distributions, the geographical origins, and the atmospheric teleconnections associated with major cold outbreaks affecting heavily populated areas of middle latitudes. The study focuses on three subregions of the United States and two subregions of Europe. The cold outbreaks affecting the United States are more extreme than those affecting Europe, in terms of both the regionally averaged and the local minimum air temperatures. There is no apparent trend toward fewer extreme cold events on either continent over the 1948–99 period, although a long station history suggests that such events may have been more frequent in the United States during the late 1800s and early 1900s. The trajectories of the coldest air masses are southward or southeastward over North America, but westward over Europe. Subsidence of several hundred millibars is typical of the trajectories of the coldest air to reach the surface in the affected regions. Sea level pressure anomalies evolve consistently with the trajectories over the 1–2 weeks prior to the extreme outbreaks, and precursors of the cold events are apparent in coherent antecedent anomaly patterns. Negative values of the North Atlantic oscillation index and positive anomalies of Arctic sea level pressure are features common to North American as well as European outbreaks. However, the strongest associated antecedent anomalies of sea level pressure are generally shifted geographically relative to the nodal locations of the North Atlantic and Arctic oscillations.
Abstract
The dynamical simulation of the latest version of the Community Atmosphere Model (CAM3) is examined, including the seasonal variation of its mean state and its interannual variability. An ensemble of integrations forced with observed monthly varying sea surface temperatures and sea ice concentrations is compared to coexisting observations. The most significant differences from the previous version of the model [Community Climate Model version 3 (CCM3)] are associated with changes to the parameterized physics package. Results show that these changes have resulted in a modest improvement in the overall simulated climate; however, CAM3 continues to share many of the same biases exhibited by CCM3.
At sea level, CAM3 reproduces the basic observed patterns of the pressure field. Simulated surface pressures are higher than observed over the subtropics, however, an error consistent with an easterly bias in the simulated trade winds and low-latitude surface wind stress. The largest regional differences over the Northern Hemisphere (NH) occur where the simulated highs over the eastern Pacific and Atlantic Oceans are too strong during boreal winter, and erroneously low pressures at higher latitudes are most notable over Europe and Eurasia. Over the Southern Hemisphere (SH), the circumpolar Antarctic trough is too deep throughout the year.
The zonal wind structure in CAM3 is close to that observed, although the middle-latitude westerlies are too strong in both hemispheres throughout the year, consistent with errors in the simulated pressure field and the transient momentum fluxes. The observed patterns and magnitudes of upper-level divergent outflow are also well simulated by CAM3, a finding consistent with an improved and overall realistic simulation of tropical precipitation. There is, however, a tendency for the tropical precipitation maxima to remain in the NH throughout the year, while precipitation tends to be less than indicated by satellite estimates along the equator.
The CAM3 simulation of tropical intraseasonal variability is quite poor. In contrast, observed changes in tropical and subtropical precipitation and the atmospheric circulation changes associated with tropical interannual variability are well simulated. Similarly, principal modes of extratropical variability bear considerable resemblance to those observed, although biases in the mean state degrade the simulated structure of the leading mode of NH atmospheric variability.
Abstract
The dynamical simulation of the latest version of the Community Atmosphere Model (CAM3) is examined, including the seasonal variation of its mean state and its interannual variability. An ensemble of integrations forced with observed monthly varying sea surface temperatures and sea ice concentrations is compared to coexisting observations. The most significant differences from the previous version of the model [Community Climate Model version 3 (CCM3)] are associated with changes to the parameterized physics package. Results show that these changes have resulted in a modest improvement in the overall simulated climate; however, CAM3 continues to share many of the same biases exhibited by CCM3.
At sea level, CAM3 reproduces the basic observed patterns of the pressure field. Simulated surface pressures are higher than observed over the subtropics, however, an error consistent with an easterly bias in the simulated trade winds and low-latitude surface wind stress. The largest regional differences over the Northern Hemisphere (NH) occur where the simulated highs over the eastern Pacific and Atlantic Oceans are too strong during boreal winter, and erroneously low pressures at higher latitudes are most notable over Europe and Eurasia. Over the Southern Hemisphere (SH), the circumpolar Antarctic trough is too deep throughout the year.
The zonal wind structure in CAM3 is close to that observed, although the middle-latitude westerlies are too strong in both hemispheres throughout the year, consistent with errors in the simulated pressure field and the transient momentum fluxes. The observed patterns and magnitudes of upper-level divergent outflow are also well simulated by CAM3, a finding consistent with an improved and overall realistic simulation of tropical precipitation. There is, however, a tendency for the tropical precipitation maxima to remain in the NH throughout the year, while precipitation tends to be less than indicated by satellite estimates along the equator.
The CAM3 simulation of tropical intraseasonal variability is quite poor. In contrast, observed changes in tropical and subtropical precipitation and the atmospheric circulation changes associated with tropical interannual variability are well simulated. Similarly, principal modes of extratropical variability bear considerable resemblance to those observed, although biases in the mean state degrade the simulated structure of the leading mode of NH atmospheric variability.
Abstract
This study presents an overview of the El Niño–Southern Oscillation (ENSO) phenomenon and Pacific decadal variability (PDV) simulated in a multicentury preindustrial control integration of the NCAR Community Climate System Model version 4 (CCSM4) at nominal 1° latitude–longitude resolution. Several aspects of ENSO are improved in CCSM4 compared to its predecessor CCSM3, including the lengthened period (3–6 yr), the larger range of amplitude and frequency of events, and the longer duration of La Niña compared to El Niño. However, the overall magnitude of ENSO in CCSM4 is overestimated by ~30%. The simulated ENSO exhibits characteristics consistent with the delayed/recharge oscillator paradigm, including correspondence between the lengthened period and increased latitudinal width of the anomalous equatorial zonal wind stress. Global seasonal atmospheric teleconnections with accompanying impacts on precipitation and temperature are generally well simulated, although the wintertime deepening of the Aleutian low erroneously persists into spring. The vertical structure of the upper-ocean temperature response to ENSO in the north and south Pacific displays a realistic seasonal evolution, with notable asymmetries between warm and cold events. The model shows evidence of atmospheric circulation precursors over the North Pacific associated with the “seasonal footprinting mechanism,” similar to observations. Simulated PDV exhibits a significant spectral peak around 15 yr, with generally realistic spatial pattern and magnitude. However, PDV linkages between the tropics and extratropics are weaker than observed.
Abstract
This study presents an overview of the El Niño–Southern Oscillation (ENSO) phenomenon and Pacific decadal variability (PDV) simulated in a multicentury preindustrial control integration of the NCAR Community Climate System Model version 4 (CCSM4) at nominal 1° latitude–longitude resolution. Several aspects of ENSO are improved in CCSM4 compared to its predecessor CCSM3, including the lengthened period (3–6 yr), the larger range of amplitude and frequency of events, and the longer duration of La Niña compared to El Niño. However, the overall magnitude of ENSO in CCSM4 is overestimated by ~30%. The simulated ENSO exhibits characteristics consistent with the delayed/recharge oscillator paradigm, including correspondence between the lengthened period and increased latitudinal width of the anomalous equatorial zonal wind stress. Global seasonal atmospheric teleconnections with accompanying impacts on precipitation and temperature are generally well simulated, although the wintertime deepening of the Aleutian low erroneously persists into spring. The vertical structure of the upper-ocean temperature response to ENSO in the north and south Pacific displays a realistic seasonal evolution, with notable asymmetries between warm and cold events. The model shows evidence of atmospheric circulation precursors over the North Pacific associated with the “seasonal footprinting mechanism,” similar to observations. Simulated PDV exhibits a significant spectral peak around 15 yr, with generally realistic spatial pattern and magnitude. However, PDV linkages between the tropics and extratropics are weaker than observed.
Abstract
Atlantic meridional overturning circulation (AMOC) variability is documented in the Community Climate System Model, version 4 (CCSM4) preindustrial control simulation that uses nominal 1° horizontal resolution in all its components. AMOC shows a broad spectrum of low-frequency variability covering the 50–200-yr range, contrasting sharply with the multidecadal variability seen in the T85 × 1 resolution CCSM3 present-day control simulation. Furthermore, the amplitude of variability is much reduced in CCSM4 compared to that of CCSM3. Similarities as well as differences in AMOC variability mechanisms between CCSM3 and CCSM4 are discussed. As in CCSM3, the CCSM4 AMOC variability is primarily driven by the positive density anomalies at the Labrador Sea (LS) deep-water formation site, peaking 2 yr prior to an AMOC maximum. All processes, including parameterized mesoscale and submesoscale eddies, play a role in the creation of salinity anomalies that dominate these density anomalies. High Nordic Sea densities do not necessarily lead to increased overflow transports because the overflow physics is governed by source and interior region density differences. Increased overflow transports do not lead to a higher AMOC either but instead appear to be a precursor to lower AMOC transports through enhanced stratification in LS. This has important implications for decadal prediction studies. The North Atlantic Oscillation (NAO) is significantly correlated with the positive boundary layer depth and density anomalies prior to an AMOC maximum. This suggests a role for NAO through setting the surface flux anomalies in LS and affecting the subpolar gyre circulation strength.
Abstract
Atlantic meridional overturning circulation (AMOC) variability is documented in the Community Climate System Model, version 4 (CCSM4) preindustrial control simulation that uses nominal 1° horizontal resolution in all its components. AMOC shows a broad spectrum of low-frequency variability covering the 50–200-yr range, contrasting sharply with the multidecadal variability seen in the T85 × 1 resolution CCSM3 present-day control simulation. Furthermore, the amplitude of variability is much reduced in CCSM4 compared to that of CCSM3. Similarities as well as differences in AMOC variability mechanisms between CCSM3 and CCSM4 are discussed. As in CCSM3, the CCSM4 AMOC variability is primarily driven by the positive density anomalies at the Labrador Sea (LS) deep-water formation site, peaking 2 yr prior to an AMOC maximum. All processes, including parameterized mesoscale and submesoscale eddies, play a role in the creation of salinity anomalies that dominate these density anomalies. High Nordic Sea densities do not necessarily lead to increased overflow transports because the overflow physics is governed by source and interior region density differences. Increased overflow transports do not lead to a higher AMOC either but instead appear to be a precursor to lower AMOC transports through enhanced stratification in LS. This has important implications for decadal prediction studies. The North Atlantic Oscillation (NAO) is significantly correlated with the positive boundary layer depth and density anomalies prior to an AMOC maximum. This suggests a role for NAO through setting the surface flux anomalies in LS and affecting the subpolar gyre circulation strength.
Abstract
The evolving roles of anthropogenic aerosols (AER) and greenhouse gases (GHG) in driving large-scale patterns of precipitation and SST trends during 1920–2080 are studied using a new set of “all-but-one-forcing” initial-condition large ensembles (LEs) with the Community Earth System Model version 1 (CESM1), which complement the original “all-forcing” CESM1 LE (ALL). The large number of ensemble members (15–20) in each of the new LEs enables regional impacts of AER and GHG to be isolated from the noise of the model’s internal variability. Our analysis approach, based on running 50-yr trends, accommodates geographical and temporal changes in patterns of forcing and response. AER are shown to be the primary driver of large-scale patterns of externally forced trends in ALL before the late 1970s, and GHG to dominate thereafter. The AER and GHG forced trends are spatially distinct except during the 1970s transition phase when aerosol changes are mainly confined to lower latitudes. The transition phase is also characterized by a relative minimum in the amplitude of forced trend patterns in ALL, due to a combination of reduced AER and partially offsetting effects of AER and GHG. Internal variability greatly limits the detectability of AER- and GHG-forced trend patterns in individual realizations based on pattern correlation metrics, especially during the historical period, highlighting the need for LEs. We estimate that <20% of the spatial variances of observed precipitation and SST trends are attributable to AER and GHG forcing, although model biases in patterns of forced response and signal-to-noise may affect this estimate.
Abstract
The evolving roles of anthropogenic aerosols (AER) and greenhouse gases (GHG) in driving large-scale patterns of precipitation and SST trends during 1920–2080 are studied using a new set of “all-but-one-forcing” initial-condition large ensembles (LEs) with the Community Earth System Model version 1 (CESM1), which complement the original “all-forcing” CESM1 LE (ALL). The large number of ensemble members (15–20) in each of the new LEs enables regional impacts of AER and GHG to be isolated from the noise of the model’s internal variability. Our analysis approach, based on running 50-yr trends, accommodates geographical and temporal changes in patterns of forcing and response. AER are shown to be the primary driver of large-scale patterns of externally forced trends in ALL before the late 1970s, and GHG to dominate thereafter. The AER and GHG forced trends are spatially distinct except during the 1970s transition phase when aerosol changes are mainly confined to lower latitudes. The transition phase is also characterized by a relative minimum in the amplitude of forced trend patterns in ALL, due to a combination of reduced AER and partially offsetting effects of AER and GHG. Internal variability greatly limits the detectability of AER- and GHG-forced trend patterns in individual realizations based on pattern correlation metrics, especially during the historical period, highlighting the need for LEs. We estimate that <20% of the spatial variances of observed precipitation and SST trends are attributable to AER and GHG forcing, although model biases in patterns of forced response and signal-to-noise may affect this estimate.
Abstract
A large set of deterministic and ensemble forecasts was produced to identify the optimal spacing for forecasting U.S. East Coast snowstorms. WRF forecasts were produced on cloud-allowing (~1-km grid spacing) and convection-allowing (3–4 km) grids, and compared against forecasts with parameterized convection (>~10 km). Performance diagrams were used to evaluate 19 deterministic forecasts from the winter of 2013–14. Ensemble forecasts of five disruptive snowstorms spanning the years 2015–18 were evaluated using various methods to evaluate probabilistic forecasts. While deterministic forecasts using cloud-allowing grids were not better than convection-allowing forecasts, both had lower bias and higher success ratios than forecasts with parameterized convection. All forecasts were underdispersive. Nevertheless, forecasts on the higher-resolution grids were more reliable than those with parameterized convection. Forecasts on the cloud-allowing grid were best able to discriminate areas that received heavy snow and those that did not, while the forecasts with parameterized convection were least able to do so. It is recommended to use convection-resolving and (if computationally possible) to use cloud-allowing forecast grids when predicting East Coast winter storms.
Abstract
A large set of deterministic and ensemble forecasts was produced to identify the optimal spacing for forecasting U.S. East Coast snowstorms. WRF forecasts were produced on cloud-allowing (~1-km grid spacing) and convection-allowing (3–4 km) grids, and compared against forecasts with parameterized convection (>~10 km). Performance diagrams were used to evaluate 19 deterministic forecasts from the winter of 2013–14. Ensemble forecasts of five disruptive snowstorms spanning the years 2015–18 were evaluated using various methods to evaluate probabilistic forecasts. While deterministic forecasts using cloud-allowing grids were not better than convection-allowing forecasts, both had lower bias and higher success ratios than forecasts with parameterized convection. All forecasts were underdispersive. Nevertheless, forecasts on the higher-resolution grids were more reliable than those with parameterized convection. Forecasts on the cloud-allowing grid were best able to discriminate areas that received heavy snow and those that did not, while the forecasts with parameterized convection were least able to do so. It is recommended to use convection-resolving and (if computationally possible) to use cloud-allowing forecast grids when predicting East Coast winter storms.
Abstract
This paper describes the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) project, which promotes the use of a unique model dataset, performed with the Community Earth System Model, with the Whole Atmosphere Community Climate Model as its atmospheric component [CESM1(WACCM)], to investigate global and regional impacts of geoengineering. The performed simulations were designed to achieve multiple simultaneous climate goals, by strategically placing sulfur injections at four different locations in the stratosphere, unlike many earlier studies that targeted globally averaged surface temperature by placing injections in regions at or around the equator. This advanced approach reduces some of the previously found adverse effects of stratospheric aerosol geoengineering, including uneven cooling between the poles and the equator and shifts in tropical precipitation. The 20-member ensemble increases the ability to distinguish between forced changes and changes due to climate variability in global and regional climate variables in the coupled atmosphere, land, sea ice, and ocean system. We invite the broader community to perform in-depth analyses of climate-related impacts and to identify processes that lead to changes in the climate system as the result of a strategic application of stratospheric aerosol geoengineering.
Abstract
This paper describes the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) project, which promotes the use of a unique model dataset, performed with the Community Earth System Model, with the Whole Atmosphere Community Climate Model as its atmospheric component [CESM1(WACCM)], to investigate global and regional impacts of geoengineering. The performed simulations were designed to achieve multiple simultaneous climate goals, by strategically placing sulfur injections at four different locations in the stratosphere, unlike many earlier studies that targeted globally averaged surface temperature by placing injections in regions at or around the equator. This advanced approach reduces some of the previously found adverse effects of stratospheric aerosol geoengineering, including uneven cooling between the poles and the equator and shifts in tropical precipitation. The 20-member ensemble increases the ability to distinguish between forced changes and changes due to climate variability in global and regional climate variables in the coupled atmosphere, land, sea ice, and ocean system. We invite the broader community to perform in-depth analyses of climate-related impacts and to identify processes that lead to changes in the climate system as the result of a strategic application of stratospheric aerosol geoengineering.
Abstract
The Pacific decadal oscillation (PDO), the dominant year-round pattern of monthly North Pacific sea surface temperature (SST) variability, is an important target of ongoing research within the meteorological and climate dynamics communities and is central to the work of many geologists, ecologists, natural resource managers, and social scientists. Research over the last 15 years has led to an emerging consensus: the PDO is not a single phenomenon, but is instead the result of a combination of different physical processes, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns. How these processes combine to generate the observed PDO evolution, including apparent regime shifts, is shown using simple autoregressive models of increasing spatial complexity. Simulations of recent climate in coupled GCMs are able to capture many aspects of the PDO, but do so based on a balance of processes often more independent of the tropics than is observed. Finally, it is suggested that the assessment of PDO-related regional climate impacts, reconstruction of PDO-related variability into the past with proxy records, and diagnosis of Pacific variability within coupled GCMs should all account for the effects of these different processes, which only partly represent the direct forcing of the atmosphere by North Pacific Ocean SSTs.
Abstract
The Pacific decadal oscillation (PDO), the dominant year-round pattern of monthly North Pacific sea surface temperature (SST) variability, is an important target of ongoing research within the meteorological and climate dynamics communities and is central to the work of many geologists, ecologists, natural resource managers, and social scientists. Research over the last 15 years has led to an emerging consensus: the PDO is not a single phenomenon, but is instead the result of a combination of different physical processes, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns. How these processes combine to generate the observed PDO evolution, including apparent regime shifts, is shown using simple autoregressive models of increasing spatial complexity. Simulations of recent climate in coupled GCMs are able to capture many aspects of the PDO, but do so based on a balance of processes often more independent of the tropics than is observed. Finally, it is suggested that the assessment of PDO-related regional climate impacts, reconstruction of PDO-related variability into the past with proxy records, and diagnosis of Pacific variability within coupled GCMs should all account for the effects of these different processes, which only partly represent the direct forcing of the atmosphere by North Pacific Ocean SSTs.
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.