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At least 235 records · Page 13

Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California

Mesoscale model predictions of wind, turbulence, and wind energy capacity factors are evaluated in the Altamont Pass Wind Resource Area of California (APWRA), where the diurnal regional sea breeze and associated terrain-driven speedup flows drive wind energy production during the summer months. Results from the Weather Research and Forecasting model version 4.4 using a novel three-dimensional planetary boundary layer (3D PBL) scheme, which treats both vertical and horizontal turbulent mixing, are compared to those using a well-established one-dimensional (1D) scheme that treats only vertical turbulent mixing. Each configuration is evaluated over a nearly 3-month-long period during the Hill Flow Study, and due to the recurring nature of the observed speedup flows, diurnal composite averaging is used to capture robust trends in model performance. Both model configurations showed similar overall skill. The general timing and direction of the speedup flows is captured, but their magnitude is overestimated within a typical wind turbine rotor layer. Both also fail to capture a persistent observed near-surface jet-like flow, likely due to the limited grid resolution that is typical of mesoscale models. However, the 3D PBL configuration shows several minor improvements over the 1D PBL configuration, including improved wind speed and turbulence kinetic energy profiles during the accelerating phase of the speedup events, as well as reduced positive wind speed bias at surface stations across the APWRA region. Using a mesoscale wind farm parameterization, modeled capacity factors are also compared to monthly data reported to the US Energy Information Administration (EIA) during the study period. Although the monthly trend in the data is captured, both model configurations overestimate capacity factors by roughly 7 %–11 %. Through model evaluation, this study provides confidence in the 3D PBL scheme for wind energy applications in complex terrain and provides guidance for future testing.

17 WIND ENERGY↗

Wind Profiling With the Airborne Doppler Aerosol Wind Lidar During the 2022 Convective Processes Experiment

The 2017 Decadal Survey for Earth Science and Applications from Space (ESAS 2017) identifies a critical need for improving our understanding of Planetary Boundary Layer (PBL) processes and air-surface fluxes as well as why clouds, convection, and heavy precipitation occur when and where they do. Lidars are uniquely capable of collecting high precision and high spatio-temporal observations that have been used for atmospheric process studies from the ground, aircraft, and space. The wind lidar team at the NASA Langley Research Center (LaRC) started the development of Doppler wind lidar more than a decade ago to demonstrate technologies required for an Earth-orbiting system to globally measure wind profiles. Since then, an airborne Doppler Aerosol WiNd (DAWN) lidar system has been developed and participated in a series of field campaigns. The Doppler Aerosol WiNd (DAWN) lidar uses atmospheric aerosol motion to derive vertical profiles of horizontal wind speed and direction beneath the aircraft. In September 2022, DAWN, along with a suite of other instruments, was flown on a NASA DC-8 as part of The Convective Processes EXperiment – Cabo Verde (CPEX-CV) field campaign. A main objective of CPEX was to obtain a comprehensive set of temperature, humidity and, particularly, wind observations over tropical waters in undisturbed conditions, Saharan dust outbreaks, and in the vicinity of scattered through organized deep convection in all phases of the convective life cycle. DAWN collected data for approximately 90 hours across 13 CPEX-CV science flights. Airborne Vertical Atmospheric Profiling System (AVAPS) dropsondes were dropped throughout the flight for profiling the atmosphere and validating the DAWN instrument. DAWN had co-located data with 347 AVAPS NRD41 dropsondes, providing 32,117 vertical levels for a comprehensive validation of DAWN wind retrievals. DAWN showed very good agreement with dropsondes of ~0.2 m/s bias and ~1.8 m/s RMS. Given this agreement, DAWN is considered to be a worthy reference dataset, and its retrievals have been compared to winds derived from GOES Atmospheric Motion Vectors (AMVs), Advanced Scatterometer winds (ASCAT), and model data from GFS, GEOS, and MERRA-2 to better understand the quality of our current models and satellite wind observations. The proposed presentation will provide a brief description of the DAWN instrument, discuss the synergistic observations collected across a wide range of atmospheric conditions sampled during the CPEX-CV flights, and a summary of comparisons between DAWN, GOES AMV, ASCAT, and model analyses/predictions, with an emphasis on the PBL.

DAWN↗

Buoyant production and consumption of turbulence kinetic energy in cloud-topped mixed layers

It is pointed out that studies of the entraining planetary boundary layer (PBL) have generally emphasized the role of buoyancy fluxes in driving entrainment. The buoyancy flux is proportional to the rate of conversion of the potential energy of the mean flow into the kinetic energy of the turbulence. It is not unusual for conversion to proceed in both directions simultaneously. This occurs, for instance, in both clear and cloudy convective mixed layers which are capped by inversions. A partitioning of the net conversion into positive parts, generating turbulence kinetic energy (TKE), and negative parts (TKE-consuming), would make it possible to include the positive part in the gross production rate, and closure would be achieved. Three different approaches to partitioning have been proposed. The present investigation is concerned with a comparison of the three partitioning theories. Particular attention is given to the cloud-topped mixed layer because in this case the differences between two partitioning approaches are most apparent.

Randall, D. A.↗

Detail Enhancement of AIRS/AMSU Temperature and Moisture Profiles Using a 3D Deep Neural Network

In recent decades, spaceborne microwave and hyperspectral infrared sounding instruments have significantly benefited weather forecasting and climate science. However, existing retrievals of lower troposphere temperature and humidity profiles have limitations in vertical resolution, and often cannot accurately represent key features such as the mixed layer thermodynamic structure and the inversion at the planetary boundary layer (PBL) top. Because of the existing limitations in PBL remote sensing from space, there is a compelling need to improve routine, global observations of the PBL and enable advances in scientific understanding and weather and climate prediction. To address this, we have developed a new 3D deep neural network (DNN) which enhances detail and reduces noise in Level 2 granules of temperature and humidity profiles from the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) sounder instruments aboard NASA’s Aqua spacecraft. We show that the enhancement improves accuracy and detail including key features such as capping inversions at the top of the PBL over land, resulting in improved accuracy in estimations of PBL height.

Adam B Milstein↗

On two-layer models and the similarity functions for the PBL

An operational Planetary Boundary Layer model which employs similarity principles and two-layer patching to provide state-of-the-art parameterization for the PBL flow is used to study the popularly used similarity functions, A and B. The expected trends with stratification are shown. The effects of baroclinicity, secondary flow, humidity, latitude, surface roughness variation and choice of characteristic height scale are discussed.

Brown, R. A.↗

Remote Sensing by Spaceborne Lidar Aided by Surface Returns

Spaceborne lidar offers the possibility of global mapping of clouds and atmospheric aerosols. Mapping of cloud-top heights, multiple layers of thin clouds and the depth of the planetary boundary layer (PBL), given sufficient aerosols, are applications that should be fairly easy to accomplish from space with even a modest lidar system. However, the constraints imposed on spaceborne lidar by large ranging distances, limited available power/weight, and fast moving platforms present significant challenges to achieving more quantitative retrievals such as extracting aerosol extinction profiles, PBL optical depths and cloud optical depths. Ways to take advantage of the strong signals available from ground/sea reflections to improve upon atmospheric aerosol and cloud retrievals as well as to distinguish certain surface types are explored.

Reagan, J. A.↗

Meteorological Characterization of Global Dust Sources

The global distribution of absorbing aerosols index (AI) derived from Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) measurements has been used to identify the major sources of atmospheric dust particles [Prospero, et al., 2000]. In this presentation, we will show that the TOMS aerosol index can also be used to the meteorological characterization of the source areas. We found a huge "dust belt" with a strong correlation between the TOMS index and the sea-level pressure wrapping all the major dust sources. To handle the difficulty of using quantitatively the TOMS Al and its strong dependency on the aerosol layer altitude, the Al has been correlated to the planetary boundary layer depth (PBL) and the surface wind speed. The strongest correlation is obtained with the product of these two variables and at the precise location of the dust sources identified by Prospero et al. The relation between the TOMS Al and the product of the PBL height and the surface wind speed has been used to study the interannual variability of the North-Africa dust sources in relation with the North Atlantic Oscillation (NAO). Finally, we will show that even on a short time base the variability of the TOMS Al can be related to the surface wind speed and PBL height.

Ginoux, Paul↗

Simultaneous lidar profiling of water vapor, aerosol, and wind over the eastern Pacific and implications for observational challenges on clouds, circulation, and climate sensitivity

Moist convective processes and related circulations are key components of the Earth’s climate system. Improving our understanding of moisture and cloud processes over oceans is especially challenging due to observational limitations, but also important due to the large radiative effects of cloud over ocean as well as the ties to local and global-scale circulations. A unique dataset for addressing these topics was collected over 5 flights with the NASA HALO (water vapor DIAL and aerosol HSRL) and DAWN (Doppler wind) lidar systems onboard the NASA DC-8 aircraft during the spring 2019 ADM-Aeolus Cal/Val test flight campaign. High-resolution water vapor, aerosol/cloud, and wind profiles were simultaneously collected and complimented with in situ high-resolution dropsonde measurements of temperature, relative humidity, and wind profiles. Airborne lidar measurements of these key variables captured both large-scale spatial variability across different cloud and atmospheric conditions as well as finer features, providing insight into processes from large-scale circulations down to aerosol/cloud interactions. The 5 flights spanned the northeast Pacific and southwest U.S. from 6 N to 52 N and 112 W to 157 W and captured several features of interest including moist layers from the ascending region of the Hadley circulation, very dry layers above midlatitude marine stratocumulus and cloud-free planetary boundary layers, and cloud top height and spatial variability. High covariance of aerosol and water vapor in the free troposphere was also observed for the first time. Preliminary analysis of these data sets will be presented as they apply to clouds and circulations, supplemented by model reanalysis to inform how regional water vapor structure and large-scale motion may contribute to observed shallow cloud formations and other meteorological processes that underpin our current understanding of how these state variables couple to impact the Earth’s weather and climate systems. The potential of complementary measurements in future field campaigns will also be mentioned.

Brian James Carroll↗

Large Methane Emissions From the Pantanal During Rising Water‐Levels Revealed by Regularly Measured Lower Troposphere CH 4 Profiles

Abstract The Pantanal region of Brazil is the largest seasonally flooded tropical grassland and, according to local chamber measurements, a substantial CH 4 source. CH 4 emissions from wetlands have recently become of heightened interest because global atmospheric 13 CH 4 data indicate they may contribute to the resumption of atmospheric CH 4 growth since 2007. We have regularly measured vertical atmospheric profiles for 2 years in the center of the Pantanal with the objectives to obtain an estimate of CH 4 emissions using an atmospheric approach, and provide information about flux seasonality and its relation to controlling factors. Boundary layer‐free troposphere differences observed in the Pantanal are large compared to other wetlands. Total emissions based on a planetary boundary layer budgeting technique are 2.0–2.8 TgCH 4 yr −1 (maximum flux ∼0.4 gCH 4 m −2 d −1 ) while those based on a Bayesian inversion using an atmospheric transport model are ∼3.3 TgCH 4 yr −1 . Compared to recent estimates for Amazonia (∼41 ± 3 TgCH 4 yr −1 , maximum flux ∼0.3 gCH 4 m −2 d −1 ) these emissions are not that large. Our Pantanal data suggest a clear flux seasonality with CH 4 being released in large amounts just after water levels begin to rise again after minimum levels have been reached. CH 4 emissions decline substantially once the maximum water level has been reached. While predictions with prognostic wetland CH 4 emission models agree well with the magnitude of the fluxes, they disagree with the phasing. Our approach shows promise for detecting and understanding longer‐term trends in CH 4 emissions and the potential for future wetlands CH 4 emissions climate feedbacks.

Gloor, M.↗

Enhanced Boundary Layer Height Detection Using Ceilometer, Surface Meteorology, and Radiation Products With a Random Forest Ensemble Method

This study develops and evaluates a Random Forest (RF) model for estimating planetary boundary layer height (PBLH) using 9 years of data from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) user facility, with potential application in the NOAA Surface Radiation (SURFRAD) Network. The model integrates ceilometer, surface meteorology, and radiation measurements, and is trained using thermodynamic PBLH estimates derived from radiosondes. This approach aims to bridge gaps between aerosol-based and thermodynamic-based PBLH estimates. The RF model outperformed traditional methods during daytime and better captured transition periods, demonstrating improved accuracy and robustness. At ARM SGP, it showed a substantial reduction in both bias and RMSE, with a bias near zero (−4.9 m) compared with traditional Haar Wavelet (HW) (70.9 m) and Vaisala BL-View software (124.1 m), and an RMSE of 303.2 m, lower than both BL-View (566.9 m) and HW (404.6 m). During daytime hours, RF consistently outperformed both alternatives, maintaining lower bias and RMSE across all periods. At a second evaluation site, RF achieved the lowest overall RMSE (323.7 m), similar to HW (326.4 m) and significantly better than BL-View (738.3 m). However, all models showed reduced accuracy under stable nighttime conditions, limiting the reliability of PBLH estimates. Key predictors for the model included the lifting condensation level height (LCLH), aerosol gradients, and month for seasonal variability. The study underscores the potential of integrating machine learning with multiple data sets such as surface energy and thermodynamic data to advance PBLH estimation.

boundary layer height↗

Toward a Unified Parameterization of the Boundary Layer and Moist Convection: A New Type of Mass-Flux Model - Part 1

Higher-order closure (HOC) models have been proposed for parameterization of the turbulent planetary boundary layer (PBL). HOC models must include closures for higher-order moments (e.g., fourth moments in third-order closure models), for pressure terms, and for dissipation terms. Mass-flux closure (MFC) models have been proposed for parameterization of cumulus convection and, more recently, the convective PBL. MFC models include closures for lateral mass exchanges and for pressure terms (which are usually ignored). The authors developed a new kind of model that combines HOC and MFC, which they hope will be useful for the parameterization of both the PBL and cumulus convection, in a unified framework. Such a model is particularly well suited to regimes in which the PBL turbulence and the cumulus convection are not well separated, for example, the broken stratocumulus and shallow cumulus regimes. The model makes use of an assumed joint probability distribution for the variables of interest, and the equations typically used in HOC models can be derived by integrating over the distribution. Accordingly, the model is called Assumed-Distribution Higher-Order Closure (ADHOC). The prognostic variables of ADHOC are the mean state, the second and third moments of the vertical velocity, and the vertical fluxes of other quantities of interest. All of the parameters of the distribution can be determined from the predicted moments, thereafter the joint distribution is effectively known, and so any and all moments can be constructed as needed. In this way, the usual closure problem of "higher moments" is avoided. The pressure-term parameterizations previously developed for HOC models are used to predict the convective fluxes and the moments of the vertical velocity. In companion papers, parameterizations of lateral mass exchanges and subplume-scale fluxes are presented, and then ADHOC is applied to several observationally based tropical, subtropical, and dry convective boundary layers.

Lappen, Cara-Lyn↗

Atmospheric Science Measurements by the EOS Geoscience Laser Altimeter System

Scheduled for Launch in July 2001, the Geoscience Laser Altimeter System (GLAS) is to be the first satellite instrument to provide full global lidar profiling of clouds and aerosol in the earth's atmosphere. GLAS is an EOS program instrument that is on its own satellite, now called the Ice, Cloud and land Elevation Satellite. The instrument is both a surface laser ranging system and an atmospheric profiling lidar. A most important surface measurement for the instrument is to study the change in the mass balance of the polar ice sheets by measuring the change in regional altitudes to an accuracy of 1.5 cm per year. The strategy to combine the surface measurement with a Cloud and aerosol lidar profiling mission is based on the compatibility of the altimetry instrument requirements with those for the required lidar measurements. The primary atmospheric science goal of the GLAS cloud and aerosol measurement is to determine the radiative forcing and vertically resolved atmospheric heating rate due to cloud and aerosol by directly observing the vertical structure and magnitude of cloud and aerosol parameters that are important for the radiative balance of the earth-atmosphere system, but which are ambiguous or impossible to obtain from existing or planned passive remote sensors. A further goal is to directly measure the height of atmospheric transition layers (inversions) which are important for dynamics and mixing, the planetary boundary layer and lifting condensation level.

Spinhirne, James↗

Vertical transport of water in the Martian boundary layer

We are continuing our examination of the transport of H2O through the martian boundary layer, and we have written a one-dimensional numerical model of the exchange of H2O between the atmosphere and subsurface of Mars through the planetary boundary layer (PBL). Our goal is to explore the mechanisms of H2O exchange, and to elucidate the role played by the regolith in the local H2O budget. The atmospheric model includes effects of Coriolis, pressure gradient, and frictional forces for momentum, as well as radiation, sensible heat flux, and advection for heat. The model differs from Flasar and Goody by use of appropriate Viking-based physical constants and inclusion of the radiative effects of atmospheric dust. We specify the pressure gradient force or compute it from a simple slope model. The subsurface model accounts for conduction of heat and diffusion of H2O through a porous adsorbing medium in response to diurnal forcing. The model is initialized with depth-independent H2O concentrations (2 kg M(exp -3)) in the regolith, and a dry atmosphere. The model terminates when the atmospheric H2O column abundance stabilizes at 0.1 percent per sol.

Zent, Aaron P.↗

The Geoscience Laser Altimeter System (GLAS) for the ICESAT Mission

Accurate measurements of surface heights and atmospheric backscatter have been demonstrated with the SLA, MOLA and LITE space lidar. Recent MOLA measurements of the Mars surface have 40 cm resolution and have reduced the global uncertainty in Mars topography from a few km to approx. 10 m. GLAS is a next generation lidar being developed as part of NASA's Icesat Mission for Earth orbit . The GLAS design combines a 10 cm precision surface lidar with a sensitive dual wavelength cloud and aerosol lidar. GLAS will precisely measure the heights of the Earth's polar ice sheets, determine the height profiles of the Earth's land topography, and profile the vertical backscatter of clouds and aerosols on a global scale. GLAS will fly on a small dedicated spacecraft in a polar orbit at 598 km altitude with an inclination of 94 degrees. GLAS is scheduled to launch in summer 2001 and to operate continuously for a minimum of 3 years with a goal of 5 years. The primary mission for GLAS is to measure the seasonal and annual changes in the heights of the Greenland and Antarctic ice sheets. GLAS will measure the vertical distance to the ice sheet from orbit with 1064 nm pulses from a Nd:Yag laser at 40 Hz. Each 5 nsec wide laser pulse is used for a single range measurement. When over land GLAS will profile the heights of the topography and vegetation. The GLAS receiver uses a I m diameter telescope and a Si APD detector. The detector signal is sampled by an all digital receiver which records each surface echo waveform with I nsec resolution and a stored echo record lengths of either 200, 400, or 600 samples. Analysis of the echo waveforms within the instrument permits discrimination between cloud and surface echoes. Ground based echo analysis permits precise ranging, determining the roughness or slopes of the surface as well as the vertical distributions of vegetation illuminated by the laser, Errors in knowledge of the laser beam pointing angle can bias height measurements of sloped surfaces. For surfaces with 2 deg. slopes, knowledge of pointing angle of the beam centroid to about 8 urad is required to achieve 10 cm height accuracy. GLAS uses a stellar reference system (SRS) to determine the pointing angle of each laser firing relative to inertial space. The SRS uses a high precision star camera oriented toward local zenith whose measurements are combined with a gyroscope to determine the inertial orientation of the SRS optical bench. The far field pattern of each laser pulse is measured with a laser reference system (LRS). Optically measuring each laser far field pattern relative to the star camera and gyroscope permits the angular offsets of each laser pulse to be determined. GLAS will also determine the vertical distributions of clouds and aerosols by measuring atmospheric backscatter profiles at both 1064 and 532 nm. The 1064 nm measurements use an analog detector and profile the height and vertical structure of thicker clouds. Measurements at 532 nm use new highly sensitive photon counting detectors, and measure the height distributions of very thin clouds and aerosol layers. With averaging these can be used to determine the height of the planetary boundary layer. The instrument design and expected performance will be discussed.

Abshire, James B.↗

The Geoscience Laser Altimeter System (GLAS) for the ICESAT Mission

The Laser In space Technology Experiment, Shuttle Laser Altimeter and the Mars Observer Laser Altimeter have demonstrated accurate measurements of atmospheric backscatter and Surface heights from space. The recent MOLA measurements of the Mars surface have 40 cm vertical resolution and have reduced the global uncertainty in Mars topography from a few km to about 5 m. The Geoscience Laser Altimeter System (GLAS) is a next generation lidar for Earth orbit being developed as part of NASA's Icesat Mission. The GLAS design combines a 10 cm precision surface lidar with a sensitive dual wavelength cloud and aerosol lidar. GLAS will precisely measure the heights of the Earth's polar ice sheets, establish a grid of accurate height profiles of the Earth's land topography, and profile the vertical backscatter of clouds and aerosols on a global scale. GLAS is being developed to fly on a small dedicated spacecraft in a polar orbit with a 590 630 km altitude at inclination of 94 degrees. GLAS is scheduled to launch in the summer 2001 and to operate continuously for a minimum of 3 years with a goal of 5 years. The primary mission for GLAS is to measure the seasonal and annual changes in the heights of the Greenland and Antarctic ice sheets. GLAS will continuously measure the vertical distance from orbit to the Earth's surface with 1064 nm pulses from a ND:YAG laser at a 40 Hz rate. Each 5 nsec wide laser pulse is used to produce a single range measurement, and the laser spots have 66 m diameter and about 170 m center-center spacings. When over land GLAS will profile the heights of the topography and vegetation. The GLAS receiver uses a 1 m diameter telescope and a Si APD detector. The detector signal is sampled by an all digital receiver which records each surface echo waveform with I nsec resolution and a stored echo record lengths of either 200, 400, or 600 samples. Analysis of the echo waveforms within the instrument permits discrimination between cloud and surface echoes. Ground based echo analysis permits precise ranging, determining the roughness or slopes of the surface as well as the vertical distributions of vegetation illuminated by the laser. Accurate knowledge of the laser beam's pointing angle is needed to prevent height biases when over sloped surfaces. For surfaces with 2 deg. slopes, knowledge of pointing angle of the beam's centroid to about 8 urad is needed to achieve 10 cm height accuracy. GLAS uses a stellar reference system (SRS) to determine the pointing angle of each laser firing relative to inertial space. The SRS uses a high precision star camera oriented toward local zenith and a gyroscope to determine the inertial orientation of the SRS optical bench. The far field pattern of each laser is measured pulse relative to the star camera with a laser reference system (LRS). Optically measuring each laser far field pattern relative to the orientation of the star camera and gyroscope permits the precise pointing angle of each laser pulse to be determined. GLAS will also determine the vertical distributions of clouds and aerosols by measuring the vertical profile of laser energy backscattered by the atmosphere at both 1064 and 532 nm. The 1064 nm measurements use the Si APD detector and profile the height and vertical structure of thicker clouds. The measurements at 532 nm use new highly sensitive photon counting, detectors, and measure the height distributions of very thin Clouds and aerosol layers. With averaging these can be used to determine the height of the planetary boundary layer. The instrument design and expected performance will be discussed.

Abshire, James B.↗

Boundary Layer Height Variation over the Savannah River Site during a Heat Wave

With the number of heat waves expect to increase in both in their severity and frequency in the coming years, an insight into their impact on planetary boundary layer (PBL) heights is essential for one development of future emergency and safety plans. Using High-Resolution Rapid Refresh (HRRR) atmospheric model output, an analysis is done on the effects a heat wave has on PBL heights and temperature inversions across the Savannah River Site (SRS). This study showed that due to its adjacency to anthropogenic land use, SRS experiences a non-negligible gradient in its PBL height, with higher heights to the northwest. The singular location PBL heigh measurement and forecasts for SRS do not account for this gradient, which has potential implications on pollutant and smoke dispersion onsite. During a heat wave this gradient is present but PBL heights are less impacted than surrounding developed areas, possibly attributable to the woody wetlands that surround the Savannah River's banks. Additionally, the heat wave appears to strongly enhance the nocturnal temperature inversions that the site and surrounding areas experience. This is possibly due to increased stability from higher pressure conditions, which are often associated with heat waves. This influence on nocturnal inversions, however, is limited to their intensity, leaving their timing relatively unaltered. The impact a heat wave has on PBL heights and temperature inversions across SRS is seen to be more dependent on adjacent land use and features rather than the unique land use types onsite.

54 ENVIRONMENTAL SCIENCES↗

Low ozone dry deposition rates to sea ice during the MOSAiC field campaign: Implications for the Arctic boundary layer ozone budget

Dry deposition to the surface is one of the main removal pathways of tropospheric ozone (O 3 ). We quantified for the first time the impact of O 3 deposition to the Arctic sea ice on the planetary boundary layer (PBL) O 3 concentration and budget using year-round flux and concentration observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign and simulations with a single-column atmospheric chemistry and meteorological model (SCM). Based on eddy-covariance O 3 surface flux observations, we find a median surface resistance on the order of 20,000 s m –1 , resulting in a dry deposition velocity of approximately 0.005 cm s –1 . This surface resistance is up to an order of magnitude larger than traditionally used values in many atmospheric chemistry and transport models. The SCM is able to accurately represent the yearly cycle, with maxima above 40 ppb in the winter and minima around 15 ppb at the end of summer. However, the observed springtime ozone depletion events are not captured by the SCM. In winter, the modelled PBL O 3 budget is governed by dry deposition at the surface mostly compensated by downward turbulent transport of O 3 towards the surface. Advection, which is accounted for implicitly by nudging to reanalysis data, poses a substantial, mostly negative, contribution to the simulated PBL O 3 budget in summer. During episodes with low wind speed (<5 m s –1 ) and shallow PBL (<50 m), the 7-day mean dry deposition removal rate can reach up to 1.0 ppb h –1 . Our study highlights the importance of an accurate description of dry deposition to Arctic sea ice in models to quantify the current and future O 3 sink in the Arctic, impacting the tropospheric O 3 budget, which has been modified in the last century largely due to anthropogenic activities.

54 ENVIRONMENTAL SCIENCES↗

Improving Boundary Layer Data Assimilation in the NASA GEOS System

The Goddard Earth Observing System (GEOS) developed by the NASA Global Modeling and Assimilation Office assimilates a wide range of observations to support various NASA Earth Science missions. As Measurement of planetary boundary layer (PBL) was designated as an incubation program by the 2018 Decadal Survey, we have aimed to improve PBL thermodynamic structure using data from multiple observing systems. In particular, we have developed strategies and infrastructure to assimilate PBL height (PBLH) data derived from radiosondes, GNSS radio occultation, space-based lidar (CALIPSO, CATS, IceSat-2), ground-based lidar (MPLNET) and radar wind profilers to produce global PBL height analyses. We have also explored methods to better represent capping inversions by using PBLH data together with other observations in the GEOS to adjust background error covariance and enhance model PBL parameterization performance.

Y. Zhu↗