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At least 379 records · Page 21

Using an Altimeter-Derived Internal Tide Model to Remove Tides from in Situ Data

Internal waves at tidal frequencies, i.e., the internal tides, are a prominent source of variability in the ocean associated with significant vertical isopycnal displacements and currents. Because the isopycnal displacements are caused by ageostrophic dynamics, they contribute uncertainty to geostrophic transport inferred from vertical profiles in the ocean. Here it is demonstrated that a newly developed model of the main semidiurnal (M2) internal tide derived from satellite altimetry may be used to partially remove the tide from vertical profile data, as measured by the reduction of steric height variance inferred from the profiles. It is further demonstrated that the internal tide model can account for a component of the near-surface velocity as measured by drogued drifters. These comparisons represent a validation of the internal tide model using independent data and highlight its potential use in removing internal tide signals from in situ observations.

Zaron, Edward D.↗

Constraining Clouds and Convective Parameterizations in A Climate Model Using Paleoclimate Data

Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity. We provide a proof-of-concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere-only version of the Goddard Institute for Space Studies Model E2.1 simulations by evaluating model biases in the present-day runs using multiple satellite climatologies and by comparing simulated δ 18 O of precipitation (δ 18 O p ), known to be sensitive to parameterization schemes, with a global database of speleothem δ 18 O records covering the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) periods. Relative to modern interannual variability, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ 18 O p values across all time periods, along with LGM and MH δ 18 O p anomalies relative to the PI, better than the default parameterization. No single set of parameterizations worked well in all climate states, likely due to the non-stationarity of cloud feedbacks under varying boundary conditions. Future work that involves varying multiple parameter sets simultaneously with coupled ocean feedbacks will likely provide improved constraints on cloud and convective parameterizations.

cloud and convective parameterization↗

Comparison of Optimum Interpolation and Cressman Analyses

The objective of this investigation is to develop a state-of-the-art optimum interpolation (O/I) objective analysis procedure for use in numerical weather prediction studies. A three-dimensional multivariate O/I analysis scheme has been developed. Some characteristics of the GLAS O/I compared with those of the NMC and ECMWF systems are summarized. Some recent enhancements of the GLAS scheme include a univariate analysis of water vapor mixing ratio, a geographically dependent model prediction error correlation function and a multivariate oceanic surface analysis.

Baker, W. E.↗

Shape of the ocean surface and implications for the Earth's interior: GEOS-3 results

A new set of 1 deg x 1 deg mean free air anomalies was used to construct a gravimetric geoid by Stokes' formula for the Indian Ocean. Utilizing such 1 deg x 1 deg geoid comparisons were made with GEOS-3 radar altimeter estimates of geoid height. Most commonly there were constant offsets and long wavelength discrepancies between the two data sets; there were many probable causes including radial orbit error, scale errors in the geoid, or bias errors in altitude determination. Across the Aleutian Trench the 1 deg x 1 deg gravimetric geoids did not measure the entire depth of the geoid anomaly due to averaging over 1 deg squares and subsequent aliasing of the data. After adjustment of GEOS-3 data to eliminate long wavelength discrepancies, agreement between the altimeter geoid and gravimetric geoid was between 1.7 and 2.7 meters in rms errors. For purposes of geological interpretation, techniques were developed to directly compute the geoid anomaly over models of density within the Earth. In observing the results from satellite altimetry it was possible to identify geoid anomalies over different geologic features in the ocean. Examples and significant results are reported.

Chapman, M. E.↗

Improving Ocean Angular Momentum Estimates Using a Model Constrained by Data

Ocean angular momentum (OAM) calculations using forward model runs without any data constraints have, recently revealed the effects of OAM variability on the Earth's rotation. Here we use an ocean model and its adjoint to estimate OAM values by constraining the model to available oceanic data. The optimization procedure yields substantial changes in OAM, related to adjustments in both motion and mass fields, as well as in the wind stress torques acting on the ocean. Constrained and unconstrained OAM values are discussed in the context of closing the planet's angular momentum budget. The estimation procedure, yields noticeable improvements in the agreement with the observed Earth rotation parameters, particularly at the seasonal timescale. The comparison with Earth rotation measurements provides an independent consistency check on the estimated ocean state and underlines the importance of ocean state estimation for quantitative. studies of the variable large-scale oceanic mass and circulation fields, including studies of OAM.

Ponte, Rui M.↗

Evaluation of single-footprint AIRS CH4 Profile Retrieval Uncertainties Using Aircraft Profile Measurements

We evaluate the uncertainties of methane optimal estimation retrievals from single footprint thermal infrared observations from the Atmospheric Infrared Sounder (AIRS). These retrievals are primarily sensitive to atmospheric methane in the mid-troposphere through the lower stratosphere (~2 to ~17 km). We compare to in situ observations made from aircraft during the Hiaper Pole to Pole Observations (HIPPO), the NASA Atmospheric Tomography Mission (ATom) campaigns, and from the NOAA ESRL aircraft network, between the surface and 5-13 km, across a range of years, latitudes between 60 S to 80 N, and over land and ocean. After a global, pressure dependent bias correction, we find that the land and ocean have similar biases and that the reported observation error (combined measurement and interference errors) of ~27 ppb is consistent with the standard deviation between aircraft and individual AIRS observations. A single measurement has measurement (noise related) uncertainty of ~17 ppb, a ~20 ppb uncertainty from radiative interferences (e.g. from water, temperature, etc.), and ~ 30 ppb due to “smoothing error”, which is partially removed when making comparisons to in situ measurements or models in a way that account for this regularization. We estimate a 16 ppb validation error because the aircraft typically did not measure methane at altitudes where the AIRS measurements have some sensitivity, e.g. the stratosphere. Daily averaged AIRS measurements of at least 9 observations over spatio-temporal domains of < 1 degree and 1 hour have a standard deviation of ~17 ppb versus aircraft, likely because the observation errors from temperature and water vapor (for example) are only partly reduced through averaging. Seasonal averages can reduce this ~17 ppb uncertainty further to ~10 ppb, as determined through comparison with NOAA aircraft, likely because uncertainties related to radiative effects of temperature and water vapor can be reduced when averaged over a season.

Susan Kulawik↗

Estimates of Diurnal and Daily Net Primary Productivity Using the Geostationary Ocean Color Imager (GOCI) Data

For the past three decades, polar-orbiting ocean color satellites have provided local, regional to global scale estimates of oceanic net primary production that have greatly aided studies of ocean carbon cycling, food web dynamics and climate change. Despite considerable progress, accurate estimates of daily ocean productivity from space have not been realized because polar-orbiting satellites are unable to account for variations in phytoplankton physiology and carbon fixation rates from changing incident irradiance levels over the course of the day. Here we have attempted to exploit the unique short-temporal measurements provided by the Korean Geostationary Ocean Color Imager (GOCI), to obtain for the first time, diurnal and daily measurements of surface- and euphotic-column integrated Net Primary Productivity (NPP). These estimates are based on the Absorption Based Productivity Model (AbPM), and are calibrated with a bio-optical database of measurements made at different times of the day during the Korea-US Ocean Color (KORUS-OC) cruise in May–June 2016. Photo-physiological rate estimates, varied across different water types encountered around the Korean Peninsula, but on account of their limited number, were regionally scaled through the use of dynamic optical-biogeochemical (O-BGC) Biomes. Comparisons of GOCI derived estimates of daily and weekly integrated NPP against in-situ measurements, clearly underscore the superiority of geostationary over polar-orbiting ocean color satellites, which consider the strong short-term fluctuations in phytoplankton light absorption and incident irradiance fields over the course of the day.

Diurnal productivity↗

Modeling Impacts of Dust Mineralogy on Fast Climate Response

Mineralogical composition drives dust impacts on Earth's climate systems. However, most climate models still use homogeneous dust, without accounting for the temporal and spatial variation in mineralogy. To quantify the radiative impact of resolving dust mineralogy on Earth's climate, we implement and simulate the distribution of dust minerals (i.e., illite, kaolinite, smectite, hematite, calcite, feldspar, quartz, and gypsum) from Claquin et al. (1999) (C1999) and activate their interaction with radiation in the GFDL AM4.0 model. Resolving mineralogy reduces dust absorption compared to the homogeneous dust used in the standard GFDL AM4.0 model that assumes a globally uniform hematite volume content of 2.7 % (HD27). The reduction in dust absorption results in improved agreement with observation-based single-scattering albedo (SSA), radiative fluxes from CERES (the Clouds and the Earth's Radiant Energy System), and land surface temperature from the CRU (Climatic Research Unit) compared to the baseline HD27 model version. It also results in distinct radiative impacts on Earth's climate over North Africa. Over the 19-year (from 2001 to 2019) modeled period during JJA (June–July–August), the reduction in dust absorption in AM4.0 leads to a reduction of over 50 % in net downward radiation across the Sahara and approximately 20 % over the Sahel at the top of the atmosphere (TOA) compared to the baseline HD27 model version. The reduced dust absorption weakens the atmospheric warming effect of dust aerosols and leads to an alteration in land surface temperature, resulting in a decrease of 0.66 K over the Sahara and an increase of 0.7 K over the Sahel. The less warming in the atmosphere suppresses ascent and weakens the monsoon inflow from the Gulf of Guinea. This brings less moisture to the Sahel, which combined with decreased ascent induces a reduction of precipitation. To isolate the effect of reduced absorption compared to resolving spatial and temporal mineralogy, we carry out a simulation where the hematite volume content of homogeneous dust is reduced from 2.7 % to 0.9 % (HD09). The dust absorption (e.g., single-scattering albedo) of HD09 is comparable to that of the mineralogically speciated model on a global mean scale, albeit with a lower spatial variation that arises solely from particle size. Comparison of the two models indicates that the spatial inhomogeneity in dust absorption resulting from resolving mineralogy does not have significant impacts on Earth's radiation and climate, provided there is a similar level of dust absorption on a global mean scale before and after resolving dust mineralogy. However, uncertainties related to emission and distribution of minerals may blur the advantages of resolving minerals to study their impact on radiation, cloud properties, ocean biogeochemistry, air quality, and photochemistry. On the other hand, lumping together clay minerals (i.e., illite, kaolinite, and smectite), but excluding externally mixed hematite and gypsum, appears to provide both computational efficiency and relative accuracy. Nevertheless, for specific research, it may be necessary to fully resolve mineralogy to achieve accuracy.

Soil dust↗

Present-day plate motions

A data set comprising 110 spreading rates, 78 transform fault azimuths and 142 earthquake slip vectors was inverted to yield a new instantaneous plate motion model, designated RM2. The mean averaging interval for the relative motion data was reduced to less than 3 My. A detailed comparison of RM2 with angular velocity vectors which best fit the data along individual plate boundaries indicates that RM2 performs close to optimally in most regions, with several notable exceptions. On the other hand, a previous estimate (RM1) failed to satisfy an extensive set of new data collected in the South Atlantic Ocean. It is shown that RM1 incorrectly predicts the plate kinematics in the South Atlantic because the presently available data are inconsistent with the plate geometry assumed in deriving RM1. It is demonstrated that this inconsistency can be remedied by postulating the existence of internal deformation with the Indian plate, although alternate explanations are possible.

Minster, J. B.↗

The Effect of Incident Light Polarization on Vegetation Bidirectional Reflectance Factor

The Laboratory-based Bidirectional Reflectance Factor (BRF) polarization study of vegetation is presented in this paper. The BRF was measured using a short-arc Xenon lamp/monochromator assembly producing an incoherent, tunable light source with a well-defined spectral bandpass at visible and near-infrared wavelengths of interest at 470 nm and 870 nm and coherent light source at 1.656 microns. All vegetation samples were measured using P and S linearly polarized incident light over a range of incident and scatter angles. By comparing these results, we quantitatively examine how the BRF of the samples depends on the polarization of the incident light. The differences are significant, depend strongly on the incident and scatter angles, and can be as high as 120% at 67 deg incident and 470nm. The global nature of Earth's processes requires consistent long-term calibration of all instruments involved in data retrieval. The BRF defines the reflection characteristics of Earth surface. It provides the reflectance of a target in a specific direction as a function of illumination and viewing geometry. The BRF is a function of wavelength and reflects the structural and optical properties of the surface. Various space and airborne radiometric and imaging remote sensing instruments are used in the remote sensing characterization of vegetation canopies and soils, oceans, or especially large pollution sources. The satellite data is validated through comparison with airborne, ground-based and laboratory-based data in an effort to fully understand the vegetation canopy reflectance, The Sun's light is assumed to be unpolarized at the top of the atmosphere; however it becomes polarized to some degree due to atmospheric effects by the time it reaches the vegetation canopy. Although there are numerous atmospheric correction models, laboratory data is needed for model verification and improvement.

Georgiev, Georgi T.↗

Direct Radiative Effect of Aerosols Based on PARASOL and OMI Satellite Observations

Accurate portrayal of the aerosol characteristics is crucial to determine aerosol contribution to the Earth's radiation budget. We employ novel satellite retrievals to make a new measurement-based estimate of the shortwave direct radiative effect of aerosols (DREA), both over land and ocean. Global satellite measurements of aerosol optical depth, single-scattering albedo (SSA), and phase function from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) are used in synergy with OMI (Ozone Monitoring Instrument) SSA. Aerosol information is combined with land-surface bidirectional reflectance distribution function and cloud characteristics from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products. Eventual gaps in observations are filled with the state-of-the-art global aerosol model ECHAM5-HAM2. It is found that our estimate of DREA is largely insensitive to model choice. Radiative transfer calculations show that DREA at top-of-atmosphere is −4.6 +/- 1.5 W/sq m for cloud-free and −2.1 +/- 0.7 W/sq m for all-sky conditions, during year 2006. These fluxes are consistent with, albeit generally less negative over ocean than, former assessments. Unlike previous studies, our estimate is constrained by retrievals of global coverage SSA, which may justify different DREA values. Remarkable consistency is found in comparison with DREA based on CERES (Clouds and the Earth's Radiant Energy System) and MODIS observations.

Globalsatellite measurements↗

Inference of subsurface thermohaline structure from fields measurable by satellite

Satellites now provide global measurements of the ocean's surface height and temperature. Ocean climatologies for the northwest Pacific and northwest Atlantic Oceans that relate sea surface height, sea surface temperature, day of the year, latitude, and longitude to temperature and salinity profiles were produced using least-squares regression. These analyses use over 33,000 profiles of historical temperature and salinity data and are considerably streamlined and compacted by expressing each profile in terms of empirical orthogonal functions. Evaluations and error analyses of the climatologies, including a comparison to the navy's Generalized Digital Environmental Model, were performed and differences between the regions are discussed. Two sample vertical sections are shown to be closely reproduced with the climatologies. Climatologies based on surface height and temperature are found to offer considerable improvement over climatologies based only on position.

Carnes, Michael R.↗

A New Atmosphere-Ocean Model for Studying Air-Sea Interactions and Coupled Data Assimilation

During the last two plus decades, The Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have developed, respectively, atmosphere-only and ocean-only global general circulation models. These two models (GEOS and MITgcm) have demonstrated their data assimilation capabilities with the recent releases of the Modern Era Reanalysis for Research Applications, Version 2 (MERRA-2) atmospheric reanalysis and the Estimating the Circulation and Climate of the Ocean, Version 4 (ECCO-v4) ocean (and sea ice) state estimate. Independently, the two modeling groups have also produced global atmosphere-only and ocean-only simulations with km-scale grid spacing which proved invaluable for process studies and for the development of satellite and in-situ sampling strategies.Recently, a new effort has been made to couple these two models and to leverage their data-assimilation and high resolution capabilities (i.e., eddy-permitting ocean, cloud-permitting atmosphere). The focus in the model development is put on sub-seasonal to decadal time scales. In this talk, I discuss the new coupled model and present some first coupled simulation results. This will include a high-resolution coupled GEOS-MIT simulation, whereby we have coupled a cubed-sphere-720 (~ 1/8°) configuration of the GEOS atmosphere to a lat-lon-cap-1080 (~ 1/12°) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere set-up to equivalent atmosphere-only and ocean-only simulations. In the comparisons we focus in particular on the differences in air-sea interactions between sea surface temperature (SST) and wind for the coupled and uncoupled simulations.

Strobach, Ehud↗

Modeling of Convective-Stratiform Precipitation Processes: Sensitivity to Partitioning Methods and Numerical Advection Schemes

Six different convective-stratiform separation techniques, including a new technique that utilizes the ratio of vertical and terminal velocities, are compared and evaluated using two-dimensional numerical simulations of a tropical [Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE)] and midlatitude continental [Preliminary Regional Experiment for STORM-Central (PRESTORM)] squall line. The simulations are made using two different numerical advection schemes: 4th order and positive definite advection. Comparisons are made in terms of rainfall, cloud coverage, mass fluxes, apparent heating and moistening, mean hydrometeor profiles, CFADs (Contoured Frequency with Altitude Diagrams), microphysics, and latent heating retrieval. Overall, it was found that the different separation techniques produced results that qualitatively agreed. However, the quantitative differences were significant. Observational comparisons were unable to conclusively evaluate the performance of the techniques. Latent heating retrieval was shown to be sensitive to the use of separation technique mainly due to the stratiform region for methods that found very little stratiform rain. The midlatitude PRESTORM simulation was found to be nearly invariant with respect to advection type for most quantities while for TOGA COARE fourth order advection produced numerous shallow convective cores and positive definite advection fewer cells that were both broader and deeper penetrating above the freezing level.

Lang, Steve↗

SeaWinds Scatterometer Wind Vector Retrievals Within Hurricanes Using AMSR and NEXRAD to Perform Corrections for Precipitation Effects: Comparison of AMSR and NEXRAD Retrievals of Rain

The opportunity provided by satellite scatterometers to measure ocean surface winds in strong storms and hurricanes is diminished by the errors in the received backscatter (SIGMA-0) caused by the attenuation, scattering and surface roughening produced by heavy rain. Providing a good rain correction is a very challenging problem, particularly at Ku band (13.4 GHz) where rain effects are strong. Corrections to the scatterometer measurements of ocean surface winds can be pursued with either of two different methods: empirical or physical modeling. The latter method is employed in this study because of the availability of near simultaneous and collocated measurements provided by the MIDORI-II suite of instruments. The AMSR was designed to measure atmospheric water-related parameters on a spatial scale comparable to the SeaWinds scatterometer. These quantities can be converted into volumetric attenuation and scattering at the Ku-band frequency of SeaWinds. Optimal estimates of the volume backscatter and attenuation require a knowledge of the three dimensional distribution of reflectivity on a scale comparable to that of the precipitation. Studies selected near the US coastline enable the much higher resolution NEXRAD reflectivity measurements evaluate the AMSR estimates. We are also conducting research into the effects of different beam geometries and nonuniform beamfilling of precipitation within the field-of-view of the AMSR and the scatterometer. Furthermore, both AMSR and NEXRAD estimates of atmospheric correction can be used to produce corrected SIGMA-0s, which are then input to the JPL wind retrieval algorithm.

SeaWinds↗

Comparison of Dust Optical Depth From Multi-Sensor Products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) Dust Reanalysis Over North Africa, the Middle East, and Europe

Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.

Michail Mytilinaios↗

Large Eddy Simulations of Upper-Ocean Turbulence Across the Equatorial Pacific Cold Tongue

Turbulence in the equatorial Pacific cold tongue plays multiple roles in the sea-surface temperature budget. However, observations of turbulence are limited to a handful of field experiments lasting from a few days to one month at 0 N , 140 W, and the key turbulent fluxes can only be inferred. Although explicit simulations of turbulence resolve these fluxes, the required large eddy simulations (LES) are costly and thus also limited to a few weeks. A two-fold hypothesis motivates this contribution to the PUMP pre-field modelling experiments in support of TPOS: 1) that there exist useful relationships between the surface wind, wave, and buoyancy forcing, oceanic shear and stratification, and turbulent mixing, but 2) these relationships differ between regions of equatorial dynamics (f~0) and higher latitudes, such that the state space is insufficiently sampled to understand these relationships and represent them in ocean general circulation models (OGCM). To address the lack of observations, we simulated 35 continuous days of upper ocean turbulence using LES during October-November 1985 at sites in two regions (70 days in total) of the cold tongue: 0 N, 140 W and 3 N, 140 W. The model reproduces many features of the observed turbulence at 0,140W, including the “deep-cycle” observed by Gregg et al. (1985) Nature and the turbulent pulses every few hours during the night and in the early morning. Furthermore, the results at 3 N support the hypothesis advanced by Cherian et al. (2021) JPO that strong, but intermittent deep-cycle turbulence is observed to the north of the equator in the presence of strong shear associated with Tropical Instability Waves. Comparisons with the K-profile parameterization (KPP) scheme show that additional tuning of the KPP parameters can reduce differences between the turbulent fluxes produced by KPP and LES at both sites. The results will suggest modifications to OGCMs and already emphasize the need for a more extensive measurements of vertical profiles of shear, stratification and turbulent mixing to reveal the spatio-temporal structure of turbulence and how it relates to forcing, shear and stratification across the equatorial Pacific Cold tongue.

Large Eddy Simulations↗

An Improved Retrieval of Tropospheric Nitrogen Dioxide from GOME

We present a retrieval of tropospheric nitrogen dioxide (NO2) columns from the Global Ozone Monitoring Experiment (GOME) satellite instrument that improves in several ways over previous retrievals, especially in the accounting of Rayleigh and cloud scattering. Slant columns, which are directly fitted without low-pass filtering or spectral smoothing, are corrected for an artificial offset likely induced by spectral structure on the diffuser plate of the GOME instrument. The stratospheric column is determined from NO2 columns over the remote Pacific Ocean to minimize contamination from tropospheric NO2. The air mass factor (AMF) used to convert slant columns to vertical columns is calculated from the integral of the relative vertical NO2 distribution from a global 3-D model of tropospheric chemistry driven by assimilated meteorological data (Global Earth Observing System (GEOS)-CHEM), weighted by altitude dependent scattering weights computed with a radiative transfer model (Linearized Discrete Ordinate Radiative Transfer), using local surface albedos determined from GOME observations at NO2 wavelengths. The AMF calculation accounts for cloud scattering using cloud fraction, cloud top pressure, and cloud optical thickness from a cloud retrieval algorithm (GOME Cloud Retrieval Algorithm). Over continental regions with high surface emissions, clouds decrease the AMT by 20- 30% relative to clear sky. GOME is almost twice as sensitive to tropospheric NO2 columns over ocean than over land. Comparison of the retrieved tropospheric NO2 columns for July 1996 with GEOS-CHEM values tests both the retrieval and the nitrogen oxide radical (NOx) emissions inventories used in GEOS-CHEM. Retrieved tropospheric NO2 columns over the United States, where NOx emissions are particularly well known, are within 18% of GEOS-CHEM columns and are strongly spatially correlated (r = 0.78, n = 288, p less than 0.005). Retrieved columns show more NO2 than GEOS-CHEM columns over the Transvaal region of South Africa and industrial regions of the northeast United States and Europe. They are lower over Houston, India, eastern Asia, and the biomass burning region of central Africa, possibly because of biases from absorbing aerosols.

Martin, Randall V.↗