ALBERT

Description: Reactive nitrogen (N r ) is an essential nutrient to plants and a limiting element for growth in many ecosystems, but it can have harmful effects on ecosystems when in excess. Satellite-derived surface observations are used together with a dry deposition model to estimate the dry deposition flux of the most abundant short-lived nitrogen species, NH 3 and NO 2 , over North America during the 2013 warm season. These fluxes demonstrate that the NH 3 contribution dominates over NO 2 for most regions (comprising ~85% of their sum in Canada and ~65% in the U.S.), with some regional exceptions (e.g. Alberta and northeastern U.S.). Nationwide, ~51 t of N from these species were dry deposited in the U.S., approximately double the ~28 t in Canada over this period. Forest fires are shown to be the major contributor of dry deposition of N r from NH 3 in northern latitudes, leading to deposition fluxes 2–3 times greater than from expected amounts without fires. ©2017. Her Majesty the Queen in Right of Canada. Reproduced with the permission of the Minister of the Environment.

Description: Presented here are comparisons between the Infrared Atmospheric Sounding instrument (IASI) and the "Line-By- Line Radiative Transfer Model" (LBLRTM). Spectral residuals from radiance closure studies during the IASI JAIVEx validation campaign provide insight into a number of spectroscopy issues relevant to remote sounding of temperature, water vapor and trace gases from IASI. In order to perform quality IASI trace gas retrievals the temperature and water vapor fields must be retrieved as accurately as possible. In general, the residuals in the CO2 ν2 region are of the order of the IASI instrument noise. However, outstanding issues in the CO2 spectral regions remain. There is a large residual ~−1.5 K in the 667 cm−1 Q-branch, and residuals in the CO2 ν2 and N2O/CO2 ν3 spectral regions that sample the troposphere are inconsistent, with the N2O/CO2 ν3 region being too negative (warmer) by ~0.6 K. Residuals on this lower wavenumber side of the CO2 ν3 band will be improved by line parameter updates, while future efforts to reduce the residuals reaching ~−0.5 K on the higher wavenumber side of the CO2 ν3 band will focus on addressing limitations in the modeling of the CO2 line shape (line coupling and duration of collision) effects. Brightness temperature residuals from the radiance closure studies in the ν2 water vapor band have standard deviations of ~0.2–0.3 K with some large peak residuals reaching ±0.5–1.0 K. These are larger than the instrument noise indicating that systematic errors still remain. New H2O line intensities and positions from Coudert have a significant impact on the retrieved water vapor, particularly in the upper troposphere where the water vapor retrievals are 10% drier when using line intensities from Coudert compared with HITRAN2004. In addition to O3, CH4, and CO, the high radiometric calibration of the IASI instrument combined with an accurate forward model allows for the detection of minor species with weak atmospheric signatures in the nadir radiances, such as HNO3 and OCS.

Description: We present a detailed description of the TES methanol (CH3OH) retrieval algorithm, along with initial global results showing the seasonal and spatial distribution of methanol in the lower troposphere. The full development of the TES methanol retrieval is described, including microwindow selection, error analysis, and the utilization of a priori and initial guess information provided by the GEOS-Chem chemical transport model. Retrieval simulations and a sensitivity analysis using the developed retrieval strategy show that TES: (i) generally provides less than 1.0 piece of information, (ii) is sensitive in the lower troposphere with peak sensitivity typically occurring between ~900–700 hPa (~1–3 km) at a vertical resolution of ~5 km, (iii) has a limit of detectability between 0.5 and 1.0 ppbv Representative Volume Mixing Ratio (RVMR) depending on the atmospheric conditions, corresponding roughly to a profile with a maximum concentration of at least 1 to 2 ppbv, and (iv) in a simulation environment has a mean bias of 0.16 ppbv with a standard deviation of 0.34 ppbv. Applying the newly derived TES retrieval globally and comparing the results with corresponding GEOS-Chem output, we find generally consistent large-scale patterns between the two. However, TES often reveals higher methanol concentrations than simulated in the Northern Hemisphere spring, summer and fall. In the Southern Hemisphere, the TES methanol observations indicate a model overestimate over the bulk of South America from December through July, and a model underestimate during the biomass burning season.

Description: Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model:TES regressions are generally consistent with the model:aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS 〉0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1–2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 0.26, 0.12 and 3.0 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.5 for expanding canopies with leaf area index

Description: Presently only limited sets of tropospheric ammonia (NH3) measurements in the Earth's atmosphere have been reported from satellite and surface station measurements, despite the well-documented negative impact of NH3 on the environment and human health. Presented here is a detailed description of the satellite retrieval strategy and analysis for the Tropospheric Emission Spectrometer (TES) using simulations and measurements. These results show that: (i) the level of detectability for a representative boundary layer TES NH3 mixing ratio value is ~0.4 ppbv, which typically corresponds to a profile that contains a maximum level value of ~1 ppbv; (ii) TES NH3 retrievals generally provide at most one degree of freedom for signal (DOFS), with peak sensitivity between 700 and 900 mbar; (iii) TES NH3 retrievals show significant spatial and seasonal variability of NH3 globally; (iv) initial comparisons of TES observations with GEOS-CHEM estimates show TES values being higher overall. Important differences and similarities between modeled and observed seasonal and spatial trends are noted, with discrepancies indicating areas where the timing and magnitude of modeled NH3 emissions from agricultural sources, and to lesser extent biomass burning sources, need further study.

Description: Modern data assimilation algorithms depend on accurate infrared spectroscopy in order to make use of the information related to temperature, water vapor (H2O), and other trace gases provided by satellite observations. Reducing the uncertainties in our knowledge of spectroscopic line parameters and continuum absorption is thus important to improve the application of satellite data to weather forecasting. Here we present the results of a rigorous validation of spectroscopic updates to an advanced radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), against a global dataset of 120 near-nadir, over-ocean, nighttime spectra from the Infrared Atmospheric Sounding Interferometer (IASI). We compare calculations from the latest version of LBLRTM (v12.1) to those from a previous version (v9.4+) to determine the impact of spectroscopic updates to the model on spectral residuals as well as retrieved temperature and H2O profiles. We show that the spectroscopy in the CO2 ν2 and ν3 bands is significantly improved in LBLRTM v12.1 relative to v9.4+, and that these spectroscopic updates lead to mean changes of ~0.5 K in the retrieved vertical temperature profiles between the surface and 10 hPa, with the sign of the change and the variability among cases depending on altitude. We also find that temperature retrievals using each of these two CO2 bands are remarkably consistent in LBLRTM v12.1, potentially allowing these bands to be used to retrieve atmospheric temperature simultaneously. The updated H2O spectroscopy in LBLRTM v12.1 substantially improves the a posteriori residuals in the P-branch of the H2O ν2 band, while the improvements in the R-branch are more modest. The H2O amounts retrieved with LBLRTM v12.1 are on average 14% lower between 100 and 200 hPa, 42% higher near 562 hPa, and 31% higher near the surface compared to the amounts retrieved with v9.4+ due to a combination of the different retrieved temperature profiles and the updated H2O spectroscopy. We also find that the use of a fixed ratio of HDO to H2O in LBLRTM may be responsible for a significant fraction of the remaining bias in the P-branch relative to the R-branch of the H2O ν2 band. There were no changes to O3 spectroscopy between the two model versions, and so both versions give positive a posteriori residuals of ~ 0.3 K in the R-branch of the O3 ν3 band. While the updates to the H2O self-continuum employed by LBLRTM v12.1 have clearly improved the match with observations near the CO2 ν3 band head, we find that these updates have significantly degraded the match with observations in the fundamental band of CO. Finally, significant systematic a posteriori residuals remain in the ν4 band of CH4, but the magnitude of the positive bias in the retrieved mixing ratios is reduced in LBLRTM v12.1, suggesting that the updated spectroscopy could improve retrievals of CH4 from satellite observations.

Description: The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m–2 on the (10 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

Description: Presently only limited sets of tropospheric ammonia (NH3) measurements in the Earth's atmosphere have been reported from satellite and surface station measurements, despite the well-documented negative impact of NH3 on the environment and human health. Presented here is a detailed description of the satellite retrieval strategy and analysis for the Tropospheric Emission Spectrometer (TES) using simulations and measurements. These results show that: (i) the level of detectability for a representative boundary layer TES NH3 mixing ratio value is ~0.3 ppbv, which typically corresponds to a profile that contains a maximum level value of ~1 ppbv; (ii) TES NH3 retrievals provide at most one degree of freedom for signal (DOFS), with peak sensitivity between 700 and 900 mbar; (iii) TES NH3 retrievals show significant spatial and seasonal variability of NH3 globally; (iv) Initial comparisons of TES observations with GEOS-CHEM estimates show TES values being higher overall. Important differences and similarities between modeled and observed seasonal and spatial trends are noted, with discrepancies indicating areas where the timing and magnitude of modeled NH3 emissions from agricultural sources, and to lesser extent biomass burning sources, need further study.

Description: We present a detailed description of the TES methanol (CH3OH) retrieval algorithm, along with initial global results showing the seasonal and spatial distribution of methanol in the lower troposphere. The full development of the TES methanol retrieval is described, including microwindow selection, error analysis, and the utilization of a priori and initial guess information provided by the GEOS-Chem chemical transport model. Retrieval simulations and a sensitivity analysis using the developed retrieval strategy show that TES: (i) generally provides between 0.5 and 1.0 pieces of information, (ii) is sensitive in the lower troposphere with peak sensitivity typically occurring between ~900–700 hPa (~1–3 km) at a vertical resolution of ~5 km, (iii) has a limit of detectability between 0.5 and 1.0 ppbv Representative Volume Mixing Ratio (RVMR) depending on the atmospheric conditions, corresponding roughly to a profile with a maximum concentration of at least 1 to 2 ppbv, and (iv) in a simulation environment has a mean bias of 0.16 ppbv and a standard deviation of 0.34 ppbv. Applying the newly-derived TES retrieval globally and comparing the results with corresponding GEOS-Chem output, we find generally consistent large-scale patterns between the two. However, TES often reveals higher methanol concentrations than predicted in the Northern Hemisphere spring, summer and fall. In the Southern Hemisphere, the TES methanol observations indicate a model overestimate over the bulk of South America from December through July, and a model underestimate during the biomass burning season.

Description: Accurate water vapor profiles from radiosondes are essential for long-term climate prediction, weather prediction, validation of remote sensing retrievals, and other applications. The Vaisala RS80, RS90, and RS92 radiosondes are among the more commonly deployed radiosondes in the world. However, numerous investigators have shown that the daytime water vapor profiles measured by these instruments present a significant dry bias due to the solar heating of the humidity sensor. This bias in the column-integrated precipitable water vapor (PWV), along with variability due to calibration, can be removed by scaling the humidity profile to agree with the PWV retrieved from a microwave radiometer (MWR), as has been demonstrated by several previous studies. Infrared radiative closure analyses have shown that the MWR PWV does not present daytime versus nighttime differences; thus, scaling by the MWR is a possible approach for removing the daytime dry bias. However, MWR measurements are not routinely available at all radiosonde launch sites. Starting from a long-term series of sonde and MWR PWV measurements from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, the authors have developed a simple correction to the column-integrated sonde PWV, derived from an analysis of the ratio of the MWR and sonde measurements; this correction is a function of the atmospheric transmittance as determined by the solar zenith angle, and it effectively removes the daytime dry bias at all solar zenith angles. The correction was validated by successfully applying it to an independent dataset from the ARM tropical western Pacific (TWP) site.