Mark W. Shephard

Radiative forcing by long‐lived greenhouse gases: Calculations with the AER radiative transfer models

A primary component of the observed, recent climate change is the radiative forcing from increased concentrations of long-lived greenhouse gases (LLGHGs). Effective simulation of anthropogenic climate change by general circulation models (GCMs) is strongly dependent on the accurate representation of radiative processes associated with water vapor, ozone and LLGHGs. In the context of the increasing application of the Atmospheric and Environmental Research, Inc. (AER) radiation models within the GCM community, their capability to calculate longwave and shortwave radiative forcing for clear sky scenarios previously examined by the radiative transfer model intercomparison project (RTMIP) is presented. Forcing calculations with the AER line-by-line (LBL) models are very consistent with the RTMIP line-by-line results in the longwave and shortwave. The AER broadband models, in all but one case, calculate longwave forcings within a range of -0.20 to 0.23 W m{sup -2} of LBL calculations and shortwave forcings within a range of -0.16 to 0.38 W m{sup -2} of LBL results. These models also perform well at the surface, which RTMIP identified as a level at which GCM radiation models have particular difficulty reproducing LBL fluxes. Heating profile perturbations calculated by the broadband models generally reproduce high-resolution calculations within a few hundredths K d{sup -1} in the troposphere and within 0.15 K d{sup -1} in the peak stratospheric heating near 1 hPa. In most cases, the AER broadband models provide radiative forcing results that are in closer agreement with high 20 resolution calculations than the GCM radiation codes examined by RTMIP, which supports the application of the AER models to climate change research.

The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation

AbstractThe 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 c...

The QME AERI LBLRTM: A Closure Experiment for Downwelling High Spectral Resolution Infrared Radiance

Abstract Research funded by the U.S. Department of Energys Atmospheric Radiation Measurement (ARM) program has led to significant improvements in longwave radiative transfer modeling over the last decade. These improvements, which have generally come in small incremental changes, were made primarily in the water vapor self- and foreign-broadened continuum and the water vapor absorption line parameters. These changes, when taken as a whole, result in up to a 6 W m−2 improvement in the modeled clear-sky downwelling longwave radiative flux at the surface and significantly better agreement with spectral observations. This paper provides an overview of the history of ARM with regard to clear-sky longwave radiative transfer, and analyzes remaining related uncertainties in the ARM state-of-the-art Line-by-Line Radiative Transfer Model (LBLRTM). A quality measurement experiment (QME) for the downwelling infrared radiance at the ARM Southern Great Plains site has been ongoing since 1994. This experiment has three...

Comparison of carbon monoxide measurements by TES and MOPITT: Influence of a priori data and instrument characteristics on nadir atmospheric species retrievals

[1] Comparisons of tropospheric carbon monoxide (CO) volume mixing ratio profiles and total columns are presented from nadir-viewing measurements made by the Tropospheric Emission Spectrometer (TES) on the NASA Aura satellite and by the Measurements of Pollution in the Troposphere (MOPITT) instrument on the NASA Terra satellite. In this paper, we first explore the factors that relate the retrieved and the true species profiles. We demonstrate that at a given location and time the retrieved species profiles reported by different satellite instrument teams can be very different from each other. We demonstrate the influence of the a priori data and instrument characteristics on the CO products from TES and MOPITT and on their comparisons. Direct comparison of TES and MOPITT retrieved CO profiles and columns show significant differences in the lower and upper troposphere. To perform a more proper and rigorous comparison between the two instrument observations we allow for different a priori profiles and averaging kernels. We compare (1) TES retrieved CO profiles adjusted to the MOPITT a priori with the MOPITT retrievals and (2) the above adjusted TES CO profiles with the MOPITT profiles vertically smoothed by the TES averaging kernels. These two steps greatly improve the agreement between the CO profiles and the columns from the two instruments. No systematic differences are found as a function of latitude in the final comparisons. These results show that knowledge of the a priori profiles, the averaging kernels, and the error covariance matrices in the standard data products provided by the instrument teams and understanding their roles in the retrieval products are essential in quantitatively interpreting both retrieved profiles and the derived total or partial columns for scientific applications.

Implementation of cloud retrievals for Tropospheric Emission Spectrometer (TES) atmospheric retrievals: part 1. Description and characterization of errors on trace gas retrievals

terms of a set of frequency-dependent nonscattering optical depths and a cloud height. These cloud parameters are retrieved jointly with surface temperature, emissivity, atmospheric temperature, and trace gases such as ozone from spectral data. We demonstrate the application of this approach using data from the Tropospheric Emission Spectrometer (TES) and test data simulated with a scattering radiative transfer model. We show the value of this approach in that it results in accurate estimates of errors for trace gas retrievals, and the retrieved values improve over the initial guess for a wide range of cloud conditions. Comparisons are made between TES retrievals of ozone, temperature, and water to model fields from the Global Modeling and Assimilation Office (GMAO), temperature retrievals from the Atmospheric Infrared Sounder (AIRS), tropospheric ozone columns from the Goddard Earth Observing System (GEOS) GEOS-Chem, and ozone retrievals from the Total Ozone Mapping Spectrometer (TOMS). In each of these cases, this cloud retrieval approach does not introduce observable biases into TES retrievals.

Improved Daytime Column-Integrated Precipitable Water Vapor from Vaisala Radiosonde Humidity Sensors

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.

Ozone-CO correlations determined by the TES satellite instrument in continental outflow regions

0.4– 1.0 mol mol � 1 and consistent with ICARTT data. The GEOS-Chem model reproduces the O3-CO enhancement ratios observed in continental outflow, but model correlations are stronger and more extensive. We show that the discrepancy can be explained by spectral measurement errors in the TES data. These errors will decrease in future data releases, which should enable TES to provide better information on O3-CO correlations. Citation: Zhang, L., et al. (2006), Ozone-CO correlations determined by the TES satellite instrument in continental outflow regions, Geophys. Res. Lett., 33, L18804, doi:10.1029/2006GL026399.

Forward model and Jacobians for Tropospheric Emission Spectrometer retrievals

The Tropospheric Emission Spectrometer (TES) is a high-resolution spaceborne sensor that is capable of observing tropospheric species. In order to exploit fully TESs potential for tropospheric constituent retrievals, an accurate and fast operational forward model was developed for TES. The forward model is an important component of the TES retrieval model, the Earth Limb and Nadir Operational Retrieval (ELANOR), as it governs the accuracy and speed of the calculations for the retrievals. In order to achieve the necessary accuracy and computational efficiency, TES adopted the strategy of utilizing precalculated absorption coefficients generated by the line-by-line calculations provided by line-by-line radiation transfer modeling. The decision to perform the radiative transfer with the highest monochromatic accuracy attainable, rather than with an accelerated scheme that has the potential to add algorithmic forward model error, has proven to be very successful for TES retrievals. A detailed description of the TES forward model and Jacobians is described. A preliminary TES observation is provided as an example to demonstrate that the TES forward model calculations represent TES observations. Also presented is a validation example, which is part of the extensive forward model validation effort.

Quantifying spatial and seasonal variability in atmospheric ammonia with in situ and space-based observations

Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios are not well known. Recently, methods have been developed for retrieving NH3 from space-based observations, but they have not been compared to in situ measurements. We have conducted a field campaign combining co-located surface measurements and satellite special observations from the Tropospheric Emission Spectrometer (TES). Our study includes 25 surface monitoring sites spanning 350 km across eastern North Carolina, a region with large seasonal and spatial variability in NH3. From the TES spectra, we retrieve a NH3 representative volume mixing ratio (RVMR), and we restrict our analysis to times when the region of the atmosphere observed by TES is representative of the surface measurement. We find that the TES NH3 RVMR qualitatively captures the seasonal and spatial variability found in eastern North Carolina. Both surface measurements and TES NH3 show a strong correspondence with the number of livestock facilities within 10 km of the observation. Furthermore, we find that TES NH3 RVMR captures the month-to-month variability present in the surface observations. The high correspondence with in situ measurements and vast spatial coverage make TES NH3 RVMR a valuable tool for understanding regional and global NH3 fluxes.

Spectroscopic improvements providing evidence of formic acid in AERI-LBLRTM validation spectra

Abstract The capabilities of new and future high-resolution passive sensors, such as the tropospheric emission spectrometer, are placing a greater demand on the accuracy of line-by-line radiative transfer calculations used directly or indirectly in the retrievals of atmospheric constituents. Presented is a validation case study at the Atmospheric Radiation Measurement Southern Great Plains site on the night of 22 July 2001 that illustrates how recent advancements in both the HITRAN2000 spectral lines and the new MT_CKD_1.0 continuum reduced residuals between the atmospheric emission radiance interferometer and line-by-line radiative transfer model radiances. These improvements reduce line parameter systematic errors in the forward model allowing for the retrieval of elevated values of formic acid (HCOOH), which has a weak atmospheric signal consisting of only ∼5% of the background downwelling zenith radiation in the ν6 HCOOH spectral region.