ALBERT

Description: The Tropospheric Emission Spectrometer (TES) on the EOS Aura satellite makes global measurements of infrared radiances which are used to derive profiles of species such as O3, CO, H2O, HDO and CH4 as routine standard products. In addition, TES has a variety of special modes that provide denser spatial mapping over a limited geographical area. A continuous-coverage mode (called ''transect'', about 460 km long) has now been used to detect additional molecules indicative of regional air pollution. On 10 July 2007 at about 05:37 UTC (13:24 LMST) TES conducted such a transect observation over the Beijing area in northeast China. Examination of the residual spectral radiances following the retrieval of the TES standard products revealed surprisingly strong features attributable to enhanced concentrations of ammonia (NH3) and methanol (CH3OH), well above the normal background levels. This is the first time that these molecules have been detected in space-based nadir viewing measurements that penetrate into the lower atmosphere.

Description: We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5-20 ppb) in the Southern Hemisphere (SH) and modest high bias (5-10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005-2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120mW/ sq. m OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39+/- 41mW/ sq. m relative to TES data. We show that there is a correlation (Sq. R = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750-2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100mW/ sq. m. Removing these models leads to a mean ozone radiative forcing of 394+/- 42mW/ sq. m. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 +/- 60mW/ sq. m derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing.

Description: Anthropogenic ozone radiative forcing is traditionally separately attributed to tropospheric and stratospheric changes assuming these have distinct causes. Using the interactive composition-climate model GISS-E2-R we find that this assumption is not justified. Our simulations show that changes in emissions of tropospheric ozone precursors have substantial effects on ozone in both regions, as do anthropogenic halocarbon emissions. Based on our results, additional simulations with the NCARCAM3.5 model, and published studies, we estimate industrial era (1850 to 2005) whole-atmosphere ozone forcing of 0.5 W/sq m due to anthropogenic tropospheric precursors and about -0.2 W/sq m due to halocarbons. The net troposphere plus stratosphere forcing is similar to the net halocarbon plus precursor ozone forcing, but the latter provides a more useful perspective. The halocarbon-induced ozone forcing is roughly two-thirds the magnitude of the halocarbon direct forcing but opposite in sign, yielding a net forcing of only 0.1 W/sq m. Thus the net effect of halocarbons has been smaller, while the effect of tropospheric ozone precursors has been greater, than generally recognized.

Description: We review the progress of tropospheric trace gas observations and address the need for additional measurement capabilities as recommended by the National Academy of Science (NAS, 2007). Tropospheric measurements from current and earlier instruments show pollution in the Northern Hemisphere as a result of fossil fuel burning and a strong seasonal dependence with the largest amounts of photochemically-generated ozone in summer. At low latitudes, where photon flux is stronger throughout the year, trace gas concentrations are driven by the abundance of the emissions, where the largest source, biomass burning, is readily seen in carbon monoxide measurements, but lightning and biogenic trace gases may also contribute to trace gas variability. Although substantive progress has been achieved in seasonal and global mapping of a few tropospheric trace gases, satellite trace-gas observations with considerably better temporal and spatial resolution are essential to forecasting air quality at scales required by policy-makers. The concurrent use of atmospheric composition measurements for both scientific and operational purposes is a new paradigm for the atmospheric chemistry community. The examples presented illustrate both the promise and challenge of merging satellite information with in situ observations in state-of-the-art data assimilation models.

Description: Using an Observing System Simulation Experiment (OSSE), we investigate the impact of JAXA Greenhouse gases Observing SATellite 'IBUKI' (GOSAT) sampling on the estimation of terrestrial biospheric flux with the NASA Carbon Monitoring System Flux (CMS-Flux) estimation and attribution strategy. The simulated observations in the OSSE use the actual column carbon dioxide (X(CO2)) b2.9 retrieval sensitivity and quality control for the year 2010 processed through the Atmospheric CO2 Observations from Space algorithm. CMS-Flux is a variational inversion system that uses the GEOS-Chem forward and adjoint model forced by a suite of observationally constrained fluxes from ocean, land and anthropogenic models. We investigate the impact of GOSAT sampling on flux estimation in two aspects: 1) random error uncertainty reduction and 2) the global and regional bias in posterior flux resulted from the spatiotemporally biased GOSAT sampling. Based on Monte Carlo calculations, we find that global average flux uncertainty reduction ranges from 25% in September to 60% in July. When aggregated to the 11 land regions designated by the phase 3 of the Atmospheric Tracer Transport Model Intercomparison Project, the annual mean uncertainty reduction ranges from 10% over North American boreal to 38% over South American temperate, which is driven by observational coverage and the magnitude of prior flux uncertainty. The uncertainty reduction over the South American tropical region is 30%, even with sparse observation coverage. We show that this reduction results from the large prior flux uncertainty and the impact of non-local observations. Given the assumed prior error statistics, the degree of freedom for signal is approx.1132 for 1-yr of the 74 055 GOSAT X(CO2) observations, which indicates that GOSAT provides approx.1132 independent pieces of information about surface fluxes. We quantify the impact of GOSAT's spatiotemporally sampling on the posterior flux, and find that a 0.7 gigatons of carbon bias in the global annual posterior flux resulted from the seasonally and diurnally biased sampling when using a diagonal prior flux error covariance.

Description: An atmospheric sounding mission starts with a wide range of concept designs involving measurement technologies, observing platforms, and observation scenarios. Observing system simulation experiment (OSSE) is a technical approach to evaluate the relative merits of mission and instrument concepts. At Jet Propulsion Laboratory (JPL), the OSSE team has developed an OSSE environment that allows atmospheric scientists to systematically explore a wide range of mission and instrument concepts and formulate a science traceability matrix with a quantitative science impact analysis. The OSSE environment virtually creates a multi-platform atmospheric sounding testbed (MAST) by integrating atmospheric phenomena models, forward modeling methods, and inverse modeling methods. The MAST performs OSSEs in four loosely coupled processes, observation scenario exploration, measurement quality exploration, measurement quality evaluation, and science impact analysis.

Description: Geostationary Coastal and Air pollution Events (GEO-CAPE) is a NASA decadal survey mission to be designed to provide surface reflectance at high spectral, spatial, and temporal resolutions from a geostationary orbit necessary for studying regional-scale air quality issues and their impact on global atmospheric composition processes. GEO-CAPE's Atmospheric Science Questions explore the influence of both gases and particles on air quality, atmospheric composition, and climate. The objective of the GEO-CAPE Observing System Simulation Experiment (OSSE) is to analyze the sensitivity of ozone to the global and regional NOx emissions and improve the science impact of GEO-CAPE with respect to the global air quality. The GEO-CAPE OSSE team at Jet propulsion Laboratory has developed a comprehensive OSSE framework that can perform adjoint-sensitivity analysis for a wide range of observation scenarios and measurement qualities. This report discusses the OSSE framework and presents the sensitivity analysis results obtained from the GEO-CAPE OSSE framework for seven observation scenarios and three instrument systems.

Description: Atmospheric moisture cycling is an important aspect of the Earth's climate system, yet the processes determining atmospheric humidity are poorly understood. For example, direct evaporation of rain contributes significantly to the heat and moisture budgets of clouds, but few observations of these processes are available. Similarly, the relative contributions to atmospheric moisture over land from local evaporation and humidity from oceanic sources are uncertain. Lighter isotopes of water vapour preferentially evaporate whereas heavier isotopes preferentially condense and the isotopic composition of ocean water is known. Here we use this information combined with global measurements of the isotopic composition of tropospheric water vapour from the Tropospheric Emission Spectrometer (TES) aboard the Aura spacecraft, to investigate aspects of the atmospheric hydrological cycle that are not well constrained by observations of precipitation or atmospheric vapour content. Our measurements of the isotopic composition of water vapour near tropical clouds suggest that rainfall evaporation contributes significantly to lower troposphere humidity, with typically 20% and up to 50% of rainfall evaporating near convective clouds. Over the tropical continents the isotopic signature of tropospheric water vapour differs significantly from that of precipitation, suggesting that convection of vapour from both oceanic sources and evapotranspiration are the dominant moisture sources. Our measurements allow an assessment of the intensity of the present hydrological cycle and will help identify any future changes as they occur.