Abstract. We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004-April 2005 global inversion of CO sources at 4 • ×5 • spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MO-PITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOSChem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a −1 . This is much higher than current bottomup emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-thanexpected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posCorrespondence to: M. Kopacz (mkopacz@princeton.edu) teriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

Abstract. The remote and high elevation regions of central Asia are influenced by black carbon (BC) emissions from a variety of locations. BC deposition contributes to melting of glaciers and questions exist, of both scientific and policy interest, as to the origin of the BC reaching the glaciers. We use the adjoint of the GEOS-Chem model to identify the location from which BC arriving at a variety of locations in the Himalayas and Tibetan Plateau originates. We then calculate its direct and snow-albedo radiative forcing. We analyze the seasonal variation in the origin of BC using an adjoint sensitivity analysis, which provides a detailed map of the location of emissions that directly contribute to black carbon concentrations at receptor locations. We find that emissions from northern India and central China contribute the majority of BC to the Himalayas, although the precise location varies with season. The Tibetan Plateau receives most BC from western and central China, as well as from India, Nepal, the Middle East, Pakistan and other countries. The magnitude of contribution from each region varies with season and receptor location. We find that sources as varied as African biomass burning and Middle Eastern fossil fuel combustion can significantly contribute to the BC reaching the Himalayas and Tibetan Plateau. We compute radiative forcing in the snow-covered regions and find the forcing due to the BC induced snow-albedo effect to vary from 5-15 W m −2 within the region, an order of magnitude larger than radiative forcing due to the direct effect, and with significant seasonal variation in the northern Tibetan Plateau. Radiative forcing fromCorrespondence to: D. L. Mauzerall (mauzeral@princeton.edu) reduced snow albedo likely accelerates glacier melting. Our analysis may help inform mitigation efforts to slow the rate of glacial melt by identifying regions that make the largest contributions to BC deposition in the Himalayas and Tibetan Plateau.

An adjoint model for the internationally used Community Multiscale Air Quality (CMAQ) modeling platform of the U.S. EPA is developed. The adjoint version for CMAQ (CMAQ-ADJ) provides the user community with forward (decoupled direct method or DDM) and backward (adjoint) sensitivity analysis capabilities. Current implementation is for gas-phase processes. Discrete adjoints are implemented for all processes with the exception of horizontal advection, for which, because of inherent discontinuities in the advection scheme, the continuous approach is superior. The adjoint of chemistry is constructed by interfacing CMAQ with the kinetic pre-processor, which provides for increased flexibility in the choice of chemical solver and facilitates the implementation of new chemical mechanisms. The adjoint implementation is evaluated both on a process-by-process basis and for the full model. In general, adjoint results show good agreement with brute-force and DDM sensitivities. As expected for a continuous adjoint implementation in a nonlinear scheme, the agreement is not perfect for horizontal transport. Sensitivities of various air quality, public health, and environmental metrics with respect to emissions are calculated using the adjoint method. In order to show applicability to regional climate studies, as an example, the sensitivities of these metrics with respect to local temperatures are calculated.

[1] We use the GEOS-Chem chemical transport model and its adjoint to quantify source contributions to ozone pollution at two adjacent sites on the U.S. west coast in spring 2006: Mt. Bachelor Observatory (MBO) at 2.7 km altitude and Trinidad Head (TH) at sea level. The adjoint computes the sensitivity of ozone concentrations at the receptor sites to ozone production rates at 2°Â 2.5°r esolution over the history of air parcels reaching the site. MBO experiences distinct Asian ozone pollution episodes; most of the ozone production in these episodes takes place over East Asia with maxima over northeast China and southern Japan, adding to a diffuse background production distributed over the extratropical northern hemisphere. TH shows the same Asian origins for ozone as MBO but no distinct Asian pollution episodes. We find that transpacific pollution plumes transported in the free troposphere are diluted by a factor of 3 when entrained into the boundary layer, explaining why these plumes are undetectable in U.S. surface air. Citation:

We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004-April 2005) global inversion of CO sources at 4 • ×5 • spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MO-PITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a −1. This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A pos-Correspondence to: M. Kopacz (mkopacz@princeton.edu) teriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

Global aerosol direct radiative forcing (DRF) is an important metric for assessing potential climate impacts of future emissions changes. However, the radiative consequences of emissions perturbations are not readily quantified nor well understood at the level of detail necessary to assess realistic policy options. To address this challenge, here we show how adjoint model sensitivities can be used to provide highly spatially resolved estimates of the DRF from emissions of black carbon (BC), primary organic carbon (OC), sulfur dioxide (SO 2 ), and ammonia (NH 3 ), using the example of emissions from each sector and country following multiple Representative Concentration Pathway (RCPs). The radiative forcing efficiencies of many individual emissions are found to differ considerably from regional or sectoral averages for NH 3 , SO 2 from the power sector, and BC from domestic, industrial, transportation and biomass burning sources. Consequently, the amount of emissions controls required to attain a specific DRF varies at intracontinental scales by up to a factor of 4. These results thus demonstrate both a need and means for incorporating spatially refined aerosol DRF into analysis of future emissions scenario and design of air quality and climate change mitigation policies.

The remote and high elevation regions of central Asia are influenced by black carbon (BC) emissions from a variety of locations. BC deposition contributes to melting of glaciers and questions exist, of both scientific and policy interest, as to the origin of the BC reaching the glaciers. We use the adjoint of the GEOS-Chem model to identify the location from which BC arriving at a variety of locations in the Himalayas and Tibetan Plateau originates. We then calculate its direct and snow-albedo radiative forcing. We analyze the seasonal variation in the origin of BC using an adjoint sensitivity analysis, which provides a detailed map of the location of emissions that directly contribute to black carbon concentrations at receptor locations. We find that emissions from northern India and central China contribute the majority of BC to the Himalayas, although the precise location varies with season. The Tibetan Plateau receives most BC from western and central China, as well as from India, Nepal, the Middle East, Pakistan and other countries. The magnitude of contribution from each region varies with season and receptor location. We find that sources as varied as African biomass burning and Middle Eastern fossil fuel combustion can significantly contribute to the BC reaching the Himalayas and Tibetan Plateau. We compute radiative forcing in the snow-covered regions and estimate the forcing due to the BC induced snow-albedo effect at about 5–15 W m⁻² within the region, an order of magnitude larger than radiative forcing due to the direct effect, and with significant seasonal variation in the northern Tibetan Plateau. Radiative forcing from reduced snow albedo accelerates glacier melting. Our analysis can help inform mitigation efforts to slow the rate of glacial melt by identifying regions that make the largest contributions to BC deposition in the Himalayas and Tibetan Plateau

Abstract. Chemical data assimilation attempts to optimally use noisy observations along with imperfect model predictions to produce a better estimate of the chemical state of the atmosphere. It is widely accepted that a key ingredient for successful data assimilation is a realistic estimation of the background error distribution. Particularly important is the specification of the background error covariance matrix, which contains information about the magnitude of the background errors and about their correlations. As models evolve toward finer resolutions, the use of diagonal background covariance matrices is increasingly inaccurate, as they captures less of the spatial error correlations. This paper discusses an efficient computational procedure for constructing nondiagonal background error covariance matrices which account for the spatial correlations of errors. The correlation length scales are specified by the user; a correct choice of correlation lengths is important for a good performance of the data assimilation system. The benefits of using the nondiagonal covariance matrices for variational data assimilation with chemical transport models are illustrated.