Anton Darmenov

The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)

The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) is the latest atmospheric reanalysis of the modern satellite era produced by NASAs Global Modeling and Assimilation Office (GMAO). MERRA-2 assimilates observation types not available to its predecessor, MERRA, and includes updates to the Goddard Earth Observing System (GEOS) model and analysis scheme so as to provide a viable ongoing climate analysis beyond MERRAs terminus. While addressing known limitations of MERRA, MERRA-2 is also intended to be a development milestone for a future integrated Earth system analysis (IESA) currently under development at GMAO. This paper provides an overview of the MERRA-2 system and various performance metrics. Among the advances in MERRA-2 relevant to IESA are the assimilation of aerosol observations, several improvements to the representation of the stratosphere including ozone, and improved representations of cryospheric processes. Other improvements in the quality of MERRA-2 compared with MERRA include the reduction of some spurious trends and jumps related to changes in the observing system, and reduced biases and imbalances in aspects of the water cycle. Remaining deficiencies are also identified. Production of MERRA-2 began in June 2014 in four processing streams, and converged to a single near-real time stream in mid 2015. MERRA-2 products are accessible online through the NASA Goddard Earth Sciences Data Information Services Center (GES DISC).

The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data Assimilation Evaluation

The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) updates NASAs previous satellite era (1980 - onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, Version 5 (GEOS-5) Earth system model. As a major step towards a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimilation of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, we document the MERRA-2 aerosol assimilation, including a description of the prognostic model (GEOS-5 coupled to the GOCART aerosol module), aerosol emissions, and the quality control of ingested observations. We provide initial validation and evaluation of the analyzed AOD fields using independent observations from ground, aircraft, and shipborne instruments. We demonstrate the positive impact of the AOD assimilation on simulated aerosols by comparing MERRA-2 aerosol fields to an identical control simulation that does not include AOD assimilation. Having shown the AOD evaluation, we take a first look at aerosol-climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. In our companion paper, we evaluate and validate available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g. aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate.

The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part II: Evaluation and Case Studies

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), is NASAs latest reanalysis for the satellite era (1980 onward) using the Goddard Earth Observing System, version 5 (GEOS-5), Earth system model. MERRA-2 provides several improvements over its predecessor (MERRA-1), including aerosol assimilation for the entire period. MERRA-2 assimilates bias-corrected aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer and the Advanced Very High Resolution Radiometer instruments. Additionally, MERRA-2 assimilates (non bias corrected) AOD from the Multiangle Imaging SpectroRadiometer over bright surfaces and AOD from Aerosol Robotic Network sunphotometer stations. This paper, the second of a pair, summarizes the efforts to assess the quality of the MERRA-2 aerosol products. First, MERRA-2 aerosols are evaluated using independent observations. It is shown that the MERRA-2 absorption aerosol optical depth (AAOD) and ultraviolet aerosol index (AI) compare well with Ozone Monitoring Instrument observations. Next, aerosol vertical structure and surface fine particulate matter (PM2.5) are evaluated using available satellite, aircraft, and ground-based observations. While MERRA-2 generally compares well to these observations, the assimilation cannot correct for all deficiencies in the model (e.g., missing emissions). Such deficiencies can explain many of the biases with observations. Finally, a focus is placed on several major aerosol events to illustrate successes and weaknesses of the AOD assimilation: the Mount Pinatubo eruption, a Saharan dust transport episode, the California Rim Fire, and an extreme pollution event over China. The article concludes with a summary that points to best practices for using the MERRA-2 aerosol reanalysis in future studies.

Improved western U.S. background ozone estimates via constraining nonlocal and local source contributions using Aura TES and OMI observations

Western U.S. near-surface ozone (O3) concentrations are sensitive to transported background O3 from the eastern Pacific free troposphere, as well as U.S. anthropogenic and natural emissions. The current 75 ppbv U.S. O3 primary standard may be lowered soon, hence accurately estimating O3 source contributions, especially background O3 in this region has growing policy-relevant significance. In this study, we improve the modeled total and background O3, via repartitioning and redistributing the contributions from nonlocal and local anthropogenic/wildfires sources in a multi-scale satellite data assimilation system containing global Goddard Earth Observing System–Chemistry model (GEOS-Chem) and regional Sulfur Transport and dEposition Model (STEM). Focusing on NASAs ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) field campaign period in June–July 2008, we first demonstrate that the negative biases in GEOS-Chem free simulation in the eastern Pacific at 400–900 hPa are reduced via assimilating Aura-Tropospheric Emission Spectrometer (TES) O3 profiles. Using the TES-constrained boundary conditions, we then assimilated into STEM the tropospheric nitrogen dioxide (NO2) columns from Aura-Ozone Monitoring Instrument to indicate U.S. nitrogen oxides (NOx = NO2 + NO) emissions at 12 × 12 km2 grid scale. Improved model skills are indicated from cross validation against independent ARCTAS measurements. Leveraging Aura observations, we show anomalously high wildfire NOx emissions in this summer in Northern California and the Central Valley while lower anthropogenic emissions in multiple urban areas than those representing the year of 2005. We found strong spatial variability of the daily maximum 8 h average background O3 and its contribution to the modeled total O3, with the mean value of ~48 ppbv (~77% of the total).

Link Between Arctic Tropospheric BrO Explosion Observed From Space and Sea‐Salt Aerosols From Blowing Snow Investigated Using Ozone Monitoring Instrument BrO Data and GEOS‐5 Data Assimilation System

Bromine radicals (Br + BrO) are important atmospheric species owing to their ability to catalytically destroy ozone as well as their potential impacts on the oxidative pathways of many trace gases, including dimethylsulfide and mercury. Using space‐based observations of BrO, recent studies have reported rapid enhancements of tropospheric BrO over large areas (so called “BrO explosions”) connected to near‐surface ozone depletion occurring in polar spring. However, the source(s) of reactive bromine and mechanism(s) that initiate these BrO explosions are uncertain. In this study, we investigate the relationships between Arctic BrO explosions and two of the proposed sources of reactive bromine: sea‐salt aerosol (SSA) generated from blowing snow and first‐year (seasonal) sea ice. We use tropospheric column BrO derived from the Ozone Monitoring Instrument (OMI) in conjunction with the Goddard Earth Observing System Version 5 (GEOS‐5) data assimilation system provided by National Aeronautics and Space Administration Global Modeling and Assimilation Office. Case studies demonstrate a strong association between the temporal and spatial extent of OMI‐observed BrO explosions and the GEOS‐5 simulated blowing snow‐generated SSA during Arctic spring. Furthermore, the frequency of BrO explosion events observed over the 11‐year record of OMI exhibits significant correlation with a time series of the simulated SSA emission flux in the Arctic and little to no correlation with a time series of satellite‐based first‐year sea ice area. Therefore, we conclude that SSA generated by blowing snow is an important factor in the formation of the BrO explosion observed from space during Arctic spring.

A new global anthropogenic SO 2 emission inventory for the last decade: A mosaic of satellite-derived and bottom-up emissions

Sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor have been used to detect emissions from large point sources. Emissions from over 400 sources have been quantified individually based on OMI observations, accounting for about a half of total reported anthropogenic SO2 emissions. Here we report a newly developed emission inventory, OMI-HTAP, by combining these OMI-based emission estimates and the conventional bottom-up inventory, HTAP, for smaller sources that OMI is not able to detect. OMI-HTAP includes emissions from OMI-detected sources that are not captured in previous leading bottom-up inventories, enabling more accurate emission estimates for regions with such missing sources. In addition, our approach offers the possibility of rapid updates to emissions from large point sources that can be detected by satellites. Our methodology applied to OMI-HTAP can also be used to merge improved satellite-derived estimates with other multi-year bottom-up inventories, which may further improve the accuracy of the emission trends. OMI-HTAP SO2 emissions estimates for Persian Gulf, Mexico, and Russia are 59 %, 65 %, and 56 % larger than HTAP estimates in 2010, respectively. We have evaluated the OMI-HTAP inventory by performing simulations with the Goddard Earth Observing System version 5 (GEOS-5) model. The GEOS5 simulated SO2 concentrations driven by both HTAP and OMI-HTAP were compared against in situ measurements. We focus for the validation on 2010 for which HTAP is most valid and for which a relatively large number of in situ measurements are available. Results show that the OMI-HTAP inventory improves the agreement between the model and observations, in particular over the US, with the normalized mean bias decreasing from 0.41 (HTAP) to −0.03 (OMIHTAP) for 2010. Simulations with the OMI-HTAP inventory capture the worldwide major trends of large anthropogenic SO2 emissions that are observed with OMI. Correlation coefficients of the observed and modeled surface SO2 in 2014 increase from 0.16 (HTAP) to 0.59 (OMI-HTAP) and the normalized mean bias dropped from 0.29 (HTAP) to 0.05 (OMIHTAP), when we updated 2010 HTAP emissions with 2014 OMI-HTAP emissions in the model.