The Montreal Protocol protects the terrestrial carbon sink.

The control of the production of ozone-depleting substances through the Montreal Protocol means that the stratospheric ozone layer is recovering1 and that consequent increases in harmful surface ultraviolet radiation are being avoided2,3. The Montreal Protocol has co-benefits for climate change mitigation, because ozone-depleting substances are potent greenhouse gases4-7. The avoided ultraviolet radiation and climate change also have co-benefits for plants and their capacity to store carbon through photosynthesis8, but this has not previously been investigated. Here, using a modelling framework that couples ozone depletion, climate change, damage to plants by ultraviolet radiation and the carbon cycle, we explore the benefits of avoided increases in ultraviolet radiation and changes in climate on the terrestrial biosphere and its capacity as a carbon sink. Considering a range of strengths for the effect of ultraviolet radiation on plant growth8-12, we estimate that there could have been 325-690 billion tonnes less carbon held in plants and soils by the end of this century (2080-2099) without the Montreal Protocol (as compared to climate projections with controls on ozone-depleting substances). This change could have resulted in an additional 115-235 parts per million of atmospheric carbon dioxide, which might have led to additional warming of global-mean surface temperature by 0.50-1.0 degrees. Our findings suggest that the Montreal Protocol may also be helping to mitigate climate change through avoided decreases in the land carbon sink.

Evaluation of NASA's high-resolution global composition simulations: Understanding a pollution event in the Chesapeake Bay during the 2017 OWLETS campaign.

Recirculation of pollutants due to a bay breeze effect is a key meteorological mechanism impacting air quality near urban coastal areas, but regional and global chemical transport models have historically struggled to capture this phenomenon. We present a case study of a high ozone (O3) episode observed over the Chesapeake Bay during the NASA Ozone Water-Land Environmental Transition Study (OWLETS) in summer 2017. OWLETS included a complementary suite of ground-based and airborne observations, with which we characterize the meteorological and chemical context of this event and develop a framework to evaluate model performance. Two publicly-available NASA global high-resolution coupled chemistry-meteorology models (CCMMs) are investigated: GEOS-CF and MERRA2-GMI. The GEOS-CF R2 value for comparisons between the NASA Sherpa C-23 aircraft measurements to the GEOS-CF resulted in good agreement (R2: 0.67) on July 19th and fair agreement (R2: 0.55) for July 20th. Compared to surface observations, we find the GEOS-CF product with a 25 x 25 km2 grid box, at an hourly (R2: 0.62 to 0.87) and 15-minute (R2: 0.64 to 0.87) interval for six regional sites outperforms the hourly nominally 50 x 50 km2 gridded MERRA2-GMI (R2: 0.53 to 0.76) for four of the six sites, suggesting it is better capable of simulating complex chemical and meteorological features associated with ozone transport within the Chesapeake Bay airshed. When the GEOS-CF product was compared to the TOLNet LiDAR observations at both NASA Langley Research Center (LaRC) and the Chesapeake Bay Bridge Tunnel (CBBT), the median differences at LaRC were -6 to 8% and at CBBT were ± 7% between 400 to 2000 m ASL. This indicates that, for this case study, the GEOS-CF is able to simulate surface level ozone diurnal cycles and vertical ozone profiles at small scales between the surface level and 2000 m ASL. Evaluating global chemical model simulations at sub-regional scales will help air quality scientists understand the complex processes occurring at small spatial and temporal scales within complex surface terrain changes, simulating nighttime chemistry and deposition, and the potential to use global chemical transport simulations in support of regional and sub-regional field campaigns.

Ensemble-based deep learning for estimating PM2.5 over California with multisource big data including wildfire smoke.

INTRODUCTION: Estimating PM2.5 concentrations and their prediction uncertainties at a high spatiotemporal resolution is important for air pollution health effect studies. This is particularly challenging for California, which has high variability in natural (e.g, wildfires, dust) and anthropogenic emissions, meteorology, topography (e.g. desert surfaces, mountains, snow cover) and land use. METHODS: Using ensemble-based deep learning with big data fused from multiple sources we developed a PM2.5 prediction model with uncertainty estimates at a high spatial (1 km × 1 km) and temporal (weekly) resolution for a 10-year time span (2008-2017). We leveraged autoencoder-based full residual deep networks to model complex nonlinear interrelationships among PM2.5 emission, transport and dispersion factors and other influential features. These included remote sensing data (MAIAC aerosol optical depth (AOD), normalized difference vegetation index, impervious surface), MERRA-2 GMI Replay Simulation (M2GMI) output, wildfire smoke plume dispersion, meteorology, land cover, traffic, elevation, and spatiotemporal trends (geo-coordinates, temporal basis functions, time index). As one of the primary predictors of interest with substantial missing data in California related to bright surfaces, cloud cover and other known interferences, missing MAIAC AOD observations were imputed and adjusted for relative humidity and vertical distribution. Wildfire smoke contribution to PM2.5 was also calculated through HYSPLIT dispersion modeling of smoke emissions derived from MODIS fire radiative power using the Fire Energetics and Emissions Research version 1.0 model. RESULTS: Ensemble deep learning to predict PM2.5 achieved an overall mean training RMSE of 1.54 µg/m3 (R2: 0.94) and test RMSE of 2.29 µg/m3 (R2: 0.87). The top predictors included M2GMI carbon monoxide mixing ratio in the bottom layer, temporal basis functions, spatial location, air temperature, MAIAC AOD, and PM2.5 sea salt mass concentration. In an independent test using three long-term AQS sites and one short-term non-AQS site, our model achieved a high correlation (>0.8) and a low RMSE (<3 µg/m3). Statewide predictions indicated that our model can capture the spatial distribution and temporal peaks in wildfire-related PM2.5. The coefficient of variation indicated highest uncertainty over deciduous and mixed forests and open water land covers. CONCLUSION: Our method can be generalized to other regions, including those having a mix of major urban areas, deserts, intensive smoke events, snow cover and complex terrains, where PM2.5 has previously been challenging to predict. Prediction uncertainty estimates can also inform further model development and measurement error evaluations in exposure and health studies.

Aircraft observations since the 1990s reveal increases of tropospheric ozone at multiple locations across the Northern Hemisphere.

Tropospheric ozone is an important greenhouse gas, is detrimental to human health and crop and ecosystem productivity, and controls the oxidizing capacity of the troposphere. Because of its high spatial and temporal variability and limited observations, quantifying net tropospheric ozone changes across the Northern Hemisphere on time scales of two decades had not been possible. Here, we show, using newly available observations from an extensive commercial aircraft monitoring network, that tropospheric ozone has increased above 11 regions of the Northern Hemisphere since the mid-1990s, consistent with the OMI/MLS satellite product. The net result of shifting anthropogenic ozone precursor emissions has led to an increase of ozone and its radiative forcing above all 11 study regions of the Northern Hemisphere, despite NO x emission reductions at midlatitudes.

The salience of nonlinearities in the boreal winter response to ENSO: Arctic stratosphere and Europe.

The Arctic stratospheric response to El Niño (EN) and La Niña (LN) is evaluated in a 41 member ensemble of the period 1980 to 2009 in the Goddard Earth Observing System Chemistry-Climate Model. We consider whether the responses to EN and LN are equal in magnitude and opposite in sign, whether the responses to moderate and extreme events are proportionate, and if the response depends on whether sea surface temperature anomalies (SSTs) peak in the Eastern Pacific (EP) or Central Pacific (CP). There is no indication of any nonlinearities between EN and LN, though in ~ 15% of the ensemble members the stratospheric sudden warming (SSW) frequencies for EN and LN are similar, suggesting that a similar SSW frequency for EN and LN, as has occurred over the past ~ 60 years, can occur by chance. The response to extreme EN events is not proportionate to the amplitude of the underlying SST anomalies in spring. EP EN events preferentially increase zonal wavenumber 1 and decrease zonal wavenumber 2 as compared to CP EN events, however the zonal-mean Arctic stratospheric and subpolar surface response is generally little different between EP EN and CP EN once one accounts for the relative weakness of CP events. These differences between EP and CP events and between moderate and extreme EN events only emerge if at least 25 events are composited, however, due to the small signal-to-noise ratio, and hence these differences may be of little practical benefit.

Ultraviolet radiation modelling using output from the Chemistry Climate Model Initiative.

We have derived values of the Ultraviolet Index (UVI) at solar noon using the Tropospheric Ultraviolet Model (TUV) driven by ozone, temperature and aerosol fields from climate simulations of the first phase of the Chemistry-Climate Model Initiative (CCMI-1). Since clouds remain one of the largest uncertainties in climate projections, we simulated only the clear-sky UVI. We compared the modelled UVI climatologies against present-day climatological values of UVI derived from both satellite data (the OMI-Aura OMUVBd product) and ground-based measurements (from the NDACC network). Depending on the region, relative differences between the UVI obtained from CCMI/TUV calculations and the ground-based measurements ranged between -5.9% and 10.6%. We then calculated the UVI evolution throughout the 21st century for the four Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0 and 8.5). Compared to 1960s values, we found an average increase in the UVI in 2100 (of 2-4%) in the tropical belt (30°N-30°S). For the mid-latitudes, we observed a 1.8 to 3.4 % increase in the Southern Hemisphere for RCP 2.6, 4.5 and 6.0, and found a 2.3% decrease in RCP 8.5. Higher increases in UVI are projected in the Northern Hemisphere except for RCP 8.5. At high latitudes, ozone recovery is well identified and induces a complete return of mean UVI levels to 1960 values for RCP 8.5 in the Southern Hemisphere. In the Northern Hemisphere, UVI levels in 2100 are higher by 0.5 to 5.5% for RCP 2.6, 4.5 and 6.0 and they are lower by 7.9% for RCP 8.5. We analysed the impacts of greenhouse gases (GHGs) and ozone-depleting substances (ODSs) on UVI from 1960 by comparing CCMI sensitivity simulations (1960-2100) with fixed GHGs or ODSs at their respective 1960 levels. As expected with ODS fixed at their 1960 levels, there is no large decrease in ozone levels and consequently no sudden increase in UVI levels. With fixed GHG, we observed a delayed return of ozone to 1960 values, with a corresponding pattern of change observed on UVI, and looking at the UVI difference between 2090s values and 1960s values, we found an 8 % increase in the tropical belt during the summer of each hemisphere. Finally we show that, while in the Southern Hemisphere the UVI is mainly driven by total ozone column, in the Northern Hemisphere both total ozone column and aerosol optical depth drive UVI levels, with aerosol optical depth having twice as much influence on the UVI as total ozone column does.

Mapping hydroxyl variability throughout the global remote troposphere via synthesis of airborne and satellite formaldehyde observations.

The hydroxyl radical (OH) fuels tropospheric ozone production and governs the lifetime of methane and many other gases. Existing methods to quantify global OH are limited to annual and global-to-hemispheric averages. Finer resolution is essential for isolating model deficiencies and building process-level understanding. In situ observations from the Atmospheric Tomography (ATom) mission demonstrate that remote tropospheric OH is tightly coupled to the production and loss of formaldehyde (HCHO), a major hydrocarbon oxidation product. Synthesis of this relationship with satellite-based HCHO retrievals and model-derived HCHO loss frequencies yields a map of total-column OH abundance throughout the remote troposphere (up to 70% of tropospheric mass) over the first two ATom missions (August 2016 and February 2017). This dataset offers unique insights on near-global oxidizing capacity. OH exhibits significant seasonality within individual hemispheres, but the domain mean concentration is nearly identical for both seasons (1.03 ± 0.25 × 106 cm-3), and the biseasonal average North/South Hemisphere ratio is 0.89 ± 0.06, consistent with a balance of OH sources and sinks across the remote troposphere. Regional phenomena are also highlighted, such as a 10-fold OH depression in the Tropical West Pacific and enhancements in the East Pacific and South Atlantic. This method is complementary to budget-based global OH constraints and can help elucidate the spatial and temporal variability of OH production and methane loss.

The Downward Influence of Sudden Stratospheric Warmings: Association with Tropospheric Precursors.

Tropospheric features preceding sudden stratospheric warming events (SSWs) are identified using a large compendium of events obtained from a chemistry-climate model. In agreement with recent observational studies, it is found that approximately one-third of SSWs are preceded by extreme episodes of wave activity in the lower troposphere. The relationship becomes stronger in the lower stratosphere, where ~60% of SSWs are preceded by extreme wave activity at 100 hPa. Additional analysis characterizes events that do or do not appear to subsequently impact the troposphere, referred to as downward and non-downward propagating SSWs, respectively. On average, tropospheric wave activity is larger preceding downward-propagating SSWs compared to non-downward propagating events, and associated in particular with a doubly strengthened Siberian high. Of the SSWs that were preceded by extreme lower-tropospheric wave activity, ~2/3 propagated down to the troposphere, and hence the presence of extreme lower-tropospheric wave activity can only be used probabilistically to predict a slight increase or decrease at the onset, of the likelihood of tropospheric impacts to follow. However, a large number of downward and non-downward propagating SSWs must be considered (>35), before the difference becomes statistically significant. The precursors are also robust upon comparison with composites consisting of randomly selected tropospheric northern annular mode (NAM) events. The downward influence and precursors to split and displacement events are also examined. It is found that anomalous upward wave-1 fluxes precede both cases. Splits exhibit a near instantaneous, barotropic response in the stratosphere and troposphere, while displacements have a stronger long-term influence.

Recent decline in extratropical lower stratospheric ozone attributed to circulation changes.

1998-2016 ozone trends in the lower stratosphere (LS) are examined using the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) and related NASA products. After removing biases resulting from step-changes in the MERRA-2 ozone observations, a discernible negative trend of -1.67±0.54 Dobson units per decade (DU/decade) is found in the 10-km layer above the tropopause between 20°N and 60°N. A weaker but statistically significant trend of -1.17±0.33 DU/decade exists between 50°S and 20°S. In the Tropics, a positive trend is seen in a 5-km layer above the tropopause. Analysis of an idealized tracer in a model simulation constrained by MERRA-2 meteorological fields provides strong evidence that these trends are driven by enhanced isentropic transport between the tropical (20°S-20°N) and extratropical LS in the past two decades. This is the first time that a reanalysis dataset has been used to detect and attribute trends in lower stratospheric ozone.

Nonlinear response of tropical lower stratospheric temperature and water vapor to ENSO.

A series of simulations using the NASA Goddard Earth Observing System Chemistry-Climate Model are analyzed in order to assess interannual and sub-decadal variability in the tropical lower stratosphere over the past 35 years. The impact of El Niño-Southern Oscillation on temperature and water vapor in this region is nonlinear in boreal spring. While moderate El Niño events lead to cooling in this region, strong El Niño events lead to warming, even as the response of the large scale Brewer Dobson Circulation appears to scale nearly linearly with El Niño. This nonlinearity is shown to arise from the response in the Indo-West Pacific to El Niño: strong El Niño events lead to tropospheric warming extending into the tropical tropopause layer and up to the cold point in this region, where it allows for more water vapor to enter the stratosphere. The net effect is that both strong La Niña and strong El Niño events lead to enhanced entry water vapor and stratospheric moistening in boreal spring and early summer. These results lead to the following interpretation of the contribution of sea surface temperatures to the decline in water vapor from the late 1990s to the early 2000s: the very strong El Niño event in 1997/1998, followed by more than two consecutive years of La Niña, led to enhanced lower stratospheric water vapor. As this period ended in early 2001, entry water vapor concentrations declined. This effect accounts for approximately one-quarter of the observed drop.