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At least 631 records · Page 35

Potential impacts of projected warming scenarios on winter wheat in the UK

The goals of this study are to analyse the impacts of 1.5 and 2.0°C scenarios on UK winter wheat using a combination of Global Climate Models (GCMs), crop models, planting dates and cultivars; to evaluate the impact of increased air temperature on winter wheat phenology and potential yield; to quantify the underlying uncertainties due to the multiple sources of variability introduced by climate scenarios, crop models and agronomic management. The data used to calibrate and evaluate three crop models were obtained from a field experiment with two irrigation amounts and two wheat cultivars that have different phenology and growth habit. After calibration, the model was applied to fifty locations across the wheat-growing area of the UK to cover all the main growing regions, with most points located in the main growing areas. Four GCMs, with two cultivars and five planting dates, were simulated at the end of the century. Results of this study showed that the UK potential wheat yield will increase by 2–8% under projected climate. Farmers will need to close such a gap in the future because it will have implications in terms of food security. Future climatic conditions might increase such a gap. Adaptation measures (e.g. moving the optimal planting time), along with climate-ready varieties bred for future conditions and with precision agriculture techniques can help to reduce this gap and ensure that the future actual UK wheat production will be close to the potential.

Climate change↗

Understanding the Microphysical Control and Spatial-Temporal Variability of Warm Rain Probability Using CloudSat and MODIS Observations

By combining measurements from MODIS and the CloudSat radar, we develop a parameterization scheme to quantify the combined microphysical controls by liquid water path (LWP) and cloud droplet number concentration (CDNC) of the probability of precipitation (PoP) in marine low cloud over tropical oceans. We demonstrate that the spatial-temporal variation of grid-mean in-cloud can be largely explained by the variation of the joint probability density function of LWP and CDNC in the phase space specified by the bivariate PoP (LWP and CDNC) function. Through a series of sensitivity tests guided by this understanding, we find that in the Southeastern Pacific and Atlantic the stratocumulus to cumulus transition of the is mainly due to the variation of CDNC while the annual cycle is mainly due to the variation of LWP. The results of this study provide a viable way to diagnose the root cause of warm rain problems in global climate models.

Zhibo Zhang↗

Simulating the Martian Middle and Upper Atmosphere with the NASA Ames Mars GCM.

The NASA Ames Mars Global Climate Model (MGCM) continues to be utilized to examine the dynamical coupling between the lower atmosphere and middle/upper atmosphere. This coupling impacts the transport of water, dust, and chemistry which augments the thermal structure and circulation. The interactions and coupling within the atmosphere are important for understanding the present-day and past atmosphere and climate. MGCM simulations are compared with observations from recent Mars missions to provide model constraints, and in turn, the simulations can then provide context to the observations. This cycle is important to move us forward in our understanding of planetary atmospheres. We will present on one of the fundamental atmospheric features, the thermal structure, and how the physics in the MGCM can elucidate the observed diurnal and seasonal behavior. Additionally, we will focus on the distribution of chemical species which influences the thermal structure and provides additional information on the coupling between the lower and middle/upper atmosphere. Lastly, we will provide a summary of the model capabilities, as the MGCM continues to be improved upon to properly simulate Mars’ atmosphere from the ground to ~250 km.

Amanda Susanne Brecht↗

The Habitability of Proxima Centauri b II. Possible Climates and Observability

Radial velocity monitoring has found the signature of a M sin i = 1.3 M(sub ⨁) planet located within the habitable zone (HZ) of Proxima Centauri. Despite a hotter past and an active host star, the planet Proxima b could have retained enough volatiles to sustain surface habitability. Here we use a 3D Global Climate Model (GCM) to simulate the atmosphere and water cycle of Proxima b for its two likely rotation modes (1:1 and 3:2 spin-orbit resonances), while varying the unconstrained surface water inventory and atmospheric greenhouse effect. Any low-obliquity, low-eccentricity planet within the HZ of its star should be in one of the climate regimes discussed here. We find that a broad range of atmospheric compositions allow surface liquid water. On a tidally locked planet with sufficient surface water inventory, liquid water is always present, at least in the substellar region. With a non-synchronous rotation, this requires a minimum greenhouse warming (~10 mbar of CO2 and 1 bar of N2). If the planet is dryer, ~0.5 bar or 1.5 bars of CO2 (for asynchronous or synchronous rotation, respectively) suffice to prevent the trapping of any arbitrary, small water inventory into polar or nightside ice caps. We produce reflection and emission spectra and phase curves for the simulated climates. We find that atmospheric characterization will be possible via direct imaging with forthcoming large telescopes. The angular separation of 7 λ/D at 1 μm (with the E-ELT) and a contrast of ~10(exp -7) will enable high-resolution spectroscopy and the search for molecular signatures, including H2O, O2, and CO2. The observation of thermal phase curves can be attempted with the James Webb Space Telescope, thanks to a contrast of 2 × 10(exp -5) at 10 μm. Proxima b will also be an exceptional target for future IR interferometers. Within a decade it will be possible to image Proxima b and possibly determine whether the surface of this exoplanet is habitable.

Proxima Cen↗

Technology Maturation for Cloud Ice Radiometers

Global measurements of ice in clouds, both the amount and particle size distribution, are critically needed to reduce uncertainties in global climate models. The retrieval of this information is best achieved with a range of receiver channels across the submillimeter wave range. Advancement of low noise Indium Phosphide (InP) MMIC amplifier technology to 25-nm gate length enabled us to develop miniature submillimeter-wave receivers for a CubeSat scale instrument that achieves 6 km spatial resolution. We developed the 25-nm InP MMICs and radiometer receivers for 240, 310, 380, 670 GHz. The 25-nm InP MMIC technology was thermal vacuum tested to reduce risk for future space mission.

Duffy, Maxwell↗

Formation of Tropopause Cirrus clouds by Typhoon-induced gravity waves during the Asian Summer Monsoon: A Case Study from the BATAL 2017 Campaign

Cirrus clouds in the Tropical Tropopause Layer (TTL) have a net warming impact on Earth’s climate and they regulate the amount of water vapor entering the lower stratosphere through dehydration process near the cold-point tropopause. During the Boreal summer, Asian Summer Monsoon (ASM) is an important source of cirrus clouds and humidity in the TTL owing to frequent deep convection. However, better representation of convection and TTL cirrus clouds in global climate models is needed for accurate assessment of their response to changing climate. In this study, we investigate the mechanisms involved in the formation of a tropopause cirrus cloud layer observed during the Balloon measurement campaigns of the Asian Tropopause Aerosol Layer (BATAL) over Hyderabad (17.47 °N, 78.58 °E), India on 23 August 2017. A subvisible cirrus cloud layer (optical thickness ~0.025) was detected by a backscatter sonde (COBALD) onboard a balloon near the cold-point tropopause (CPT, temperature~ -86.4 ° C, altitude~17.9 km) which was later confirmed by the CATS lidar on the ISS. Simultaneous measurements from an optical particle counter (Boulder Counter) revealed the presence of ice crystals smaller than 50 microns in this layer. The formation mechanism responsible for this tropopause cirrus is investigated using a technique combining three-dimensional back-trajectories, satellite observations, and ERA5 reanalysis data. Satellite observations revealed that the overshooting convection associated with a category-3 typhoon Hato, which hit Macau and Hong Kong on 23 August 2017 injected ice into the lower stratosphere. This caused a hydration patch that followed the ASM anticyclone subsequently moving towards Hyderabad. The presence of tropopause cirrus cloud layers in the cold temperature anomalies and updrafts along the back-trajectories indicated towards the role of typhoon-induced gravity waves in their formation. This case study highlights the role of typhoons in influencing the formation of tropopause cirrus clouds through stratospheric hydration and gravity waves in the ASM anticyclone.

Amit Kumar Pandit↗

Uncertainty in Aerosol–Cloud Radiative Forcing Is Driven By Clean Conditions

Atmospheric aerosols and their impact on cloud properties remain the largest uncertainty in the human forcing of the climate system. By increasing the concentration of cloud droplets (Nd), aerosols reduce droplet size and increase the reflectivity of clouds (a negative radiative forcing). Central to this climate impact is the susceptibility of cloud droplet number to aerosol (β), the diversity of which explains much of the variation in the radiative forcing from aerosol–cloud interactions (RFaci) in global climate models. This has made measuring β a key target for developing observational constraints of the aerosol forcing.

Edward Gryspeerdt↗

Martian B Storm Genesis and Evolution: Initial Analysis of Thermal Datasets.

Introduction: Dust lifting on Mars likely occurs primarily as a result of the exchange of momentum between the atmosphere and the surface via saltation. During saltation, sand-sized particles are mobilized but do not enter into suspension. When these larger particles fall back to the surface, kinetic energy is transferred to smaller dust particles which are then lofted into suspension in the atmosphere. Depending on the altitude to which dust is lofted, it can have a significant effect on atmospheric temperatures. As a strong absorber and emitter in the infrared, dust can influence atmospheric heating and modify the global circulation and weather on Mars [1,2]. Although dust is present in Mars’ atmosphere throughout the year, the atmosphere is generally dustier during the second half of the year when Mars is near perihelion. Observations reveal that episodic global-scale dust storms and fairly regular regional-scale dust storms are superimposed on a well-defined and highly repeatable seasonal cycle of dust opacity and associated mid-level atmospheric temperature responses. Kass et al. (2016) used 50 Pa temperature observations from MRO/MCS to identify three highly repeatable time periods during which regional dust storms occur, and designated them the “A”, “B” and “C” storms. While “A” and “C” storms have been studied a fair amount to-date, “B” storms have not yet been investigated in detail. This study explores the generation and evolution of the annually recurring regional dust storm known as the “B” storm, which was identified and categorized by Kass et al. (2016) based on 25 km (50 Pa) temperature observations. The B storm is a southern-hemisphere (SH) phenomenon that originates at the cap edge just after perihelion and which reaches peak intensity during the SH summer solstice, Ls 270. It may originate from the cap edge storms that spawn near the edge of the seasonal CO2 cap during retreat, but the mechanisms for B storm genesis have yet to be determined definitively [1]. Methods: We will use observational data sets and a global climate model (GCM) to investigate “B” regional storms. The data analysis component will include the analysis of imagery from MGS/MOC and MRO/MARCI, and spectroscopic data sets of dust and temperatures from MGS/TES and MRO/MCS with the goal of fully characterizing the behavior of these storms. Both MGS and TES provide data well-suited for temperature analysis at 25 km. MCS measures atmospheric temperature, dust extinction, and water ice extinction at 5 km intervals from the surface to about 80 km. TES measured atmospheric temperatures, column dust and water ice opacities, and column water vapor abundances. Measurements made by TES extended from the surface to about 40 km [1]. At the 50 Pa (25 km) level, local dust events usually confined to shallower depths are effectively filtered out of the analysis leaving the regional dust events identifiable by their temperature signatures [1]. Our preliminary analysis makes use of the fact that the brightness temperature at 15 microns (T15 temperature) is a close approximation to observed temperature at 25 km. We first reproduce the zonal mean 50 Pa level temperature plots for MY 29-32 to establish a baseline for our procedures moving forward [1]. Expanding on Kass et al. (2016), we include recent MCS data from MY 33 and 34 as well. Preliminary Analysis: The daytime (3PM) T15 temperatures in Figure 1 indicate: in MY 29, a strong A storm at Ls 240, a B storm at high southern latitudes just after Ls 270, and a C storm at Ls 320; in MY 30, a B storm at Ls 270; in MY 31 & MY 32, a B storm just before Ls 270; in MY 33, a B storm at Ls 270; and in MY 34, a strong A storm in the northern hemisphere at Ls 210, and a B storm around Ls 270 although there is a data gap. For the B storms, each is indicative of lofted dust and resultant warming. The daytime temperature structure illustrates that the B storm occurs annually around Ls 270 and is confined to high southern latitudes. It reaches its peak intensity around SH summer solstice, Ls 270, consistently for all six MY assessed. Since direct solar heating is absent overnight, the nighttime T15 temperatures (Figure 2) are often useful for differentiating the heat signature of direct solar heating from the dynamical response to that heating. However, in the southern polar latitudes at perihelion the sun does not set and direct solar heating remains present throughout the night. Importantly for our study, dust lofted in the B storm experiences this direct heating day and night for the entirety of its lifetime. The B storm expands as far north as -60 latitude and decays in latitudinal extent more gradually than it grows. This feature is less obvious in the nighttime (3AM) T15 temperatures (Figure 2). The temperature signal is stronger at night for MY 30-33. The warm pool is larger in area relative to the background at night in these four cases. This more uniform warming masks the “tail” feature somewhat, such that it is barely noticeable during these years. Unfortunately, gaps in MCS data in MY 29 and 34 prevent confirmation of the tail feature during those years, however, the B storm temperature signature follows a very different pattern than that described for MY 30-33. MY 29 and 34 appear to show smaller centers of warming at night and larger centers of warming during the day. This is in opposition to that previously described for MY 30-33. Conclusions and Future Work: We will continue investigating the heat signatures of B storms by looking at the total column heating as recorded by TES. We will also look at lower altitudes for patterns that may describe the relationship between B storms and the cap edge storms that develop while the seasonal cap is retreating. In the future, we will use GCM simulations to determine the atmospheric and thermo-dynamic conditions associated with these storms.

Courtney Marylou Batterson↗

The B Regional Dust Storm in the New NASA Ames Mars GCM

Introduction The Thermal Emission Spectrometer (TES) and the Mars Climate Sounder (MCS) instruments have been ob- serving global dust and temperature on Mars twice daily for a combined ∼12 Mars Years (MYs). Analysis of these data by [5] reveal three highly repeatable, regional scale dust events occurring annually during years lack- ing a global dust storm (GDS). Named the "A," "B," and "C" storms in seasonal order, these recurring dust storms develop in the southern hemisphere of Mars during the perihelion season(Ls =180°–360°)when Mars is closest to the sun and the southern hemisphere experiences sum- mer [5]. The "A" and "C" storms occur in the southern midlatitudes where they amplify the Hadley circulation causing dynamical warming in the northern hemisphere. In contrast, the "B" storm (hereafter, B storm) and its ef- fects are entirely confined to the south pole [5]. All three storms are large enough to inject dust above the boundary layer [8]. As a result, the annually-recurring regional storms produce significant temperature perturbations in the middle atmosphere, raising zonal mean 50 Pa ( 25 km) temperatures above 200 K (Figure 1) [5]. In this work, we seek to identify the mechanisms responsible for lofting dust into the middle atmosphere during the B storm by simulating the storm with the new NASA Ames Mars Global Climate Model (MGCM). We find that the simulated B storm is driven by a series of dust plumes that form in the high southern latitudes during southern summer solstice. We also find that radiative-dynamic feedbacks between airborne dust and incoming shortwave radiation are crucial for the pluming mechanism.

C M L Batterson↗

A LaGrangian Perspective of the Surface Energy Budget Contributions to Sea Ice Evolution in the ‘New Arctic’

Recent Arctic warming outpaces global warming and is characterized by dramatic changes in sea ice (record sea ice loss, thinner and more seasonal ice cover), warming SSTs, and a lengthening melt season. These changes impact the surface energy budget and the sensitivity of sea ice to radiative forcing, namely an increased sensitivity of thinner ice to local radiative forcings and a weaker buffering of surface-atmosphere exchanges of heat and moisture. However, these processes are a large source of uncertainty in global climate models with prior studies finding that poor representations of downwelling longwave radiation and sea ice albedo lead to model spread in sea ice conditions. A limitation of prior work is examining sea ice-atmosphere interactions through an Eulerian framework. This study utilizes a sea ice parcel dataset in a LaGrangian framework, allowing for tracking of surface energy budget-sea ice interactions over the lifespan of individual sea ice parcels; this framework also allows for the quantification of the sea ice response to episodic weather events along with seasonal drivers, including the drivers of rapid growth and melt events. First, lag-lead relationships between relevant surface energy budget terms and sea ice thickness changes are explored to understand the atmospheric conditions preceding rapid growth and melt. The impact of episodic events- moisture intrusion, warm air outbreaks, cyclones- on sea ice growth are also investigated by stratifying first-year parcels by sea ice thickness at the end of the growth season and analyzing the effect of atmospheric variability (number and intensity of episodic events) on parcel thickness change. Lastly, parcel growth and melt and the associated radiative anomalies are compared to snowfall events/snow thickness to determine how snowfall modifies the interaction between the local surface energy budget and sea ice mass balance.

Patrick Taylor↗

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗

Climate-Water-Electricity Interactions in the U.S. Under Alternative Decarbonized Futures

The U.S. electric sector is rapidly evolving, with widespread renewable energy deployment, building and transport electrification, and nuanced decarbonization policies. Climate change influences the supply and demand for electricity by altering water resources for cooling and hydropower, thermal plant efficiencies, and heating and cooling demand. This research combines global climate model data, asset-level water and streamflow modeling, and electric sector capacity expansion modeling to study climate-water-electricity interactions across myriad future climate and electricity scenarios that consider electrification and decarbonization using renewable, hydrogen, carbon capture, and nuclear technologies. Multi-model integration leads to insights into power-water sector interactions and their impacts on grid economics and environmental outcomes.

climate change↗

Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model

The global climate effects of time-dependent atmospheric trace gas and aerosol variations are simulated by NASA-Goddard's three-dimensional climate model II, which possesses 8 x 10-deg horizontal resolution, for the cases of a 100-year control run and three different atmospheric composition scenarios in which trace gas growth is respectively a continuation of current exponential trends, a reduced linear growth, and a rapid curtailment of emissions due to which net climate forcing no longer increases after the year 2000. The experiments begin in 1958, run to the present, and encompass measured or estimated changes in CO2, CH4, N2O, chlorofluorocarbons, and stratospheric aerosols. It is shown that the greenhouse warming effect may be clearly identifiable in the 1990s.

Hansen, J.↗

The Added Value to Global Model Projections of Climate Change by Dynamical Downscaling: A Case Study over the Continental U.S. using the GISS-ModelE2 and WRF Models

Dynamical downscaling is being increasingly used for climate change studies, wherein the climates simulated by a coupled atmosphere-ocean general circulation model (AOGCM) for a historical and a future (projected) decade are used to drive a regional climate model (RCM) over a specific area. While previous studies have demonstrated that RCMs can add value to AOGCM-simulated climatologies over different world regions, it is unclear as to whether or not this translates to a better reproduction of the observed climate change therein. We address this issue over the continental U.S. using the GISS-ModelE2 and WRF models, a state-of-the-science AOGCM and RCM, respectively. As configured here, the RCM does not effect holistic improvement in the seasonally and regionally averaged surface air temperature or precipitation for the individual historical decades. Insofar as the climate change between the two decades is concerned, the RCM does improve upon the AOGCM when nudged in the domain proper, but only modestly so. Further, the analysis indicates that there is not a strong relationship between skill in capturing climatological means and skill in capturing climate change. Though additional research would be needed to demonstrate the robustness of this finding in AOGCM/RCM models generally, the evidence indicates that, for climate change studies, the most important factor is the skill of the driving global model itself, suggesting that highest priority should be given to improving the long-range climate skill of AOGCMs.

Racherla, P. N.↗

Characteristics of Tropical Cyclones in High-resolution Models in the Present Climate

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.

Tropical Cyclones↗

Characteristics of Tropical Cyclones in High-Resolution Models of the Present Climate

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) in two types of experiments, using a climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.

Typical Cyclone↗

Climate Change Penalty and Benefit on Surface Ozone: A Global Perspective Based on CMIP6 Earth System Models

This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C−1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C−1, with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C−1, implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

surface ozone↗

Climate change penalty and benefit on surface ozone: a global perspective based on CMIP6 earth system models

Abstract This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C −1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C −1 , with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C −1 , implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

Zanis, Prodromos↗