Review of the Monitoring Programme: Baseline Measurement and Analysis of UK Ozone and UV

The Department for Environment, Food and Rural Affairs (Defra) and the Devolved Administrations (DA) continue to fund a long-running programme Baseline Measurement and Analysis of UK Ozone and UV to monitor column (effectively stratospheric) ozone and surface UV. The main driver for the monitoring programme is the 1985 Vienna Convention on the Protection of the Ozone Layer. The Convention obliges parties (including the UK) to undertake inter alia monitoring, data dissemination and information exchange activities. The current monitoring programme comprises: • measurements of column ozone at two sites in the UK (Lerwick and Reading) • spectrally-resolved UV measurements at one site (Reading) The ozone element of the monitoring programme was reviewed in 2002. Defra has commissioned this review of the programme to ensure that it continues to meet current and future policy and scientific requirements as well as international obligations. The Review The review was structured in terms of 7 questions, which addressed a range of strategic, technical and organisational aspects of the monitoring programme. 1. How does the monitoring programme help to meet the UK obligations under the Vienna Convention on the Protection of the Ozone Layer? 2. Are the data currently collected in the monitoring programme fit for purpose? If not, what measures could be employed to make the data fit for purpose? Are there any activities in the current monitoring programme which are no longer needed? 3. Are the current measurement techniques viable into the future (over a 5-20 year timescale), and what other techniques/instruments are available? 4. Are current methodologies for disseminating information sufficient? If other techniques/instruments are preferable, how (or indeed could) they be introduced whilst maintaining the continuity of the results? 5. Is the current monitoring programme cost effective? 6. Is the current monitoring programme structured for optimum delivery? 7. Should all or part of the programme be competitively tendered, or indeed should it be competitively tendered at all? Summary of Findings The key findings were 1. The current monitoring programme is working well but it has a low profile and impact 2. There are options to evolve the programme but these require further, more detailed evaluation

Leaf phenology amplitude derived from MODIS NDVI and EVI: maps of leaf phenology synchrony for Meso‐ and South America

The leaf phenology (i.e. the seasonality of leaf amount and leaf demography) of ecosystems can be characterized through the use of Earth observation data using a variety of different approaches. The most common approach is to derive time series of vegetation indices (VIs) which are related to the temporal evolution of FPAR, LAI and GPP or alternatively used to derive phenology metrics that quantify the growing season. The product presented here shows a map of average ‘amplitude’ (i.e. maximum minus minimum) of annual cycles observed in MODIS‐derived NDVI and EVI from 2000 to 2013 for Meso‐ and South America. It is a robust determination of the amplitude of annual cycles of vegetation greenness derived from a Lomb–Scargle spectral analysis of unevenly spaced data. VI time series pre‐processing was used to eliminate measurement outliers, and the outputs of the spectral analysis were screened for statistically significant annual signals. Amplitude maps provide an indication of net ecosystem phenology since the satellite observations integrate the greenness variations across the plant individuals within each pixel. The average amplitude values can be interpreted as indicating the degree to which the leaf life cycles of individual plants and species are synchronized. Areas without statistically significant annual variations in greenness may still consist of individuals that show a well‐defined annual leaf phenology. In such cases, the timing of the phenology events will vary strongly within the year between individuals. Alternatively, such areas may consist mainly of plants with leaf turnover strategies that maintain a constant canopy of leaves of different ages. Comparison with in situ observations confirms our interpretation of the average amplitude measure. VI amplitude interpreted as leaf life cycle synchrony can support model evaluation by informing on the likely leaf turn over rates and seasonal variation in ecosystem leaf age distribution

Comparison of greenhouse gas fluxes from tropical forests and oil palm plantations on mineral soil

In Southeast Asia, oil palm (OP) plantations have largely replaced tropical forests. The impact of this shift in land use on greenhouse gas (GHG) fluxes remains highly uncertain, mainly due to a relatively small pool of available data. The aim of this study is to quantify differences of nitrous oxide (N2O) and methane (CH4) fluxes as well as soil carbon dioxide (CO2) respiration rates from logged forests, oil palm plantations of different ages, and an adjacent small riparian area. Nitrous oxide fluxes are the focus of this study, as these emissions are expected to increase significantly due to the nitrogen (N) fertilizer application in the plantations. This study was conducted in the SAFE (Stability of Altered Forest Ecosystems) landscape in Malaysian Borneo (Sabah) with measurements every 2 months over a 2-year period. GHG fluxes were measured by static chambers together with key soil physicochemical parameters and microbial biodiversity. At all sites, N2O fluxes were spatially and temporally highly variable. On average the largest fluxes (incl. 95 % CI) were measured from OP plantations (45.1 (24.0–78.5) µg m−2 h−1 N2O-N), slightly smaller fluxes from the riparian area (29.4 (2.8–84.7) µg m−2 h−1 N2O-N), and the smallest fluxes from logged forests (16.0 (4.0–36.3) µg m−2 h−1 N2O-N). Methane fluxes were generally small (mean ± SD): −2.6 ± 17.2 µg CH4-C m−2 h−1 for OP and 1.3 ± 12.6 µg CH4-C m−2 h−1 for riparian, with the range of measured CH4 fluxes being largest in logged forests (2.2 ± 48.3 µg CH4-C m−2 h−1). Soil respiration rates were larger from riparian areas (157.7 ± 106 mg m−2 h−1 CO2-C) and logged forests (137.4 ± 95 mg m−2 h−1 CO2-C) than OP plantations (93.3 ± 70 mg m−2 h−1 CO2-C) as a result of larger amounts of decomposing leaf litter. Microbial communities were distinctly different between the different land-use types and sites. Bacterial communities were linked to soil pH, and fungal and eukaryotic communities were linked to land use. Despite measuring a large number of environmental parameters, mixed models could only explain up to 17 % of the variance of measured fluxes for N2O, 3 % of CH4, and 25 % of soil respiration. Scaling up measured N2O fluxes to Sabah using land areas for forest and OP resulted in emissions increasing from 7.6 Mt (95 % confidence interval, −3.0–22.3 Mt) yr−1 in 1973 to 11.4 Mt (0.2–28.6 Mt) yr−1 in 2015 due to the increasing area of forest converted to OP plantations over the last ∼ 40 years

Investigation of the summer 2018 European ozone air pollution episodes using novel satellite data and modelling

In the summer of 2018, Europe experienced an intense heat wave which coincided with several persistent large-scale ozone (O3) pollution episodes. Novel satellite data of lower tropospheric column O3 from the Global Ozone Monitoring Experiment-2 (GOME-2) and Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite showed substantial enhancements in 2018 relative to other years since 2012. Surface observations also showed ozone enhancements across large regions of continental Europe in summer 2018 compared to 2017. Enhancements to surface temperature and the O3 precursor gases carbon monoxide and methanol in 2018 were co-retrieved from MetOp observations by the same scheme. This analysis was supported by the TOMCAT chemistry transport model (CTM) to investigate processes driving the observed O3 enhancements. Through several targeted sensitivity experiments we show that meteorological processes, and emissions to a secondary order, were important for controlling the elevated O3 concentrations at the surface. However, mid-tropospheric (~500 hPa) O3 enhancements were dominated by meteorological processes. We find that contributions from stratospheric O3 intrusions ranged between 15&ndash;40 %. Analysis of back trajectories indicates that the import of O3-enriched air masses into Europe originated over the North Atlantic substantially increasing O3 in the 500 hPa layer during summer 2018.</p

Evaluation of wetland CH4 in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations

Wetlands are the largest natural source of methane. The ability to model the emissions of methane from natural wetlands accurately is critical to our understanding of the global methane budget and how it may change under future climate scenarios. The simulation of wetland methane emissions involves a complicated system of meteorological drivers coupled to hydrological and biogeochemical processes. The Joint UK Land Environment Simulator (JULES) is a process-based land surface model that underpins the UK Earth System Model (UKESM) and is capable of generating estimates of wetland methane emissions. In this study, we use GOSAT satellite observations of atmospheric methane along with the TOMCAT global 3-D chemistry transport model to evaluate the performance of JULES in reproducing the seasonal cycle of methane over a wide range of tropical wetlands. By using an ensemble of JULES simulations with differing input data and process configurations, we investigate the relative importance of the meteorological driving data, the vegetation, the temperature dependency of wetland methane production and the wetland extent. We find that JULES typically performs well in replicating the observed methane seasonal cycle. We calculate correlation coefficients to the observed seasonal cycle of between 0.58 and 0.88 for most regions; however, the seasonal cycle amplitude is typically underestimated (by between 1.8 and 19.5 ppb). This level of performance is comparable to that typically provided by state-of-the-art data-driven wetland CH4 emission inventories. The meteorological driving data are found to be the most significant factor in determining the ensemble performance, with temperature dependency and vegetation having moderate effects. We find that neither wetland extent configuration outperforms the other, but this does lead to poor performance in some regions. We focus in detail on three African wetland regions (Sudd, Southern Africa and Congo) where we find the performance of JULES to be poor and explore the reasons for this in detail. We find that neither wetland extent configuration used is sufficient in representing the wetland distribution in these regions (underestimating the wetland seasonal cycle amplitude by 11.1, 19.5 and 10.1 ppb respectively, with correlation coefficients of 0.23, 0.01 and 0.31). We employ the Catchment-based Macro-scale Floodplain (CaMa-Flood) model to explicitly represent river and floodplain water dynamics and find that these JULES-CaMa-Flood simulations are capable of providing a wetland extent that is more consistent with observations in this regions, highlighting this as an important area for future model development.</p

A framework for improved predictions of the climate impacts on potential yields of UK winter wheat and its applicability to other UK crops

•Changes in the frequency of extreme weather events related to climate change potentially pose significant challenges to UK agricultural production. There is a need for improved climate change risk assessments to support adaptation strategies and to ensure security of food production in future. •We describe an innovative and practical framework for spatially explicit modelling of climate change impacts on crop yields, based on the UKCP18 climate projections. Our approach allows the integration of relatively simple crop growth models with high spatial and temporal resolution Earth Observation datasets, describing changes in crop growth parameters within year and over the longer term. We focus on modelling winter wheat, a commercially important crop. We evaluate the results of the model against precision yield data collected from 719 fields. We show that the assimilation of leaf area index data from Sentinel-2 satellite observations improves the agreement of the modelled yields with those observed. Our national-scale results indicate that wheat production initially becomes more favourable under climate change across much of the UK with the projected increase in temperature. From 2050 onwards, yields increase northwards, whilst they decline in South East England as the decrease in precipitation offsets the benefits of rising temperature. •Our framework can readily accommodate growth models for other crops and LAI retrievals from other satellite sensors. The ability to explore impacts of crop yields at fine spatial resolutions is an important part of assessing the potential risks of climate change to UK agriculture and of designing more climate resilient agricultural systems

Increased importance of methane reduction for a 1.5 degree target

To understand the importance of methane on the levels of carbon emission reductions required to achieve temperature goals, a processed-based approach is necessary rather than reliance on the Transient Climate Response to Emissions. We show that plausible levels of methane (CH4) mitigation can make a substantial difference to the feasibility of achieving the Paris climate targets through increasing the allowable carbon emissions. This benefit is enhanced by the indirect effects of CH4 on ozone (O3). Here the differing effects of CH4 and CO2 on land carbon storage, including the effects of surface O3, lead to an additional increase in the allowable carbon emissions with CH4 mitigation. We find a simple robust relationship between the change in the 2100 CH4 concentration and the extra allowable cumulative carbon emissions between now and 2100 (0.27 ± 0.05 GtC per ppb CH4). This relationship is independent of modelled climate sensitivity and precise temperature target, although later mitigation of CH4 reduces its value and thus methane reduction effectiveness. Up to 12% of this increase in allowable emissions is due to the effect of surface ozone. We conclude early mitigation of CH4 emissions would significantly increase the feasibility of stabilising global warming below 1.5C, alongside having co-benefits for human and ecosystem health

Inundation prediction in tropical wetlands from JULES-CaMa-Flood global land surface simulations

Wetlands play a key role in hydrological and biogeochemical cycles and provide multiple ecosystem services to society. However, reliable data on the extent of global inundated areas and the magnitude of their contribution to local hydrological dynamics remain surprisingly uncertain. Global hydrological models and land surface models (LSMs) include only the most major inundation sources and mechanisms; therefore, quantifying the uncertainties in available data sources remains a challenge. We address these problems by taking a leading global data product on inundation extents (Global Inundation Extent from Multi-Satellites, GIEMS) and matching against predictions from a global hydrodynamic model (Catchment-based Macro-scale Floodplain – CaMa-Flood) driven by runoff data generated by a land surface model (Joint UK Land and Environment Simulator, JULES). The ability of the model to reproduce patterns and dynamics shown by the observational product is assessed in a number of case studies across the tropics, which show that it performs well in large wetland regions, with a good match between corresponding seasonal cycles. At a finer spatial scale, we found that water inputs (e.g. groundwater inflow to wetland) became underestimated in comparison to water outputs (e.g. infiltration and evaporation from wetland) in some wetlands (e.g. Sudd, Tonlé Sap), and the opposite occurred in others (e.g. Okavango) in our model predictions. We also found evidence for an underestimation of low levels of inundation in our satellite-based inundation data (approx. 10 % of total inundation may not be recorded). Additionally, some wetlands display a clear spatial displacement between observed and simulated inundation as a result of overestimation or underestimation of overbank flooding upstream. This study provides timely information on inherent biases in inundation prediction and observation that can contribute to our current ability to make critical predictions of inundation events at both regional and global levels

Regional variation in the effectiveness of methane-based and land-based climate mitigation options

Scenarios avoiding global warming greater than 1.5 or 2°C, as stipulated in the Paris Agreement, may require the combined mitigation of anthropogenic greenhouse gas emissions alongside enhancing negative emissions through approaches such as afforestation/reforestation (AR) and biomass energy with carbon capture and storage (BECCS). We use the JULES land-surface model coupled to an inverted form of the IMOGEN climate emulator to investigate mitigation scenarios that achieve the 1.5 or 2°C warming targets of the Paris Agreement. Specifically, within this IMOGEN-JULES framework, we focus on and characterise the global and regional effectiveness of land-based (BECCS and/or AR) and anthropogenic methane (CH4) emission mitigation, separately and in combination, on the anthropogenic fossil fuel carbon dioxide (CO2) emission budgets (AFFEBs) to 2100. We use consistent data and socio-economic assumptions from the IMAGE integrated assessment model for the second Shared Socioeconomic Pathway (SSP2). The analysis includes the effects of the methane and carbon-climate feedbacks from wetlands and permafrost thaw, which we have shown previously to be significant constraints on the AFFEBs. Globally, mitigation of anthropogenic CH4 emissions has large impacts on the anthropogenic fossil fuel emission budgets, potentially offsetting (i.e. allowing extra) carbon dioxide emissions of 188-212 GtC. This is because of (a) the reduction in the direct and indirect radiative forcing of methane in response to the lower emissions and hence atmospheric concentration of methane; and (b) carbon-cycle changes leading to increased uptake by the land and ocean by CO2-based fertilisation. Methane mitigation is beneficial everywhere, particularly for the major CH4-emitting regions of India, USA and China. Land-based mitigation has the potential to offset 51-100 GtC globally, the large range reflecting assumptions and uncertainties associated with BECCS. The ranges for CH4 reduction and BECCs implementation are valid for both the 1.5° and 2°C warming targets. 2 That is the mitigation potential of the CH4 and of the land-based scenarios is similar for whether society aims for one or other 35 of the final stabilised warming levels. Further, both the effectiveness and the preferred land-management strategy (i.e., AR or BECCS) have strong regional dependencies. Additional analysis shows extensive BECCS could adversely affect water security for several regions. Although the primary requirement remains mitigation of fossil fuel emissions, our results highlight the potential for the mitigation of CH4 emissions to make the Paris climate targets more achievabl

Evaluation of wetland CH4 in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations

Wetlands are the largest natural source of methane. The ability to model the emissions of methane from natural wetlands accurately is critical to our understanding of the global methane budget and how it may change under future climate scenarios. The simulation of wetland methane emissions involves a complicated system of meteorological drivers coupled to hydrological and biogeochemical processes. The Joint UK Land Environment Simulator (JULES) is a process-based land surface model that underpins the UK Earth System Model (UKESM) and is capable of generating estimates of wetland methane emissions. In this study, we use GOSAT satellite observations of atmospheric methane along with the TOMCAT global 3-D chemistry transport model to evaluate the performance of JULES in reproducing the seasonal cycle of methane over a wide range of tropical wetlands. By using an ensemble of JULES simulations with differing input data and process configurations, we investigate the relative importance of the meteorological driving data, the vegetation, the temperature dependency of wetland methane production and the wetland extent. We find that JULES typically performs well in replicating the observed methane seasonal cycle. We calculate correlation coefficients to the observed seasonal cycle of between 0.58 and 0.88 for most regions; however, the seasonal cycle amplitude is typically underestimated (by between 1.8 and 19.5 ppb). This level of performance is comparable to that typically provided by state-of-the-art data-driven wetland CH4 emission inventories. The meteorological driving data are found to be the most significant factor in determining the ensemble performance, with temperature dependency and vegetation having moderate effects. We find that neither wetland extent configuration outperforms the other, but this does lead to poor performance in some regions. We focus in detail on three African wetland regions (Sudd, Southern Africa and Congo) where we find the performance of JULES to be poor and explore the reasons for this in detail. We find that neither wetland extent configuration used is sufficient in representing the wetland distribution in these regions (underestimating the wetland seasonal cycle amplitude by 11.1, 19.5 and 10.1 ppb respectively, with correlation coefficients of 0.23, 0.01 and 0.31). We employ the Catchment-based Macro-scale Floodplain (CaMa-Flood) model to explicitly represent river and floodplain water dynamics and find that these JULES-CaMa-Flood simulations are capable of providing a wetland extent that is more consistent with observations in this regions, highlighting this as an important area for future model development