Description: A quality assessment of the CFC-11 (CCl3F), CFC-12 (CCl2F2), HF, and SF6 products from limb-viewing satellite instruments is provided by means of a detailed intercomparison. The climatologies in the form of monthly zonal mean time series are obtained from HALOE, MIPAS, ACE-FTS, and HIRDLS within the time period 1991-2010. The intercomparisons focus on the mean biases of the monthly and annual zonal mean fields and aim to identify their vertical, latitudinal and temporal structure. The CFC evaluations (based on MIPAS, ACE-FTS and HIRDLS) reveal that the uncertainty in our knowledge of the atmospheric CFC-11 and CFC-12 mean state, as given by satellite data sets, is smallest in the tropics and mid-latitudes at altitudes below 50 and 20 hPa, respectively, with a 1sigma multi-instrument spread of up to ±5 %. For HF, the situation is reversed. The two available data sets (HALOE and ACE-FTS) agree well above 100 hPa, with a spread in this region of ±5 to ±10 %, while at altitudes below 100 hPa the HF annual mean state is less well known, with a spread ±30 % and larger. The atmospheric SF6 annual mean states derived from two satellite data sets (MIPAS and ACE-FTS) show only very small differences with a spread of less than ±5 % and often below ±2.5 %. While the overall agreement among the climatological data sets is very good for large parts of the upper troposphere and lower stratosphere (CFCs, SF6) or middle stratosphere (HF), individual discrepancies have been identified. Pronounced deviations between the instrument climatologies exist for particular atmospheric regions which differ from gas to gas. Notable features are differently shaped isopleths in the subtropics, deviations in the vertical gradients in the lower stratosphere and in the meridional gradients in the upper troposphere, and inconsistencies in the seasonal cycle. Additionally, long-term drifts between the instruments have been identified for the CFC-11 and CFC-12 time series. The evaluations as a whole provide guidance on what data sets are the most reliable for applications such as studies of atmospheric transport and variability, model-measurement comparisons and detection of long-term trends.

Description: Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(10), (2021): E1897–E1935, https://doi.org/10.1175/BAMS-D-19-0316.1.

Description: Life on Earth vitally depends on the availability of water. Human pressure on freshwater resources is increasing, as is human exposure to weather-related extremes (droughts, storms, floods) caused by climate change. Understanding these changes is pivotal for developing mitigation and adaptation strategies. The Global Climate Observing System (GCOS) defines a suite of essential climate variables (ECVs), many related to the water cycle, required to systematically monitor Earth’s climate system. Since long-term observations of these ECVs are derived from different observation techniques, platforms, instruments, and retrieval algorithms, they often lack the accuracy, completeness, and resolution, to consistently characterize water cycle variability at multiple spatial and temporal scales. Here, we review the capability of ground-based and remotely sensed observations of water cycle ECVs to consistently observe the hydrological cycle. We evaluate the relevant land, atmosphere, and ocean water storages and the fluxes between them, including anthropogenic water use. Particularly, we assess how well they close on multiple temporal and spatial scales. On this basis, we discuss gaps in observation systems and formulate guidelines for future water cycle observation strategies. We conclude that, while long-term water cycle monitoring has greatly advanced in the past, many observational gaps still need to be overcome to close the water budget and enable a comprehensive and consistent assessment across scales. Trends in water cycle components can only be observed with great uncertainty, mainly due to insufficient length and homogeneity. An advanced closure of the water cycle requires improved model–data synthesis capabilities, particularly at regional to local scales.

Description: WD acknowledges ESA’s QA4EO (ISMN) and CCI Soil Moisture projects. WD, CRV, AG, and KL acknowledge the G3P project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement 870353. MIH and MS acknowledge ESA’s CCI Water Vapour project. MS and RH acknowledges the support by the EUMETSAT member states through CM SAF. DGM acknowledges support from the European Research Council (ERC) under Grant Agreement 715254 (DRY–2–DRY). Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004).

Description: 2022-04-01

Description: Reanalysis data sets are widely used to understand atmospheric processes and past variability, and are often used to stand in as "observations" for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. In this paper, we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere–troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. We also provide a systematic documentation of the treatment of WV and O3 in current reanalyses to aid future research and guide the interpretation of differences amongst reanalysis fields. The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. However, significant biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses. In contrast to O3, reanalysis estimates of stratospheric WV are not directly constrained by assimilated data. Observations of atmospheric humidity are typically used only in the troposphere, below a specified vertical level at or near the tropopause. The fidelity of reanalysis stratospheric WV products is therefore mainly dependent on the reanalyses' representation of the physical drivers that influence stratospheric WV, such as temperatures in the tropical tropopause layer, methane oxidation, and the stratospheric overturning circulation. The lack of assimilated observations and known deficiencies in the representation of stratospheric transport in reanalyses result in much poorer agreement amongst observational and reanalysis estimates of stratospheric WV. Hence, stratospheric WV products from the current generation of reanalyses should generally not be used in scientific studies.

Description: The climate research community uses atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere, yet different reanalyses may give very different results for the same diagnostics. The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP) is a coordinated activity to compare reanalysis data sets using a variety of key diagnostics. The objectives of this project are to identify differences among reanalyses and understand their underlying causes, to provide guidance on appropriate usage of various reanalysis products in scientific studies, particularly those of relevance to SPARC, and to contribute to future improvements in the reanalysis products by establishing collaborative links between reanalysis centres and data users. The project focuses predominantly on differences among reanalyses, although studies that include operational analyses and studies comparing reanalyses with observations are also included when appropriate. The emphasis is on diagnostics of the upper troposphere, stratosphere, and lower mesosphere. This paper summarizes the motivation and goals of the S-RIP activity and extensively reviews key technical aspects of the reanalysis data sets that are the focus of this activity. The special issue "The SPARC Reanalysis Intercomparison Project (S-RIP)" in this journal serves to collect research with relevance to the S-RIP in preparation for the publication of the planned two (interim and full) S-RIP reports.

Description: Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, 〈 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.