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In this study we examine the determination accuracy of both the mean radiant temperature (Tmrt) and the Universal Thermal Climate Index (UTCI) within the scope of numerical weather prediction (NWP), and global (GCM) and regional (RCM) climate model simulations. First, Tmrt is determined and the so-called UTCI-Fiala model is then used for the calculation of UTCI. Taking into account the uncertainties of NWP model (among others the HIgh Resolution Limited Area Model HIRLAM) output (temperature, downwelling short-wave and long-wave radiation) stated in the literature, we simulate and discuss the uncertainties of Tmrt and UTCI at three stations in different climatic regions of Europe. The results show that highest negative (positive) differences to reference cases (under assumed clear-sky conditions) of up to -21°C (9°C) for Tmrt and up to -6°C (3.5°C) for UTCI occur in summer (winter) due to cloudiness. In a second step, the uncertainties of RCM simulations are analyzed: three RCMs, namely ALADIN (Aire Limitée Adaptation dynamique Développement InterNational), RegCM (REGional Climate Model) and REMO (REgional MOdel) are nested into GCMs and used for the prediction of temperature and radiation fluxes in order to estimate Tmrt and UTCI. The inter-comparison of RCM output for the three selected locations shows that biases between 0.0 and ±17.7°C (between 0.0 and ±13.3°C) for Tmrt (UTCI), and RMSE between ±0.5 and ±17.8°C (between ±0.8 and ±13.4°C) for Tmrt (UTCI) may be expected. In general the study shows that uncertainties of UTCI, due to uncertainties arising from calculations of radiation fluxes (based on NWP models) required for the prediction of Tmrt, are well below ±2°C for clear-sky cases. However, significant higher uncertainties in UTCI of up to ±6°C are found, especially when prediction of cloudiness is wrong.

Forest biomass is one of the main contributors to the EU's renewable energy target of 20% gross final energy consumption in 2020 (Renewable Energy Directive). Following the RED, new sustainability principles are launched by the European energy sector, such as the Initiative Wood Pellet Buyers (IWPB or SBP). The aim of our study is the investigation of the quantitative impacts from IWPB's principles for forest biomass for energy only. We deploy a bottom up method that quantifies the supplies and the costs from log harvest until forest chip delivery at a domestic consumer. We have a reference situation with existing national (forest) legislation and voluntary certification schemes (scenario 1) and a future situation with additional criteria based on the IWPB principles (scenario 2). Two country studies were selected for our (2008) survey: one in Finland with nearly 100% certification and one in Leningrad province with a minor areal share of certification in scenario 1. The sustainable potential of forest resources for energy is about 54 Mm3 (385 PJ) in Finland and about 13.5 Mm3 (95 PJ) in Leningrad in scenario 1 without extra criteria. The potential volumes reduce considerably by maximum 43% respectively 39% after new criteria from the IWPB, like a minimum use of sawlogs, stumps and slash for energy, and by an increased area of protected forests (scenario 2A Maximum extra restrictions). In case sawlogs can be used, but instead ash recycling is applied after a maximum stump and slash recovery (scenario 2B Minimum extra restrictions), the potential supply is less reduced: 5% in Finland and 22% in Leningrad region. The estimated reference costs for forest chips are between €18 and €45 solid m-3 in Finland and between €7 and €33 solid m-3 in the Leningrad region. In scenario 2A, the costs will mainly increase by €7 m-3 for delimbing full trees (Finland), and maximum €0.3 m-3 for suggested improved forest management (Leningrad region). In scenario 2B, when ash recycling is applied, costs increase by about €0.3 to €1.6 m-3, depending on the rate of soil contamination. This is an increase of 2%, on top of the costs in scenario 2A.

The river flow regime and water resources are highly important for economic growths, flood security, and ecosystem dynamics in the Mekong basin - an important transboundary river basin in South East Asia. The river flow, although remains relatively unregulated, is expected to be increasingly perturbed by climate change and rapidly accelerating socioeconomic developments. Current understanding about hydrological changes under the combined impacts of these drivers, however, remains limited. This study presents projected hydrological changes caused by multiple drivers, namely climate change, large-scale hydropower developments, and irrigated land expansions by 2050s. We found that the future flow regime is highly susceptible to all considered drivers, shown by substantial changes in both annual and seasonal flow distribution. While hydropower developments exhibit limited impacts on annual total flows, climate change and irrigation expansions cause changes of +15% and -3% in annual flows, respectively. However, hydropower developments show the largest seasonal impacts characterized by higher dry season flows (up to +70%) and lower wet season flows (-15%). These strong seasonal impacts tend to outplay those of the other drivers, resulting in the overall hydrological change pattern of strong increases of the dry season flow (up to +160%); flow reduction in the first half of the wet season (up to -25%); and slight flow increase in the second half of the wet season (up to 40%). Furthermore, the cumulative impacts of all drivers cause substantial flow reductions during the early wet season (up to -25% in July), posing challenges for crop production and saltwater intrusion in the downstream Mekong Delta. Substantial flow changes and their consequences require careful considerations of future development activities, as well as timely adaptation to future changes.

This review gathers information about the current legal requirements related to the emission of ammonia and greenhouse gases from animal housing in 21 out of the 28 EU countries and in 5 non-EU countries. Overall the review shows that most of the included countries have established substantial procedures to limit ammonia emission and practically no procedures to limit greenhouse gas emission. The review can also be seen as an introduction to the substantial initiatives and decisions taken by the EU in relation to ammonia emission from animal housing, and as a notification on the absence of corresponding initiatives and decisions in relation to greenhouse gases. An EU directive on industrial emissions from 2010 and an implementation decision from 2017 are the main general instruments to reduce ammonia emission from animal housing in the EU. These treaties put limits to ammonia emissions from installations with more than 2000 places for fattening pigs, with more than 750 places for sows and with more than 40,000 places for poultry. As an example, the upper general limit for fattening pigs is 2.6 kg ammonia per animal place per year. This review indicates that the important animal producing countries in the EU have implemented the EU requirements, and, that only a few countries with a large pig population, in relation to their geographical size, have implemented requirements that are stricter than what is required by the EU.

------------------------------------------------------------------------------------------------------------------------------------------- This version has been superseded. The latest version is at https://doi.org/10.5281/zenodo.5517550 ------------------------------------------------------------------------------------------------------------------------------------------- Eddy covariance flux tower datasets of all Urban-PLUMBER sites, associated with the manuscript: "Harmonized, gap-filled dataset from 20 urban flux tower sites" Use of any data must give credit through citation of the above manuscript and other sources as appropriate. We recommend data users consult with site contributing authors and/or the coordination team in the project planning stage. Relevant contacts are included in timeseries metadata. For site information and timeseries plots see https://urban-plumber.github.io/sites. For processing code see https://github.com/matlipson/urban-plumber_pipeline. Within each site folder: - `index.html`: A summary page with site characteristics and timeseries plots. - `SITENAME_sitedata_vX.csv`: comma seperated file for numerical site characteristics e.g. location, surface cover fraction etc. - `timeseries/` (following files available as netCDF and txt) - `SITENAME_raw_observations_vX`: site observed timeseries before project-wide quality control. - `SITENAME_clean_observations_vX`: site observed timeseries after project-wide quality control. - `SITENAME_metforcing_vX`: site observed timeseries after project-wide quality control and gap filling. - `SITENAME_era5_corrected_vX`: site ERA5 surface data (1990-2020) with bias corrections as applied in the final dataset. - `log_processing_SITENAME_vX.txt`: a log of the print statements through running the create_dataset_SITENAME scripts. Authors Mathew Lipson, Sue Grimmond, Martin Best, Andreas Christen, Andrew Coutts, Ben Crawford, Bert Heusinkveld, Erik Velasco, Helen Claire Ward, Hirofumi Sugawara, Je-Woo Hong, Jinkyu Hong, Jonathan Evans, Joseph McFadden, Keunmin Lee, Krzysztof Fortuniak, Leena Järvi, Matthias Roth, Nektarios Chrysoulakis, Nigel Tapper, Oliver Michels, Simone Kotthaus, Stevan Earl, Sungsoo Jo, Valéry Masson, Winston Chow, Wlodzimierz Pawlak, Yeon-Hee Kim. Corresponding author: Mathew Lipson <m.lipson@unsw.edu.au>

AbstractThe recent rise in atmospheric methane (CH4) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom‐up (BU) process‐based biogeochemical models and top‐down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi‐model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better‐performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU‐ and TD‐based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year−1) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter‐site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site‐specific and ecosystem‐specific variabilities inferred from observations.

The warming of the climate system is unequivocal as evidenced by an increase in global temperatures by 0.8C over the past century. However, the attribution of the observed warming to human activities remains less clear, particularly because of the apparent slow-down in warming since the late 1990s. Here we analyse radiative forcing and temperature time series with state-of-the-art statistical methods to address this question without climate model simulations. We show that long-term trends in total radiative forcing and temperatures have largely been determined by atmospheric greenhouse gas concentrations, and modulated by other radiative factors. We identify a pronounced increase in the growth rates of both temperatures and radiative forcing around 1960, which marks the onset of sustained global warming. Our analyses also reveal a contribution of human interventions to two periods when global warming slowed down. Our statistical analysis suggests that the reduction in the emissions of ozone-depleting substances under the Montreal Protocol, as well as a reduction in methane emissions, contributed to the lower rate of warming since the 1990s. Furthermore, we identify a contribution from the two world wars and the Great Depression to the documented cooling in the mid-twentieth century, through lower carbon dioxide emissions. We conclude that reductions in greenhouse gas emissions are effective in slowing the rate of warming in the short term.

Climate Data Records of soil moisture are fundamental for improving our understanding of long-term dynamics in the coupled water, energy, and carbon cycles over land. To respond to this need, in 2012 the European Space Agency (ESA) released the first multi-decadal, global satellite-observed soil moisture (SM) dataset as part of its Climate Change Initiative (CCI) program. This product, named ESA CCI SM, combines various single-sensor active and passive microwave soil moisture products into three harmonised products: a merged ACTIVE, a merged PASSIVE, and a COMBINED active + passive microwave product. Compared to the first product release, the latest version of ESA CCI SM includes a large number of enhancements, incorporates various new satellite sensors, and extends its temporal coverage to the period 1978–2015. In this study, we first provide a comprehensive overview of the characteristics, evolution, and performance of the ESA CCI SM products. Based on original research and a review of existing literature we show that the product quality has steadily increased with each successive release and that the merged products generally outperform the single-sensor input products. Although ESA CCI SM generally agrees well with the spatial and temporal patterns estimated by land surface models and observed in-situ, we identify surface conditions (e.g., dense vegetation, organic soils) for which it still has large uncertainties. Second, capitalising on the results of > 100 research studies that made use of the ESA CCI SM data we provide a synopsis of how it has contributed to improved process understanding in the following Earth system domains: climate variability and change, land-atmosphere interactions, global biogeochemical cycles and ecology, hydrological and land surface modelling, drought applications, and meteorology. While in some disciplines the use of ESA CCI SM is already widespread (e.g. in the evaluation of model soil moisture states) in others (e.g. in numerical weather prediction or flood forecasting) it is still in its infancy. The latter is partly related to current shortcomings of the product, e.g., the lack of near-real-time availability and data gaps in time and space. This study discloses the discrepancies between current ESA CCI SM product characteristics and the preferred characteristics of long-term satellite soil moisture products as outlined by the Global Climate Observing System (GCOS), and provides important directions for future ESA CCI SM product improvements to bridge these gaps.