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Terrestrial climate is influenced by various land–atmosphere interactions that involve numerous land surface state variables. In several regions on Earth, soil moisture plays an important role for climate via its control on the partitioning of net radiation into sensible and latent heat fluxes; consequently, soil moisture also impacts on temperature and precipitation. The Global Land–Atmosphere Coupling Experiment–Coupled Model Intercomparison Project phase 5 (GLACE-CMIP5) aims to quantify the impact of soil moisture on these important climate variables and to trace the individual coupling mechanisms. GLACE-CMIP5 provides experiments with different soil moisture prescriptions that can be used to isolate the effect of soil moisture on climate. Using a theoretical framework that relies on the distinct relation of soil moisture with evaporative fraction (the ratio of latent heat flux over net radiation) in different soil moisture regimes, the climate impact of the soil moisture prescriptions in the GLACE-CMIP5 experiments can be emulated and quantified. The framework-based estimation of the soil moisture effect on the evaporative fraction agrees very well with estimations obtained directly from the GLACE-CMIP5 experiments (pattern correlation of 0.85). Moreover, the soil moisture effect on the daily maximum temperature is well captured in regions where soil moisture exerts a strong control on latent heat fluxes. The theoretical approach is further applied to quantify the soil moisture contribution to the projected change of the temperature on the hottest day of the year, confirming recent estimations by other studies. Finally, GLACE-style soil moisture prescriptions are emulated in an extended set of CMIP5 models. The results indicate consistency between the soil moisture–climate coupling strength estimated with the GLACE-CMIP5 and the CMIP5 models. Although the theoretical approach is only designed to capture the local soil moisture–climate coupling strength, it can also help to distinguish non-local from local soil moisture–atmosphere feedbacks where sensitivity experiments (such as GLACE-CMIP5) are available. Overall, the theoretical framework-based approach presented here constitutes a simple and powerful tool to quantify local soil moisture–climate coupling in both the GLACE-CMIP5 and CMIP5 models that can be applied in the absence of dedicated sensitivity experiments. [ABSTRACT FROM AUTHOR]

Abstract: The evolution of near‐surface air temperature is influenced by various dynamical, radiative, and surface‐atmosphere exchange processes whose contributions are still not completely quantified. Applying stepwise multiple linear regression to Coupled Model Intercomparison Project phase 5 (CMIP5) model simulations and focusing on radiation (diagnosed by incoming shortwave and incoming longwave radiation) and land surface conditions (diagnosed by soil moisture and albedo) about 79% of the interannual variability and 99% of the multidecadal trend of monthly mean daily maximum temperature over land can be explained. The linear model captures well the temperature variability in middle‐to‐high latitudes and in regions close to the equator, whereas its explanatory potential is limited in deserts. While radiation is an essential explanatory variable over almost all of the analyzed domain, land surface conditions show a pronounced relation to temperature in some confined regions. These findings highlight that considering local‐to‐regional processes is crucial for correctly assessing interannual temperature variability and future temperature trends. [ABSTRACT FROM AUTHOR]

Terrestrial climate is influenced by various land-atmosphere interactions that involve numerous land surface state variables. In several regions on Earth, soil moisture plays an important role for climate through its control on the partitioning of net radiation into sensible and latent heat fluxes and, consequently, its impact on temperature and precipitation. The Global Land-Atmosphere Climate Experiment-Coupled Model Intercomparison Project phase 5 (GLACE-CMIP5) aims to quantify the impact of soil moisture on these important climate variables and to trace the individual coupling mechanisms. GLACE-CMIP5 provides experiments with different soil moisture prescriptions that can be used to isolate the effect of soil moisture on climate. Using a theoretical approach that relies on the distinct relation of soil moisture with evaporative fraction (the ratio of latent heat flux over net radiation) and daily maximum near-surface air temperature in different soil moisture regimes, the climate impact of the soil moisture prescriptions in the GLACE-CMIP5 experiments can be emulated and quantified. The theoretical estimation of the soil moisture effect on evaporative fraction agrees very well with estimations obtained directly from the GLACE-CMIP5 experiments (pattern correlation of 0.85). Moreover, the soil moisture effect on daily maximum temperature is well captured in those regions where soil moisture exerts a strong control on latent heat fluxes. The theoretical approach is further applied to quantify the soil moisture contribution to the projected change of the temperature on the hottest day of the year, confirming recent estimations by other studies. Finally, GLACE-style soil moisture prescriptions are emulated in an extended set of CMIP5 models. The results indicate consistency between the soil moisture-climate coupling strength estimated with GLACE-CMIP5 and CMIP5 models. Although the theoretical approach is designed to capture only the local soil moisture-climate coupling strength, it can also help to distinguish non-local from local soil moisture-atmosphere feedbacks where sensitivity experiments (such as GLACE-CMIP5) are available. Overall, the presented theoretical approach constitutes a simple and powerful tool to quantify local soil moisture-climate coupling in both GLACE-CMIP5 and CMIP5 models that can be applied in the absence of dedicated sensitivity experiments. [ABSTRACT FROM AUTHOR]

Soil moisture plays a crucial role for the energy partitioning at Earth's surface. Changing fractions of latent and sensible heat fluxes caused by soil moisture variations can affect both near-surface air temperature and precipitation. In this study, a simple framework for the dependence of evaporative fraction (the ratio of latent heat flux over net radiation) on soil moisture is used to analyze spatial and temporal variations of land-atmosphere coupling and its effect on near-surface air temperature. Using three different data sources (two reanalysis datasets and one combination of different datasets), three key parameters for the relation between soil moisture and evaporative fraction are estimated: 1) the frequency of occurrence of different soil moisture regimes, 2) the sensitivity of evaporative fraction to soil moisture in the transitional soil moisture regime, and 3) the critical soil moisture value that separates soil moisture- and energy-limited evapotranspiration regimes. The results show that about 30%-60% (depending on the dataset) of the global land area is in the transitional regime during at least half of the year. Based on the identification of transitional regimes, the effect of changes in soil moisture on near-surface air temperature is analyzed. Typical soil moisture variations (standard deviation) can impact air temperature by up to 1.1-1.3 K, while changing soil moisture over its full range in the transitional regime can alter air temperature by up to 6-7 K. The results emphasize the role of soil moisture for atmosphere and climate and constitute a useful benchmark for the evaluation of the respective relationships in Earth system models. [ABSTRACT FROM AUTHOR]

This paper presents an update of a basin-scale diagnostic dataset of monthly variations in terrestrial water storage for large river basins worldwide (BSWB v2016, doi:10.5905/ethz-1007-82). Terrestrial water storage comprises all forms of water storage on land surfaces, and its seasonal and inter-annual variations are mostly determined by soil moisture, groundwater, snow cover, and surface water. The dataset presented is derived using a combined atmospheric and terrestrial water-balance approach with conventional streamflow measurements and reanalysis data of atmospheric moisture flux convergence. It extends a previous, existing version of the dataset (Mueller et al., 2011) temporally and spatially. [ABSTRACT FROM AUTHOR]

This paper presents an update of a basin-scale diagnostic dataset of monthly variations in terrestrial water storage for large river basins worldwide (BSWB v2016, http://dx.doi.org/10.5905/ethz-1007-58doi:10.5905/ethz-1007-58). Terrestrial water storage comprises all forms of water storage on land surfaces, and its seasonal and inter-annual variations are mostly determined by soil moisture, groundwater, snow cover, and surface water. The presented dataset is derived using a combined atmospheric and terrestrial water-balance approach with conventional streamflow measurements and re-analysis data of atmospheric moisture flux convergence. It extends a previous existing version of the dataset (Mueller et al., 2011) temporally and spatially. [ABSTRACT FROM AUTHOR]

Monthly weather forecasts (MOFCs) were shown to have skill in extratropical continental regions for lead times up to 3 weeks, in particular for temperature and if weekly averaged. This skill could be exploited in practical applications for implementations exhibiting some degree of memory or inertia toward meteorological drivers, potentially even for longer lead times. Many agricultural applications fall into these categories because of the temperature-dependent development of biological organisms, allowing simulations that are based on temperature sums. Most such agricultural models require local weather information at daily or even hourly temporal resolution, however, preventing direct use of the spatially and temporally aggregated information of MOFCs, which may furthermore be subject to significant biases. By the example of forecasting the timing of life-phase occurrences of the codling moth (Cydia pomonella), which is a major insect pest in apple orchards worldwide, the authors investigate the application of downscaled weekly temperature anomalies of MOFCs for use in an impact model requiring hourly input. The downscaling and postprocessing included the use of a daily weather generator and a resampling procedure for creating hourly weather series and the application of a recalibration technique to correct for the original underconfidence of the forecast occurrences of codling moth life phases. Results show a clear skill improvement of up to 3 days in root-mean-square error over the full forecast range when incorporating MOFCs as compared with deterministic benchmark forecasts using climatological information for predicting the timing of codling moth life phases. [ABSTRACT FROM AUTHOR]

Global warming will lead to earlier beginnings and prolongation of growing seasons in temperate regions and will have pronounced effects on phenology and life-history adaptation in many species. These changes were not easy to simulate for actual phenologies because of the rudimentary temporal (season) and spatial (regional) resolution of climate model projections. We investigate the effect of climate change on the regional incidence of a pest insect with nearly worldwide distribution and very high potential for adaptation to season length and temperature - the Codling Moth, Cydia pomonella. Seasonal and regional climate change signals were downscaled to the hourly temporal scale of a pest phenology model and the spatial scale of pest habitats using a stochastic weather generator operating at daily scale in combination with a resampling approach for simulation of hourly weather data. Under future conditions of increased temperatures (2045-2074), the present risk of below 20% for a pronounced second generation (peak larval emergence) in Switzerland will increase to 70-100%. The risk of an additional third generation will increase from presently 0-2% to 100%. We identified a significant two-week shift to earlier dates in phenological stages, such as overwintering adult flight. The relative extent (magnitude) of first generation pupae and all later stages will significantly increase. The presence of first generation pupae and later stages will be prolonged. A significant decrease in the length of overlap of first and second generation larval emergence was identified. Such shifts in phenology may induce changes in life-history traits regulating the life cycle. An accordingly lifehistory adaptation in photoperiodic diapause induction to shorter day-length is expected and would thereby even more increase the risk of an additional generation. With respect to Codling Moth management, the shifts in phenology and voltinism projected here will require adaptations of plant protection strategies to maintain their sustainability. [ABSTRACT FROM AUTHOR]

In a previous study, an intra-annual relationship of observed precipitation, manifested by negative correlations between domain-averaged spring and autumn precipitation of the same year, was found in two domains covering France and Central Europe for the period 1972-1990 (Hirschi et al., J Geophys Res 112(D22109), ). Here, this link and its temporal evolution over France during the twentieth century is further investigated and related to the atmospheric circulation and North Atlantic/Mediterranean sea surface temperature (SST) patterns. Observational datasets of precipitation, mean sea level pressure (MSLP), atmospheric teleconnection patterns, and SST, as well as various global and regional climate model simulations are analyzed. The investigation of observed precipitation by means of a running correlation with a 30-year time window for the period 1901-present reveals a decreasing trend in the spring-to-autumn correlations, which become significantly negative in the second half of the twentieth century. These negative correlations are connected with similar spring-to-autumn correlations in observed MSLP, and with negatively correlated spring East Atlantic (EA) and autumn Scandinavian (SCA) teleconnection pattern indices. Maximum covariance analyses of SST with these atmospheric variables indicate that at least part of the identified spring-to-autumn link is mediated through SST, as spring precipitation and MSLP are connected with the same autumn SST pattern as are autumn precipitation, MSLP and the SCA pattern index. Except for ERA-40 driven regional climate models from the EU-FP6 project ENSEMBLES, the analyzed regional and global climate models, including Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) simulations, do not capture this observed variability in precipitation. This is associated with the failure of most models in simulating the observed correlations between spring and autumn MSLP. While the causes for the identified relationship cannot be fully established its timing suggests a possible link with increased aerosol loading in the global dimming period. [ABSTRACT FROM AUTHOR]

This paper presents a new diagnostic dataset of monthly variations in terrestrial water storage for 37 midlatitude river basins in Europe, Asia, North America, and Australia. Terrestrial water storage is the sum of all forms of water storage on land surfaces, and its seasonal and interannual variations are in principle determined by soil moisture, groundwater, snow cover, and surface water. The dataset is derived with the combined atmospheric and terrestrial water-balance approach using conventional streamflow measurements and atmospheric moisture convergence data from the ECMWF 40-yr Re-Analysis (ERA-40). A recent study for the Mississippi River basin (Seneviratne et al. 2004) has demonstrated the validity of this diagnostic approach and found that it agreed well with in situ observations in Illinois. The present study extends this previous analysis to other regions of the midlatitudes. A systematic analysis is presented of the slow drift that occurs with the water-balance approach. It is shown that the drift not only depends on the size of the catchment under consideration, but also on the geographical region and the underlying topography. The drift is in general not constant in time, but artificial inhomogeneities may result from changes in the global observing system used in the 44 yr of the reanalysis. To remove this time-dependent drift, a simple high-pass filter is applied. Validation of the results is conducted for several catchments with an appreciable coverage of in situ soil moisture and snow cover depth observations in the former Soviet Union, Mongolia, and China. Although the groundwater component is not accounted for in these observations, encouraging correlations are found between diagnostic and in situ estimates of terrestrial water storage, both for seasonal and interannual variations. Comparisons conducted against simulated ERA-40 terrestrial water storage variations suggest that the reanalysis substantially underestimates the amplitude of the seasonal cycle. The basin-scale water-balance (BSWB) dataset is available for download over the Internet. It constitutes a useful tool for the validation of climate models, large-scale land surface data assimilation systems, and indirect observations of terrestrial water storage variations. [ABSTRACT FROM AUTHOR]

Simulations with seven regional climate models driven by a common control climate simulation of a GCM carried out for Europe in the context of the (European Union) EU-funded Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project were analyzed with respect to land surface hydrology in the Rhine basin. In particular, the annual cycle of the terrestrial water storage was compared to analyses based on the 40-yr ECMWF Re-Analysis (ERA-40) atmospheric convergence and observed Rhine discharge data. In addition, an analysis was made of the partitioning of convergence anomalies over anomalies in runoff and storage. This analysis revealed that most models underestimate the size of the water storage and consequently overestimated the response of runoff to anomalies in net convergence. The partitioning of these anomalies over runoff and storage was indicative for the response of the simulated runoff to a projected climate change consistent with the greenhouse gas A2 Synthesis Report on Emission Scenarios (SRES). In particular, the annual cycle of runoff is affected largely by the terrestrial storage reservoir. Larger storage capacity leads to smaller changes in both wintertime and summertime monthly mean runoff. The sustained summertime evaporation resulting from larger storage reservoirs may have a noticeable impact on the summertime surface temperature projections. [ABSTRACT FROM AUTHOR]

Climatological drought monitoring in Switzerland relies heavily on station-based precipitation and temperature data. Due to the high spatial variability and complexity of droughts, it is important to complement station-based drought indices with gridded information and to couple multiple drought indicators within the monitoring system. Here, long-term satellite-based drought parameters from the EUMETSAT SAF network are analyzed in terms of dry anomalies within their climatology's, namely ASCAT soil water index (SWI), CM SAF land surface temperature (LST), complemented with NOAA vegetation data, and LSA SAF Meteosat evapotranspiration data. The upcoming EUMETSAT SAF climate data records on land surface temperature and evapotranspiration will cover for the first time the WMO climatological 30-year reference period. This study is the first study investigating the potential of those long-term data records for climate monitoring of droughts in Europe. The satellite datasets are compared with the standardized precipitation index (SPI), soil moisture observations from the SwissSMEX measurement network, with a modelled soil moisture index (SMI) based on observations, and with evapotranspiration measurements, focusing on the temporal dynamics of the anomalies. For vegetation and surface temperature, the dry years of 2003, 2015, and 2018 are clearly visible in the satellite data. CM SAF LSTs show strong anomalies at the beginning of the drought period. The comparison of in situ and modelled soil moisture and evapotranspiration measurements with the satellite parameters shows strong agreement in terms of anomalies. The SWI indicates high anomaly correlations of 0.56 to 0.83 with measurements and 0.63 to 0.76 with the SMI at grassland sites. The Meteosat evapotranspiration data strongly agree with the measurements, with anomaly correlations of 0.63 and 0.67 for potential and actual evapotranspiration, respectively. Due to the prevailing humid climate conditions at the considered sites, evapotranspiration anomalies during the investigated dry periods were mostly positive and thus not water limited, but were also a driver for soil moisture drought. The results indicate that EUMETSAT SAF satellite data can well complement the station-based drought monitoring in Switzerland with spatial information. [ABSTRACT FROM AUTHOR]

In the 2022 summer, western–central Europe and several other regions in the northern extratropics experienced substantial soil moisture deficits in the wake of precipitation shortages and elevated temperatures. Much of Europe has not witnessed a more severe soil drought since at least the mid-20th century, raising the question whether this is a manifestation of our warming climate. Here, we employ a well-established statistical approach to attribute the low 2022 summer soil moisture to human-induced climate change using observation-driven soil moisture estimates and climate models. We find that in western–central Europe, a June–August root zone soil moisture drought such as in 2022 is expected to occur once in 20 years in the present climate but would have occurred only about once per century during preindustrial times. The entire northern extratropics show an even stronger global warming imprint with a 20-fold soil drought probability increase or higher, but we note that the underlying uncertainty is large. Reasons are manifold but include the lack of direct soil moisture observations at the required spatiotemporal scales, the limitations of remotely sensed estimates, and the resulting need to simulate soil moisture with land surface models driven by meteorological data. Nevertheless, observation-based products indicate long-term declining summer soil moisture for both regions, and this tendency is likely fueled by regional warming, while no clear trends emerge for precipitation. Finally, our climate model analysis suggests that under 2 ∘ C global warming, 2022-like soil drought conditions would become twice as likely for western–central Europe compared to today and would take place nearly every year across the northern extratropics. [ABSTRACT FROM AUTHOR]

In the 2022 summer, West-Central Europe and several other northern-hemisphere mid-latitude regions experienced substantial soil moisture deficits in the wake of precipitation shortages and elevated temperatures. Much of Europe has not witnessed a more severe soil drought since at least the mid-20th century, raising the question whether this is a manifestation of our warming climate. Here, we employ a well-established statistical approach to attribute the low 2022 summer soil moisture to human-induced climate change, using observation-driven soil moisture estimates and climate models. We find that in West-Central Europe, a June-August root-zone soil moisture drought such as in 2022 is expected to occur once in 20 years in the present climate, but would have occurred only about once per century during pre-industrial times. The entire northern extratropics show an even stronger global warming imprint with a 20-fold soil drought probability increase or higher, but we note that the underlying uncertainty is large. Reasons are manifold, but include the lack of direct soil moisture observations at the required spatiotemporal scales, the limitations of remotely sensed estimates, and the resulting need to simulate soil moisture with land surface models driven by meteorological data. Nevertheless, observationbased products indicate long-term declining summer soil moisture for both regions, and this tendency is likely fueled by regional warming, while no clear trends emerge for precipitation. Finally, our climate model analysis suggests that in a 2 °C world, 2022-like soil drought conditions would become twice as likely for West-Central Europe compared to today, and would take place nearly every year across the northern extratropics. [ABSTRACT FROM AUTHOR]

If climate services are to lead to effective use of climate information in decision-making to enable the transition to a climate-smart, climate-ready world, then the question of trust in the products and services is of paramount importance. The Copernicus Climate Change Service (C3S) has been actively grappling with how to build such trust: provision of demonstrably independent assessments of the quality of products, which was deemed an important element in such trust-building processes. C3S provides access to essential climate variables (ECVs) from multiple sources to a broad set of users ranging from scientists to private companies and decision-makers. Here we outline the approach -undertaken to coherently assess the quality of a suite of observation- and reanalysis-based ECV products covering the atmosphere, ocean, land, and cryosphere. The assessment is based on four pillars: basic data checks, maturity of the datasets, fitness for purpose (scientific use cases and climate studies), and guidance to users. It is undertaken independently by scientific experts and presented alongside the datasets in a fully traceable, replicable, and transparent manner. The methodology deployed is detailed, and example assessments are given. These independent scientific quality assessments are intended to guide users to ensure they use tools and datasets that are fit for purpose to answer their specific needs rather than simply use the first product they alight on. This is the first such effort to develop and apply an assessment framework consistently to all ECVs. Lessons learned and future perspectives are outlined to potentially improve future assessment activities and thus climate services. [ABSTRACT FROM AUTHOR]

Many countries rely on regional climate model (RCM) simulations to quantify the projectedimpacts of climate change and design their national adaptation plans. The accuracy andreliability of RCM simulations is thus of fundamental importance and, in particular, it iscrucial to include all relevant climate processes in RCMs. One of the processes notconsidered in most RCMs is the response of plants to elevated atmospheric CO2concentrations (the plant physiological CO2 effect); a process which is however includedin most global climate models (GCMs). Here we show that due to this missingprocess, RCMs underestimate the future increase of extreme temperatures compared toGCMs. The plant physiological CO2 effect takes into account that at higher CO2 concentrationsplants increase their water use efficiency, i.e. the fraction of CO2 uptake to transpiration. As aconsequence, plants reduce the openings of their leaf stomata at elevated CO2 concentrations.This causes a reduction of plant transpiration, resulting in a decrease of latent heat flux and anincrease of sensible heat flux. Ultimately, the plant physiological CO2 effect can thusalter near-surface air temperatures. Using a state-of-the-art regional climate model(COSMO-CLM2), we perform two model simulations: one that includes the plantphysiological CO2 effect and one where plants are insensitive to the atmospheric CO2increase. The simulations cover the European domain and the time span 1971-2099. In thesimulation that includes the plant physiological CO2 effect, evapotranspiration in central andnorthern Europe at the end of the 21st century is significantly lower than in the simulationwith insensitive plants (calculated as changes with respect to 1971-2000). In contrast, theevapotranspiration difference between both simulations is small in southern Europe,suggesting that other factors, such as soil moisture limitations, prevent a strongimpact of the plant physiological CO2 effect on evapotranspiration in this region. Theresults obtained with COSMO-CLM2 are in line with the fact that RCMs fromthe EURO-CORDEX multi-model ensemble also exhibit lower evapotranspirationcompared to GCMs in central and northern Europe at the end of the 21st century (withrespect to 1971-2000). Additionally, the results from COSMO-CLM2 agree verywell with estimations of the plant physiological CO2 effect from dedicated CMIP5experiments. Including the plant physiological CO2 effects in COSMO-CLM2 also affectsnear-surface air temperatures. In central and northern Europe, the annual maximumtemperature (TXx) is about 1 K higher in the COSMO-CLM2 simulation with plantphysiological CO2 effects compared to the simulation with insensitive plants at theend of the 21st century. This result can partially explain the discrepancy betweenthe TXx evolution in GCMs and RCMs in central and northern Europe where atthe end of the 21st century GCMs exhibit a TXx increase that is about 2 K higherthan the TXx increase in RCMs. According to the COSMO-CLM2 simulations,the plant physiological CO2 effect accounts for about 50 % of the TXx differencebetween GCMs and RCMs. Neglecting the plant physiological CO2 effect can thusresult in a substantial underestimation of future temperature increases in RCMs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: Soil moisture is a key variable of the climate system. It constrains plant transpiration and photosynthesis in several regions of the world, with consequent impacts on the water, energy and biogeochemical cycles. Moreover it is a storage component for precipitation and radiation anomalies, inducing persistence in the climate system. Finally, it is involved in a number of feedbacks at the local, regional and global scales, and plays a major role in climate-change projections. In this review, we provide a synthesis of past research on the role of soil moisture for the climate system, based both on modelling and observational studies. We focus on soil moisture–temperature and soil moisture–precipitation feedbacks, and their possible modifications with climate change. We also highlight further impacts of soil moisture on climate, and the state of research regarding the validation of the relevant processes. There are promises for major advances in this research field in coming years thanks to the development of new validation datasets and multi-model initiatives. However, the availability of ground observations continues to be critical in limiting progress and should therefore strongly be fostered at the international level. Exchanges across disciplines will also be essential for bridging current knowledge gaps in this field. This is of key importance given the manifold impacts of soil moisture on climate, and their relevance for climate-change projections. A better understanding and quantification of the relevant processes would significantly help to reduce uncertainties in future-climate scenarios, in particular with regard to changes in climate variability and extreme events, as well as ecosystem and agricultural impacts. [Copyright &y& Elsevier]

The Tiled ECMWF Scheme for Surface Exchanges over Land (TESSEL) is used operationally in the Integrated Forecast System (IFS) for describing the evolution of soil, vegetation, and snow over the continents at diverse spatial resolutions. A revised land surface hydrology (H-TESSEL) is introduced in the ECMWF operational model to address shortcomings of the land surface scheme, specifically the lack of surface runoff and the choice of a global uniform soil texture. New infiltration and runoff schemes are introduced with a dependency on the soil texture and standard deviation of orography. A set of experiments in stand-alone mode is used to assess the improved prediction of soil moisture at the local scale against field site observations. Comparison with basin-scale water balance (BSWB) and Global Runoff Data Centre (GRDC) datasets indicates a consistently larger dynamical range of land water mass over large continental areas and an improved prediction of river runoff, while the effect on atmospheric fluxes is fairly small. Finally, the ECMWF data assimilation and prediction systems are used to verify the effect on surface and near-surface quantities in the atmospheric-coupled mode. A midlatitude error reduction is seen both in soil moisture and in 2-m temperature. [ABSTRACT FROM AUTHOR]

Soil moisture observations are of broad scientific interest and practical value for a wide range of applications. The scientific community has made significant progress in estimating soil moisture from satellite-based Earth observation data, particularly in operationalizing coarse-resolution (25-50 km) soil moisture products. This review summarizes existing applications of satellite-derived soil moisture products and identifies gaps between the characteristics of currently available soil moisture products and the application requirements from various disciplines. We discuss the efforts devoted to the generation of high-resolution soil moisture products from satellite Synthetic Aperture Radar (SAR) data such as Sentinel-1 C-band backscatter observations and/or through downscaling of existing coarse-resolution microwave soil moisture products. Open issues and future opportunities of satellite-derived soil moisture are discussed, providing guidance for further development of operational soil moisture products and bridging the gap between the soil moisture user and supplier communities. • Applications of high-resolution satellite-based soil moisture products are reviewed. • The gaps between product characteristics and user requirements are identified. • Open issues and opportunities for developments of high-resolution satellite-based soil moisture products are discussed. [ABSTRACT FROM AUTHOR]

This presentation will provide an overview on changes in climate extremes at 1.5°C vs 2°C global warming, based on chapter 3 of the IPCC Special Report on 1.5°C global warming (Hoegh-Guldberg et al. 2019) as well as on several recent publications (Seneviratne et al. 2016; Wartenburger et al. 2017; Seneviratne et al. 2018a,b). There are substantial differences in regional climate means and extremes at 1.5°C vs 2°C global warming, with up to 2-3 times larger increases in hot extremes over land compared to the global mean temperature. There are also detectable differences in heavy precipitation and droughts in some regions. Limiting global warming to 1.5°C avoids substantial risks compared to higher levels of warming, including irreversible impacts. However, it does not completely remove the risk of some regional extremes reaching dangerous levels for ecosystems and societies in the coming decades.References: Hoegh-Guldberg, O., D. Jacob, M. Taylor, M. Bindi, S. Brown, I. Camilloni, A. Diedhiou, R. Djalante, K. Ebi, F. Engelbrecht, J. Guiot, Y. Hijioka, S. Mehrotra, A. Payne, S. I. Seneviratne, A. Thomas, R. Warren, G. Zhou, 2019, Impacts of 1.5ºC global warming on natural and human systems. In: Global warming of 1.5°C. An IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [V. Masson-Delmotte, et al. (eds.)]. In Press.Seneviratne, S.I., M. Donat, A.J. Pitman, R. Knutti, and R.L. Wilby, 2016: Allowable CO2 emissions based on regional and impact-related climate targets. Nature, 529, 477-483, doi:10.1038/nature16542.Seneviratne, S.I., J. Rogelj, R. Séférian, R. Wartenburger, M.R. Allen, M. Cain, R.J. Millar, K.L. Ebi, N. Ellis, O. Hoegh-Guldberg, A.J. Payne, C.-F. Schleussner, P. Tschakert, R.F. Warren, 2018a: The many possible climates from the Paris Agreement's aim of 1.5°C warming. Nature. 558, 41-49. Seneviratne, S.I., R. Wartenburger, B.P. Guillod, A.L. Hirsch, M.M. Vogel, V. Brovkin, D.P. van Vuuren, N. Schaller, L. Boysen, K.V. Calvin, J. Doelman, P. Greve, P. Havlik, F. Humpenöder, T. Krisztin, D. Mitchell, A. Popp, K. Riahi, J. Rogelj, C.-F. Schleussner, J. Sillmann, E. Stehfest, 2018b: Climate extremes, land-climate feedbacks and land-use forcing at 1.5°C. Phil. Trans. R. Soc. A. 376.Wartenburger, H., H. Hirschi, M.G. Donat, P. Greve, A.J. Pitman, S.I. Seneviratne, 2017: Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework. Geoscientific Model Development, 10, 3609-3634. [ABSTRACT FROM AUTHOR]

Quality assurance of satellite-derived soil moisture datasets is key for ensuring users are provided with datasets of sufficient quality to their applications. Currently, such activities are undertaken on an ad-hoc basis or using a protocol designed for a specific product. These results are useful, but differ in terms of output validation data, plots and reports and therefore are difficult to inter-compare.The aim of the Quality Assurance for Soil Moisture (QA4SM) (www.qa4sm.eodc.eu) project (supported by the Austrian Space Application Programme) is to bring together methodologies and protocols used for the validation and quality control of soil moisture data products and develop this into a coherent methodology allowing the provision of standardised, and above all traceable validation results to the user community. QA4SM is driven by validation best practice guidelines resulting from a collaborative effort of the entire satellite soil moisture validation community, including the Committee on Earth Observation Satellites, the Global Climate Observing System, and the validation teams of the individual satellite missions.An easy-to-use functional, web-based test application has been made available to the user community. The application currently allows users to compare medium coarse resolution satellite datasets to in-situ validation data (made available through the International Soil Moisture Network (ISMN) (http://ismn.geo.tuwien.ac.at)) and global land surface models. Later updates of the system will allow the upload and comparison of user's own datasets as well as the validation of high resolution (1 km) products. The web-based graphical front-end allows users to easily select specific criteria for the comparison process including control of the masking applied to each dataset, the metrics calculated and so on. The validation results are provided as a netCDF file which includes traceability data in the global attributes as well as plots of each metric.Various satellite-derived soil moisture products are available for validation within the QA4SM system including SMAP L3 and the SMOS IC soil moisture products as well as the European Space Agency (ESA) Climate Change Initiative (CCI) and EU Copernicus Climate Changes Services (C3S) soil moisture products. These latter two products are produced by systematically combining Level-2 datasets from separate missions. The combination of individual Level 2 datasets into a single product gives us the opportunity to profit from the advantages of individual missions, and to obtain homogenised CDRs with improved spatial and temporal coverage.The accuracy of the ESA CCI and C3S products are routinely assessed (each time a new version is generated) through comparison to in-situ (ISMN) and global models. The quality assessment also includes consideration of the stability of the product and a completeness / consistency check. The aim of these assessments is to ensure that the highest quality product is provided to the data users. With the availability of the QA4SM system, this can now be achieved in a robust and traceable manner.The goal of this presentation is to present the QA4SM system, show validation results for both the ESA CCI and C3S soil moisture products using the system, and collect feedback from the wider satellite soil moisture validation/calibration community. [ABSTRACT FROM AUTHOR]