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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]

Drought events have multiple adverse impacts on environment, society, and economy. It is thus crucial to monitor and characterise such events. Here, we compare the ability of selected state-of-the-art long-term reanalysis and remote-sensing products to represent major seasonal and multi-year drought events in the 2000–2020 period globally. We focus on soil moisture (or agroecological) drought and place the results in the context of trends in dry-season soil moisture. We consider surface and root-zone soil moisture from ERA5, the related ERA5-Land, and MERRA-2 reanalysis products, the ESA CCI remote-sensing surface soil moisture products (encompassing an ACTIVE, a PASSIVE and a COMBINED product), as well as its near real-time counterpart produced within C3S. In addition, we use a new root-zone soil moisture dataset derived from the ESA CCI COMBINED product. Except for ESA CCI surface and root-zone soil moisture, the considered products offer opportunities for drought monitoring since they are available in near real-time. We analyse 18 documented drought events within predefined spatial and temporal bounds derived from scientific literature. Based on standardised daily anomalies of surface and root-zone soil moisture, the drought events are characterised by their severity (the time accumulated standardised anomalies), magnitude (the minimum of the standardised anomalies over time), duration, and spatial extent. Product deviations in drought severity and magnitude are then placed in the context of trends in dry-season soil moisture, and potential reasons for diverging global soil moisture trends in the products are further investigated. All investigated products capture the considered drought events. Overall, responses of surface soil moisture tend to be weakest for the ACTIVE remote-sensing products in all metrics, but most pronounced in the drought magnitudes. Also, MERRA‑2 shows lower magnitudes than the other products. Except for the COMBINED products, the remote-sensing products tend to underestimate the spatial extents of larger droughts. Product differences in drought severity and magnitude for single events are consistent with the differences in dry-season soil moisture trends. These trends are globally diverse and partly contradictory between products. ERA5, ERA5-Land and the COMBINED products show larger fractions of drying trends, MERRA-2 and the C3S ACTIVE and PASSIVE products more widespread wetting trends. MERRA-2 surface air temperature shows regionally negative biases in trends compared to a ground observational product, which suggests that this reanalysis product underestimates drought trends. Also, the comparison with trends in selected land-surface characteristics and bioclimatic indicators shows that dry-season soil moisture trends may be affected by retrieval or modelling artifacts in some cases. In the root zone (based on the reanalysis products and the ESA CCI root-zone soil moisture dataset), the droughts are dampened in magnitude and smaller in spatial extent but show a tendency to prolonged durations. Based on the overall observational evidence and the consideration of the respective limitations of the included products, the present analyses suggest a consistent tendency towards drying during the last two decades in some regions, namely in parts of central Europe, in a region north of the Black Sea/Caspian Sea, in southern Africa, and in parts of Australia, Siberia and South America. [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]

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]

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]

Crop producers face significant and increasing drought risks. We evaluate whether insurances based on globally and freely available satellite-retrieved soil moisture data can reduce farms' financial drought risk exposure. We design farm individual soil moisture index insurances for wheat, maize and rapeseed production using a case study for Eastern Germany. We find that the satellite-retrieved soil moisture index insurances significantly decrease risk exposure for these crops compared to the situation where production is not insured. The satellite-retrieved index also outperforms one based on soil moisture estimates derived from meteorological measurements at ground stations. Important implications for insurers and policy makers are that they could and should develop better suited insurances. Available satellite-retrieved data can be used to increase farmers' resilience in a changing climate. [ABSTRACT FROM AUTHOR]

The article focuses on the evaluation of different methods for gap filling of long-term actual evapotranspiration time series measured by lysimeters. It explore four different gap filling methods namely potential terrestrial evapotranspiration method, the ratio method, and the FAO-based water balance method, and HYDRUS modeling. It also mentions that gap-filling methods do not perform very differently for dry and wet conditions.

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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]

Core Ideas: We saw generally high agreement between lysimeters, despite substantial design differences.Large‐lysimeter processing was optimized in light of highly resolved mini‐lysimeter data.Smoothing filter and setting of ET to zero in wet hours was useful for the large lysimeter.Lysimeter precipitation types were identified using an opto‐electric precipitation monitor.Protrusion of the large lysimeter may cause precipitation under‐catch by flow distortion. Weighing lysimeters are a well‐established means of accurately obtaining local‐scale estimates of actual evapotranspiration (ET), precipitation, and seepage within soils. At the Rietholzbach research catchment in northeastern Switzerland, two weighing lysimeters are in operation. One is a recently installed state‐of‐the‐art monolithic mini‐lysimeter with a tension‐controlled lower boundary; the other is a large backfilled free‐drainage lysimeter in operation since 1976. For this study, the mini‐lysimeter measurements were processed using the Adaptive‐Window and Adaptive‐Threshold (AWAT) filter. The resulting water‐balance estimates were then compared with those of the lower resolution large lysimeter, whose processing has remained unchanged since its installation. A number of additional, retrospectively applicable processing steps for the large lysimeter were then tested to mitigate the main sources of error for this instrument. Those found to be most beneficial were the application of a 10‐min moving average to the mass measurements and the setting of ET and condensation to zero in hours with liquid precipitation. In spite of the differences in design, a generally close agreement between the two lysimeters was observed, which was further improved with the optimized large‐lysimeter processing. A comparison of the lysimeter mass increases associated with liquid precipitation further revealed, however, that the large lysimeter experiences a previously unknown under‐catch of about 11.5%, which could also be important for other lysimeter facilities. This under‐catch led to a reduction in large‐lysimeter seepage during the analyzed period, although the ET flux was not found to be affected. [ABSTRACT FROM AUTHOR]

Accurate measurements of evapotranspiration are required for many meteorological, climatological, ecological, and hydrological research applications and developments. Here we examine and compare two wellestablished methods to determine evapotranspiration at the site level: lysimeter-based measurements (EL) and eddy covariance (EC) flux measurements (EEC). The analyses are based on parallel measurements carried out with these two methods at the research catchment Rietholzbach in northeastern Switzerland, and cover the time period of June 2009 to December 2015. The measurements are compared on various timescales, and with respect to a 40-year lysimeter-based evapotranspiration time series. Overall, the lysimeter and EC measurements agree well, especially on the annual timescale. On that timescale, the long-term lysimeter measurements also correspond well with catchment water-balance estimates of evapotranspiration. This highlights the representativeness of the site-level lysimeter and EC measurements for the entire catchment despite their comparatively small source areas and the heterogeneous land use and topography within the catchment. Furthermore, we identify that lack of reliable EC measurements using open-path gas analyzers during and following precipitation events (due to limitations of the measurement technique under these conditions) significantly contributes to an underestimation of EEC and to the overall energy balance gap at the site. [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]

Accurate measurements of evapotranspiration are required for many meteorological, climatological, ecological, and hydrological research applications and developments. Here we examine and compare two well-established methods to determine evapotranspiration at the site level: lysimeter-based measurements (EL) and eddy-covariance (EC) flux measurements (EEC). The analyses are based on parallel measurements carried out with these two methods at the research catchment Rietholzbach in northeastern Switzerland, and cover the time period June 2009 to December 2015. The measurements are compared on various time scales, and with respect to a 40-year lysimeter-based evapotranspiration time series. Overall, the lysimeter and EC measurements agree well, especially on the annual time scale. On that time scale, the long-term lysimeter measurements also correspond well with catchment water-balance estimates of evapotranspiration. This highlights the representativeness of the site-level lysimeter and EC measurements for the entire catchment despite their comparatively small source areas and the heterogeneous land use and topography within the catchment. Furthermore, we identify that lack of reliable EC measurements during and following rainfall events (due to limitations of the measurement technique under these conditions) significantly contributes to an underestimation of EEC and to the overall energy balance gap at the site. [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]

Terrestrial water storage is an important component of the climate system as it determines the partitioning of the water and energy fluxes at the land surface. Since in situ measurements are scarce, there is a strong need for alternative validation data sources. Here we present a new dataset of monthly basin-scale terrestrial water storage changes (TWSC) derived with the combined atmospheric-terrestrial water-balance approach, also referred to as basin-scale water-balance (BSWB) approach. It is diagnosed from observation-constrained reanalysis data for the atmospheric fields and observed streamflow. A previous BSWB dataset derived from the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis ERA-40 provided reasonable estimates of TWSC for mid-latitude basins. The here presented BSWB dataset is derived from the latest ECMWF reanalysis ERA-Interim, which is available in real time. The potential real-time availability of TWSC derived from ERA-Interim is of great relevance for several agricultural, hydrological, and climate applications. An uncertainty analysis of the derived TWSC highlights the importance of the atmospheric moisture flux convergence fields from the reanalysis for the resulting product uncertainty. We find that the BSWB estimates have a relative uncertainty of about 4-6% in basins larger than 1·5 × 10 km compared with the mean seasonal cycle. The ERA-Interim based dataset compares better with in situ soil moisture, snow depth, and groundwater measurements in the Ob basin and Illinois than the previous ERA-40 based dataset. We further compare the BSWB datasets to retrievals from the Gravity Recovery And Climate Experiment (GRACE), scatterometer data from the European Remote Sensing (ERS) satellites, and land surface model output from the second phase of the Global Soil Wetness Project (GSWP). We find a better correlation between ERS and the BSWB data than between GRACE and the BSWB data, which might be related to the relatively coarse resolution of GRACE. GSWP model output and the BSWB datasets compare well in most of the studied river basins. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]