Abstract. Water availability for societies and ecosystems depends upon Terrestrial Water Storage (TWS), yet global, spatially resolved measurements are largely unavailable before the advent of the Gravity Recovery and Climate Experiment (GRACE) gravimetric measurements in 2002. By exploiting a larger set of model and observations-based datasets than previously considered, along with statistical and machine learning techniques, we advance understanding of TWS changes since the 1980s, including accounting for human water management (HWM). A decline in TWS during 2002–2019 is identified for three global hydrologic models with HWM and bias-corrected precipitation forcing (-0.91 to -0.06 mm yr-1) with only one showing larger decreases than observed by GRACE observations (-0.80 mm y-1). We further identify a longer-term decline in TWS during 1980–2019 in these models, linked with regional precipitation decreases and the net effects of HWM through TWS drawdowns over northern India, southwest U.S. and northeastern China, yet the amplitude of the global land trends remains poorly quantified, ranging from -0.72 to +0.04 mm y-1. Statistical / Machine Learning (ML) reconstructions are found to match GRACE variability but their fidelity in the pre-GRACE/FO period remains unknown. A stronger decline in TWS since 1980 in the European Centre for Medium-range Weather Forecasts 5th generation reanalysis (ERA5) enhanced land component (ERA5-Land) is linked to an artificial drop in precipitation around 2000–2002 in ERA5 that is most pronounced over equatorial central Africa, northeastern China and the northern Argentina / La Plata region. Our findings urge caution in inferring changes in hydroclimate variables from ERA5-Land and other reanalyses due to inhomogeneities in the assimilated observational data. Continued emphasis on bias corrections to hydrometeorological data and better modeling of HWM are crucial to improving all retrospective analyses of changes in land surface hydrology and terrestrial water stores.

Reliable estimation of evapotranspiration (ET) over irrigated croplands is crucial for agricultural water management, hydrological modeling, and monitoring of land-atmosphere exchanges. Yet, the reliability of global ET datasets in these environments remains insufficiently assessed. Here, we evaluate six widely used global ET products (FLUXCOM RS, GLEAM4.3a, PMLv2, ERA5-Land, MOD16A2, and SSEBop v6.1), covering a wide range of modeling approaches, to assess their ability to capture irrigation-related ET signals. The assessment combines spatial and seasonal evaluations across diverse agro-climatic regions, using three complementary references: a map of area equipped for irrigation, the OpenET ensemble, and eddy covariance measurements from irrigated croplands. Results reveal marked differences in how the products represent irrigation-related ET variability. PMLv2, SSEBop v6.1, and FLUXCOM RS generally show stronger and more consistent agreement with the reference datasets in terms of spatial patterns and seasonal dynamics, although differences in ET magnitude remain between them. MOD16A2 and GLEAM4.3a capture temporal irrigation-related variability across most regions but show more variable spatial agreement with irrigation extent and generally lower ET magnitudes. ERA5-Land exhibits the weakest correspondence, reflecting limitations linked to its precipitation-driven soil-water-balance and stress formulations. Differences among products mainly reflect how vegetation water stress is represented and the extent to which irrigation-sensitive variables (e.g., land surface temperature and vegetation properties) are incorporated. This multi-scale evaluation provides guidance for selecting ET products in irrigated regions and highlights priorities for improving the representation of irrigation in global ET models.

Essential Climate Variables, such as near-surface (T2m) and land surface temperatures (LST), are typically reported in Coordinated Universal Time (UTC) for global consistency. However, their diurnal variability leads to temperature trends that differ by the local hour, a factor not analyzed on the global nor regional scale. Using ECMWF ERA5-Land reanalysis data (1981-2022), we assess temperature trends by local hour and month. Our results show that the trends can change significantly during the day. LST and T2m warming or cooling trends peak in the afternoon, while showing large spatial variability across both hemispheres. Using MODIS observations, we show how the nominal Equator crossing times of TERRA and AQUA influence LST trends. These findings highlight the necessity of accounting for local time in climate assessments to improve adaptation strategies.

We provide a description and concise evaluation of the European Centre of Medium-range Weather Forecasts Reanalysis v.5 (ERA5) global reanalysis from an additional extension back to 1940 that was released in March 2023, including its timely updates to the end of 2022. The ERA5 product from 1979 to end 2020 and a preliminary back extension from 1950 to 1978 have already been described elsewhere. The new back extension that spans 1940 to 1978 represents the official release and supersedes the preliminary product. Currently, the ERA5 data record extends over more than 83 years of hourly global three-dimensional fields for many quantities that describe the global atmosphere, land surface, and ocean waves at a horizontal resolution of about 31 km. ERA5 relies on the ingestion of sub-daily in-situ and satellite observations, and the number of these increases from 17,000 per day in 1940 to 25 million per day by 2022. Accordingly, the quality of the reanalysis improves throughout the period. Over the Northern Hemisphere ERA5 generally provides a reliable representation of the synoptic situation from the early 1940s and provides long-term variability that is in line with other datasets. Over the Southern Hemisphere, however, for the early period the description of ERA5 seems mainly statistical. Furthermore, there is a small deviation in surface temperature compared with reconstructions based on monthly aggregations of observations over land before 1946. For this period, the absence of upper air temperature observations reveals a model cold bias in the lower stratosphere. For the period from 1950 to 1978, the final release described here improves on the suboptimal treatment of International Best Track Archive for Climate Stewardship observations in the preliminary release, with, as a result, a much more homogeneous representation of tropical cyclones over the entire ERA5 record. Longer spin-up periods also have a beneficial impact on soil moisture. This article provides a description and concise evaluation of the European Centre of Medium-range Weather Forecasts Reanalysis v.5 (ERA5) global reanalysis from 1940 to 2022. ERA5 relies on the ingestion of observations, and the number of these increases from 17,000 per day in 1940 to 25 million per day by 2022. The figure illustrates the increase in quality of reanalysis throughout the period; reliable representation of the synoptic situation from 1940s over the Northern Hemisphere and mainly statistical over the Southern Hemisphere for the early period. image

Atmospheric reanalyses combine observations and models through data assimilation techniques to provide spatio-temporally continuous fields of key surface variables. They can do so for extended historical periods whilst ensuring a coherent representation of the main Earth system cycles. ERA5 and its enhanced land surface component, ERA5-Land, are widely used in Earth system science and form the flagship products of the Copernicus Climate Change Service (C3S) of the European Commission. Such land surface modelling frameworks generally rely on a state variable called leaf area index (LAI), representing the number of leaves in a grid cell at a given time, to quantify the fluxes of carbon, water and energy between the vegetation and the atmosphere. However, the LAI within the modelling framework behind ERA5 and ERA5-Land is prescribed as a climatological seasonal cycle, neglecting any interannual variability and the potential consequences that this uncoupling between vegetation and atmosphere may have on the surface energy balance and the climate. To evaluate the impact of this mismatch in LAI, we analyse the corresponding effect it has on land surface temperature (LST) by comparing what is simulated to satellite observations. We characterise a hysteretic behaviour between LST biases and LAI biases that evolves differently along the year depending on the background climate. We further analyse the repercussions for the reconstructed climate during more extreme conditions in terms of LAI deviations, with a specific focus on the 2003, 2010 and 2018 heat waves in Europe for which LST mismatches are exacerbated. We anticipate that our results will assist users of ERA5 and ERA5-Land data in understanding where and when the larger discrepancies can be expected, but also guide developers towards improving the modelling framework. Finally, this study could provide a blueprint for a wider benchmarking framework for land surface model evaluation that exploits the capacity of LST to integrate the effects of both radiative and non-radiative processes affecting the surface energy.

Reanalysis is a key activity within the Copernicus Climate Change Service (C3S), which is funded by the European Union Copernicus programme and implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF). Currently, the latest generation of European Reanalysis, ERA5 and ERA5-Land, are available through the C3S Climate Data Store (https://cds.climate.copernicus.eu/). ERA5 provides hourly snapshots of the Earth's atmosphere, land surface and ocean waves from 1950 to present, thus providing a global view of the evolution of the Earth’s climate without temporal or spatial gaps for the last seven decades. The land surface component, although part of the ERA5 portfolio, contains few inconsistencies. For instance, significant regional steps between different production segments are present, compromising the reliability of long-term trends. In addition, ERA5 does not provide sufficient resolution for a large and growing number of land applications.ERA5-Land was designed to overcome the above-mentioned shortcomings of the land branch of reanalysis. For instance, steps in the seam between production segments may be avoided by applying a long spin-up strategy for the initialization of each production segment. ERA5-Land is a unique dataset of its kind, providing a global scale description of the continental water and energy cycles through a series of 50 key surface variables, hourly at a spatial resolution of 9 km, from 1950 to present. ERA5-Land is driven by the near-surface meteorology of ERA5, and temperature is adjusted by considering the orographic differences between ERA5 and ERA5-Land numerical grids. The fidelity of ERA5-Land was assessed by comparing the main fields to a large number of available in-situ observations distributed along the world from 2000 onwards. The variables under analysis were soil moisture, snow depth, lake surface water temperature, river discharge, surface latent and sensible heat fluxes, and skin temperature. The results of the evaluation analysis suggested significant improvements of the ERA5-Land hydrological cycle in comparison to those of ERA5 and ERA-Interim.The number of ERA5-Land users is counted in thousands. Very recently and similarly to ERA5T, the ERA5-Land-T facility was enabled, which means that preliminary updates are made available daily with only 5-days delay with respect to real time. The final quality-checked product is published with 2-3 month delay with respect to real time. ERA5-Land-T is the result of a requirement of users needing more recent data and opens the door to new applications such as flood forecasting or biomass monitoring.In this paper the main characteristics of ERA5-Land dataset will be highlighted, its main strengths and weaknesses, as well as the current status.

The aim of Copernicus Climate Change Service (C3S) is to supply reliable climate data in support of strategies to adaptation and mitigation to climate change. The C3S provides access to high-quality climate data through its Climate Data Records (CDRs) of atmospheric, marine and land Essential Climate Variables (ECVs). Global Earth Surface Albedo (SA) satellite-based products are included in the land (biosphere) portfolio. SA is a magnitude which quantifies the fraction of solar energy reflected by the surface of the Earth. This paper details the retrieval methodology and preliminary validation results for global estimates of surface albedo based on Sentinel-3 observations for the C3S ECVs data (C3S SA v3.0). The retrieval algorithm exploits the synergistic use of the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR) on-board Sentinel-3 A and B satellites. Firstly, the atmospherically corrected reflectances are generated in the Copernicus Global Land Service framework. After that, the Bidirectional Reflectance Distribution Function (BRDF) inversion module concludes the BRDF model parameters, which are transferred to the angular integration module in order to generate spectral albedo quantities for the selected OLCI (Oa03, Oa04, Oa07, Oa17 and Oa21) and SLSTR (S1, S2, S5 and S6) bands. At the end, the spectral integration module generates broadband albedo quantities in three different standard broadband spectral regions (visible [0.4 mu m - 0.7 mu m ], near infrared [0.7 mu m - 4 mu m] and total shortwave [0.3 mu m - 4 mu m]). Preliminary validation results over 10-months demonstration period (July 2018-April 2019) show, in terms of spatial and temporal consistency, that C3S Sentinel-3 SA global estimates reached in general good agreement as compared to other satellite operational references derived from MODIS (MCD43A3 C6) and PROBA-V (C3S PROBA-V SA v1.0) acquisitions. The comparison with ground data shows similar results to the MCD43A3 C6 comparisons but opposite sign in differences (marginally positive in case of Sentinel-3), with accuracy of 0.005 (3.7%), precision of 0.016 (11.3%) and uncertainty of 0.032 (22.7%). Our results have demonstrated the feasibility to estimate global fields of SA from Sentinel-3 observations, with similar quality of existing operational products. These Sentinel-3 based SA datasets will give the continuity to the existing C3S SA CDR, introducing improvements in terms of spatial resolution (300 m) and spectral information (9 spectral albedos) in contrast to previous datasets based on Advanced Very High Resolution Radiometer (AVHRR; 4 km, 4 channels) and Vegetation instruments (VGT; 1 km, 4 channels).

The Copernicus Climate Change Service (C3S) provides open and free access to state-of-the-art climate data and tools for use by governments, public authorities, and private entities around the world. It is fully funded by the European Union and implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) together with public and private entities in Europe and elsewhere. With over 120,000 registered users worldwide, C3S has rapidly become an authoritative climate service in Europe and beyond, delivering quality-assured climate data and information based on the latest science. Established in 2014, C3S became fully operational in 2018 with the launch of its Climate Data Store, a powerful cloud-based infrastructure providing access to a vast range of global and regional information, including climate data records derived from observations, the latest ECMWF reanalyses, seasonal forecast data from multiple providers, and a large collection of climate projections. The system has been designed to be accessible to nonspecialists, offering a uniform interface to all data and documentation as well as a Python-based toolbox that can be used to process and use the data online. C3S publishes European State of the Climate reports annually for policy-makers, as well as monthly and annual summaries that are widely disseminated in the international press. Together with users, C3S develops customized indicators of climate impacts in economic sectors such as energy, water management, agriculture, insurance, health, and urban planning. C3S works closely with national climate service providers, satellite agencies, and other stakeholders on the improvement of its data and services.

Climate observations inform about the past and present state of the climate system. They underpin climate science, feed into policies for adaptation and mitigation, and increase awareness of the impacts of climate change. The Global Climate Observing System (GCOS), a body of the World Meteorological Organization (WMO), assesses the maturity of the required observing system and gives guidance for its development. The Essential Climate Variables (ECVs) are central to GCOS, and the global community must monitor them with the highest standards in the form of Climate Data Records (CDR). Today, a single ECV—the sea ice ECV—encapsulates all aspects of the sea ice environment. In the early 1990s it was a single variable (sea ice concentration) but is today an umbrella for four variables (adding thickness, edge/extent, and drift). In this contribution, we argue that GCOS should from now on consider a set of seven ECVs (sea ice concentration, thickness, snow depth, surface temperature, surface albedo, age, and drift). These seven ECVs are critical and cost effective to monitor with existing satellite Earth observation capability. We advise against placing these new variables under the umbrella of the single sea ice ECV. To start a set of distinct ECVs is indeed critical to avoid adding to the suboptimal situation we experience today and to reconcile the sea ice variables with the practice in other ECV domains.

The land-surface developments of the European Centre for Medium-range Weather Forecasts (ECMWF) are based on the Carbon-Hydrology Tiled Scheme for Surface Exchanges over Land (CHTESSEL) and form an integral part of the Integrated Forecasting System (IFS), supporting a wide range of global weather, climate and environmental applications. In order to structure, coordinate and focus future developments and benefit from international collaboration in new areas, a flexible system named ECLand, which would facilitate modular extensions to support numerical weather prediction (NWP) and society-relevant operational services, for example, Copernicus, is presented. This paper introduces recent examples of novel ECLand developments on (i) vegetation; (ii) snow; (iii) soil; (iv) open water/lake; (v) river/inundation; and (vi) urban areas. The developments are evaluated separately with long-range, atmosphere-forced surface offline simulations and coupled land-atmosphere-ocean experiments. This illustrates the benchmark criteria for assessing both process fidelity with regards to land surface fluxes and reservoirs of the water-energy-carbon exchange on the one hand, and on the other hand the requirements of ECMWF's NWP, climate and atmospheric composition monitoring services using an Earth system assimilation and prediction framework.

Land surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. This article presents the algorithm concepts for the remote sensing of this variable based on the heritage of several developments which were performed at Méteo France over the last decade and described in several papers by Carrer et al. The scientific algorithm comprises four steps: an atmospheric correction, a sensor harmonisation (optional), a BRDF (Bidirectional Reflectance Distribution Function) inversion, and the albedo calculation. At the time being, the method has been applied to 11 sensors in the framework of two European initiatives (Satellite Application Facility on Land Surface Analysis—LSA SAF, and Copernicus Climate Change Service—C3S): NOAA-7-9-11-14-16-17/AVHRR2-3, SPOT/VGT1-2, Metop/AVHRR-3, PROBA-V, and MSG/SEVIRI. This work leads to a consistent archive of almost 40 years of satellite-derived albedo data (available in 2020). From a single sensor, up to three different albedo products with different characteristics have been developed to address the requirements of both, near real-time (NRT) (weather prediction with a demand of timeliness of 1 h) and climate communities. The evaluation of the algorithm applied to different platforms was recently made by Lellouch et al. and Sánchez Zapero et al. in 2020 which can be considered as companion papers. After a summary of the method for the retrieval of these surface albedos, this article describes the specificities of each retrieval, lists the differences, and discusses the limitations. The plan of continuity with the next European satellite missions and perspectives of improvements are introduced. For example, Metop/AVHRR-3 albedo will soon become the medium resolution sensor product with the longest NRT data record, since MODIS is approaching the end of its life-cycle. Additionally, Metop-SG/METimage will ensure its continuity thanks to consistent production of data sets guaranteed till 2050 by the member states of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). In the end, the common strategy which we proposed through the different programmes may offer an unprecedented opportunity to study the temporal trends affecting surface properties and to analyse human-induced climate change. Finally, the access to the source code (called PYALUS) is provided through an open access platform in order to share with the community the expertise on the satellite retrieval of this variable.

In this paper we present L-band data usage for Numerical Weather Prediction applications and Emergency Services at the European Centre for Medium-Range Weather Forecasts (ECMWF).

The extension of the ERA5 reanalysis back to 1950 supplements the previously published segment covering 1979 to the present. It features the assimilation of additional conventional observations, as well as improved use of early satellite data. The number of observations assimilated increases from 53,000 per day in early 1950 to 570,000 per day by the end of 1978. Accordingly, the quality of the reanalysis improves throughout the period, generally joining seamlessly with the segment covering 1979 to the present. The fidelity of the extension is illustrated by the accurate depiction of the North Sea storm of 1953, and the events leading to the first discovery of sudden stratospheric warmings in 1952. Time series of ERA5 global surface temperature anomalies show temperatures to be relatively stable from 1950 until the late 1970s, in agreement with the other contemporary full‐input reanalysis covering this period and with independent data sets, although there are significant differences in the accuracy of representing specific regions, Europe being well represented in the early period but Australia less so. The variability of ERA5 precipitation from month to month agrees well with observations for all continents, with correlations above 90% for most of Europe and generally in excess of 70% for North America, Asia and Australia. The evolution of upper air temperatures, humidities and winds shows smoothly varying behaviour, including tropospheric warming and stratospheric cooling, modulated by volcanic eruptions. The Quasi‐Biennial Oscillation is well represented throughout. Aspects to be improved upon in future reanalyses include the assimilation of tropical cyclone data, the spin‐up of soil moisture and stratospheric humidity, and the representation of surface temperatures over Australia.

a description of the ERA5-Land product and an evaluation of it mainly against in-situ but also one satellite-based dataset (skin temperature). The same evaluation is also done for ERA-Interim and ERA5, which indicates the added value but also limitations of ERA5-Land. Further, the downscaled ERA5-Land meteorological data (surface air temperature and surface net radiation) is used to force the land evaporation model GLEAM.

At the European Centre for Medium-Range Weather Forecasts (ECMWF), reanalysis is a key contribution to the Copernicus Climate Change Service (C3S) that is implemented at ECMWF on behalf of the European Commission. The most recent ECMWF global reanalysis, ERA5, provides hourly snapshots of the Earth’s atmosphere, land surface and ocean waves from 1950 with updates with a latency of 5 days. It is highly popular and used for a wide range of applications. The focus will be on the ERA5 back extension from 1950 to 1978 that supplements the previously published segment from 1979 onwards. It features the assimilation of many conventional observations and improved use of early satellite data. The fidelity of the extension is illustrated by the accurate depiction of the North Sea Storm of 1953, and the events leading to the first discovery of Sudden Stratospheric Warmings in 1952. Time series of ERA5 global surface temperature anomalies show temperatures to be relatively stable from 1950 until the late 1970s, in agreement with the other contemporary full-input reanalyses and independent datasets. The evolution of upper air temperatures, humidities and winds show smoothly varying behaviour, including tropospheric warming and stratospheric cooling, modulated by volcanic eruptions. The Quasi Biennial Oscillation is well represented throughout. Despite these good characteristics, the ERA5 back extension did use historical observations for tropical cyclones in a sub-optimal way, which, given their sparsity is a challenging subject in itself. The back extension was published as a separate, preliminary data set and the production of an improved version is currently in progress. The presentation will end with an outlook on future ECMWF reanalysis plans.

Abstract. Framed within the Copernicus Climate Change Service of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the 5th generation of European ReAnalysis (ERA5), hereafter named as ERA5-Land. Once completed, the period covered will span from 1950 to present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, enabling the characterisation of trends and anomalies. This is achieved through global high resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parametrizations that guarantees the use of the state-of-the-art land surface modeling applied to Numerical Weather Prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed behaviour when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available extends from January 1981 to near present, with 2 to 3 months delay with respect to real-time. The segment prior to 1981 is in production, aiming to a release of the whole dataset in summer 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialise NWP and climate models, and to support diverse applications dealing with water resource, land and environmental management. The full ERA5-Land hourly and monthly averaged dataset presented in this paper are available through the Climate Data Store, https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.

This work describes the different algorithmic steps used to retrieve the first Surface Albedo (SA) product based on Sentinel-3 (S-3) data in the framework of the Copernicus Climate Change Service (C3S). The atmospherically corrected Top-Of-Atmosphere (TOA) reflectances into Top-Of-Canopy (TOC) reflectances are brokered from the Copernicus Global Land Service (CGLS). The TOC reflectances are used to obtain a BRDF model. Next, the spectral and angular integration steps are implemented, which take the latter coefficients as input to produce spectral and broadband albedo quantities. The preliminary quality assessment of BSA broadband albedo for the total shortwave shows good overall spatiotemporal consistency with C3S PROBA-V SA products, and good spatial consistency with MODIS MCD43A3 C6 over the Iberian Peninsula (mean bias lower than 5%), with some underestimation of snow targets.

Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available has extended from January 1981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management. The full ERA5-Land hourly (Muñoz-Sabater, 2019a) and monthly (Muñoz-Sabater, 2019b) averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.

Abstract. Climate reanalyses provide a plethora of global atmospheric and surface parameters in a consistent manner over multi-decadal timescales. Hence, they are widely used in many fields, and an in-depth evaluation of the different variables provided by reanalyses is a necessary means to provide feedback on the quality to their users and the operational centres producing these data sets, and to help guide their development. Recently, the European Centre for Medium-Range Weather Forecasts (ECMWF) released the new state-of-the-art climate reanalysis ERA5, following up on its popular predecessor ERA-Interim. Different sets of variables from ERA5 were already evaluated in a handful of studies, but so far, the quality of land-surface energy partitioning has not been assessed. Here, we evaluate the surface energy partitioning over land in ERA5 and concentrate on the appraisal of the surface latent heat flux, surface sensible heat flux, and Bowen ratio against different reference data sets and using different modelling tools. Most of our analyses point towards a better quality of surface energy partitioning in ERA5 than in ERA-Interim, which may be attributed to a better representation of land-surface processes in ERA5 and certainly to the better quality of near-surface meteorological variables. One of the key shortcomings of the reanalyses identified in our study is the overestimation of the surface latent heat flux over land, which – although substantially lower than in ERA-Interim – still remains in ERA5. Overall, our results indicate the high quality of the surface turbulent fluxes from ERA5 and the general improvement upon ERA-Interim, thereby endorsing the efforts of ECMWF to improve their climate reanalysis and to provide useful data to many scientific and operational fields.

The assimilation of L-band surface brightness temperature (Tb) into the land surface model (LSM) component of a numerical weather prediction (NWP) system is generally expected to improve the quality of summertime 2-m air temperature (T2m) forecasts during water-limited surface conditions. However, recent retrospective results from the European Centre for Medium-Range Weather Forecasts (ECMWF) suggest that the assimilation of L-band Tb from the European Space Agency's (ESA) Soil Moisture Ocean Salinity (SMOS) mission may, under certain circumstances, degrade the accuracy of growing-season 24-h T2m forecasts within the central United States. To diagnose the source of this degradation, we evaluate ECMWF soil moisture (SM) and evapotranspiration (ET) forecasts using both in situ and remote sensing resources. Results demonstrate that the assimilation of SMOS Tb broadly improves the ECMWF SM analysis in the central United States while simultaneously degrading the quality of 24-h ET forecasts. Based on a recently derived map of true global SM-ET coupling and a synthetic fraternal twin data assimilation experiment, we argue that the spatial and temporal characteristics of ECMWF SM analyses and ET forecast errors are consistent with the hypothesis that the ECMWF LSM overcouples SM and ET and, as a result, is unable to effectively convert an improved SM analysis into enhanced ET and T2m forecasts. We demonstrate that this overcoupling is likely linked to the systematic underestimation of root-zone soil water storage capacity by LSMs within the U.S. Corn Belt region.