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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 and monthly 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 FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Climate reanalyses provide a plethora of global atmospheric and surface parameters in a consistent manner over multi-decadal time scales. 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 centers producing these data sets, and to help guiding their development. Recently, the European Centre for Medium Range Weather Forecast (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 surface energy partitioning has not been assessed yet. 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, 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. [ABSTRACT FROM AUTHOR]

Climate change mitigation efforts require information on the current greenhouse gas atmospheric concentrations and their sources and sinks. Carbon dioxide (CO2) is the most abundant anthropogenic greenhouse gas. Its variability in the atmosphere is modulated by the synergy between weather and CO2 surface fluxes, often referred to as CO2 weather. It is interpreted with the help of global or regional numerical transport models, with horizontal resolutions ranging from a few hundreds of kilometres to a few kilometres. Changes in the model horizontal resolution affect not only atmospheric transport but also the representation of topography and surface CO2 fluxes. This paper assesses the impact of horizontal resolution on the simulated atmospheric CO2 variability with a numerical weather prediction model. The simulations are performed using the Copernicus Atmosphere Monitoring Service (CAMS) CO2 forecasting system at different resolutions from 9 to 80 km and are evaluated using in situ atmospheric surface measurements and atmospheric column-mean observations of CO2 , as well as radiosonde and SYNOP observations of the winds. The results indicate that both diurnal and day-to-day variability of atmospheric CO2 are generally better represented at high resolution, as shown by a reduction in the errors in simulated wind and CO2. Mountain stations display the largest improvements at high resolution as they directly benefit from the more realistic orography. In addition, the CO2 spatial gradients are generally improved with increasing resolution for both stations near the surface and those observing the total column, as the overall inter-station error is also reduced in magnitude. However, close to emission hotspots, the high resolution can also lead to a deterioration of the simulation skill, highlighting uncertainties in the high-resolution fluxes that are more diffuse at lower resolutions. We conclude that increasing horizontal resolution matters for modelling CO2 weather because it has the potential to bring together improvements in the surface representation of both winds and CO2 fluxes, as well as an expected reduction in numerical errors of transport. Modelling applications like atmospheric inversion systems to estimate surface fluxes will only be able to benefit fully from upgrades in horizontal resolution if the topography, winds and prior flux distribution are also upgraded accordingly. It is clear from the results that an additional increase in resolution might reduce errors even further. However, the horizontal resolution sensitivity tests indicate that the change in the CO2 and wind modelling error with resolution is not linear, making it difficult to quantify the improvement beyond the tested resolutions. Finally, we show that the high-resolution simulations are useful for the assessment of the small-scale variability of CO2 which cannot be represented in coarser-resolution models. These representativeness errors need to be considered when assimilating in situ data and high-resolution satellite data such as Greenhouse gases Observing Satellite (GOSAT), Orbiting Carbon Observatory-2 (OCO-2), the Chinese Carbon Dioxide Observation Satellite Mission (TanSat) and future missions such as the Geostationary Carbon Observatory (GeoCarb) and the Sentinel satellite constellation for CO2. For these reasons, the high-resolution CO2 simulations provided by the CAMS in real time can be useful to estimate such small-scale variability in real time, as well as providing boundary conditions for regional modelling studies and supporting field experiments. [ABSTRACT FROM AUTHOR]

Climate change mitigation efforts require information on the current greenhouse gas atmospheric concentrations and their sources and sinks. Carbon dioxide (CO2) is the most abundant anthropogenic greenhouse gas. Its variability in the atmosphere is modulated by the synergy between weather and CO2 surface fluxes, often referred to as CO2 weather. It is interpreted with the help of global or regional numerical transport models, with horizontal resolutions ranging from a few hundreds of km to a few km. Changes in the model horizontal resolution affect not only atmospheric transport, but also the representation of topography and surface CO2 fluxes. This paper assesses the impact of horizontal resolution on the simulated atmospheric CO2 variability with a numerical weather prediction model. The simulations are performed using the Copernicus Atmosphere Monitoring Service (CAMS) CO2 forecasting system at different resolutions from 9 km to 80 km and are evaluated using in situ atmospheric surface measurements and atmospheric column-mean observations of CO2, as well as radiosonde and SYNOP observations of the winds. The results indicate that both diurnal and day-to-day variability of atmospheric CO2 are generally better represented at high resolution, as shown by a reduction in the errors in simulated wind and CO2. Mountain stations display the largest improvements at high resolution as they directly benefit from the more realistic orography. In addition, the CO2 spatial gradients are generally improved with increasing resolution for both stations near the surface and those observing the total column, as the overall inter-station error is also reduced in magnitude. However, close to emission hotspots, the high resolution can also lead to a deterioration of the simulation skill, highlighting uncertainties in the high resolution fluxes that are more diffuse at lower resolutions. We conclude that increasing horizontal resolution matters for modelling CO2 weather because it has the potential to bring together improvements in the surface representation of both winds and CO2 fluxes, as well as an expected reduction in numerical errors of transport. Modelling applications like atmospheric inversion systems to estimate surface fluxes will only be able to benefit fully from upgrades in horizontal resolution if the topography, winds and prior flux distribution are also upgraded accordingly. It is clear from the results that an additional increase in resolution might reduce errors even further. However, the horizontal resolution sensitivity tests indicate that the change in the CO2 and wind modelling error with resolution is not linear, making it difficult to extrapolate the results beyond the tested resolutions. Finally, we show that the high resolution simulations are useful for the assessment of the small-scale variability of CO2 which cannot be represented in coarser resolution models. These representativeness errors need to be considered when assimilating in situ data and high resolution satellite data such as Greenhouse gases Observing Satellite (GOSAT), Orbiting Carbon Observatory-2 (OCO-2), the Chinese Carbon Dioxide Observation Satellite Mission (TanSat) and future missions such as the Geostationary Carbon Observatory (GeoCarb) and the Sentinel satellite constellation for CO2. For these reasons, the high resolution CO2 simulations provided by the CAMS in real-time can be useful to estimate such small-scale variability in real time, as well as providing boundary conditions for regional modelling studies and supporting field experiments. [ABSTRACT FROM AUTHOR]