ERA5-Land: a state-of-the-art global reanalysis dataset for land applications

Earth system science data, Journal Year: 2021, Volume and Issue: 13(9), P. 4349 - 4383

Published: Sept. 7, 2021

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

Language: Английский

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Variable 21st Century Climate Change Response for Rivers in High Mountain Asia at Seasonal to Decadal Time Scales

Water Resources Research, Journal Year: 2021, Volume and Issue: 57(5)

Published: May 1, 2021

Abstract The hydrological response to climate change in mountainous basins manifests itself at varying spatial and temporal scales, ranging from catchment large river basin scale sub‐daily decade century scale. To robustly assess the 21st impact for hydrology entire High Mountain Asia (HMA) a wide range of we use high resolution cryospheric‐hydrological model covering 15 upstream HMA quantify compound effects future changes precipitation temperature based on projections Coupled Model Intercomparison Project Phase 6 ensemble. Our analysis reveals contrasting responses HMA's rivers, dictated by their regimes. At seasonal scale, earlier onset melting causes shift magnitude peak water availability, year. after an initial increase, glacier melt declines mid or end except Tarim basin, where it continues increase. Despite variability regimes across our results indicate relatively consistent terms total availability decadal time scales. Although increases headwaters, seasonality may diverge widely between need be addressed while adapting region food security, energy security as well biodiversity, livelihoods many depend HMA.

Language: Английский

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Improved daily SMAP satellite soil moisture prediction over China using deep learning model with transfer learning

Journal of Hydrology, Journal Year: 2021, Volume and Issue: 600, P. 126698 - 126698

Published: July 16, 2021

Language: Английский

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Estimation of Global Irrigation Water Use by the Integration of Multiple Satellite Observations

Water Resources Research, Journal Year: 2022, Volume and Issue: 58(3)

Published: March 1, 2022

Abstract Quantification of the global irrigation water use (IWU) is crucial to understanding anthropogenic disturbance natural hydrological cycle and optimal agricultural management. However, it challenging obtain time series data with conventional survey‐based approach, while current satellite‐based IWU estimations are subject gaps model structure. In this paper, we propose a comprehensive framework couple different processes associated integrate multiple satellite observations estimate IWU. The ensemble demonstrates an improved performance when compared obtained from individual observations. results show reasonable correlation withdrawal in states US (bias = −0.42 km 3 ), provinces China −3.10 country statistics Food Agriculture Organization −10.84 ). Large amounts apparent India, China, US, Europe, Pakistan, making up >70% A general underestimation found both work previous studies, due coarse resolution asynchronism various products, changes irrigated areas, deficiency detecting events under case saturated soil moisture. Nevertheless, demonstrate advantages integrating reduce uncertainty estimating additional efforts needed produce high‐quality finer spatiotemporal further improve accuracy estimation.

Language: Английский

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A global dataset of terrestrial evapotranspiration and soil moisture dynamics from 1982 to 2020

Scientific Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: May 3, 2024

Quantifying terrestrial evapotranspiration (ET) and soil moisture dynamics accurately is crucial for understanding the global water cycle surface energy balance. We present a novel, long-term dataset of ET derived from newly developed Simple Terrestrial Hydrosphere model, version 2 (SiTHv2). This ecohydrological driven by multi-source satellite observations hydrometeorological variables reanalysis data, provides daily ET-related estimates (e.g., total ET, plant transpiration, evaporation, intercepted evaporation) three-layer at 0.1° spatial resolution. Validation with in-situ measurements comparisons mainstream products demonstrate robust performance SiTHv2 in both magnitude temporal multiple scales. The comprehensive path characterization model makes this seamless particularly valuable studies requiring synchronized budget vegetation response to constraints. With its coverage high spatiotemporal resolution, SiTHv2-derived product will be suitable support analyses related hydrologic cycle, drought assessment, ecosystem health.

Language: Английский

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Pakistan's 2022 floods: Spatial distribution, causes and future trends from Sentinel-1 SAR observations

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 304, P. 114055 - 114055

Published: Feb. 21, 2024

Language: Английский

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Evaluation of Long-Term and High-Resolution Gridded Precipitation and Temperature Products in the Qilian Mountains, Qinghai–Tibet Plateau

Frontiers in Environmental Science, Journal Year: 2022, Volume and Issue: 10

Published: May 25, 2022

Long-term and high-resolution gridded products of precipitation temperature data are highly important to study the changes in climate environment under global warming. Considering uncertainties these mountainous areas, it is necessary evaluate reliability. This evaluates performances CMFD (China Meteorological Forcing Dataset) ERA5-Land simulating Qilian Mountains over period 1980–2018. We use observation 28 basic meteorological stations compare with reanalysis products. Error metrics (the correlation coefficient (CC), root mean square error (RMSE), absolute (MAE), relative bias (BIAS)) used quantify monthly differences existence between observed data. Our findings indicate that both could well reproduce spatial distribution region. A good found OBS different amounts conditions. The average temperatures reveal a high results. Moreover, CC values highest autumn lowest winter, higher spring autumn. However, we find underestimate varying degrees, amount overestimated by ERA5-Land. results evaluation show errors yielded as whole distinctly fewer than those ERA5-Land, while air nearly identical each other. Overall, more suitable for studying trends Mountains. As simulation precipitation, performs better central eastern parts Mountains, whereas western part

Language: Английский

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A First Evaluation of ERA5-Land Reanalysis Temperature Product Over the Chinese Qilian Mountains

Frontiers in Earth Science, Journal Year: 2022, Volume and Issue: 10

Published: Aug. 8, 2022

Reanalysis temperature products are important datasets for estimates over high-elevation areas with few meteorological stations. In this study, surface 2 m air data from 17 stations 1979 to 2017 in the Qilian Mountains (QLM) used comparison newest reanalysis product: ERA5-Land derived European Centre Medium-Range Weather Forecasts (ECMWF). general, product can reproduce observation variation at different time scales very well. A high monthly correlation coefficient that ranges 0.978 0.998 suggests could capture observations However, attention should be paid before using individual sites because of average root-mean-square-error (RMSE) 2.2°C all The biases between and mainly caused by elevation differences grid points sites. annual mean shows a significant warming trend (0.488°C/decade) based on observations. captures increasing well (0.379°C/decade). biggest positive trends both found summer values 0.574°C/decade 0.496°C/decade, respectively. We suggest generally reproduces is reliable scientific research QLM.

Language: Английский

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A new 2010 permafrost distribution map over the Qinghai–Tibet Plateau based on subregion survey maps: a benchmark for regional permafrost modeling

Earth system science data, Journal Year: 2023, Volume and Issue: 15(9), P. 3905 - 3930

Published: Sept. 4, 2023

Abstract. Permafrost over the Qinghai–Tibet Plateau (QTP) has received increasing attention due to its high sensitivity climate change. Numerous spatial modeling studies have been conducted on QTP assess status of permafrost, project future changes in and diagnose contributors permafrost degradation. Due scarcity ground stations QTP, these are often hampered by lack validation references, calibration targets, model constraints; however, a high-quality distribution map would be good option as benchmark for simulations. Existing maps can poorly serve this purpose. An ideal should methodologically sound, sufficient accuracy, based observations from mapping years rather than all historical data spanning several decades. Therefore, study, we created new 2010 using novel approach with satellite-derived surface thawing freezing indices inputs survey-based subregion constraints. This accounted effects local factors incorporating (into model) an empirical soil parameter whose values were optimally estimated through clustering optimization constrained maps, was also improved reduce parametric equifinality. showed total area about 1.086×106 km2 (41.2 % area) seasonally frozen 1.447×106 (54.9 %) 2010, excluding glaciers lakes. Validations (κ=0.74) borehole records (overall accuracy =0.85 κ=0.43) higher compared two other recent maps. Inspection regions obvious distinctions between affirms that is more realistic Zou et al. (2017) map. Given demonstrated excellent constraining/validating land simulations reference projecting context global warming. The dataset available repository hosted Figshare (Cao al., 2022): https://doi.org/10.6084/m9.figshare.19642362.

Language: Английский

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Evaluating the performance of key ERA‐Interim, ERA5 and ERA5‐Land climate variables across Siberia

International Journal of Climatology, Journal Year: 2024, Volume and Issue: 44(7), P. 2318 - 2342

Published: April 11, 2024

Abstract Reanalysis datasets provide a continuous picture of the past climate for every point on Earth. They are especially useful in areas with few direct observations, such as Siberia. However, to ensure these sufficiently accurate they need be validated against readings from meteorological stations. Here, we analyse how values six variables—the minimum, mean and maximum 2‐metre air temperature, snow depth (SD), total precipitation wind speed (WSP)—from three reanalysis datasets—ERA‐Interim, ERA5 ERA5‐Land—compare observations 29 stations across Siberia Russian Far East daily timescale 1979 2019. All reanalyses produce temperature that close those observed, average absolute bias not exceeding 1.54°C. care should taken minimum during summer months—there nine where correlation <0.60 due inadequate night‐time cooling. The SD generally observed after 1992, ERA5, when data some began assimilated, but used caution (if at all) before 1992 lack assimilation leads large overestimations. For low good approximations, however struggle attain extreme high values. Similarly, 10‐metre WSP; perform well speeds up 2.5 ms −1 above 5.0 . variables, recommend using over ERA‐Interim ERA5‐Land future research. shows minor improvements ERA‐Interim, and, despite an increased spatial resolution, there is no advantage ERA5‐Land.

Language: Английский

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