scholarly journals Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim

Author(s):  
Pere Quintana-Seguí ◽  
Marco Turco ◽  
Sixto Herrera ◽  
Gonzalo Miguez-Macho

Abstract. Offline Land-Surface Model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/80–2013/14). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate Regional Climate Models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The results show that SAFRAN and Spain02 have very similar skill scores, although the later has better scores in general. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well, in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.

2017 ◽  
Vol 21 (4) ◽  
pp. 2187-2201 ◽  
Author(s):  
Pere Quintana-Seguí ◽  
Marco Turco ◽  
Sixto Herrera ◽  
Gonzalo Miguez-Macho

Abstract. Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980–2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.


2006 ◽  
Vol 7 (1) ◽  
pp. 61-80 ◽  
Author(s):  
B. Decharme ◽  
H. Douville ◽  
A. Boone ◽  
F. Habets ◽  
J. Noilhan

Abstract This study focuses on the influence of an exponential profile of saturated hydraulic conductivity, ksat, with soil depth on the water budget simulated by the Interaction Soil Biosphere Atmosphere (ISBA) land surface model over the French Rhône River basin. With this exponential profile, the saturated hydraulic conductivity at the surface increases by approximately a factor of 10, and its mean value increases in the root zone and decreases in the deeper region of the soil in comparison with the values given by Clapp and Hornberger. This new version of ISBA is compared to the original version in offline simulations using the Rhône-Aggregation high-resolution database. Low-resolution simulations, where all atmospheric data and surface parameters have been aggregated, are also performed to test the impact of the modified ksat profile at the typical scale of a climate model. The simulated discharges are compared to observations from a dense network consisting of 88 gauging stations. Results of the high-resolution experiments show that the exponential profile of ksat globally improves the simulated discharges and that the assumption of an increase in saturated hydraulic conductivity from the soil surface to a depth close to the rooting depth in comparison with values given by Clapp and Hornberger is reasonable. Results of the scaling experiments indicate that this parameterization is also suitable for large-scale hydrological applications. Nevertheless, low-resolution simulations with both model versions overestimate evapotranspiration (especially from the plant transpiration and the wet fraction of the canopy) to the detriment of total runoff, which emphasizes the need for implementing subgrid distribution of precipitation and land surface properties in large-scale hydrological applications.


2020 ◽  
Author(s):  
Omar Müller ◽  
Pier Luigi Vidale ◽  
Patrick McGuire ◽  
Benoît Vannière ◽  
Reinhard Schiemann ◽  
...  

<p>Previous studies showed that high resolution GCMs overestimate land precipitation when compared against gridded observations or reanalysis (Demory et al. 2014, Vannière et al. 2019). In particular, grid point models (eg. HadGEM3) show a significant increase of precipitation on regions dominated by complex orography, where the scarcity of gauge stations increase the uncertainty of gridded observations. The goal of this work is to assess the effect of such differences in precipitation on river discharge, considering it as an integrator of the water balance at catchment scale. A set of JULES and CLM simulations have been conducted turning rivers on with Total Runoff Integrating Pathways (TRIP) and the River Transport Model (RTM) respectively. The simulations form three ensembles for each land surface model (LSM) which main difference is given by the forcing dataset. The forcings are WFDEI (reanalysis), LR (~1° resolution in meteorological data from GCMs) and HR (~0.25° resolution in meteorological data from GCMs). These ensembles are evaluated in a set of 280 catchments distributed around the world.</p><p>In terms of correlation between simulated and observed river discharge observations, the results show that LSMs forced by reanalysis have higher performance than LSMs forced by GCMs as expected. In terms of biases, the river discharge is underestimated in eight out of eleven major basins when LSMs are forced by reanalysis. On those basins, the extra precipitation estimated by GCMs help to simulate an amount of river discharge closer to observations (Eg. Yenisey and Lena). Moreover, 37 small basins with a strong component of orographic precipitation over the Andes, the Rocky Mountains, the Alps and in the Maritime Continent were evaluated. In most cases HR offers notably better results than LR and WFDEI, suggesting that high resolution models produce orographic precipitation in the correct place and time.</p><p>In future works offline TRIP simulations will be carried out directly forced by runoff and subsurface runoff from GCMs. It will allow to discard errors in evapotranspiration produced by JULES or CLM when they are used to simulate river discharge. This work is part of the European Process-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment (PRIMAVERA) Project. PRIMAVERA is a collaboration between 19 funded by the European Union’s Horizon 2020 Research & Innovation Programme.</p><p>Demory, M. E., Vidale, P. L., Roberts, M. J., Berrisford, P., Strachan, J., Schiemann, R., & Mizielinski, M. S. (2014). The role of horizontal resolution in simulating drivers of the global hydrological cycle. CLIM DYNAM, 42(7-8), 2201-2225.</p><p>Vannière, B., Demory, M. E., Vidale, P. L., Schiemann, R., Roberts, M. J., Roberts, C. D., ... & Senan, R. (2018). Multi-model evaluation of the sensitivity of the global energy budget and hydrological cycle to resolution. CLIM DYNAM, 1-30.</p>


2021 ◽  
Author(s):  
Joaquín Muñoz-Sabater ◽  
Emanuel Dutra ◽  
Anna Agustí-Panareda ◽  
Clément Albergel ◽  
Gabriele Arduini ◽  
...  

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.


2009 ◽  
Vol 6 (2) ◽  
pp. 2733-2750 ◽  
Author(s):  
G. Schumann ◽  
D. J. Lunt ◽  
P. J. Valdes ◽  
R. A. M. de Jeu ◽  
K. Scipal ◽  
...  

Abstract. We demonstrate that global satellite products can be used to evaluate climate model soil moisture predictions but conclusions should be drawn with care. The quality of a limited area climate model (LAM) was compared to a general circulation model (GCM) using soil moisture data from two different Earth observing satellites within a model validation scheme that copes with the presence of uncertain data. Results showed that in the face of imperfect models and data, it is difficult to investigate the quality of current land surface schemes in simulating hydrology accurately. Nevertheless, a LAM provides, in general, a better representation of spatial patterns and dynamics of soil moisture. However, in months when data uncertainty is higher, particularly in colder months and in periods when vegetation cover and soil moisture are out of phase (e.g. August in the case of Western Europe), it is not possible to draw firm conclusions about model acceptability. Our work indicates that a higher resolution LAM has more benefits to soil moisture prediction than are due to the resolution alone and can be attributed to an overall intensification of the hydrological cycle relative to the GCM.


2012 ◽  
Vol 9 (7) ◽  
pp. 8213-8256 ◽  
Author(s):  
J.-P. Vergnes ◽  
B. Decharme

Abstract. Groundwater is a non-negligible component of the global hydrological cycle, and its interaction with its overlying unsaturated zones can influence water and energy fluxes between the land surface and the atmosphere. Despite its importance, groundwater is not yet represented in most climate models. In this paper, the simple groundwater scheme implemented in the Total Runoff Integrating Pathways (TRIP) river routing model is applied in off-line mode at global scale using a 0.5° model resolution. The simulated river discharges are evaluated against a large dataset of about 3500 gauging stations compiled from the Global Data Runoff Center (GRDC) and other sources, while the Terrestrial Water Storage (TWS) variations derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission helps to evaluate the simulated TWS. The forcing fields (surface runoff and deep drainage) come from an independent simulation of the ISBA land surface model covering the period from 1950 to 2008. Results show that groundwater improves the efficiency scores for about 70% of the gauging stations and deteriorates them for 15%. The simulated TWS are also in better agreement with the GRACE estimates. These results are mainly explained by the lag introduced by the low-frequency variations of groundwater, which tend to shift and smooth the simulated river discharges and TWS. A sensitivity study on the global precipitation forcing used in ISBA to produce the forcing fields is also proposed. It shows that the groundwater scheme is not influenced by the uncertainties in precipitation data.


2012 ◽  
Vol 16 (10) ◽  
pp. 3889-3908 ◽  
Author(s):  
J.-P. Vergnes ◽  
B. Decharme

Abstract. Groundwater is a non-negligible component of the global hydrological cycle, and its interaction with overlying unsaturated zones can influence water and energy fluxes between the land surface and the atmosphere. Despite its importance, groundwater is not yet represented in most climate models. In this paper, the simple groundwater scheme implemented in the Total Runoff Integrating Pathways (TRIP) river routing model is applied in off-line mode at global scale using a 0.5° model resolution. The simulated river discharges are evaluated against a large dataset of about 3500 gauging stations compiled from the Global Data Runoff Center (GRDC) and other sources, while the terrestrial water storage (TWS) variations derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission help to evaluate the simulated TWS. The forcing fields (surface runoff and deep drainage) come from an independent simulation of the Interactions between Soil-Biosphere-Atmosphere (ISBA) land surface model covering the period from 1950 to 2008. Results show that groundwater improves the efficiency scores for about 70% of the gauging stations and deteriorates them for 15%. The simulated TWS are also in better agreement with the GRACE estimates. These results are mainly explained by the lag introduced by the low-frequency variations of groundwater, which tend to shift and smooth the simulated river discharges and TWS. A sensitivity study on the global precipitation forcing used in ISBA to produce the forcing fields is also proposed. It shows that the groundwater scheme is not influenced by the uncertainties in precipitation data.


2021 ◽  
Vol 13 (9) ◽  
pp. 4349-4383
Author(s):  
Joaquín Muñoz-Sabater ◽  
Emanuel Dutra ◽  
Anna Agustí-Panareda ◽  
Clément Albergel ◽  
Gabriele Arduini ◽  
...  

Abstract. 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.


2018 ◽  
Vol 22 (1) ◽  
pp. 673-687 ◽  
Author(s):  
Antoine Colmet-Daage ◽  
Emilia Sanchez-Gomez ◽  
Sophie Ricci ◽  
Cécile Llovel ◽  
Valérie Borrell Estupina ◽  
...  

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.


2016 ◽  
Vol 52 (4) ◽  
pp. 950-964 ◽  
Author(s):  
Alan D. Snow ◽  
Scott D. Christensen ◽  
Nathan R. Swain ◽  
E. James Nelson ◽  
Daniel P. Ames ◽  
...  

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