scholarly journals Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional Reference Crop Evaporation over Land during the Twentieth Century

2011 ◽  
Vol 12 (5) ◽  
pp. 823-848 ◽  
Author(s):  
G. P. Weedon ◽  
S. Gomes ◽  
P. Viterbo ◽  
W. J. Shuttleworth ◽  
E. Blyth ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Land Surface ◽  
Water Cycle ◽  
Potential Evapotranspiration ◽  
Reanalysis Data ◽  
Meteorological Forcing ◽  
Global Average ◽  
Murray Darling Basin ◽  
Terrestrial Water ◽  
Reference Crop

Abstract The Water and Global Change (WATCH) project evaluation of the terrestrial water cycle involves using land surface models and general hydrological models to assess hydrologically important variables including evaporation, soil moisture, and runoff. Such models require meteorological forcing data, and this paper describes the creation of the WATCH Forcing Data for 1958–2001 based on the 40-yr ECMWF Re-Analysis (ERA-40) and for 1901–57 based on reordered reanalysis data. It also discusses and analyses model-independent estimates of reference crop evaporation. Global average annual cumulative reference crop evaporation was selected as a widely adopted measure of potential evapotranspiration. It exhibits no significant trend from 1979 to 2001 although there are significant long-term increases in global average vapor pressure deficit and concurrent significant decreases in global average net radiation and wind speed. The near-constant global average of annual reference crop evaporation in the late twentieth century masks significant decreases in some regions (e.g., the Murray–Darling basin) with significant increases in others.

scholarly journals Evaluation of Global Water Resources Reanalysis Products in the Upper Blue Nile River Basin

2020 ◽  
Vol 21 (5) ◽  
pp. 935-952 ◽  
Author(s):  
Marika Koukoula ◽  
Efthymios I. Nikolopoulos ◽  
Zoi Dokou ◽  
Emmanouil N. Anagnostou
Keyword(s):  
Water Resources ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Water Cycle ◽  
Spatial Scales ◽  
Meteorological Forcing ◽  
Blue Nile ◽  
Blue Nile Basin ◽  
Terrestrial Water

AbstractWater resources reanalysis (WRR) can be used as a numerical tool to advance our understanding of hydrological processes where in situ observations are limited. However, WRR products are associated with uncertainty that needs to be quantified to improve usability of such products in water resources applications. In this study, we evaluate estimates of water cycle components from 18 state-of-the-art WRR datasets derived from different land surface/hydrological models, meteorological forcing, and precipitation datasets. The evaluation was conducted at three spatial scales in the upper Blue Nile basin in Ethiopia. Precipitation, streamflow, evapotranspiration (ET), and terrestrial water storage (TWS) were evaluated against in situ daily precipitation and streamflow measurements, remote sensing–derived ET, and the NASA Gravity Recovery and Climate Experiment (GRACE) product, respectively. Our results highlight the current strengths and limitations of the available WRR datasets in analyzing the hydrological cycle and dynamics of the study basins, showing an overall underestimation of ET and TWS and overestimation of streamflow. While calibration improves streamflow simulation, it results in a relatively poorer performance in terms of ET. In addition, we show that the differences in the schemes used in the various land surface models resulted in significant differences in the estimation of the water cycle components from the respective WRR products, while we noted small differences among the products related to precipitation forcing. We did not identify a single product that consistently outperformed others; however, we found that there are specific WRR products that provided accurate representation of a single component of the water cycle (e.g., only runoff) in the area.

scholarly journals Diagnosing hydrological limitations of a land surface model: application of JULES to a deep-groundwater chalk basin

2016 ◽  
Vol 20 (1) ◽  
pp. 143-159 ◽  
Author(s):  
N. Le Vine ◽  
A. Butler ◽  
N. McIntyre ◽  
C. Jackson
Keyword(s):  
Land Surface ◽  
Expert Knowledge ◽  
Water Cycle ◽  
Land Surface Model ◽  
Surface Model ◽  
Deep Groundwater ◽  
Resolution Model ◽  
Terrestrial Water ◽  
Water Redistribution ◽  
Types Of Information

Abstract. Land surface models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy, and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation and improvement is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution, and spatial water redistribution over the catchment's groundwater and surface-water systems. Three types of information are utilized to improve the model's hydrology: (a) observations, (b) information about expected response from regionalized data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.

Intercomparison of terrestrial water budgets in EURO-CORDEX and TSMP evaluation runs

2020 ◽  
Author(s):  
Mohamed Eltahan ◽  
Klaus Goergen ◽  
Carina Furusho-Percot ◽  
Stefan Kollet
Keyword(s):  
Land Surface ◽  
Water Budget ◽  
Climate Models ◽  
Water Cycle ◽  
Weather Prediction ◽  
Regional Climate ◽  
Shallow Groundwater ◽  
Surface Model ◽  
Frequency Distributions ◽  
Terrestrial Water

<p>Water is one of Earth’s most important geo-ecosystem components. Here we present an evaluation of water cycle components using 12 EURO-CORDEX Regional Climate Models (RCMs) and the Terrestrial Systems Modeling Platform (TSMP) from ERA-Interim driven evaluation runs. Unlike the other RCMs, TSMP provides an <span>integrated</span> representation of the terrestrial water cycle by coupling the numerical weather prediction model COSMO, the land surface model CLM and the surface-subsurface hydrological model ParFlow, which simulates shallow groundwater states and fluxes. The study analyses precipitation (P), evapotranspiration (E), runoff (R), and terrestrial water storage (TWS=P-E-R) at a 0.11degree spatial resolution (about 12km) on EUR-11 CORDEX grid from 1996 to 2008. As reference datasets, we use ERA5 reanalysis to <span>represent</span> the complete terrestrial water budget, <span>as well as </span>the E-OBS, GLEAM and E-Run datasets for precipitation, evapotranspiration and runoff, respectively. The terrestrial water budget is investigated for twenty catchments over Europe (Guadalquivir, Guadiana, Tagus, Douro, Ebro, Garonne, Rhone, Po, Seine, Rhine, Loire, Maas, Weser, Elbe, Oder, Vistuala, Danube, Dniester, Dnieper, and Neman). Annual cycles, seasonal variations, empirical frequency distributions, spatial distributions for the water cycle components and budgets over the catchments are assessed. The analysis <span>demonstrates</span> the capability of the RCMs and TSMP to reproduce the overall <span>characteristics of the</span> water cycle over the EURO-CORDEX domain<span>, which is a prerequisite if, e.g., climate change projections with the CORDEX RCMs or TSMP are to be used for vulnerability, impacts, and adaptation studies.</span></p>

The AmazonWater Cycle: Perspectives fromWater Budget Closure and Ocean Salinity

2020 ◽  
pp. 1-44
Author(s):  
J. E. Jack Reeves Eyre ◽  
Xubin Zeng
Keyword(s):  
Water Vapor ◽  
Land Surface ◽  
Water Cycle ◽  
Water Storage ◽  
River Mouth ◽  
Small Subset ◽  
Terrestrial Water Storage ◽  
Crucial Component ◽  
Ocean Salinity ◽  
Terrestrial Water

AbstractGlobal and regional water cycle includes precipitation, water vapor divergence, and change of column water vapor in the atmosphere, and land surface evapotranspiration, terrestrial water storage change, and river discharge which is linked to ocean salinity near the river mouth. The water cycle is a crucial component of the Earth system, and numerous studies have addressed its individual components (e.g., precipitation). Here we assess, for the first time, if remote sensing and reanalysis datasets can accurately and self consistently portray the Amazon water cycle. This is further assisted with satellite ocean salinity measurements near the mouth of the Amazon River. The widely-used practice of taking the mean of an ensemble of datasets to represent water cycle components (e.g., precipitation) can produce large biases in water cycle closure. Closure is achieved with only a small subset of data combinations (e.g., ERA5 reanalysis precipitation and evapotranspiration plus GRACE satellite terrestrial water storage), which rules out the lower precipitation and higher evapotranspiration estimates, providing valuable constraints on assessments of precipitation, evapotranspiration and their ratio. The common approach of using the Óbidos stream gauge (located hundreds of kilometres from the river mouth) multiplied by a constant (1.25) to represent the entire Amazon discharge is found to misrepresent the seasonal cycle, and this can affect the apparent influence of Amazon discharge on tropical Atlantic salinity.

scholarly journals Diagnosing hydrological limitations of a Land Surface Model: application of JULES to a deep-groundwater chalk basin

2015 ◽  
Vol 12 (8) ◽  
pp. 7541-7582
Author(s):  
N. Le Vine ◽  
A. Butler ◽  
N. McIntyre ◽  
C. Jackson
Keyword(s):  
Land Surface ◽  
Expert Knowledge ◽  
Water Cycle ◽  
Land Surface Model ◽  
Surface Model ◽  
Deep Groundwater ◽  
Resolution Model ◽  
Terrestrial Water ◽  
Water Redistribution ◽  
Types Of Information

Abstract. Land Surface Models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution and spatial water redistribution over the catchment's groundwater and surface water systems. Three types of information are utilised to improve the model's hydrology: (a) observations, (b) information about expected response from regionalised data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.

scholarly journals UniFHy v0.1: A community framework for the terrestrial water cycle in Python

2021 ◽  
Author(s):  
Thibault Hallouin ◽  
Richard J. Ellis ◽  
Douglas B. Clark ◽  
Simon J. Dadson ◽  
Andrew G. Hughes ◽  
...  
Keyword(s):  
Land Surface ◽  
Hydrological Cycle ◽  
Water Cycle ◽  
System Model ◽  
Unified Framework ◽  
Future Developments ◽  
Land System ◽  
Road Map ◽  
Terrestrial Water ◽  
Floods And Droughts

Abstract. Land surface, hydrological, and groundwater modelling communities all have expertise in simulating the hydrological processes at play in the land system, but these communities have largely remained distinct with limited collaboration between disciplines. In order to address key societal questions regarding the future availability of water resources and the intensity of extreme events such as floods and droughts in a changing climate, these communities must build on the strengths of one another. The development of a common modelling infrastructure, a framework, can contribute to stimulating cross-fertilisation between them. By allowing (parts of) their existing models to be coupled together, improved land system models can be built to better understand and simulate the terrestrial hydrological cycle. This paper presents a Python implementation of such a framework named the Unified Framework for Hydrology (unifhy). The framework aims to provide the technical infrastructure required to couple models, taking into account the specific needs of a land system model. Its conceptual design and technical capabilities are outlined first, before its usage and useful characteristics are demonstrated through case studies. The limitations of the current framework and necessary future developments are finally presented as a road map for later versions and/or other implementations of the framework.

scholarly journals Intercomparison of the Surface Energy Partitioning in CMIP5 Simulations

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 602 ◽  
Author(s):  
Yang ◽  
Wang ◽  
Huang
Keyword(s):  
Soil Moisture ◽  
Surface Energy ◽  
Land Surface ◽  
Radiative Forcing ◽  
Climate Models ◽  
Water Cycle ◽  
Potential Evapotranspiration ◽  
Sensible Heat Flux ◽  
Coupled Model ◽  
Energy Partitioning

The warming climate significantly modifies the global water cycle. Global evapotranspiration has increased over the past decades, yet climate models agree on the drying trend of land surface. In this study, we conducted an intercomparison analysis of the surface energy partitioning across Coupled Model Intercomparison Phase 5 (CMIP5) simulations and evaluated its behaviour with surface temperature and soil moisture anomalies, against the theoretically derived thermodynamic formula. Different responses over land and sea surfaces to elevated greenhouse gas emissions were found. Under the Representative Concentration Pathway of +8.5 W m−2 (RCP8.5) warming scenario, the multi-model mean relative efficiency anomaly from CMIP5 simulations is 3.83 and −0.12 over global sea and land, respectively. The significant anomaly over sea was captured by the thermodynamic solution based on the principle of maximum entropy production, with a mean relative error of 14.6%. The declining trend over land was also reproduced, but an accurate prediction of its small anomaly will require the inclusions of complex physical processes in future work. Despite increased potential evapotranspiration under rising temperatures, both CMIP5 simulations and thermodynamic principles suggest that the soil moisture-temperature feedback cannot support long-term enhanced evapotranspiration at the global scale. The dissipation of radiative forcing eventually shifts towards sensible heat flux and accelerates the warming over land, especially over South America and Europe.

scholarly journals A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset

2016 ◽  
Author(s):  
Jaap Schellekens ◽  
Emanuel Dutra ◽  
Alberto Martínez-de la Torre ◽  
Gianpaolo Balsamo ◽  
Albert van Dijk ◽  
...  
Keyword(s):  
Land Surface ◽  
Snow Water Equivalent ◽  
Water Cycle ◽  
Signal To Noise Ratio ◽  
Model Performance ◽  
Meteorological Forcing ◽  
Unconstrained Model ◽  
Total Runoff ◽  
Ensemble Mean ◽  
Benchmark Datasets

Abstract. The dataset presented here consists of an ensemble of ten global hydrological and land surface models for the period 1979–2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state-of-the-art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominate regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not being reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3/yr (334 kg/m2/yr) while the ensemble mean of total evaporation was 537 kg/m2/yr. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. The doi for the data is: doi:10.5281/zenodo.167070

Water Cycle Extremes in the GRACE and GRACE-FO Data Record

2020 ◽  
Author(s):  
Matthew Rodell ◽  
Bailing Li
Keyword(s):  
Land Surface ◽  
Water Mass ◽  
Water Cycle ◽  
Land Surface Model ◽  
Surface Model ◽  
Drought Event ◽  
Terrestrial Water Storage ◽  
Data Record ◽  
Terrestrial Water ◽  
Hydrological Droughts

<p>A unique aspect of satellite gravimetry is its ability to quantify changes in all water stored at all depths on and beneath the land surface.  Hence, GRACE and GRACE-FO are well suited for quantifying both hydrological droughts, when terrestrial water storage (TWS) is low, and pluvial events, when TWS is high.  In this study we use GRACE and GRACE-FO data assimilation within a land surface model to fill the 1-year gap between the two missions and to replace other missing data.  We apply a cluster analysis approach to identify the locations and extents of TWS extreme events in resulting data record.  We then rank these events based on their intensity, i.e., the integral of the non-seasonal water mass anomaly over the period of the event.  In this presentation we report on the largest wet and dry events over each continent.  During the period of study, Africa, North America, and Australia each had a wet event with an intensity that exceeded 10,000 km<sup>3</sup> * month, although the 2010-2012 event in Australia can largely be attributed to a depressed baseline TWS during the period caused by the millennial drought.  With 30 more years of data it is probable that the intensity of that drought would have been greater than the recovery and wet event during 2010-2012.  As it stands, the biggest drought event was determined to be one occurred in South America during 2015-2016, with an intensity of over 10,000 km<sup>3</sup> * month.</p>

scholarly journals Evaluating Surface Water Cycle Simulated by the Australian Community Land Surface Model (CABLE) across Different Spatial and Temporal Domains

2013 ◽  
Vol 14 (4) ◽  
pp. 1119-1138 ◽  
Author(s):  
Huqiang Zhang ◽  
Bernard Pak ◽  
Ying Ping Wang ◽  
Xinyao Zhou ◽  
Yongqiang Zhang ◽  
...  
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Parameters ◽  
Global Soil ◽  
Australian Community ◽  
Forest Regions ◽  
Terrestrial Water ◽  
Multimodel Ensembles

Abstract The terrestrial water cycle in the Australian Community Atmosphere Biosphere Land Exchange (CABLE) model has been evaluated across a range of temporal and spatial domains. A series of offline experiments were conducted using the forcing data from the second Global Soil Wetness Project (GSWP-2) for the period of 1986–95, but with its default parameter settings. Results were compared against GSWP-2 multimodel ensembles and a range of observationally driven datasets. CABLE-simulated global mean evapotranspiration (ET) and runoff agreed well with the GSWP-2 multimodel climatology and observations, and the spatial variations of ET and runoff across 150 large catchments were well captured. Nevertheless, at regional scales it underestimated ET in the tropics and had some significant runoff errors. The model sensitivity to a number of selected parameters is further examined. Results showed some significant model uncertainty caused by its sensitivity to soil wilting point as well as to the root water uptaking efficiency and canopy water storage parameters. The sensitivity was large in tropical rain forest and midlatitude forest regions, where the uncertainty caused by the model parameters was comparable to a large part of its difference against the GSWP-2 multimodel mean. Furthermore, the discrepancy among the CABLE perturbation experiments caused by its sensitivity to model parameters was equivalent to about 20%–40% of the intermodel difference among the GSWP-2 models, which was primarily caused by different model structure/processes. Although such results are model dependent, they suggest that soil/vegetation parameters could be another source of uncertainty in estimating global surface energy and water budgets.

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