Evaluation of the effects of general circulation models' subgrid variability and patchiness of rainfall and soil moisture on land surface water balance fluxes

Abstract. Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982–2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p < 0.01) in the Everglades of Florida over the years 1996–2001. The modeled monthly soil moisture for Illinois of the US agrees well (R2 = 0.79, p < 0.01) with the observed over the years 1984–2001. The modeled monthly stream flow for most 12 major rivers in the US is consistent R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficients >0.52) with observed values over the years 1982–2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

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HAPEX—MOBILHY: A Hydrologic Atmospheric Experiment the Study of Water Budget and Evaporation Flux at the Climatic Scale

Bulletin of the American Meteorological Society ◽

10.1175/1520-0477-67.2.138 ◽

1986 ◽

Vol 67 (2) ◽

pp. 138-144 ◽

Cited By ~ 7

Author(s):

Jean-Claude André ◽

Jean-Paul Goutorbe ◽

Alain Perrier

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Land Surface ◽

Water Budget ◽

General Circulation ◽

Circulation Model ◽

Surface Energy Budget ◽

Surface Hydrology ◽

Land Surface Water ◽

Evaporation Flux

The HAPEX-MOBILHY program is aimed at studying the hydrological budget and evaporation flux at the scale of a GCM (general circulation model) grid square, i.e., 104 km2. Different surface and subsurface networks will be operated during the year 1986, to measure and monitor soil moisture, surface-energy budget and surface hydrology, as well as atmospheric properties. A two-and-a-half-month special observing period will allow for detailed measurements of atmospheric fluxes and for intensive remote sensing of surface properties using well-instrumented aircraft. The main objective of the program, for which guest investigations are strongly encouraged, is to provide a data base against which parameterization schemes for the land-surface water budget will be tested and developed.

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HydroPy (v1.0): A new global hydrology model written in Python

10.5194/gmd-2021-53 ◽

2021 ◽

Author(s):

Tobias Stacke ◽

Stefan Hagemann

Keyword(s):

Surface Water ◽

Water Balance ◽

Land Surface ◽

Max Planck ◽

Water Balance Components ◽

Meteorological Model ◽

Land Surface Water ◽

Hydrology Model ◽

Flexible Infrastructure ◽

The Tropics

Abstract. Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components as well as their past evolution and potential future development under various scenarios. While GHMs are a part of the Hydrologist's toolbox since several decades, the models are continuously developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max-Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge, however they can – at least to some part – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similar to MPI-HM and, thus, conclude the successful transition from MPI-HM to HydroPy.

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Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

Hydrology and Earth System Sciences ◽

10.5194/hess-16-2547-2012 ◽

2012 ◽

Vol 16 (8) ◽

pp. 2547-2565 ◽

Cited By ~ 4

Author(s):

G. Tang ◽

P. J. Bartlein

Keyword(s):

Soil Moisture ◽

Surface Water ◽

Surface Runoff ◽

Land Surface ◽

Surface Hydrology ◽

Large Spatial Scale ◽

Land Surface Water ◽

Land Surface Hydrology ◽

Water Balances ◽

Global Vegetation

Abstract. Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981–2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981–2006 (R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15%) with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH-modeled monthly soil moisture for the state of Illinois (US) agreed well (R2 = 0.79, p < 0.01) with observed data for the years 1984–2001. Overall, this study justifies both the feasibility of incorporating satellite-based land covers into a DGVM and the reliability of LH to simulate land-surface water balances. To better estimate surface/river runoff at mid-to-high latitudes, we recommended that LPJ-DGVM considers the effects of solar radiation on snowmelt.

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Understanding the Distinct Impacts of MCS and Non-MCS Rainfall on the Surface Water Balance in the Central United States Using a Numerical Water-Tagging Technique

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0081.1 ◽

2020 ◽

Vol 21 (10) ◽

pp. 2343-2357

Author(s):

Huancui Hu ◽

L. Ruby Leung ◽

Zhe Feng

Keyword(s):

United States ◽

Soil Moisture ◽

Surface Water ◽

Water Balance ◽

Surface Runoff ◽

Land Surface ◽

Warm Season ◽

Surface Model ◽

Central United States ◽

Infiltration Excess

ABSTRACTWarm-season rainfall associated with mesoscale convective systems (MCSs) in the central United States is characterized by higher intensity and nocturnal timing compared to rainfall from non-MCS systems, suggesting their potentially different footprints on the land surface. To differentiate the impacts of MCS and non-MCS rainfall on the surface water balance, a water tracer tool embedded in the Noah land surface model with multiparameterization options (WT-Noah-MP) is used to numerically “tag” water from MCS and non-MCS rainfall separately during April–August (1997–2018) and track their transit in the terrestrial system. From the water-tagging results, over 50% of warm-season rainfall leaves the surface–subsurface system through evapotranspiration by the end of August, but non-MCS rainfall contributes a larger fraction. However, MCS rainfall plays a more important role in generating surface runoff. These differences are mostly attributed to the rainfall intensity differences. The higher-intensity MCS rainfall tends to produce more surface runoff through infiltration excess flow and drives a deeper penetration of the rainwater into the soil. Over 70% of the top 10th percentile runoff is contributed by MCS rainfall, demonstrating its important contribution to local flooding. In contrast, lower-intensity non-MCS rainfall resides mostly in the top layer and contributes more to evapotranspiration through soil evaporation. Diurnal timing of rainfall has negligible effects on the flux partitioning for both MCS and non-MCS rainfall. Differences in soil moisture profiles for MCS and non-MCS rainfall and the resultant evapotranspiration suggest differences in their roles in soil moisture–precipitation feedbacks and ecohydrology.

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Evaluation of AMIP II Global Climate Model Simulations of the Land Surface Water Budget and Its Components over the GEWEX-CEOP Regions

Journal of Hydrometeorology ◽

10.1175/jhm579.1 ◽

2007 ◽

Vol 8 (3) ◽

pp. 304-326 ◽

Cited By ~ 2

Author(s):

P. Irannejad ◽

A. Henderson-Sellers

Keyword(s):

Surface Water ◽

Water Balance ◽

Land Surface ◽

Water Budget ◽

Global Climate Model ◽

Atmospheric Model ◽

Water Balance Components ◽

Land Surface Water ◽

Simulated Precipitation ◽

Basin Scale

Abstract The land surface water balance components simulated by 20 atmospheric global circulation models (AGCMs) participating in phase II of the Atmospheric Model Intercomparison Project (AMIP II) are analyzed globally and over seven Global Energy and Water Cycle Experiment Coordinated Enhanced Observing Period basins. In contrast to the conclusions from analysis of AMIP I, the results presented here suggest that the group average of available AGCMs does not outperform all individual AGCMs in simulating the surface water balance components. Analysis shows that the available reanalysis products are not appropriate for evaluation of AGCMs’ simulated land surface water components. The worst simulation of the surface water budget is in the Murray–Darling, the most arid basin, where all the reanalyses and seven of the AGCMs produce a negative surface water budget, with evaporation alone exceeding precipitation and soil moisture decreasing over the whole AMIP II period in this basin. The spatiotemporal correlation coefficients between observed and AGCM-simulated runoff are smaller than those for precipitation. In almost all basins (except for the two most arid basins), the spatiotemporal variations of the AGCMs’ simulated evaporation are more coherent and agree better with observations, compared to those of simulated precipitation. This suggests that differences among the AGCMs’ surface water budget predictions are not solely due to model-generated precipitation differences. Specifically, it is shown that different land surface parameterization schemes partition precipitation between evaporation and runoff differently and that this, in addition to the predicted differences in atmospheric forcings, is responsible for different predictions of basin-scale water budgets. The authors conclude that the selection of a land surface scheme for an atmospheric model has significant impacts on the predicted continental and basin-scale surface hydrology.

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HydroPy (v1.0): a new global hydrology model written in Python

Geoscientific Model Development ◽

10.5194/gmd-14-7795-2021 ◽

2021 ◽

Vol 14 (12) ◽

pp. 7795-7816

Author(s):

Tobias Stacke ◽

Stefan Hagemann

Keyword(s):

Surface Water ◽

Water Balance ◽

Land Surface ◽

Max Planck ◽

Water Balance Components ◽

Meteorological Model ◽

Land Surface Water ◽

Hydrology Model ◽

Flexible Infrastructure ◽

The Tropics

Abstract. Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components and their past evolution as well as potential future development under various scenarios. While GHMs have been part of the hydrologist's toolbox for several decades, the models are continuously being developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance, and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge; however, they can – at least to some extent – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similarly to MPI-HM and thus conclude the successful transition from MPI-HM to HydroPy.

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Simulating AOGCM Soil Moisture Using an Off-Line Thornthwaite Potential Evapotranspiration–Based Land Surface Scheme. Part I: Control Runs

Journal of Climate ◽

10.1175/2007jcli1675.1 ◽

2008 ◽

Vol 21 (13) ◽

pp. 3097-3117 ◽

Cited By ~ 3

Author(s):

Adam R. Cornwell ◽

L. D. Danny Harvey

Keyword(s):

Soil Moisture ◽

Land Surface ◽

General Circulation ◽

Potential Evapotranspiration ◽

General Circulation Models ◽

The United States ◽

Atmospheric Forcing ◽

Control Climate ◽

The Difference ◽

Parameter Values

Abstract Atmosphere–ocean general circulation models (AOGCMs) employ very different land surface schemes (LSSs) and, as a result, their predictions of land surface quantities are often difficult to compare. Some of the disagreement in quantities such as soil moisture is likely due to differences in the atmospheric component; however, previous intercomparison studies have determined that different LSSs can produce very different results even when supplied with identical atmospheric forcing. A simple off-line LSS is presented that can reproduce the soil moisture simulations of various AOGCMs, based on their modeled temperature and precipitation. The scheme makes use of the well-established Thornthwaite method for estimating potential evapotranspiration combined with a variation of the Manabe “bucket” model. The model can be tuned to reproduce the control climate soil moisture of an AOGCM by adjusting the ease with which runoff and evapotranspiration continue as the moisture level in the bucket goes down. This produces a set of parameter values that provides a good fit to each of several AOGCM control climates. In addition, the parameter values can be set to imitate the LSS from one AOGCM while the model is forced with atmospheric data from another, thus providing an estimate of the magnitude of variation caused by the differences in land surface parameterization and by differences in atmospheric forcing. In general, the authors find that differences in LSSs account for about half of the difference in soil moisture as simulated by different AOGCMs, and the differences in atmospheric forcing account for the other half of the difference. However, the LSS can be more important than differences in atmospheric forcing in some regions (such as the United States) and less important in others (such as East Africa).

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Verification and Intercomparison of Multimodel Simulated Land Surface Hydrological Datasets over the United States

Journal of Hydrometeorology ◽

10.1175/2011jhm1317.1 ◽

2011 ◽

Vol 12 (4) ◽

pp. 531-555 ◽

Cited By ~ 19

Author(s):

Yun Fan ◽

Huug M. van den Dool ◽

Wanru Wu

Keyword(s):

United States ◽

Soil Moisture ◽

Surface Water ◽

Water Balance ◽

Time Scales ◽

Land Surface ◽

The United States ◽

Surface Model ◽

Spatial And Temporal Variability ◽

Water Balance Components

Abstract Several land surface datasets, such as the observed Illinois soil moisture dataset; three retrospective offline run datasets from the Noah land surface model (LSM), Variable Infiltration Capacity (VIC) LSM, and Climate Prediction Center leaky bucket soil model; and three reanalysis datasets (North American Regional Reanalysis, NCEP/Department of Energy Global Reanalysis, and 40-yr ECMWF Re-Analysis), are used to study the spatial and temporal variability of soil moisture and its response to the major components of land surface hydrologic cycles: precipitation, evaporation, and runoff. Detailed analysis was performed on the evolution of the soil moisture vertical profile. Over Illinois, model simulations are compared to observations, but for the United States as a whole some impressions can be gained by comparing the multiple soil moisture–precipitation–evaporation–runoff datasets to one another. The magnitudes and partitioning of major land surface water balance components on seasonal–interannual time scales have been explored. It appears that evaporation has the most prominent annual cycle but its interannual variability is relatively small. For other water balance components, such as precipitation, runoff, and surface water storage change, the amplitudes of their annual cycles and interannual variations are comparable. This study indicates that all models have a certain capability to reproduce observed soil moisture variability on seasonal–interannual time scales, but offline runs are decidedly better than reanalyses (in terms of validation against observations) and more highly correlated to one another (in terms of intercomparison) in general. However, noticeable differences are also observed, such as the degree of simulated drought severity and the locations affected—this is due to the uncertainty in model physics, input forcing, and mode of running (interactive or offline), which continue to be major issues for land surface modeling.

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