Improving the global modeling of soils in JULES and the Unified Model: Updating from UM/HWSD to SoilGrids soil properties and from the Brooks & Corey to the van Genuchten soil-hydraulics model

2021 ◽  
Author(s):  
Patrick C. McGuire ◽  
Pier Luigi Vidale ◽  
Martin J. Best ◽  
David H. Case ◽  
Imtiaz Dharssi ◽  
...  
Keyword(s):  
Soil Properties ◽  
Land Surface ◽  
Climate Model ◽  
Model Updating ◽  
Unified Model ◽  
Pedotransfer Functions ◽  
Hydraulic Parameters ◽  
Near Surface ◽  
Soil Database ◽  
Soil Hydraulic

<p>    We have updated the soil properties used in JULES (Joint UK Land Environment Simulator), which is the land-surface component of the UM (Unified Model, the UK Met Office’s climate model). JULES models the interaction of the land surface with the atmosphere, and simulates the energy, water, and carbon fluxes. JULES allows either: (i) the Brooks & Corey (BC) model for estimating soil hydraulic properties, or (ii) the van Genuchten (VG) model but using hydraulic parameters translated from the BC model. One advantage of the VG model over the BC model is the smoother dependence of water retention upon matric potential for nearly saturated soils. Herein, we report on our work towards fully implementing the VG model in JULES and in the UM, through the implementation and evaluation of several VG pedotransfer functions (PTFs) for estimating the soil hydraulic parameters used in the hydraulic functions.</p> <p>    We have tested three VG PTFs in global offline JULES runs (driven with WFDEI data over 1979-2012): the combination of Tóth et al. PTFs 17 & 20, the Weynants et al. PTF, and the Zhang & Schaap ROSETTA3 H1 PTF (modified for sandy soils). We also modernized the soil basic properties that are conventionally used for JULES and the UM, from the UM version of the Harmonized World Soil Database (HWSD) to the SoilGrids database.</p> <p>    Evaluation of JULES simulations shows (i) that the modified version of the Zhang & Schaap ROSETTA3 H1 PTF is the best VG option, and (ii) that it compares favorably with the BC control model (which uses the Cosby et al. PTF and the UM/HWSD soils), in terms of the surface energy balance and the mitigation of near-surface temperature biases over mid-latitude continental regions. This modified version of the Zhang & Schaap ROSETTA3 H1 PTF with SoilGrids soils is also currently being used in coupled land-atmosphere UM runs.</p>

Development of a China Dataset of Soil Hydraulic Parameters Using Pedotransfer Functions for Land Surface Modeling

2013 ◽  
Vol 14 (3) ◽  
pp. 869-887 ◽  
Author(s):  
Yongjiu Dai ◽  
Wei Shangguan ◽  
Qingyun Duan ◽  
Baoyuan Liu ◽  
Suhua Fu ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Land Surface ◽  
Soil Characteristics ◽  
Surface Modeling ◽  
Pedotransfer Functions ◽  
Water Retention Curve ◽  
Hydraulic Parameters ◽  
Land Surface Modeling ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

Abstract The objective of this study is to develop a dataset of the soil hydraulic parameters associated with two empirical soil functions (i.e., a water retention curve and hydraulic conductivity) using multiple pedotransfer functions (PTFs). The dataset is designed specifically for regional land surface modeling for China. The authors selected 5 PTFs to derive the parameters in the Clapp and Hornberger functions and the van Genuchten and Mualem functions and 10 PTFs for soil water contents at capillary pressures of 33 and 1500 kPa. The inputs into the PTFs include soil particle size distribution, bulk density, and soil organic matter. The dataset provides 12 estimated parameters and their associated statistical values. The dataset is available at a 30 × 30 arc second geographical spatial resolution and with seven vertical layers to the depth of 1.38 m. The dataset has several distinct advantages even though the accuracy is unknown for lack of in situ and regional measurements. First, this dataset utilizes the best available soil characteristics dataset for China. The Chinese soil characteristics dataset was derived by using the 1:1 000 000 Soil Map of China and 8595 representative soil profiles. Second, this dataset represents the first attempt to estimate soil hydraulic parameters using PTFs directly for continental China at a high spatial resolution. Therefore, this dataset should capture spatial heterogeneity better than existing estimates based on lookup tables according to soil texture classes. Third, the authors derived soil hydraulic parameters using multiple PTFs to allow flexibility for data users to use the soil hydraulic parameters most preferable to or suitable for their applications.

scholarly journals Evaluation and improvement of the default soil hydraulic parameters for the Noah Land Surface Model

Geoderma ◽  
2017 ◽  
Vol 285 ◽  
pp. 247-259 ◽  
Author(s):  
Andrea Sz. Kishné ◽  
Yohannes Tadesse Yimam ◽  
Cristine L.S. Morgan ◽  
Bright C. Dornblaser
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Hydraulic Parameters ◽  
Soil Hydraulic Parameters ◽  
Noah Land Surface Model ◽  
Soil Hydraulic

Evaluating the role of soil physical properties on simulated land-atmosphere interactions over South Africa using coupled atmosphere-hydrological modeling

2021 ◽  
Author(s):  
Zhenyu Zhang ◽  
Patrick Laux ◽  
Joël Arnault ◽  
Jianhui Wei ◽  
Jussi Baade ◽  
...  
Keyword(s):  
South Africa ◽  
Physical Properties ◽  
Land Degradation ◽  
Land Surface ◽  
Soil Physical Properties ◽  
Near Surface ◽  
Soil Database ◽  
Global Soil ◽  
The Impact

<p>Land degradation with its direct impact on vegetation, surface soil layers and land surface albedo, has great relevance with the climate system. Assessing the climatic and ecological effects induced by land degradation requires a precise understanding of the interaction between the land surface and atmosphere. In coupled land-atmosphere modeling, the low boundary conditions impact the thermal and hydraulic exchanges at the land surface, therefore regulates the overlying atmosphere by land-atmosphere feedback processes. However, those land-atmosphere interactions are not convincingly represented in coupled land-atmosphere modeling applications. It is partly due to an approximate representation of hydrological processes in land surface modeling. Another source of uncertainties relates to the generalization of soil physical properties in the modeling system. This study focuses on the role of the prescribed physical properties of soil in high-resolution land surface-atmosphere simulations over South Africa. The model used here is the hydrologically-enhanced Weather Research and Forecasting (WRF-Hydro) model. Four commonly used global soil datasets obtained from UN Food and Agriculture Organization (FAO) soil database, Harmonized World Soil Database (HWSD), Global Soil Dataset for Earth System Model (GSDE), and SoilGrids dataset, are incorporated within the WRF-Hydro experiments for investigating the impact of soil information on land-atmosphere interactions. The simulation results of near-surface temperature, skin temperature, and surface energy fluxes are presented and compared to observational-based reference dataset. It is found that simulated soil moisture is largely influenced by soil texture features, which affects its feedback to the atmosphere.</p>

scholarly journals Complexity of Snow Schemes in a Climate Model and Its Impact on Surface Energy and Hydrology

2012 ◽  
Vol 13 (2) ◽  
pp. 521-538 ◽  
Author(s):  
Emanuel Dutra ◽  
Pedro Viterbo ◽  
Pedro M. A. Miranda ◽  
Gianpaolo Balsamo
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Climate Models ◽  
Climate Model ◽  
Single Layer ◽  
Atmospheric Temperature ◽  
Soil Freezing ◽  
Near Surface ◽  
Northern Latitudes ◽  
Tightly Coupled

Abstract Three different complexity snow schemes implemented in the ECMWF land surface scheme Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) are evaluated within the EC-EARTH climate model. The snow schemes are (i) the original HTESSEL single-bulk-layer snow scheme, (ii) a new snow scheme in operations at ECMWF since September 2009, and (iii) a multilayer version of the previous. In offline site simulations, the multilayer scheme outperforms the single-layer schemes in deep snowpack conditions through its ability to simulate sporadic melting events thanks to the lower thermal inertial of the uppermost layer. Coupled atmosphere–land/snow simulations performed by the EC-EARTH climate model are validated against remote sensed snow cover and surface albedo. The original snow scheme has a systematic early melting linked to an underestimation of surface albedo during spring that was partially reduced with the new snow schemes. A key process to improve the realism of the near-surface atmospheric temperature and at the same time the soil freezing is the thermal insulation of the snowpack (tightly coupled with the accuracy of snow mass and density simulations). The multilayer snow scheme outperforms the single-layer schemes in open deep snowpack (such as prairies or tundra in northern latitudes) and is instead comparable in shallow snowpack conditions. However, the representation of orography in current climate models implies limitations for accurately simulating the snowpack, particularly over complex terrain regions such as the Rockies and the Himalayas.

scholarly journals Flux Replacement as a Method to Diagnose Coupled Land–Atmosphere Model Feedback

2004 ◽  
Vol 5 (6) ◽  
pp. 1034-1048 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
Mei Zhao
Keyword(s):  
Surface State ◽  
Land Surface ◽  
Climate Model ◽  
Initial Conditions ◽  
Systematic Errors ◽  
Surface Fluxes ◽  
Boreal Summer ◽  
Near Surface ◽  
Soil Wetness ◽  
The Impact

Abstract The potential role of the land surface state in improving predictions of seasonal climate is investigated with a coupled land–atmosphere climate model. Climate simulations for 18 boreal-summer seasons (1982–99) have been conducted with specified observed sea surface temperature (SST). The impact on prediction skill of the initial land surface state (interannually varying versus climatological soil wetness) and the effect of errors in downward surface fluxes (precipitation and longwave/shortwave radiation) over land are investigated with a number of parallel experiments. Flux errors are addressed by replacing the downward fluxes with observed values in various combinations to ascertain the separate roles of water and energy flux errors on land surface state variables, upward water and energy fluxes from the land surface, and the important climate variables of precipitation and near-surface air temperature. Large systematic errors are found in the model, which are only mildly alleviated by the specification of realistic initial soil wetness. The model shows little skill in simulating seasonal anomalies of precipitation, but it does have skill in simulating temperature variations. Replacement of the downward surface fluxes has a clear positive impact on systematic errors, suggesting that the land–atmosphere feedback is helping to exacerbate climate drift. Improvement in the simulation of year-to-year variations in climate is even more evident. With flux replacement, the climate model simulates temperature anomalies with considerable skill over nearly all land areas, and a large fraction of the globe shows significant skill in the simulation of precipitation anomalies. This suggests that the land surface can communicate climate anomalies back to the atmosphere, given proper meteorological forcing. Flux substitution appears to have the largest benefit to improving precipitation skill over the Northern Hemisphere midlatitudes, whereas use of realistic land surface initial conditions improves skill to significant levels over regions of the Southern Hemisphere. Correlations between sets of integrations show that the model has a robust and systematic global response to SST anomalies.

Impact of Soil Moisture on Winter 2-m Temperature Forecast in Northern China

2020 ◽  
Author(s):  
Ji-Qin Zhong ◽  
Bing Lu ◽  
Wei Wang ◽  
Cheng-Cheng Huang ◽  
Yang Yang
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Northern China ◽  
Heat Fluxes ◽  
Specific Humidity ◽  
Hydraulic Parameters ◽  
Temperature Range ◽  
Temperature Forecast ◽  
Soil Hydraulic ◽  
Soil Moisture Initialization

<p> The causes of the underestimated diurnal 2-m temperature range and the overestimated 2-m specific humidity in Northern China’s winter in the Rapid-refresh Multi-scale Analysis and Prediction System - Short Term (RMAPS-ST) system are investigated. Three simulations based on RMAPS-ST are conducted from Nov. 1st, 2016 to Feb. 28th, 2017. Further analyses show that the partitioning of surface upward sensible heat fluxes and downward ground heat fluxes might be the main contributing factor in 2-m temperature forecast biases. In this study, two simulations are conducted to examine the effect of soil moisture initialization and soil hydraulic property on the 2-m temperature and 2-m specific humidity forecast biases. Firstly, the High-Resolution Land Data Assimilation System (HRLDAS) is used to provide an alternative soil moisture initialization, and the result shows that the drier soil moisture leads to noticeable change in energy partition at the land surface, which in turn results in improved prediction of the diurnal 2-m temperature range, although it also enlarges the 2-m specific humidity bias in some parts of the domain. Secondly, a soil texture dataset developed by Beijing Normal University (BNU) and a revised hydraulic parameters are applied to provide a more detailed description of soil properties, which could further improve the 2-m specific humidity biases. In summary, the combination of using optimized soil moisture initialization, updated soil map and revised soil hydraulic parameters can help improve the 2-m temperature and 2-m specific humidity prediction in RMAPS-ST.</p>

A general BEST method predicting soil hydraulic parameters for any type of water retention and hydraulic conductivity curves

2020 ◽  
Author(s):  
Jesús Fernández-Gálvez ◽  
Joseph Pollacco ◽  
Laurent Lassabatere ◽  
Rafael Angulo-Jaramillo ◽  
Sam Carrick
Keyword(s):  
Hydraulic Conductivity ◽  
Water Retention ◽  
Pedotransfer Functions ◽  
Distribution Data ◽  
Hydraulic Parameters ◽  
Pore Size Distributions ◽  
Soil Transfer ◽  
Soil Hydraulic Parameters ◽  
Transfer Parameters ◽  
Soil Hydraulic

<p>Soil hydraulic characterization is crucial to describe the retention and transport of water in soil, but current methodologies limit its spatial applicability. This work presents a cost-effective general Beerkan Estimation of Soil Transfer parameters (BEST) methodology using single ring infiltration experiments to derive soil hydraulic parameters for any type of unimodal water retention and hydraulic conductivity functions. The proposed method relies on the BEST approach. The novelty lies in the use of Kosugi hydraulic parameters without need for textural information. Kosugi functions were chosen because they are based on physical principles (log-normal distribution for pore size distributions). A link between the Kosugi parameters (i.e., relationship between <em>σ</em> and <em>h</em><sub>kg</sub>) was introduced to reduce the number of parameters estimated and to avoid the need for information on the soil texture. This simplifies the procedures and avoids sources of errors related to the use of pedotransfer functions as for the previous BEST methods. Lastly, the method uses a quasi-exact formulation that is valid for all times, instead of the approximate expansions previously used, avoiding related inaccuracy and allowing the use of any infiltration data encompassing or not both transient and steady states. The new BEST methods were tested against numerically generated data for several contrasting synthetic soils, and the results show that these methods provide consistent hydraulic functions close to the target functions. The new BEST method is accurate and can use any type of water retention and hydraulic conductivity functions (Fernández-Gálvez et al., 2019).</p><p> </p><p> </p><p><strong>Reference</strong></p><p>Fernández-Gálvez, J., Pollacco, J.A.P., Lassabatere, L., Angulo-Jaramillo, R., Carrick, S., 2019. A general Beerkan Estimation of Soil Transfer parameters method predicting hydraulic parameters of any unimodal water retention and hydraulic conductivity curves: Application to the Kosugi soil hydraulic model without using particle size distribution data. Adv. Water Resour. 129, 118–130. https://doi.org/10.1016/j.advwatres.2019.05.005</p>

euptfv2: updated hydraulic pedotransfer functions for Europe

2021 ◽  
Author(s):  
Brigitta Szabó ◽  
Melanie Weynants ◽  
Tobias Weber
Keyword(s):  
Hydraulic Conductivity ◽  
Soil Properties ◽  
Water Content ◽  
Hydraulic Properties ◽  
Field Capacity ◽  
Pedotransfer Functions ◽  
Predictor Variables ◽  
Soil Hydraulic Properties ◽  
Matric Potential ◽  
Soil Hydraulic

<p>We present improved European hydraulic pedotransfer functions (PTFs) which now use the machine learning algorithm random forest and include prediction uncertainties. The new PTFs (euptfv2) are an update of the previously published euptfv1 (Tóth et al., 2015). With the derived hydraulic PTFs soil hydraulic properties and van Genuchten-Mualem model parameters can be predicted from easily available soil properties. The updated PTFs perform significantly better than euptfv1 and are applicable for 32 predictor variables combinations. The uncertainties reflect uncertainties from the considered input data, predictors and the applied algorithm. The euptfv2 includes transfer functions to compute soil water content at saturation (0 cm matric potential head), field capacity (both -100 and -330 cm matric potential head) and wilting point (-15,000 cm matric potential head), plant available water content computed with field capacity at -100 and -330 cm matric potential head, saturated hydraulic conductivity, and Mualem-van Genuchten parameters of the moisture retention and hydraulic conductivity curves. The influence of predictor variables on predicted soil hydraulic properties is explored and suggestions to best predictor variables given.</p><p>The algorithms have been implemented in a web interface (https://ptfinterface.rissac.hu) and an R package (https://doi.org/10.5281/ZENODO.3759442) to facilitate the use of the PTFs, where the PTFs’ selection is automated based on soil properties available for the predictions and required soil hydraulic property.</p><p>The new PTFs will be applied to derive soil hydraulic properties for field- and catchment- scale hydrological modelling in European case studies of the OPTAIN project (https://www.optain.eu/). Functional evaluation of the PTFs is performed under the iAqueduct research project.</p><p> </p><p>This research has been supported by the Hungarian National Research, Development and Innovation Office (grant no. KH124765), the János Bolyai Research Scholarship of the Hungarian Academy of Sciences (grant no. BO/00088/18/4), and the German Research Foundation (grant no. SFB 1253/12017). OPTAIN is funded by the European Union’s Horizon 2020 Program for research and innovation under Grant Agreement No. 862756.</p>

Impact of Soil Moisture on Winter 2-m Temperature Forecasts in Northern China

2020 ◽  
Vol 21 (4) ◽  
pp. 597-614 ◽  
Author(s):  
Ji-Qin Zhong ◽  
Bing Lu ◽  
Wei Wang ◽  
Cheng-Cheng Huang ◽  
Yang Yang
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Northern China ◽  
Heat Fluxes ◽  
Specific Humidity ◽  
Hydraulic Parameters ◽  
Temperature Range ◽  
Temperature Forecast ◽  
Soil Hydraulic ◽  
Soil Moisture Initialization

AbstractIn this study, the causes of the underestimated diurnal 2-m temperature range and the overestimated 2-m specific humidity in the winter of northern China in the Rapid-Refresh Multiscale Analysis and Prediction System–Short Term (RMAPS-ST) are investigated. Three simulations based on RMAPS-ST are conducted from 1 November 2016 to 28 February 2017. Further analyses show that the partitioning of surface upward sensible heat fluxes and downward ground heat fluxes might be the main contributing factor to the 2-m temperature forecast bias. In this study, two simulations are conducted to examine the effect of soil moisture initialization and soil hydraulic property on the 2-m temperature and 2-m specific humidity forecasts. First, the High-Resolution Land Data Assimilation System (HRLDAS) is used to provide an alternative soil moisture initialization. The results show that the drier soil moisture could lead to noticeable change in energy partitioning at the land surface, which in turn results in improved prediction of the diurnal 2-m temperature range, although it also enlarges the 2-m specific humidity bias in some parts of the domain. Second, a soil texture dataset developed by Beijing Normal University and the revised hydraulic parameters are applied to provide a more detailed description of soil properties, which could further improve the 2-m specific humidity bias. In summary, the combination of using optimized soil moisture initialization, an updated soil map, and revised soil hydraulic parameters can help improve the 2-m temperature and 2-m specific humidity prediction in RMAPS-ST.

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