A Global Intercomparison of Modeled and Observed Land–Atmosphere Coupling*

Abstract Land–atmosphere coupling strength or the degree to which land surface anomalies influence boundary layer development—and in extreme cases, rainfall—is arguably the single most fundamental criterion for evaluating hydrological model performance. The Global Land–Atmosphere Coupling Experiment (GLACE) showed that strength of coupling and its representation can affect a model’s ability to simulate climate predictability at the seasonal time scale. And yet, the lack of sufficient observations of coupling at appropriate temporal and spatial scales has made achieving “true” coupling in models an elusive goal. This study uses Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) soil moisture (SM), multisensor remote sensing (RS) evaporative fraction (EF), and Atmospheric Infrared Sounder (AIRS) lifting condensation level (LCL) to evaluate the realism of coupling in the Global Land Data Assimilation System (GLDAS) suite of land surface models (LSMs), Princeton Global Forcing Variable Infiltration Capacity model (PGF–VIC), seven global reanalyses, and the North American Regional Reanalysis (NARR) over a 5-yr period (2003–07). First, RS and modeled estimates of SM, EF, and LCL are intercompared. Then, emphasis is placed on quantifying RS and modeled differences in convective-season daily correlations between SM–LCL, SM–EF, and EF–LCL for global, regional, and conditional samples. RS is found to yield a substantially weaker state of coupling than model products. However, the rank order of basins by coupling strength calculated from RS and models do roughly agree. Using a mixture of satellite and modeled variables, a map of hybrid coupling strength was produced, which supports the findings of GLACE that transitional zones tend to have the strongest coupling.

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Development of a Distributed Hydrologic Model for a Region with Fragipan Soils to Study Impacts of Climate on Soil Moisture: A Case Study on the Obion River Watershed in West Tennessee

Geosciences ◽

10.3390/geosciences8100364 ◽

2018 ◽

Vol 8 (10) ◽

pp. 364

Author(s):

Seyed Ghaneeizad ◽

Athanasios Papanicolaou ◽

Benjamin Abban ◽

Christopher Wilson ◽

Christos Giannopoulos ◽

...

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Model Performance ◽

Hydrologic Model ◽

Infiltration Capacity ◽

River Watershed ◽

Saturation Zone ◽

Variable Infiltration Capacity Model ◽

Capacity Model ◽

Physically Based

Previous land surface modeling efforts to predict and understand water budgets in the U.S. Southeast for soil water management have struggled to characterize parts of the region due to an extensive presence of fragipan soils for which current calibration approaches are not adept at handling. This study presents a physically based approach for calibrating fragipan-dominated regions based on the “effective” soil moisture capacity concept, which accounts for the dynamic perched saturation zone effects created by the low hydraulic capacities of the fragipan layers. The approach is applied to the Variable Infiltration Capacity model to develop a hydrologic model of the Obion River Watershed (ORW), TN, which has extensive fragipan coverage. Model calibration was performed using observed streamflow data, as well as evapotranspiration and soil moisture data, to ensure correct partitioning of surface and subsurface fluxes. Estimated Nash-Sutcliffe coefficients for the various sub-drainage areas within ORW were all greater than 0.65, indicating good model performance. The model results suggest that ORW has a high responsivity and high resilience. Despite forecasted temperature increases, the simulation results suggest that water budget trends in the ORW are unlikely to change significantly in the near future up to 2050 due to sufficient precipitation amounts.

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Benchmarking of a Physically Based Hydrologic Model

Journal of Hydrometeorology ◽

10.1175/jhm-d-16-0284.1 ◽

2017 ◽

Vol 18 (8) ◽

pp. 2215-2225 ◽

Cited By ~ 31

Author(s):

Andrew J. Newman ◽

Naoki Mizukami ◽

Martyn P. Clark ◽

Andrew W. Wood ◽

Bart Nijssen ◽

...

Keyword(s):

Land Surface ◽

Model Performance ◽

Hydrologic Model ◽

Complex Model ◽

Model Parameters ◽

Infiltration Capacity ◽

Large Sample ◽

Variable Infiltration Capacity Model ◽

Capacity Model ◽

Physically Based

Abstract The concepts of model benchmarking, model agility, and large-sample hydrology are becoming more prevalent in hydrologic and land surface modeling. As modeling systems become more sophisticated, these concepts have the ability to help improve modeling capabilities and understanding. In this paper, their utility is demonstrated with an application of the physically based Variable Infiltration Capacity model (VIC). The authors implement VIC for a sample of 531 basins across the contiguous United States, incrementally increase model agility, and perform comparisons to a benchmark. The use of a large-sample set allows for statistically robust comparisons and subcategorization across hydroclimate conditions. Our benchmark is a calibrated, time-stepping, conceptual hydrologic model. This model is constrained by physical relationships such as the water balance, and it complements purely statistical benchmarks due to the increased physical realism and permits physically motivated benchmarking using metrics that relate one variable to another (e.g., runoff ratio). The authors find that increasing model agility along the parameter dimension, as measured by the number of model parameters available for calibration, does increase model performance for calibration and validation periods relative to less agile implementations. However, as agility increases, transferability decreases, even for a complex model such as VIC. The benchmark outperforms VIC in even the most agile case when evaluated across the entire basin set. However, VIC meets or exceeds benchmark performance in basins with high runoff ratios (greater than ~0.8), highlighting the ability of large-sample comparative hydrology to identify hydroclimatic performance variations.

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Comprehensive Evaluation of the Variable Infiltration Capacity (VIC) Model in the North American Land Data Assimilation System

Journal of Hydrometeorology ◽

10.1175/jhm-d-18-0139.1 ◽

2018 ◽

Vol 19 (11) ◽

pp. 1853-1879 ◽

Cited By ~ 7

Author(s):

Youlong Xia ◽

David M. Mocko ◽

Shugong Wang ◽

Ming Pan ◽

Sujay V. Kumar ◽

...

Keyword(s):

Land Surface ◽

Comprehensive Evaluation ◽

Model Performance ◽

Variable Infiltration Capacity ◽

Infiltration Capacity ◽

Vic Model ◽

The North ◽

Land Data Assimilation ◽

Land Data Assimilation System ◽

Data Assimilation System

Abstract Since the second phase of the North American Land Data Assimilation System (NLDAS-2) was operationally implemented at NOAA/NCEP as part of the production suite in August 2014, developing the next phase of NLDAS has been a key focus of the NCEP and NASA NLDAS teams. The Variable Infiltration Capacity (VIC) model is one of the four land surface models of the NLDAS system. The current operational NLDAS-2 uses version 4.0.3 (VIC403), the research NLDAS-2 used version 4.0.5 (VIC405), and the NASA Land Information System (LIS)-based NLDAS uses version 4.1.2.l (VIC412). The purpose of this study is to evaluate VIC403 and VIC412 and check if the latter version has better performance for the next phase of NLDAS. Toward this, a comprehensive evaluation was conducted, targeting multiple variables and using multiple metrics to assess the performance of different model versions. The evaluation results show large and significant improvements in VIC412 over the southeastern United States when compared with VIC403 and VIC405. In other regions, there are very limited improvements or even deterioration to some degree. This is partially due to 1) the sparseness of USGS streamflow observations for model parameter calibration and 2) a deterioration of VIC model performance in the Great Plains (GP) region after a model upgrade to a newer version. Overall, the model upgrade enhances model performance and skill scores for most parts of the continental United States; exceptions include the GP and western mountainous regions, as well as the daily soil moisture simulation skill, suggesting that VIC model development is on the right path. Further efforts are needed for scientific understanding of land surface physical processes in the GP, and a recalibration of VIC412 using reasonable reference datasets is recommended.

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Comparison of NLDAS-2 Simulated and NASMD Observed Daily Soil Moisture. Part I: Comparison and Analysis

Journal of Hydrometeorology ◽

10.1175/jhm-d-14-0096.1 ◽

2015 ◽

Vol 16 (5) ◽

pp. 1962-1980 ◽

Cited By ~ 48

Author(s):

Youlong Xia ◽

Michael B. Ek ◽

Yihua Wu ◽

Trent Ford ◽

Steven M. Quiring

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Soil Layer ◽

Infiltration Capacity ◽

Soil Layers ◽

Climate Conditions ◽

Soil Moisture Accounting ◽

The North ◽

West Texas ◽

Capacity Model

Abstract Soil moisture observations from seven observational networks (spanning portions of seven states) with different biome and climate conditions were used in this study to evaluate multimodel simulated soil moisture products. The four land surface models, including Noah, Mosaic, Sacramento soil moisture accounting (SAC), and the Variable Infiltration Capacity model (VIC), were run within phase 2 of the North American Land Data Assimilation System (NLDAS-2), with a ⅛° spatial resolution and hourly temporal resolution. Hundreds of sites in Alabama, Colorado, Michigan, Nebraska, Oklahoma, West Texas, and Utah were used to evaluate simulated soil moisture in the 0–10-, 10–40-, and 40–100-cm soil layers. Soil moisture was spatially averaged in each state to reduce noise. In general, the four models captured broad features (e.g., seasonal variation) of soil moisture variations in all three soil layers in seven states, except for the 10–40-cm soil layer in West Texas and the 40–100-cm soil layer in Alabama, where the anomaly correlations are weak. Overall, Mosaic, SAC, and the ensemble mean have the highest simulation skill and VIC has the lowest simulation skill. The results show that Noah and VIC are wetter than the observations while Mosaic and SAC are drier than the observations, mostly likely because of systematic errors in model evapotranspiration.

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Changes in the future summer Mediterranean climate: contribution of teleconnections and local factors

10.5194/esd-2018-85 ◽

2019 ◽

Cited By ~ 3

Author(s):

Monika J. Barcikowska ◽

Sarah B. Kapnick ◽

Lakshmi Krishnamurty ◽

Simone Russo ◽

Annalisa Cherchi ◽

...

Keyword(s):

Land Surface ◽

Mediterranean Climate ◽

Eastern Mediterranean ◽

Spatial Scales ◽

Geophysical Fluid Dynamics Laboratory ◽

Local Surface ◽

Central Mediterranean ◽

The Balkans ◽

The North ◽

The North Atlantic Oscillation

Abstract. The realistic simulation of the summer Mediterranean climate requires not only refined spatial scales, but also an adequate representation of land-atmosphere interactions and teleconnections. Addressing all of these issues remains a challenge for most of the CMIP3/CMIP5 generation models. In this study we analyze high-resolution (~0.5° lat x lon) RCP8.5 future projections of the Geophysical Fluid Dynamics Laboratory CM2.5 model with a new incorporated land model (LM3). The simulated regional future changes suggest pronounced warming and drying over most parts of the Mediterranean. However the changes are distinctively less radical when compared with the CMIP5 multimodel ensemble. Moreover, changes over the Southeast (off the coast area of the Balkans) and Central Europe indicate not only a very modest warming, compared to the CMIP5 projections, but also wetting tendencies. The difference of CM2.5 projections of future changes over previous-generation models highlights the importance of a) a correctly projected magnitude of changes of the North Atlantic Oscillation and its regional impacts, which have the capacity to partly offset the anthropogenic warming and drying over the western and central Mediterranean; b) a refined representation of land surface-atmospheric interactions, which are a governing factor for thermal- and hydro-climate over Central and Southeastern Europe. The CM2.5 projections also indicate a maximum of warming (Levant) and drying (Asia Minor) over the eastern Mediterranean. The changes derived in this region indicate a decreasing influence of atmospheric dynamics in maintaining the regional temperature and precipitation balance and instead an increasing influence of local surface temperature on the local surface atmospheric circulation.

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Assessment of WRF Land Surface Model Performance over West Africa

Advances in Meteorology ◽

10.1155/2020/6205308 ◽

2020 ◽

Vol 2020 ◽

pp. 1-30

Author(s):

Ifeanyi C. Achugbu ◽

Jimy Dudhia ◽

Ayorinde A. Olufayo ◽

Ifeoluwa A. Balogun ◽

Elijah A. Adefisan ◽

...

Keyword(s):

West Africa ◽

Land Surface ◽

Model Performance ◽

Wrf Model ◽

Land Surface Model ◽

Surface Model ◽

Reanalysis Dataset ◽

The North ◽

Temperature And Precipitation ◽

Moisture Advection

Simulations with four land surface models (LSMs) (i.e., Noah, Noah-MP, Noah-MP with ground water GW option, and CLM4) using the Weather Research and Forecasting (WRF) model at 12 km horizontal grid resolution were carried out as two sets for 3 months (December–February 2011/2012 and July–September 2012) over West Africa. The objective is to assess the performance of WRF LSMs in simulating meteorological parameters over West Africa. The model precipitation was assessed against TRMM while surface temperature was compared with the ERA-Interim reanalysis dataset. Results show that the LSMs performed differently for different variables in different land-surface conditions. Based on precipitation and temperature, Noah-MP GW is overall the best for all the variables and seasons in combination, while Noah came last. Specifically, Noah-MP GW performed best for JAS temperature and precipitation; CLM4 was the best in simulating DJF precipitation, while Noah was the best in simulating DJF temperature. Noah-MP GW has the wettest Sahel while Noah has the driest one. The strength of the Tropical Easterly Jet (TEJ) is strongest in Noah-MP GW and Noah-MP compared with that in CLM4 and Noah. The core of the African Easterly Jet (AEJ) lies around 12°N in Noah and 15°N for Noah-MP GW. Noah-MP GW and Noah-MP simulations have stronger influx of moisture advection from the southwesterly monsoonal wind than the CLM4 and Noah with Noah showing the least influx. Also, analysis of the evaporative fraction shows sharp gradient for Noah-MP GW and Noah-MP with wetter Sahel further to the north and further to the south for Noah. Noah-MP-GW has the highest amount of soil moisture, while the CLM4 has the least for both the JAS and DJF seasons. The CLM4 has the highest LH for both DJF and JAS seasons but however has the least SH for both DJF and JAS seasons. The principal difference between the LSMs is in the vegetation representation, description, and parameterization of the soil water column; hence, improvement is recommended in this regard.

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The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations

Geoscientific Model Development ◽

10.5194/gmd-10-1487-2017 ◽

2017 ◽

Vol 10 (4) ◽

pp. 1487-1520 ◽

Cited By ~ 215

Author(s):

David Walters ◽

Ian Boutle ◽

Malcolm Brooks ◽

Thomas Melvin ◽

Rachel Stratton ◽

...

Keyword(s):

Land Surface ◽

Weather Prediction ◽

Model Performance ◽

Land Surface Model ◽

Unified Model ◽

Surface Model ◽

Main Trunk ◽

Global Land ◽

Prediction Systems ◽

The Tropics

Abstract. We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

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Modelling the snow distribution at two high arctic sites at Svalbard, Norway, and at an alpine site in central Norway

Hydrology Research ◽

10.2166/nh.2004.0014 ◽

2004 ◽

Vol 35 (3) ◽

pp. 191-208 ◽

Cited By ~ 41

Author(s):

Oddbjørn Bruland ◽

Glen E. Liston ◽

Jorien Vonk ◽

Knut Sand ◽

Ånund Killingtveit

Keyword(s):

Snow Cover ◽

Frequency Distribution ◽

Land Surface ◽

Snow Depth ◽

Rank Order ◽

Model Performance ◽

The Arctic ◽

Major Influence ◽

Model Parameters ◽

Snow Distribution

In Arctic regions snow cover has a major influence on the environment both in a hydrological and ecological context. Due to strong winds and open terrain the snow is heavily redistributed and the snow depth is quite variable. This has a significant influence on the snow cover depletion and the duration of the melting season. In many ways these are important parameters in the climate change aspect. They influence the land surface albedo, the possibilities of greenhouse gas exchange and the length of the plant-growing season, the latter also being important for the arctic terrestrial fauna. The aim of this study is to test to what degree a numerical model is able to recreate an observed snow distribution in sites located in Svalbard and Norway. Snow depth frequency distribution, a snow depth rank order test and the location of snowdrifts and erosion areas were used as criteria for the model performance. SnowTran-3D is the model used in this study. In order to allow for occasions during the winter with milder climate and temperatures above freezing, a snow strengthening calculation was included in the model. The model result was compared to extensive observation datasets for each site and the sensitivity of the main model parameters to the model result was tested. For all three sites, the modelled snow depth frequency distribution was highly correlated to the observed distribution and the snowdrifts and erosion areas were located correspondingly by the model to those observed at the sites.

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