scholarly journals Reconciling Land–Ocean Moisture Transport Variability in Reanalyses with P − ET in Observationally Driven Land Surface Models

2016 ◽  
Vol 29 (23) ◽  
pp. 8625-8646 ◽  
Author(s):  
Franklin R. Robertson ◽  
Michael G. Bosilovich ◽  
Jason B. Roberts
Keyword(s):  
Land Surface ◽  
Moisture Transport ◽  
Global Climate ◽  
Principal Component ◽  
Rain Gauge ◽  
Atmospheric Moisture ◽  
Land Surface Models ◽  
Dynamic Component ◽  
Near Surface ◽  
Surface Models

Abstract Vertically integrated atmospheric moisture transport from ocean to land [vertically integrated atmospheric moisture flux convergence (VMFC)] is a dynamic component of the global climate system but remains problematic in atmospheric reanalyses, with current estimates having significant multidecadal global trends differing even in sign. Continual evolution of the global observing system, particularly stepwise improvements in satellite observations, has introduced discrete changes in the ability of data assimilation to correct systematic model biases, manifesting as nonphysical variability. Land surface models (LSMs) forced with observed precipitation P and near-surface meteorology and radiation provide estimates of evapotranspiration (ET). Since variability of atmospheric moisture storage is small on interannual and longer time scales, VMFC = P − ET is a good approximation and LSMs can provide an alternative estimate. However, heterogeneous density of rain gauge coverage, especially the sparse coverage over tropical continents, remains a serious concern. Rotated principal component analysis (RPCA) with prefiltering of VMFC to isolate the artificial variability is used to investigate artifacts in five reanalysis systems. This procedure, although ad hoc, enables useful VMFC corrections over global land. The P − ET estimates from seven different LSMs are evaluated and subsequently used to confirm the efficacy of the RPCA-based adjustments. Global VMFC trends over the period 1979–2012 ranging from 0.07 to −0.03 mm day−1 decade−1 are reduced by the adjustments to 0.016 mm day−1 decade−1, much closer to the LSM P − ET estimate (0.007 mm day−1 decade−1). Neither is significant at the 90% level. ENSO-related modulation of VMFC and P − ET remains the largest global interannual signal, with mean LSM and adjusted reanalysis time series correlating at 0.86.

scholarly journals Evaluation of air–soil temperature relationships simulated by land surface models during winter across the permafrost region

2016 ◽  
Vol 10 (4) ◽  
pp. 1721-1737 ◽  
Author(s):  
Wenli Wang ◽  
Annette Rinke ◽  
John C. Moore ◽  
Duoying Ji ◽  
Xuefeng Cui ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Land Surface ◽  
Snow Depth ◽  
Soil Depth ◽  
Permafrost Region ◽  
Simple Relationship ◽  
Land Surface Models ◽  
Cross Model ◽  
Near Surface ◽  
Surface Models

Abstract. A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (ΔT; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C °C−1), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km2). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.

scholarly journals Inter-comparison of two land-surface models applied at different scales and their feedbacks while coupled with a regional climate model

2012 ◽  
Vol 16 (3) ◽  
pp. 1017-1031 ◽  
Author(s):  
F. Zabel ◽  
W. Mauser ◽  
T. Marke ◽  
A. Pfeiffer ◽  
G. Zängl ◽  
...  
Keyword(s):  
Land Use ◽  
Land Surface ◽  
Regional Climate ◽  
Moderate Increase ◽  
Net Radiation ◽  
Land Surface Models ◽  
Near Surface ◽  
Temporal Behaviour ◽  
Surface Models ◽  
The Alps

Abstract. Downstream models are often used in order to study regional impacts of climate and climate change on the land surface. For this purpose, they are usually driven offline (i.e., 1-way) with results from regional climate models (RCMs). However, the offline approach does not allow for feedbacks between these models. Thereby, the land surface of the downstream model is usually completely different to the land surface which is used within the RCM. Thus, this study aims at investigating the inconsistencies that arise when driving a downstream model offline instead of interactively coupled with the RCM, due to different feedbacks from the use of different land surface models (LSM). Therefore, two physically based LSMs which developed from different disciplinary backgrounds are compared in our study: while the NOAH-LSM was developed for the use within RCMs, PROMET was originally developed to answer hydrological questions on the local to regional scale. Thereby, the models use different physical formulations on different spatial scales and different parameterizations of the same land surface processes that lead to inconsistencies when driving PROMET offline with RCM output. Processes that contribute to these inconsistencies are, as described in this study, net radiation due to land use related albedo and emissivity differences, the redistribution of this net radiation over sensible and latent heat, for example, due to different assumptions about land use impermeability or soil hydraulic reasons caused by different plant and soil parameterizations. As a result, simulated evapotranspiration, e.g., shows considerable differences of max. 280 mm yr−1. For a full interactive coupling (i.e., 2-way) between PROMET and the atmospheric part of the RCM, PROMET returns the land surface energy fluxes to the RCM and, thus, provides the lower boundary conditions for the RCM subsequently. Accordingly, the RCM responses to the replacement of the LSM with overall increased annual mean near surface air temperature (+1 K) and less annual precipitation (−56 mm) with different spatial and temporal behaviour. Finally, feedbacks can set up positive and negative effects on simulated evapotranspiration, resulting in a decrease of evapotranspiration South of the Alps a moderate increase North of the Alps. The inconsistencies are quantified and account for up to 30% from July to Semptember when focused to an area around Milan, Italy.

scholarly journals Surface response to rain events throughout the West African monsoon

2013 ◽  
Vol 13 (7) ◽  
pp. 18581-18620 ◽  
Author(s):  
F. Lohou ◽  
L. Kergoat ◽  
F. Guichard ◽  
A. Boone ◽  
B. Cappelaere ◽  
...  
Keyword(s):  
Land Surface ◽  
Recovery Period ◽  
Bare Soil ◽  
Rain Event ◽  
Land Surface Models ◽  
Evaporative Fraction ◽  
Near Surface ◽  
African Monsoon ◽  
Surface Response ◽  
Surface Models

Abstract. This study analyses the response of the continental surface to a rain event, taking advantage of the long-term near-surface measurements over different vegetation covers at different latitudes, acquired during the African Monsoon Multidisciplinary Analysis (AMMA) experiment. The simulated surface response by nine land surface models involved in AMMA Land Model Intercomparison Project (ALMIP), is compared to the observations. The surface response, described via the evaporative fraction, evolves in two steps: the immediate surface response and the surface recovery. The immediate surface response corresponds to an increase in the evaporative fraction occurring immediately after the rain. For all the experimental sites, the immediate surface response is strongest when the surface is relatively dry. From the simulation point of view, this relationship is highly model and latitude dependent. The recovery period, characterized by a decrease of the evaporative fraction during several days after the rain, follows an exponential relationship whose rate is vegetation dependent: from 1 day over bare soil to 70 days over the forest. Land surface models correctly simulate the decrease of EF over vegetation covers whereas a slower and more variable EF decrease is simulated over bare soil.

scholarly journals Identification of catchment functional units by time series of thermal remote sensing images

2014 ◽  
Vol 18 (12) ◽  
pp. 5345-5359 ◽  
Author(s):  
B. Müller ◽  
M. Bernhardt ◽  
K. Schulz
Keyword(s):  
Remote Sensing ◽  
Principal Component Analysis ◽  
Time Series ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Principal Component ◽  
Component Analysis ◽  
Land Surface Models ◽  
Surface Models ◽  
Functional Units

Abstract. The identification of catchment functional behavior with regards to water and energy balance is an important step during the parameterization of land surface models. An approach based on time series of thermal infrared (TIR) data from remote sensing is developed and investigated to identify land surface functioning as is represented in the temporal dynamics of land surface temperature (LST). For the mesoscale Attert catchment in midwestern Luxembourg, a time series of 28 TIR images from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) was extracted and analyzed, applying a novel process chain. First, the application of mathematical–statistical pattern analysis techniques demonstrated a strong degree of pattern persistency in the data. Dominant LST patterns over a period of 12 years were then extracted by a principal component analysis. Component values of the two most dominant components could be related for each land surface pixel to land use data and geology, respectively. The application of a data condensation technique ("binary words") extracting distinct differences in the LST dynamics allowed the separation into landscape units that show similar behavior under radiation-driven conditions. It is further outlined that both information component values from principal component analysis (PCA), as well as the functional units from the binary words classification, will highly improve the conceptualization and parameterization of land surface models and the planning of observational networks within a catchment.

scholarly journals Lower boundary conditions in land surface models – effects on the permafrost and the carbon pools: a case study with CLM4.5

2020 ◽  
Vol 13 (3) ◽  
pp. 1663-1683 ◽  
Author(s):  
Ignacio Hermoso de Mendoza ◽  
Hugo Beltrami ◽  
Andrew H. MacDougall ◽  
Jean-Claude Mareschal
Keyword(s):  
Heat Flux ◽  
Soil Carbon ◽  
Land Surface ◽  
Lower Boundary ◽  
Surface Model ◽  
Seasonal Temperature ◽  
Land Surface Models ◽  
Near Surface ◽  
Recent Climate ◽  
Surface Models

Abstract. Earth system models (ESMs) use bottom boundaries for their land surface model (LSM) components which are shallower than the depth reached by surface temperature changes in the centennial timescale associated with recent climate change. Shallow bottom boundaries reflect energy to the surface, which along with the lack of geothermal heat flux in current land surface models, alter the surface energy balance and therefore affect some feedback processes between the ground surface and the atmosphere, such as permafrost and soil carbon stability. To evaluate these impacts, we modified the subsurface model in the Community Land Model version 4.5 (CLM4.5) by setting a non-zero crustal heat flux bottom boundary condition uniformly across the model and by increasing the depth of the lower boundary from 42.1 to 342.1 m. The modified and original land models were run during the period 1901–2005 under the historical forcing and between 2005 and 2300 under forcings for two future scenarios of moderate (Representative Concentration Pathway 4.5; RCP4.5) and high (RCP8.5) emissions. Increasing the thickness of the subsurface by 300 m increases the heat stored in the subsurface by 72 ZJ (1 ZJ = 1021 J) by the year 2300 for the RCP4.5 scenario and 201 ZJ for the RCP8.5 scenario (respective increases of 260 % and 217 % relative to the shallow model), reduces the loss of near-surface permafrost area in the Northern Hemisphere between 1901 and 2300 by 1.6 %–1.9 %, reduces the loss of intermediate-depth permafrost area (above 42.1 m depth) by a factor of 3–5.5 and reduces the loss of soil carbon by 1.6 %–3.6 %. Each increase of 20 mW m−2 of the crustal heat flux increases the temperature at 3.8 m (the soil–bedrock interface) by 0.04±0.01 K. This decreases near-surface permafrost area slightly (0.3 %–0.8 %) and produces local differences in initial stable size of the soil carbon pool across the permafrost region, which reduces the loss of soil carbon across the region by as much as 1.1 %–5.6 % for the two scenarios. Reducing subsurface thickness from 42.1 to 3.8 m, used by many LSMs, produces a larger effect than increasing it to 342.1 m, because 3.8 m is not enough to damp the annual signal and the subsurface closely follows the air temperature. We determine the optimal subsurface thickness to be 100 m for a 100-year simulation and 200 m for a simulation of 400 years. We recommend short-term simulations to use a subsurface of at least 40 m, to avoid the perturbation of seasonal temperature propagation.

scholarly journals Lower boundary conditions in Land Surface Models. Effects on the permafrost and the carbon pools

2018 ◽  
Author(s):  
Ignacio Hermoso de Mendoza ◽  
Hugo Beltrami ◽  
Andrew H. MacDougall ◽  
Jean-Claude Mareschal
Keyword(s):  
Heat Flux ◽  
Soil Carbon ◽  
Land Surface ◽  
Lower Boundary ◽  
Surface Model ◽  
Land Surface Models ◽  
Near Surface ◽  
Recent Climate ◽  
Surface Models ◽  
Rcp 8.5

Abstract. Earth System Models (ESMs) use bottom boundaries for their land surface model components which are shallower than the depth reached by surface temperature changes in the centennial time scale associated with recent climate change. Shallow bottom boundaries reflect energy to the surface, which along with the lack of geothermal heat flux in current land surface models, alter the surface energy balance and therefore affect some feedback processes between the ground surface and the atmosphere, such as permafrost and soil carbon stability. To evaluate these impacts, we modified the subsurface model in the Community Land Model version 4.5 (CLM4.5) by setting a non-zero crustal heat flux bottom boundary condition and by increasing the depth of the lower boundary by 300 m. The modified and original land models were run during the period 1901–2005 under the historical forcing and between 2005–2300 under two future scenarios of moderate (RCP 4.5) and high (RCP 8.5) emissions. Increasing the thickness of the subsurface by 300 m increases the heat stored in the subsurface by 72 ZJ (1 ZJ = 1021 J) by year 2300 for the RCP 4.5 scenario and 201 ZJ for the RCP 8.5 scenario (respective increases of 260 % and 217 % relative to the shallow model), reduces the loss of near-surface permafrost between 1901 and 2300 by 1.6 %–1.9 %, and reduces the loss of soil carbon by 1.6 %–3.6 %. Each increase of 0.02 W m−2 of the crustal heat flux increases the temperature at the soil-bedrock frontier by 0.4 ± 0.01 K, which decreases near-surface permafrost area slightly (0.3–0.8 %), but reduces the loss of soil carbon by as much as 1.1 %–5.6 % for the two scenarios.

scholarly journals A Conjunctive Surface–Subsurface Flow Representation for Mesoscale Land Surface Models

2013 ◽  
Vol 14 (5) ◽  
pp. 1421-1442 ◽  
Author(s):  
Hyun Il Choi ◽  
Xin-Zhong Liang ◽  
Praveen Kumar
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Moisture Transport ◽  
Overland Flow ◽  
Spatial Scales ◽  
Subsurface Flow ◽  
Land Surface Models ◽  
Local Soil ◽  
Common Land Model ◽  
Surface Models

Abstract Most current land surface models used in regional weather and climate studies capture soil-moisture transport in only the vertical direction and are therefore unable to capture the spatial variability of soil moisture and its lateral transport. They also implement simplistic surface runoff estimation from local soil water budget and ignore the role of surface flow depth on the infiltration rate, which may result in significant errors in the terrestrial hydrologic cycle. To address these issues, this study develops and describes a conjunctive surface–subsurface flow (CSSF) model that comprises a 1D diffusion wave model for surface (overland) flow fully interacted with a 3D volume-averaged soil-moisture transport model for subsurface flow. The proposed conjunctive flow model is targeted for mesoscale climate application at relatively large spatial scales and coarse computational grids as compared to the traditional coupled surface–subsurface flow scheme in a typical basin. The CSSF module is substituted for the existing 1D scheme in the common land model (CoLM) and the performance of this hydrologically enhanced version of the CoLM (CoLM+CSSF) is evaluated using a set of offline simulations for catchment-scale basins around the Ohio Valley region. The CoLM+CSSF simulations are explicitly implemented at the same resolution of the 30-km grids as the target regional climate models to avoid downscaling and upscaling exchanges between atmospheric forcings and land responses. The results show that the interaction between surface and subsurface flow significantly improves the stream discharge prediction crucial to the terrestrial water and energy budget.

scholarly journals Identification of catchment functional units by time series of thermal remote sensing images

2014 ◽  
Vol 11 (6) ◽  
pp. 7019-7052 ◽  
Author(s):  
B. Müller ◽  
M. Bernhardt ◽  
K. Schulz
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Land Surface ◽  
Temporal Dynamics ◽  
Principal Component ◽  
Land Surface Models ◽  
Principal Component Analysis Component ◽  
Functional Behavior ◽  
Surface Models ◽  
Functional Units

Abstract. The identification of catchment functional behavior with regard to water and energy balance is an important step during the parameterization of land surface models. An approach based on time series of thermal infrared (TIR) data from remote sensing is developed and investigated to identify land surface functioning as is represented in the temporal dynamics of land surface temperature (LST). For the meso-scale Attert catchment in midwestern Luxembourg, a time series of 28 TIR images from ASTER was extracted and analyzed. The application mathematical-statistical pattern analysis techniques demonstrated a strong degree of pattern persistency in the data. Dominant LST patterns over a period of 12 years were extracted by a principal component analysis. Component values of the 2 most dominant components could be related for each land surface pixel to vegetation/land use data, and geology, respectively. A classification of the landscape by introducing "binary word", representing distinct differences in LST dynamics, allowed the separation into functional units under radiation driven conditions. It is further outlined that both information, component values from PCA as well as the functional units from "binary words" classification, will highly improve the conceptualization and parameterization of land surface models and the planning of observational networks within a catchment.

scholarly journals Emulation of high-resolution land surface models using sparse Gaussian processes with application to JULES

2021 ◽  
Author(s):  
Evan Baker ◽  
Anna Harper ◽  
Daniel Williamson ◽  
Peter Challenor
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Global Climate ◽  
Computational Cost ◽  
Land Surface Model ◽  
Parameter Tuning ◽  
Surface Model ◽  
Climate Projections ◽  
Land Surface Models ◽  
Surface Models

Abstract. Land surface models are typically integrated into global climate projections, but as their spatial resolution increases the prospect of using them to aid in local policy decisions becomes more appealing. If these complex models are to be used to make local decisions, then a full quantification of uncertainty is necessary, but the computational cost of running just one simulation at high resolution can hinder proper analysis. Statistical emulation is an increasingly common technique for developing fast approximate models in a way that maintains accuracy but also provides comprehensive uncertainty bounds for the approximation. In this work, we develop a statistical emulation framework for land surface models which acknowledges the forcing data fed into the model, providing predictions at a high resolution. We use The Joint UK Land Environment Simulator (JULES) as a case study for this strategy, and perform initial sensitivity analysis and parameter tuning to showcase its capabilities. JULES is perhaps one of the most complex land surface models, and so our success here suggests incredible gains can be made for all types of land surface model.

Evaluation of the new irrigation implementation in CTSM

2021 ◽  
Author(s):  
Yi Yao ◽  
Sean Swenson ◽  
David Lawrence ◽  
Danica Lombardozzi ◽  
Inne Vanderkelen ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Land Surface Models ◽  
Near Surface ◽  
Surface Energy Fluxes ◽  
Systems Model ◽  
Surface Models ◽  
Modelling Studies ◽  
Community Earth System Model

<p>Many observational and modelling studies have highlighted the important role that irrigation plays in the terrestrial hydrological and energy cycle. Land surface models are a key tool to study these interactions, underlining the importance of an accurate representation of irrigation in these models. However, most land surface models either ignore irrigation or represent it in a crude way. Here we improve and evaluate the implementation of irrigation in the Community Terrestrial Systems Model (CTSM), the land component of the Community Earth System Model (CESM). In this improvement, we consider three irrigation techniques (flood, sprinkler and drip), which differ in the amount and way of water applied. By combining global maps of the area equipped for irrigation with the distribution of different irrigation techniques, we represent the transient spatial distribution of irrigation techniques. Subsequently, we evaluate the performance of CTSM with the improved irrigation module. Three experiments are conducted: one with irrigation switched off, the second with the original irrigation module and the third with the improved irrigation module implemented. All three outputs are evaluated against observed or remotely sensed land surface energy fluxes and near-surface climate datasets. We anticipate that the results will reveal how our new irrigation schemes improve or reduce the performance of the land surface model.</p>

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