scholarly journals Precipitation, Recycling, and Land Memory: An Integrated Analysis

2009 ◽  
Vol 10 (1) ◽  
pp. 278-288 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
C. Adam Schlosser ◽  
Kaye L. Brubaker
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
General Circulation ◽  
Water Cycle ◽  
Circulation Model ◽  
Integrated Analysis ◽  
Forecast Models ◽  
Precipitation Recycling ◽  
High Degree

Abstract A synthesis of several approaches to quantifying land–atmosphere interactions is presented. These approaches use data from observations or atmospheric reanalyses applied to atmospheric tracer models and stand-alone land surface schemes. None of these approaches relies on the results of general circulation model simulations. A high degree of correlation is found among these independent approaches, and constructed here is a composite assessment of global land–atmosphere feedback strength as a function of season. The composite combines the characteristics of persistence of soil moisture anomalies, strong soil moisture regulation of evaporation rates, and reinforcement of water cycle anomalies through recycling. The regions and seasons that have a strong composite signal predominate in both summer and winter monsoon regions in the period after the rainy season wanes. However, there are exceptions to this pattern, most notably over the Great Plains of North America and the Pampas/Pantanal of South America, where there are signs of land–atmosphere feedback throughout most of the year. Soil moisture memory in many of these regions is long enough to suggest that real-time monitoring and accurate initialization of the land surface in forecast models could lead to improvements in medium-range weather to subseasonal climate forecasts.

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

1986 ◽  
Vol 67 (2) ◽  
pp. 138-144 ◽  
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.

An Integrated Variational Framework for Mapping Evapotranspiration by Assimilating GOES LST and SMAP data

2020 ◽  
Author(s):  
Leila farhadi ◽  
Abedeh Abdolghafoorian
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
Water Cycle ◽  
Spatial Scales ◽  
Coupled Model ◽  
Balance Model ◽  
Parameter Estimates ◽  
Dynamic Feedback ◽  
Unknown Parameters

<p>Evapotranspiration (ET) is a key component of terrestrial water cycle that plays an important role in the Earth system. Aaccurate estimation of ET is crucial in various hydrological, meteorological, and agricultural applications. In situ measurements of ET are costly and cannot be readily scaled to regional scales relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of ET using land surface state observations that are widely available from remote sensing across a range of spatial scales.</p><p>In this work, A variational data (VDA) assimilation framework is developed to estimate ET by assimilating Soil Moisture Active Passive (SMAP) soil moisture and Geostationary Operational Environmental Satellite (GOES) land surface temperature data into a coupled dual-source energy and water balance model.</p><p>The VDA framework estimates the key parameters of the coupled model, which regulate the partitioning of available energy (i.e., neutral bulk heat transfer coefficient (CH<sub>N</sub>) and evaporative fraction from soil (EF<sub>S</sub>) and canopy (EF<sub>C</sub>)). The uncertainties of the retrieved unknown parameters are estimated through the inverse of Hessian of cost function, obtained using the Lagrangian methodology. Analysis of the second-order information provides a tool to identify the optimum parameter estimates and guides towards a well-posed estimation problem.</p><p>The VDA framework is implemented over an area of 21780 km<sup>2</sup> in the U.S. Southern Great Plains (with computational grid size of 0.05 degree) during a nine-month period. The maps of retrieved evaporation and transpiration are used to study a number of dynamic feedback mechanisms between the land and atmosphere, such as the dependence of evapotranspiration on vegetation and soil moisture.</p>

scholarly journals Potential Predictability of Long-Term Drought and Pluvial Conditions in the U.S. Great Plains

2008 ◽  
Vol 21 (4) ◽  
pp. 802-816 ◽  
Author(s):  
Siegfried D. Schubert ◽  
Max J. Suarez ◽  
Philip J. Pegion ◽  
Randal D. Koster ◽  
Julio T. Bacmeister
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
General Circulation ◽  
Storm Track ◽  
Warm Season ◽  
Circulation Model ◽  
Skewed Distribution ◽  
Soil Conditions ◽  
Unexpected Result ◽  
Potential Predictability

Abstract This study examines the predictability of seasonal mean Great Plains precipitation using an ensemble of century-long atmospheric general circulation model (AGCM) simulations forced with observed sea surface temperatures (SSTs). The results show that the predictability (intraensemble spread) of the precipitation response to SST forcing varies on interannual and longer time scales. In particular, this study finds that pluvial conditions are more predictable (have less intraensemble spread) than drought conditions. This rather unexpected result is examined in the context of the physical mechanisms that impact precipitation in the Great Plains. These mechanisms include El Niño–Southern Oscillation’s impact on the planetary waves and hence the Pacific storm track (primarily during the cold season), the role of Atlantic SSTs in forcing changes in the Bermuda high and low-level moisture flux into the continent (primarily during the warm season), and soil moisture feedbacks (primarily during the warm season). It is found that the changes in predictability are primarily driven by changes in the strength of the land–atmosphere coupling, such that under dry conditions a given change in soil moisture produces a larger change in evaporation and hence precipitation than the same change in soil moisture would produce under wet soil conditions. The above changes in predictability are associated with a negatively skewed distribution in the seasonal mean precipitation during the warm season—a result that is not inconsistent with the observations.

scholarly journals Multi-variable evaluation of land surface processes in forced and coupled modes reveals new error sources to the simulated water cycle in the IPSL climate model

2020 ◽  
Author(s):  
Hiroki Mizuochi ◽  
Agnes Ducharne ◽  
Frédérique Cheruy ◽  
Josefine Ghattas ◽  
Amen Al-Yaari ◽  
...  
Keyword(s):  
Land Surface ◽  
General Circulation ◽  
Climate Model ◽  
Water Cycle ◽  
Circulation Model ◽  
Surface Model ◽  
Coupled Modes ◽  
Error Sources ◽  
Area Index ◽  
Coupled Mode

Abstract. Evaluating land surface models (LSMs) using available observations is important to understand the potential and limitations of current Earth system models in simulating water- and carbon-related variables. To reveal the error sources of a land surface model (LSM), four essential climate variables have been evaluated in this paper (i.e., surface soil moisture, evapotranspiration, leaf area index, and surface albedo) via simulations with IPSL LSM ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems), particularly focusing on the difference between (i) forced simulations with atmospheric forcing data (WATCH-Forcing-DATA-ERA-Interim: WFDEI) and (ii) coupled simulations with the IPSL atmospheric general circulation model. Results from statistical evaluation using satellite- and ground-based reference data show that ORCHIDEE is well equipped to represent spatiotemporal patterns of all variables in general. However, further analysis against various landscape/meteorological factors (e.g., plant functional type, slope, precipitation, and irrigation) suggests potential uncertainty relating to freezing/snowmelt, temperate plant phenology, irrigation, as well as contrasted responses between forced and coupled mode simulations. The biases in the simulated variables are amplified in coupled mode via surface–atmosphere interactions, indicating a strong link between irrigation–precipitation and a relatively complex link between precipitation–evapotranspiration that reflects the hydrometeorological regime of the region (energy-limited or water-limited) and snow-albedo feedback in mountainous and boreal regions. The different results between forced and coupled modes imply the importance of model evaluation under both modes to isolate potential sources of uncertainty in the model.

scholarly journals Impacts of soil-aquifer heat and water fluxes on simulated global climate

2013 ◽  
Vol 10 (1) ◽  
pp. 1185-1212 ◽  
Author(s):  
N. Y. Krakauer ◽  
M. J. Puma ◽  
B. I. Cook
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
General Circulation ◽  
Soil Column ◽  
Circulation Model ◽  
The Arctic ◽  
Water Fluxes ◽  
Limited Impact ◽  
Mean Climate ◽  
The Impact

Abstract. Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50 m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer-soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer-soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil-aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of >1 K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and land-surface temperature, and decrease the soil moisture memory of the land surface on annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence.

scholarly journals Impacts of soil–aquifer heat and water fluxes on simulated global climate

2013 ◽  
Vol 17 (5) ◽  
pp. 1963-1974 ◽  
Author(s):  
N. Y. Krakauer ◽  
M. J. Puma ◽  
B. I. Cook
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
General Circulation ◽  
Soil Column ◽  
Circulation Model ◽  
The Arctic ◽  
Water Fluxes ◽  
Limited Impact ◽  
Mean Climate ◽  
The Impact

Abstract. Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50 m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer–soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer–soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil–aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of > 1 K in the Arctic. The soil–aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and in land-surface temperature, and decrease the soil moisture memory of the land surface on seasonal to annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence.

Sensitivity of Global Tropical Climate to Land Surface Processes: Mean State and Interannual Variability

2013 ◽  
Vol 26 (5) ◽  
pp. 1818-1837 ◽  
Author(s):  
Hsi-Yen Ma ◽  
Heng Xiao ◽  
C. Roberto Mechoso ◽  
Yongkang Xue
Keyword(s):  
Soil Moisture ◽  
Indirect Effect ◽  
Land Surface ◽  
Seasonal Cycle ◽  
General Circulation ◽  
Global Climate ◽  
Circulation Model ◽  
Equatorial Pacific ◽  
Surface Processes ◽  
Mean State

Abstract This study examines the sensitivity of the global climate to land surface processes (LSP) using an atmospheric general circulation model both uncoupled (with prescribed SSTs) and coupled to an oceanic general circulation model. The emphasis is on the interactive soil moisture and vegetation biophysical processes, which have first-order influence on the surface energy and water budgets. The sensitivity to those processes is represented by the differences between model simulations, in which two land surface schemes are considered: 1) a simple land scheme that specifies surface albedo and soil moisture availability and 2) the Simplified Simple Biosphere Model (SSiB), which allows for consideration of interactive soil moisture and vegetation biophysical process. Observational datasets are also employed to assess the extent to which results are realistic. The mean state sensitivity to different LSP is stronger in the coupled mode, especially in the tropical Pacific. Furthermore, the seasonal cycle of SSTs in the equatorial Pacific, as well as the ENSO frequency, amplitude, and locking to the seasonal cycle of SSTs, is significantly modified and more realistic with SSiB. This outstanding sensitivity of the atmosphere–ocean system develops through changes in the intensity of equatorial Pacific trades modified by convection over land. The results further demonstrate that the direct impact of land–atmosphere interactions on the tropical climate is modified by feedbacks associated with perturbed oceanic conditions (“indirect effect” of LSP). The magnitude of such an indirect effect is strong enough to suggest that comprehensive studies on the importance of LSP on the global climate have to be made in a system that allows for atmosphere–ocean interactions.

scholarly journals Multivariable evaluation of land surface processes in forced and coupled modes reveals new error sources to the simulated water cycle in the IPSL (Institute Pierre Simon Laplace) climate model

2021 ◽  
Vol 25 (4) ◽  
pp. 2199-2221
Author(s):  
Hiroki Mizuochi ◽  
Agnès Ducharne ◽  
Frédérique Cheruy ◽  
Josefine Ghattas ◽  
Amen Al-Yaari ◽  
...  
Keyword(s):  
Land Surface ◽  
General Circulation ◽  
Climate Model ◽  
Water Cycle ◽  
Circulation Model ◽  
Coupled Modes ◽  
Error Sources ◽  
Area Index ◽  
Coupled Mode ◽  
The Difference

Abstract. Evaluating land surface models (LSMs) using available observations is important for understanding the potential and limitations of current Earth system models in simulating water- and carbon-related variables. To reveal the error sources of a LSM, five essential climate variables have been evaluated in this paper (i.e., surface soil moisture, evapotranspiration, leaf area index, surface albedo, and precipitation) via simulations with the IPSL (Institute Pierre Simon Laplace) LSM ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) model, particularly focusing on the difference between (i) forced simulations with atmospheric forcing data (WATCH Forcing Data ERA-Interim – WFDEI) and (ii) coupled simulations with the IPSL atmospheric general circulation model. Results from statistical evaluation, using satellite- and ground-based reference data, show that ORCHIDEE is well equipped to represent spatiotemporal patterns of all variables in general. However, further analysis against various landscape and meteorological factors (e.g., plant functional type, slope, precipitation, and irrigation) suggests potential uncertainty relating to freezing and/or snowmelt, temperate plant phenology, irrigation, and contrasted responses between forced and coupled mode simulations. The biases in the simulated variables are amplified in the coupled mode via surface–atmosphere interactions, indicating a strong link between irrigation–precipitation and a relatively complex link between precipitation–evapotranspiration that reflects the hydrometeorological regime of the region (energy limited or water limited) and snow albedo feedback in mountainous and boreal regions. The different results between forced and coupled modes imply the importance of model evaluation under both modes to isolate potential sources of uncertainty in the model.

scholarly journals Assessment of soil moisture fields from imperfect climate models with uncertain satellite observations

2009 ◽  
Vol 6 (2) ◽  
pp. 2733-2750 ◽  
Author(s):  
G. Schumann ◽  
D. J. Lunt ◽  
P. J. Valdes ◽  
R. A. M. de Jeu ◽  
K. Scipal ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Circulation Model ◽  
Data Uncertainty ◽  
Limited Area

Abstract. We demonstrate that global satellite products can be used to evaluate climate model soil moisture predictions but conclusions should be drawn with care. The quality of a limited area climate model (LAM) was compared to a general circulation model (GCM) using soil moisture data from two different Earth observing satellites within a model validation scheme that copes with the presence of uncertain data. Results showed that in the face of imperfect models and data, it is difficult to investigate the quality of current land surface schemes in simulating hydrology accurately. Nevertheless, a LAM provides, in general, a better representation of spatial patterns and dynamics of soil moisture. However, in months when data uncertainty is higher, particularly in colder months and in periods when vegetation cover and soil moisture are out of phase (e.g. August in the case of Western Europe), it is not possible to draw firm conclusions about model acceptability. Our work indicates that a higher resolution LAM has more benefits to soil moisture prediction than are due to the resolution alone and can be attributed to an overall intensification of the hydrological cycle relative to the GCM.

scholarly journals Modelling root water uptake in a complex land surface scheme coupled to a GCM

1998 ◽  
Vol 2 (2/3) ◽  
pp. 239-255 ◽  
Author(s):  
P. de Rosnay ◽  
J. Polcher
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Water Uptake ◽  
Land Surface ◽  
General Circulation ◽  
Circulation Model ◽  
Root Water Uptake ◽  
Soil Water Storage ◽  
Land Surface Scheme ◽  
Surface Scheme

Abstract. The aim of this paper is to improve the representation of root water uptake in the land surface scheme SECHIBA coupled to the LMD General Circulation Model (GCM). Root water uptake mainly results from the interaction between soil moisture and root profiles. Firstly, one aspect of the soil hydrology in SECHIBA is changed: it is shown that increasing the soil water storage capacity leads to a reduction in the frequency of soil water drought, but enhances the mean evapotranspiration. Secondly, the representation of the soil-vegetation interaction is improved by allowing a different root profile for each type of vegetation. The interaction between sub-grid scale variabilities in soil moisture and vegetation is also studied. The approach consists of allocating a separate soil water column to each vegetation type, thereby 'tiling' the grid square. However, the possibility of choosing the degree of soil moisture spatial heterogeneity is retained. These enhancements of the land surface system are compared within a number of GCM experiments.

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