Exploring the effects of the land surface on tropical precipitation

Author(s):  
Marianne Pietschnig ◽  
Abigail L. S. Swann ◽  
Ruth Geen ◽  
F. Hugo Lambert ◽  
Geoffrey K. Vallis

<p>Projected precipitation changes over tropical land tend to be enhanced by vegetation responses to CO<sub>2</sub> forcing in Earth System Models. Projected decreases in rainfall over the Amazon basin and increases over the Maritime Continent are both stronger when plant physiological changes are modelled than if these changes are neglected, but the reasons for this amplification remain unclear. The responses of vegetation to increasing CO<sub>2 </sub>levels are complex and uncertain, but changes in stomatal conductance likely dominate the evapotranspiration response in Earth System Models.</p><p>We investigate why vegetation changes cause precipitation to increase more strongly over the Maritime Continent while decreasing more strongly over the Amazon basin. We employ an idealized Atmospheric General Circulation Model with a simplified vegetation scheme that captures CO<sub>2</sub>-driven stomatal closure.</p><p>We find that – counter-intuitively – rainfall is enhanced over a narrow rectangular island when terrestrial evaporation falls to zero with high CO<sub>2</sub>. Strong heating and ascent over the island trigger moisture advection from the surrounding ocean. In contrast, over larger continents rainfall depends on continental moisture recycling.</p><p>Simulations with two large rectangular continents representing South America and Africa reveal that the stronger decrease in rainfall over the Amazon basin is due to a combination of local and remote effects:</p><p>Finally, we investigate the impact of land-surface hydrology on continental rainfall on seasonal timescales. Using our idealized model and realistic continents, we study the strength of the South East Asian monsoon for different continental evaporation schemes. Surprisingly, when terrestrial evapotranspiration is unlimited (i.e. does not depend on soil moisture availability), monsoon precipitation is much weaker than when terrestrial evapotranspiration is limited by soil moisture. In order to explain this behavior, we compare the atmospheric energy budgets and circulation between the simulations.</p><p>Our results show that the land-surface hydrology plays an important role in modifying tropical precipitation and atmospheric dynamics on seasonal timescales and in the long-term under climate change, and that further investigation into the topic is called for.</p>

2021 ◽  
Author(s):  
Michel Bechtold ◽  
Sarith P. Mahanama ◽  
Rolf H. Reichle ◽  
Randal D. Koster ◽  
Gabrielle J. M. De Lannoy

<p>Mapping the global peatland distribution is important for embedding peatland processes into Earth System Models. Peatland maps are typically compiled from nation-specific soil or ecosystem maps or based on machine learning tools trained on such data. Here, we evaluate the performance of a land surface model with two different peatland map inputs in providing critical land surface estimates (soil moisture, temperature) to a Radiative Transfer Model (RTM) for L-band brightness temperature (Tb). We hypothesize that an improved performance of the land surface model in Tb space indicates a better spatial peatland distribution input within the footprint of Tb observations (~40 km).</p><p>We employ the NASA Catchment Land Surface Model (CLSM) with a recently added module for peatland hydrology (PEATCLSM modules). We run this model at a 9-km EASEv2 resolution over the Northern Hemisphere for two soil maps that differ in their peatland distributions. The applied soil distributions are: (MAP1) a combination of the Harmonized World Soil Database and the State Soil Geographic Database, also used to generate the Soil Moisture Active Passive (SMAP) Level-4 soil moisture product, and (MAP2) a hybrid of HWSD-STATSGO and the ‘PEATMAP’ product, which is mainly compiled from national peatland maps. MAP2 indicates ~30 % more peatland area over the Northern Hemisphere. For both peat distributions, CLSM is run and parameters of the RTM are calibrated with 10 years of multi-angular L-band Tb observations from the Soil Moisture and Ocean Salinity SMOS mission. Afterwards, CLSM is run together with the calibrated RTM within a data assimilation system, with and without (open-loop) assimilating SMAP Tb observations, for the period 2015-2020. Our results demonstrate that Tb misfits (in both the open-loop and assimilation runs) are reduced in the areas with the largest differences in peat distribution, thus indicating a basic validity of assuming a peatland-like hydrological dynamics for the larger peat extent of MAP2. Results will be discussed in the context of how peatlands are defined in global peatland maps and the question of what is typically modeled as a peatland in Earth System Models. We propose the evaluation of future releases of peatland maps in Tb space as a tool to evaluate their suitability for implementation into Earth System Models.</p>


2018 ◽  
Vol 54 (12) ◽  
Author(s):  
Wondmagegn Yigzaw ◽  
Hong‐Yi Li ◽  
Yonas Demissie ◽  
Mohamad I. Hejazi ◽  
L. Ruby Leung ◽  
...  

2021 ◽  
pp. 1-50
Author(s):  
Marianne Pietschnig ◽  
Abigail L. S. Swann ◽  
F. Hugo Lambert ◽  
Geoffrey K. Vallis

AbstractFuture projections of precipitation change over tropical land are often enhanced by vegetation responses to CO2 forcing in Earth System Models. Projected decreases in rainfall over the Amazon basin and increases over the Maritime Continent are both stronger when plant physiological changes are modelled than if these changes are neglected, but the reasons for this amplification remain unclear. The responses of vegetation to increasing CO2 levels are complex and uncertain, including possible decreases in stomatal conductance and increases in leaf area index due to CO2-fertilisation. Our results from an idealised Atmospheric General Circulation Model show that the amplification of rainfall changes occurs even when we use a simplified vegetation parameterisation based solely on CO2-driven decreases in stomatal conductance, indicating that this mechanism plays a key role in complex model projections. Based on simulations with rectangular continentswe find that reducing terrestrial evaporation to zero with increasing CO2 notably leads to enhanced rainfall over a narrow island. Strong heating and ascent over the island trigger moisture advection from the surrounding ocean. In contrast, over larger continents rainfall depends on continental evaporation. Simulations with two rectangular continents representing South America and Africa reveal that the stronger decrease in rainfall over the Amazon basin seen in Earth System Models is due to a combination of local and remote effects, which are fundamentally connected to South America’s size and its location with respect to Africa. The response of tropical rainfall to changes in evapotranspiration is thus connected to size and configuration of the continents.


2012 ◽  
Vol 16 (8) ◽  
pp. 2547-2565 ◽  
Author(s):  
G. Tang ◽  
P. J. Bartlein

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.


2017 ◽  
Vol 21 (1) ◽  
pp. 217-233 ◽  
Author(s):  
Elham Rouholahnejad Freund ◽  
James W. Kirchner

Abstract. Most Earth system models are based on grid-averaged soil columns that do not communicate with one another, and that average over considerable sub-grid heterogeneity in land surface properties, precipitation (P), and potential evapotranspiration (PET). These models also typically ignore topographically driven lateral redistribution of water (either as groundwater or surface flows), both within and between model grid cells. Here, we present a first attempt to quantify the effects of spatial heterogeneity and lateral redistribution on grid-cell-averaged evapotranspiration (ET) as seen from the atmosphere over heterogeneous landscapes. Our approach uses Budyko curves, as a simple model of ET as a function of atmospheric forcing by P and PET. From these Budyko curves, we derive a simple sub-grid closure relation that quantifies how spatial heterogeneity affects average ET as seen from the atmosphere. We show that averaging over sub-grid heterogeneity in P and PET, as typical Earth system models do, leads to overestimations of average ET. For a sample high-relief grid cell in the Himalayas, this overestimation bias is shown to be roughly 12 %; for adjacent lower-relief grid cells, it is substantially smaller. We use a similar approach to derive sub-grid closure relations that quantify how lateral redistribution of water could alter average ET as seen from the atmosphere. We derive expressions for the maximum possible effect of lateral redistribution on average ET, and the amount of lateral redistribution required to achieve this effect, using only estimates of P and PET in possible source and recipient locations as inputs. We show that where the aridity index P/PET increases with altitude, gravitationally driven lateral redistribution will increase average ET (and models that overlook lateral redistribution will underestimate average ET). Conversely, where the aridity index P/PET decreases with altitude, gravitationally driven lateral redistribution will decrease average ET. The effects of both sub-grid heterogeneity and lateral redistribution will be most pronounced where P is inversely correlated with PET across the landscape. Our analysis provides first-order estimates of the magnitudes of these sub-grid effects, as a guide for more detailed modeling and analysis.


2020 ◽  
Author(s):  
Norman Steinert ◽  
Fidel González-Rouco ◽  
Stefan Hagemann ◽  
Philipp de Vrese ◽  
Elena García-Bustamante ◽  
...  

&lt;p&gt;The representation of the thermal and hydrological state in the land model component of Earth System Models is crucial to have a realistic simulation of subsurface processes and the coupling between the atmo-, lito- and biosphere. There is evidence suggesting an inaccurate simulation of subsurface thermodynamics in current-generation Earth System Models, which have Land Surface Models that are too shallow. In simulations with a bottom boundary too close to the surface, the energy propagation and spatio-temporal variability of subsurface temperatures are affected. This potentially restrains the simulation of land-air interactions and subsurface phenomena, e.g. energy/moisture balance and storage capacity, freeze/thaw cycles and permafrost evolution. We introduce modifications for a deeper soil into the JSBACH soil model component of the MPI-ESM for climate projections of the 21st century. Subsurface layers are added progressively to increase the bottom boundary depth from 10m to 1400m. This leads to near-surface cooling of the soil and encourages regional terrestrial energy uptake by one order of magnitude and more. &lt;br&gt;The depth-changes in the soil also have implications for the hydrological regime, in which the moisture between the surface and the bedrock is sensitive to variations in the thermal regime. Additionally, we compare two different global soil parameter datasets that have major implications for the vertical distribution and availability of soil moisture and its exchange with the land surface. The implementation of supercool water and water phase changes in the soil creates a coupling between the soil thermal and hydrological regimes. In both cases of bottom boundary and water depth changes, we explore the sensitivity of JSBACH from the perspective of changes in the soil thermodynamics, energy balance and storage, as well as the effect of including freezing and thawing processes and their influence on the simulation of permafrost areas in the Northern Hemisphere high latitudes. The latter is of particular interest due to their vulnerability to long-term climate change.&lt;/p&gt;


2020 ◽  
Author(s):  
Nathaniel W. Chaney ◽  
Laura Torres-Rojas ◽  
Noemi Vergopolan ◽  
Colby K. Fisher

Abstract. Over the past decade, there has been appreciable progress towards modeling the water, energy, and carbon cycles at field-scales (10–100 m) over continental to global extents. One such approach, named HydroBlocks, accomplishes this task while maintaining computational efficiency via sub-grid tiles, or Hydrologic Response Units (HRUs), learned via a hierarchical clustering approach from available global high-resolution environmental data. However, until now, there has yet to be a macroscale river routing approach that is able to leverage HydroBlocks' approach to sub-grid heterogeneity, thus limiting the added value of field-scale land surface modeling in Earth System Models (e.g., riparian zone dynamics, irrigation from surface water, and interactive floodplains). This paper introduces a novel dynamic river routing scheme in HydroBlocks that is intertwined with the modeled field-scale land surface heterogeneity. The primary features of the routing scheme include: 1) the fine-scale river network of each macroscale grid cell's is derived from very high resolution (


2013 ◽  
Vol 6 (1) ◽  
pp. 255-296
Author(s):  
C. Ottlé ◽  
J. Lescure ◽  
F. Maignan ◽  
B. Poulter ◽  
T. Wang ◽  
...  

Abstract. High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover datasets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing earth system models. Earth system models also require specific land cover classification systems based on plant functional types, rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover datasets against one another and with auxiliary data to identify key uncertainties that contribute to variability in Plant Functional Type (PFT) classifications that would introduce errors in earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, continuous vegetation fields (MODIS-VCF) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover dataset, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFTs maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT dataset, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground-truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to better represent the water and carbon cycles in northern latitudes. Updated land cover datasets are critical for improving and maintaining the relevance of earth system models for assessing climate and human impacts on biogeochemistry and biophysics. The new PFT map at 5 km scale is available for download from the PANGAEA website, at: doi:10.1594/PANGAEA.810709.


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