scholarly journals Soil moisture–atmosphere feedback dominates land carbon uptake variability

Nature ◽  
2021 ◽  
Vol 592 (7852) ◽  
pp. 65-69
Author(s):  
Vincent Humphrey ◽  
Alexis Berg ◽  
Philippe Ciais ◽  
Pierre Gentine ◽  
Martin Jung ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Dominant Role ◽  
Vapour Pressure Deficit ◽  
Terrestrial Ecosystems ◽  
Surface Model ◽  
Carbon Uptake ◽  
Model Simulations

AbstractYear-to-year changes in carbon uptake by terrestrial ecosystems have an essential role in determining atmospheric carbon dioxide concentrations1. It remains uncertain to what extent temperature and water availability can explain these variations at the global scale2–5. Here we use factorial climate model simulations6 and show that variability in soil moisture drives 90 per cent of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture–atmosphere feedback amplifies temperature and humidity anomalies and enhances the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate that soil moisture has a dominant role4, which is not readily apparent from land surface model simulations and observational analyses2,5. These findings highlight the need to account for feedback between soil and atmospheric dryness when estimating the response of the carbon cycle to climatic change globally5,7, as well as when conducting field-scale investigations of the response of the ecosystem to droughts8,9. Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects that are controlled by soil moisture.

scholarly journals Evaluation of drought representation and propagation in regional climate model simulations across Spain

2019 ◽  
Vol 23 (12) ◽  
pp. 5111-5131 ◽  
Author(s):  
Anaïs Barella-Ortiz ◽  
Pere Quintana-Seguí
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Model ◽  
Model Simulation ◽  
Regional Climate ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Surface Model ◽  
Model Structure ◽  
Model Simulations

Abstract. Drought is an important climatic risk that is expected to increase in frequency, duration, and severity as a result of a warmer climate. It is complex to model due to the interactions between atmospheric and continental processes. A better understanding of these processes and how the current modelling tools represent them and characterize drought is vital. The aim of this study is to analyse how regional climate models (RCMs) represent meteorological, soil moisture, and hydrological drought as well as propagation from precipitation anomalies to soil moisture and streamflow anomalies. The analysis was carried out by means of standardized indices calculated using variables directly related to each type of drought: precipitation (SPI), soil moisture (SSMI), runoff (SRI), and streamflow (SSI). The RCMs evaluated are the CNRM-RCSM4, COSMO-CLM, and PROMES. All of the simulations were obtained from the Med-CORDEX database and were forced with ERA-Interim. The following datasets were used as references: SAFRAN (meteorological drought), offline land surface model simulations from ISBA-3L and ORCHIDEE (soil moisture drought), a SIMPA hydrological model simulation, and observed streamflow (hydrological drought). The results show that RCMs improve meteorological drought representation. However, uncertainties are identified in their characterization of soil moisture and hydrological drought, as well as in drought propagation. These are mainly explained by the model structure. For instance, model structure affects the temporal scale at which precipitation variability propagates to soil moisture and streamflow.

scholarly journals The DeepMIP contribution to PMIP4: experimental design for model simulations of the EECO, PETM, and pre-PETM (version 1.0)

2017 ◽  
Vol 10 (2) ◽  
pp. 889-901 ◽  
Author(s):  
Daniel J. Lunt ◽  
Matthew Huber ◽  
Eleni Anagnostou ◽  
Michiel L. J. Baatsen ◽  
Rodrigo Caballero ◽  
...  
Keyword(s):  
Experimental Design ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Initial Conditions ◽  
Geological Data ◽  
Time Model ◽  
Model Simulations ◽  
Intercomparison Project ◽  
Climate Model Simulations

Abstract. Past warm periods provide an opportunity to evaluate climate models under extreme forcing scenarios, in particular high ( >  800 ppmv) atmospheric CO2 concentrations. Although a post hoc intercomparison of Eocene ( ∼  50  Ma) climate model simulations and geological data has been carried out previously, models of past high-CO2 periods have never been evaluated in a consistent framework. Here, we present an experimental design for climate model simulations of three warm periods within the early Eocene and the latest Paleocene (the EECO, PETM, and pre-PETM). Together with the CMIP6 pre-industrial control and abrupt 4 ×  CO2 simulations, and additional sensitivity studies, these form the first phase of DeepMIP – the Deep-time Model Intercomparison Project, itself a group within the wider Paleoclimate Modelling Intercomparison Project (PMIP). The experimental design specifies and provides guidance on boundary conditions associated with palaeogeography, greenhouse gases, astronomical configuration, solar constant, land surface processes, and aerosols. Initial conditions, simulation length, and output variables are also specified. Finally, we explain how the geological data sets, which will be used to evaluate the simulations, will be developed.

scholarly journals Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts

2021 ◽  
Vol 12 (3) ◽  
pp. 919-938
Author(s):  
Mengyuan Mu ◽  
Martin G. De Kauwe ◽  
Anna M. Ukkola ◽  
Andy J. Pitman ◽  
Weidong Guo ◽  
...  
Keyword(s):  
Land Surface ◽  
Forest Canopy ◽  
Climate Models ◽  
Root Zone ◽  
Stomatal Closure ◽  
Capillary Rise ◽  
Vapour Pressure Deficit ◽  
Global Climate Models ◽  
Surface Model ◽  
The Impact

Abstract. The co-occurrence of droughts and heatwaves can have significant impacts on many socioeconomic and environmental systems. Groundwater has the potential to moderate the impact of droughts and heatwaves by moistening the soil and enabling vegetation to maintain higher evaporation, thereby cooling the canopy. We use the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled to a groundwater scheme, to examine how groundwater influences ecosystems under conditions of co-occurring droughts and heatwaves. We focus specifically on south-east Australia for the period 2000–2019, when two significant droughts and multiple extreme heatwave events occurred. We found groundwater plays an important role in helping vegetation maintain transpiration, particularly in the first 1–2 years of a multi-year drought. Groundwater impedes gravity-driven drainage and moistens the root zone via capillary rise. These mechanisms reduced forest canopy temperatures by up to 5 ∘C during individual heatwaves, particularly where the water table depth is shallow. The role of groundwater diminishes as the drought lengthens beyond 2 years and soil water reserves are depleted. Further, the lack of deep roots or stomatal closure caused by high vapour pressure deficit or high temperatures can reduce the additional transpiration induced by groundwater. The capacity of groundwater to moderate both water and heat stress on ecosystems during simultaneous droughts and heatwaves is not represented in most global climate models, suggesting that model projections may overestimate the risk of these events in the future.

scholarly journals Development of a Unified Land Model for Prediction of Surface Hydrology and Land–Atmosphere Interactions

2011 ◽  
Vol 12 (6) ◽  
pp. 1299-1320 ◽  
Author(s):  
Ben Livneh ◽  
Pedro J. Restrepo ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
A Priori ◽  
Model Performance ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Frozen Soil ◽  
Surface Model ◽  
Soil Moisture Accounting

Abstract A unified land model (ULM) is described that combines the surface flux parameterizations in the Noah land surface model (used in most of NOAA’s coupled weather and climate models) with the Sacramento Soil Moisture Accounting model (Sac; used for hydrologic prediction within the National Weather Service). The motivation was to develop a model that has a history of strong hydrologic performance while having the ability to be run in the coupled land–atmosphere environment. ULM takes the vegetation, snow model, frozen soil, and evapotranspiration schemes from Noah and merges them with the soil moisture accounting scheme from Sac. ULM surface fluxes, soil moisture, and streamflow simulations were evaluated through comparisons with observations from the Ameriflux (surface flux), Illinois Climate Network (soil moisture), and Model Parameter Estimation Experiment (MOPEX; streamflow) datasets. Initially, a priori parameters from Sac and Noah were used, which resulted in ULM surface flux simulations that were comparable to those produced by Noah (Sac does not predict surface energy fluxes). ULM with the a priori parameters had streamflow simulation skill that was generally similar to Sac’s, although it was slightly better (worse) for wetter (more arid) basins. ULM model performance using a set of parameters identified via a Monte Carlo search procedure lead to substantial improvements relative to the a priori parameters. A scheme for transfer of parameters from streamflow simulations to nearby flux and soil moisture measurement points was also evaluated; this approach did not yield conclusive improvements relative to the a priori parameters.

scholarly journals An Evaluation of Modeled Evaporation Regimes in Europe Using Observed Dry Spell Land Surface Temperature

2017 ◽  
Vol 18 (5) ◽  
pp. 1453-1470 ◽  
Author(s):  
Phil P. Harris ◽  
Sonja S. Folwell ◽  
Belen Gallego-Elvira ◽  
José Rodríguez ◽  
Sean Milton ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Climate Models ◽  
Bare Soil ◽  
Surface Model ◽  
Continental Scale ◽  
Dry Spells ◽  
Dry Spell

Abstract Soil moisture availability exerts control over the land surface energy partition in parts of Europe. However, determining the strength and variability of this control is impeded by the lack of reliable evaporation observations at the continental scale. This makes it difficult to refine the broad range of soil moisture–evaporation behaviors across global climate models (GCMs). Previous studies show that satellite observations of land surface temperature (LST) during rain-free dry spells can be used to diagnose evaporation regimes at the GCM gridbox scale. This relative warming rate (RWR) diagnostic quantifies the increase in dry spell LST relative to air temperature and is used here to evaluate a land surface model (JULES) both offline and coupled to a GCM (HadGEM3-A). It is shown that RWR can be calculated using outputs from an atmospheric GCM provided the satellite clear-sky sampling bias is incorporated. Both offline JULES and HadGEM3-A reproduce the observed seasonal and regional RWR variations, but with weak springtime RWRs in central Europe. This coincides with sustained bare soil evaporation (Ebs) during dry spells, reflecting previous site-level JULES studies in Europe. To assess whether RWR can discriminate between surface descriptions, the bare soil surface conductance and the vegetation root profile are revised to limit Ebs. This increases RWR by increasing the occurrence of soil moisture–limited dry spells, yielding more realistic springtime RWRs as a function of antecedent precipitation but poorer relationships in summer. This study demonstrates the potential for using satellite LST to assess evaporation regimes in climate models.

scholarly journals Reducing climate model biases by exploring parameter space with large ensembles of climate model simulations and statistical emulation

2019 ◽  
Vol 12 (7) ◽  
pp. 3017-3043 ◽  
Author(s):  
Sihan Li ◽  
David E. Rupp ◽  
Linnia Hawkins ◽  
Philip W. Mote ◽  
Doug McNeall ◽  
...  
Keyword(s):  
Parameter Space ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Atmospheric Model ◽  
Bias Reduction ◽  
Sensitivity Analyses ◽  
Model Framework ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. Understanding the unfolding challenges of climate change relies on climate models, many of which have large summer warm and dry biases over Northern Hemisphere continental midlatitudes. This work, with the example of the model used in the updated version of the weather@home distributed climate model framework, shows the potential for improving climate model simulations through a multiphased parameter refinement approach, particularly over the northwestern United States (NWUS). Each phase consists of (1) creating a perturbed parameter ensemble with the coupled global–regional atmospheric model, (2) building statistical emulators that estimate climate metrics as functions of parameter values, (3) and using the emulators to further refine the parameter space. The refinement process includes sensitivity analyses to identify the most influential parameters for various model output metrics; results are then used to cull parameters with little influence. Three phases of this iterative process are carried out before the results are considered to be satisfactory; that is, a handful of parameter sets are identified that meet acceptable bias reduction criteria. Results not only indicate that 74 % of the NWUS regional warm biases can be reduced by refining global atmospheric parameters that control convection and hydrometeor transport, as well as land surface parameters that affect plant photosynthesis, transpiration, and evaporation, but also suggest that this iterative approach to perturbed parameters has an important role to play in the evolution of physical parameterizations.

scholarly journals The waxing and waning of the Northern Hemisphere ice sheets

1995 ◽  
Vol 21 ◽  
pp. 96-102 ◽  
Author(s):  
I. Marsiat
Keyword(s):  
Mass Balance ◽  
Northern Hemisphere ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Ice Age ◽  
Surface Model ◽  
Glacial Cycle ◽  
Ice Volume

Past modelling studies have shown that the energy balance of the ice-sheet surface is of primary importance in representing the 100 000 year glacial cycle. In particular, modelling of the net mass-balance function is an important part of coupled ice-sheet/climate models. We conduct a series of palaeoclimatic simulations with a vertically integrated ice-flow model coupled to the two-dimensional statistical-dynamical LLN (Louvain-la-Neuve) climate model. The models are coupled through a land-surface model which computes seasonal cycles of surface temperature and precipitation at the real altitude of the surface and evaluates the annual snow and/or ice-mass budget. The present-day climate of the Northern Hemisphere, the Greenland mass balance and the snowfield characteristics are quite well represented despite the relative simplicity of the model. Total ice-volume and sea-level variations during the last glacial cycle are well simulated. This suggests that the physical mechanisms included in the models are sufficient to explain the most striking features of the ice-age cycle. Introducing an improved and more detailed topography improves the simulation of the total ice volume but fails to correct inadequacies in the simulated ice distribution on the surface of the Earth.

scholarly journals Streamflow data assimilation for soil moisture analysis

2010 ◽  
Vol 3 (1) ◽  
pp. 1-12 ◽  
Author(s):  
K. Warrach-Sagi ◽  
V. Wulfmeyer
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
Climate Models ◽  
Root Zone ◽  
Weather Forecast ◽  
Surface Model ◽  
River Catchment ◽  
Streamflow Data ◽  
The Impact

Abstract. Streamflow depends on the soil moisture of a river catchment and can be measured with relatively high accuracy. The soil moisture in the root zone influences the latent heat flux and, hence, the quantity and spatial distribution of atmospheric water vapour and precipitation. As numerical weather forecast and climate models require a proper soil moisture initialization for their land surface models, we enhanced an Ensemble Kalman Filter to assimilate streamflow time series into the multi-layer land surface model TERRA-ML of the regional weather forecast model COSMO. The impact of streamflow assimilation was studied by an observing system simulation experiment in the Enz River catchment (located at the downwind side of the northern Black Forest in Germany). The results demonstrate a clear improvement of the soil moisture field in the catchment. We illustrate the potential of streamflow data assimilation for weather forecasting and discuss its spatial and temporal requirements for a corresponding, automated river gauging network.

scholarly journals ERA-5 and ERA-Interim driven ISBA land surface model simulations: which one performs better?

2018 ◽  
Vol 22 (6) ◽  
pp. 3515-3532 ◽  
Author(s):  
Clement Albergel ◽  
Emanuel Dutra ◽  
Simon Munier ◽  
Jean-Christophe Calvet ◽  
Joaquin Munoz-Sabater ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Surface ◽  
Snow Depth ◽  
Land Surface Model ◽  
Surface Model ◽  
Area Index ◽  
Model Simulations ◽  
In Situ Observations

Abstract. The European Centre for Medium-Range Weather Forecasts (ECMWF) recently released the first 7-year segment of its latest atmospheric reanalysis: ERA-5 over the period 2010–2016. ERA-5 has important changes relative to the former ERA-Interim atmospheric reanalysis including higher spatial and temporal resolutions as well as a more recent model and data assimilation system. ERA-5 is foreseen to replace ERA-Interim reanalysis and one of the main goals of this study is to assess whether ERA-5 can enhance the simulation performances with respect to ERA-Interim when it is used to force a land surface model (LSM). To that end, both ERA-5 and ERA-Interim are used to force the ISBA (Interactions between Soil, Biosphere, and Atmosphere) LSM fully coupled with the Total Runoff Integrating Pathways (TRIP) scheme adapted for the CNRM (Centre National de Recherches Météorologiques) continental hydrological system within the SURFEX (SURFace Externalisée) modelling platform of Météo-France. Simulations cover the 2010–2016 period at half a degree spatial resolution. The ERA-5 impact on ISBA LSM relative to ERA-Interim is evaluated using remote sensing and in situ observations covering a substantial part of the land surface storage and fluxes over the continental US domain. The remote sensing observations include (i) satellite-driven model estimates of land evapotranspiration, (ii) upscaled ground-based observations of gross primary production, (iii) satellite-derived estimates of surface soil moisture and (iv) satellite-derived estimates of leaf area index (LAI). The in situ observations cover (i) soil moisture, (ii) turbulent heat fluxes, (iii) river discharges and (iv) snow depth. ERA-5 leads to a consistent improvement over ERA-Interim as verified by the use of these eight independent observations of different land status and of the model simulations forced by ERA-5 when compared with ERA-Interim. This is particularly evident for the land surface variables linked to the terrestrial hydrological cycle, while variables linked to vegetation are less impacted. Results also indicate that while precipitation provides, to a large extent, improvements in surface fields (e.g. large improvement in the representation of river discharge and snow depth), the other atmospheric variables play an important role, contributing to the overall improvements. These results highlight the importance of enhanced meteorological forcing quality provided by the new ERA-5 reanalysis, which will pave the way for a new generation of land-surface developments and applications.

Evaluation of the regional climate model RegCM4.7 over the Carpathian region for very wet and average years

2020 ◽  
Author(s):  
Tímea Kalmár ◽  
Ildikó Pieczka ◽  
Rita Pongrácz
Keyword(s):  
Soil Moisture ◽  
Regional Climate Model ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Cloud Microphysics ◽  
Mountainous Area ◽  
Model Version ◽  
Carpathian Region

<p>Precipitation is one of the most important climate variables in many aspects due to its key impact on agriculture, water management, etc. However, it remains a challenge for climate models to realistically simulate the regional patterns, temporal variations, and intensity of precipitation. The difficulty arises from the complexity of precipitation processes within the atmosphere stemming from cloud microphysics, cumulus convection, large-scale circulations, planetary boundary layer (PBL) processes, and many others. This is especially true for heterogeneous surfaces with complex orography such as the Carpathian region.  Thus, the Carpathian Basin, with its surrounding mountains, requires higher model resolution, along with different parameterizations, compared to more homogenous regions. The aim of the study is to reproduce the historical precipitation pattern through testing the parameterization of surface processes. The appropriate representations of land surface component in climate models are essential for the simulation of surface and subsurface runoff, soil moisture, and evapotranspiration. Furthermore, PBL strongly influences temperature, moisture, and wind through the turbulent transfer of air mass. The current study focuses on the newest model version of RegCM (RegCM4.7), with which we carry out simulations using different parameterization schemes over the Carpathian region. We investigate the effects of land-surface schemes (i.e. BATS - Biosphere-Atmosphere Transfer Scheme and CLM4.5 - Community Land Model version 4.5) in the regional climate model. Studies over different regions have shown that CLM offers improvements in terms of land–atmosphere exchanges of moisture and energy and associated surface climate feedbacks compared with BATS. Our aim includes evaluating whether this is the case for the Carpathian region.</p><p>Four 1-year-long experiments both for 1981 and 2010 (excluding the spin-up time) are completed using the same domain, initial and lateral atmospheric boundary data conditions (i.e. ERA-Interim), with a 10 km spatial resolution. These years were chosen because 1981 was a normal year in terms of precipitation, while 2010 was the wettest year in Hungary from the beginning of the 20th century. We carry out a detailed analysis of RegCM outputs focusing not only on standard climatological variables (precipitation and temperature), but also on additional meteorological variables, which have important roles in the water cycle (e.g. soil moisture, evapotranspiration). The simulations are compared with the CARPATCLIM observed, homogenised, gridded dataset and other databases (ESA CCI Soil Moisture Product New Version Release (v04.5) and Surface Solar Radiation Data Set - Heliosat (SARAH)). It is found that the simulated near-surface temperature and precipitation are better represented in the CLM scheme than in the BATS when compared with observations, both over the lowland and mountainous area. The model simulations also show that the precipitation is overestimated more over mountainous area in 2010 than in 1981.  </p>

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