Impact of ozone on the carbon, heat and water fluxes in a land-surface model

2021 ◽  
Author(s):  
Noel Clancy ◽  
William Collins ◽  
Pier Luigi Vidale ◽  
Gerd Folberth
Keyword(s):  
Land Surface ◽  
Hydrological Cycle ◽  
Carbon Sink ◽  
Land Surface Model ◽  
Surface Model ◽  
Water Fluxes ◽  
Ozone Sensitivity ◽  
Energy Cycle ◽  
Earth’S Climate ◽  
Quantitative Impact

<p>Carbon uptake by land ecosystems is a hugely important carbon sink for the Earth's climate. Plants uptake carbon dioxide from the atmosphere via pores on the surface of their leaves called stomata. However, ozone can also be taken up by plants in this way leading to damage to the plant, a decrease in its growth rate and an impact on the carbon cycle. Ozone damage to plants also modifies other processes within the ecosystem such as transpiration and respiration rates, thereby effecting the hydrological cycle and energy cycle. The Joint UK Land and Environment Simulator (JULES) land-surface model includes ozone sensitivity parameters for all its vegetation cover (plant functional types). Our recent results from JULES experiments at FLUXNET sites show that ozone reduces photosynthesis and suppresses transpiration, thereby impacting the carbon, heat and water fluxes in JULES. Furthermore, we identify differences in a quantitative impact on leaf phenology.</p>

scholarly journals Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves

2021 ◽  
Author(s):  
Mengyuan Mu ◽  
Martin De Kauwe ◽  
Anna Ukkola ◽  
Andy Pitman ◽  
Teresa Gimeno ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Strong Impact ◽  
Water Fluxes ◽  
Land Surface Models ◽  
Groundwater Aquifer ◽  
Surface Models

<p>Land surface models underpin coupled climate model projections of droughts and heatwaves. However, the lack of simultaneous observations of individual components of evapotranspiration, concurrent with root-zone soil moisture, has limited previous model evaluations. Here, we use a comprehensive set of observations from a water-limited site in southeastern Australia including both evapotranspiration and soil moisture to a depth of 4.5 m to evaluate the Community Atmosphere-Biosphere Land Exchange (CABLE) land surface model. We demonstrate that alternative process representations within CABLE had the capacity to improve simulated evapotranspiration, but not necessarily soil moisture dynamics - highlighting problems of model evaluations against water fluxes alone. Our best simulation was achieved by resolving a soil evaporation bias; a more realistic initialisation of the groundwater aquifer state; higher vertical soil resolution informed by observed soil properties; and further calibrating soil hydraulic conductivity. Despite these improvements, the role of the empirical soil moisture stress function in influencing the simulated water fluxes remained important: using a site calibrated function reduced the soil water stress on plants by 36 % during drought and 23 % at other times. These changes in CABLE not only improve the seasonal cycle of evapotranspiration, but also affect the latent and sensible heat fluxes during droughts and heatwaves. The range of parameterisations tested led to differences of ~150 W m<sup>-2</sup> in the simulated latent heat flux during a heatwave, implying a strong impact of parameterisations on the capacity for evaporative cooling and feedbacks to the boundary layer (when coupled). Overall, our results highlight the opportunity to advance the capability of land surface models to capture water cycle processes, particularly during meteorological extremes, when sufficient observations of both evapotranspiration fluxes and soil moisture profiles are available.</p>

Hydrological impact of the new ECMWF multi-layer snow scheme

2021 ◽  
Author(s):  
Gabriele Arduini ◽  
Ervin Zsoter ◽  
Hannah Cloke ◽  
Elisabeth Stephens ◽  
Christel Prudhomme
Keyword(s):  
Land Surface ◽  
River Discharge ◽  
Hydrological Cycle ◽  
Land Surface Model ◽  
Single Layer ◽  
Observation Time ◽  
Surface Model ◽  
Earth System ◽  
Hydrological Impact ◽  
Energy And Momentum

<p>Snow processes, with the water stored in the snowpack and released as snowmelt, are very important components of the water balance, in particular in high latitude and mountain regions. The evolution of the snow cover and the timing of the snow melt can have major impact on river discharge. Land surface models are used in Earth System models to compute exchanges of water, energy and momentum between the atmosphere and the surface underneath, and also to compute other components of the hydrological cycle. In order to improve the snow representation, a new multi-layer snow scheme is under development in the HTESSEL land surface model of the European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), to replace the current single-layer snow scheme used in HTESSEL. The new scheme has already been shown to improve snow and 2‐metre temperature, while in this study, the wider hydrological impact is evaluated and documented.</p><p>The analysis is done in the reanalysis context by comparing two ERA5-forced offline HTESSEL experiments. The runoff output of HTESSEL is coupled to the CaMa-Flood hydrodynamic model in order to derive river discharge. The analysis is done globally for the period between 1980-2018. The evaluation was carried out using over 1000 discharge observation time-series with varying catchment size. The hydrological response of the multi-layer snow scheme is generally positive, but in some areas the improvement is not clear and can even be negative with deteriorated signal in river discharge. Further investigation is needed to understand the complex hydrological impact of the new snow scheme, making sure it contributes to an improved description of all hydrological components of the Earth System.</p>

scholarly journals Contrasting roles of interception and transpiration in the hydrological cycle – Part 1: Temporal characteristics over land

2014 ◽  
Vol 5 (2) ◽  
pp. 441-469 ◽  
Author(s):  
L. Wang-Erlandsson ◽  
R. J. van der Ent ◽  
L. J. Gordon ◽  
H. H. G. Savenije
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Land Surface Model ◽  
Open Water ◽  
Water Evaporation ◽  
Surface Model ◽  
Rain Event ◽  
Temporal Characteristics ◽  
Moisture Recycling

Abstract. Moisture recycling, the contribution of terrestrial evaporation to precipitation, has important implications for both water and land management. Although terrestrial evaporation consists of different fluxes (i.e. transpiration, vegetation interception, floor interception, soil moisture evaporation, and open-water evaporation), moisture recycling (terrestrial evaporation–precipitation feedback) studies have up to now only analysed their combined total. This paper constitutes the first of two companion papers that investigate the characteristics and roles of different evaporation fluxes for land–atmosphere interactions. Here, we investigate the temporal characteristics of partitioned evaporation on land and present STEAM (Simple Terrestrial Evaporation to Atmosphere Model) – a hydrological land-surface model developed to provide inputs to moisture tracking. STEAM estimates a mean global terrestrial evaporation of 73 900 km3 year-1, of which 59% is transpiration. Despite a relatively simple model structure, validation shows that STEAM produces realistic evaporative partitioning and hydrological fluxes that compare well with other global estimates over different locations, seasons, and land-use types. Using STEAM output, we show that the terrestrial residence timescale of transpiration (days to months) has larger inter-seasonal variation and is substantially longer than that of interception (hours). Most transpiration occurs several hours or days after a rain event, whereas interception is immediate. In agreement with previous research, our simulations suggest that the vegetation's ability to transpire by retaining and accessing soil moisture at greater depth is critical for sustained evaporation during the dry season. We conclude that the differences in temporal characteristics between evaporation fluxes are substantial and reasonably can cause differences in moisture recycling, which is investigated more in the companion paper (van der Ent et al., 2014, hereafter Part 2).

scholarly journals Recent Changes in the Moisture Source of Precipitation over the Tibetan Plateau

2017 ◽  
Vol 30 (5) ◽  
pp. 1807-1819 ◽  
Author(s):  
Chi Zhang ◽  
Qiuhong Tang ◽  
Deliang Chen
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Land Surface Model ◽  
Water Vapor Transport ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Precipitation Trend ◽  
Moisture Source ◽  
Moisture Supply

Abstract Evidence has suggested a wetting trend over part of the Tibetan Plateau (TP) in recent decades, although there are large uncertainties in this trend due to sparse observations. Examining the change in the moisture source for precipitation over a region in the TP with the most obvious increasing precipitation trend may help understand the precipitation change. This study applied the modified Water Accounting Model with two atmospheric reanalyses, ground-observed precipitation, and evaporation from a land surface model to investigate the change in moisture source of the precipitation over the targeted region. The study estimated that on average more than 69% and more than 21% of the moisture supply to precipitation over the targeted region came from land and ocean, respectively. The moisture transports from the west of the TP by the westerlies and from the southwest by the Indian summer monsoon likely contributed the most to precipitation over the targeted region. The moisture from inside the region may have contributed about 18% of the total precipitation. Most of the increased moisture supply to the precipitation during 1979–2013 was attributed to the enhanced influx from the southwest and the local moisture supply. The precipitation recycling ratio over the targeted region increased significantly, suggesting an intensified hydrological cycle. Further analysis at monthly scale and with wet–dry-year composites indicates that the increased moisture contribution was mainly from the southwest and the targeted region during May and September. The enhanced water vapor transport from the Indian Ocean during July and September and the intensified local hydrological recycling seem to be the primary reasons behind the recent precipitation increase over the targeted region.

scholarly journals Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves

2021 ◽  
Vol 25 (1) ◽  
pp. 447-471
Author(s):  
Mengyuan Mu ◽  
Martin G. De Kauwe ◽  
Anna M. Ukkola ◽  
Andy J. Pitman ◽  
Teresa E. Gimeno ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Strong Impact ◽  
Water Fluxes ◽  
Land Surface Models ◽  
Groundwater Aquifer ◽  
Surface Models

Abstract. Land surface models underpin coupled climate model projections of droughts and heatwaves. However, the lack of simultaneous observations of individual components of evapotranspiration, concurrent with root-zone soil moisture, has limited previous model evaluations. Here, we use a comprehensive set of observations from a water-limited site in southeastern Australia including both evapotranspiration and soil moisture to a depth of 4.5 m to evaluate the Community Atmosphere-Biosphere Land Exchange (CABLE) land surface model. We demonstrate that alternative process representations within CABLE had the capacity to improve simulated evapotranspiration, but not necessarily soil moisture dynamics–highlighting problems of model evaluations against water fluxes alone. Our best simulation was achieved by resolving a soil evaporation bias, using a more realistic initialisation of the groundwater aquifer state and higher vertical soil resolution informed by observed soil properties, and further calibrating soil hydraulic conductivity. Despite these improvements, the role of the empirical soil moisture stress function in influencing the simulated water fluxes remained important: using a site-calibrated function reduced the soil water stress on plants by 36 % during drought and 23 % at other times. These changes in CABLE not only improve the seasonal cycle of evapotranspiration but also affect the latent and sensible heat fluxes during droughts and heatwaves. The range of parameterisations tested led to differences of ∼150 W m−2 in the simulated latent heat flux during a heatwave, implying a strong impact of parameterisations on the capacity for evaporative cooling and feedbacks to the boundary layer (when coupled). Overall, our results highlight the opportunity to advance the capability of land surface models to capture water cycle processes, particularly during meteorological extremes, when sufficient observations of both evapotranspiration fluxes and soil moisture profiles are available.

Coupling an individual-based boreal forest model with a permafrost land-surface model to forecast biomass development in boreal larch forests at the Siberian treeline

2020 ◽  
Author(s):  
Simone Stünzi ◽  
Stefan Kruse ◽  
Julia Boike ◽  
Ulrike Herzschuh ◽  
Moritz Langer
Keyword(s):  
Land Surface ◽  
Boreal Forests ◽  
Environmental Changes ◽  
Carbon Sink ◽  
Land Surface Model ◽  
Radiation Budget ◽  
Surface Model ◽  
Data Set ◽  
Forest Model ◽  
Larch Forests

<p>The fate of boreal forests under global warming and forced rapid environmental changes is still highly uncertain, in terms of remaining a carbon sink or becoming a future carbon source. Forest dynamics and resulting ecosystem services are strongly interlinked in the vast permafrost-covered regions of the Siberian treeline ecotone. Consequently, understanding the role of current and future active layer dynamics is crucial for the prediction of aboveground biomass and thus carbon stock developments.</p><p>We present a coupled model version combining CryoGrid, a sophisticated one-dimensional permafrost land surface model adapted for the use in forest ecosystems, with LAVESI, a detailed, individual-based and spatially explicit larch forest model. Subsequently, parameterizing against an extensive field data set of >100 forest inventories conducted along the treeline of larch-dominated boreal forests in Siberia (97-169° E), we run simulations covering the upcoming decades under contrasting climatic change scenarios.</p><p>The model setup can reproduce the energy transfer and thermal regime in permafrost ground as well as the radiation budget, nitrogen and photosynthetic profiles, canopy turbulence and leaf fluxes and predict the expected establishment, die-off and treeline movements of larch forests. Our results will show vegetation and permafrost dynamics, quantify the magnitudes of different feedback processes between permafrost, vegetation, and climate and reveal their impact on carbon stocks in Northern Siberia.</p>

The detection of irrigation through remote sensing soil moisture and a land surface model: a case study in Spain

2020 ◽  
Author(s):  
Jacopo Dari ◽  
Pere Quintana-Seguí ◽  
María José Escorihuela ◽  
Luca Brocca ◽  
Renato Morbidelli ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Land Surface Model ◽  
Surface Model ◽  
Data Sets ◽  
Data Set ◽  
Agricultural Areas ◽  
Irrigation Practices

<p>Irrigation practices introduce imbalances in the natural hydrological cycle at different spatial scales and put pressure on water resources, especially under climate changing and population increasing scenarios. Despite the implications of irrigation on food production and on the rational management of the available freshwater, detailed information about the areas where irrigation actually occurs is still lacking. For this reason, the comprehensive knowledge of the dynamics of the hydrological cycle over agricultural areas is often tricky.</p><p>The first aim of this study is to evaluate the capability of five remote sensing soil moisture data sets to detect the irrigation signal over an intensely irrigated area located within the Ebro river basin, in the North of Spain, during the biennium 2016-2017. As a second objective, a methodology to map the irrigated areas through the K-means clustering algorithm is proposed. The remotely sensed soil moisture products used in this study are: SMOS (Soil Moisture and Ocean Salinity) at 1 km, SMAP (Soil Moisture Active Passive) at 1 km and 9 km, Sentinel-1 at 1 km and ASCAT (Advanced SCATterometer) at 12.5 km. The 1 km versions of SMOS and SMAP are DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled versions of the corresponding coarser resolution products. An additional data set of soil moisture simulated by the SURFEX-ISBA (<em>Surface Externalisée - Interaction Sol Biosphère Atmosphère</em>) land surface model is used as a support for the performed analyses.</p><p>The capability of soil moisture products to detect irrigation has been investigated by exploiting indices representing the spatial and temporal dynamics of soil moisture. The L-band passive microwave downscaled products, especially SMAP at 1 km, result the best performing ones in detecting the irrigation signal over the pilot area; on the basis of these data sets, the K-means algorithm has been employed to classify three kinds of surfaces within the study area: the dryland, the forest or natural areas, and the actually irrigated areas. The resulting maps have been validated by exploiting maps of crops in Catalonia as ground truth data set. The percentage of irrigated areas well classified by the proposed method reaches the value of 78%; this result is obtained for the period May - September 2017. In addition, the method performs well in distinguishing the irrigated areas from rainfed agricultural areas, which are dry during summer, thus representing a useful tool to obtain explicit spatial information about where irrigation practices actually occur over agricultural areas equipped for this purpose.</p>

scholarly journals Multimodel Analysis of Energy and Water Fluxes: Intercomparisons between Operational Analyses, a Land Surface Model, and Remote Sensing

2012 ◽  
Vol 13 (1) ◽  
pp. 3-26 ◽  
Author(s):  
Raghuveer K. Vinukollu ◽  
Justin Sheffield ◽  
Eric F Wood ◽  
Michael G. Bosilovich ◽  
David Mocko
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Land Surface Model ◽  
Global Scale ◽  
Heat Fluxes ◽  
Surface Model ◽  
Water Fluxes ◽  
Net Radiation ◽  
Energy Fluxes ◽  
Ensemble Mean

Abstract Using data from seven global model operational analyses (OA), one land surface model, and various remote sensing retrievals, the energy and water fluxes over global land areas are intercompared for 2003/04. Remote sensing estimates of evapotranspiration (ET) are obtained from three process-based models that use input forcings from multisensor satellites. An ensemble mean (linear average) of the seven operational (mean-OA) models is used primarily to intercompare the fluxes with comparisons performed at both global and basin scales. At the global scale, it is found that all components of the energy budget represented by the ensemble mean of the OA models have a significant bias. Net radiation estimates had a positive bias (global mean) of 234 MJ m−2 yr−1 (7.4 W m−2) as compared to the remote sensing estimates, with the latent and sensible heat fluxes biased by 470 MJ m−2 yr−1 (13.3 W m−2) and −367 MJ m−2 yr−1 (11.7 W m−2), respectively. The bias in the latent heat flux is affected by the bias in the net radiation, which is primarily due to the biases in the incoming shortwave and outgoing longwave radiation and to the nudging process of the operational models. The OA models also suffer from improper partitioning of the surface heat fluxes. Comparison of precipitation (P) analyses from the various OA models, gauge analysis, and remote sensing retrievals showed better agreement than the energy fluxes. Basin-scale comparisons were consistent with the global-scale results, with the results for the Amazon in particular showing disparities between OA and remote sensing estimates of energy fluxes. The biases in the fluxes are attributable to a combination of errors in the forcing from the OA atmospheric models and the flux calculation methods in their land surface schemes. The atmospheric forcing errors are mainly attributable to high shortwave radiation likely due to the underestimation of clouds, but also precipitation errors, especially in water-limited regions.

scholarly journals Global evaluation of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 (r5986)

2021 ◽  
Vol 14 (4) ◽  
pp. 1987-2010
Author(s):  
Yan Sun ◽  
Daniel S. Goll ◽  
Jinfeng Chang ◽  
Philippe Ciais ◽  
Betrand Guenet ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Production Efficiency ◽  
Carbon Sink ◽  
A Priori ◽  
Land Surface Model ◽  
Terrestrial Ecosystems ◽  
Surface Model ◽  
Global Evaluation ◽  
Biomass Turnover

Abstract. The availability of phosphorus (P) and nitrogen (N) constrains the ability of ecosystems to use resources such as light, water and carbon. In turn, nutrients impact the distribution of productivity, ecosystem carbon turnovers and their net exchange of CO2 with the atmosphere in response to variation of environmental conditions in both space and time. In this study, we evaluated the performance of the global version of the land surface model ORCHIDEE-CNP (v1.2), which explicitly simulates N and P biogeochemistry in terrestrial ecosystems coupled with carbon, water and energy transfers. We used data from remote sensing, ground-based measurement networks and ecological databases. Components of the N and P cycle at different levels of aggregation (from local to global) are in good agreement with data-driven estimates. When integrated for the period 1850 to 2017 forced with variable climate, rising CO2 and land use change, we show that ORCHIDEE-CNP underestimates the land carbon sink in the Northern Hemisphere (NH) during recent decades despite an a priori realistic gross primary productivity (GPP) response to rising CO2. This result suggests either that processes other than CO2 fertilization, which are omitted in ORCHIDEE-CNP such as changes in biomass turnover, are predominant drivers of the northern land sink and/or that the model parameterizations produce emerging nutrient limitations on biomass growth that are too strict in northern areas. In line with the latter, we identified biases in the simulated large-scale patterns of leaf and soil stoichiometry as well as plant P use efficiency, pointing towards P limitations that are too severe towards the poles. Based on our analysis of ecosystem resource use efficiencies and nutrient cycling, we propose ways to address the model biases by giving priority to better representing processes of soil organic P mineralization and soil inorganic P transformation, followed by refining the biomass production efficiency under increasing atmospheric CO2, phenology dynamics and canopy light absorption.

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