Did the rise of highly-transpiring angiosperms influenced Cretaceous climate ? A modelling approach with the IPSL atmosphere-land surface model.

2020 ◽  
Author(s):  
Julia Bres ◽  
Pierre Sepulchre ◽  
Nicolas Vuichard ◽  
Nicolas Viovy
Keyword(s):  
Stomatal Conductance ◽  
Land Surface ◽  
Fossil Record ◽  
Hydrological Cycle ◽  
Land Surface Model ◽  
Plant Evolution ◽  
Surface Model ◽  
Vegetation Model ◽  
Leaf Vein ◽  
Modelling Approach

<p><span><span>The Cretaceous angiosperm radiation was a major event for terrestrial plant evolution, and flowering plants represent more than 94 % of present-day plant diversity. The fossil record shows that angiosperm leaf vein densities reached particularly high values (> 12 mm/mm</span></span><sup><span><span>2</span></span></sup><span><span>)</span></span> <span><span>between the </span></span><span>Albian and the Cenomanian (108–94 Ma) </span><span><span>compared to gymnosperms (~ 2.5 mm/mm</span></span><sup><span><span>2</span></span></sup><span><span>). Empirical models</span></span> <span><span>also suggest that stomatal conductance to water vapour increases as a response to higher leaf vein densities. How much do this shift to higher values of stomatal conductance have modified the continental transpiration budget,</span></span> <span><span>and ultimately global hydrological cycle ? To address this question we used the IPSL coupled atmosphere-vegetation model forced by Cretaceous boundary conditions, and built plant functional types including</span></span> <span><span>stomatal conductance values consistent with the fossil record. We quantify the transpiration fluxes through different sensitivity experiments and explore the vegetation-atmosphere feedbacks and their impact on the Cretaceous climate.</span></span></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 Observed nighttime conductance alters modeled global hydrology and carbon budgets

2015 ◽  
Vol 8 (12) ◽  
pp. 10339-10363 ◽  
Author(s):  
D. L. Lombardozzi ◽  
M. J. B. Zeppel ◽  
R. A. Fisher ◽  
A. Tawfik
Keyword(s):  
Stomatal Conductance ◽  
Land Surface ◽  
Arid Regions ◽  
Land Surface Model ◽  
Carbon Gain ◽  
Surface Model ◽  
Land Surface Models ◽  
Climate Simulations ◽  
Surface Models ◽  
Semi Arid

Abstract. The terrestrial biosphere regulates climate through carbon, water, and energy exchanges with the atmosphere. Land surface models estimate plant transpiration, which is actively regulated by stomatal pores, and provide projections essential for understanding Earth's carbon and water resources. Empirical evidence from 204 species suggests that significant amounts of water are lost through leaves at night, though land surface models typically reduce stomatal conductance to nearly zero at night. Here, we apply observed nighttime stomatal conductance values to a global land surface model, to better constrain carbon and water budgets. We find that our modifications increase transpiration up to 5 % globally, reduce modeled available soil moisture by up to 50 % in semi-arid regions, and increase the importance of the land surface on modulating energy fluxes. Carbon gain declines up to ~ 4 % globally and > 25 % in semi-arid regions. We advocate for realistic constraints of minimum stomatal conductance in future climate simulations, and widespread field observations to improve parameterizations.

scholarly journals Comparative Evaluation of Hydrological Cycle in South and North Korea using a Land Surface Model

2017 ◽  
Vol 19 (1) ◽  
pp. 16-29
Author(s):  
Sung-uk Song ◽  
Jinwook Lee ◽  
Eunsaem Cho ◽  
Chulsang Yoo
Keyword(s):  
Land Surface ◽  
North Korea ◽  
Comparative Evaluation ◽  
Hydrological Cycle ◽  
Land Surface Model ◽  
Surface Model

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>

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 Averaging over spatiotemporal heterogeneity substantially biases evapotranspiration rates in a mechanistic large-scale land evaporation model

2020 ◽  
Author(s):  
Elham Rouholahnejad Freund ◽  
Massimiliano Zappa ◽  
James W. Kirchner
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Land Surface Model ◽  
Aggregation Bias ◽  
Surface Model ◽  
Land Surface Models ◽  
Evaporation Model ◽  
Surface Models ◽  
Large Scale Land

Abstract. Evapotranspiration (ET) influences land-climate interactions, regulates the hydrological cycle, and contributes to the Earth's energy balance. Due to its feedbacks to large-scale hydrological processes and its impact on atmospheric dynamics, ET is a key driver of droughts and heatwaves. Existing land surface models differ substantially, both in their estimates of current ET fluxes and in their projections of how ET will evolve in the future. Any bias in estimated ET fluxes will affect the partitioning between sensible and latent heat, and thus alter model predictions of temperature and precipitation. One potential source of bias is the so-called aggregation bias that arises whenever nonlinear processes, such as those that regulate ET fluxes, are modeled using averages of heterogeneous inputs. Here we demonstrate a general mathematical approach to quantifying and correcting for this aggregation bias, using the GLEAM land evaporation model as a relatively simple example. We demonstrate that this aggregation bias can lead to substantial overestimates in ET fluxes in a typical large-scale land surface model when sub-grid heterogeneities in land surface properties are averaged out. Using Switzerland as a test case, we examine the scale-dependence of this aggregation bias and show that it can lead to overestimation of daily ET fluxes by as much as 21 % averaged over the whole country. We show how our approach can be used to identify the dominant drivers of aggregation bias, and to estimate sub-grid closure relationships that can correct for aggregation biases in ET estimates, without explicitly representing sub-grid heterogeneities in large-scale land surface models.

Sign in / Sign up

Export Citation Format

Share Document