Study of the sensitivity of land-convection coupling in the European summer

2021 ◽  
Author(s):  
Lisa Jach ◽  
Thomas Schwitalla ◽  
Kirsten Warrach-Sagi ◽  
Volker Wulfmeyer
Keyword(s):  
Coupling Strength ◽  
Land Surface ◽  
Climate Models ◽  
Layer Structure ◽  
Regional Scale ◽  
Atmospheric Temperature ◽  
Global Climate Models ◽  
Limiting Factor ◽  
Perturbation Approach ◽  
Temperature And Humidity

<p>The state of the land surface can have a crucial influence on the triggering of convection. Investigations of the land-atmosphere coupling strength on the regional scale are still rare, and have been mainly performed using global climate models with coarse resolutions. Increasing the horizontal resolution and the concomitant improved representation of the land surface are expected to refine the representation of feedbacks. A strong limiting factor, especially for process-based studies of the link between surface moisture availability, land cover properties, and convection triggering, is the availability of data with sufficient vertical resolution and temporal coverage. A convenient metric to investigate this link is the ‘Convection Triggering Potential’-‘Low-Level Humidity Index’ framework, which is applied in this study. This process-based coupling metric examines the boundary layer structure based on temperature and humidity profiles to draw conclusions on the potential strength of interactions. However, increasing the resolution of a simulation usually aggravates the amount of storage capacity needed, and in practice the number of vertical levels written out is often decreased to a handful over the total column. Consequently, a comprehensive regional model intercomparison targeting land-convection coupling strength is challenging.</p><p>In this study, a perturbation approach was applied as an attempt to overcome this limitation. Differences in the choice and configuration of models cause a spread in mean and variance of atmospheric temperature and humidity between models that in turn may impact the outcome of the framework. Perturbation factors of different magnitudes were added to modify summer atmospheric temperature and humidity from a WRF simulation over the entire column on a daily basis. The simulation covered the period 1986-2015 over the EURO-CORDEX domain. The perturbations were chosen to approximate a potential model spread to some extent. Sensitivity in the coupling strength was assessed in relation to the unperturbed case by applying the framework to a range of perturbation cases with differently strong combinations of temperature and humidity changes.</p><p>We will present results 1) of how warmer, cooler, dryer or moister conditions in the atmosphere changed the frequency of summer days with high feedback potential, 2) how the different conditions influenced the occurrence of positive relative to negative feedbacks, and 3) of spatial differences in the sensitivity of the coupling strength to temperature or humidity modifications, respectively, over Europe.</p>

scholarly journals Quantifying the added value of high resolution climate models: A systematic comparison of WRF simulations for complex Himalayan terrain

2017 ◽  
Author(s):  
Ramchandra Karki ◽  
Shabeh Hasson ◽  
Lars Gerlitz ◽  
Udo Schickhoff ◽  
Thomas Scholten ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Regional Scale ◽  
Wrf Model ◽  
Global Climate Models ◽  
Added Value ◽  
Cold Bias ◽  
Near Surface ◽  
Monsoonal Precipitation ◽  
High Elevations

Abstract. Mesoscale dynamical refinements of global climate models or atmospheric reanalysis have shown their potential to resolve the intricate atmospheric processes, their land surface interactions, and subsequently, realistic distribution of climatic fields in complex terrains. Given that such potential is yet to be explored within the central Himalayan region of Nepal, we investigate the skill of the Weather Research and Forecasting (WRF) model with different spatial resolutions in reproducing the spatial, seasonal and diurnal characteristics of the near-surface air temperature and precipitation, as well as, the spatial shifts in the diurnal monsoonal precipitation peak over the Khumbu (Everest), Rolwaling and adjacent southern areas. Therefore, the ERA-Interim (0.75°) reanalysis has been dynamically refined to 25, 5 and 1 km (D1, D2 and D3) for one complete hydrological year (Oct 2014–Sep 2015), using the one-way nested WRF model run with mild-nudging and parameterized convection for the outer but explicitly resolved convection for the inner domains. Our results suggest that D3 realistically reproduces the monsoonal precipitation, as compared to its underestimation by D1 but overestimation by D2. All three resolutions however overestimate precipitation from the westerly disturbances, owing to simulating anomalously higher intensity of few intermittent events. Temperatures are though generally well reproduced by all resolutions, winter and pre-monsoon seasons feature a high cold bias for high elevations while lower show a simultaneous warm bias. Contrary to higher resolutions, D1 fails to realistically reproduce the regional-scale nocturnal monsoonal peak precipitation observed at the Himalayan foothills and its diurnal shift towards high elevations, whereas D2 resolves these characteristics but exhibits a limited skill in reproducing such peak at the river valley scale due to the limited representation of the narrow valleys at 5 km resolution. Nonetheless, featuring a substantial skill over D1 and D2, D3 simulates almost realistic shapes of the seasonal and diurnal precipitation and the peak timings even at valley scales. These findings clearly suggest an added value of the convective scale resolutions in realistically resolving the topo-climates over the central Himalaya, which in turn allow simulating their interactions with the synoptic scale weather systems prevailing over High Asia.

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 Influence of the representation of convection on the mid-Holocene West African Monsoon

2021 ◽  
Vol 17 (4) ◽  
pp. 1665-1684
Author(s):  
Leonore Jungandreas ◽  
Cathy Hohenegger ◽  
Martin Claussen
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Monsoon Season ◽  
West African Monsoon ◽  
West African ◽  
Global Climate Models ◽  
African Monsoon ◽  
Monsoonal Precipitation

Abstract. Global climate models experience difficulties in simulating the northward extension of the monsoonal precipitation over north Africa during the mid-Holocene as revealed by proxy data. A common feature of these models is that they usually operate on grids that are too coarse to explicitly resolve convection, but convection is the most essential mechanism leading to precipitation in the West African Monsoon region. Here, we investigate how the representation of tropical deep convection in the ICOsahedral Nonhydrostatic (ICON) climate model affects the meridional distribution of monsoonal precipitation during the mid-Holocene by comparing regional simulations of the summer monsoon season (July to September; JAS) with parameterized and explicitly resolved convection. In the explicitly resolved convection simulation, the more localized nature of precipitation and the absence of permanent light precipitation as compared to the parameterized convection simulation is closer to expectations. However, in the JAS mean, the parameterized convection simulation produces more precipitation and extends further north than the explicitly resolved convection simulation, especially between 12 and 17∘ N. The higher precipitation rates in the parameterized convection simulation are consistent with a stronger monsoonal circulation over land. Furthermore, the atmosphere in the parameterized convection simulation is less stably stratified and notably moister. The differences in atmospheric water vapor are the result of substantial differences in the probability distribution function of precipitation and its resulting interactions with the land surface. The parametrization of convection produces light and large-scale precipitation, keeping the soils moist and supporting the development of convection. In contrast, less frequent but locally intense precipitation events lead to high amounts of runoff in the explicitly resolved convection simulations. The stronger runoff inhibits the moistening of the soil during the monsoon season and limits the amount of water available to evaporation in the explicitly resolved convection simulation.

A simple approach to mimic the effect of active vegetation in hydrological models to better estimate hydrological variables under climate change

2021 ◽  
Author(s):  
Thedini Asali Peiris ◽  
Petra Döll
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Global Climate Models ◽  
Hydrological Models ◽  
Net Radiation ◽  
Ensemble Mean ◽  
The Impact

<p>Unlike global climate models, hydrological models cannot simulate the feedbacks among atmospheric processes, vegetation, water, and energy exchange at the land surface. This severely limits their ability to quantify the impact of climate change and the concurrent increase of atmospheric CO<sub>2</sub> concentrations on evapotranspiration and thus runoff. Hydrological models generally calculate actual evapotranspiration as a fraction of potential evapotranspiration (PET), which is computed as a function of temperature and net radiation and sometimes of humidity and wind speed. Almost no hydrological model takes into account that PET changes because the vegetation responds to changing CO<sub>2</sub> and climate. This active vegetation response consists of three components. With higher CO<sub>2</sub> concentrations, 1) plant stomata close, reducing transpiration (physiological effect) and 2) plants may grow better, with more leaves, increasing transpiration (structural effect), while 3) climatic changes lead to changes in plants growth and even biome shifts, changing evapotranspiration. Global climate models, which include dynamic vegetation models, simulate all these processes, albeit with a high uncertainty, and take into account the feedbacks to the atmosphere.</p><p>Milly and Dunne (2016) (MD) found that in the case of RCP8.5 the change of PET (computed using the Penman-Monteith equation) between 1981- 2000 and 2081-2100 is much higher than the change of non-water-stressed evapotranspiration (NWSET) computed by an ensemble of global climate models. This overestimation is partially due to the neglect of active vegetation response and partially due to the neglected feedbacks between the atmosphere and the land surface.</p><p>The objective of this paper is to present a simple approach for hydrological models that enables them to mimic the effect of active vegetation on potential evapotranspiration under climate change, thus improving computation of freshwater-related climate change hazards by hydrological models. MD proposed an alternative approach to estimate changes in PET for impact studies that is only a function of the changes in energy and not of temperature and achieves a good fit to the ensemble mean change of evapotranspiration computed by the ensemble of global climate models in months and grid cells without water stress. We developed an implementation of the MD idea for hydrological models using the Priestley-Taylor equation (PET-PT) to estimate PET as a function of net radiation and temperature. With PET-PT, an increasing temperature trend leads to strong increases in PET. Our proposed methodology (PET-MD) helps to remove this effect, retaining the impact of temperature on PET but not on long-term PET change.</p><p>We implemented the PET-MD approach in the global hydrological model WaterGAP2.2d. and computed daily time series of PET between 1981 and 2099 using bias-adjusted climate data of four global climate models for RCP 8.5. We evaluated, computed PET-PT and PET-MD at the grid cell level and globally, comparing also to the results of the Milly-Dunne study. The global analysis suggests that the application of PET-MD reduces the PET change until the end of this century from 3.341 mm/day according to PET-PT to 3.087 mm/day (ensemble mean over the four global climate models).</p><p>Milly, P.C.D., Dunne K.A. (2016). DOI:10.1038/nclimate3046.</p>

scholarly journals Calculating the turbulent fluxes in the atmospheric surface layer with neural networks

2018 ◽  
Author(s):  
Lukas Hubert Leufen ◽  
Gerd Schädler
Keyword(s):  
Land Surface ◽  
Field Experiments ◽  
Climate Models ◽  
Similarity Theory ◽  
Turbulent Fluxes ◽  
Global Climate Models ◽  
Surface Model ◽  
Time Step ◽  
One Dimensional ◽  
Stability Functions

Abstract. The turbulent fluxes of momentum, heat and water vapour link the Earth's surface with the atmosphere. The correct modelling of the flux interactions between these two systems with very different time scales is therefore vital for climate (resp. Earth system) models. Conventionally, these fluxes are modelled using Monin–Obukhov similarity theory (MOST) with stability functions derived from a small number of field experiments; this results in a range of formulations of these functions and thus also in the flux calculations; furthermore, the underlying equations are non-linear and have to be solved iteratively at each time step of the model. For these reasons, we tried here a different approach, namely using an artificial neural network (ANN) to calculate the fluxes resp. the scaling quantities u* and θ*, thus avoiding explicit formulas for the stability functions. The network was trained and validated with multi-year datasets from seven grassland, forest and wetland sites worldwide using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton backpropagation algorithm and six-fold cross validation. Extensive sensitivity tests showed that an ANN with six input variables and one hidden layer gave results comparable to (and in some cases even slightly better than) the standard method. Similar satisfying results were obtained when the ANN routine was implemented in a one-dimensional stand alone land surface model (LSM), opening the way to implementation in three-dimensional climate models. In case of the one-dimensional LSM, no CPU time was saved when using the ANN version, since the small time step of the standard version required only one iteration in most cases. This could be different in models with longer time steps, e.g. global climate models.

scholarly journals Terrestrial Aridity and Its Response to Greenhouse Warming across CMIP5 Climate Models

2015 ◽  
Vol 28 (14) ◽  
pp. 5583-5600 ◽  
Author(s):  
Jacob Scheff ◽  
Dargan M. W. Frierson
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Aridity Index ◽  
Global Climate Models ◽  
Greenhouse Warming ◽  
Dimensionless Ratio ◽  
The Tropics

Abstract The aridity of a terrestrial climate is often quantified using the dimensionless ratio of annual precipitation (P) to annual potential evapotranspiration (PET). In this study, the climatological patterns and greenhouse warming responses of terrestrial P, Penman–Monteith PET, and are compared among 16 modern global climate models. The large-scale climatological values and implied biome types often disagree widely among models, with large systematic differences from observational estimates. In addition, the PET climatologies often differ by several tens of percent when computed using monthly versus 3-hourly inputs. With greenhouse warming, land P does not systematically increase or decrease, except at high latitudes. Therefore, because of moderate, ubiquitous PET increases, decreases (drying) are much more widespread than increases (wetting) in the tropics, subtropics, and midlatitudes in most models, confirming and expanding on earlier findings. The PET increases are also somewhat sensitive to the time resolution of the inputs, although not as systematically as for the PET climatologies. The changes in the balance between P and PET are also quantified using an alternative aridity index, the ratio , which has a one-to-one but nonlinear correspondence with . It is argued that the magnitudes of changes are more uniformly relevant than the magnitudes of changes, which tend to be much higher in wetter regions. The ratio and its changes are also found to be excellent statistical predictors of the land surface evaporative fraction and its changes.

One stomatal model to rule them all? Evaluating competing hypotheses to regulate the exchange of carbon and water against experimental data

2020 ◽  
Author(s):  
Manon Sabot ◽  
Martin De Kauwe ◽  
Belinda Medlyn ◽  
Andy Pitman
Keyword(s):  
Stomatal Conductance ◽  
Land Surface ◽  
Model Comparison ◽  
Climate Models ◽  
Global Climate ◽  
Model Performance ◽  
Vapour Pressure Deficit ◽  
Global Climate Models ◽  
Model Complexity ◽  
Coupled Climate Models

<p>Nearly 2/3 of the annual global evapotranspiration (ET) over land arises from the vegetation. Yet, coupled-climate models only attribute between 22% – 58% of the annual terrestrial ET to plants. In coupled-climate models, the exchange of carbon and water between the terrestrial biosphere and the atmosphere is simulated by land-surface models (LSMs). Within those LSMs, stomatal conductance (g<sub>s</sub>) models allow plants to regulate their transpiration and carbon uptake, but most are empirically linked to climate, soil moisture availabilty, and CO<sub>2</sub>. Therefore, how and which g<sub>s</sub> schemes are implemented within LSMs is a key source of model uncertainty. This uncertainty has led to considerable investment in theory development in the recent years; multiple alternative hypotheses of optimal leaf-level regulation of gas exchange have been proposed as solutions to reduce existing model biases. However, a systematic inter-model evaluation is lacking (i.e. inter-model comparison within a single framework is needed to understand how different mechanistic assumptions across these new g<sub>s</sub> models affect plant behaviour). Here, we asked how, and under what conditions, nine novel optimal g<sub>s</sub> models differ from one another. The models were trained to match under average conditions before being subjected to: (i) a dry-down, (ii) high vapour pressure deficit, and (iii) elevated CO<sub>2</sub>. These experiments allowed us to identify the models’ specific responses and sensitivities. To further assess whether the models’ responses were realistic, we tested them against photosynthetic and hydraulic field data measured along mesic-xeric gradients in Europe and Australia. Finally, we evaluated model performance versus model complexity and the amount of information taken in by each model, which enables us to make recommendations regarding the use of stomatal conductance schemes in global climate models.</p>

scholarly journals Complexity of Snow Schemes in a Climate Model and Its Impact on Surface Energy and Hydrology

2012 ◽  
Vol 13 (2) ◽  
pp. 521-538 ◽  
Author(s):  
Emanuel Dutra ◽  
Pedro Viterbo ◽  
Pedro M. A. Miranda ◽  
Gianpaolo Balsamo
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Climate Models ◽  
Climate Model ◽  
Single Layer ◽  
Atmospheric Temperature ◽  
Soil Freezing ◽  
Near Surface ◽  
Northern Latitudes ◽  
Tightly Coupled

Abstract Three different complexity snow schemes implemented in the ECMWF land surface scheme Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) are evaluated within the EC-EARTH climate model. The snow schemes are (i) the original HTESSEL single-bulk-layer snow scheme, (ii) a new snow scheme in operations at ECMWF since September 2009, and (iii) a multilayer version of the previous. In offline site simulations, the multilayer scheme outperforms the single-layer schemes in deep snowpack conditions through its ability to simulate sporadic melting events thanks to the lower thermal inertial of the uppermost layer. Coupled atmosphere–land/snow simulations performed by the EC-EARTH climate model are validated against remote sensed snow cover and surface albedo. The original snow scheme has a systematic early melting linked to an underestimation of surface albedo during spring that was partially reduced with the new snow schemes. A key process to improve the realism of the near-surface atmospheric temperature and at the same time the soil freezing is the thermal insulation of the snowpack (tightly coupled with the accuracy of snow mass and density simulations). The multilayer snow scheme outperforms the single-layer schemes in open deep snowpack (such as prairies or tundra in northern latitudes) and is instead comparable in shallow snowpack conditions. However, the representation of orography in current climate models implies limitations for accurately simulating the snowpack, particularly over complex terrain regions such as the Rockies and the Himalayas.

scholarly journals Cold season emissions dominate the Arctic tundra methane budget

2015 ◽  
Vol 113 (1) ◽  
pp. 40-45 ◽  
Author(s):  
Donatella Zona ◽  
Beniamino Gioli ◽  
Róisín Commane ◽  
Jakob Lindaas ◽  
Steven C. Wofsy ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Regional Scale ◽  
Terrestrial Ecosystems ◽  
Arctic Tundra ◽  
Cold Season ◽  
Global Climate Models ◽  
The Arctic ◽  
Late Season ◽  
Aircraft Data

Arctic terrestrial ecosystems are major global sources of methane (CH4); hence, it is important to understand the seasonal and climatic controls on CH4 emissions from these systems. Here, we report year-round CH4 emissions from Alaskan Arctic tundra eddy flux sites and regional fluxes derived from aircraft data. We find that emissions during the cold season (September to May) account for ≥50% of the annual CH4 flux, with the highest emissions from noninundated upland tundra. A major fraction of cold season emissions occur during the “zero curtain” period, when subsurface soil temperatures are poised near 0 °C. The zero curtain may persist longer than the growing season, and CH4 emissions are enhanced when the duration is extended by a deep thawed layer as can occur with thick snow cover. Regional scale fluxes of CH4 derived from aircraft data demonstrate the large spatial extent of late season CH4 emissions. Scaled to the circumpolar Arctic, cold season fluxes from tundra total 12 ± 5 (95% confidence interval) Tg CH4 y−1, ∼25% of global emissions from extratropical wetlands, or ∼6% of total global wetland methane emissions. The dominance of late-season emissions, sensitivity to soil environmental conditions, and importance of dry tundra are not currently simulated in most global climate models. Because Arctic warming disproportionally impacts the cold season, our results suggest that higher cold-season CH4 emissions will result from observed and predicted increases in snow thickness, active layer depth, and soil temperature, representing important positive feedbacks on climate warming.

scholarly journals Observing regional-scale pack-ice decay processes with helicopter-borne sensors and moored upward-looking sonars

2011 ◽  
Vol 52 (57) ◽  
pp. 35-42 ◽  
Author(s):  
Simon J. Prinsenberg ◽  
Ingrid K. Peterson
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Spatial Scales ◽  
Regional Scale ◽  
Global Climate Models ◽  
First Year ◽  
Coarse Scale ◽  
Interaction Processes ◽  
Pack Ice ◽  
Ice Floes

AbstractThe variability of Arctic pack-ice parameters (e.g. extent and ice type) has been monitored by satellite-borne sensors since the early 1960s, and information on ice thickness is now becoming available from satellite altimeters. However, the spatial resolution of satellite-derived ice properties is too coarse to validate fine-scale ice variability generated by regional-scale interaction processes that affect the coarse-scale pack-ice albedo, strength and decay. To understand these regional processes, researchers rely on other data-monitoring platforms such as moored upward-looking sonars and helicopter-borne sensors. Backed by observations, two such regional-scale pack-ice decay processes are discussed: the break-up of large pack-ice floes by long-period waves generated by distant storms, and the spring decay of first-year-ice ridges in a diverging pack-ice environment. These two processes, although occurring on regional spatial scales, are important contributors to the evolution of the total pack ice and need to be included in global climate models, especially as the conditions for their occurrence will alter due to climate change.

Sign in / Sign up

Export Citation Format

Share Document