A Full Characterisation of Stars and Planets through High Resolution Spectroscopy and 3D Simulations.

2021 ◽  
Author(s):  
Maria Chiara Maimone ◽  
Andrea Chiavassa ◽  
Jeremy Leconte ◽  
Matteo Brogi

<p>The study of exoplanets atmospheres is one of the most intriguing challenges in the exoplanet field nowadays and the High Resolution Spectroscopy (HRS) has recently emerged as one of the leading methods for detecting atomic and molecular species in their atmospheres (e.g., Birkby, 2018). While this technique is particularly robust against contaminant absorption in the Earth’s atmosphere, the non-stationary stellar spectrum, in the form of either Doppler shift or distortion of the line profile during planetary transits, creates a non-negligible source of noise that can alter or even prevent detection. In the last years, it has become computationally possible to simulate the stellar surface convection that, in the end, allows to correctly reproduce asymmetric and blue-shifted spectral lines due to the granulation pattern of the stellar disk, which is a very important source of uncertainties (Chiavassa & Brogi, 2019). In the context of HRS and on the planet hand side, only recently multidimensional models have been used to detect the weak planet signal in the spectrum (e.g., Flowers et al. 2019).</p> <p>However, these numerical simulations have been computed independently for star and planet so far, while acquired spectra are the result of the natural coupling at each phase along the planet orbit. A next step forward is needed: coupling stellar and planetary 3D models dynamics during the transit.</p> <p>I will present the unprecedented precise synthetic spectra obtained with the upgraded 3D radiative transfer code Optim3D (Chiavassa et al. 2009). Optim3D takes as inputs the state-of-art 3D RHD stellar simulations (Stagger code, Nordlund et al. 2009, Magic et al. 2013) and the 3D Global Climate Models (SPARC/MITgcms, Showman et al. 2009, Parmentier et al. 2021) for stars and planets respectively, coupling them at any phase along the planet orbit. I will show the impact of this new approach on the detection of molecules by cross-correlating our spectra with HRS observations (e.g., Snellen et al 2010 and Brogi et al. 2016). This approach is particularly advantageous for those molecular species that are present in both the atmospheres and form in the same region of the spectrum, resulting in mixed and overlapped spectral lines (e.g. CO and H2O, crucial to constrain the C/O ratio). Moreover, the use of 3D models provides us with information about the dynamics processes at play, such as stellar convection and planetary winds.</p> <p> </p>

2020 ◽  
Author(s):  
Maria Chiara Maimone ◽  
Andrea Chiavassa ◽  
Jeremy Leconte ◽  
Matteo Brogi

<p>The study of exoplanets atmospheres is one of the most intriguing challenges in exoplanet field nowadays and the High Resolution Spectroscopy (HRS) has recently emerged as one of the leading methods for detecting atomic and molecular species in their atmospheres. In terms of numbers, if we define the resolution power R,<span class="Apple-converted-space">  </span>where λ is the wavelength and Δλ is the spectral resolution:</p> <p><span class="Apple-converted-space">     R= λ/Δλ</span></p> <p>then, “High Resolution Spectroscopy” means R > 50 000.</p> <p>Nevertheless extraordinary results have been achieved (Birkby, 2018), High Resolution Spectroscopy alone is not enough. 1D models of the host star have been coupled to HRS observations, but they do not reproduce the complexity of stellar convection mechanism (Chiavassa & Brogi, 2019). On the contrary,<span class="Apple-converted-space">  </span>3D Radiative Hydrodynamical simulations (3D RHS) take it into account intrinsically, allowing us to correctly reproduce asymmetric and blue-shifted spectral lines due to the granulation pattern of the stellar disk, which is a very important source of uncertainties at this resolution level (Chiavassa et al. 2017).</p> <p>However, numerical simulations have been computed independently for star and planet so far, while the acquired spectra are an entanglement of both the signals. In particular, some molecular species (e.g, CO) form in the same region of the spectrum, thus planetary and stellar spectral lines are completely mixed and overlapped.<span class="Apple-converted-space"> </span></p> <p>Therefore, a next step forward is needed: computing stellar and planetary models <em>together.</em></p> <p>With our work, we aim at upgrading the already-in-place 3D radiative transfer code Optim3D (Chiavassa et al. 2009) —largely used for stellar purposes so far — to taking into account also the exoplanetary contribution.<span class="Apple-converted-space"> </span>We propose to use simultaneously 3D RHS, performed for stars, and the innovative Global Climate Model (GCM), drawn up for exoplanets, in order to generate unprecedented precise synthetic spectra. As a springboard to test the code, we are carrying out the analysis of CO and H2O molecules on the well-know benchmark HD189733. Indeed, to disentangle those star’s and its companion’s signals due to the same molecules is one of the most challenging problems. In the end, we will be able to compute a complete dynamic characterisation: on one side, a precise knowledge of the stellar dynamic (i.e. convection-related surface structures) would allow to extract unequivocally the planetary signal; on the other one, a well-modelled dynamic of the planet (i.e. depth, shape, and position of spectral lines) would provide us with considerable information about the planetary atmospheric circulation.</p>


2013 ◽  
Vol 14 (4) ◽  
pp. 1175-1193 ◽  
Author(s):  
Irena Ott ◽  
Doris Duethmann ◽  
Joachim Liebert ◽  
Peter Berg ◽  
Hendrik Feldmann ◽  
...  

Abstract The impact of climate change on three small- to medium-sized river catchments (Ammer, Mulde, and Ruhr) in Germany is investigated for the near future (2021–50) following the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario. A 10-member ensemble of hydrological model (HM) simulations, based on two high-resolution regional climate models (RCMs) driven by two global climate models (GCMs), with three realizations of ECHAM5 (E5) and one realization of the Canadian Centre for Climate Modelling and Analysis version 3 (CCCma3; C3) is established. All GCM simulations are downscaled by the RCM Community Land Model (CLM), and one realization of E5 is downscaled also with the RCM Weather Research and Forecasting Model (WRF). This concerted 7-km, high-resolution RCM ensemble provides a sound basis for runoff simulations of small catchments and is currently unique for Germany. The hydrology for each catchment is simulated in an overlapping scheme, with two of the three HMs used in the project. The resulting ensemble hence contains for each chain link (GCM–realization–RCM–HM) at least two members and allows the investigation of qualitative and limited quantitative indications of the existence and uncertainty range of the change signal. The ensemble spread in the climate change signal is large and varies with catchment and season, and the results show that most of the uncertainty of the change signal arises from the natural variability in winter and from the RCMs in summer.


Author(s):  
Mark D. Risser ◽  
Michael F. Wehner

Abstract. Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern global high-resolution models with a horizontal resolution of tens of kilometers, this is an oversight since there are likely grid cells where the physical output of a climate model is compared with a statistically interpolated quantity instead of actual measurements of the climate system. In this paper, we quantify the impact of geographic sampling on the relative performance of high-resolution climate model representations of precipitation extremes in boreal winter (December–January–February) over the contiguous United States (CONUS), comparing model output from five early submissions to the HighResMIP subproject of the CMIP6 experiment. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance. Across the models considered, failing to account for sampling impacts the different metrics (extreme bias, spatial pattern correlation, and spatial variability) in different ways (both increasing and decreasing). We argue that the geographic sampling of weather stations should be accounted for in order to yield a more straightforward and appropriate comparison between models and observational data sets, particularly for high-resolution models with a horizontal resolution of tens of kilometers. While we focus on the CONUS in this paper, our results have important implications for other global land regions where the sampling problem is more severe.


2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.


2021 ◽  
Author(s):  
Mickaël Lalande ◽  
Martin Ménégoz ◽  
Gerhard Krinner

<p>The High Mountains of Asia (HMA) region and the Tibetan Plateau (TP), with an average altitude of 4000 m, are hosting the third largest reservoir of glaciers and snow after the two polar ice caps, and are at the origin of strong orographic precipitation. Climate studies over HMA are related to serious challenges concerning the exposure of human infrastructures to natural hazards and the water resources for agriculture, drinking water, and hydroelectricity to whom several hundred million inhabitants of the Indian subcontinent are depending. However, climate variables such as temperature, precipitation, and snow cover are poorly described by global climate models because their coarse resolution is not adapted to the rugged topography of this region. Since the first CMIP exercises, a cold model bias has been identified in this region, however, its attribution is not obvious and may be different from one model to another. Our study focuses on a multi-model comparison of the CMIP6 simulations used to investigate the climate variability in this area to answer the next questions: (1) are the biases in HMA reduced in the new generation of climate models? (2) Do the model biases impact the simulated climate trends? (3) What are the links between the model biases in temperature, precipitation, and snow cover extent? (4) Which climate trajectories can be projected in this area until 2100? An analysis of 27 models over 1979-2014 still show a cold bias in near-surface air temperature over the HMA and TP reaching an annual value of -2.0 °C (± 3.2 °C), associated with an over-extended relative snow cover extent of 53 % (± 62 %), and a relative excess of precipitation of 139 % (± 38 %), knowing that the precipitation biases are uncertain because of the undercatch of solid precipitation in observations. Model biases and trends do not show any clear links, suggesting that biased models should not be excluded in trend and projections analysis, although non-linear effects related to lagged snow cover feedbacks could be expected. On average over 2081-2100 with respect to 1995-2014, for the scenarios SSP126, SSP245, SSP370, and SSP585, the 9 available models shows respectively an increase in annual temperature of 1.9 °C (± 0.5 °C), 3.4 °C (± 0.7 °C), 5.2 °C (± 1.2 °C), and 6.6 °C (± 1.5 °C); a relative decrease in the snow cover extent of 10 % (± 4.1 %), 19 % (± 5 %), 29 % (± 8 %), and 35 % (± 9 %); and an increase in total precipitation of 9 % (± 5 %), 13 % (± 7 %), 19 % (± 11 %), and 27 % (± 13 %). Further analyses will be considered to investigate potential links between the biases at the surface and those at higher tropospheric levels as well as with the topography. The models based on high resolution do not perform better than the coarse-gridded ones, suggesting that the race to high resolution should be considered as a second priority after the developments of more realistic physical parameterizations.</p>


2018 ◽  
Vol 45 (8) ◽  
pp. 3728-3736 ◽  
Author(s):  
Penelope Maher ◽  
Geoffrey K. Vallis ◽  
Steven C. Sherwood ◽  
Mark J. Webb ◽  
Philip G. Sansom

2021 ◽  
Vol 12 (3) ◽  
pp. 919-938
Author(s):  
Mengyuan Mu ◽  
Martin G. De Kauwe ◽  
Anna M. Ukkola ◽  
Andy J. Pitman ◽  
Weidong Guo ◽  
...  

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.


2011 ◽  
Vol 8 (5) ◽  
pp. 9847-9899 ◽  
Author(s):  
D.-G. Kim ◽  
R. Vargas ◽  
B. Bond-Lamberty ◽  
M. R. Turetsky

Abstract. The rewetting of dry soils and the thawing of frozen soils are short-term, transitional phenomena in terms of hydrology and the thermodynamics of soil systems. The impact of these short-term phenomena on larger scale ecosystem fluxes has only recently been fully appreciated, and a growing number of studies show that these events affect various biogeochemical processes including fluxes of soil gases such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), ammonia (NH3) and nitric oxide (NO). Global climate models predict that future climatic change is likely to alter the frequency and intensity of drying-rewetting events and thawing of frozen soils, highlighting the importance of understanding how rewetting and thawing will influence soil gas fluxes. Here we summarize findings in a new database based on 338 studies conducted from 1956 to 2010, and highlight open research questions. The database revealed conflicting results following rewetting and thawing in various terrestrial ecosystems, ranging from large increases in gas fluxes to non-significant changes. An analysis of published field studies (n = 142) showed that after rewetting or thawing, CO2, CH4, N2O, NO and NH3 fluxes increase from pre-event fluxes following a power function, with no significant differenced among gases. We discuss possible mechanisms and controls that regulate flux responses, and note that a high temporal resolution of flux measurements is critical to capture rapid changes in gas fluxes after these soil perturbations. Finally, we propose that future studies should investigate the interactions between biological (i.e. microbial community and gas production) and physical (i.e. flux, diffusion, dissolution) changes in soil gas fluxes, and explore synergistic experimental and modelling approaches.


2017 ◽  
Author(s):  
Imme Benedict ◽  
Chiel C. van Heerwaarden ◽  
Albrecht H. Weerts ◽  
Wilco Hazeleger

Abstract. The hydrological cycle of river basins can be simulated by combining global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. To further improve simulations of precipitation and river-runoff on a global scale, we assess and compare the benefits of an increased resolution for a GCM and a GHM. We focus on the Rhine and Mississippi basin. Increasing the resolution of a GCM (1.125° to 0.25°) results in more realistic large-scale circulation patterns over the Rhine and an improved precipitation budget. These improvements with increased resolution are not found for the Mississippi basin, most likely because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, because the hydrological processes depend highly on other parameter values that are not readily available at high resolution. Therefore, increasing the resolution of the GCM provides the most straightforward route to better results. This route works best for basins driven by large-scale precipitation, such as the Rhine basin. For basins driven by convective processes, such as the Mississippi basin, improvements are expected with even higher resolution convection permitting models.


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