scholarly journals Asynchronous rotation of Earth-mass planets in the habitable zone of lower-mass stars

Science ◽  
2015 ◽  
Vol 347 (6222) ◽  
pp. 632-635 ◽  
Author(s):  
Jérémy Leconte ◽  
Hanbo Wu ◽  
Kristen Menou ◽  
Norman Murray
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Terrestrial Planets ◽  
Habitable Zone ◽  
Lower Mass ◽  
Solar Mass ◽  
Simple Scaling ◽  
Earth Like Planets ◽  
Thermal Tides

Planets in the habitable zone of lower-mass stars are often assumed to be in a state of tidally synchronized rotation, which would considerably affect their putative habitability. Although thermal tides cause Venus to rotate retrogradely, simple scaling arguments tend to attribute this peculiarity to the massive Venusian atmosphere. Using a global climate model, we show that even a relatively thin atmosphere can drive terrestrial planets’ rotation away from synchronicity. We derive a more realistic atmospheric tide model that predicts four asynchronous equilibrium spin states, two being stable, when the amplitude of the thermal tide exceeds a threshold that is met for habitable Earth-like planets with a 1-bar atmosphere around stars more massive than ~0.5 to 0.7 solar mass. Thus, many recently discovered terrestrial planets could exhibit asynchronous spin-orbit rotation, even with a thin atmosphere.

scholarly journals Global 3D modelling of Martian CO2 clouds

2021 ◽  
Author(s):  
Christophe Mathé ◽  
Anni Määttänen ◽  
Joachim Audouard ◽  
Constantino Listowski ◽  
Ehouarn Millour ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Martian Atmosphere ◽  
Polar Regions ◽  
Northern Latitudes ◽  
1D Model ◽  
Mesospheric Clouds ◽  
Microphysical Processes ◽  
Thermal Tides

<p>In the Martian atmosphere, carbon dioxide (CO<sub>2</sub>) clouds have been revealed by numerous instruments around Mars from the beginning of the XXI century. These observed clouds can be distinguished by two kinds involving different formation processes: those formed during the winter in polar regions located in the troposphere, and those formed during the Martian year at low- and mid-northern latitudes located in the mesosphere (Määattänen et al, 2013). Microphysical processes of formation of theses clouds are still not fully understood. However, modeling studies revealed processes necessary for their formation: the requirement of waves that perturb the atmosphere leading to a temperature below the condensation of CO<sub>2</sub> (transient planetary waves for tropospheric clouds (Kuroda et al., 20123), thermal tides (Gonzalez-Galindo et al., 2011) and gravity waves for mesospheric clouds (Spiga et al., 2012)). In the last decade, a state-of-the-art microphysical column (1D) model for CO<sub>2</sub> clouds in a Martian atmosphere was developed at Laboratoire Atmosphères, Observations Spatiales (LATMOS) (Listowski et al., 2013, 2014). We use our full microphysical model of CO<sub>2</sub> clouds formation to investigate the occurrence of these CO<sub>2</sub> clouds by coupling it with the Global Climate Model (GCM) of the Laboratoire de Météorologie Dynamique (LMD) (Forget et al., 1999). Last modeling results on Martian CO<sub>2</sub> clouds properties and their impacts on the atmosphere will be presented and be compared to observational data.</p>

scholarly journals Robust assessment of future changes in extreme precipitation over the Rhine basin using a GCM

2010 ◽  
Vol 7 (6) ◽  
pp. 9043-9066 ◽  
Author(s):  
S. F. Kew ◽  
F. M. Selten ◽  
G. Lenderink ◽  
W. Hazeleger
Keyword(s):  
Time Series ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Large River ◽  
Ensemble Size ◽  
Rhine Basin ◽  
Scaling Methods ◽  
Long Time ◽  
Simple Scaling

Abstract. Estimates of future changes in extremes of multiday precipitation sums are critical for estimates of future discharge extremes of large river basins. Here we use a large ensemble of global climate model SRES A1b scenario simulations to estimate changes in extremes of 1–20 day precipitation sums over the Rhine basin, projected for the period 2071–2100 with reference to 1961–1990. We find that in winter, an increase of order 10%, for the 99th percentile precipitation sum, is approximately fixed across the selected range of multiday sums, whereas in summer, the changes become increasingly negative as the summation time lengthens. Explanations for these results are presented that have implications for simple scaling methods for creating time series of a future climate. We show that this scaling behavior is sensitive to the ensemble size and indicate that currently available discharge estimates from previous studies are based on insufficiently long time series.

scholarly journals Robust assessment of future changes in extreme precipitation over the Rhine basin using a GCM

2011 ◽  
Vol 15 (4) ◽  
pp. 1157-1166 ◽  
Author(s):  
S. F. Kew ◽  
F. M. Selten ◽  
G. Lenderink ◽  
W. Hazeleger
Keyword(s):  
Time Series ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Large River ◽  
Ensemble Size ◽  
Rhine Basin ◽  
Scaling Methods ◽  
Long Time ◽  
Simple Scaling

Abstract. Estimates of future changes in extremes of multiday precipitation sums are critical for estimates of future discharge extremes of large river basins. Here we use a large ensemble of global climate model SRES A1b scenario simulations to estimate changes in extremes of 1–20 day precipitation sums over the Rhine basin, projected for the period 2071–2100 with reference to 1961–1990. We find that in winter, an increase of order 10%, for the 99th percentile precipitation sum, is approximately fixed across the selected range of multiday sums, whereas in summer, the changes become increasingly negative as the summation time lengthens. Explanations for these results are presented that have implications for simple scaling methods for creating time series of a future climate. We show that the dependence of quantile changes on summation time is sensitive to the ensemble size and indicate that currently available discharge estimates from previous studies are based on insufficiently long time series.

High bit rate ACTS experiments for performing global science - Keck Telescope and global climate model

1996 ◽  
Author(s):  
Larry Bergman ◽  
J. Gary ◽  
Burt Edelson ◽  
Neil Helm ◽  
Judith Cohen ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Bit Rate ◽  
Global Science ◽  
High Bit Rate

scholarly journals A comparison of ship and satellite measurements of cloud properties with global climate model simulations in the southeast Pacific stratus deck

2010 ◽  
Vol 10 (14) ◽  
pp. 6527-6536 ◽  
Author(s):  
M. A. Brunke ◽  
S. P. de Szoeke ◽  
P. Zuidema ◽  
X. Zeng
Keyword(s):  
Diurnal Cycle ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Cloud Fraction ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Southeast Pacific ◽  
Cloud Thickness

Abstract. Here, liquid water path (LWP), cloud fraction, cloud top height, and cloud base height retrieved by a suite of A-train satellite instruments (the CPR aboard CloudSat, CALIOP aboard CALIPSO, and MODIS aboard Aqua) are compared to ship observations from research cruises made in 2001 and 2003–2007 into the stratus/stratocumulus deck over the southeast Pacific Ocean. It is found that CloudSat radar-only LWP is generally too high over this region and the CloudSat/CALIPSO cloud bases are too low. This results in a relationship (LWP~h9) between CloudSat LWP and CALIPSO cloud thickness (h) that is very different from the adiabatic relationship (LWP~h2) from in situ observations. Such biases can be reduced if LWPs suspected to be contaminated by precipitation are eliminated, as determined by the maximum radar reflectivity Zmax>−15 dBZ in the apparent lower half of the cloud, and if cloud bases are determined based upon the adiabatically-determined cloud thickness (h~LWP1/2). Furthermore, comparing results from a global model (CAM3.1) to ship observations reveals that, while the simulated LWP is quite reasonable, the model cloud is too thick and too low, allowing the model to have LWPs that are almost independent of h. This model can also obtain a reasonable diurnal cycle in LWP and cloud fraction at a location roughly in the centre of this region (20° S, 85° W) but has an opposite diurnal cycle to those observed aboard ship at a location closer to the coast (20° S, 75° W). The diurnal cycle at the latter location is slightly improved in the newest version of the model (CAM4). However, the simulated clouds remain too thick and too low, as cloud bases are usually at or near the surface.

Two-way coupling of an ENSO model to the global climate model CLIMBER-3

2009 ◽  
Vol 29 (1) ◽  
pp. 94-101 ◽  
Author(s):  
Heiko Goelzer ◽  
Anders Levermann ◽  
Stefan Rahmstorf
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Enso Model

Downscaling of precipitation on a lake basin: evaluation of rule and decision tree induction algorithms

2012 ◽  
Vol 43 (3) ◽  
pp. 215-230 ◽  
Author(s):  
Manish Kumar Goyal ◽  
C. S. P. Ojha
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Lake Basin ◽  
Monthly Precipitation ◽  
M5 Model Tree ◽  
Reanalysis Dataset ◽  
Model Tree ◽  
Basin Scale ◽  
M5 Model

We investigate the performance of existing state-of-the-art rule induction and tree algorithms, namely Single Conjunctive Rule Learner, Decision Table, M5 Model Tree, Decision Stump and REPTree. Downscaling models are developed using these algorithms to obtain projections of mean monthly precipitation to lake-basin scale in an arid region in India. The effectiveness of these algorithms is evaluated through application to downscale the predictand for the Lake Pichola region in Rajasthan state in India, which is considered to be a climatically sensitive region. The predictor variables are extracted from (1) the National Centre for Environmental Prediction (NCEP) reanalysis dataset for the period 1948–2000 and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 2001–2100. M5 Model Tree algorithm was found to yield better performance among all other learning techniques explored in the present study. The precipitation is projected to increase in future for A2 and A1B scenarios, whereas it is least for B1 and COMMIT scenarios using predictors.

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