A seasonal global climate model with an equivalent meridional atmospheric circulation

Tellus ◽  
1982 ◽  
Vol 34 (6) ◽  
pp. 514-525 ◽  
Author(s):  
E. ELIASEN ◽  
L. LAURSEN
Keyword(s):  
Atmospheric Circulation ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model

scholarly journals The ExtremeX global climate model experiment: Investigating thermodynamic and dynamic processes contributing to weather and climate extremes

2021 ◽  
Author(s):  
Kathrin Wehrli ◽  
Fei Luo ◽  
Mathias Hauser ◽  
Hideo Shiogama ◽  
Daisuke Tokuda ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Atmospheric Circulation ◽  
Great Plains ◽  
Land Surface ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Climate Extremes ◽  
The United States ◽  
Weather And Climate

Abstract. The mechanisms leading to the occurrence of extreme weather and climate events are varied and complex. They generally encompass a combination of dynamical and thermodynamical processes, as well as drivers external to the climate system, such as anthropogenic greenhouse gas emissions and land-use change. Here we present the ExtremeX multi-model intercomparison experiment, which was designed to investigate the contribution of dynamic and thermodynamic processes to recent weather and climate extremes. The numerical experiments are performed with three Earth System Models: CESM, MIROC, and EC-Earth. They include control experiments with interactive atmosphere and land surface conditions, and experiments where either the atmospheric circulation, soil moisture or both are constrained using observation-based values. The temporal evolution and magnitude of temperature anomalies during heatwaves is well represented in the experiments with constrained atmosphere. However, mean climatological biases in temperature and precipitation are not substantially reduced in any of the constrained experiments, highlighting the importance of error compensations and tuning in the standard model versions. The results further reveal that both atmospheric circulation patterns and soil moisture conditions substantially contribute to the occurrence of heat extremes. Soil moisture effects are particularly important in the tropics, the monsoon areas and the Great Plains of the United States.

scholarly journals What do moisture recycling estimates tell us? Exploring the extreme case of non-evaporating continents

2011 ◽  
Vol 15 (10) ◽  
pp. 3217-3235 ◽  
Author(s):  
H. F. Goessling ◽  
C. H. Reick
Keyword(s):  
Atmospheric Circulation ◽  
Climate Model ◽  
Global Climate ◽  
Thermal Structure ◽  
Global Climate Model ◽  
Extreme Case ◽  
Active Role ◽  
Large Spatial Scale ◽  
Moisture Recycling ◽  
Local Coupling

Abstract. Moisture recycling estimates are diagnostic measures that could ideally be used to deduce the response of precipitation to modified land-evaporation. Recycling estimates are based on moisture-budget considerations in which water is treated as a passive tracer. But in reality water is a thermodynamically active component of the atmosphere. Accordingly, recycling estimates are applicable to deduce the response to a perturbation only if other mechanisms by which evaporation affects climate do not dominate the response – a condition that has not received sufficient attention in the literature. In our analysis of what moisture recycling estimates tell us, we discuss two such additional mechanisms that result from water's active role. These are (I) local coupling, by which precipitation is affected locally via the thermal structure of the atmosphere, and (II) the atmospheric circulation, by which precipitation is affected on a large spatial scale. We perform two global climate model experiments: One with and another without continental evaporation. By this extreme perturbation we test the predictive utility of a certain type of recycling measure, the "continental recycling ratio". Moreover, by such a strong perturbation the whole spectrum of possible responses shows up simultaneously, giving us the opportunity to discuss all concurrent mechanisms jointly. The response to this extreme perturbation largely disagrees with the hypothesis that moisture recycling is the dominant mechanism. Instead, most of the response can be attributed to changes in the atmospheric circulation, while the contributions to the response by moisture recycling as well as local coupling, though noticeable, are smaller. By our case study it is not possible to give a general answer to the question posed in the title, but it demonstrates that recycling estimates do not necessarily mirror the consequences of land-use change for precipitation.

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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