scholarly journals Simulating Springtime Temperature Patterns in the Community Atmosphere Model Coupled to the Community Land Model Using Prognostic Leaf Area

2004 ◽  
Vol 17 (23) ◽  
pp. 4531-4540 ◽  
Author(s):  
Samuel Levis ◽  
Gordon B. Bonan
Keyword(s):  
Leaf Area ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Dynamic Coupling ◽  
Model Simulations ◽  
Community Land Model ◽  
Leaf Emergence ◽  
Community Atmosphere Model ◽  
Surface Climate ◽  
Atmosphere Model

Abstract Observations show that emergence of foliage in springtime slows surface air temperature warming as a result of greater transpiration. Model simulations with the Community Atmosphere Model coupled to the Community Land Model confirm that evapotranspiration contributes to this pattern and that this pattern occurs more reliably with prognostic leaf area as opposed to prescribed leaf area. With prescribed leaf area, leaves emerge independent of prevailing environmental conditions, which may preclude photosynthesis from occurring. In contrast, prognostic leaf area ensures that leaves emerge when conditions are favorable for photosynthesis, and thus transpiration. These results reveal a dynamic coupling between the atmosphere and vegetation in which the observed reduction in the springtime warming trend only occurs when photosynthesis, stomatal conductance, and leaf emergence are synchronized with the surface climate.

The Formulation and Atmospheric Simulation of the Community Atmosphere Model Version 3 (CAM3)

2006 ◽  
Vol 19 (11) ◽  
pp. 2144-2161 ◽  
Author(s):  
William D. Collins ◽  
Philip J. Rasch ◽  
Byron A. Boville ◽  
James J. Hack ◽  
James R. McCaa ◽  
...  
Keyword(s):  
Finite Volume ◽  
Radiative Forcing ◽  
General Circulation ◽  
Circulation Model ◽  
Surface Radiation ◽  
Time Step ◽  
Community Land Model ◽  
Enso Events ◽  
Community Atmosphere Model ◽  
Atmosphere Model

Abstract A new version of the Community Atmosphere Model (CAM) has been developed and released to the climate community. CAM Version 3 (CAM3) is an atmospheric general circulation model that includes the Community Land Model (CLM3), an optional slab ocean model, and a thermodynamic sea ice model. The dynamics and physics in CAM3 have been changed substantially compared to implementations in previous versions. CAM3 includes options for Eulerian spectral, semi-Lagrangian, and finite-volume formulations of the dynamical equations. It supports coupled simulations using either finite-volume or Eulerian dynamics through an explicit set of adjustable parameters governing the model time step, cloud parameterizations, and condensation processes. The model includes major modifications to the parameterizations of moist processes, radiation processes, and aerosols. These changes have improved several aspects of the simulated climate, including more realistic tropical tropopause temperatures, boreal winter land surface temperatures, surface insolation, and clear-sky surface radiation in polar regions. The variation of cloud radiative forcing during ENSO events exhibits much better agreement with satellite observations. Despite these improvements, several systematic biases reduce the fidelity of the simulations. These biases include underestimation of tropical variability, errors in tropical oceanic surface fluxes, underestimation of implied ocean heat transport in the Southern Hemisphere, excessive surface stress in the storm tracks, and offsets in the 500-mb height field and the Aleutian low.

scholarly journals Boreal Winter MJO Teleconnection in the Community Atmosphere Model Version 5 with the Unified Convection Parameterization

2015 ◽  
Vol 28 (20) ◽  
pp. 8135-8150 ◽  
Author(s):  
Changhyun Yoo ◽  
Sungsu Park ◽  
Daehyun Kim ◽  
Jin-Ho Yoon ◽  
Hye-Mi Kim
Keyword(s):  
Deep Convection ◽  
Surface Air Temperature ◽  
Dominant Mode ◽  
Boreal Winter ◽  
Convective Heating ◽  
Model Version ◽  
Community Atmosphere Model ◽  
Circulation Anomalies ◽  
Atmosphere Model ◽  
Convection Schemes

Abstract The Madden–Julian oscillation (MJO), the dominant mode of tropical intraseasonal variability, influences weather and climate in the extratropics through atmospheric teleconnection. In this study, two simulations using the Community Atmosphere Model version 5 (CAM5)—one with the default shallow and deep convection schemes and the other with the unified convection scheme (UNICON)—are employed to examine the impacts of cumulus parameterizations on the simulation of the boreal wintertime MJO teleconnection in the Northern Hemisphere. It is demonstrated that the UNICON substantially improves the MJO teleconnection. When the UNICON is employed, the simulated circulation anomalies associated with the MJO better resemble the observed counterpart, compared to the simulation with the default convection schemes. Quantitatively, the pattern correlation for the 300-hPa geopotential height anomalies between the simulations and observation increases from 0.07 for the default schemes to 0.54 for the UNICON. These circulation anomalies associated with the MJO further help to enhance the surface air temperature and precipitation anomalies over North America, although room for improvement is still evident. Initial value calculations suggest that the realistic MJO teleconnection with the UNICON is not due to the changes in the background wind, but rather primarily to the improved tropical convective heating associated with the MJO.

scholarly journals Impact of Cloud Physics on the Greenland Ice Sheet Near‐Surface Climate: A Study With the Community Atmosphere Model

2020 ◽  
Vol 125 (7) ◽  
Author(s):  
Jan T. M. Lenaerts ◽  
Andrew Gettelman ◽  
Kristof Van Tricht ◽  
Leo Kampenhout ◽  
Nathaniel B. Miller
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Cloud Physics ◽  
Near Surface ◽  
Community Atmosphere Model ◽  
Surface Climate ◽  
Atmosphere Model

Changes in the Amplitude of the Temperature Annual Cycle in China and Their Implication for Climate Change Research

2011 ◽  
Vol 24 (20) ◽  
pp. 5292-5302 ◽  
Author(s):  
Cheng Qian ◽  
Congbin Fu ◽  
Zhaohua Wu
Keyword(s):  
Climate Change ◽  
Annual Cycle ◽  
Linear Trend ◽  
Surface Air Temperature ◽  
Mean Amplitude ◽  
Warming Trend ◽  
Ensemble Empirical Mode Decomposition ◽  
Surface Solar Radiation ◽  
Climate Change Research ◽  
Annual Cycles

Abstract Climate change is not only reflected in the changes in annual means of climate variables but also in the changes in their annual cycles (seasonality), especially in the regions outside the tropics. In this study, the ensemble empirical mode decomposition (EEMD) method is applied to investigate the nonlinear trend in the amplitude of the annual cycle (which contributes 96% of the total variance) of China’s daily mean surface air temperature for the period 1961–2007. The results show that the variation and change in the amplitude are significant, with a peak-to-peak annual amplitude variation of 13% (1.8°C) of its mean amplitude and a significant linear decrease in amplitude by 4.6% (0.63°C) for this period. Also identified is a multidecadal change in amplitude from significant decreasing (−1.7% decade−1 or −0.23°C decade−1) to significant increasing (2.2% decade−1 or 0.29°C decade−1) occurring around 1993 that overlaps the systematic linear trend. This multidecadal change can be mainly attributed to the change in surface solar radiation, from dimming to brightening, rather than to a warming trend or an enhanced greenhouse effect. The study further proposes that the combined effect of the global dimming–brightening transition and a gradual increase in greenhouse warming has led to a perceived warming trend that is much larger in winter than in summer and to a perceived accelerated warming in the annual mean since the early 1990s in China. It also notes that the deseasonalization method (considering either the conventional repetitive climatological annual cycle or the time-varying annual cycle) can also affect trend estimation.

scholarly journals Representing winter wheat in the Community Land Model (version 4.5)

2017 ◽  
Vol 10 (5) ◽  
pp. 1873-1888 ◽  
Author(s):  
Yaqiong Lu ◽  
Ian N. Williams ◽  
Justin E. Bagley ◽  
Margaret S. Torn ◽  
Lara M. Kueppers
Keyword(s):  
Heat Flux ◽  
Winter Wheat ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Latent Heat Flux ◽  
Carbon Allocation ◽  
Net Ecosystem Exchange ◽  
Area Index ◽  
Community Land Model ◽  
The Us

Abstract. Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of Earth's croplands. As such, it plays an important role in carbon cycling and land–atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under a changing climate, but also for accurately predicting the energy and water cycles for winter wheat dominated regions. We modified the winter wheat model in the Community Land Model (CLM) to better simulate winter wheat leaf area index, latent heat flux, net ecosystem exchange of CO2, and grain yield. These included schemes to represent vernalization as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the US Southern Great Plains ARM site (US-ARM), and validated the model performance at eight additional sites across North America. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, reduced latent heat flux, and net ecosystem exchange root mean square error (RMSE) by 41 and 35 % during the spring growing season. The model accurately simulated the interannual variation in yield at the US-ARM site, but underestimated yield at sites and in regions (northwestern and southeastern US) with historically greater yields by 35 %.

Sign in / Sign up

Export Citation Format

Share Document