Publication Abstracts
Chen et al. 2006
, F. Aires, J.A. Francis, and J.R. Miller, 2006: Observed relationships between Arctic longwave cloud forcing and cloud parameters using a neural network. J. Climate, 19, 4087-4104, doi:10.1175/JCLI3839.1.
A neural network technique is used to quantify relationships involved in cloud-radiation feedbacks based on observations from the Surface Heat Budget of the Arctic (SHEBA) project. Sensitivities of longwave cloud forcing (CFL) to cloud parameters indicate that a bimodal distribution pattern dominates the histogram of each sensitivity. Although the mean states of the relationships agree well with those derived in a previous study, they do not often exist in reality. The sensitivity of CFL to cloud cover (CLD) increases as the cloudiness increases with a range of 0.1 to 0.9 W/m2%. There is a saturation effect of liquid water path (LWP) on CFL. The highest sensitivity of CFL to LWP corresponds to clouds with low LWP, and sensitivity decreases as LWP increases. The sensitivity of CFL to cloud-base height (CBH) depends on whether the clouds are below or above an inversion layer. The relationship is negative for clouds higher than 0.8 km at the SHEBA site. The strongest positive relationship corresponds to clouds with low CBH. The dominant mode of the sensitivity of CFL to cloud-base temperature (CBT) is near zero and corresponds to warm clouds with base temperature higher than -9 °C. The low and high sensitivity regimes correspond to summer and winter seasons, respectively, especially for LWP and CBT. Overall, the neural network technique is able to separate two distinct regimes of clouds that correspond to different sensitivities, i.e., it captures the non-linear behavior in the relationships. This study demonstrates a new method for evaluating non-linear relationships between climate variables. It could also be used as an effective tool for evaluating feedback processes in climate models.
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BibTeX Citation
@article{ch03700t, author={Chen, Y.-H. and Aires, F. and Francis, J. A. and Miller, J. R.}, title={Observed relationships between Arctic longwave cloud forcing and cloud parameters using a neural network}, year={2006}, journal={J. Climate}, volume={19}, pages={4087--4104}, doi={10.1175/JCLI3839.1}, }
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RIS Citation
TY - JOUR ID - ch03700t AU - Chen, Y.-H. AU - Aires, F. AU - Francis, J. A. AU - Miller, J. R. PY - 2006 TI - Observed relationships between Arctic longwave cloud forcing and cloud parameters using a neural network JA - J. Climate VL - 19 SP - 4087 EP - 4104 DO - 10.1175/JCLI3839.1 ER -
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