scholarly journals A multi-level canopy radiative transfer scheme for ORCHIDEE (SVN r2566), based on a domain-averaged structure factor

2016 ◽  
Author(s):  
Matthew J. McGrath ◽  
James Ryder ◽  
Bernard Pinty ◽  
Juliane Otto ◽  
Kim Naudts ◽  
...  
Keyword(s):  
Structure Factor ◽  
Radiation Transfer ◽  
Computational Cost ◽  
Heat Fluxes ◽  
Energy Budgets ◽  
Level Energy ◽  
Transfer Scheme ◽  
Area Index ◽  
Global Circulation Models ◽  
Multi Level

Abstract. In order to better simulate heat fluxes over multilayer ecosystems, in particular tropical forests and savannahs, the next generation of Earth system models will likely include vertically-resolved vegetation structure and multi-level energy budgets. We present here a multi-level radiation transfer scheme which is capable of being used in conjunction with such methods. It is based on a previously established scheme which encapsulates the three dimensional nature of canopies, through the use of a domain-averaged structure factor, referred to here as the effective leaf area index. The fluxes are tracked throughout the canopy in an iterative fashion until they escape into the atmosphere or are absorbed by the canopy or soil; this approach explicitly includes multiple scattering between the canopy layers. A series of tests show that the results from the two-layer case are in acceptable agreement with those from the single layer, although the computational cost is necessarily increased due to the iterations. The ten-layer case is less precise, but still provides results to within an acceptable range. This new approach allows for the calculation of radiation transfer in vertically resolved vegetation canopies simulated in global circulation models.

scholarly journals Disentangling the response of forest and grassland energy exchange to heatwaves under idealized land–atmosphere coupling

2014 ◽  
Vol 11 (4) ◽  
pp. 5969-5995
Author(s):  
C. C. van Heerwaarden ◽  
A. J. Teuling
Keyword(s):  
Heat Wave ◽  
Heat Waves ◽  
Dynamic Properties ◽  
Sensible Heat Flux ◽  
Early Morning ◽  
Stomatal Resistance ◽  
Heat Fluxes ◽  
Sensible Heat ◽  
Area Index ◽  
Wave Conditions

Abstract. This study investigates the difference in land–atmosphere interactions between grassland and forest during typical heat wave conditions in order to understand the controversial results of Teuling et al. (2010) (T10, hereafter), who have found the systematic occurrence of higher sensible heat fluxes over forest than over grassland during heat wave conditions. With a simple, but accurate coupled land–atmosphere model, we are able to reproduce the findings of T10 for both normal summer and heat wave conditions, and to carefully explore the sensitivity of the coupled land–atmosphere system to changes in incoming radiation and early-morning temperature. Our results emphasize the importance of fast processes during the onset of heat waves, since we are able to explain the results of T10 without having to take into account changes in soil moisture. In order to disentangle the contribution of differences in several static and dynamic properties between forest and grassland, we have performed an experiment in which new land use types are created that are equal to grassland, but with one of its properties replaced by that of forest. From these, we conclude that the closure of stomata in the presence of dry air is by far the most important process in creating the different behavior of grassland and forest during the onset of a heat wave. However, we conclude that for a full explanation of the results of T10 also the other properties (albedo, roughness and the ratio of minimum stomatal resistance to leaf-area index) play an important, but indirect role; their influences mainly consist of strengthening the feedback that leads to the closure of the stomata by providing more energy that can be converted into sensible heat. The model experiment also confirms that, in line with the larger sensible heat flux, higher atmospheric temperatures occur over forest.

Multi-level energy integration between units, plants and sites for natural gas industrial parks

2018 ◽  
Vol 88 ◽  
pp. 1-15 ◽  
Author(s):  
Bing J. Zhang ◽  
Qiao Q. Tang ◽  
Yue Zhao ◽  
Yu Q. Chen ◽  
Qing L. Chen ◽  
...  
Keyword(s):  
Natural Gas ◽  
Level Energy ◽  
Energy Integration ◽  
Industrial Parks ◽  
Multi Level

Y-Net: Dual-branch Joint Network for Semantic Segmentation

2021 ◽  
Vol 17 (4) ◽  
pp. 1-22
Author(s):  
Yizhen Chen ◽  
Haifeng Hu
Keyword(s):  
Feature Vector ◽  
State Of The Art ◽  
Computational Cost ◽  
Receptive Fields ◽  
Semantic Segmentation ◽  
Global Context ◽  
Multi Level ◽  
The One ◽  
Public Datasets ◽  
High Level

Most existing segmentation networks are built upon a “ U -shaped” encoder–decoder structure, where the multi-level features extracted by the encoder are gradually aggregated by the decoder. Although this structure has been proven to be effective in improving segmentation performance, there are two main drawbacks. On the one hand, the introduction of low-level features brings a significant increase in calculations without an obvious performance gain. On the other hand, general strategies of feature aggregation such as addition and concatenation fuse features without considering the usefulness of each feature vector, which mixes the useful information with massive noises. In this article, we abandon the traditional “ U -shaped” architecture and propose Y-Net, a dual-branch joint network for accurate semantic segmentation. Specifically, it only aggregates the high-level features with low-resolution and utilizes the global context guidance generated by the first branch to refine the second branch. The dual branches are effectively connected through a Semantic Enhancing Module, which can be regarded as the combination of spatial attention and channel attention. We also design a novel Channel-Selective Decoder (CSD) to adaptively integrate features from different receptive fields by assigning specific channelwise weights, where the weights are input-dependent. Our Y-Net is capable of breaking through the limit of singe-branch network and attaining higher performance with less computational cost than “ U -shaped” structure. The proposed CSD can better integrate useful information and suppress interference noises. Comprehensive experiments are carried out on three public datasets to evaluate the effectiveness of our method. Eventually, our Y-Net achieves state-of-the-art performance on PASCAL VOC 2012, PASCAL Person-Part, and ADE20K dataset without pre-training on extra datasets.

scholarly journals A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981–2015

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Zhongen Niu ◽  
Honglin He ◽  
Gaofeng Zhu ◽  
Xiaoli Ren ◽  
Li Zhang ◽  
...  
Keyword(s):  
Hydrological Cycle ◽  
Terrestrial Ecosystem ◽  
Research Network ◽  
Energy Budgets ◽  
Climate Data ◽  
Area Index ◽  
Large Variability ◽  
Ecosystem Research ◽  
Insight Into

Abstract The ratio of plant transpiration to total terrestrial evapotranspiration (T/ET) captures the role of vegetation in surface-atmosphere interactions. However, several studies have documented a large variability in T/ET. In this paper, we present a new T/ET dataset (also including transpiration, evapotranspiration data) for China from 1981 to 2015 with spatial and temporal resolutions of 0.05° and 8 days, respectively. The T/ET dataset is based on a model-data fusion method that integrates the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model with multivariate observational datasets (transpiration and evapotranspiration). The dataset is driven by satellite-based leaf area index (LAI) data from GLASS and GLOBMAP, and climate data from the Chinese Ecosystem Research Network (CERN). Observational annual T/ET were used to validate the model, with R2 and RMSE values were 0.73 and 0.07 (12.41%), respectively. The dataset provides significant insight into T/ET and its changes over the Chinese terrestrial ecosystem and will be beneficial for understanding the hydrological cycle and energy budgets between the land and the atmosphere.

scholarly journals Arctic Intense Summer Storms and Their Impacts on Sea Ice—A Regional Climate Modeling Study

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 218 ◽  
Author(s):  
Alexander Semenov ◽  
Xiangdong Zhang ◽  
Annette Rinke ◽  
Wolfgang Dorn ◽  
Klaus Dethloff
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Chukchi Sea ◽  
Regional Climate ◽  
Turbulent Fluxes ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Energy Budgets ◽  
Sea Ice Concentration ◽  
Storm Activity

Various temporal and spatial changes have manifested in Arctic storm activities, including the occurrence of the anomalously intense storms in the summers of 2012 and 2016, along with the amplified warming and rapidly decreased sea ice. To detect the variability of and changes in storm activity and understand its role in sea ice changes, we examined summer storm count and intensity year-by-year from ensemble hindcast simulations with an Arctic regional coupled climate model for the period of 1948–2008. The results indicated that the model realistically simulated the climatological spatial structure of the storm activity, characterized by the storm count and intensity. The simulated storm count captures the variability derived from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP–NCAR) reanalysis, though the simulated one is higher than that in the reanalysis. This could be attributed to the higher resolution of the model that may better represent smaller and shallower cyclones. The composite analysis shows that intense storms tend to form a low-pressure pattern with centers over the Kara Sea and Chukchi Sea, respectively, generating cyclonic circulation over the North Atlantic and North Pacific Arctic Ocean. The former drives intensification of the transpolar drift and Fram Strait sea ice export, and the latter suppresses thick ice transport from the Canada Basin to the Beaufort–Chukchi Seas, in spite of an increase in sea ice transport to the East Siberian Sea. Associated with these changes in sea ice transport, sea ice concentration and thickness show large decreases in the Barents–Kara Seas and the Chukchi–East-Siberian Seas, respectively. Energy budgets analysis suggests that more numerous intense storms substantially decrease the downward net sea ice heat fluxes, including net radiative fluxes, turbulent fluxes, and oceanic heat fluxes, compared with that when a lower number of intense storms occur. The decrease in the heat fluxes could be attributable to an increased cloudiness and the resultant reduction of downward shortwave radiation, as well as a destabilized boundary layer induced increase in upward turbulent fluxes.

scholarly journals Sensitivity and predictive uncertainty of the ACASA model at a spruce forest site

2010 ◽  
Vol 7 (11) ◽  
pp. 3685-3705 ◽  
Author(s):  
K. Staudt ◽  
E. Falge ◽  
R. D. Pyles ◽  
K. T. Paw U ◽  
T. Foken
Keyword(s):  
Latent Heat ◽  
Goodness Of Fit ◽  
Net Ecosystem Exchange ◽  
Heat Fluxes ◽  
Transfer Model ◽  
Forest Site ◽  
Area Index ◽  
Predictive Uncertainty ◽  
Mountainous Regions ◽  
Generalized Likelihood Uncertainty Estimation

Abstract. The sensitivity and predictive uncertainty of the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) was assessed by employing the Generalized Likelihood Uncertainty Estimation (GLUE) method. ACASA is a stand-scale, multi-layer soil-vegetation-atmosphere transfer model that incorporates a third order closure method to simulate the turbulent exchange of energy and matter within and above the canopy. Fluxes simulated by the model were compared to sensible and latent heat fluxes as well as the net ecosystem exchange measured by an eddy-covariance system above the spruce canopy at the FLUXNET-station Waldstein-Weidenbrunnen in the Fichtelgebirge Mountains in Germany. From each of the intensive observation periods carried out within the EGER project (ExchanGE processes in mountainous Regions) in autumn 2007 and summer 2008, five days of flux measurements were selected. A large number (20000) of model runs using randomly generated parameter sets were performed and goodness of fit measures for all fluxes for each of these runs were calculated. The 10% best model runs for each flux were used for further investigation of the sensitivity of the fluxes to parameter values and to calculate uncertainty bounds. A strong sensitivity of the individual fluxes to a few parameters was observed, such as the leaf area index. However, the sensitivity analysis also revealed the equifinality of many parameters in the ACASA model for the investigated periods. The analysis of two time periods, each representing different meteorological conditions, provided an insight into the seasonal variation of parameter sensitivity. The calculated uncertainty bounds demonstrated that all fluxes were well reproduced by the ACASA model. In general, uncertainty bounds encompass measured values better when these are conditioned on the respective individual flux only and not on all three fluxes concurrently. Structural weaknesses of the ACASA model concerning the soil respiration calculations and the simulation of the latent heat flux during dry conditions were detected, with improvements suggested for each.

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