Amar Desai

Vegetation albedo is a critical component of the Earth's climate system, yet efforts to evaluate and improve albedo parameterizations in climate models have lagged relative to other aspects of model development. Here, we calculated growing season albedos for deciduous and evergreen forests, crops, and grasslands based on over 40 site-years of data from the AmeriFlux network and compared them with estimates presently used in the land surface formulations of a variety of climate models. Generally, the albedo estimates used in land surface models agreed well with this data compilation. However, a variety of models using fixed seasonal estimates of albedo overestimated the growing season albedo of northerly evergreen trees. In contrast, climatemodels that rely on a common two-stream albedo submodel provided accurate predictions of boreal needle-leaf evergreen albedo but overestimated grassland albedos. Inverse analysis showed that parameters of the two-stream model were highly correlated. Consistent with recent observations based on remotely sensed albedo, the AmeriFlux dataset demonstrated a tight linear relationship between canopy albedo and foliage nitrogen concentration. However, this relationship saturated at the higher nitrogen concentrations displayed by soybean foliage. We developed similar relationships between a foliar parameter used in the two-stream albedo model and foliage nitrogen concentration. These nitrogen-based relationships can serve as the basis for a new approach to land surface albedo modeling that simplifies albedo estimation while providing a link to other important ecosystem processes. © 2009 Blackwell Publishing Ltd.

Copyright © 2014 by the American Thoracic Society. Rationale: A low respiratory arousal threshold is one of several traits involved in obstructive sleep apnea pathogenesis and may be a therapeutic target; however, there is no simple way to identify patients without invasive measurements. Objectives: To determine the physiologic determinates of the ArTH and develop a clinical tool that can identify patients with low ArTH. Methods: Anthropometric data were collected in 146 participants who underwent overnight polysomnography with an epiglottic catheter to measure the ArTH. The ArTH was measured from up to 20 non-REM and REM respiratory events selected randomly. Multiple linear regression was used to determine the independent predictors of the ArTH. Logistic regression was used to develop a clinical scoring system. Measurements and Main Results: Nadir oxygen saturation as measured by pulse oximetry, apnea-hypopnea index, and the fraction of events that were hypopneas were independent predictors of the ArTH 1. A score of 2 or above correctly predicted a low arousal threshold in 84.1% of participants with a sensitivity of 80.4% and a specificity of 88.0%, a finding that was confirmed using leave-one-out cross-validation analysis. Conclusions: Our results demonstrate that individuals with a low ArTH can be identified from standard, clinically available variables. This finding could facilitate larger interventional studies targeting the ArTH.