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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

TU-H-CAMPUS-JeP1-04: Deformable Image Registration Performances in Pelvis Patients: Impact of CBCT Image Quality

Purpose: To investigate the accuracy and robustness, against image noise and artifacts (typical of CBCT images), of a commercial algorithm for deformable image registration (DIR), to propagate regions of interest (ROIs) in computational phantoms based on real prostate patient images. Methods: The Anaconda DIR algorithm, implemented in RayStation was tested. Two specific Deformation Vector Fields (DVFs) were applied to the reference data set (CTref) using the ImSimQA software, obtaining two deformed CTs. For each dataset twenty-four different level of noise and/or capping artifacts were applied to simulate CBCT images. DIR was performed between CTref and each deformed CTs and CBCTs. In order to investigate the relationship between image quality parameters and the DIR results (expressed by a logit transform of the Dice Index) a bilinear regression was defined. Results: More than 550 DIR-mapped ROIs were analyzed. The Statistical analysis states that deformation strenght and artifacts were significant prognostic factors of DIR performances, while noise appeared to have a minor role in DIR process as implemented in RayStation as expected by the image similarity metric built in the registration algorithm. Capping artifacts reveals a determinant role for the accuracy of DIR results. Two optimal values for capping artifacts were found to obtain acceptable DIR results (DICE> 075/ 0.85). Various clinical CBCT acquisition protocol were reported to evaluate the significance of the study. Conclusion: This work illustrates the impact of image quality on DIR performance. Clinical issues like Adaptive Radiation Therapy (ART) and Dose Accumulation need accurate and robust DIR software. The RayStation DIR algorithm resulted robust against noise, but sensitive to image artifacts. This result highlights the need of robustness quality assurance against image noise and artifacts in the commissioning of a DIR commercial system and underlines the importance to adopt optimized protocols for CBCT image acquisitions in ART clinical implementation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The Greenhouse Effect and Climate Change: The Intensified Greenhouse Effect

We report that human activities over the past 200 years have increased Earth’s greenhouse effect by about 1% relative to the radiative fluxes that drive the climate system. This Resource Letter introduces the physics of this intensified greenhouse effect and of the processes that govern resultant change in climate and provides resources for further study. Context for this examination is provided in a companion Resource Letter (GECC-1) that examined the radiative fluxes that comprise Earth’s climate system and the present-day greenhouse effect. The increase in global temperature and other changes in climate resulting from the intensified greenhouse effect are of great societal concern. Developing prognostic capability to determine these responses to the small perturbations that constitute the intensified greenhouse effect to an accuracy that would be useful to inform policymaking is the major challenge facing climate scientists today.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

How do deer respiratory epithelial cells weather the initial storm of SARS-CoV-2 WA1/2020 strain?

The potential infectivity of severe acute respiratory syndrome associated coronavirus-2 (SARS-CoV-2) in animals raises a public health and economic concern, particularly the high susceptibility of white-tailed deer (WTD) to SARS-CoV-2. The disparity in the disease outcome between humans and WTD is very intriguing, as the latter are often asymptomatic, subclinical carriers of SARS-CoV-2. To date, no studies have evaluated the innate immune factors responsible for the contrasting SARS-CoV-2-associated disease outcomes in these mammalian species. A comparative transcriptomic analysis in primary respiratory epithelial cells of human (HRECs) and WTD (Deer-RECs) infected with the SARS-CoV-2 WA1/2020 strain was assessed throughout 48 h post inoculation (hpi). Both HRECs and Deer-RECs were susceptible to virus infection, with significantly ( P < 0.001) lower virus replication in Deer-RECs. The number of differentially expressed genes (DEG) gradually increased in Deer-RECs but decreased in HRECs throughout the infection. The ingenuity pathway analysis of DEGs further identified that genes commonly altered during SARS-CoV-2 infection mainly belong to cytokine and chemokine response pathways mediated via interleukin-17 (IL-17) and nuclear factor-κB (NF-κB) signaling pathways. Inhibition of the NF-κB signaling in the Deer-RECs pathway was predicted as early as 6 hpi. The findings from this study could explain the lack of clinical signs reported in WTD in response to SARS-CoV-2 infection as opposed to the severe clinical outcomes reported in humans. IMPORTANCE. This study demonstrated that human and white-tailed deer primary respiratory epithelial cells are susceptible to the SARS-CoV-2 WA1/2020 strain infection. However, the comparative transcriptomic analysis revealed that deer cells could limit viral replication without causing hypercytokinemia by downregulating IL-17 and NF-κB signaling pathways. Identifying differentially expressed genes in human and deer cells that modulate key innate immunity pathways during the early infection will lead to developing targeted therapies toward preventing or mitigating the “cytokine storm” often associated with severe cases of coronavirus disease 19 (COVID-19). Moreover, results from this study will aid in identifying novel prognostic biomarkers in predicting SARS-CoV-2 adaption and transmission in deer and associated cervids.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Low-frequency noise in as-fabricated and degraded blue InGaAs/GaN LEDs

Study of the spectral noise density and its dependence on current density in as-fabricated and degraded blue light-emitting diodes (LEDs) based on InGaN/GaN quantum-well structures are reported. It is shown that defects are generated nonuniformly in the course of degradation, being concentrated along extended defects penetrating into the active region of LEDs. It is demonstrated that the decrease in the external quantum efficiency in the course of aging is due to the enhancement of charge transport uniformity, which leads to the formation of shunts and local overheating regions. Typically, in blue LEDs, these effects are responsible for the ambiguous development of the degradation process, which hinders prognostication of LED service life. The effect of noise suppression is observed in a narrow current density range (10{sup -2} to 10{sup -1} A cm{sup -2}) corresponding to the onset of radiative recombination.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation

Extraction and enhancement of weak impulse signature is the key of rolling bearing fault prognostics in which case the features are often weak and covered by noise. Tunable Q-factor wavelet transform (TQWT), as an emerging wavelet construction theory developed in a frequency domain explicitly, has the advantages of matching with the specific oscillation behavior of signal components. In this article, an adaptive sparse representation (ASR) method is proposed, which integrates the sparse code shrinkage (SCS) and parameter optimization into TQWT. However, direct application of ASR is difficult to extract fault signatures at the early stage or low-speed operation due to weak fault symptoms and background noise. A novel fault diagnosis strategy based on continuous wavelet transform (CWT) and ASR is investigated. CWT owns significant advantages on multiscale subdivision and weak signal detection. The results of simulated and experimental vibration signal analyses verify the effectiveness of the proposed method in accurately extracting weak impulse features from the noise environment.

Yuan, Xing↗
DOE OSTI2016

Methodology for Risk-informed O&M decision making in power plants

Incorporation of real-time component information using equipment condition assessment (ECA) through the development of enhanced risk monitors (ERM) for active components in advanced reactor (AR) and advanced small modular reactor (SMR) designs. We incorporate time-dependent failure probabilities from prognostic health management (PHM) systems to dynamically update the risk metric of interest. This information is used to augment data used for supervisory control and plant-wide coordination of multiple modules by providing the incremental risk incurred due to aging and demands placed on components that support mission requirements.

Source record↗
DOE OSTI2020

Auto-BLAST (AutoBLAST) [SWR-20-93]

Battery life modeling often involves a lot of manual parameter fitting and is not easy for users to adopt the model and use it. To reduce the difficulties for users to adopt battery lifetime models, an automatic battery lifetime modeling analysis and simulation tool suite, Auto-BLAST, has been developed. Auto-BLAST includes a lithium-loss-base life model, a battery electric model, and an algorithm which automatically fits all key parameters in the electric and life models using user provided data. The models and algorithm are packaged into two user-friendly GUIs, Auto-LifeMod, for easy battery life prognostic model fitting and Auto-LifeSim, for easy battery lifetime simulation. The lithium-loss-based life model adopts a similar model framework that models degradations using aging rate models, using battery cycling data to predict battery degradation and expected lifetime. The electric model is an equivalent circuit model which simulates battery voltage responses based on current/power demand profiles. The auto-fitting algorithm uses the user-input data to generate custom battery life model(s). Two GUIs, wrapping around the life model and the auto-fitting algorithm, provide friendly interfaces for users to generate a life model and use it for case study. One GUI requires summary data from accelerated battery life degradation tests as an input and produces battery life models predicting (a) capacity degradation, and (b) resistance growth of the battery. The GUI displays the electrical model response and the input experimental data against the life model predictions with fitted model parameters and fitting error. The GUI also generates an output file to save the fitted model parameters. The second GUI uses the life model from the first GUI and a user-defined battery cycling profile to predict battery lifetime degradation and expected lifetime. Predicted capacity and resistance vs. time are plotted in the GUI and saved to output file. There is a user guide for both GUIs

Mishra, Partha↗
DOE OSTI2023

Transcatheter Arterial Chemoembolization for Treatment-Naive Hepatocellular Carcinoma Has Different Treatment Effects Depending on Central or Peripheral Tumor Location

Introduction: The purpose of this study was to evaluate the treatment efficacy of transcatheter arterial chemoembolization (TACE) for treatment-naive hepatocellular carcinoma (HCC) according to tumor location and burden. Methods: Between 2010 and 2019, consecutive patients who underwent TACE as the first treatment were enrolled. Tumors were classified into two categories based on their location, as central or peripheral tumors. Tumors in the central zone, which is within 1 cm of the main trunk or the first branch of the portal vein, were classified as central tumors, while those located in the peripheral zone were classified as peripheral tumors. Patients were grouped according to the HCC location and up-to-7 criteria. Patients with central tumors were classified into the central arm and those with only peripheral tumors were classified into the peripheral arm. Patients within and beyond the up-to-7 criteria were classified into the up-to-7 in and up-to-7 out-groups, respectively. Local recurrence-free survival (LRFS) and progression-free survival (PFS) were compared per nodule (central tumor vs. peripheral tumor) and per patient (central arm vs. peripheral arm), respectively. The prognostic factors of LRFS and PFS were analyzed by univariate and multivariate analyses. Results: A total of 174 treatment-naive patients with 352 HCCs were retrospectively enrolled. Ninety-six patients and 130 lesions were selected by propensity score matching. Median LRFS was longer for peripheral tumors than central tumors (not reached vs. 3.3 months, p < 0.001). Median PFS was 17.1 months (8.3–24.9) in the peripheral arm and up-to-7 in, 7.0 months (3.3–12.7) in the peripheral arm and up-to-7 out, 8.4 months (4.0–12.6) in the central arm and up-to-7 in, and 3.0 months (1.2–4.9) in the central arm and up-to-7 out-groups. The peripheral arm and up-to-7 in-groups had significantly longer PFS than the other three groups (p = 0.013, p = 0.015, p < 0.001, respectively). Multivariate analysis confirmed that the central zone and central arm were associated with high adjusted hazard ratios for tumor recurrence or death (2.87, p < 0.001; 2.89, p < 0.001, respectively). Conclusion: Treatment-naive HCCs in the peripheral zone had a longer LRFS and PFS following TACE compared to those in the central zone.

Gastroenterology & Hepatology↗
DOE OSTI2024

Proteomics identifies complement protein signatures in patients with alcohol-associated hepatitis

Diagnostic challenges continue to impede development of effective therapies for successful management of alcohol-associated hepatitis (AH), creating an unmet need to identify noninvasive biomarkers for AH. In murine models, complement contributes to ethanol-induced liver injury. Therefore, we hypothesized that complement proteins could be rational diagnostic/prognostic biomarkers in AH. Here, we performed a comparative analysis of data derived from human hepatic and serum proteome to identify and characterize complement protein signatures in severe AH (sAH). The quantity of multiple complement proteins was perturbed in liver and serum proteome of patients with sAH. Multiple complement proteins differentiated patients with sAH from those with alcohol cirrhosis (AC) or alcohol use disorder (AUD) and healthy controls (HCs). Serum collectin 11 and C1q binding protein were strongly associated with sAH and exhibited good discriminatory performance among patients with sAH, AC, or AUD and HCs. Furthermore, complement component receptor 1-like protein was negatively associated with pro-inflammatory cytokines. Additionally, lower serum MBL associated serine protease 1 and coagulation factor II independently predicted 90-day mortality. In summary, meta-analysis of proteomic profiles from liver and circulation revealed complement protein signatures of sAH, highlighting a complex perturbation of complement and identifying potential diagnostic and prognostic biomarkers for patients with sAH.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A Low Mach Number Model for Moist Atmospheric Flows

A low Mach number model for moist atmospheric flows is introduced that accurately incorporates reversible moist processes in flows whose features of interest occur on advective rather than acoustic time scales. Total water is used as a prognostic variable, so that water vapor and liquid water are diagnostically recovered as needed from an exact Clausius–Clapeyron formula for moist thermodynamics. Low Mach number models can be computationally more efficient than a fully compressible model, but the low Mach number formulation introduces additional mathematical and computational complexity because of the divergence constraint imposed on the velocity field. Here in this paper, latent heat release is accounted for in the source term of the constraint by estimating the rate of phase change based on the time variation of saturated water vapor subject to the thermodynamic equilibrium constraint. Finally, the authors numerically assess the validity of the low Mach number approximation for moist atmospheric flows by contrasting the low Mach number solution to reference solutions computed with a fully compressible formulation for a variety of test problems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Evaluation of Subgrid-scale Hydrometeor Transport Schemes using a High-resolution Cloud-resolving Model

Potential ways of parameterizing vertical turbulent fluxes of hydrometeors are examined using a high-resolution cloud-resolving model. The cloud-resolving model uses the Morrison microphysics scheme, which contains prognostic variables for rain, graupel, ice, and snow. A benchmark simulation with a horizontal grid spacing of 250 m of a deep convection case carried out to evaluate three different ways of parameterizing the turbulent vertical fluxes of hydrometeors: an eddy-diffusion approximation, a quadrant-based decomposition, and a scaling method that accounts for within-quadrant (subplume) correlations. Results show that the down-gradient nature of the eddy-diffusion approximation tends to transport mass away from concentrated regions, whereas the benchmark simulation indicates that the vertical transport tends to transport mass from below the level of maximum to aloft. Unlike the eddy-diffusion approach, the quadri-modal decomposition is able to capture the signs of the flux gradient but underestimates the magnitudes. The scaling approach is shown to perform the best by accounting for within-quadrant correlations, and improves the results for all hydrometeors except for snow. A sensitivity study is performed to examine how vertical transport may affect the microphysics of the hydrometeors. The vertical transport of each hydrometeor type is artificially suppressed in each test. Results from the sensitivity tests show that cloud-droplet-related processes are most sensitive to suppressed rain or graupel transport. In particular, suppressing rain or graupel transport has a strong impact on the production of snow and ice aloft. Lastly, a viable subgrid-scale hydrometeor transport scheme in an assumed probability density function parameterization is discussed.

cloud-resolving model↗
DOE OSTI2018

Simulation of Mesoscale Cellular Convection in Marine Stratocumulus. Part I: Drizzling Conditions

This study uses eddy-permitting simulations to investigate the mechanisms that promote mesoscale variability of moisture in drizzling stratocumulus-topped marine boundary layers. Simulations show that precipitation tends to increase horizontal scales. Analysis of terms in the prognostic equation for total water mixing ratio variance indicates that moisture stratification plays a leading role in setting horizontal scales. This result is supported by simulations in which horizontal mean thermodynamic profiles are strongly nudged to their initial well-mixed state, which limits cloud scales. It is found that the spatial variability of subcloud moist cold pools surprisingly tends to respond to, rather than determine, the mesoscale variability, which may distinguish them from dry cold pools associated with deeper convection. Finally, simulations also indicate that moisture stratification increases cloud scales specifically by increasing latent heating within updrafts, which increases updraft buoyancy and favors greater horizontal scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The Effect of Ice Nuclei Efficiency on Arctic Mixed-Phase Clouds from Large-Eddy Simulations

The effects of ice nuclei (IN) efficiency on the persistent ice formation in Arctic mixed-phase clouds (AMCs) are investigated using a large-eddy simulation model, coupled to a bin microphysics scheme with a prognostic IN formulation. In the three cases where the IN efficiency is high, ice formation and IN depletion are fast. When the IN concentration is 1 and 10 g -1 , IN are completely depleted and the cloud becomes purely liquid phase before the end of the 24-h simulation. When the IN concentration is 100 g -1 , the IN supply is sufficient but the liquid water is completely consumed so that the cloud dissipates quickly. In the three cases when the IN efficiency is low, ice formation is negligible in the first several hours but becomes significant as the temperature is decreased through longwave cooling. Before the end of the simulation, the cloud is in mixed phase when the IN concentration is 1 and 10 g -1 but dissipates when the IN concentration is 100 g -1 . In the case where two types of IN are considered, ice formation persists throughout the simulation. Analysis shows that as the more efficient IN are continuously removed through ice formation, the less efficient IN gradually nucleate more ice crystals because the longwave cooling decreases the cloud temperature. This mechanism is further illustrated with a simple model. These results indicate that a spectrum of IN efficiency is necessary to maintain the persistent ice formation in AMCs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part II: Idealized Markov Chain Monte Carlo Experiments

Observationally informed development of a new framework for bulk rain microphysics, the Bayesian Observationally Constrained Statistical–Physical Scheme (BOSS; described in Part I of this study), is demonstrated. This scheme’s development is motivated by large uncertainties in cloud and weather simulations associated with approximations and assumptions in existing microphysics schemes. Here, a proof-of-concept study is introduced using a Markov chain Monte Carlo sampling algorithm with BOSS to probabilistically estimate microphysical process rates and parameters directly from a set of synthetically generated rain observations. The framework utilized is an idealized steady-state one-dimensional column rainshaft model with specified column-top rain properties and a fixed thermodynamical profile. Different configurations of BOSS—flexibility being a key feature of this approach—are constrained via synthetic observations generated from a traditional three-moment bulk microphysics scheme. The ability to retrieve correct parameter values when the true parameter values are known is illustrated. For cases when there is no set of true parameter values, the accuracy of configurations of BOSS that have different levels of complexity is compared. It is found that addition of the sixth moment as a prognostic variable improves prediction of the third moment (proportional to bulk rain mass) and rain rate. In contrast, increasing process rate formulation complexity by adding more power terms has little benefit—a result that is explained using further-idealized experiments. BOSS rainshaft simulations are shown to well estimate the true process rates from constraint by bulk rain observations, with the further benefit of rigorously quantified uncertainty of these estimates.

58 GEOSCIENCES↗
DOE OSTI2021

Comments on 'Do ultrafine cloud condensation nuclei invigorate deep convection?'

Here we elaborated on the deficiencies associated with the theoretical arguments and model simulations in Grawbowski and Morrison (2020; GM20), and showed that the concept of convective invigoration by aerosols can be supported by both accurate theoretical analysis and explicit physics modeling with prognostic aerosols and supersaturation. Above the freezing level, droplet freezing itself does not change mass loading and the latent heat release resulting from freezing leads to an increase in the buoyancy. The derivation in GM20 is erroneous because of omitting the liquid water sink term. They also ignored the effect of enhanced latent heating from the subsequent growth processes (deposition and riming) after freezing. Regarding aerosol effect on condensational growth, the quasi-steady assumption for supersaturation as adopted in GM20 is invalidated especially when droplet number concentration is low and updraft is strong from both theoretical analysis and our bin microphysics modeling results. The quasi-steady assumption makes condensation independent of droplet number and size and therefore reduces the overall aerosol effects on cloud dynamics. Studying aerosol effects on clouds particularly deep convective clouds requires the exact solution of supersaturation. Any assumption imposed to supersaturation such as saturation adjustment and quasi-steady approximation leads to incorrect aerosol effects on diffusional growth. The exact supersaturation equation clearly shows that condensation depends on droplet number and size, and more droplets in the polluted clouds increase condensation (thus lower supersaturation), leading to enhanced buoyancy and updraft speeds.

Convective invigoration, deep convective clouds, a↗
DOE OSTI2024

Cloud-Resolving ICON Simulations of Secondary Ice Production in Arctic Mixed-Phase Stratocumuli Observed during M-PACE

Field measurements and modeling studies suggest that secondary ice production (SIP) may close the gap between observed Arctic ice nucleating particle (INP) concentrations and ice crystal number concentrations ni. Here, we explore sensitivities with respect to the complexity of different INP parameterizations under the premise that ni is governed by SIP. Idealized, cloud-resolving simulations are performed for the marine cold air outbreak cloud deck sampled during the Mixed-Phase Arctic Cloud Experiment (M-PACE) with the Icosahedral Nonhydrostatic (ICON) model. The impact of the droplet shattering (DS) of raindrops and collisional breakup (BR) in addition to the existing Hallet–Mossop rime splintering mechanism were investigated. Overall, 12 different model experiments (12-h runs) were performed and analyzed. Despite the considerable amount of uncertainty remaining with regard to SIP mechanisms and their process representation in numerical models, we conclude from these experiments that (i) only simulations where DS dominates the SIP signal (potentially amplified by BR) capture observed ice-phase and liquid-phase cloud properties, and (ii) SIP events cluster around the convective outflow region and are structurally linked to mesoscale cloud organization. In addition, interactions with primary nucleation parameterizations of varied complexity were investigated. Here, our simulations show that (i) a stable long-lived mixed-phase cloud (MPC) can be maintained in the absence of primary nucleation once SIP is established, (ii) experiments using a computationally more efficient relaxation-based parameterization of primary nucleation are statistically invariant from simulations considering prognostic INP, and (iii) primary nucleation at cloud-top controls the areal extent of the mixed-phase cloud region, and reduces SIP efficacy via DS due to increased depletion of cloud liquid throughout the entire cloud column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Evaluation of the New CNDV Option of the Community Land Model: Effects of Dynamic Vegetation and Interactive Nitrogen on CLM4 Means and Variability

The Community Land Model, version 4 (CLM4) includes the option to run the prognostic carbon–nitrogen (CN) model with dynamic vegetation (CNDV). CNDV, which simulates unmanaged vegetation, modifies the CN framework to implement plant biogeography updates. CNDV simulates a reasonable present-day distribution of plant functional types but underestimates tundra vegetation cover. The CNDV simulation is compared against a CN simulation using a vegetation distribution generated by CNDV and against a carbon-only simulation with prescribed nitrogen limitation (CDV). The comparisons focus on the means and variability of carbon pools and fluxes and biophysical factors, such as albedo, surface radiation, and heat fluxes. The study assesses the relative importance of incorporating interactive nitrogen (CDV to CNDV) versus interactive biogeography (CN to CNDV) in present-day equilibrium simulations. None of the three configurations performs consistently better in simulating carbon or biophysical variables compared to observational estimates. The interactive nitrogen ( N ) cycle reduces annual means and interannual variability more than dynamic vegetation. Dynamic vegetation reduces seasonal variability in leaf area and, therefore, in moisture fluxes and surface albedo. The interactive N cycle has the opposite effect of enhancing seasonal variability in moisture fluxes and albedo. CNDV contains greater degrees of freedom than CN or CDV by adjusting both through nitrogen–carbon interactions and through vegetation establishment and mortality. Thus, in these equilibrium simulations, CNDV acts as a stronger “regulator” of variability compared to the other configurations. To conclude, discussed are plausible explanations for this behavior, which has been shown in past studies to improve climate simulations through better represented climate–vegetation interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

A Sensitivity Analysis of Surface Biophysical, Carbon, and Climate Impacts of Tropical Deforestation Rates in CCSM4-CNDV*

The biophysical–climate and combined biophysical and carbon–climate feedbacks of tropical deforestation rates are explored through sensitivity analyses using the Community Climate System Model 4 with prognostic carbon–nitrogen and dynamic vegetation. Simulations test 5%, 2%, 1%, and 0.5% annual deforestation rates, each paired with preservation targets of 10% per tropical tree type. Perturbations are applied over pan-tropical land but analyses also explore responses over the subcontinental areas of the Amazon basin, central Africa, and Southeast Asia. Sensitivities [expressed as the change in a variable per million square kilometers (Mkm 2 ) of change in tree cover] and means of selected biophysical, carbon, and climate variables during and after deforestation are compared across rates. The most apparent effect of the rates is in hastening/postponing climate change, but otherwise results show no consistent differences across rates and vary more across subcontinents (with the Amazon basin reflecting highest sensitivities in albedo and ground temperatures, and Southeast Asia for total ecosystem carbon). Furthermore, biophysical feedbacks alone were found to have significant impact on climate over subcontinental scales. In the Amazon, ground temperature increase due to biophysical feedbacks is as much as 55%, and precipitation decrease up to 61%, of combined biophysical and carbon impacts. Replication with other models is required. While it is still unclear whether a slow but prolonged deforestation differs in impacts from one that is rapid but short, the rate can still be relevant to planning with regards to the timing of impacts.

54 ENVIRONMENTAL SCIENCES↗