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Khanna, Jaya; Medvigy, David; Fueglistaler, Stephan; Walko, Robert
Abstract:
More than 20% Amazon rainforest has been cleared in the past three decades triggering important hydroclimatic changes. Small-scale (~few kilometers) deforestation in the 1980s has caused thermally-triggered atmospheric circulations that increase regional cloudiness and precipitation frequency. However, these circulations are predicted to diminish as deforestation increases. Here we use multi-decadal satellite records and numerical model simulations to show a regime shift in the regional hydroclimate accompanying increasing deforestation in Rondônia, Brazil. Compared to the 1980s, present-day deforested areas in downwind western Rondônia are found to be wetter than upwind eastern deforested areas during the local dry season. The resultant precipitation change in the two regions is approximately ±25% of the deforested area mean. Meso-resolution simulations robustly reproduce this transition when forced with increasing deforestation alone, showing a negligible role of large-scale climate variability. Furthermore, deforestation-induced surface roughness reduction is found to play an essential role in the present-day dry season hydroclimate. Our study illustrates the strong scale-sensitivity of the climatic response to Amazonian deforestation and suggests that deforestation is sufficiently advanced to have caused a shift from a thermally- to a dynamically-driven hydroclimatic regime.
Amazonian deforestation causes systematic changes in regional dry season precipitation. Some of these changes at contemporary large scales (a few hundreds of kilometers) of deforestation have been associated with a ‘dynamical mesoscale circulation’, induced by the replacement of rough forest with smooth pasture. In terms of decadal averages, this dynamical mechanism yields increased precipitation in downwind regions and decreased precipitation in upwind regions of deforested areas. Daily, seasonal, and interannual variations in this phenomenon may exist, but have not yet been identified or explained. This study uses observations and numerical simulations to develop relationships between the dynamical mechanism and the local- and continental-scale atmospheric conditions across a range of time scales. It is found that the strength of the dynamical mechanism is primarily controlled by the regional-scale thermal and dynamical conditions of the boundary layer, and not by the continental- and global-scale atmospheric state. Lifting condensation level and wind speed within the boundary layer have large and positive correlations with the strength of the dynamical mechanism. The strength of these relationships depends on time scale and is strongest over the seasonal cycle. Overall, the dynamical mechanism is found to be strongest during times when the atmosphere is relatively stable. Hence, for contemporary large scales of deforestation this phenomenon is found to be the prevalent convective triggering mechanism during the dry and parts of transition seasons (especially during the dry-to-wet transition), significantly affecting the hydroclimate during this period.
Kiefer, Janik; Brunner, Claudia E.; Hansen, Martin O. L.; Hultmark, Marcus
Abstract:
This data set contains data of a NACA 0021 airfoil as it undergoes upward ramp-type pitching motions at high Reynolds numbers and low Mach numbers. The parametric study covers a wide range of chord Reynolds numbers, reduced frequencies and pitching geometries characterized by varying mean angle and angle amplitude. The data were acquired in the High Reynolds number Test Facility at Princeton University, which is a closed-loop wind tunnel that can be pressurized up to 23 MPa and allowed for variation of the chord Reynolds number over a range of 5.0 × 10^5 ≤ Re_c ≤ 5.5 × 10^6. Data were acquired using 32 pressure taps along the surface of the airfoil. The data are the phase-averaged results of 150 individual half-cycles for any given test case.
Kim, Donghoon; Duffy, Thomas S.; Smith, Raymond F.; Ocampo, Ian K.; Coppari, Federica; Marshall, Michelle C.; Ginnane, Mary Kate; Wicks, June; Tracy, Sally J.; Millot, Marius; Lazicki, Amy; Rygg, Jame R.; Eggert, Jon H.
Kim, Donghoon; Tracy, Sally J; Smith, Raymond F; Gleason, Arianna E; Bolme, Cindy A; Prakapenka, Vitali B; Appel, Karen; Speziable, Sergio; Wicks, June K; Berryman, Eleanor J; Han, Sirus K; Schoelmerich, Markus O; Lee, Hae Ja; Nagler, Bob; Cunningham, Eric F; Akin, Minta C; Asimow, Paul D; Eggert, Jon H; Duffy, Thomas S
Severe acute respiratory coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, is of zoonotic origin. Evolutionary analyses assessing whether coronaviruses similar to SARS-CoV-2 infected ancestral species of modern-day animal hosts could be useful in identifying additional reservoirs of potentially dangerous coronaviruses. We reasoned that if a clade of species has been repeatedly exposed to a virus, then their proteins relevant for viral entry may exhibit adaptations that affect host susceptibility or response. We perform comparative analyses across the mammalian phylogeny of angiotensin-converting enzyme 2 (ACE2), the cellular receptor for SARS-CoV-2, in order to uncover evidence for selection acting at its binding interface with the SARS-CoV-2 spike protein. We uncover that in rodents there is evidence for adaptive amino acid substitutions at positions comprising the ACE2-spike interaction interface, whereas the variation within ACE2 proteins in primates and some other mammalian clades is not consistent with evolutionary adaptations. We also analyze aminopeptidase N (APN), the receptor for the human coronavirus 229E, a virus that causes the common cold, and find evidence for adaptation in primates. Altogether, our results suggest that the rodent and primate lineages may have had ancient exposures to viruses similar to SARS-CoV-2 and HCoV-229E, respectively. Included in this repository are the instructions and corresponding code required to build the dataset and run the analysis in the manuscript.
This dataset includes information about approximately 6,000 books and other items with bibliographic data as well as summary information about when the item circulated in the Shakespeare and Company lending library and the number of times an item was borrowed or purchased.
This dataset includes information about approximately 6,000 books and other items with bibliographic data as well as summary information about when the item circulated in the Shakespeare and Company lending library and the number of times an item was borrowed or purchased.
The Shakespeare and Company Project: Lending Library Events dataset includes information about approximately 35,000 lending library events including membership activities such as subscriptions, renewals and reimbursements and book-related activities such as borrowing and purchasing. For events related to lending library cards that are available as digital surrogates, IIIF links are provided.
The Shakespeare and Company Project: Lending Library Events dataset includes information about approximately 35,000 lending library events including membership activities such as subscriptions, renewals and reimbursements and book-related activities such as borrowing and purchasing. For events related to lending library cards that are available as digital surrogates, IIIF links are provided.
The Shakespeare and Company Project: Lending Library Members dataset includes information about approximately 5,600 members of Sylvia Beach's Shakespeare and Company lending library.
The Shakespeare and Company Project: Lending Library Members dataset includes information about approximately 5,200 members of Sylvia Beach's Shakespeare and Company lending library.
The Shakespeare and Company Project makes three datasets available to download in CSV and JSON formats. The datasets provide information about lending library members; the books that circulated in the lending library; and lending library events, including borrows, purchases, memberships, and renewals. The datasets may be used individually or in combination site URLs are consistent identifiers across all three. The DOIs for each dataset are as follows: Members (https://doi.org/10.34770/nsa4-3t76); Books (https://doi.org/10.34770/079z-h206); Events (https://doi.org/10.34770/rtbp-kv40).
The Shakespeare and Company Project makes three datasets available to download in CSV and JSON formats. The datasets provide information about lending library members; the books that circulated in the lending library; and lending library events, including borrows, purchases, memberships, and renewals. The datasets may be used individually or in combination site URLs are consistent identifiers across all three.
Kramer, G. J.; Bortolon, A.; Ferraro, N. M.; Spong, D. A.; Crocker, N. A.; Darrow, D. S.; Fredrickson, E. D.; Kubota, S.; Park, J.-K.; Podesta, M.; Heidbrink, W. W.
Kraus, B. Frances; Gao, Lan; Hill, K. W.; Bitter, M.; Efthimion, P. C.; Hollinger, R.; Wang, Shoujun; Song, Huanyu; Nedbailo, R.; Rocca, J. J.; Mancini, R. C.; MacDonald, M. J.; Beatty, C. B.; Shepherd, R.
We provide all the test data and corresponding predictions for our paper, “Practical Fluorescence Reconstruction Microscopy for High-Content Imaging”. Please refer to the Methods section in this paper for experimental details. For each experimental condition, we provide the input transmitted-light images (either phase contrast or DIC), the ground truth fluorescence images, and the output predicted fluorescence images which should reconstruct the ground truth fluorescence images.
The dataset contains the model file for the Global Adjoint Tomography Model 25 (GLAD-M25). The model file contains parameters defined on the spectral-element mesh and is recommend to be used in SPECFEM3D GLOBE for seismic wave simulation at the global scale.
