1. |
|
|
2. |
|
|
3. |
|
|
4. |
|
|
5. |
|
|
6. |
|
|
7. |
|
|
8. |
|
|
9. |
- Buchanan, E. M., et al.
(author)
-
The Psychological Science Accelerator's COVID-19 rapid-response dataset
- 2023
-
In: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 10:1
-
Journal article (peer-reviewed)abstract
- In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.
|
|
10. |
|
|
11. |
|
|
12. |
|
|
13. |
- Smerdon, J. E., et al.
(author)
-
Comparing proxy and model estimates of hydroclimate variability and change over the Common Era
- 2017
-
In: Climate of the Past. - : Copernicus GmbH. - 1814-9324 .- 1814-9332. ; 13:12, s. 1851-1900
-
Journal article (peer-reviewed)abstract
- Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations. We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.
|
|
14. |
|
|
15. |
- Cook, ER, et al.
(author)
-
Old World megadroughts and pluvials during the Common Era
- 2015
-
In: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 1:10
-
Journal article (peer-reviewed)abstract
- Climate model projections suggest widespread drying in the Mediterranean Basin and wetting in Fennoscandia in the coming decades largely as a consequence of greenhouse gas forcing of climate. To place these and other “Old World” climate projections into historical perspective based on more complete estimates of natural hydroclimatic variability, we have developed the “Old World Drought Atlas” (OWDA), a set of year-to-year maps of tree-ring reconstructed summer wetness and dryness over Europe and the Mediterranean Basin during the Common Era. TheOWDAmatches historical accounts of severe drought and wetness with a spatial completeness not previously available. In addition, megadroughts reconstructed over north-central Europe in the 11th and mid-15th centuries reinforce other evidence from North America and Asia that droughts were more severe, extensive, and prolonged over Northern Hemisphere land areas before the 20th century, with an inadequate understanding of their causes. The OWDA provides new data to determine the causes of Old World drought and wetness and attribute past climate variability to forced and/or internal variability.
|
|
16. |
|
|
17. |
- Uvo, Cintia Bertacchi, et al.
(author)
-
The relationships between tropical Pacific and Atlantic SST and northeast Brazil monthly precipitation
- 1998
-
In: Journal of Climate. - 0894-8755. ; 11:4, s. 551-562
-
Journal article (peer-reviewed)abstract
- The monthly patterns of northest Brazil (NEB) precipitation are analyzed in relation to sea surface temperature (SST) in the tropical Pacific and Atlantic Oceans, using singular value decomposition. It is found that the relationships between precipitation and SST in both basins vary considerably throughout the rainy season (February-May). In January, equatorial Pacific SST is weakly correlated with precipitation in small areas of southern NEB, but Atlantic SST shows no significant correlation with regional precipitation. In February, Pacific SST is not well related to precipitation, but south equatorial Atlantic SST is positively correlated with preciptiation over the nrothern Nordeste, the latter most likely reflecting an anomalously early (or late) southward migration of the ITCZ precipitation zone. During March, equatorial Pacific SST is negatively correlated with Nordste precipitation, but no consistent relationship between precipitation and Atlantic SST is found. Atlantic SST-precipitation correlations for April and May are the strongest found among all months or either ocean. Precipiation in the Nordeste is positively correlated with SST in the south tropical Atlantic and negatively correlated with SST in the north tropical Atlantic. These relationships are storng enough to determine the structure of the seasonal mean SST-precipitation correlations, even though the corresponding patterns for the earlier months of the season are quite different. Pacific SST-precipitation correlations for April and May are similar to those for March. Extreme wet (dry) years for the Nordeste occur when both Pacific and Atlantic SST patterns for April and May occur simultaneously. A separate analysis reinforces previous findings in showig that SST in the tropical Pacific and the northern tropical Atlantic are positively correlated and that tropical Pacific-south Atlantic correlations are negligible. Time-lagged analyses show the potential for forecasting either seasonal mean or monthly precipitation patterns with some degree of skill. In some instances, individual monthly mean SST versus seasonal mean (February-May) precipitation relationships differ considerably from the corresponding monthly SST versus monthly precipitation relationships. It is argued that the seasonal mean relationships result from the relatively strong monthly relationships toward the end of the season, combined with the considerable persistence of SST in both oceans.
|
|