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6 results for “Future bias”
Dataset for the paper "Historical model biases in monthly high temperature anomalies indicate under-projection of future temperature extremes"
<div> <div>This repository holds data and scripts related to the revision of the paper entitled: <span>"Historical model biases in monthly high temperature anomalies indicate under-projection of future temperature extremes" </span>by Lei Duan, Lyssa M. Freese, Govindasamy Bala, and Ken Caldeira. <span>The paper is currently submitted for peer review. </span>Any questions regarding the data and paper could be sent to the corresponding author: Lei Duan (leiduan@carnegiescience.edu). </div> </div>
Data from: Evaluation of different bias correction methods for dynamical downscaled future projections of the California Current Upwelling System
<p class="Abstract">Biases in global Earth System Models (ESMs) are an important source of errors when used to obtain boundary conditions for regional models. Here we examine historical and future conditions in the California Current System (CCS) using three different methods to force the regional model: (1) interpolation of ESM output to the regional grid with no bias correction; (2) a "seasonally-varying" delta method that obtains a season-dependent mean climate change signal from the ESM for a 30-year future period; and (3) a "time-varying" delta method that includes the interannual variability of the ESM over the 1980–2100 period. To compare these methods, we use a high-resolution (0.1˚) physical-biogeochemical regional model to dynamically downscale an ESM projection under the RCP8.5 emission scenario. Using different downscaling methods, the sign of future changes agrees for most of the physical and ecosystem variables, but the spatial patterns and magnitudes of these changes differ, with the seasonal- and time-varying delta simulations showing more similar changes. Not correcting the ESM forcing leads to amplification of biases in some ecosystem variables as well as misrepresentation of the California Undercurrent and CCS source waters. In the non-bias corrected and time-varying delta simulations, most of the ecosystem variables inherit trends and decadal variability from the ESM, while in the seasonally-varying delta simulation, the future variability reflects the observed historical variability (1980–2010). Our results demonstrate that bias correcting the forcing prior to downscaling improves historical simulations and that the bias correction method may impact the spatial and temporal variability of future projections. </p>
Data from: Past population control biases interpretations of contemporary genetic data: implications for future invasive Sitka black-tailed deer management in Haida Gwaii
<p>Invasive species management practices often include genetic analyses to better inform decision-making and resource allocation. Yet, past management actions may artificially bias recovered patterns of genetic variation; for example, a population bottleneck caused by contemporary culling may mirror some patterns associated with historical isolation. Here, we aimed to disentangle the impacts of past management activities from natural processes for Sitka black-tailed deer (<em>Odocoileus</em> <em>hemionus</em> <em>sitkensis</em>), an invasive species that has been repeatedly culled on two islands, SGang Gwaay and Reef, within the Haida Gwaii archipelago (Canada). We applied a recently developed Genotyping-in-Thousands by sequencing panel to contemporary (e.g., blood, serum, tissue, muscle, feces) and archived deer samples, the latter collected prior to management activity within the system (c. 1997–1998), which allowed us to contextualize conflicting patterns of isolation and connectivity previously observed on SGang Gwaay and Reef. Successful genotyping (92.6%) and population genetic analysis of 292 individuals at 236 SNPs revealed signals of historical isolation on SGang Gwaay and Reef, provided evidence of a founder effect during initial colonization, and indicated an absence of ongoing gene flow. Furthermore, our spatiotemporal analyses consistently supported a priori predictions associated with bottlenecks within post-cull populations, such as within-island loss of genetic variation, elevated within-island kinship, and increased levels of among-island genetic differentiation. These findings are promising for future management of deer on SGang Gwaay and Reef, suggesting that eradications on these islands may be durable. More broadly, our work highlights the importance of understanding management history before interpreting contemporary population genetic data.</p>
Data from: Past population control biases interpretations of contemporary genetic data: implications for future invasive Sitka black-tailed deer management in Haida Gwaii
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Data from: Evaluation of different bias correction methods for dynamical downscaled future projections of the California Current Upwelling System
Open the record for dataset details and reuse information.
Multi-model ensemble bias-corrected precipitation dataset for historical and future climate (1961–2099) in China
<p>本文基于耦合模式比较项目第六阶段(CMIP6)的27个全球气候模式(GCM),采用随机森林(RF)模型和EQM方法整合27个大气监测模型的降水模拟数据,进一步修正中国综合月降水数据。修正后的降水资料在月降水量和极端降水量方面均明显优于原GCM降水资料。数据以 GeoTIFF 格式,其中嵌入了具有 1° 空间分辨率的地理配准信息。LST在GeoTIFF中的单位是mm。压缩文件被命名为历史文件.zip、SSP126.zip、SSP245.zip 和 SSP585.zip。压缩文件中的每个文件都命名为“yyyymm.tif”,其中“yyyy”和“mm”分别表示年份和月份。例如,文件“196101.tif”存储了 1961 年 1 月中国每月降水量。</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.