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6 results for “near-term forecasting”
State-of-the-art review of near-term freshwater forecasting literature published between 2017 and 2022
This data publication includes code and results from a systematic literature review on the current state of near-term forecasting of freshwater quality. The review aimed to address the following questions: (1) Freshwater variables, scales, models, and skill: Which freshwater variables and temporal scales are most commonly targeted for near-term forecasts, and what modeling methods are most commonly employed to develop these forecasts? How is the accuracy of freshwater quality forecasts assessed, and how accurate are they? How is uncertainty typically incorporated into water quality forecast output? (2) Forecast infrastructure and workflows: Are iterative, automated workflows commonly employed in near-term freshwater quality forecasting? How are forecasts validated and archived? (3) Human dimensions: What is the stated motivation for development of most near-term freshwater quality forecasts, and who are the most common end users (if any)? How are end users engaged in forecast development? An initial search was conducted for published papers presenting freshwater quality forecasts from 1 January 2017 to 17 February 2022 in the Web of Science Core Collection. Results were subsequently analyzed in three stages. First, paper titles were screened for relevance. Second, an initial screen was conducted to assess whether each paper presented a near-term freshwater quality forecast. Third, papers that passed the initial screen were analyzed using a standardized matrix to assess the state of near-term freshwater quality forecasting and identify areas of recent progress and ongoing challenges. Additional details regarding the systematic literature search and review are presented in the Methods section of the metadata.
Data assimilation experiments inform monitoring needs for near-term ecological forecasts in a eutrophic reservoir: data, forecasts, and scores
<p>This data publication contains zipped parquet from the Beaverdam Reservoir forecasting data assimilation experiments using the FLARE (Forecasting Lake And Reservoir Ecosystems) system: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations and meteorological data, forecasts.zip contains forecast parquet files generated from the BVR FLARE DA experiment workflow, and scores.zip contains forecast skill metrics required for analysis. Within the forecasts and scores folders, there are four runs that were conducted with different parameter tuning and uncertainty quantification. The "all_UC" folder includes forecasts run with process, driver, parameter, and initial condition uncertainty quantification. The "IC_off" folder includes forecasts run without initial conditions uncertainty included (i.e., only process, driver, and parameter uncertainty). The "constant_bad_pars" folder includes forecasts run with constant parameters (but daily updating of initial conditions) that were not tuned for Beaverdam Reservoir before forecasts were generated. Finally, the "tuned_bad_pars" folder includes forecasts that were run with daily updating of initial conditions and parameters, but the parameters started out at random values that were not tuned for Beaverdam Reservoir.</p>
Systematic review of near-term ecological forecasting literature published between 1932 and 2020
This data publication includes results and code from a systematic review of near-term ecological forecasting literature. The study had two primary goals: (1) analyze the state of near-term ecological forecasting literature, and (2) compare forecast skill across ecosystems and variables. We began by conducting a Web of Science search for “forecast*” in the title, abstract, and keywords of all papers published in ecological journals, then screened all papers from this search to identify near-term ecological forecasts. We defined a near-term ecological forecast as future predictions of community, population, or biogeochemical variables ≤ 10 years from the forecast date. To more broadly survey the literature, we then searched all papers that cited or were cited by the near-term ecological forecasts we identified. We performed an in-depth review of all near-term ecological forecasting papers identified through this search process, and recorded forecast skill data for all papers that reported R or R2. Our results indicate that the rate of publication of near-term ecological forecasts is increasing over time and the field is becoming increasingly open and automated. Across published forecasts, we find that forecast skill decreases in predictable patterns and these patterns differ between forecast variables. This data publication includes three products from this analysis: (1) a database of all papers identified in the two searches, including our assessment of whether they included an ecological focal variable, included a forecast, and whether the forecast was near-term (≤10 years), (2) a matrix of all data collected on the near-term ecological forecasts we identified, and (3) a database of R2 values for papers that reported R or R2.
Code for Manuscript - Near-term lake water temperature forecasts can be used to anticipate the ecological dynamics of freshwater species -
<p>Code for Manuscript - Near-term lake water temperature forecasts can be used to anticipate the ecological dynamics of freshwater species -</p>
Data and GrADS scripts needed to reproduce the figures in the article "Probabilistic forecasts of near-term climate change: verification for temperature and precipitation changes from years 1971-2000 to 2011-2020"
<p>Data and GrADS scripts needed to reproduce the figures in the article "Probabilistic forecasts of near-term climate change: verification for temperature and precipitation changes from years 1971-2000 to 2011-2020", submitted for publication in Climate Dynamics.</p> <p>Please see the file README for further details.</p> <p> </p>
A multi-model ensemble of baseline and process-based models improves the predictive skill of near-term lake forecasts: data, forecasts, and scores
<p>This data publication contains zipped parquet from the Falling Creek Reservoir multi-model ensemble (MME) forecasting work using the FLARE (Forecasting Lake And Reservoir Ecosystems) system and baseline models: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations, forecasts.zip contains forecast parquet files generated from the MME workflow (FLARE & baseline models), and scores.zip contains forecast skill metrics required for analysis.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.