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1. Yenisei River-South TRISH dataset of tree-ring chronologies (2025)

   https://doi.org/10.18739/a2fj29f7d  

   Panyushkina, Irina (January 2025, NSF Arctic Data Center)

   This is a two-file dataset of 111 tree-ring index chronologies calculated from ITRDB downloaded raw ring data (International Tree-Ring Data Bank at www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring) and tree rings collected by TRISH project (Collaborative Research: Fresh water and heat fluxes to the Arctic Ocean modeled with tree-ring proxies, U.S. NSF OPP award # 1917503) relevant to reconstruction of hydrologic variables for the upper reaches of Yenisei River basin. The data are in specific format suitable for a web-based reconstruction tool called Tree-Ring Integrated System for Hydrology (TRISH, https://trish.sr.unh.edu/). This data is an extended dataset of TRISH tool built-in network of tree rings called "Yenisei ITRDB (TRISH team)" that geographically focused on the upper reaches of the Yenisei River basin.\n File 1: TreeMeta111YeniseiSouthTRISH.txt\n File 2: TreeData111YeniseiSouthTRISH.txt\n READme file with the attributes of dataset."]} 

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2. TRISH: Tree-ring integrated system for hydrology, a web-based tool for reconstruction

   https://doi.org/10.1016/j.envsoft.2025.106590  

   Prusevich, Alexander A; Meko, David M; Panyushkina, Irina P; Shiklomanov, Alexander I; Lammers, Richard B; Glidden, Stanley J; Thaxton, Richard D (August 2025, Environmental Modelling & Software)

   TRISH (Tree-Ring Integrated System for Hydrology), a new web-based tool for reconstruction of water-balance variables from tree-ring proxies is described. The tool makes use of a mapping application, a global water balance model and R-based reconstruction software. Long time series of water balance variables can be reconstructed by regression or analog statistical methods from tree-ring data uploaded by the user or available in TRISH as previously uploaded public datasets. A predictand hydroclimatic time series averaged or summed over a river basin or arbitrary polygon can be generated interactively by clicking on the map. Control over reconstruction modeling includes optional lagging of predictors, transformation of predictand, and reduction of predictors by principal component analysis. Output includes displayed and downloadable graphics, statistics, and time series. The two-stage reconstruction approach in TRISH allows assessment of the strength of the hydroclimatic signal in individual chronologies in addition to providing a reconstruction based on the tree-ring network. TRISH facilitates the testing of sensitivity of reconstructions to modeling choices and allows a user to explore hydrologic reconstruction in ungauged basins. The R software for reconstruction is available for running offline in the RStudio development environment. TRISH is an open-science resource designed to be shared broadly across the Earth Science research community and to engage water resource management. 

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3. Direct Versus Indirect Tree Ring Reconstruction of Annual Discharge of Chemora River, Algeria

   https://doi.org/10.3390/f11090986  

   Meko, David; Touchan, Ramzi; Kherchouche, Dalila; Slimani, Said (September 2020, Forests)

   Annual river discharge is a critical variable for water resources planning and management. Tree rings are widely used to reconstruct annual discharge, but errors can be large when tree growth fails to respond commensurately to hydrologically important seasonal components of climate. This paper contrasts direct and indirect reconstruction as statistical approaches to discharge reconstruction for the Chemora River, in semi-arid northeastern Algeria, and explores indirect reconstruction as a diagnostic tool in reconstruction error analysis. We define direct reconstruction as predictions from regression of annual discharge on tree ring data, and indirect reconstruction as predictions from a four-stage process: (1) regression of precipitation on tree rings, (2) application of the regression model to get reconstructed precipitation for grid cells over the basin, (3) routing of reconstructed precipitation through a climatological water balance (WB) model, and (4) summing model runoff over cells to get the reconstructed discharge at a gage location. For comparative purposes, the potential predictors in both modeling approaches are the same principal components of tree ring width chronologies from a network of drought-sensitive sites of Pinus halepensis and Cedrus atlantica in northern Algeria. Results suggest that both modeling approaches can yield statistically significant reconstructions for the Chemora River. Greater accuracy and simplicity of the direct method are countered by conceptual physical advantages of the indirect method. The WB modeling inherent to the indirect method is useful as a diagnostic tool in error analysis of discharge reconstruction, points out the low and declining importance of snowmelt to the river discharge, and gives clues to the cause of severe underestimation of discharge in the outlier high-discharge year 1996. Results show that indirect reconstruction would benefit most in this basin from tree ring resolution of seasonal precipitation. 

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4. Warm Core Ring Trajectories in the Northwest Atlantic Slope Sea (2000-2010)

   https://doi.org/10.5281/zenodo.7406675  

   Porter, Nicholas; Silver, Adrienne; Gangopadhyay, Avijit (January 2022, Zenodo)

   {"Abstract":["This dataset consists of weekly trajectory information of Gulf Stream Warm Core Rings from 2000-2010. This work builds upon Silver et al. (2022a) ( https://doi.org/10.5281/zenodo.6436380) which contained Warm Core Ring trajectory information from 2011 to 2020. Combining the two datasets a total of 21 years of weekly Warm Core Ring trajectories can be obtained. An example of how to use such a dataset can be found in Silver et al. (2022b).<\/p>\n\nThe format of the dataset is similar to that of  Silver et al. (2022a), and the following description is adapted from their dataset. This dataset is comprised of individual files containing each ring\u2019s weekly center location and its area for 374 WCRs present between January 1, 2000 and December 31, 2010. Each Warm Core Ring is identified by a unique alphanumeric code 'WEyyyymmddA', where 'WE' represents a Warm Eddy (as identified in the analysis charts); 'yyyymmdd' is the year, month and day of formation; and the last character 'A' represents the sequential sighting of the eddies in a particular year. Continuity of a ring which passes from one year to the next is maintained by the same character in the first sighting.  For example, the first ring in 2002 having a trailing alphabet of 'F' indicates that five rings were carried over from 2001 which were still observed on January 1, 2002. Each ring has its own netCDF (.nc) filename following its alphanumeric code. Each file contains 4 variables, \u201cLon\u201d- the ring center\u2019s weekly longitude, \u201cLat\u201d- the ring center\u2019s weekly latitude, \u201cArea\u201d - the rings weekly size in km^{2<\/sup>, and \u201cDate\u201d in days - representing the days since Jan 01, 0000. <\/p>\n\n}The process of creating the WCR tracking dataset follows the same methodology of the previously generated WCR census (Gangopadhyay et al., 2019, 2020). The Jenifer Clark\u2019s Gulf Stream Charts used to create this dataset are 2-3 times a week from 2000-2010. Thus, we used approximately 1560 Charts for the 10 years of analysis. All of these charts were reanalyzed between 75° and 55°W using QGIS 2.18.16 (2016) and geo-referenced on a WGS84 coordinate system (Decker, 1986). <\/p>\n\n <\/p>\n\nSilver, A., Gangopadhyay, A, & Gawarkiewicz, G. (2022a). Warm Core Ring Trajectories in the Northwest Atlantic Slope Sea (2011-2020) (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6436380<\/p>\n\nSilver, A., Gangopadhyay, A., Gawarkiewicz, G., Andres, M., Flierl, G., & Clark, J. (2022b). Spatial Variability of Movement, Structure, and Formation of Warm Core Rings in the Northwest Atlantic Slope Sea. Journal of Geophysical Research: Oceans<\/em>, 127<\/em>(8), e2022JC018737. https://doi.org/10.1029/2022JC018737 <\/p>\n\nGangopadhyay, A., G. Gawarkiewicz, N. Etige, M. Monim and J. Clark, 2019. An Observed Regime Shift in the Formation of Warm Core Rings from the Gulf Stream, Nature - Scientific Reports, https://doi.org/10.1038/s41598-019-48661-9. www.nature.com/articles/s41598-019-48661-9.<\/p>\n\nGangopadhyay, A., N. Etige, G. Gawarkiewicz, A. M. Silver, M. Monim and J. Clark, 2020.  A Census of the Warm Core Rings of the Gulf Stream (1980-2017). Journal of Geophysical Research, Oceans, 125, e2019JC016033. https://doi.org/10.1029/2019JC016033.<\/p>\n\nQGIS Development Team. QGIS Geographic Information System (2016).<\/p>\n\nDecker, B. L. World Geodetic System 1984. World geodetic system 1984 (1986).<\/p>\n\n <\/p>"],"Other":["Funded by two NSF US grants OCE-1851242, OCE-212328","{"references": ["Silver, A., Gangopadhyay, A, & Gawarkiewicz, G. (2022). Warm Core Ring Trajectories in the Northwest Atlantic Slope Sea (2011-2020) (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6436380", "Silver, A., Gangopadhyay, A., Gawarkiewicz, G., Andres, M., Flierl, G., & Clark, J. (2022b). Spatial Variability of Movement, Structure, and Formation of Warm Core Rings in the Northwest Atlantic Slope Sea.\\u00a0Journal of Geophysical Research: Oceans,\\u00a0127(8), e2022JC018737.\\u00a0https://doi.org/10.1029/2022JC018737", "Gangopadhyay, A., G. Gawarkiewicz, N. Etige, M. Monim and J. Clark, 2019. An Observed Regime Shift in the Formation of Warm Core Rings from the Gulf Stream, Nature - Scientific Reports, https://doi.org/10.1038/s41598-019-48661-9. www.nature.com/articles/s41598-019-48661-9.", "Gangopadhyay, A., N. Etige, G. Gawarkiewicz, A. M. Silver, M. Monim and J. Clark, 2020. A Census of the Warm Core Rings of the Gulf Stream (1980-2017). Journal of Geophysical Research, Oceans, 125, e2019JC016033. https://doi.org/10.1029/2019JC016033.", "QGIS Development Team. QGIS Geographic Information System (2016).", "Decker, B. L. World Geodetic System 1984. World geodetic system 1984 (1986)."]}"]} 

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5. Tree‐Ring Perspectives on the Colorado River: Looking Back and Moving Forward

   https://doi.org/10.1111/1752-1688.12989  

   Meko, David M.; Woodhouse, Connie A.; Winitsky, Anabel G. (March 2022, JAWRA Journal of the American Water Resources Association)

   Abstract Tree rings have been central to the understanding of variability of flow of the Colorado River. Spurred by steadily declining flows after the 1920s, early tree‐ring research drew attention to the importance of climate variability to water supply by identifying episodes in the past that were even drier. Application of modern statistical methods to tree‐ring data later yielded a reconstruction of annual flows at Lees Ferry back to the early 1500s that highlighted the unprecedented wetness of the base period for the 1922 Colorado River Compact. That reconstruction served as the framework for a collection of papers in a 1995 special issue ofWater Resources Bulletinon coping with severe sustained drought on the Colorado River. This retrospective paper reviews historical aspects of the dendrohydrology of the Colorado River, and the updates since 1995. A constantly expanding tree‐ring network has been subjected to an array of new statistical approaches to reconstruction. Climate change and increasing demand for water have meanwhile driven increased interest in the processing and presentation of reconstructions for optimal use in water resources planning and management. While highlighting the robustness of main findings of earlier studies, recent research yields improved estimates of magnitudes of flow anomalies, extends annual flows to more than 1200 years, and underscores unmatched drought duration in the medieval period. 

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