80 citations as recorded by crossref.

1. Assessing forest vulnerability to climate warming using a process‐based model of tree growth: bad prospects for rear‐edges R. Sánchez‐Salguero et al. https://doi.org/10.1111/gcb.13541
2. The importance of input data quality and quantity in climate field reconstructions – results from the assimilation of various tree-ring collections J. Franke et al. https://doi.org/10.5194/cp-16-1061-2020
3. The climatic drivers of normalized difference vegetation index and tree‐ring‐based estimates of forest productivity are spatially coherent but temporally decoupled in Northern Hemispheric forests K. Seftigen et al. https://doi.org/10.1111/geb.12802
4. Northeastern North America as a potential refugium for boreal forests in a warming climate L. D’Orangeville et al. https://doi.org/10.1126/science.aaf4951
5. Possible Increase of Vegetation Exposure to Spring Frost under Climate Change in Switzerland O. Lhotka & S. Brönnimann https://doi.org/10.3390/atmos11040391
6. Decadal–centennial hydroclimate variability over eastern China during the last millennium: Results from the product of Paleo Hydrodynamics Data Assimilation Y. Peng https://doi.org/10.1016/j.aosl.2021.100038
7. Intra-annual density fluctuations in Pinus massoniana across subtropical forests in China: Occurrence patterns and triggering factors Q. He et al. https://doi.org/10.1016/j.agrformet.2025.110990
8. Testing the performance of dendroclimatic process-based models at global scale with the PAGES2k tree-ring width database J. Rezsöhazy et al. https://doi.org/10.1007/s00382-021-05789-7
9. New tree-ring data from Canadian boreal and hemi-boreal forests provide insight for improving the climate sensitivity of terrestrial biosphere models A. Mirabel et al. https://doi.org/10.1016/j.scitotenv.2022.158062
10. Process representation of conifer tree-ring growth is improved by incorporation of climate memory effects X. ZENG et al. https://doi.org/10.1016/j.agrformet.2022.109196
11. Climate field reconstruction uncertainty arising from multivariate and nonlinear properties of predictors M. Evans et al. https://doi.org/10.1002/2014GL062063
12. Application and evaluation of the dendroclimatic process-based model MAIDEN during the last century in Canada and Europe J. Rezsöhazy et al. https://doi.org/10.5194/cp-16-1043-2020
13. Challenges and perspectives for large‐scale temperature reconstructions of the past two millennia B. Christiansen & F. Ljungqvist https://doi.org/10.1002/2016RG000521
14. Regional climate and site conditions, not species, determine growth and vulnerability to future climate extremes of Central European oaks M. Vejpustková et al. https://doi.org/10.1016/j.tfp.2026.101199
15. Tree growth decline as a response to projected climate change in the 21st century in Mediterranean mountain forests of Chile V. Matskovsky et al. https://doi.org/10.1016/j.gloplacha.2020.103406
16. A triple tree-ring constraint for tree growth and physiology in a global land surface model J. Barichivich et al. https://doi.org/10.5194/bg-18-3781-2021
17. rwl_read: A MATLAB program to identify and correct formatting errors in tree-ring measurement files Y. Liu https://doi.org/10.1016/j.softx.2022.101285
18. An Artificial Neural Networks‐Based Tree Ring Width Proxy System Model for Paleoclimate Data Assimilation M. Fang & X. Li https://doi.org/10.1029/2018MS001525
19. Atmospheric dynamics drive most interannual U.S. droughts over the last millennium M. Erb et al. https://doi.org/10.1126/sciadv.aay7268
20. Last Millennium ENSO Diversity and North American Teleconnections: New Insights From Paleoclimate Data Assimilation X. Luo et al. https://doi.org/10.1029/2021PA004283
21. Two types of North American droughts related to different atmospheric circulation patterns A. Burgdorf et al. https://doi.org/10.5194/cp-15-2053-2019
22. Seasonal Growth of Pine Tree Rings: Comparison of Direct Observations and Simulation E. Babushkina et al. https://doi.org/10.3390/f13121978
23. Predicting spatiotemporal variability in radial tree growth at the continental scale with machine learning P. Bodesheim et al. https://doi.org/10.1017/eds.2022.8
24. Insights into the BRT (Boosted Regression Trees) Method in the Study of the Climate-Growth Relationship of Masson Pine in Subtropical China H. Gu et al. https://doi.org/10.3390/f10030228
25. Should artificial neural networks replace linear models in tree ring based climate reconstructions? J. Jevšenak & T. Levanič https://doi.org/10.1016/j.dendro.2016.08.002
26. Non-linear modelling reveals a predominant moisture limit on juniper growth across the southern Tibetan Plateau H. Jia et al. https://doi.org/10.1093/aob/mcac065
27. Evidence of advancing spring xylem phenology in Chinese forests under global warming H. Xue et al. https://doi.org/10.1007/s11430-022-1149-x
28. A tree-ring perspective on the terrestrial carbon cycle F. Babst et al. https://doi.org/10.1007/s00442-014-3031-6
29. Climate response of oak (Quercus spp.), an evidence of a bioclimatic boundary induced by the Carpathians C. Nechita et al. https://doi.org/10.1016/j.scitotenv.2017.05.118
30. An overview of tree-ring width records across the Northern Hemisphere S. St. George https://doi.org/10.1016/j.quascirev.2014.04.029
31. Tropical Pacific Modulation of the Asian Summer Monsoon Over the Last Millennium in Paleoclimate Data Assimilation Reconstructions J. Hu et al. https://doi.org/10.1029/2023JD039207
32. Different Radial Growth Responses to Climate Change of Three Dominant Conifer Species in Temperate Forest, Northeastern China H. Wang et al. https://doi.org/10.3389/ffgc.2021.820800
33. Climate change detection and attribution using observed and simulated tree-ring width J. Franke et al. https://doi.org/10.5194/cp-18-2583-2022
34. A reconstruction of global hydroclimate and dynamical variables over the Common Era N. Steiger et al. https://doi.org/10.1038/sdata.2018.86
35. DOCU-CLIM: A global documentary climate dataset for climate reconstructions A. Burgdorf et al. https://doi.org/10.1038/s41597-023-02303-y
36. The summer standardized precipitation evapotranspiration index (SPEI) dataset for six European regions over the past millennium reconstructed by tree-ring chronologies L. Zhang et al. https://doi.org/10.1080/20964471.2023.2247864
37. Correlation and causation in tree‐ring‐based reconstruction of paleohydrology in cold semiarid regions A. Elshorbagy et al. https://doi.org/10.1002/2016WR018985
38. A monthly global paleo-reanalysis of the atmosphere from 1600 to 2005 for studying past climatic variations J. Franke et al. https://doi.org/10.1038/sdata.2017.76
39. Last Millennium Reanalysis with an expanded proxy database and seasonal proxy modeling R. Tardif et al. https://doi.org/10.5194/cp-15-1251-2019
40. Was the Little Ice Age more or less El Niño-like than the Medieval Climate Anomaly? Evidence from hydrological and temperature proxy data L. Henke et al. https://doi.org/10.5194/cp-13-267-2017
41. Increased growth of Qinghai spruce in northwestern China during the recent warming hiatus L. Gao et al. https://doi.org/10.1016/j.agrformet.2018.05.025
42. The International Tree‐Ring Data Bank (ITRDB) revisited: Data availability and global ecological representativity S. Zhao et al. https://doi.org/10.1111/jbi.13488
43. Paleoclimate data assimilation: Its motivation, progress and prospects M. Fang & X. Li https://doi.org/10.1007/s11430-015-5432-6
44. Climate Warming Alters Age-Dependent Growth Sensitivity to Temperature in Eurasian Alpine Treelines R. Sanchez-Salguero et al. https://doi.org/10.3390/f9110688
45. A database of databases for Common Era paleoclimate applications M. Evans et al. https://doi.org/10.5194/essd-18-1185-2026
46. Modeled Tracheidograms Disclose Drought Influence on Pinus sylvestris Tree-Rings Structure From Siberian Forest-Steppe M. Popkova et al. https://doi.org/10.3389/fpls.2018.01144
47. An interpreted language implementation of the Vaganov–Shashkin tree-ring proxy system model K. Anchukaitis et al. https://doi.org/10.1016/j.dendro.2020.125677
48. Spatial patterns of precipitation-induced moisture availability and their effects on the divergence of conifer stem growth in the western and eastern parts of China’s semi-arid region X. Zeng et al. https://doi.org/10.1016/j.foreco.2019.117524
49. Species-specific climate–growth interactions determine tree species dynamics in mixed Central European mountain forests J. Kašpar et al. https://doi.org/10.1088/1748-9326/abd8fb
50. Dendrobox – An interactive exploration tool for the International Tree Ring Data Bank C. Zang https://doi.org/10.1016/j.dendro.2014.10.002
51. Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model W. Acevedo et al. https://doi.org/10.5194/cp-13-545-2017
52. Forward Modeling Reveals Multidecadal Trends in Cambial Kinetics and Phenology at Treeline J. Tumajer et al. https://doi.org/10.3389/fpls.2021.613643
53. Disentangling the multi-faceted growth patterns of primary Picea abies forests in the Carpathian arc J. Björklund et al. https://doi.org/10.1016/j.agrformet.2019.03.002
54. Response of Larix chinensis Radial Growth to Climatic Factors Using the Process-Based Vaganov–Shashkin-Lite Model at Mt. Taibai, China S. Li et al. https://doi.org/10.3390/f13081252
55. Process-Based Modeling of Phenology and Radial Growth in Pinus tabuliformis in Response to Climate Factors over a Cold and Semi-Arid Region Z. Man et al. https://doi.org/10.3390/plants13070980
56. How can the parameterization of a process-based model help us understand real tree-ring growth? I. Tychkov et al. https://doi.org/10.1007/s00468-018-1780-2
57. Linkage between growth phenology and climate-growth responses along landscape gradients in boreal forests J. Tumajer et al. https://doi.org/10.1016/j.scitotenv.2023.167153
58. Assimilating an expanded tree ring dataset to reconstruct the millennial air temperature fields for the Northern Hemisphere M. Fang et al. https://doi.org/10.1002/joc.7528
59. Daily climate data reveal stronger climate-growth relationships for an extended European tree-ring network J. Jevšenak https://doi.org/10.1016/j.quascirev.2019.105868
60. Simultaneous Optimal Target Season Estimation and Local Climate Reconstruction Using Tree Rings N. Hwangbo et al. https://doi.org/10.1029/2025GL116495
61. Drought explains variation in the radial growth of white spruce in western Canada L. Chen et al. https://doi.org/10.1016/j.agrformet.2016.11.012
62. An additional step toward comprehensive paleoclimate reanalyses H. Goosse https://doi.org/10.1002/2016MS000739
63. Comparing proxy and model estimates of hydroclimate variability and change over the Common Era https://doi.org/10.5194/cp-13-1851-2017
64. Forward modeling of tree-ring width improves simulation of forest growth responses to drought M. Mina et al. https://doi.org/10.1016/j.agrformet.2016.02.005
65. Converging Climate Sensitivities of European Forests Between Observed Radial Tree Growth and Vegetation Models Z. Zhang et al. https://doi.org/10.1007/s10021-017-0157-5
66. Tunneling-induced groundwater depletion limits long-term growth dynamics of forest trees H. Behzad et al. https://doi.org/10.1016/j.scitotenv.2021.152375
67. Resist, recover or both? Growth plasticity in response to drought is geographically structured and linked to intraspecific variability in Pinus pinaster R. Sánchez‐Salguero et al. https://doi.org/10.1111/jbi.13202
68. Beyond meteorological data: Modelling tree growth with ERA5-Land M. Schönauer et al. https://doi.org/10.1016/j.agrformet.2025.110679
69. Evaluation of daily gridded climate products using in situ FLUXNET data and tree growth modeling F. Wang et al. https://doi.org/10.1088/1748-9326/ae384b
70. Temporal changes in climatic limitation of tree-growth at upper treeline forests: Contrasted responses along the west-to-east humidity gradient in Northern Patagonia A. Lavergne et al. https://doi.org/10.1016/j.dendro.2015.09.001
71. Towards the assimilation of tree-ring-width records using ensemble Kalman filtering techniques W. Acevedo et al. https://doi.org/10.1007/s00382-015-2683-1
72. Increasing moisture limitation of Norway spruce in Central Europe revealed by forward modelling of tree growth in tree-ring network J. Tumajer et al. https://doi.org/10.1016/j.agrformet.2017.07.015
73. Growth-limiting factors and climate response variability in Norway spruce (Picea abies L.) along an elevation and precipitation gradients in Slovenia J. Jevšenak et al. https://doi.org/10.1007/s00484-020-02033-5
74. ModE-RA: a global monthly paleo-reanalysis of the modern era 1421 to 2008 V. Valler et al. https://doi.org/10.1038/s41597-023-02733-8
75. Impact of disturbance signatures on tree-ring width and blue intensity chronology structure and climatic signals in Carpathian Norway spruce Y. Jiang et al. https://doi.org/10.1016/j.agrformet.2022.109236
76. Contrasting growth responses in Himalayan trees to future climate R. Dhyani et al. https://doi.org/10.1016/j.scitotenv.2025.179700
77. 古气候数据同化<bold>: </bold>缘起<bold>、</bold>进展与展望 苗. 方 & 新. 李 https://doi.org/10.1360/N072015-00432
78. When tree rings go global: Challenges and opportunities for retro- and prospective insight F. Babst et al. https://doi.org/10.1016/j.quascirev.2018.07.009
79. Climate sensitivity of seasonal radial growth in young stands of Mexican conifers M. Pompa-García et al. https://doi.org/10.1007/s00484-022-02312-3
80. The Historical Development of Large‐Scale Paleoclimate Field Reconstructions Over the Common Era J. Smerdon et al. https://doi.org/10.1029/2022RG000782