Your search found 3 records
1 Duan, Q.; Sorooshian , S.; Gupta, V. 1992. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resources Research, 28(4):1015-1031.
(Location: IWMI-HQ Call no: PER Record No: H010412)
2 Clark, M. P.; Luce, C. H.; AghaKouchak, A.; Berghuijs, W.; David, C. H.; Duan, Q.; Ge, S.; van Meerveld, I.; Zheng, C.; Parlange, M. B.; Tyler, S. W. 2021. Open science: open data, open models, …and open publications? Water Resources Research, 57(4):e2020WR029480. [doi: https://doi.org/10.1029/2020WR029480]
Open science ; Open data ; Open access ; Models ; Publications ; Journals ; Funding ; Costs ; Access to information ; Institutions ; Research
(Location: IWMI HQ Call no: e-copy only Record No: H050359)
(0.19 MB)
This commentary explores the challenges and opportunities associated with a possible transition of Water Resources Research to a publication model where all articles are freely available upon publication (“Gold” open access). It provides a review of the status of open access publishing models, a summary of community input, and a path forward for AGU leadership. The decision to convert to open access is framed by a mix of finances and values. On the one hand, the challenge is to define who pays, and how, and what we can do to improve the affordability of publishing. On the other hand, the challenge is to increase the extent to which science is open and accessible. The next steps for the community include an incisive analysis of the financial feasibility of different cost models, and weighing the financial burden for open access against the desire to further advance open science.
3 Fan, X.; Miao, C.; Duan, Q.; Shen, C.; Wu, Y. 2021. Future climate change hotspots under different 21st century warming scenarios. Earth’s Future, 9(6):e2021EF002027. [doi: https://doi.org/10.1029/2021EF002027]
Climate change ; Forecasting ; Global warming ; Extreme weather events ; Precipitation ; Temperature ; Emission ; Models ; Uncertainty ; Indicators / Central Africa / West Africa / Southern Africa / Central America / Arctic Region / Indonesia / Tibetan Plateau / Amazon
(Location: IWMI HQ Call no: e-copy only Record No: H050397)
https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2021EF002027
https://vlibrary.iwmi.org/pdf/H050397.pdf
https://vlibrary.iwmi.org/pdf/H050397.pdf
(4.65 MB) (4.65 MB)
Identifying climate change hotspot regions is critical for planning effective mitigation and adaptation activities. We use standard Euclidean distance (SED) to calculate integrated changes in precipitation and temperature means, interannual variability, and extremes between different future warming levels and a baseline period (1995–2014) using the Coupled Model Intercomparison Project Phase 6 (CMIP6) climate model ensemble. We find consistent hotspots in the Amazon, central and western Africa, Indonesia and the Tibetan Plateau at warming levels of 1.5 °C, 2 °C and 3 °C for all scenarios explored; the Arctic, Central America and southern Africa emerge as hotspots at 4 °C warming and at the end of the 21st century under two Shared Socioeconomic Pathways scenarios, SSP3-7.0 and SSP5-8.5. CMIP6 models show higher SED values than CMIP5, suggesting stronger aggregated effects of climate change under the new scenarios. Hotspot time of emergence (TOE) is further investigated; TOE is defined as the year when the climate change signal first exceeds the noise of natural variability in 21st century projections. The results indicate that TOEs for warming would occur over all primary hotspots, with the earliest occurring in the Arctic and Indonesia. For precipitation, TOEs occur before 2100 in the Arctic, the Tibetan Plateau and Central America. Results using a geographical detector model show that patterns of SED are shaped by extreme hot and dry occurrences at low-to-medium warming, while precipitation and temperature means and extreme precipitation occurrences are the dominant influences under the high emission scenario and at high warming levels.
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