Advances in weather prediction
Abstract
Weather forecasting provides numerous societal benefits, from extreme weather warnings to agricultural planning. In recent decades, advances in forecasting have been rapid, arising from improved observations and models, and better integration of these through data assimilation and related techniques. Further improvements are not yet constrained by limits on predictability. Better forecasting, in turn, can contribute to a wide range of environmental forecasting, from forest-fire smoke to bird migrations.
Get full access to this article
View all available purchase options and get full access to this article.
Already a Subscriber?Sign In
Correction (25 January 2019): The credits for the wildfire photo and the Tomorrow's Earth illustration have been corrected.
References and Notes
1
P. Bauer, A. Thorpe, G. Brunet, Nature 525, 47 (2015).
2
A. Perrels et al., Adv. Sci. Res. 10, 65 (2013).
3
J. K. Lazo, R. E. Morss, J. L. Demuth, Bull. Am. Meteorol. Soc. 90, 785 (2009).
4
K. Emanuel, F. Zhang, J. Atmos. Sci. 73, 3739 (2016).
5
H. Kim, F. Vitart, D. E. Waliser, J. Clim. 31, 9425 (2018).
6
O. E. J. Wing et al., Environ. Res. Lett. 13, 1 (2018).
7
D. P. Rogers, V. V. Tsirkunov, Weather and Climate Resilience: Effective Preparedness Through National Meteorological and Hydrological Services. Directions in Development (World Bank, Washington, DC, 2013).
8
F. Zhang, Y. Weng, Bull. Am. Meteorol. Soc. 96, 25 (2015).
9
L. Zampieri et al., Geophys. Res. Lett. 45, 9731 (2018).
10
B. M. Van Doren, K. G. Horton, Science 361, 1115 (2018).
11
G. Krinner, M. G. Flanner, Proc. Natl. Acad. Sci. U.S.A. 115, 9462 (2018).
12
Y. Zhang et al., Mon. Weather Rev. 146, 3363 (2018).
Information & Authors
Information
Published In
Science
Volume 363 | Issue 6425
25 January 2019
25 January 2019
Copyright
Copyright © 2019, American Association for the Advancement of Science.
This is an article distributed under the terms of the Science Journals Default License.
Submission history
Published in print: 25 January 2019
Acknowledgments
We thank colleagues, including R. Wakimoto (president of the American Meteorological Society), for comments. We acknowledge partial support from the National Science Foundation under grant OPP-1738934 and AGS-1712290. All authors contributed equally to the content and writing of this Perspective.
Authors
Metrics & Citations
Metrics
Article Usage
Altmetrics
Citations
Export citation
Select the format you want to export the citation of this publication.
Cited by
- Green Algorithms: Quantifying the Carbon Footprint of Computation, Advanced Science, 8, 12, (2100707), (2021).https://doi.org/10.1002/advs.202100707
- A forecast for large-scale, predictive biology: Lessons from meteorology, Cell Systems, 12, 6, (488-496), (2021).https://doi.org/10.1016/j.cels.2021.05.014
- Impact of Aeolus horizontal line of sight wind observations in a global NWP system, Atmospheric Research, 261, (105742), (2021).https://doi.org/10.1016/j.atmosres.2021.105742
- Service design for climate-smart agriculture, Information Processing in Agriculture, 8, 2, (328-340), (2021).https://doi.org/10.1016/j.inpa.2020.07.003
- Partial Adversarial Training for Neural Network-Based Uncertainty Quantification, IEEE Transactions on Emerging Topics in Computational Intelligence, 5, 4, (595-606), (2021).https://doi.org/10.1109/TETCI.2019.2936546
- Post-processing correction method for surface solar irradiance forecast data from the numerical weather model using geostationary satellite observation data, Solar Energy, 223, (202-216), (2021).https://doi.org/10.1016/j.solener.2021.05.055
- Perceived links between climate change and weather forecast accuracy: new barriers to tools for agricultural decision-making, Climatic Change, 168, 1-2, (2021).https://doi.org/10.1007/s10584-021-03207-9
- Diagrammatic Representations of Uncertainty in Meteorological Forecasting, Diagrammatic Representation and Inference, (466-479), (2021).https://doi.org/10.1007/978-3-030-86062-2_48
- Evaluation of Subseasonal-to-Seasonal (S2S) precipitation forecast from the North American Multi-Model ensemble phase II (NMME-2) over the contiguous U.S., Journal of Hydrology, 603, (127058), (2021).https://doi.org/10.1016/j.jhydrol.2021.127058
- Realizing the potential of digital development: The case of agricultural advice, Science, 366, 6471, (2021)./doi/10.1126/science.aay3038
- See more
Loading...
View Options
Get Access
Log in to view the full text
AAAS login provides access to Science for AAAS Members, and access to other journals in the Science family to users who have purchased individual subscriptions.
- Become a AAAS Member
- Activate your AAAS ID
- Purchase Access to Other Journals in the Science Family
- Account Help
Log in via OpenAthens.
Log in via Shibboleth.
More options
Purchase digital access to this article
Download and print this article for your personal scholarly, research, and educational use.
Buy a single issue of Science for just $15 USD.
View options
PDF format
Download this article as a PDF file
Download PDF