563 research outputs found
Correction to: Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions (Advances in Atmospheric Sciences, (2022), 39, 6, (819-860), 10.1007/s00376-021-1371-9)
No full textThe article “Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions”, written by Yun QIAN, TC CHAKRABORTY, Jianfeng LI, Dan LI, Cenlin HE, Chandan SARANGI, Fei CHEN, Xuchao YANG, and L. Ruby LEUNG was originally published electronically on the publisher’s internet portal on 25 of January 2022 with open access.</p
MJO-QBO Model Inter-comparison Data
No full textData in support of the paper "The Lack of a QBO-MJO Connection in Climate Models with a Nudged Stratosphere" by Zane K. Martin, Isla R. Simpson, Pu Lin, Clara Orbe, Qi Tang, Julie M. Caron, Chih-Chieh Chen, Hyemi Kim, L. Ruby Leung, Jadwiga H. Richter, and Shaocheng Xie, currently in preparation for submission.
Data is organized by model, then ensemble member, then the temporal data resolution.
Daily data are daily model OLR (olr/) and precipitation (precip/) in lat/lon/time format, over at least the tropical region spanning all longitudes and 20N to 20S. Daily data also include the Real-time Multivariate MJO index (RMM; RMM_index/) value from each model and ensemble members. OLR and precip files are provided on a 2.5 x 2.5 degree similar grid, rather than the models' native grid.
Monthly data are temperature (temp/, at all vertical levels and all longitudes, from at least 20N to 20S, and the 100 hPa temperature file, as described more in the paper) zonal wind (at all vertical levels, and the 50 hPa wind file; wind/), and TEM vertical velocity (wtem/)
Atmospheric_river_land_hydrology_western_US_HUC8_datasets
No full textDataset for the manuscript entitled "Impact of Atmospheric Rivers on Surface Hydrological Processes in Western U.S. Watersheds".
It includes daily meteorological and surface hydrological data from western U.S. WRF simulation. Data is aggregated to 8-digit Hydrological Unit (HUC8) watersheds.
To use this dataset, please cite the following two publications:
Chen, X., Leung, L. R., Gao, Y., Liu, Y., Wigmosta, M., & Richmond, M. (2018). Predictability of extreme precipitation in western U.S. watersheds based on atmospheric river occurrence, intensity, and duration. Geophysical Research Letters, 45, 11,693–11,701. https://doi.org/10.1029/2018GL079831
Chen, X., Leung, L. R., Wigmosta, M., & Richmond, M. (2019). Impact of Atmospheric Rivers on Surface Hydrological Processes in Western U.S. Watersheds. Journal of Geophysical Research: Atmospheres, https://doi.org/10.1029/2019JD03468</p
A multi-algorithm approach for modeling coastal wetland eco-geomorphology
No full textCoastal wetlands play an important role in the global water and biogeochemical
cycles. Climate change makes it more difficult for these ecosystems to adapt
to the fluctuation in sea levels and other environmental changes. Given the
importance of eco-geomorphological processes for coastal wetland resilience,
many eco-geomorphology models differing in complexity and numerical
schemes have been developed in recent decades. However, their divergent
estimates of the response of coastal wetlands to climate change indicate
that substantial structural uncertainties exist in these models. To investigate
the structural uncertainty of coastal wetland eco-geomorphology models,
we developed a multi-algorithm model framework of eco-geomorphological
processes, such as mineral accretion and organic matter accretion, within a
single hydrodynamics model. The framework is designed to explore possible
ways to represent coastal wetland eco-geomorphology in Earth system models
and reduce the related uncertainties in global applications. We tested this model
framework at three representative coastal wetland sites: two saltmarsh wetlands
(Venice Lagoon and Plum Island Estuary) and a mangrove wetland (Hunter
Estuary). Through the model–data comparison, we showed the importance
of using a multi-algorithm ensemble approach for more robust predictions of
the evolution of coastal wetlands. We also found that more observations of
mineral and organic matter accretion at different elevations of coastal wetlands
and evaluation of the coastal wetland models at different sites in diverse
environments can help reduce the model uncertainty
THE RUBY LASER AS A RAMAN SOURCE
No full textNow at the Physics Dept., Washington, University, St. Louis, Missouri. S. P. S. Porto And D. L. Wood, J. Opt. Soc. Am, 52, 251, 1962.Author Institution: Bell Telephone Laboratories Incorporated“The ruby laser has been used successfully by Porto and Wood as a source of Raman The main difficulty in their original experiments wag the large number of flashes necessary to obtain the effect even for and . Recent improvements in our instrumentation, the most important of which is a more powerful later, has mode it possible to obtain tile Raman effect of vibration if benzene in one laser burst. Details of the instrumentation will be discussed well as the possibility of using the gas lasers as source for the Raman effect.
Atmospheric_river_precipitation_predictability_data
No full text<p>Data for the manuscript entitled "Predictability of Extreme Precipitation Associated With Atmospheric Rivers in Western U.S. Watersheds".</p>
<p> </p>
<p>It includes daily precipitation data from WRF and PRISM. Also includes atmospheric river information derived from ARTMIP Tier 1 archive.</p>
<p> </p>
<p>The tools used to generate the figures in the paper is at: <a href="https://github.com/lucas-uw/Chen-2018-GRL">https://github.com/lucas-uw/Chen-2018-GRL</a></p>
<p> </p>
<p>If you use this dataset, please cite the following paper:</p>
<p> </p>
<p>Chen, X., Leung, L. R., Gao, Y., Liu, Y., Wigmosta, M., & Richmond, M. (2018). Predictability of extreme precipitation in western U.S. watersheds based on atmospheric river occurrence, intensity, and duration. Geophysical Research Letters, 45, 11,693–11,701. <a href="http://doi.org/10.1029/2018GL079831">https://doi.org/10.1029/2018GL079831</a></p>
<p> </p>
<p>Chen, X., Leung, L. R., Wigmosta, M., & Richmond, M. (2019). Impact of Atmospheric Rivers on Surface Hydrological Processes in Western U.S. Watersheds. Journal of Geophysical Research: Atmospheres, <a href="http://doi.org/10.1029/2019JD03468">https://doi.org/10.1029/2019JD03468</a></p>
Precipitation objects under the current and future climate: WRF 6-km hydroclimate simulation of the western US
No full textThis folder includes the precipitation objects that are used in the following manuscript:
Chen et al., Sharpening of Cold Season Storms over the Western US.
It is generated using WRF V3.8 at PNNL. A historical simulation ("NARR") is done for 1981-2010, and five future simulations ("CanESM2", "CESM1-CAM5", "GFDL-ESM2M", "HadGEM2-ES", "MPI-ESM-MR") are done for 2041-2070 using the Pseudo Global Warming (PGW) approach. For the WRF model configuration and the simulation details, please refer to the abovementioned manuscript and Chen et al. (2018).
This is the preliminary version of the dataset that contains the precipitation object features as analyzed in the manuscript. More data (including the WRF raw precipitation output) and the finalized scripts will be included here before the manuscript is published.
Reference:
Chen, X., L. R. Ruby, Y. Gao, Y. Liu, M. Wigmosta, and M. Richmond (2018), Predictability of Extreme Precipitation in Western U.S. Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration, Geophys. Res. Lett. doi: 10.1029/2018GL079831
Chen, X., L. R. Ruby, Y. Gao, Y. Liu, and M. Wigmosta (xxxx), Sharpening of Cold Season Storms over the Western US, Nat. Clim. Change
An analysis of the reading difficulties of selected groups of Atlanta University students enrolled in reading, 1967
No full textIdentification and localization of cardiac myosin in preimplantation and cultured rabbit embryos
No full text- …
