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Hydroelectric dam on the river, water discharge from the reservoir, aerial photography

Hydropower: Worldwide Transition to Low-Carbon Energy Could Threaten Ecologically Sensitive Rivers

The global transition towards a low-carbon future could substantially accelerate hydropower deployment in ecologically sensitive rivers, according to a new study led by researchers at the University of Maryland’s Earth System Science Interdisciplinary Center (ESSIC) in collaboration with Pacific Northwest National Lab (PNNL)’s Joint Global Change Research Institute (JGCRI) and Tufts University. Published in Nature Sustainability, the paper analyzes the future hydropower expansion in the world’s 20 most ecologically sensitive rivers under different socio-economic and energy sector development scenarios.

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Isaac Moradi smiles for the camera, wearing a red gridded button-up and a red tie

Moradi Appointed to AMS Radio Frequency Allocation Committee

Isaac Moradi, a research scientist and lead of the ESSIC numerical modeling and data assimilation affinity group, has been appointed as a member of the AMS Radio Frequency Allocation Committee, bringing invaluable expertise in microwave and radar observations and their role in weather predictions. The committee focuses on coordinating radio frequency spectrum management crucial to weather, water, and climate services. It serves a pivotal role in evaluating how spectrum policy changes might impact meteorological data collection and distribution. Moradi’s career, marked by advancements in data assimilation and numerical modeling through enhancing radiative transfer models, observations error analysis, improving the data assimilation systems for assimilating these observations, and developing advanced calibration techniques for satellite data, aligns seamlessly with the committee’s mission.

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Xin-Zhong Liang Elected as AGU Fellow

Xin-Zhong Liang has been elected Fellow of the American Geophysical Union (AGU). He joins 55 other individuals in the 2023 Class of Fellows. Since 1962, the AGU Union Fellows Committee has selected less than 0.1% of members as new Fellows. AGU, a nonprofit organization that supports 130,000 enthusiasts to experts worldwide in Earth and space sciences, annually recognizes a select number of individuals as part of its Honors and Recognition program.

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Figure 5. (a, b) The analysis RMSE under full-coverage observing network for the atmosphere (a) and ocean (b) with the SC 3D-VAR (green), 4D-Var (blue), 4D-Var/3DFGAT CERA (cyan dash), 40-member ETKF (red), and 20-member ETKF (gray) for the last 1000 d. Time-averaged analysis RMSE for the last 13.7 years for all methods are shown in the figure. Panels (c) and (d) are similar to (a) and (b) except for only assimilating atmosphere observations. Adapted from Penny et al. (2019) and Da (2022).

Towards Strongly Coupled Ensemble Data Assimilation

A team of international researchers led by ESSIC Scientist Distinguished University Professor Eugenia Kalnay and including Dr. Cheng Da recently reviewed their latest research progress on coupled data assimilation in a new paper published in Nonlinear Processes in Geophysics titled, “Review article: Towards strongly coupled ensemble data assimilation with additional improvements from machine learning”.

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Jifu Yin presents “Refinement of NOAA AMSR-2 Soil Moisture Data Product using an Optimal Machine Learning Model”

ESSIC Scientists Present at NCWCP-UMD Mini-Conference

Recently, researchers from NOAA Center for Weather and Climate Prediction (NCWCP) and University of Maryland gathered for a mini-conference to share presentations from recent conferences such as the American Geophysical Union (AGU) and American Meteorological Society (AMS) annual meetings.

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