Home » Hydrology and Land Surface Processes

Tag: Hydrology and Land Surface Processes

Terrestrial Water Storage In 2023: A Review

Earlier this month, Nature Reviews Earth & Environment released their annual Climate Chronicles, a collection of their ‘Year in Review’ articles. In these pieces, leading experts outline the observed characteristics and changes to select climate metrics and policies over the course of the year, collectively documenting the state of the climate and its ongoing evolution.

Read More »

April Showers Bring May Flowers … But With Drizzles Or Downpours?

As spring finally arrives in typical Maryland style – downpours – people take comfort in these wet days by dreaming of the blooms that the rain nurtures. However, a new study by an Earth System Science Interdisciplinary Center researcher published in Nature Reviews Earth & Environment shows that whether rainfall comes as drizzle events or downpours matters for plant growth.

Read More »
Figure A

Machine Learning-Based Estimation of Tropical Cyclone Intensity from Advanced Technology Microwave Sounder Using a U-Net Algorithm

ESSIC/CISESS scientists Yong-Keun Lee and Christopher Grassotti are co-authors on a new paper in Remote Sensing led by first author Zichao Liang, a student who interned with the MiRS team during the summer of 2023. NOAA scientists Lin Lin and Quanhua Liu also co-authored the paper. The paper, titled “Machine Learning-Based Estimation of Tropical Cyclone Intensity from Advanced Technology Microwave Sounder Using a U-Net Algorithm”, assesses the use of the U-Net model to estimate surface wind speed and surface pressure over pure ocean conditions.

Read More »
Photo by David R. Gonzalez of the Minnesota Department of Transportation

Sujay Kaushal Hosts Reddit Ask Me Anything

ESSIC scientist Sujay Kaushal and Ph.D. candidate Sydney Shelton hosted an “Ask Me Anything” (AMA) thread on Reddit on the /r/askscience subreddit. For two and a half hours, Kaushal and Shelton answered questions from the public regarding salinization and its impact on our planet.

Read More »
SatERR is a bottom-up approach, where the four types of errors including measurement, preprocessing, observation operator, and representativeness errors are generated from sources and forward propagate through radiances, science products, and data assimilation systems. This approach can quantify and partition errors and uncertainties in science products, and capture leading features of the most important errors in a statistical sense for data assimilation.

Leveraging Satellite Observations with a Comprehensive Simulator

Satellite observations are vital for weather forecasts, climate monitoring, and environmental studies. In recent years, there has been a concerted effort to develop methods for quantifying and representing errors associated with satellite observations. ESSIC scientist John Xun Yang has led a team of scientists in the creation of an error inventory simulator, the Satellite Error Representation and Realization (SatERR).

Read More »