Session Advancements in Analysis and Prediction of Drought


Description:

Drought is a multi-faceted phenomenon that challenges our current prediction capabilities, yet its environmental and economic consequences are among the most serious of all natural disasters. In the changing environment of a warming climate, drought is expected to increase in frequency, duration, and intensity at both regional and global scales, and this will result in increasing environmental security risk. Improving analysis and prediction of all drought types requires the use of multiple data sources, including in-situ and remote-sensing data, surface observations, and indicators of societal impact. Satellite hydrological variables and vegetation indices have contributed dramatically to our understanding of the mechanisms of drought occurrence and development, while facilitating the separation of the drought signal from normal hydrologic and vegetation conditions. Remotely sensed land observations are used to force or parameterize models, and the hydrological outputs provide the foundation for existing drought indicators. However, making significant improvements in monitoring and prediction will not only require advances in understanding drought mechanisms, but also of the societal impacts and how to better manage water resources. There are still many open scientific questions related to data fusion, integration of drought indicators, emerging social media data sources and the optimal combination of these data sets for providing insights to climate, environmental security, and societal changes with respect to drought events. Addressing these outstanding challenges related to drought monitoring and prediction directly aligns with this year’s AMS Meeting Theme of “Living in a Changing Environment.”

 

Specific topics addressed by presenters could include but are not limited to: current drought prediction science and skills at various lead times; advances in our understanding of the causes and characteristics of drought and impacts of land-atmosphere interactions, data analyses and numerical modeling; innovative management uses of drought science; and case studies illustrating advances in understanding, monitoring and prediction of drought and drought impacts. Further, papers identifying and/or addressing gaps and deficiencies in our current methods for predicting droughts and estimating its effects on vegetation, water and energy resources, environmental security, and the health and food security of human populations are also invited.

Submitters: Joshua K. Roundy, Department of Civil, Environmental, and Architectural Engineering, Univ. of Kansas, Lawrence, KS; Molly Woloszyn; Maya Robinson, NOAA, Urbana, IL and Jason A. Otkin, CIMSS, Madison, WI


Papers:
A Global Evaluation of the Uncertainty in Land-Atmosphere Coupling-based Drought Metrics Due to Different Soil Moisture Products
Payal Ramniklal Makhasana, The University of Kansas, Lawrence, KS; University of Kansas, Lawrence, KS; and J. K. Roundy, J. A. Santanello Jr., and P. Lawston Parker

Changes in hydrological extremes as revealed by GRACE/GRACE FO data
Bailing Li, GSFC, Greenbelt, MD; University of Maryland, College Park, MD; and M. Rodell

Changes in global drought propagation driven by anthropogenic land surface transformations
Sujay V. Kumar, GSFC, Greenbelt, MD; and G. Konapala, W. Nie, and A. Getirana

Projection of Ecological Drought Under Climate Change in the Eastern United States
Catherine Anna Nikiel, ORISE/USGS Research Program Participant with the Southeast Climate Adaptation Science Center, Raleigh, NC

Evaluation of Drought Indices and Indicators for Ecological Drought in the Mid-Atlantic United States
Jacklynn Kay Beck, The Ohio State University, Columbus, OH; and S. M. Quiring

Using Seasonal Evaporative Stress Across Europe to Identify Areas Primed for Flash Drought
Daniel F. Mesheske, University of Oklahoma, Norman, OK; and J. B. Basara, J. I. Christian, and J. C. Furtado

Anticipating the Impact of the Saharan Air Layer on the Puerto Rican Early Rainfall Season
Marcus Cameron Watkins, Louisiana State University, Baton Rouge, LA; and P. W. Miller and C. A. Ramseyer, PhD

Submission Deadline: Thursday, 31 August 2023