Description:

Food production, a cornerstone of our global economy, is under threat from the escalating impacts of climate change. Our warming planet is experiencing an unprecedented surge in drought and heat waves, posing a significant challenge to food security.

Farmers, growers, and city planners live in a transforming era with advanced technology like satellite information, numerical modeling at small-scale resolution, big observational data, and sophisticated assimilation systems. However, there are still challenges in the predictability of drought and, most importantly, challenges in how people are using or will use state-of-the-art climate information. 

This session is open for presenters willing to show their current challenges and limitations to advances in drought predictability at diverse time scales (seasonal, interannual, and decadal) and domains (local, regional, and global). This session will provide a platform to converge multiple disciplines studying drought using observation, modeling, and statistical post-processing. We would like you sharing with a large audience the potential of your work, find opportunities for collaboration, and, therefore, improve our efforts and help others. 

We appreciate contributions that focus on the following:

1. Modeling and computing limitations 

The predictability of climate parameters like drought has been limited in the near past. For example,drought forecasting was not blessed by the bloom of satellite information or the birth of supercomputers in the 1960s. NCAR updated its computing facility with 2488 compute nodes, each with 128 processing cores, which means 318 464 computers in the palm of a single application. This example tells how fast transformation is happening in several institutions in the US and around the globe. Therefore, we live in an unprecedented time powered by climate tools that visionaries like Ed Lorenz could not imagine. This session will try to answer how we are doing about answering societal questions like the challenges and limitations to achieve better or improved drought forecasting in a critical and transforming time. 

2. Observational aspects of drought and intense post-processing 

In the past decades, we generated massive amounts of climate data. Since the 90s, when Dr. Kalnay first introduced the NCEP/NCAR reanalysis, it was gold in the palm of a hand. Nowadays, we have massively replicated that effort, and we have multiple reanalyses with various sources of data and models. What started as a curiosity, driven by the passion for science, is now how we generate massive climate information. Thus, this session wants to open the floor to scientists using current massive information and will open opportunities for innovative and intelligent post-processing approaches; here is where the opportunities reside for Big Data and AI-ML procedures. 

The value of a forecast is tied to the trust of the forecast's end user. However, the interconnection of the problem among several disciplines targeting similar questions from different perspectives has not been discussed openly. Nowadays, people (scientists and citizen scientists) have relatively open access to models, satellite information, and affordable sensors. All of them can help with the problem's interconnection. Therefore, this session opens the opportunity to tell their stories about drought forecasting challenges and limitations.