Skip to main content
U.S. flag

An official website of the United States government

Investigating the Effects of Co-Occurring Weather Phenomena on Extreme Precipitation in Reanalysis, E3SM, and CMIP6

Funding Program Area(s)
Project Type
University Grant
Project Term
Project Team

Principal Investigator

Co-Principal Investigator

Project Participant

This collaborative project aims to advance understanding of co-occurring weather phenomena and their effects on precipitation in nature and in climate model simulations by studying the co-occurrence of weather phenomena–specifically, tropical low-pressure systems (LPS), fronts, mesoscale convective systems (MCS), and atmospheric rivers (AR)–in reanalyses and climate model simulations.

Phenomenon-focused research on precipitation has just emerged to a point where multiple climate models can be evaluated based on their ability to simulate multiple types of weather phenomena. A recent paper led by members of this project team (Leung et al. 2022; doi:10.1175/JCLI-D-21-0590.1), which emerged from an ad hoc international collaboration following the 2019 DOE Workshop on Benchmarking Simulated Precipitation in Climate Models, examines the ability of High Resolution Model Intercomparison Project (HighResMIP) models to simulate tropical LPS, fronts, MCS, and ARs. This project addresses several unanswered questions arising from that working group:

Q1a How do the meteorological characteristics of weather phenomena (e.g., wind and precipitation in fronts) vary when they are or are not associated with another weather phenomenon (e.g., ARs) and how does this vary across phenomena, in space, and in time?

Q1b Does the co-occurrence of phenomena alter the statistical characteristics of precipitation (e.g., is precipitation more extreme when phenomena co-occur)?

Q2 How well does the Energy Exascale Earth System Model (E3SM) simulate co-occurring phenomena compared to individually-occurring phenomena?

Q3 What types of meteorological situations and combinations of weather phenomena do climate models simulate effectively?

We aim to answer questions Q1a–Q3 using objective methods for identifying fronts, tropical LPS, MCS, and ARs in observational datasets and climate model simulations. As outcomes and deliverables of this proposed project, we will:

1.  advance the understanding of water cycle extremes and their relationship to co-occurring phenomena in observations and climate models through research and peer-reviewed publications addressing Q1a-Q3;

2.  lower the barrier-to-entry for future research on this topic by publishing 3 open-access catalogues of the occurrence (and co-occurrence) of LPS, fronts, MCS, and ARs in ERA5, E3SMv1 HR, and HighResMIP; and

3.  enable multi-metric-based evaluation of precipitation in E3SM and HighResMIP by disseminating our metrics via a public web-based model evaluation system.

Recent Content