P.I.: Trent Ford (Southern Illinois U)
Co-I: Paul A. Dirmeyer (GMU)
Program:
NOAA Modeling, Analysis and Prediction and Projection (MAPP) Program
S2S Prediction Task Force
Project Summary:
Abstract:
This research addresses the critical need to improve our understanding of how land surface initialization and
land-atmosphere interactions influence subseasonal to seasonal (S2S) predictability of extreme heat and heat
waves over North America. Accurate forecasting of extreme heat events, particularly on S2S timescales, is
important for public health preparation as vulnerability to extreme heat has increased over time. Soil moisture
anomalies, through their control on the partitioning of sensible and latent heat fluxes, are linked to temperature
extremes. Dry soils limit evapotranspiration and can establish and perpetuate extreme heat events through
atmospheric heat accumulation (e.g., Miralles et al. 2014). Therefore it is not surprising antecedent soil moisture
deficits are found to correspond strongly with extreme temperatures in most regions of the world. Recent studies
have demonstrated large spread in model forecasts and simulation of heat wave events over Europe and North America.
Significant inter-model variability is purported to be a potential consequence of different boundary layer and
convective parameterizations, land surface treatments, and coupled land-atmosphere model sensitivity. To date, few
studies have explicitly evaluated the influence of the land surface and its initialization on model predictions of
heat waves at S2S time scales.
The influence of antecedent drought conditions is particularly important in North America as past heat wave events
may be established and prolonged by both advection of warm, dry air and limitation of local moisture recycling due
to dry soils. The strong connection between the land surface and subsequent extreme heat offers promise that
realistic soil moisture initialization could improve model forecast skill. Indeed, previous results over the
contiguous United States suggest the land surface has a significant impact on extreme heat forecasts, particularly
during boreal summer (Ford and Quiring, 2014). However, there is still a lack of consensus about: (1) the role of
antecedent drought conditions in forcing heat waves over North America (2) the ability of numerical forecast models
to predict extreme heat events at S2S time scales, and (3) the importance of realistic land surface initialization
and model fidelity for accurate and timely extreme heat predictions. The goal of this project is to enhance our
understanding of the connection between droughts and heat waves in the United States, as well as evaluating the
ability of a suite of climate forecast models to predict heat wave occurrence. This goal will be achieved by
addressing three main objectives:
(1) Evaluate the ability of numerical forecast models included in the Sub-seasonal to Seasonal (S2S) Prediction
and North American Multi-Model Ensemble (NMME) Phase II projects to predict heat waves following drought events in
the United States
(2) Relate model forecast performance to parameterization of land surface variables, coupled land-atmosphere
metrics and initialization of land surface conditions
(3) Assess how more realistic land surface initialization in forecast models influences their ability to predict
and simulate heat wave events in the United States
This project specifically addresses the MAPP Competition 2 priority area of addressing the predictability of S2S
phenomena in the context of extremes and their key underlying physical processes. We will be using reforecast
datasets from the S2S Prediction Project and the North American Multi-Model Ensemble project. Our project goals are
closely aligned with the mission of the Climate Prediction Task Force of achieving significant new advances in
current capabilities to understand and predict intra-seasonal to inter-annual climate variability. In addition, the
objectives of this research addresses the NOAA high priority of the S2S prediction gap (NWS Goal 3, element 1.20 of
the Strategic Plan) as well as NOAA's goals for leadership in science and innovation. Finally the contributions of
this project to the MAPP S2S Task Force address the important issues of S2S predictability and prediction of
extreme heat in the context of land-atmosphere coupling and model land surface initialization.
Paul Dirmeyer is co-lead of the NOAA/MAPP Subseasonal-to-Seasonal Prediction Task Force
Reports:
Year 1 Progress Report
Year 2 Progress Report
Publications:
Ford, T. W. and P. A. Dirmeyer, 2016: Land-atmosphere interactions and subseasonal-to-seasonal forecasting of extreme heat in the United States. US CLIVAR Variations, 14(4), 30-35.
Ford, T. W., P. A. Dirmeyer and D. O. Benson, 2018: Evaluation of heat wave forecasts seamlessly across S2S time scales: skill attribution and the role of land-atmosphere interactions. npj Climate Atmos. Sci., doi: 10.1038/s41612-018-0027-7 (in press).