NSC projects November 2018 - October 2019

Turbulent flow over two- and three-dimensional forested hills

Project lead: Edward Patton, MMM
Cheyenne allocation: 8 million core-hours

This project serves as a request for the core-hours necessary to complete an effort initiated by a 2017 NSC award. Under this continuation effort, we will perform eight to 10 additional turbulence-resolving simulations of flow over two-dimensional and three-dimensional canopy-covered low hills. Analysis of data arising from these simulations will work to extend the community's current theory of flow over two-dimensional to three-dimensional canopy-covered hills spanning a range of hill steepness, shape, canopy density, and atmospheric stability for more accurate parameterization of orographic drag and improved weather and climate prediction.

After this past year's successful effort studying the influence of hill slope and hill shape for a single canopy-density distribution, our 2018 effort will focus on interrogating the influence of canopy-density variation and atmospheric stability. Eight to 10 simulations will be conducted to establish the influence of radiational heating/cooling on orographic drag and the influence of canopy-induced processes. Then we'll work to establish the canopy-induced mechanisms controlling orographic drag by undertaking a number of simulations varying the canopy-density distribution (i.e., shifting to a more sparse/dense but horizontally-homogeneous canopy, to canopy configuration representing a broadleaf vs. evergreen forest, and then possibly to a more natural situation where the flow is in equilibrium with a sparse grassy surface and then impinges on an isolated forested hill).

Subseasonal to seasonal prediction with NCAR's CESM2-WACCM: role of stratosphere and MLT predictability

Project lead: Jadwiga Richter, CGD
Cheyenne allocation: 12.7 million core-hours

Subseasonal-to-seasonal (S2S) prediction is a fast-growing research area and becoming a larger strategic priority for CGD and for NCAR as a whole. This project aims to better understand the processes responsible for predictability on the S2S timescales (2 to 6 weeks), in particular the role of the stratosphere and role of improved model physics. In addition to understanding S2S prediction in the troposphere, this project will perform the first in-depth study of the predictability of the mesosphere and lower thermosphere (MLT). Variability in the MLT drives a significant portion of near-Earth space weather, and understanding the predictability in the MLT is thus an important component of enhancing space weather forecasting, an important priority within HAO/NCAR.

We propose here to run S2S hindcasts for the time period from 1999 to 2018 using CESM2-WACCM in order to: a) understand processes that contribute to increased predictability on the S2S timescale, with the focus on stratospheric influences, b) quantify change in predictive skill of CESM2-WACCM as compared to the default CESM2, and c) begin investigations of predictability of the MLT region.

Quantification of mass, energy and momentum transport processes by organized convection for MCSP parameterization development in CESM2

Project lead: Changhai Liu, RAL
Cheyenne allocation: 6 million core-hours

In this project we propose to conduct high-resolution regional simulations of tropical convection with the Weather Research and Forecasting (WRF) model at 0.5-km grid spacing in order to investigate convective mass, energy and momentum transport processes and improve their parameterizations for global climate models (GCMs). Specifically, six two-week-long simulations with a horizontal domain of 2500 km × 2500 km will be performed over the Indian Ocean and tropical Pacific regions, with initial and boundary conditions from hourly, 31-km-resolution ERA5 reanalysis. These multiple large-domain simulations provide a sufficient sampling of organized mesoscale convective systems under a variety of large-scale environments, lending a unique opportunity to examine the mass, energy and momentum transport by tropical convection for parameterization development in GCMs. Specifically, key questions to be addressed in this proposed project are: 1) to quantify mesoscale vs. cumulus momentum transports; 2) determine optimal parameterization parameters in the newly developed multiscale coherent structure parameterization (MCSP); 3) refine MCSP by determining relationships between MCS propagation and the environmental state, e.g., shear, mean-flow, and convective available potential energy (CAPE); and 4) investigate the effects of westward-moving organized superclusters on large-scale, eastward-moving convective coherence (i.e., convectively coupled Kelvin waves and the MJO). This project is of high strategic importance because it addresses some poorly-treated convective processes in contemporary global weather and climate models. It directly tackles one of the grand challenges articulated in the NCAR strategic plan: “Improved understanding and prediction of atmospheric, chemical and space weather hazards and their impacts on ecosystems, people and society,” and is directly related to the NCAR imperative “Conduct innovative fundamental research to advance the atmospheric and related sciences.” The proposed research fits well into NWSC Community Science Domain A.1.5 “Improved treatments of sub-grid-scale physical, chemical and biological phenomena in component models of global climate models” and A.2.1 “Explicitly resolve all climate processes (rather than using parameterization or compensating for errors).” The series of large-domain, convection-resolving simulations will provide a unique high-resolution community dataset for tropical convection research, including international projects coordinated by the Global Energy and Water Exchanges (GEWEX) Atmospheric System Studies (GASS) program of the World Meteorological Organization.

High-resolution ensemble analysis and forecast system development

Project lead: Glen Romine, MMM
Cheyenne allocation: 22.5 million core-hours

High-impact weather prediction capability has steadily improved over time, largely owing to advances in numerical models, data assimilation methods, and the emergence of convection-permitting ensemble (CPE) forecasts that provide probabilistic guidance on hazards. A major recent advance in CPE analysis capability enabled large-scale, high-resolution ensemble analysis which allows for the use of cloud-scale observations to improve the ensemble initial state and subsequent forecasts. Still, progress in improving forecast skill and reliability of CPE forecasts has been hampered by uncertainty in best-practice for analysis and prediction system design given the very recent emergence of this capability. This activity will examine two key design choices in CPE analysis. First, we will compare two approaches to carry forward background information forward, or “cycling,” where one method only uses short forecasts from prior analyses (continuous cycling) and the other method periodically replaces the background with a coarse resolution analysis from another system (partial cycling). Second, we will investigate an alternative continuous cycling approach where the center of the cycled analysis state is replaced using an alternative analysis method (hybrid approach). Accompanying these tests, we will also investigate model physics adjustments on continuous cycling performance, and will continue analysis activities on prior computational results.

High-resolution simulation of the effects of climate-urbanization-crop interactions

Project lead: Fei Chen, RAL
Cheyenne allocation: 11.9 million core-hours

This study continues to advance scientific knowledge and predictive modeling capabilities for linked agricultural and urban dynamics on regional and decadal scales. It is directly applicable to the NCAR Grand Challenge #1 (Improved understanding and prediction of atmospheric hazards and their impacts on ecosystems, people and society) and NCAR Imperative 1 (Conduct innovative fundamental research to advance the atmospheric sciences), Imperative 3 (Develop, deliver and support advanced community models) and Imperative 5 (Develop and transfer science to meet societal needs) highlighted in the current strategic plan. It will provide unique mesoscale simulations that reflect two-way, fine-scale, climate-urbanization-agriculture interactions and provide useful guidance for urban planning and agriculture decision makers.

Collaborative Research: Regional-scale process models to facilitate observational deployments in the Equatorial Pacific Cold Tongue

Project lead: Scott Bachman, CGD
Cheyenne allocation: 10.7 million core-hours

Due to far-reaching societal impacts, developing models that enable reliable forecasts of the tropical Pacific Ocean and the Equatorial Cold Tongue (ECT) is a high priority. However, global ocean models used for this purpose have significant deficiencies resulting from poorly- constrained parameterizations and/or coarse grid resolution. Equatorial upwelling is one such process that is crucial to the heat budget of the ECT, but has traditionally been difficult to observe, occurs at scales much smaller than a typical model grid cell, and is highly sensitive to model resolution and parameterization schemes.

This proposal is to conduct process-oriented numerical experiments to study how small-scale (< 10 km) processes contribute to upwelling and the heat budget of the ECT. By identifying aspects of the model solutions that are most biased in their representation of vertical heat and tracer fluxes, the simulation results will be used to help constrain parameterization and model development efforts and improve global model solutions and forecasts in line with NCAR’s strategic plan. The simulations will also help to inform NOAA’s redesigned Tropical Pacific Observing System (TPOS), a starting point for ongoing TPOS collaboration between NCAR scientists and university partners.