Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Climate Variability & Predictability (CVP) logo

Tropical Pacific moist dynamical processes, sensitivity and biases

Moist dynamical processes, originating in the atmosphere but involving ocean-atmosphere feedbacks, are among the leading effects requiring better constraints to address tropical Pacific biases and many applications to Pacific variability. We propose to bring together two themes developed under prior work: fast-process diagnostics from observations and parameter perturbation runs aimed at assessing sensitivity of moist processes to parameterized physics. Specifically, we will have available from prior work a set of runs with the Community Earth System Model (CESM1; atmospheric component Community Atmosphere Model 5) that perturb the convective physics in both uncoupled and coupled modes. These include nonstandard, high time-resolution output to aid assessment of fast-process diagnostics and sufficient length to establish statistical significance in quantities that might elude short-term forecast experiments. Data from a related set of perturbed physics runs from the NOAA Geophysical Fluid Dynamics Laboratory High Resolution Atmospheric Model (HIRAM) model will also be available via existing collaborations. In both models, initial results suggest high parameter sensitivity in the tropical Pacific, for instance, precipitation differences exceeding ± 3 mm/day across large parts of the basin for convection-related parameters varied across their feasible range. The proposed work addresses some of the challenges in making use of such information: (i) Sensitivity does not necessarily equate to improvement. We will quantify contributions to this across multiple variables and parameters, including assessing trade-offs where some metrics improve while others degrade for a given parameter change. (ii) The impacts on the climatology involve large-scale dynamical ocean-atmosphere feedbacks even in experiments where the parameterization change is known. We will aim to disentangle such effects using hypothesis-driven investigation informed by simpler models. Examples of this include assessment of convective instability as a function of parameter and model state using a column version of the CAM, and convective margins diagnostics. (iii) Reduction of biases should not simply be a tuning exercise based on improvement in the climatology. Rather, we will seek cases where current fast-process diagnostics can provide independent constraints on the parameter range or parameterization form. For example, diagnostics for convective onset as a function of temperature and water vapor will be used to constrain the entrainment range. Processes exhibiting high sensitivity in the Pacific will be used to target the development of further diagnostics, and parallels with common error modes in the Coupled Model Intercomparison Project phase 5 will be examined.

The proposed work, for the competition Improved Understanding of Tropical Pacific Processes, Biases, and Climatology (Earth System Science Competition 3, Climate Variability and Predictability), addresses the following aspects of the competition goals: intercomparison of model parameterizations, including convection and clouds, and reduced and conceptual modeling coordinated with analysis of full coupled model experiments and development of metrics for atmospheric relationships that constrain moist dynamical processes key to understanding and reducing biases. It addresses elements of the NOAA long-term climate goal as described in NOAA’s Next-Generation Strategic Plan in the core capability of “Understanding and modeling”, supporting the “ Predictions and projections” capability. Furthermore, the information from the observational analysis will help to design and refine the diagnostics that can be obtained from observing systems. The proposed work is relevant to societal challenges identified in the NGSP of climate impacts in water resources, changes in extremes of weather and climate, and provides current climate baselines for model projections for mitigating climate change impacts.

Scroll to Top