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Abstract Overly smooth topography in general circulation models (GCMs) underestimates the blocking effect of the steep mountain ranges flanking the eastern Pacific. We explore the impact of this bias on common biases in Pacific climate simulation [i.e., the unrealistic cross-equatorial symmetry of near-surface winds, sea surface temperatures (SSTs), and precipitation] through sensitivity experiments with modified Central and/or South American topography in an atmosphere–ocean coupled GCM. Quantifying orographic blocking potential via the Froude number, we determine that an envelope topographic interpolation scheme best captures observed blocking patterns. Implementing envelope topography only in Central America reduced model biases as greater blocking of the trade winds warmed SST and enhanced convergence in the northeastern Pacific. Doing so additionally over the Andes improved the simulation of South Pacific circulation and the South Pacific convergence zone as stronger deflection of the westerlies intensified the South Pacific anticyclone. This mitigated convection biases in the southeast Pacific by increasing subsidence and cooling SST. However, remote impacts of the Andes exacerbated the dry bias in the northeast tropical Pacific, resulting in negligible improvement in the East Pacific double-ITCZ. We find that, due to the significant role of large-scale convergence in driving precipitation patterns, other model biases, such as cloud-radiative biases, may modulate the impact of altering topography. Our results highlight the importance of considering alternate methods for calculating model topographic boundary conditions, though the optimal interpolation scheme will vary with model resolution and the impact of topography on GCM biases can be sensitive to choices made in formulating parameterizations. Significance StatementIn this study, we explore how the mountain ranges spanning Central and South America shape the climate of the Pacific by blocking large-scale midlatitude and tropical winds. We show that the height of these mountains is typically too low in climate models and that elevating them can improve patterns of rainfall, surface ocean temperatures, and near-surface winds in the Pacific. This is important because model biases in the Pacific climate limit their utility for understanding current and future climate variability. Improving the representation of blocking by mountains can thus be a simple method for reducing uncertainties in future climate projections.
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Dynamical Constraint on Precipitation Biases Over the Indo‐Pacific Region During Boreal Summer in AMIP6 Models
Abstract Climate models suffer from longstanding precipitation biases, much of which has been attributed to their atmospheric component owing to unrealistic parameterizations. Here we investigate precipitation biases in 37 Atmospheric Model Intercomparison Project Phase 6 (AMIP6) models, focusing on the Indo‐Pacific region during boreal summer. These models remain plagued by considerable precipitation biases, especially over regions of strong precipitation. In particular, 22 models overestimate the Asian‐Pacific monsoon precipitation, while 28 models underestimate the southern Indian Ocean Intertropical Convergence Zone precipitation. The inter‐model spread in summer precipitation is decomposed into Empirical Orthogonal Functions (EOFs). The leading EOF mode features an anomalous anticyclone circulation spanning the Indo‐northwest Pacific oceans, which we show is energized by barotropic conversion from the confluence of the background monsoonal westerlies and trade‐wind easterlies. Our results suggest precipitation biases in atmospheric models, though caused by unrealistic parameterizations, are organized by dynamical feedbacks of the mean flow.
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- Award ID(s):
- 2311170
- PAR ID:
- 10569115
- Publisher / Repository:
- AGU
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 51
- Issue:
- 6
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript
- Journal Article:
- https://doi.org/10.1029/2023GL107181
