Process-oriented Diagnostics in CMIP6 Models and Beyond

Description:

There is growing community interest in moving beyond typical model evaluation metrics to process-oriented diagnostics. These diagnostics better constrain poorly-represented physics components in climate models, provide actionable feedback to model developers, and are expected to play a key role in advancing the next-generation climate and earth system models.

The scope of this collection encompasses studies developing new process-oriented diagnostics—and the underlying understanding of climate system processes—as well as those applying existing diagnostics to climate models. Of particular interest are applications to models participating in the Phase 6 of the Coupled Model Intercomparison Project (CMIP6) models but the scope is open to diagnostics of models beyond CMIP6, including higher-resolution models.

The special collection solicits studies from all realms of the climate system, and therefore spans several American Meteorological Society (AMS) journals. The special collection is organized by members of the NOAA Model Diagnostics Force (MDTF). The collection contains contributions from current task force members as well as community-wide contributions.

Organizers:
J David Neelin, University of California, Los Angeles
John Krasting, Geophysical Fluid Dynamics Laboratory
Fiaz Ahmed, University of California, Los Angeles
Allison Wing, Florida State University
Eric Maloney, Colorado State University

Process-oriented Diagnostics in CMIP6 Models and Beyond

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Todd Emmenegger
,
Fiaz Ahmed
,
Yi-Hung Kuo
,
Shaocheng Xie
,
Chengzhu Zhang
,
Cheng Tao
, and
J. David Neelin

Abstract

Conditional instability and the buoyancy of plumes drive moist convection but have a variety of representations in model convective schemes. Vertical thermodynamic structure information from Atmospheric Radiation Measurement (ARM) sites and reanalysis (ERA5), satellite-derived precipitation (TRMM3b42), and diagnostics relevant for plume buoyancy are used to assess climate models. Previous work has shown that CMIP6 models represent moist convective processes more accurately than their CMIP5 counterparts. However, certain biases in convective onset remain pervasive among generations of CMIP modeling efforts. We diagnose these biases in a cohort of nine CMIP6 models with subdaily output, assessing conditional instability in profiles of equivalent potential temperature, θe , and saturation equivalent potential temperature, θes , in comparison to a plume model with different mixing assumptions. Most models capture qualitative aspects of the θes vertical structure, including a substantial decrease with height in the lower free troposphere associated with the entrainment of subsaturated air. We define a “pseudo-entrainment” diagnostic that combines subsaturation and a θes measure of conditional instability similar to what entrainment would produce under the small-buoyancy approximation. This captures the trade-off between larger θes lapse rates (entrainment of dry air) and small subsaturation (permits positive buoyancy despite high entrainment). This pseudo-entrainment diagnostic is also a reasonable indicator of the critical value of integrated buoyancy for precipitation onset. Models with poor θe /θes structure (those using variants of the Tiedtke scheme) or low entrainment runs of CAM5, and models with low subsaturation, such as NASA-GISS, lie outside the observational range in this diagnostic.

Open access
Wenhao Dong
,
John P. Krasting
, and
Huan Guo

Abstract

The diurnal cycle of precipitation and precipitation variances at different time scales are analyzed in this study based on multiple high-resolution 3-h precipitation datasets. The results are used to evaluate nine CMIP6 models and a series of GFDL-AM4.0 model simulations, with the goal of examining the impact of SST diurnal cycle, varying horizontal resolutions, and different microphysics schemes on these two precipitation features. It is found that although diurnal amplitudes are reasonably simulated, models generally generate too early diurnal peaks over land, with a diurnal phase peaking around noon instead of the observed late afternoon (or early evening) peak. As for precipitation variances, irregular subdaily fluctuations dominate the total variance, followed by variance of daily mean precipitation and variance associated with the mean diurnal cycle. While the spatial and zonal distributions of precipitation variances are generally captured by the models, significant biases are present in tropical regions, where large mean precipitation biases are observed. The comparisons based on AM4.0 model simulations demonstrate that the inclusion of ocean coupling, adoption of a new microphysics scheme, and increasing of horizontal resolution have limited impacts on these two simulated features, emphasizing the need for future investigation into these model deficiencies at the process level. Conducting routine examinations of these metrics would be a crucial first step toward better simulation of precipitation intermittence in future model development. Last, distinct differences in these two features are found among observational datasets, highlighting the urgent need for a detailed evaluation of precipitation observations, especially at subdaily time scales, as model evaluation heavily relies on high-quality observations.

Significance Statement

High-frequency precipitation data, such as 3-hourly or finer resolution, provide detailed and precise information about the intensity, timing, and location of individual precipitation events. This information is essential for evaluating physically based numerical weather and climate models, which are important tools for understanding and predicting precipitation changes. We compared several global high-resolution observation datasets with nine CMIP6 GCMs and a series of GFDL-AM4.0 model simulations to evaluate the precipitation diurnal cycle and variance, with the goal of examining the impact of SST diurnal cycle, varying horizontal resolutions, and different microphysics schemes on these metrics. Despite the impact of these factors on the simulated precipitation diurnal cycle and variance being evident, our results also show that they are not consistently aligned with observed features. This highlights the need for further investigation into model deficiencies at the process level. Therefore, conducting routine examinations of these metrics could be a crucial first step toward improving the simulation of precipitation intermittency in future model development. Additionally, given the large uncertainties, there is an urgent need for a detailed evaluation of observational precipitation products, particularly at subdaily time scales.

Open access
Caitlin A. Dirkes
,
Allison A. Wing
,
Suzana J. Camargo
, and
Daehyun Kim

Abstract

Global models are frequently used for tropical cyclone (TC) prediction and climate projections but have biases in their representation of TCs that are not fully understood. The objective of this work is to assess how well and how robustly physical processes that are important for TC development are represented in modern reanalysis products and to consider whether reanalyses can serve as an observationally constrained reference against which model representation of these physical processes can be evaluated. Differences in the representation of large-scale environmental variables relevant to TC development do not readily explain the spread in TC climatologies across climate models, as found in prior work, or across reanalysis datasets, as shown here. This motivates the use of process-oriented diagnostics that focus on how convection, moisture, clouds, and related processes are coupled and can be used to identify areas to target for model improvement. Using the column-integrated moist static energy (MSE) variance budget, we analyze radiative and surface flux feedbacks across five different reanalyses. We construct an intensity-bin composite of the MSE variance budget to compare storms of similar intensity. Our results point to some fundamental differences across reanalyses in how they represent MSE variance and surface flux and radiative feedbacks in TCs, which could contribute to differences across reanalyses in how they represent TCs, but other factors also likely contribute. Any future work that evaluates these diagnostics in GCMs against reanalyses should do so cautiously, and efforts should be undertaken to provide a true observational estimate of these processes.

Free access
Huaxia Liao
,
Zhichao Cai
,
Jingsong Guo
, and
Zhenya Song

Abstract

El Niño–Southern Oscillation (ENSO) is the most influential interannual climate variability on Earth. The tendency of the mature phase of ENSO, characterized by the strongest sea surface temperature (SST) anomalies, to appear during the boreal winter is known as seasonal phase locking. Climate models are challenged by biases in simulating ENSO seasonal phase locking. Here, we evaluated the ENSO phase-locking simulation performance in 50 models of phase 6 of the Coupled Model Intercomparison Project (CMIP6) and found that the models with the intertropical convergence zone (ITCZ) poleward bias tended to simulate more ENSO events that peaked out of the boreal winter season. The contributions of the ITCZ poleward bias to the ENSO phase-locking bias were also evaluated, yielding a correlation coefficient of 0.55, which can explain approximately 30% of the ENSO seasonal phase-locking bias. The mechanism that influences the simulation of ENSO seasonal phase locking was also assessed. The ITCZ poleward bias induces a dry bias over the equatorial Pacific, especially during the boreal summer. During ENSO events, the meridional movement of the ITCZ is prevented, and the equatorial precipitation and convection anomalies that respond to ENSO events are also restrained. The restrained convection anomaly weakens the ENSO-related zonal wind anomaly, triggering a weaker eastern tropical Pacific thermocline anomaly during the following autumn. The weakened thermocline anomaly cannot sustain further development of ENSO-related SST anomalies. Therefore, ENSO events in models containing the ITCZ poleward bias are restrained during the boreal summer and autumn and, thus, tend to peak out of the winter season.

Significance Statement

We aimed to better understand the mechanism that induces bias when simulating ENSO seasonal phase locking, that is, what disturbs the simulated ENSO events peaking during the boreal winter. As previous studies have primarily focused on the South Pacific convergence zone (SPCZ) bias and other biases, this study is the first to propose the effects of the poleward ITCZ latitude bias and clarify the corresponding mechanism. We show that latitudinal bias can explain approximately 30% of the ENSO seasonal phase-locking bias. This is important because the biases in simulating ENSO seasonal phase locking have long hampered the prediction of ENSO. Our study highlights the importance of the latitude of the ITCZ and provides a basis for the future development of climate models.

Open access
Jiacheng Ye
and
Zhuo Wang

Abstract

Many coupled climate models suffer from a late retreat bias in North American monsoon (NAM) simulations, which is manifested by overestimated precipitation in October. The overestimated precipitation has long been attributed to the negative sea surface temperature (SST) biases in the tropical Atlantic and insufficient model resolution to resolve mesoscale features. However, we found little correlation between CMIP6 model resolutions and the simulated NAM retreat-season precipitation in October. Instead, we showed that tropical eastern North Pacific SST biases and the associated large-scale circulation biases play a dominant role in inducing the retreat-season biases, with SST biases in other ocean basins playing a secondary role. As revealed by simulations using a hierarchy of models, the positive SST biases in the tropical eastern North Pacific enhance local convection and lead to positive diabatic heating biases throughout the troposphere; the diabatic heating biases generate a Matsuno–Gill type of response that strengthens the subtropical high over the North Atlantic and weakens the subtropical high over the North Pacific, enhancing the low-level northward moisture transport from the tropics to the NAM region. The conclusion is robust across phase 6 of CMIP (CMIP6) models. The precipitation seasonality in the NAM region is used to constrain future projection. The “good” CMIP6 models project that the timing of the NAM peak season remains the same, but the peak-season precipitation is reduced and monsoon retreat is delayed, while the “poor” CMIP6 models project a delayed monsoon peak season with slightly enhanced peak-season precipitation. Both model groups project a drier dry season in the NAM region.

Free access
Jiaxin Ye
,
Chaoxia Yuan
,
Mengzhou Yang
,
Xinyu Lu
,
Jing-Jia Luo
, and
Toshio Yamagata

Abstract

Significant anomalies in frequency of summer extreme hot days (SEHDs) are broadly observed in the Asian monsoon region (AMR) in the post-ENSO summers. The delayed ENSO impacts are mainly conveyed by provoking the Indo-western Pacific Ocean capacitor (IPOC) effect that maintains the anomalous anticyclone in the western North Pacific. The related diabatic heating anomaly can trigger the westward-propagating Rossby wave to the Indian subcontinent, which increases the geopotential heights, reduces the cloud cover, and thus increases the seasonal surface temperature and SEHD frequency in the southern AMR. Besides, the reduced atmospheric moisture in the western North Pacific hinders the northward propagation of intraseasonal oscillation (ISO) and modulates the occurrence frequency of individual ISO phases, contributing to the significantly increased/decreased SEHDs in eastern China/Hokkaido, Japan, in the post–El Niño summers. The 25-model-ensemble mean of CMIP6 historical runs can reproduce well the observed SEHD anomalies in the southern AMR in the post-ENSO summers mainly due to the realistic simulation of ENSO impacts on the seasonal surface temperature, although a large intermodel spread exists due to different strengths of IPOC effect in each model owing to model biases in the mean state of the eastern tropical Pacific, the ENSO variance, and teleconnection to the Indian Ocean. Furthermore, future projections under the SSP5-8.5 scenario show that the delayed ENSO impacts on the southern AMR remain stable under global warming via a similar mechanism as in the observations and historical runs.

Free access
H. Annamalai
,
Richard B. Neale
, and
Jan Hafner

Abstract

Climate model fidelity in representing ENSO-induced teleconnection is assessed with process-oriented diagnostics that examine a chain of processes, from equatorial Pacific precipitation to the midlatitude circulation pattern over the Pacific–North American regions. Such processes are rarely addressed during model development. Using an upper-tropospheric divergent level, local vorticity gradient of the ambient zonal flow ( 2 U ¯ / y 2 ) and a restoring force for Rossby waves ( β * ) are estimated, the equivalent barotropic vorticity equation is solved, and an anomalous Rossby wave source (RWS′) quantified. The analysis is applied to AMIP5 and AMIP6 simulations. For a realistic circulation response representation, the hypothesis that models accurately represent the strength and location of RWS′, and spatial variations in β * is tested. Compared to AMIP5, in AMIP6 there are clear improvements in representing RWS′ and β * . To validate the hypothesis, the analysis identifies two metrics: spatially coherent RWS′ in the subtropical North Pacific, and longitudes of negative β * over the western-central North Pacific. By projecting these metrics in two and three-dimensional views, improvements or degradations in model versions are apparent. If a model’s fidelity in representing 2 U ¯ / y 2 and RWS′ are compromised, then radiated Rossby waves are reflected more equatorward, resulting in zonally elongated circulation anomalies over the central North Pacific. Thus, during climate model development, applying this analysis frequently will keep a regular check on the fidelity of the modeled response to anomalous El Niño convection in conjunction with changing model ambient flow dependencies. This analysis is intended to form a process-oriented diagnostics package, a community contribution to the NOAA Model Diagnostics Task Force.

Significance Statement

The seasonal changes in tropical Pacific sea surface temperatures associated with El Niño events can have a significant impact in the atmospheric circulation through the North Pacific and on the annual climate variations over North America. Our skill in predicting these impacts depends critically on the ability of climate models to represent these global-scale connections accurately. We show a number of metrics that describe critical processes along this North Pacific pathway that can be used to examine the progress in climate model skill. In the future, these models could benefit significantly from using these metrics with the end goal of much improved predictions of El Niño–related variability.

Free access
Cong Tang
,
Jian Shi
,
Yu Zhang
,
Shengpeng Wang
,
Chun Li
,
Riyu Lu
,
Tengfei Yu
,
Ruiqi Wang
, and
Ziyan Chen

Abstract

In the last decade, three persistent warm blob events (2013/14, 2015, and 2019/20) in the northeast Pacific (NEP) have been hotly debated given their substantial effects on climate, ecosystems, and the socioeconomy. This study investigates the changes of such long-lived NEP warm blobs in terms of their intensity, duration, structure, and occurrence frequency under Shared Socioeconomic Pathway (SSP) 119 and 126 low-warming scenarios of phase 6 of the Coupled Model Intercomparison Project. Results show that the peak timing of the warm blobs shifts from the cold season to boreal summer. For the summer-peak warm blobs, their maximum intensity increases by 6.7% (10.0%) under the SSP119 (SSP126) scenario, but their duration reduces by 31.0% (20.4%) under the SSP119 (SSP126) scenario. In terms of their vertical structure, the most pronounced temperature signal is located at the surface, and their vertical penetration is mostly confined to the mixed layer, which becomes shallower in warming climates. Based on a mixed layer heat budget analysis, we reveal that a shoaling mixed layer depth plays a dominant role in driving the stronger intensity of the warm blobs under low-warming scenarios, while the stronger magnitude of ocean heat loss after their peaks explains the faster decay and thus shorter duration. Regarding occurrence frequency, the total number of the warm blobs does not change robustly in the low-warming climates. Following the summer peak of the warm blobs, extreme El Niño events may occur more frequently under the low-warming scenarios, possibly through stronger air–sea coupling induced by tropical Pacific southwesterly anomalies.

Free access
Chathurika Wickramage
,
Armin Köhl
,
Johann Jungclaus
, and
Detlef Stammer

Abstract

The dependence of future regional sea level changes on ocean model resolution is investigated based on Max Planck Institute Earth System Model (MPI-ESM) simulations with varying spatial resolution, ranging from low resolution (LR), high resolution (HR), to eddy-rich (ER) resolution. Each run was driven by the shared socioeconomic pathway (SSP) 5-8.5 (fossil-fueled development) forcing. For each run the dynamic sea level (DSL) changes are evaluated by comparing the time mean of the SSP5-8.5 climate change scenario for the years 2080–99 to the time mean of the historical simulation for the years 1995–2014. Respective results indicate that each run reproduces previously identified large-scale DSL change patterns. However, substantial sensitivity of the projected DSL changes can be found on a regional to local scale with respect to model resolution. In comparison to models with parameterized eddies (HR and LR), enhanced sea level changes are found in the North Atlantic subtropical region, the Kuroshio region, and the Arctic Ocean in the model version capturing mesoscale processes (ER). Smaller yet still significant sea level changes can be found in the Southern Ocean and the North Atlantic subpolar region. These sea level changes are associated with changes in the regional circulation. Our study suggests that low-resolution sea level projections should be interpreted with care in regions where major differences are revealed here, particularly in eddy active regions such as the Kuroshio, Antarctic Circumpolar Current, Gulf Stream, and East Australian Current.

Significance Statement

Sea level change is expected to be more realistic when mesoscale processes are explicitly resolved in climate models. However, century-long simulations with eddy-resolving models are computationally expensive. Therefore, current sea level projections are based on climate models in which ocean eddies are parameterized. The representation of sea level by these models considerably differs from actual observations, particularly in the eddy-rich regions such as the Southern Ocean and the western boundary currents, implying erroneous ocean circulation that affects the sea level projections. Taking this into account, we review the sea level change pattern in a climate model with featuring an eddy-rich ocean model and compare the results to state-of-the-art coarser-resolution versions of the same model. We found substantial DSL differences in the global ocean between the different resolutions. Relatively small-scale ocean eddies can hence have profound large-scale effects on the projected sea level which may affect our understanding of future sea level change as well as the planning of future investments to adapt to climate change around the world.

Open access
Youtong Zheng
and
Yi Ming

Abstract

Interpreting behaviors of low-level clouds (LLCs) in a climate model is often not straightforward. This is particularly so over polar oceans where frozen and unfrozen surfaces coexist, with horizontal winds streaming across them, shaping LLCs. To add clarity to this interpretation issue, we conduct budget analyses of LLCs using a global atmosphere model with a fully prognostic cloud scheme. After substantiating the model’s skill in reproducing observed LLCs, we use the modeled budgets of cloud fraction and water content to elucidate physics governing changes of LLCs across sea ice edges. Contrasting LLC regimes between open water and sea ice are found. LLCs over sea ice are primarily maintained by large-scale condensation: intermittent intrusions of maritime humid air and surface radiative cooling jointly sustain high relative humidity near the surface, forming extensive but tenuous stratus. This contrasts with the LLCs over open water where the convection and boundary layer condensation sustain the LLCs on top of deeper boundary layers. Such contrasting LLC regimes are influenced by the direction of horizontal advection. During on-ice flow, large-scale condensation dominates the regions, both open water and sea ice regions, forming clouds throughout the lowest several kilometers of the troposphere. During off-ice flow, as cold air masses travel over the open water, the cloud layer lifts and becomes denser, driven by increased surface fluxes that generate LLCs through boundary layer condensation and convective detrainment. These results hold in all seasons except summer when the atmosphere–surface decoupling substantially reduces the footprints of surface type changes.

Open access