We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). SPEAR (Seamless System for Prediction and EArth System Research) is built from component models recently developed at GFDL ‐ the AM4 atmosphere model, MOM6 ocean code, LM4 land model and SIS2 sea ice model. The SPEAR models are specifically designed with attributes needed for a prediction model for seasonal to decadal time scales, including the ability to run large ensembles of simulations with available computational resources. For computational speed SPEAR uses a coarse ocean resolution of approximately 1.0o (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1o to 0.25o. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM 4 models, but with design choices geared toward seasonal to multidecadal physical climate prediction and projection. We document simulation characteristics for the time‐mean climate, aspects of internal variability, and the response to both idealized and realistic radiative forcing change. We describe in greater detail one focus of the model development process that was motivated by the importance of the Southern Ocean to the global climate system. We present sensitivity tests that document the influence of the Antarctic surface heat budget on Southern Ocean ventilation and deep global ocean circulation. These findings were also useful in the development processes for the GFDL CM4 and ESM 4 models.
Zhang, Honghai, in press: Tropical Pacific intensifies June extreme rainfall over Southwestern United States/Northwestern Mexico. Climate Dynamics. DOI:10.1007/s00382-020-05291-6. May 2020. Abstract
Extreme rainfall over Southwestern United States/Northwestern Mexico (SWUNWM) has been mostly investigated during wet seasons, while no or little attention has been paid to extreme rainfall during dry seasons despite its vital importance for sustaining vegetation and ecosystems. Here we examine the top 1% rainfall over SWUNWM in June, the driest month on average, and assess how it is affected by the ocean with a 50 km-resolution global climate model. Comparing millennia-long simulations with and without the ocean, we find that the ocean does not change the pattern and magnitude of atmospheric circulation associated with June extreme rainfall, but significantly enhances rainfall intensity. This intensification is attributed to a larger variability of atmospheric moisture content enhanced mainly by the sea surface temperature (SST) in the tropical Pacific. The similarities in the atmospheric circulation associated with, and the temporal characteristics of, June extreme rainfall between the two simulations point to a dominant control of extreme rainfall dynamics by atmospheric intrinsic processes and atmosphere-land coupling. These modeling results imply that the predictability of occurrence of June extreme rainfall over SWUNWM is limited by atmospheric intrinsic dynamics and atmosphere-land coupling, while reliable predictions of its intensity likely require a faithful simulation of SST variability, especially in the tropical Pacific.
The Angola Low is a summertime low-pressure system that affects the convergence of low-level moisture fluxes into southern Africa. Interannual variations of the Angola Low reduce the seasonal prediction skills for this region that arise from coupled atmosphere-ocean variability. Despite its importance, the interannual dynamics of the Angola Low, and its relationship with El Niño-Southern Oscillation (ENSO) and other coupled modes of variability, are still poorly understood, mostly because of the scarcity of atmospheric data and short-term duration of atmospheric reanalyses in the region. To bypass this issue, we use a long-term (3500 years) run from a 50-km-resolution global coupled model capable of simulating the summertime southern African large-scale circulation and teleconnections. We find that the meridional displacement and strength of the Angola Low are moderately modulated by local sea surface temperature anomalies, especially those in proximity of the southeastern African coast, and to a lesser extent by ENSO and other coupled atmosphere-ocean modes like the Subtropical Indian Ocean Dipole. Comparison of the coupled run with a 1000-year run driven by climatological sea surface temperatures reveals that the interannual excursions of the Angola Low are in both cases associated with geopotential height anomalies over the southern Atlantic and Indian Ocean related to extratropical atmospheric variability. Midlatitude atmospheric variability explains almost 60% of the variance of the Angola Low variability in the uncoupled run, but only 20% in the coupled run. Therefore, while the Angola Low appears to be intrinsically controlled by atmospheric extratropical variability, the interference of the atmospheric response forced by tropical sea surface temperature anomalies weakens this influence.
The past few years have seen a growing investment in the development of global eddy‐resolving ocean models, but the impact of incorporating such high ocean resolution on precipitation responses to CO2 forcing has yet to be investigated. This study analyzes precipitation changes from a suite of GFDL models incorporating eddy‐resolving (0.1o), eddy‐permitting (0.25o) and eddy‐parameterizing (1o) ocean models. The incorporation of eddy resolution does not challenge the large‐scale structure of precipitation changes but results in substantial regional differences, particularly over ocean. These oceanic differences are primarily driven by the pattern of SST changes with greater sensitivity in lower latitudes. The largest impact of ocean resolution on SST changes occurs in eddy rich regions (e.g., boundary currents and the Southern Ocean), where impact on precipitation changes is also found to various degrees. In the Gulf Stream region where previous studies found considerable impact of eddy resolution on the simulation of climatological precipitation, we do not find such impact from the GFDL models but we do find substantial impact on precipitation changes. The eddy‐parameterizing model projects a banded structure common to the CMIP5 models, whereas the higher‐resolution models project a poleward shift of precipitation maxima associated with an enhanced Gulf Stream warming. Over land, precipitation changes are generally not very sensitive to ocean resolution. In eastern North America adjacent to the Gulf Stream region, moderate differences are found between resolutions. We discuss the mechanisms of land differences, which arise through the simulation of both climatological SST and SST changes.
Regional hydroclimate changes on decadal time scales contain substantial natural variability. This presents a challenge for the detection of anthropogenically forced hydroclimate changes on these spatiotemporal scales, because the “signal” of anthropogenic changes is modest compared to the “noise” of natural variability. However, previous studies have shown that this “signal to noise” ratio can be greatly improved in a large model ensemble where each member contains the same “signal” but different “noise”. Here using multiple state-of-the-art large ensembles from two climate models, we quantitatively assess the detectability of anthropogenically caused decadal shifts in precipitation-minus-evaporation (PmE) mean state against natural variability, focusing on North America during 2000-2050.
Anthropogenic forcing is projected to cause detectable (“signal” larger than “noise”) shifts in PmE mean state relative to the 1950-1999 climatology over 50-70% of North America by 2050. The earliest detectable signals include, during November-April, a moistening over northeastern North America and a drying over southwestern North America and, during May- October, a drying over central North America. Different processes are responsible for these signals. Changes in submonthly transient eddy moisture fluxes account for the northeastern moistening and central drying while monthly atmospheric circulation changes explain the southwestern drying. Our model findings suggest that, despite the dominant role of natural internal variability on decadal time scales, anthropogenic shifts in PmE mean state can be detected over most of North America before the middle of the current century.
Zhang, Honghai, and Thomas L Delworth, March 2018: Robustness of anthropogenically forced decadal precipitation changes projected for the 21st century. Nature Communications, 9, 1150, DOI:10.1038/s41467-018-03611-3. Abstract
Precipitation is characterized by substantial natural variability, including on regional and decadal scales. This relatively large variability poses a grand challenge in assessing the significance of anthropogenically forced precipitation changes. Here we use multiple large ensembles of climate change experiments to evaluate whether, on regional scales, anthropogenic changes in decadal precipitation mean state are distinguishable. Here, distinguishable means the anthropogenic change is outside the range expected from natural variability. Relative to the 1950–1999 period, simulated anthropogenic shifts in precipitation mean state for the 2000–2009 period are already distinguishable over 36–41% of the globe—primarily in high latitudes, eastern subtropical oceans, and the tropics. Anthropogenic forcing in future medium-to-high emission scenarios is projected to cause distinguishable shifts over 68–75% of the globe by 2050 and 86–88% by 2100. Our findings imply anthropogenic shifts in decadal-mean precipitation will exceed the bounds of natural variability over most of the planet within several decades.
Observed austral summertime (November through April) rainfall in southeastern South America (SESA)—including northern Argentina, Uruguay, southern Brazil and Paraguay—has exhibited substantial low-frequency variations with a multi-decadal moistening trend during the 20th century and a subsequent decadal drying trend during the current century. Understanding the mechanisms responsible for these variations is essential for predicting long-term rainfall changes. Here with a suite of attribution experiments using a pair of high-resolution global climate models—GFDL CM2.5 and FLOR_FA, we investigate the causes of these regional rainfall variations. Both models reproduce the 20th-century moistening trend, albeit with a weaker magnitude than observed, in response to the radiative forcing associated with increasing greenhouse gases. The increasing greenhouse gases drive tropical expansion; consequently, the subtropical dry branch of Hadley cell moves away from SESA, leading to the rainfall increase. The amplitude discrepancy between the observed and simulated rainfall changes suggests a possible underestimation by the models of the atmospheric response to the radiative forcing, as well as an important role for low-frequency internal variability in the observed moistening trend. Over the current century, increasing greenhouse gases drive a continuous SESA rainfall increase in the models. However, the observed decadal rainfall decline is largely (~60%) reproduced in response to the observed Pacific trade wind strengthening, which is likely associated with natural Pacific decadal variability. These results suggest that the recent summertime rainfall decline in SESA is temporary and the positive trend will resume in response to both increasing greenhouse gases and a return of Pacific trade winds to normal conditions.