Three consecutive dry winters (2015–2017) in southwestern South Africa (SSA) resulted in the Cape Town “Day Zero” drought in early 2018. The contribution of anthropogenic global warming to this ...prolonged rainfall deficit has previously been evaluated through observations and climate models. However, model adequacy and insufficient horizontal resolution make it difficult to precisely quantify the changing likelihood of extreme droughts, given the small regional scale. Here, we use a high-resolution large ensemble to estimate the contribution of anthropogenic climate change to the probability of occurrence of multiyear SSA rainfall deficits in past and future decades. We find that anthropogenic climate change increased the likelihood of the 2015–2017 rainfall deficit by a factor of five to six. The probability of such an event will increase from 0.7 to 25% by the year 2100 under an intermediate-emission scenario (Shared Socioeconomic Pathway 2-4.5 SSP2-4.5) and to 80% under a high-emission scenario (SSP5-8.5). These results highlight the strong sensitivity of the drought risk in SSA to future anthropogenic emissions.
This study assesses the ability of a newly developed high-resolution coupled model from the Geophysical Fluid Dynamics Laboratory to simulate the cold-season hydroclimate in the present climate and ...examines its response to climate change forcing. Output is assessed from a 280-yr control simulation that is based on 1990 atmospheric composition and an idealized 140-yr future simulation in which atmospheric carbon dioxide increases at 1% yr−1until doubling in year 70 and then remains constant. When compared with a low-resolution model, the high-resolution model is found to better represent the geographic distribution of snow variables in the present climate. In response to idealized radiative forcing changes, both models produce similar global-scale responses in which global-mean temperature and total precipitation increase while snowfall decreases. Zonally, snowfall tends to decrease in the low to midlatitudes and increase in the mid- to high latitudes. At the regional scale, the high- and low-resolution models sometimes diverge in the sign of projected snowfall changes; the high-resolution model exhibits future increases in a few select high-altitude regions, notably the northwestern Himalaya region and small regions in the Andes and southwestern Yukon, Canada. Despite such local signals, there is an almost universal reduction in snowfall as a percent of total precipitation in both models. By using a simple multivariate model, temperature is shown to drive these trends by decreasing snowfall almost everywhere while precipitation increases snowfall in the high altitudes and mid- to high latitudes. Mountainous regions of snowfall increases in the high-resolution model exhibit a unique dominance of the positive contribution from precipitation over temperature.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A stationary low pressure system and elevated levels of precipitable water provided a nearly continuous source of precipitation over Louisiana, United States (US), starting around 10 August 2016. ...Precipitation was heaviest in the region broadly encompassing the city of Baton Rouge, with a 3-day maximum found at a station in Livingston, LA (east of Baton Rouge), from 12 to 14 August 2016 (648.3 mm, 25.5 inches). The intense precipitation was followed by inland flash flooding and river flooding and in subsequent days produced additional backwater flooding. On 16 August, Louisiana officials reported that 30 000 people had been rescued, nearly 10 600 people had slept in shelters on the night of 14 August and at least 60 600 homes had been impacted to varying degrees. As of 17 August, the floods were reported to have killed at least 13 people. As the disaster was unfolding, the Red Cross called the flooding the worst natural disaster in the US since Super Storm Sandy made landfall in New Jersey on 24 October 2012. Before the floodwaters had receded, the media began questioning whether this extreme event was caused by anthropogenic climate change. To provide the necessary analysis to understand the potential role of anthropogenic climate change, a rapid attribution analysis was launched in real time using the best readily available observational data and high-resolution global climate model simulations. The objective of this study is to show the possibility of performing rapid attribution studies when both observational and model data and analysis methods are readily available upon the start. It is the authors' aspiration that the results be used to guide further studies of the devastating precipitation and flooding event. Here, we present a first estimate of how anthropogenic climate change has affected the likelihood of a comparable extreme precipitation event in the central US Gulf Coast. While the flooding event of interest triggering this study occurred in south Louisiana, for the purposes of our analysis, we have defined an extreme precipitation event by taking the spatial maximum of annual 3-day inland maximum precipitation over the region of 29–31° N, 85–95° W, which we refer to as the central US Gulf Coast. Using observational data, we find that the observed local return time of the 12–14 August precipitation event in 2016 is about 550 years (95 % confidence interval (CI): 450–1450). The probability for an event like this to happen anywhere in the region is presently 1 in 30 years (CI 11–110). We estimate that these probabilities and the intensity of extreme precipitation events of this return time have increased since 1900. A central US Gulf Coast extreme precipitation event has effectively become more likely in 2016 than it was in 1900. The global climate models tell a similar story; in the most accurate analyses, the regional probability of 3-day extreme precipitation increases by more than a factor of 1.4 due to anthropogenic climate change. The magnitude of the shift in probabilities is greater in the 25 km (higher-resolution) climate model than in the 50 km model. The evidence for a relation to El Niño half a year earlier is equivocal, with some analyses showing a positive connection and others none.
Responses of tropical cyclones (TCs) to CO
2
doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ ...25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO
2
TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO
2
-induced warming patterns and CO
2
doubling. Isolated CO
2
doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO
2
concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.
The recent multi-year 2015–2019 drought after a multi-decadal drying trend over Central America raises the question of whether anthropogenic climate change (ACC) played a role in exacerbating these ...events. While the occurrence of the 2015–2019 drought in Central America has been asserted to be associated with ACC, we lack an assessment of natural vs anthropogenic contributions. Here, we use five different large ensembles—including high-resolution ensembles (i.e., 0.5
∘
horizontally)—to estimate the contribution of ACC to the probability of occurrence of the 2015–2019 event and the recent multi-decadal trend. The comparison of ensembles forced with natural and natural plus anthropogenic forcing suggests that the recent 40-year trend is likely associated with internal climate variability. However, the 2015–2019 rainfall deficit has been made more likely by ACC. The synthesis of the results from model ensembles supports the notion of a significant increase, by a factor of four, over the last century for the 2015–2019 meteorological drought to occur because of ACC. All the model results further suggest that, under intermediate and high emission scenarios, the likelihood of similar drought events will continue to increase substantially over the next decades.
Precipitation extremes have a widespread impact on societies and ecosystems; it is therefore important to understand current and future patterns of extreme precipitation. Here, a set of new global ...coupled climate models with varying atmospheric resolution has been used to investigate the ability of these models to reproduce observed patterns of precipitation extremes and to investigate changes in these extremes in response to increased atmospheric CO₂ concentrations. The atmospheric resolution was increased from 2° × 2° grid cells (typical resolution in the CMIP5 archive) to 0.25° × 0.25° (tropical cyclone permitting). Analysis has been confined to the contiguous United States (CONUS). It is shown that, for these models, integrating at higher atmospheric resolution improves all aspects of simulated extreme precipitation: spatial patterns, intensities, and seasonal timing. In response to 2 × CO₂ concentrations, all models show a mean intensification of precipitation rates during extreme events of approximately 3%–4%K−1. However, projected regional patterns of changes in extremes are dependent on model resolution. For example, the highest-resolution models show increased precipitation rates during extreme events in the hurricane season in the U.S. Southeast; this increase is not found in the low-resolution model. These results emphasize that, for the study of extreme precipitation there is a minimum model resolution that is needed to capture the weather phenomena generating the extremes. Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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 year) 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 the subtropical Indian Ocean dipole. Comparison of the coupled run with a 1000-yr 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 sea surface temperature anomalies weakens this influence.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The Mediterranean region, located in the transition zone between the dry subtropical and wet European mid-latitude climate, is very sensitive to changes in the global mean climate state. Projecting ...future changes of the Mediterranean hydroclimate under global warming therefore requires dynamic climate models to reproduce the main mechanisms controlling regional hydroclimate with sufficiently high resolution to realistically simulate climate extremes. To assess future winter precipitation changes in the Mediterranean region we use the Geophysical Fluid Dynamics Laboratory high-resolution general circulation model for control simulations with pre-industrial greenhouse gas and aerosol concentrations which are compared to future scenario simulations. Here we show that the coupled model is able to reliably simulate the large-scale winter circulation, including the North Atlantic Oscillation and Eastern Atlantic patterns of variability, and its associated impacts on the mean Mediterranean hydroclimate. The model also realistically reproduces the regional features of daily heavy rainfall, which are absent in lower-resolution simulations. A five-member future projection ensemble, which assumes comparatively high greenhouse gas emissions (RCP8.5) until 2100, indicates a strong winter decline in Mediterranean precipitation for the coming decades. Consistent with dynamical and thermodynamical consequences of a warming atmosphere, derived changes feature a distinct bipolar behavior, i.e. wetting in the north—and drying in the south. Changes are most pronounced over the northwest African coast, where the projected winter precipitation decline reaches 40% of present values. Despite a decrease in mean precipitation, heavy rainfall indices show drastic increases across most of the Mediterranean, except the North African coast, which is under the strong influence of the cold Canary Current.
Compared to the Arctic, seasonal predictions of Antarctic sea ice have received relatively little attention. In this work, we utilize three coupled dynamical prediction systems developed at the ...Geophysical Fluid Dynamics Laboratory to assess the seasonal prediction skill and predictability of Antarctic sea ice. These systems, based on the FLOR, SPEAR_LO, and SPEAR_MED dynamical models, differ in their coupled model components, initialization techniques, atmospheric resolution, and model biases. Using suites of retrospective initialized seasonal predictions spanning 1992–2018, we investigate the role of these factors in determining Antarctic sea ice prediction skill and examine the mechanisms of regional sea ice predictability. We find that each system is capable of skillfully predicting regional Antarctic sea ice extent (SIE) with skill that exceeds a persistence forecast. Winter SIE is skillfully predicted 11 months in advance in the Weddell, Amundsen/Bellingshausen, Indian, and west Pacific sectors, whereas winter skill is notably lower in the Ross sector. Zonally advected upper-ocean heat content anomalies are found to provide the crucial source of prediction skill for the winter sea ice edge position. The recently developed SPEAR systems are more skillful than FLOR for summer sea ice predictions, owing to improvements in sea ice concentration and sea ice thickness initialization. Summer Weddell SIE is skillfully predicted up to 9 months in advance in SPEAR_MED, due to the persistence and drift of initialized sea ice thickness anomalies from the previous winter. Overall, these results suggest a promising potential for providing operational Antarctic sea ice predictions on seasonal time scales.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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 1.0° (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1° to 0.25°. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM4 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 ESM4 models.
Plain Language Summary
In this paper we describe the development and simulation characteristics of a new climate model that will be used for seasonal to multidecadal climate prediction and projection. The model combines a set of newly developed components that simulate the ocean, atmosphere, land, and sea ice. We document this model by assessing its performance in simulating the current climate and by showing the model's response to changing greenhouse gases and aerosols over the 20th and 21st centuries. We also show results from a set of sensitivity experiments that were an important part of the model development process. These sensitivity tests explore connections between the surface energy balance over Antarctica and the circulation of the deep ocean.
Key Points
Development and performance of the next generation GFDL seasonal to decadal prediction model is documented
The response of this model to realistic radiative forcing changes is shown via a large ensemble of climate simulations for 1921–2100
The influence of the Antarctic surface energy balance on the world ocean was crucial in model development as shown via sensitivity tests
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