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GFDL Research Highlights

January 7th, 2020 - Impacts of Extratropical Weather Perturbations on Tropical Cyclone Activity: Idealized Sensitivity Experiments with a Regional Atmospheric Model

Recent observational studies suggested that Atlantic hurricane activity is strongly affected by weather processes outside of the tropics, but modeling studies reported divergent findings regarding the importance of such an impact. Using a regional atmospheric model with imposed boundary conditions, the authors conducted idealized experiments to explore whether and how extratropical weather perturbations affect Atlantic hurricane activity. Read More…

November 6th, 2019 - Structure and Performance of GFDL’s CM4.0 Climate Model

This paper describes the GFDL’s latest multi-purpose atmosphere-ocean coupled climate model, CM4.0. It consists of GFDL’s newest atmosphere and land models at about 100 km horizontal resolution, and ocean and sea ice models at roughly 25 km horizontal resolution. A handful of standard experiments have been conducted with CM4.0 for participation in the Coupled Model Inter-comparison Project Phase 6 (CMIP6), an archive of climate model results utilized by the Intergovernmental Panel on Climate Change (IPCC) and the climate research community more generally. Read More…

November 4th, 2019 - On the Mechanisms of the Active 2018 Tropical Cyclone Season in the North Pacific

The 2018 tropical cyclone (TC) season in the North Pacific was very active, with 39 tropical storms including 8 typhoons/hurricanes. Unlike the typical limitations in skill of seasonal predictions made before April initial forecasts, the active 2018 TC season was successfully predicted by the Geophysical Fluid Dynamic Laboratory Forecast-oriented Low Ocean Resolution (FLOR) global coupled model 3–5 months in advance (i.e., successful predictions from 1 February 2018). Read More…

October 1st, 2019 - Rising temperatures increase importance of oceanic evaporation as a source for continental precipitation

In many parts of the world, water resources for humans and ecosystems are heavily dependent on precipitation. Terrestrial precipitation is fed by moisture originating as evaporation from oceans and from recycling of water evaporated from continental sources. Understanding the vulnerability of regional precipitation to changing climatic conditions and to changing land cover conditions is of critical importance to society. Read More…

September 6th, 2019 - Hurricane Model Development at GFDL: A Collaborative Success Story from a Historical Perspective

In 1970, a new hurricane project was established at GFDL to perform basic hurricane research using numerical modeling. Within a few years, this pioneering research had led to the development of a new hurricane model. As the reputation of the model grew, GFDL was approached in 1986 by the director of the National Meteorological Center to establish a collaboration between the two Federal organizations to transition the model into an operational modeling system. After a multi-year effort by GFDL scientists to develop a system that could support rigorous requirements of operations, and multi-year testing had demonstrated its superior performance compared to existing guidance products, the model became operational in 1995. Through additional collaborations between GFDL and the U.S. Navy, the model was also made operational at Fleet Numerical Meteorology and Oceanography Center in 1996. Read More…

August 27th, 2019 - Skillful Prediction of Monthly North Atlantic Major Hurricane Activity with Two-way Nesting

Existing hurricane prediction systems fall into two categories: hurricane track and intensity predictions on a weekly timescale; and the prediction of hurricane activity on a seasonal timescale. Substantial progress has been made in improving the predictions on the two distinct timescales in the past decade. However, the prediction of hurricane activity on a subseasonal timescale (from two weeks to two months) has not shown much advancement. Credible subseasonal hurricane predictions can have significant socioeconomic impacts, but are challenging. There is much uncertainty in the sources of predictability; furthermore, the realistic simulation of hurricanes requires high horizontal resolution (at least finer than 10 km), which is expensive when using global prediction systems. Read More…

August 26th, 2019 - Predicting the evolution of the 2014-2016 California Current System marine heatwave from an ensemble of coupled global climate forecasts

The factors contributing to heatwaves have been the subject of intensive research for many decades. The urgency of this work arises from the steep toll that heatwaves impose on public health, and the prospect that climate change may increase the frequency and severity of these events. Heatwaves also occur beneath the waves, where they can severely affect living marine resources upon which our coastal economies and food supply relies. Read More…

August 16th, 2019 - Tropical Cyclone sensitivities to CO2 doubling: Roles of atmospheric resolution and background climate changes.

This research explored the sensitivity of large-scale surface climate and tropical cyclone activity to a doubling of CO2, using three coupled global climate models that span a range of horizontal atmospheric and land resolutions. The authors investigated the impact of resolution changes in the atmosphere within a family of coupled global climate models with identical ocean and sea ice components, and whose atmospheric configurations differ only in their horizontal resolution (~200km, ~50km, and ~25km). Read More…

August 1st, 2019 - A spring barrier for regional predictions of summer Arctic sea ice

A central goal of the sea ice research community is to assess the ability of climate models to accurately predict Arctic sea ice. A broad range of stakeholders have a pressing need for regional forecasts. Previous studies assessing sea ice prediction skill suggest that some regions in the Arctic have a “prediction skill barrier” in the spring season, where predictions of summer sea ice made prior to May are substantially less accurate than predictions made after May. However, this barrier has only been documented in a few climate models. This study employs a simple model that uses sea ice volume to predict summer sea ice area. Read More…

July 29th, 2019 - Seasonal prediction potential for springtime dustiness in the U.S.

Severe dust storms reduce visibility and cause breathing problems and lung diseases, affecting public health, transportation, and safety. Reliable forecasts for dust storms and overall dustiness are important for hazard preventions and resource planning. Most dust forecast models focus on short, sub-seasonal lead times, i.e., three to six days, and the skill of seasonal prediction is not clear. In this study we examine the potential of seasonal dust prediction in the U.S. using an observation-constrained regression model, with key variables predicted by a seasonal prediction model, GFDL’s Forecast-Oriented Low Ocean Resolution (FLOR). Read More…

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