MAPP Webinar

Abstracts:

Gabe Vecchi — Hurricane Prediction Across Timescales — Abstract TBD

Jae-Kyung Schemm — Dynamic Hurricane Season Prediction with the NCEP CFS CGCM — Since 1998 the Climate Prediction Center of NOAA has issued Hurricane Season Outlook (HSO) for the North Atlantic and Eastern North Pacific basins. In 2009 a dynamic hurricane season prediction system was introduced to support the HSOs. The dynamic system is based on the T382 version of the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS), which is a fully coupled atmosphere-land-ocean general circulation model (CGCM). The T382 refers to spectral truncation at wave number 382 and it was the horizontal spatial resolution of the NCEP Global Forecast System that was used for daily weather forecasts in 2009.

Predictability of tropical storms in the coupled prediction system was assessed based on a series of hindcast runs with the T382 CFS CGCM for the storm season of May through November. The hindcast runs were made for the 1981-2008 period using initial conditions from mid-April for each year in order to evaluate tropical storm statistics in the CFS at the highest possible spatial resolution available in 2008. Tropical storms in the CFS runs were identified and tracked using the tropical storm detection method devised by Carmago and Zebiak (2002). Storms depicted in the CFS had very realistic tracks and robust seasonal cycles in all four basins over the Northern Hemisphere. Comparison of interannual variability in storm activities to the observed indicates that the CFS has a fair level of forecast skill and captures the shift to a more active storm era in the Atlantic basin during the post-1995 period.

An introduction to the dynamic prediction system and real time prediction assessment for the 2009-2012 seasons will be presented. Also presented will be the impact of dynamic prediction inputs on the verification of NOAA’s Hurricane Season Outlooks.

George Halliwell — Application of ocean Observing System Simulation Experiments to Improve Hurricane Forecasting — This presentation will describe the application of a new ocean OSSE system developed at NOAA/AOML and RSMAS, University of Miami to evaluate the impact of new ocean observing systems and alternate observing strategies on improving hurricane intensity forecasts. Hurricane intensity in influenced by the amount of thermal energy available in the upper ocean. For individual storms, the rate of storm-forced SST cooling is slower in regions with large heat content where thick warm layers at the surface make it difficult to entrain colder water from below. This situation maintains larger heat flux from ocean to atmosphere, thus potentially resulting in stronger storms. On longer time scales, interannual differences in the seasonal evolution of the Atlantic warm pool produce significant year-to-year differences in ocean thermal energy available to storms, potentially influencing seasonal predictions of the number and intensity of these storms. Ocean observing systems are critically important to forecasting the ocean response to individual storms, and also to forecasting the seasonal evolution of heat content in storm regions, because they constrain the ocean analysis products used to initialize forecast models. The initial application of the OSSE system has been to determine the impact of targeted rapid-response airborne observations of the upper ocean in the Gulf of Mexico on the accuracy of ocean analysis products used to initialize hurricane forecasts. Work is now commencing to extend the OSSE system to cover the full North Atlantic hurricane region. Planned OSSE studies in this larger region will focus not only on the impact of targeted rapid-response observations for improving individual storm forecasts, but also on the impact of the existing operational ocean observing system and potential enhancements to this system for monitoring and forecasting the upper ocean heat content over seasonal time scales.

Chunzai Wang — Relationships of Dust Aerosol with the AMO and Atlantic Hurricanes — Most studies of African dust and North Atlantic climate have been limited to the short time period since the satellite era (1980 onward), precluding the examination of their relationship on longer timescales.  Here we use a new dust data set with the record extending back to the 1950s to show that tropical North Atlantic (TNA) dust aerosol, Sahel rainfall, and Atlantic hurricanes vary with the Atlantic Multidecadal Oscillation (AMO).  When the AMO was in the cold phase from the late 1960s to the early 1990s, the Sahel received less rainfall and the TNA experienced high concentration of dust.  The opposite was true when the AMO was in the warm phases before the late 1960s and after the early 1990s.  This suggests a novel mechanism for the AMO – a positive feedback between North Atlantic SST, African dust, and Sahel rainfall on multidecadal timescales.  That is, a warm (cold) North Atlantic Ocean produces a wet (dry) condition in the Sahel and thus leads to low (high) concentration of dust in the TNA which in turn warms (cools) the North Atlantic Ocean.  An implication of this study is that climate models need to be able to simulate this aerosol-related feedback in order to correctly simulate climate in the North Atlantic.  Additionally, it is found that dust in the TNA varies inversely with the number of Atlantic hurricanes on multidecadal timescales due to the multidecadal variability of both direct and indirect influences of dust on vertical wind shear in the hurricane main development region.

Yolande Serra — Dynamically Downscaled HadGEM2-ES Historical Simulations And Future Projections of North American Monsoon And IAS Rainfall – What Are We Learning From Our Regional Model? — Coarse model investigations of the North American monsoon (NAM) and Intra-Americas Sea (IAS) regions performed as part of this funded project suggest that observable changes in regional precipitation patterns and synoptic wave activity are present in the CMIP5 future climate projections for the RCP 4.5 and RCP 8.5 warming scenarios.  The second part of this study is now underway to better define the impact of these changes on precipitation at the sub-meso-scales (<100 km) not resolved by the coarse CMIP5 models.  This presentation will present results of our downscaled HadGEM2-ES simulations for the 1977-2003 and 2069-2098 time periods using a 35 km domain encompassing the IAS and NAM regions.  We will assess the downscaled precipitation fields with respect to observations and coarse model fields.  We will additionally present projected changes to the seasonal cycle in precipitation and extreme precipitation events for key regions within our model domain where coarse models predict significant warm season drying and potential regional scale mechanisms responsible for the projected changes.