Recent research has shown that assimilating remotely sensed rain rates improves not only precipitation predictions,
but also the outgoing long wave radiation of the planetary energy budget. This yields improved short-term forecasts,
including hurricane tracks and threat scores. Previous long-term reanlyses of the Earth's climate had unacceptable levels
of uncertainty in precipitation and inter-annual variability. The improved diagnostics of the water cycle developed by
NASA's Global Modeling and Assimilation Office (GMAO), combined with the ever-advancing art of large-scale computation,
will enable MERRA to produce data products which directly address the variability and predictability of the
hydrological cycle.
Beyond the focus of the hydrological cycle, there are numerous other potential uses for reanalysis data.
The disseminated data products will provide much improved initial conditions for predicting weather and other
subseasonal variability that is strongly linked to tropical moisture. Studies of climate variability rely on
reanalysis data sets. Limited domain models use reanalyses to provide the boundary forcing and initial conditions
for mesoscale and regional climate simulations. The reanalysis data can be used in applications driven projects.
For example, the precipitation, evaporation and runoff can drive river flow models and help to study sensitive
ecosystems, such as estuaries. Transport models can use the reanalysis winds to evaluate aerosols.
The educational component of the MERRA project will involve college students running simplified versions of the
assimilation infrastructure to study climate change. MERRA data products will conform to ESE standards, and will be
disseminated over the Internet. The MERRA dataset will be a cornerstone of the collective data developed for addressing
the NASA Earth Science mission.
With the current keen interest of the scientific community and society on climate and predictability,
MERRA will answer the call for a 21st century reanalysis product that capitalizes on state-of-the-art
assimilation and modeling techniques and the incorporation of NASA's remotely sensed observations. MERRA
is funded by a NASA Cooperative Agreement Notice (CAN): Earth Science REASoN - Research, Education, and
Applications Solutions Network.
