Accurate modeling of atmospheric absorption and constraints on
surface properties are needed to improve atmospheric retrievals
and impact of assimilated satellite data on the weather forecasts.
AER has developed line-by-line models (LBLRTM and MonoRTM) that
have been used in many centers (including the JCSDA) as reference
in the development of fast transmittance parameterizations as well
as the Optimal Spectral Sampling (OSS) method for fast and
numerically accurate parameterization of molecular absorption in
the atmosphere. The line-by-line models are continuously validated
and updated at AER. Recent updates have been made to the water
vapor continuum in the microwave region and linemixing in the 4.3
micron CO2 band, and improvements have been made in the modeling
of the 2400 cm-1 band head. The OSS model has been selected by
EUMETSAT for the MTG-IRS L2 concept processor development and is
among the candidate FRTM’s for integration in the future MTG
operational ground segment. The focus of current and future OSS
development is on refining our generalized training capability. A
status of the models will be discussed. A description of the work
in progress on the use of our dynamically updated global atlas of
microwave surface emissivities (sample hosted at the JCSDA) in the
production of land surface temperatures under cloudy conditions
will be provided.
Remote Access
Online video access:
Link to be posted soon.
Audio / conference call:
USA participants: 1-866-715-2479
Passcode: 9457557
International: 1-517-345-5260
The ECMWF forecasting system continues to be world leading in
terms of forecast performance in the medium range. Both the
deterministic and probabilistic forecast products are continuously
improved; in early 2010 a new model version with an increased
spatial resolution is being introduced, which will help to
maintain the positive performance trends. Research is focused on
new data assimilation techniques, improved description of physical
processes and development of enhanced ensemble prediction methods.
Monthly and seasonal forecasts are also produced; the current El
Nino event was predicted more than a year ago. Re-analyses are
regularly produced and updated. In recent years the re-analysis
shows global temperature trends over land areas that are
significantly warmer than results from other data sets
suggest.