Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: David Carvalho x
  • Journal of Atmospheric and Oceanic Technology x
  • All content x
Clear All Modify Search
Will McCarty, David Carvalho, Isaac Moradi, and Nikki C. Privé


A set of observing system simulation experiments (OSSEs) was performed to investigate the utility of a constellation of passive infrared spectrometers, strategically designed with the aim of deriving the three-dimensional retrievals of the horizontal wind via atmospheric motion vectors (AMVs) from instruments with the spectral resolution of an infrared sounder. The instrument and constellation designs were performed in the context of the Midwave Infrared Sounding of Temperature and humidity in a Constellation for Winds (MISTiC Winds). The Global Modeling and Assimilation Office OSSE system, which includes a full suite of operational meteorological observations, served as the control. To illustrate the potential impact of this observing strategy, two experiments were performed by adding the new simulated observations to the control. First, perfect (error free) simulated AMVs and radiances were assimilated. Second, the data were made imperfect by adding realistic modeled errors to the AMVs and radiances that were assimilated. The experimentation showed beneficial impacts on both the mass and wind fields, as based on analysis verification, forecast verification, and the assessment of the observations using the forecast sensitivity to observation impact (FSOI) metric. In all variables and metrics, the impacts of the imperfect observations were smaller than those of the perfect observations, although much of the positive benefit was retained. The FSOI metric illustrated two key points. First, the largest impacts were seen in the middle troposphere AMVs, which is a targeted capability of the constellation strategy. Second, the addition of modeled errors showed that the assimilation system was unable to fully exploit the 4.3-μm carbon dioxide absorption radiances.

Restricted access
Ronald M. Errico, David Carvalho, Nikki C. Privé, and Meta Sienkiewicz


An algorithm to simulate locations of atmospheric motion vectors for use in observing system simulation experiments is described and demonstrated. It is intended to obviate likely deficiencies in nature run data if used to produce images for feature tracking. The algorithm employs probabilistic functions that are tuned based on distributions of real observations and histograms of nature run fields. For distinct observation types, the algorithm produces geographical and vertical distributions, time-mean counts, and typical spacings of simulated locations that are, at least qualitatively, similar to those of real observations and are associated with nature run cloud and water vapor fields. It thus appears suitable for generating realistic atmospheric motion vectors for use in observing system simulation experiments.

Free access