Engineering topics

Fleming, Eric

Publications and source records attributed to Fleming, Eric.

4 records

NASA NTRS2003

The SPARC Intercomparison of Middle Atmosphere Climatologies

Our current confidence in 'observed' climatological winds and temperatures in the middle atmosphere (over altitudes approx. 10-80 km) is assessed by detailed intercomparisons of contemporary and historic data sets. These data sets include global meteorological analyses and assimilations, climatologies derived from research satellite measurements, and historical reference atmosphere circulation statistics. We also include comparisons with historical rocketsonde wind and temperature data, and with more recent lidar temperature measurements. The comparisons focus on a few basic circulation statistics, such as temperature, zonal wind, and eddy flux statistics. Special attention is focused on tropical winds and temperatures, where large differences exist among separate analyses. Assimilated data sets provide the most realistic tropical variability, but substantial differences exist among current schemes.

Randel, William↗

NASA NTRS2002

SPARC Intercomparison of Middle Atmosphere Climatologies

This atlas presents detailed incomparisons of several climatological wind and temperature data sets which cover the middle atmosphere (over altitudes approx. 10-80 km). A number of middle atmosphere climatologies have been developed in the research community based on a variety of meteorological analyses and satellite data sets. Here we present comparisons between these climatological data sets for a number of basic circulation statistics, such as zonal mean temperature, winds and eddy flux statistics. Special attention is focused on tropical winds and temperatures, where large differences exist among separate analyses. We also include comparisons between the global climatologies and historical rocketsonde wind and temperature measurements, and also with more recent lidar temperature data. These comparisons highlight differences and uncertainties in contemporary middle atmosphere data sets, and allow biases in particular analyses to be isolated. In addition, a brief atlas of zonal mean temperature and wind statistics is provided to highlight data availability and as a quick-look reference. This technical report is intended as a companion to the climatological data sets held in archive at the SPARC Data Center (http://www.sparc.sunysb.edu).

Randel, William↗

NASA NTRS2002

Comparison of a 2D Photochemical Model to Data Using Statistical Trend Analysis

We have analyzed our 23-year merged ozone data set for variability and trends with a statistical time-series model. To assist in that analysis, we have analyzed the Goddard 2D photochemical model for the same time period with the same time-series model. Multiple runs of the photochemical model allow us to separate the effects of various terms on ozone, such as solar cycle and volcanic eruptions. We use this to help us separate those signals from each other in the data. We also used a smoothed version of the photochemical model's prediction of global ozone change in place of a simple linear trend. We find a number of interesting results. This particular photochemical model is more sensitive to chlorine perturbations than the atmosphere appears to be. It is less sensitive to solar cycle. It predicts an effect from the Pinatubo eruption that is nearly symmetric in the two hemispheres, but the data appears to have not responded to Pinatubo in the southern mid-latitudes. These results and their uncertainties will be discussed.

Bhartia, P. K.↗

NASA NTRS1998

HSCT Assessment Calculations with the AER 2-D Model: Sensitivities to Transport Formulation, PSC Formulation, Interannual Temperature Variation

The summary are: (1) Some chemical differences in background atmosphere are surprisingly large (NOY). (2) Differences in model transport explain a majority of the intertnodel differences in the absence of PSCs. (3) With PSCS, large differences exist in predicted O3 depletion between models with the same transport. (4) AER/LLNL model calculates more O3 depletion in NH than LLNL. (5) AER/GSFC model cannot match calculated O3 depletion of GSFC model in SH. and (6) Results sensitive to interannual temperature variations (at least in NH).

Weisenstein, Debra K.↗