Citation
Abstract
We examine ~20 years of brightness temperature measurements, including the meteorological data derived from these measurements, from the advanced water vapor radiometers (AWVRs) at the Deep Space Network (DSN) site of Goldstone, California in the Mojave Desert. This study reexamines 15 years of data from 2001 to 2015, reported in a previous article, and recent data from 2015 to 2021, which was used for training and testing as part of a machine learning (ML) weather forecasting study. This article describes the calibration and validation processes used to quantify the statistical behavior of the various data types over the ~20-year period. We also studied seasonal behavior by closely examining the statistics for a sample summer month and a sample winter month. We find that the data types show no significant trends during the ~20-year period, remaining within the ~1 K calibration uncertainty of the AWVR brightness temperatures. The 1.02 cm average of the annual integrated water vapor (IWV) extracted from the AWVR brightness temperatures is consistent with the 1.00 cm average from an earlier one-year study for Goldstone conducted in 1993–1994.
Details
- Volume
- 42-228
- Published
- February 15, 2022
- Pages
- 1–18
- File Size
- 7.5 MB