Abstract:

NOAA’s Low earth orbit satellite sensors provide more than 80 percent of data assimilated into numerical weather prediction models and are critical for producing timely and accurate weather forecasts. Recent expansion of 5G wireless technology could impact weather forecasting by introducing unwanted radio signals or radio frequency interference (RFI) to temperature and moisture sounding channels used by passive satellite microwave radiometers. In this project a new method for assessing radio frequency interference impact across globally diverse environmental conditions for the Advanced Technology Microwave Sounder (ATMS) 50 – 53 GHz channel measurements is suggested. The method is based on the analysis of the ATMS brightness temperatures simulated using the Community Radiative transfer model (CRTM) and Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV). Synthetic noise equivalent delta temperature (NEDT) (i.e. per channel brightness temperature uncertainty due to instrument noise), and a spectrally non-uniform radio frequency interference (RFI) – induced brightness temperature perturbation were applied to evaluate the impact of sensor noise and RFI on the simulated observations. Different combinations of ATMS channels were excluded from a machine-learning based retrieval algorithm predictor set to evaluate the impact of channel-specific information loss on retrieved satellite soundings. Comparison with retrievals derived from observed ATMS brightness temperatures showed the best agreement for atmospheric temperature using noise with a standard deviation of 1 times the nominal NEDT while those for humidity showed the closest agreement with 3times the nominal NEDT. The ATMS configuration comparison demonstrated slight degradation with removal of channels 3, 4 and 5 with the exclusion of channel 5introducing the largest impact among the three. The exclusion of the full V-band introduced a degradation of approximately 2 K near the surface and 5K in the upper troposphere The inclusion of a 10 K RFI perturbation resulted in a drastic degradation of the retrieval error in the mid troposphere when applied to channels 5-6 and near the surface when applied to 3 4. These results support the need for RFI detection capability in order to preserve observation accuracy for the ATMS and future microwave sounder satellites.

The results presented are from the NOAA Experiential Research Training Opportunity (NERTO) graduate internship project conducted under the mentorship of Lihang Zhou, LEO Satellite Product Manager at NOAA NESDIS, JPSS. This NERTO experience aligns with the NOAA Cooperative Science Center in CESSRST-II, supporting the Center’s goal of conducting NOAA mission-aligned collaborative research to understand and predict changes in weather and atmosphere, land and water, oceans and coasts. This project, titled Retrieval Assessments for Different Microwave Sounder Configurations: Examining the Impact of Radio Frequency Interference on the Advanced Technology Microwave Sounder addressed the research question: what is the potential impact radio frequency interference from recent FTU allocations on ATMS temperature and humidity sounding data products. The work provides value to the scientific community and program stakeholders by creating a rapid assessment methodology to support the development of next generation technology for microwave sounders in support of emerging architectures that emphasize rapid sensor development and deployment while still preserving data integrity of data products while applying the methodology to a real world case study that provides direct support to current NESDIS priorities. Through this internship, the student deepened their understanding of NOAA mission areas and gained enhanced skills in atmospheric retrievals, algorithm development, satellite mission operations, JPSS mission science, model simulations, calibration and validation processes and algorithm development.