New Radiosonde Temperature Bias Adjustments for Potential NWP Applications Based on GPS RO Data

Thursday, 18 December 2014
Bomin Sun1, Anthony Reale2, Bradley Ballish2 and Dian J Seidel2, (1)IMSG, College Park, MD, United States, (2)NOAA College Park, College Park, MD, United States
Conventional radiosonde observations (RAOBs), along with satellite and other in situ data, are assimilated in numerical weather prediction (NWP) models to generate a forecast. Radiosonde temperature observations, however, have solar and thermal radiation induced biases (typically a warm daytime bias from sunlight heating the sensor and a cold bias at night as the sensor emits longwave radiation). Radiation corrections made at stations based on algorithms provided by radiosonde manufacturers or national meteorological agencies may not be adequate, so biases remain. To adjust these biases, NWP centers may make additional adjustments to radiosonde data. However, the radiation correction (RADCOR) schemes used in the NOAA NCEP data assimilation and forecasting system is outdated and does not cover several widely-used contemporary radiosonde types. This study focuses on work whose objective is to improve these corrections and test their impacts on the NWP forecasting and analysis.

GPS Radio Occultation (RO) dry temperature (Tdry) is considered to be highly accurate in the upper troposphere and low stratosphere where atmospheric water vapor is negligible. This study uses GPS RO Tdry from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) as the reference to quantify the radiation induced RAOB temperature errors by analyzing ~ 3-yr collocated RAOB and COSMIC GPS RO data compile by the NOAA Products Validation System (NPROVS). The new radiation adjustments are developed for different solar angle categories and for all common sonde types flown in the WMO global operational upper air network.

Results for global and several commonly used sondes are presented in the context of NCEP Global Forecast System observation-minus-background analysis, indicating projected impacts in reducing forecast error. Dedicated NWP impact studies to quantify the impact of the new RADCOR schemes on the NCEP analyses and forecast are under consideration.