A novel synergistic retrieval approach to enable tropospheric temperature and humidity profiling under all weather conditions for an improved quantification of evaporation rates

• Applicant: Dr. Andreas Foth
• Subject Area: Atmospheric Science
• Term: from 2020 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 438108095

The steady enhancements and improvements of weather and climate models is challenging for the atmospheric remote sensing community. In order to evaluate and improve these models, the observations need to be enhanced. The implementation of clouds and precipitation microphysics, such as precipitation-evaporation, into small scale models is based on highly empirical parametrizations which are strongly dependent on the thermodynamic state. Common approaches fail to continuously observe two of the major meteorological variables, temperature and humidity during all weather conditions and especially during rain. However, a wind profiling radar is capable to retrieve vertical information of the temperature and humidity gradient during such conditions. The proposed novel method based on a synergy between wind profiling radar (including a radio acoustic sounding system), Raman lidar, microwave radiometer, and cloud radar enables an automated and continuous observation of temperature and humidity profiles even during precipitation. The proposed variational approach (optimal estimation) provides a robust tool to combine various instruments with respect to uncertainties of the single systems. Within the optimal estimation, a given state (e.g. local climatology or last known state) is iteratively modified until it matches the measurements within their uncertainties. This approach enables a comprehensive analysis of the uncertainties of the results and an assessment of the contribution of each single instrument.The Meteorologisches Observatorium Lindenberg – Richard Aßmann Observatorium (MOL-RAO) has a unique suite of remote sensing instruments, including a 482 MHz wind profiling radar resulting in a long time series of atmospheric profile observations. The proposer will use this data set and apply his comprehensive experience with instrument synergy and retrieval development to obtain a continuous time series of temperature and humidity profiles with unprecedented accuracy within and above clouds and especially during precipitation. These precise thermodynamic profiles provide the ideal possibility to quantify evaporation rates and the referred cooling with an improved accuracy. The uncertainty induced by poor relative humidity and temperature profiles will be assessed by means of simulations of the evaporation rates. The evaporation and cooling rates will be determined by observations of a long-term data set at MOL-RAO to produce significant statistics. The results will be evaluated for different conditions as stratiform and convective precipitation and for different seasons. The community of atmospheric researchers will benefit from these findings with respect to evaporation rate parametrizations used in small scale models.

• DFG Programme: Research Grants