Physical retrievals of temperature and humidity profiles at Nainital from a combination of passive and active sensors

 

Authors

Maria Paola Cadeddu — Argonne National Laboratory
Narendra Ojha — Aryabhatta Research Institute of Observational Sciences

Category

ARM Infrastructure

Description

We developed a new physical retrieval of vertical profiles of temperature and humidity from the 12-channel microwave radiometer (MWRP) in combination with the 2-channel MWR, the Vaisala Ceilometer, and the surface met system. Vertical profiles of temperature and humidity have low vertical resolution and need to be constrained with some prior information on the atmospheric state. For this reason the algorithm uses the closest radiosonde launch as prior information and retrieves temperature and humidity profiles with an optimal estimation technique by minimizing the root-mean-square difference between the measured and simulated brightness temperatures. In this poster we present clear-sky retrievals from the Ganges Valley Aerosol Experiment (GVAX). It is shown that the technique is useful to capture changes in the atmospheric state between radiosondes launches. Clear-sky profiles were computed every 30 minutes from the month of November 2011 to March 2012 and were evaluated by using the retrieved profiles as input to the Santa Barbara DISORT Atmospheric Radiative Transfer code (SBDART) and comparing the short-wave broadband flux simulations to observations from the co-located SKYRAD. Results show that with the retrieved profiles it is possible to capture the diurnal variability of the incoming flux. We show the advantages of using high temporal resolution profiles by comparing the results with those obtained by using mean temperature and humidity profiles as input to the radiative transfer code. Although the presented retrievals are only for clear-sky cases an extension of the retrieval to cloudy skies is in development. The retrieval uses information from the 2-channel MWR and the Vaisala ceilometer to identify the liquid water path and the location of clouds. The algorithm is developed in a way that allows the inclusion of additional instruments with minimal changes so that additional sensors such as radar or wind profiler can be added.