Use of Solar Reflectance Hyperspectral Data for Cloud Base Retrieval Andrew Heidinger, NOAA/NESDIS/ORA Washington D.C, USA Outline " Physical basis for cloud base information in hyperspectral data " Efficient radiative transfer modelling  Simulated results for MODIS 0.94  m water vapour bands " Preliminary results from MODIS " Conclusions and future work

Why attempt to measure cloud base? " Current passive sensors microwave, visible, infrared sensors offer little direct sensitivity of cloud base. " Active sensor satellite programs like Cloudsat and Calipso, will offer detailed information but poor spatial and temporal sampling. " Cloud base determines the downwelling longwave radiation at the surface and the magnitude of in-cloud radiative heating " Support of aviation cloudiness requirements Current capabilities: Non-overlapped Cloud amount, cloud-top position, optical thickness

Physical Basis for Cloud Base Retrieval from Solar Reflectance in Absorption Lines " This remote sensing technique has a long heritage in astrophysics where the depth of absorption lines was used to estimate how much gas is in an atmosphere (co 2 on mars) " Outside of a molecular absorption band, two clouds (with same optical thickness) would appear identical. " In an absorption line, the greater the pressure thickness of a cloud, the more absorbing gas the more absorption will occu and the lower the reflectance. Sun Satellite Cloud

Using MODIS as a Test bed for Hyperspectral Cloud Base Retrieval  MODIS resolves the 0.94  m water vapour line(ch 17,18,19) – a relatively strong and broad absorption band as well as one channel centred in the 1.4  m band.(ch26) " Ideally, a hyperspectral sensor would provide information for other gases such as co 2 and o 2. This would remove the need to retrieve the water vapour profile as well. " Allows for testing of approach on globally available satellite data

Sample MODIS Ch2,Ch17,CH18,Ch26 Reflectances for Stratus near CA

" MODIS channels offer the following vertical profile of cloud base sensitivity  The 1.38  m channel offers information for cirrus and will be available on VIIRS Information in MODIS concerning Cloud Base

Efficient Radiative Transfer Modeling " To model reflectance in an absorption band, you need to account for the interaction of the gas with the scatters in the cloud " Using the equivalence theorem of Irvine(1964), if you know the photon pathlengths without absorption, you can include absorption easily. " So the forward model is based on a lookup table of the form R = f( , r e,        ) " Use of the photon pathlength (two more dimensions in a lookup table) allows for rapid estimation of reflectances for many channels of differing absorption strength (ideal for hyperspectral modelling). Pathlength Dist.

Limits of Forward Mode l " Model assumes no vertical heterogeneity in cloud and gas (cloud is assumed saturated) " For thick clouds, this limits accuracy " Approximation included to estimate using pathlengths how scatterings are distributed through multiple layers in cloud

Retrieval Algorithm " Sensitivity analyses showed that to retrieve cloud pressure thickness, Cloud optical depth and above cloud precipitable water " Cloud top pressure is assumed known to 50 mb.(from MODIS IR/CO 2 ) " Results indicate, cloud base pressure is more difficult to retrieve than above cloud precipitable water. " Noise in Ch26 of MODIS is prohibits it use for cloud base retrieval for some scenarios (preliminary). " Forward model is used in 1d-Var retrieval approach using reflectances and reflectance ratios (ch18/ch2). " High clouds of moderate optical thickness are easiest, low thin clouds in a moist atmosphere are most challenging.

Above cloud water vapour is retrievable for clouds below 500 mb. Hyperspectral spectra should allow for retrieval of smaller water vapour amounts over higher clouds Above Cloud Water Vapor

Simulated Results " Simulations with 2% calibration errors on reflectances show 20 mb accuracy for many scenarios " As shown, there is a need for cloud top pressure and information on water vapour profile helps

Sample Retrieval Results for Stratus off California viewed by MODIS Ch31 (11  m) Temperature Reflectance Ratio (Ch18/Ch2) Reflectance Ratio clearly shows above cloud water vapour and cloud height – cloud pressure thickness signal not clear in this scene

Sample Results for the nadir slice through this scene " May not be properly separating cloud base signal from above cloud tpw " Increase in apparent cloud pressure thickness due to multi-layers clouds

Conclusions and Future Work  The MODIS channels in the 0.94  m water vapour absorption offer a chance to test some hyperspectral cloud retrieval concepts " A fast radiative transfer model suitable for modelling reflectances in absorption bands has been developed " Simulation indicates cloud base should be retrievable for many single layer cloudiness scenarios. " Application to MODIS of cloud base retrieval has been demonstrated but not yet validated. " This retrieval will be validated over a range of cloudiness using MODIS " Similar approach to estimating aerosol height will be explored.