Evaluation of the Ozone Fields in NASA's MERRA-2 Reanalysis

We describe and assess the quality of the assimilated ozone product from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) produced at NASA's Global Modeling and Assimilation Office (GMAO) spanning the time period from 1980 to present. MERRA-2 assimilates partial column ozone retrievals from a series of Solar Backscatter Ultraviolet (SBUV) radiometers on NASA and NOAA spacecraft between January 1980 and September 2004; starting in October 2004 retrieved ozone profiles from the Microwave Limb Sounder (MLS) and total column ozone from the Ozone Monitoring Instrument on NASA's EOS Aura satellite are assimilated. We compare the MERRA-2 ozone with independent satellite and ozonesonde data focusing on the representation of the spatial and temporal variability of stratospheric and upper tropospheric ozone and on implications of the change in the observing system from SBUV to EOS Aura. The comparisons show agreement within 10 % (standard deviation of the difference) between MERRA-2 profiles and independent satellite data in most of the stratosphere. The agreement improves after 2004 when EOS Aura data are assimilated. The standard deviation of the differences between the lower stratospheric and upper tropospheric MERRA-2 ozone and ozonesondes is 11.2 % and 24.5 %, respectively, with correlations of 0.8 and above, indicative of a realistic representation of the near-tropopause ozone variability in MERRA-2. The agreement improves significantly in the EOS Aura period, however MERRA-2 is biased low in the upper troposphere with respect to the ozonesondes. Caution is recommended when using MERRA-2 ozone for decadal changes and trend studies.

Landsat ETM+ images in the estimation of seasonal lake water quality in boreal river basins

We investigated the use of Landsat ETM+ images in the monitoring of turbidity, colored dissolved organic matter (CDOM), and Secchi disk transparency (Z(SD)) in lakes of two river basins located in southern Finland. The ETM+ images were acquired in May, June, and September 2002 and were corrected for atmospheric disturbance using the simplified method of atmospheric correction (SMAC) model. The in situ measurements consisted of water sampling in the largest lake of the region, routine monitoring results for the whole study area, and Z(SD) observations made by volunteers. The ranges of the water quality variables in the dataset were as follows: turbidity, 0.6-25 FNU; absorption coefficient of CDOM at 400 nm, 1.0-12.2 m(-1); Z(SD), 0.5-5.5 m; and chlorophyll a concentration, 2.4-80 microg L(-1). The estimation accuracies of the image-specific empirical algorithms expressed as relative errors were 23.0% for turbidity, 17.4% for CDOM, and 21.1% for Z(SD). If concurrent in situ measurements had not been used for algorithm training, the average error would have been about 37%. The atmospheric correction improved the estimation accuracy only slightly compared with the use of top-of-atmospheric reflectances. The accuracy of the water quality estimates without concurrent in situ measurements could have been improved if in-image atmospheric parameters had been available. The underwater reflectance simulations of the ETM+ channel wavelengths using water quality typical for Finnish lakes (data from 1113 lakes) indicated that region-specific algorithms may be needed in other parts of the country, particularly in the case of Z(SD). Despite the limitations in the spectral and radiometric resolutions, ETM+ imagery can be an effective aid, particularly in the monitoring and management of small lakes (<1 km(2)), which are often not included in routine monitoring programs.