Person:

Liu, Xiong

We analyze the theoretical basis of three different methods to validate and intercompare satellite measurements of atmospheric composition, and apply them to tropospheric ozone retrievals from the Tropospheric Emission Spectrometer (TES) and the Ozone Monitoring Instrument (OMI). The first method (in situ method) uses in situ vertical profiles for absolute instrument validation; it is limited by the sparseness of in situ data. The second method (CTM method) uses a chemical transport model (CTM) as an intercomparison platform; it provides a globally complete intercomparison with relatively small noise from model error. The third method (averaging kernel smoothing method) involves smoothing the retrieved profile from one instrument with the averaging kernel matrix of the other; it also provides a global intercomparison but dampens the actual difference between instruments and adds noise from the a priori. We apply the three methods to a full year (2006) of TES and OMI data. Comparison with in situ data from ozonesondes shows mean positive biases of 5.3 parts per billion volume (ppbv) (10%) for TES and 2.8 ppbv (5%) for OMI at 500 hPa. We show that the CTM method (using the GEOS-Chem CTM) closely approximates results from the in situ method while providing global coverage. It reveals that differences between TES and OMI are generally less than 10 ppbv (18%), except at northern mid-latitudes in summer and over tropical continents. The CTM method further allows for CTM evaluation using both satellite observations. We thus find that GEOS-Chem underestimates tropospheric ozone in the tropics due to possible underestimates of biomass burning, soil, and lightning emissions. It overestimates ozone in the northern subtropics and southern mid-latitudes, likely because of excessive stratospheric influx of ozone.

TEMPO was selected in 2012 by NASA as the first Earth Venture Instrument, for launch circa 2018. It will measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO measures from Mexico City to the Canadian tar sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution (~2 km N/S×4.5 km E/W at 36.5°N, 100°W). TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry. Measurements are from geostationary (GEO) orbit, to capture the inherent high variability in the diurnal cycle of emissions and chemistry. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies.

TEMPO takes advantage of a commercial GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve (O_3), (NO_2), (SO_2), (H_2CO), (C_2H_2O_2), (H_2O), aerosols, cloud parameters, and UVB radiation. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric (O_3) chemistry cycle. Multi-spectral observations provide sensitivity to (O_3) in the lowermost troposphere, substantially reducing uncertainty in air quality predictions. TEMPO quantifies and tracks the evolution of aerosol loading. It provides near-real-time air quality products that will be made widely, publicly available. TEMPO will launch at a prime time to be the North American component of the global geostationary constellation of pollution monitoring together with European Sentinel-4 and Korean GEMS.

We present the first directly retrieved global distribution of tropospheric column ozone from Global Ozone Monitoring Experiment (GOME) ultraviolet measurements during December 1996 to November 1997. The retrievals clearly show signals due to convection, biomass burning, stratospheric influence, pollution, and transport. They are capable of capturing the spatiotemporal evolution of tropospheric column ozone in response to regional or short time-scale events such as the 1997–1998 El Niño event and a 10–20 DU change within a few days. The global distribution of tropospheric column ozone displays the well-known wave-1 pattern in the tropics, nearly zonal bands of enhanced tropospheric column ozone of 36–48 DU at 20°S–30°S during the austral spring and at 25°N–45°N during the boreal spring and summer, low tropospheric column ozone of <30 DU uniformly distributed south of 35°S during all seasons, and relatively high tropospheric column ozone of >33 DU at some northern high-latitudes during the spring. Simulation from a chemical transport model corroborates most of the above structures, with small biases of <±5 DU and consistent seasonal cycles in most regions, especially in the southern hemisphere. However, significant positive biases of 5–20 DU occur in some northern tropical and subtropical regions such as the Middle East during summer. Comparison of GOME with monthly-averaged Measurement of Ozone and Water Vapor by Airbus in-service Aircraft (MOZAIC) tropospheric column ozone for these regions usually shows good consistency within 1σ standard deviations and retrieval uncertainties. Some biases can be accounted for by inadequate sensitivity to lower tropospheric ozone, the different spatiotemporal sampling and the spatiotemporal variations in tropospheric column ozone.

We validate the Ozone Monitoring Instrument (OMI) ozone-profile (PROFOZ) product from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against ozonesonde observations. We also evaluate the effects of OMI Row anomaly (RA) on the retrieval by dividing the data set into before and after the occurrence of serious OMI RA, i.e., pre-RA (2004-2008) and post-RA (2009-2014). The retrieval shows good agreement with ozonesondes in the tropics and mid-latitudes and for pressure < ~50 hPa in the high latitudes. It demonstrates clear improvement over the a priori down to the lower troposphere in the tropics and down to an average of ~550 (300) hPa at middle (high latitudes). In the tropics and mid-latitudes, the profile mean biases (MBs) are less than 6%, and the standard deviations (SDs) range from 5-10% for pressure < ~50 hPa to less than 18% (27%) in the tropics (midlatitudes) for pressure > ~50 hPa after applying OMI averaging kernels to ozonesonde data. The MBs of the stratospheric ozone column (SOC) are within 2% with SDs of < 5% and the MBs of the tropospheric ozone column (TOC) are within 6% with SDs of 15%. In the high latitudes, the profile MBs are within 10% with SDs of 5-15% for pressure < ~50 hPa, but increase to 30% with SDs as great as 40% for pressure > ~50 hPa. The SOC MBs increase up to 3% with SDs as great as 6% and the TOC SDs increase up to 30%. The comparison generally degrades at larger solarzenith angles (SZA) due to weaker signals and additional sources of error, leading to worse performance at high latitudes and during the mid-latitude winter. Agreement also degrades with increasing cloudiness for pressure > ~100 hPa and varies with cross-track position, especially with large MBs and SDs at extreme off-nadir positions. In the tropics and mid-latitudes, the post-RA comparison is considerably worse with larger SDs reaching 2% in the stratosphere and 8% in the troposphere and up to 6% in TOC. There are systematic differences that vary with latitude compared to the pre-RA comparison. The retrieval comparison demonstrates good long-term stability during the pre-RA period, but exhibits a statistically significant trend of 0.14-0.7%/year for pressure < ~ 80 hPa, 0.7 DU/year in SOC and -0.33 DU/year in TOC during the post-RA period. The spatiotemporal variation of retrieval performance suggests the need to improve OMI’s radiometric calibration especially during the post-RA period to maintain the long-term stability and reduce the latitude/season/SZA and cross-track dependence of retrieval quality.