Considerable uncertainties remain in the global pattern of diurnal variation in stratospheric ozone, particularly lower to middle stratospheric ozone, which is the principal contributor to total column ozone. The Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) attached to the Japanese Experiment Module (JEM) on board the International Space Station (ISS) was developed to gather high-quality global measurements of stratospheric ozone at various local times, with the aid of superconducting mixers cooled to 4K by a compact mechanical cooler. Using the SMILES dataset, as well as data from nudged chemistry-climate models (MIROC3.2-CTM and SD-WACCM), we show that the SMILES observational data have revealed the global pattern of diurnal ozone variations throughout the stratosphere. We also found that these variations can be explained by both photochemistry and dynamics. The peak-to-peak difference in the stratospheric ozone mixing ratio (total column ozone) reached 8% (1%) over the course of a day. This variation needs to be considered when merging ozone data from different satellite measurements and even from measurements made using one specific instrument at different local times.
Research Containing: Global climate models
Evaluating the Diurnal Cycle of Upper-Tropospheric Ice Clouds in Climate Models Using SMILES Observations
Upper-tropospheric ice cloud measurements from the Superconducting Submillimeter Limb Emission Sounder (SMILES) on the International Space Station (ISS) are used to study the diurnal cycle of upper-tropospheric ice cloud in the tropics and midlatitudes (40°S?40°N) and to quantitatively evaluate ice cloud diurnal variability simulated by 10 climate models. Over land, the SMILES-observed diurnal cycle has a maximum around 1800 local solar time (LST), while the model-simulated diurnal cycles have phases differing from the observed cycle by ?4 to 12 h. Over ocean, the observations show much smaller diurnal cycle amplitudes than over land with a peak at 1200 LST, while the modeled diurnal cycle phases are widely distributed throughout the 24-h period. Most models show smaller diurnal cycle amplitudes over ocean than over land, which is in agreement with the observations. However, there is a large spread of modeled diurnal cycle amplitudes ranging from 20% to more than 300% of the observed over both land and ocean. Empirical orthogonal function (EOF) analysis on the observed and model-simulated variations of ice clouds finds that the first EOF modes over land from both observation and model simulations explain more than 70% of the ice cloud diurnal variations and they have similar spatial and temporal patterns. Over ocean, the first EOF from observation explains 26.4% of the variance, while the first EOF from most models explains more than 70%. The modeled spatial and temporal patterns of the leading EOFs over ocean show large differences from observations, indicating that the physical mechanisms governing the diurnal cycle of oceanic ice clouds are more complicated and not well simulated by the current climate models.
Direct estimation of the rate constant of the reaction ClO + HO2 → HOCl + O2 from SMILES atmospheric observations
Diurnal variations of ClO, HO2, and HOCl were simultaneously observed by the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) between 12 October 2009 and 21 April 2010. These were the first global observations of the diurnal variation of HOCl in the upper atmosphere. A major reaction for the production of HOCl is ClO + HO2 → HOCl + O2 (Reaction (R1)) in extra-polar regions. A model study suggested that in the mesosphere, this is the only reaction influencing the amount of HOCl during the night. The evaluation of the pure reaction period, when only Reaction (R1) occurred in the Cly chemical system, was performed by checking the consistency of the HOCl production rate with the ClO loss rate from SMILES observation data. It turned out that the SMILES data at the pressure level of 0.28 hPa (about 58 km) in the autumn mid-latitude region (20–40°, February–April 2010) during night (between modified local time 18:30 and 04:00) were suitable for the estimation of the rate constant, k1. The rate constant obtained from SMILES observations was k1(245 K) = (7.75 ± 0.25) × 10−12 cm3 molecule−1 s−1. This result is consistent with results from a laboratory experiment and ab initio calculations for similar low-pressure conditions.
Overview and sample applications of SMILES and Odin-SMR retrievals of upper tropospheric humidity and cloud ice mass
Retrievals of cloud ice mass and humidity from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and the Odin-SMR (Sub-Millimetre Radiometer) limb sounder are presented and example applications of the data are given. SMILES data give an unprecedented view of the diurnal variation of cloud ice mass. Mean regional diurnal cycles are reported and compared to some global climate models. Some improvements in the models regarding diurnal timing and relative amplitude were noted, but the models' mean ice mass around 250 hPa is still low compared to the observations. The influence of the ENSO (El Niño–Southern Oscillation) state on the upper troposphere is demonstrated using 12 years of Odin-SMR data. The same retrieval scheme is applied for both sensors, and gives low systematic differences between the two data sets. A special feature of this Bayesian retrieval scheme, of Monte Carlo integration type, is that values are produced for all measurements but for some atmospheric states retrieved values only reflect a priori assumptions. However, this "all-weather" capability allows a direct statistical comparison to model data, in contrast to many other satellite data sets. Another strength of the retrievals is the detailed treatment of "beam filling" that otherwise would cause large systematic biases for these passive cloud ice mass retrievals. The main retrieval inputs are spectra around 635/525 GHz from tangent altitudes below 8/9 km for SMILES/Odin-SMR, respectively. For both sensors, the data cover the upper troposphere between 30° S and 30° N. Humidity is reported as both relative humidity and volume mixing ratio. The vertical coverage of SMILES is restricted to a single layer, while Odin-SMR gives some profiling capability between 300 and 150 hPa. Ice mass is given as the partial ice water path above 260 hPa, but for Odin-SMR ice water content, estimates are also provided. Besides a smaller contrast between most dry and wet cases, the agreement with Aura MLS (Microwave Limb Sounder) humidity data is good. In terms of tropical mean humidity, all three data sets agree within 3.5 %RHi. Mean ice mass is about a factor of 2 lower compared to CloudSat. This deviation is caused by the fact that different particle size distributions are assumed, combined with saturation and a priori influences in the SMILES and Odin-SMR data.