O. E. García

Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopologues: 1. Comparison between models and observations

The goal of this study is to determine how H2O and HDO measurements in water vapor can be used to detect and diagnose biases in the representation of processes controlling tropospheric humidity in atmospheric general circulation models (GCMs). We analyze a large number of isotopic data sets (four satellite, sixteen ground-based remote-sensing, five surface in situ and three aircraft data sets) that are sensitive to different altitudes throughout the free troposphere. Despite significant differences between data sets, we identify some observed HDO/H2O characteristics that are robust across data sets and that can be used to evaluate models. We evaluate the isotopic GCM LMDZ, accounting for the effects of spatiotemporal sampling and instrument sensitivity. We find that LMDZ reproduces the spatial patterns in the lower and mid troposphere remarkably well. However, it underestimates the amplitude of seasonal variations in isotopic composition at all levels in the subtropics and in midlatitudes, and this bias is consistent across all data sets. LMDZ also underestimates the observed meridional isotopic gradient and the contrast between dry and convective tropical regions compared to satellite data sets. Comparison with six other isotope-enabled GCMs from the SWING2 project shows that biases exhibited by LMDZ are common to all models. The SWING2 GCMs show a very large spread in isotopic behavior that is not obviously related to that of humidity, suggesting water vapor isotopic measurements could be used to expose model shortcomings. In a companion paper, the isotopic differences between models are interpreted in terms of biases in the representation of processes controlling humidity. Copyright

Analysis of satellite sea surface temperature time series in the Brazil-Malvinas Current Confluence region: Dominance of the annual and semiannual periods

We study the dominant periodic variations of sea surface temperature (SST) in the Brazil-Malvinas Confluence region from a satellite-derived data set compiled by Olson et al. (1988). This data set is composed of 202 sea surface temperature images with a 4 × 4 km resolution and extends over 3 years (from July 1984 to July 1987). Each image is a 5-day composite. The dominant signal, as already observed by Podesta et al. (1991), has a 1-year period. We first fit a single-frequency sinusoidal model of the annual cycle in order to estimate mean temperature, amplitude, and phase at 159 points uniformly distributed over the region. The residuals are generally small (less than 2°C). The largest departures from this cycle are located either in the Brazil-Malvinas frontal region or in the southeastern part of the region. Other periods in SST variations are identified by means of periodograms of the 159 residual time series in which the annual cycle has been substracted. The periodograms show that a semiannual frequency signal is present at almost every location. The ratio of the semiannual amplitude to the annual amplitude increases southward from 0% at 30°S to reach up to 45% at 50°S. In the south the semiannual signal creates an asymmetry, and the resulting (total) annual cycle has a cold period (winter) longer than the warm one (summer). In the frontal region the annual and semiannual signals have an important interannual variation. This semiannual frequency is associated with the semiannual wave present in the atmospheric forcing of the southern hemisphere. Differential heating over the mid-latitude oceans and the high-latitude ice-covered Antarctic Continent has been suggested as the cause of this semiannual wave (Van Loon, 1967).

CO2 total column amounts at TCCON sites Izana (28.3 N, 16.5 W) and Karlsruhe (49.1 N, 8.5 E)

The Total Carbon Observing Network (TCCON) is a global network of ground-based Fourier Transform Spectrometers recording direct solar spectra in the near-infrared (NIR) spectral region. Accurate and precise columnaveraged abundances of different greenhouse gases (GHGs) are retrieved, which are used for carbon cycle research [1] and for satellite validation (e.g. SCIAMACHY, GOSAT, OCOII). Official TCCON data are generated using the GFIT code compared FTIR retrieval results with in-situ measurements developed at NASA/JPL [2]. In this study, we compare FTIR retrieval results with in-situ measurements as well as the GFIT code with the radiative transfer and retrieval algorithm PROFFIT [3].