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A three-dimensional gridded climatology of carbon monoxide (CO) has been developed by trajectory mapping of global MOZAIC-IAGOS in situ measurements from commercial aircraft data. CO measurements made during aircraft ascent and descent, comprising nearly 41 200 profiles at 148 airports worldwide from December 2001 to December 2012 are used. Forward and backward trajectories are calculated from meteorological reanalysis data in order to map the CO measurements to other locations, and so to fill in the spatial domain. This domain-filling technique employs 15 800 000 calculated trajectories to map otherwise sparse MOZAIC-IAGOS data into a quasi-global field. The resulting trajectory-mapped CO dataset is archived monthly from 2001–2012 on a grid of 5° longitude × 5° latitude × 1 km altitude, from the surface to 14 km altitude.
The mapping product has been carefully evaluated, by comparing maps constructed using only forward trajectories and using only backward trajectories. The two methods show similar global CO distribution patterns. The magnitude of their differences is most commonly 10 % or less, and found to be less than 30 % for almost all cases. The trajectory-mapped CO dataset has also been validated by comparison profiles for individual airports with those produced by the mapping method when data from that site are excluded. While there are larger differences below 2 km, the two methods agree very well between 2 and 10 km with the magnitude of biases within 20 %.
Maps are also compared with Version 6 data from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. While agreement is good in the lowermost troposphere, the MOPITT CO profile shows negative biases of ∼ 20 % between 500 and 300 hPa. These upper troposphere biases are not related to the
mapping procedure, as almost identical differences are found with the original in situ MOZAIC-IAGOS data. The total CO trajectory-mapped MOZAIC-IAGOS climatology column agrees with the MOPITT CO total column within ±5 %, which is consistent with previous reports.
The maps clearly show major regional CO sources such as biomass burning in the central and southern Africa and anthropogenic emissions in eastern China. The dataset shows the seasonal CO cycle over different latitude bands and altitude ranges that are representative of the regions as well as long-term trends over latitude bands. We observe a decline in CO over the Northern Hemisphere extratropics and the tropics consistent with that reported by previous studies.
Similar maps have been made using the concurrent O3 measurements by MOZAICIAGOS, as the global variation of O3–CO correlations can be a useful tool for the evaluation of ozone sources and transport in chemical transport models. We anticipate use of the trajectory-mapped MOZAIC-IAGOS CO dataset as an a priori climatology for satellite retrieval, and for air quality model validation and initialization.
A three-dimensional gridded climatology of carbon monoxide (CO) has been developed by trajectory mapping of global MOZAIC-IAGOS in situ measurements from commercial aircraft data. CO measurements made during aircraft ascent and descent, comprising nearly 41 200 profiles at 148 airports worldwide from December 2001 to December 2012, are used. Forward and backward trajectories are calculated from meteorological reanalysis data in order to map the CO measurements to other locations and so to fill in the spatial domain. This domain-filling technique employs 15 800 000 calculated trajectories to map otherwise sparse MOZAIC-IAGOS data into a quasi-global field. The resulting trajectory-mapped CO data set is archived monthly from 2001 to 2012 on a grid of 5° longitude × 5° latitude × 1 km altitude, from the surface to 14 km altitude.
The mapping product has been carefully evaluated, firstly by comparing maps constructed using only forward trajectories and using only backward trajectories. The two methods show similar global CO distribution patterns. The magnitude of their differences is most commonly 10 % or less and found to be less than 30 % for almost all cases. Secondly, the method has been validated by comparing profiles for individual airports with those produced by the mapping method when data from that site are excluded. While there are larger differences below 2 km, the two methods agree very well between 2 and 10 km with the magnitude of biases within 20 %. Finally, the mapping product is compared with global MOZAIC-IAGOS cruise-level data, which were not included in the trajectory-mapped data set, and with independent data from the NOAA aircraft flask sampling program. The trajectory-mapped MOZAIC-IAGOS CO values show generally good agreement with both independent data sets.
Maps are also compared with version 6 data from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. Both data sets clearly show major regional CO sources such as biomass burning in Central and southern Africa and anthropogenic emissions in eastern China. While the maps show similar features and patterns, and relative biases are small in the lowermost troposphere, we find differences of ∼ 20 % in CO volume mixing ratios between 500 and 300 hPa. These upper-tropospheric biases are not related to the mapping procedure, as almost identical differences are found with the original in situ MOZAIC-IAGOS data. The total CO trajectory-mapped MOZAIC-IAGOS column is also higher than the MOPITT CO total column by 12–16 %.
The data set shows the seasonal CO cycle over different latitude bands and altitude ranges as well as long-term trends over different latitude bands. We observe a decline in CO over the northern hemispheric extratropics and the tropics consistent with that reported by previous studies using other data sources.
We anticipate use of the trajectory-mapped MOZAIC-IAGOS CO data set as an a priori climatology for satellite retrieval and for air quality model validation and initialization.
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.