Seasonal-to-decadal predictions are inevitably uncertain, depending on the size of the predictable signal relative to unpredictable chaos. Uncertainties can be accounted for using ensemble techniques, permitting quantitative probabilistic forecasts. In a perfect system, each ensemble member would represent a potential realization of the true evolution of the climate system, and the predictable components in models and reality would be equal. However, we show that the predictable component is sometimes lower in models than observations, especially for seasonal forecasts of the North Atlantic Oscillation and multiyear forecasts of North Atlantic temperature and pressure. In these cases the forecasts are underconfident, with each ensemble member containing too much noise. Consequently, most deterministic and probabilistic measures underestimate potential skill and idealized model experiments underestimate predictability. However, skilful and reliable predictions may be achieved using a large ensemble to reduce noise and adjusting the forecast variance through a postprocessing technique proposed here.

No abstract

Abstract. Substantial amounts of secondary organic aerosol (SOA) can be formed from isoprene epoxydiols (IEPOX), which are oxidation products of isoprene mainly under low-NO conditions. Total IEPOX-SOA, which may include SOA formed from other parallel isoprene oxidation pathways, was quantified by applying positive matrix factorization (PMF) to aerosol mass spectrometer (AMS) measurements. The IEPOX-SOA fractions of organic aerosol (OA) in multiple field studies across several continents are summarized here and show consistent patterns with the concentration of gas-phase IEPOX simulated by the GEOS-Chem chemical transport model. During the Southern Oxidant and Aerosol Study (SOAS), 78 % of PMF-resolved IEPOX-SOA is accounted by the measured IEPOX-SOA molecular tracers (2-methyltetrols, C5-Triols, and IEPOX-derived organosulfate and its dimers), making it the highest level of molecular identification of an ambient SOA component to our knowledge. An enhanced signal at C5H6O+ (m/z 82) is found in PMF-resolved IEPOX-SOA spectra. To investigate the suitability of this ion as a tracer for IEPOX-SOA, we examine fC5H6O (fC5H6O= C5H6O+/OA) across multiple field, chamber, and source data sets. A background of ~ 1.7 ± 0.1 ‰ (‰ = parts per thousand) is observed in studies strongly influenced by urban, biomass-burning, and other anthropogenic primary organic aerosol (POA). Higher background values of 3.1 ± 0.6 ‰ are found in studies strongly influenced by monoterpene emissions. The average laboratory monoterpene SOA value (5.5 ± 2.0 ‰) is 4 times lower than the average for IEPOX-SOA (22 ± 7 ‰), which leaves some room to separate both contributions to OA. Locations strongly influenced by isoprene emissions under low-NO levels had higher fC5H6O (~ 6.5 ± 2.2 ‰ on average) than other sites, consistent with the expected IEPOX-SOA formation in those studies. fC5H6O in IEPOX-SOA is always elevated (12–40 ‰) but varies substantially between locations, which is shown to reflect large variations in its detailed molecular composition. The low fC5H6O (< 3 ‰) reported in non-IEPOX-derived isoprene-SOA from chamber studies indicates that this tracer ion is specifically enhanced from IEPOX-SOA, and is not a tracer for all SOA from isoprene. We introduce a graphical diagnostic to study the presence and aging of IEPOX-SOA as a triangle plot of fCO2 vs. fC5H6O. Finally, we develop a simplified method to estimate ambient IEPOX-SOA mass concentrations, which is shown to perform well compared to the full PMF method. The uncertainty of the tracer method is up to a factor of ~ 2, if the fC5H6O of the local IEPOX-SOA is not available. When only unit mass-resolution data are available, as with the aerosol chemical speciation monitor (ACSM), all methods may perform less well because of increased interferences from other ions at m/z 82. This study clarifies the strengths and limitations of the different AMS methods for detection of IEPOX-SOA and will enable improved characterization of this OA component.

Bioaerosols are relevant for public health and may play an important role in the climate system, but their atmospheric abundance, properties, and sources are not well understood. Here we show that the concentration of airborne biological particles in a North American forest ecosystem increases significantly during rain and that bioparticles are closely correlated with atmospheric ice nuclei (IN). The greatest increase of bioparticles and IN occurred in the size range of 2–6 μm, which is characteristic for bacterial aggregates and fungal spores. By DNA analysis we found high diversities of airborne bacteria and fungi, including groups containing human and plant pathogens (mildew, smut and rust fungi, molds, Enterobacteriaceae, Pseudomonadaceae). In addition to detecting known bacterial and fungal IN (Pseudomonas sp., Fusarium sporotrichioides), we discovered two species of IN-active fungi that were not previously known as biological ice nucleators (Isaria farinosa and Acremonium implicatum). Our findings suggest that atmospheric bioaerosols, IN, and rainfall are more tightly coupled than previously assumed