Dynamics of ''internal'' interannual variability of the Indian summer monsoon in a GCM

1] The poor predictability of the Indian summer monsoon ( ISM) appears to be due to the fact that a large fraction of interannual variability (IAV) is governed by unpredictable "internal'' low frequency variations. Mechanisms responsible for the internal IAV of the monsoon have not been clearly identified. Here, an attempt has been made to gain insight regarding the origin of internal IAV of the seasonal ( June - September, JJAS) mean rainfall from "internal'' IAV of the ISM simulated by an atmospheric general circulation model (AGCM) driven by fixed annual cycle of sea surface temperature (SST). The underlying hypothesis that monsoon ISOs are responsible for internal IAV of the ISM is tested. The spatial and temporal characteristics of simulated summer intraseasonal oscillations ( ISOs) are found to be in good agreement with those observed. A long integration with the AGCM forced with observed SST, shows that ISO activity over the Asian monsoon region is not modulated by the observed SST variations. The internal IAV of ISM, therefore, appears to be decoupled from external IAV. Hence, insight gained from this study may be useful in understanding the observed internal IAV of ISM. The spatial structure of the ISOs has a significant projection on the spatial structure of the seasonal mean and a common spatial mode governs both intraseasonal and interannual variability. Statistical average of ISO anomalies over the season ( seasonal ISO bias) strengthens or weakens the seasonal mean. It is shown that interannual anomalies of seasonal mean are closely related to the seasonal mean of intraseasonal anomalies and explain about 50% of the IAV of the seasonal mean. The seasonal mean ISO bias arises partly due to the broad-band nature of the ISO spectrum allowing the time series to be aperiodic over the season and partly due to a non-linear process where the amplitude of ISO activity is proportional to the seasonal bias of ISO anomalies. The later relation is a manifestation of the binomial character of rainfall time series. The remaining 50% of the IAV may arise due to land-surface processes, interaction between high frequency variability and ISOs, etc.

Role of the cloud adjustment time scale in simulation of the interannual variability of Indian summer monsoon

The simulation of precipitation in a general circulation model relying on relaxed mass flux cumulus parameterization scheme is sensitive to cloud adjustment time scale (CATS). In this study, the frequency of the dominant intra-seasonal mode and interannual variability of Indian summer monsoon rainfall (ISMR) simulated by an atmospheric general circulation model is shown to be sensitive to the CATS. It has been shown that a longer CATS of about 5 h simulates the spatial distribution of the ISMR better. El Nio Southern Oscillation-ISMR relationship is also sensitive to CATS. The equatorial Indian Ocean rainfall and ISMR coupling is sensitive to CATS. Our study suggests that a careful choice of CATS is necessary for adequate simulation of spatial pattern as well as interannual variation of Indian summer monsoon precipitation.

On the trail of interannual variability in phytoplankton and climate [abstract and figures]

EXTRACT (SEE PDF FOR FULL ABSTRACT): A selective but nontheless real record of phytoplankton activity over the Santa Barbara Basin can be obtained from the underlying varved sediments. The phytoplankton groups preserved are: diatoms (frustrules and spores), silicoflagellates, dinoflagellates (cysts) and coccoliths.

Interannual variability of siliceous phytoplankton fluxes and relationships with hydrography in the northeastern subarctic Pacific, 1982-1986 [abstract and figures]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Time-series flux variabilities of biogenic opal particles were measured during 1982-1986 at pelagic Station PAPA (50° N, 145° W) located just south of the Gulf of Alaska, eastern North Pacific. PARFLUX sediment traps with two week sampling increments were deployed at 1000 m and 3800 m in 4200 m deep water, yielding nearly continuous time-series flux records for four years. The flux data allowed us to examine interannual and seasonal variabilities of siliceous phytoplankton production as well as environmental signals retained within the siliceous shells, which can be used to reconstruct environments.

Interannual variability in the PFEG coastal upwelling indices

Numerous studies examine decadal-scale variability in basin-scale parameters in the Northern Pacific. Characterizing such interannual-to-interdecadal variability is essential to identifying long-term climate changes. The Pacific Fisheries Environmental Group (PFEG) coastal upwelling indices display variability on these time scales and may help explain the mechanisms responsible for such climate variability. ... In this study, examination of 49-year time series of monthly mean upwelling indices at the 15 PFEG-standard positions along the west coast of North America revealed variability on large spatial scales as well as temporal scales.

vertical growth of thalassia testudinum seasonal and interannual variability

The vertical growth of shoots of the seagrass Thalassia testudinum Banks ex Konig in four meadows, along a range of exposure to waves, in the Mexican Caribbean was examined to elucidate its magnitude and its relationship to sediment dynamics. Average internodal length varied between 0.17 and 12.75 mm, and was greatest in the meadow which experienced the greatest burial by sand waves moved by Hurricane Gilbert (September 1988). Internodal length showed annual cycles, confirmed by the flower scars always preceding or coinciding with the annual minimum internodal length. These annual cycles on the shoot allowed estimation of annual leaf production, which varied, on average, between 14.2 and 19.3 leaves per shoot year-1. High vertical shoot growth was associated with long internodes and high leaf production rate, which increased with increasing vertical shoot growth to a maximum of approximately 25 leaves per shoot year-1, with vertical growth of about 30 mm year-1 or more. Average internodal length showed substantial interannual differences from perturbations derived from the passage of Hurricane Gilbert. The growth response of the plants surviving moderate burial and erosion after the hurricane involved enhanced vertical growth and increased leaf production, and reduced vertical growth, respectively, after 1988. The variability in shoot vertical growth of T testudinum can be separated into seasonal changes in plant growth, and long-term variability associated with episodic perturbations involving sediment redistribution by hurricanes.

IMPACTS OF THE TROPICAL PACIFIC COUPLED PROCESS ON THE INTERANNUAL VARIABILITY IN THE INDIAN OCEAN

The basic features of climatology and interannual variations of tropical Pacific and Indian Oceans were analyzed using a coupled general circulation model (CGCM), which was constituted with an intermediate 2.5-layer ocean model and atmosphere model ECHAM4. The CGCM well captures the spatial and temporal structure of the Pacific El Nino-Southern Oscillation (ENSO) and the variability features in the tropical Indian Ocean. The influence of Pacific air-sea coupled process on the Indian Ocean variability was investigated carefully by conducting numerical experiments. Results show that the occurrence frequency of positive/negative Indian Ocean Dipole (IOD) event will decrease/increase with the presence/absence of the coupled process in the Pacific Ocean. Further analysis demonstrated that the air-sea coupled process in the Pacific Ocean affects the IOD variability mainly by influencing the zonal gradient of thermocline via modulating the background sea surface wind.

Seasonal and interannual variability of primary and export production in the South China Sea: a three-dimensional physical-biogeochemical model study

To investigate the seasonal and interannual variations in biological productivity in the South China Sea (SCS), a Pacific basin-wide physical - biogeochemical model has been developed and used to estimate the biological productivity and export flux in the SCS. The Pacific circulation model, based on the Regional Ocean Model Systems (ROMS), is forced with daily air-sea fluxes derived from the NCEP (National Centers for Environmental Prediction) reanalysis between 1990 and 2004. The biogeochemical processes are simulated with a carbon, Si(OH)(4), and nitrogen ecosystem (CoSiNE) model consisting of silicate, nitrate, ammonium, two phytoplankton groups (small phytoplankton and large phytoplankton), two zooplankton grazers (small micrograzers and large mesozooplankton), and two detritus pools. The ROMS-CoSiNE model favourably reproduces many of the observed features, such as ChI a, nutrients, and primary production (PP) in the SCS. The modelled depth-integrated PP over the euphotic zone (0-125 m) varies seasonally, with the highest value of 386 mg C m (-2) d (-1) during winter and the lowest value of 156 mg C m (-2) d (-1) during early summer. The annual mean value is 196 mg C m (-2) d (-1). The model-integrated annual mean new production (uptake of nitrate), in carbon units, is 64.4 mg C m (-2) d (-1) which yields an f-ratio of 0.33 for the entire SCS. The modelled export ratio (e-ratio: the ratio of export to PP) is 0.24 for the basin-wide SCS. The year-to-year variation of biological productivity in the SCS is weaker than the seasonal variation. The large phytoplankton group tends to dominate over the smaller phytoplankton group, and likely plays an important role in determining the interannual variability of primary and new production.

Interannual variability of marine zooplankton and their environments: Within- and between-region comparisons

The work highlights the first Global Comparison of Zooplankton Time Series. ► Variation of the peak in abundance is affected by annual temperature anomalies. ► Results show no global-scale synchrony in zooplankton time-series. ► There are spatial autocorrelations over substantial distances (1000–3000 km). ► There remains considerable uncertainty about the relative causes of shifts in distributions.