Maps of subsoil temperature and active layer depth of Yakutian ASSR (Autonomous Soviet Socialist Republic of the Soviet Union)

Based on the map of landscapes and permafrost conditions in Yakutia (Merzlotno-landshaftnaya karta Yakutskoi0 ASSR, Gosgeodeziya SSSR, 1991), rasterized maps of permafrost temperature and active-layer thickness of Yakutia, East Siberia were derived. The mean and standard deviation at 0.5-degree grid cell size are estimated by assigning a probability density function at 0.001-degree spatial resolution. Spatial pattern of both variables are dominated by a climatic gradient from north to south, and by mountains and the soil type distribution. Uncertainties are highest in mountains and in the sporadic permafrost zone in the south. The maps are best suited as a benchmark for land surface models which include a permafrost module.

Environmental context of all samples from the Tara Oceans Expedition (2009-2013), about depth specific features

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides environmental context to all samples from the Tara Oceans Expedition (2009-2013), including calculated averages of mesaurements made concurrently at the sampling location and depth, and calculated averages from climatologies (AMODIS, VGPM) and satellite products.

Mixed-layer salinity budget in the tropical Indian Ocean: seasonal cycle based only on observations

The mixed-layer salinity (MLS) budget in the tropical Indian Ocean is estimated from a combination of satellite products and in situ observations over the 2004-2012 period, to investigate the mechanisms controlling the seasonal MLS variability. In contrast with previous studies in the tropical Indian Ocean, our results reveal that the coverage, resolution, and quality of available observations are now sufficient to approach a closed monthly climatology seasonal salt budget. In the South-central Arabian Sea and South-western Tropical Indian Ocean (SCAS and STIO, respectively), where seasonal variability of the MLS is pronounced, the monthly MLS tendency terms are well captured by the diagnostic. In the SCAS region, in agreement with previous results, the seasonal cycle of the MLS is mainly due to meridional advection driven by the monsoon winds. In the STIO, contrasting previous results indicating the control of the meridional advection over the seasonal MLS budget, our results reveal the leading role of the freshwater flux due to precipitation.

QuasiGeostrophic Diagnosis of Mixed-Layer Dynamics Embedded in a Mesoscale Turbulent Field

A quasigeostrophic model is developed to diagnose the three-dimensional circulation, including the vertical velocity, in the upper ocean from high-resolution observations of sea surface height and buoyancy. The formulation for the adiabatic component departs from the classical surface quasigeostrophic framework considered before since it takes into account the stratification within the surface mixed layer that is usually much weaker than that in the ocean interior. To achieve this, the model approximates the ocean with two constant stratification layers: a finite-thickness surface layer (or the mixed layer) and an infinitely deep interior layer. It is shown that the leading-order adiabatic circulation is entirely determined if both the surface streamfunction and buoyancy anomalies are considered. The surface layer further includes a diabatic dynamical contribution. Parameterization of diabatic vertical velocities is based on their restoring impacts of the thermal wind balance that is perturbed by turbulent vertical mixing of momentum and buoyancy. The model skill in reproducing the three-dimensional circulation in the upper ocean from surface data is checked against the output of a high-resolution primitive equation numerical simulation

Warm pool thermodynamics from the Arabian Sea Monsoon Experiment (ARMEX)

Before the onset of the south Asian summer monsoon, sea surface temperature (SST) of the north Indian Ocean warms to 30–32°C. Climatological mean mixed layer depth in spring (March–May) is 10–20 m, and net surface heat flux (Q net ) is 80–100 W m−2 into the ocean. Previous work suggests that observed spring SST warming is small mainly because of (1) penetrative flux of solar radiation through the base of the mixed layer (Q pen ) and (2) advective cooling by upper ocean currents. We estimate the role of these two processes in SST evolution from a two-week Arabian Sea Monsoon Experiment process experiment in April–May 2005 in the southeastern Arabian Sea. The upper ocean is stratified by salinity and temperature, and mixed layer depth is shallow (6 to 12 m). Current speed at 2 m depth is high even under light winds. Currents within the mixed layer are quite distinct from those at 25 m. On subseasonal scales, SST warming is followed by rapid cooling, although the ocean gains heat at the surface: Q net is about 105 W m−2 in the warming phase and 25 W m−2 in the cooling phase; penetrative loss Q pen is 80 W m−2 and 70 W m−2. In the warming phase, SST rises mainly because of heat absorbed within the mixed layer, i.e., Q net minus Q pen ; Q pen reduces the rate of SST warming by a factor of 3. In the second phase, SST cools rapidly because (1) Q pen is larger than Q net and (2) advective cooling is ∼85 W m−2. A calculation using time-averaged heat fluxes and mixed layer depth suggests that diurnal variability of fluxes and upper ocean stratification tends to warm SST on subseasonal timescale. Buoy and satellite data suggest that a typical premonsoon intraseasonal cooling event occurs under clear skies when the ocean is gaining heat through the surface. In this respect, premonsoon SST cooling in the north Indian Ocean is different from that due to the Madden-Julian oscillation or monsoon intraseasonal oscillation.

Data assimilation using ensemble transform Kalman filter (ETKF) in ROMS model for Indian Ocean

Study of Oceans dynamics and forecast is crucial as it influences the regional climate and other marine activities. Forecasting oceanographic states like sea surface currents, Sea surface temperature (SST) and mixed layer depth at different time scales is extremely important for these activities. These forecasts are generated by various ocean general circulation models (OGCM). One such model is the Regional Ocean Modelling System (ROMS). Though ROMS can simulate several features of ocean, it cannot reproduce the thermocline of the ocean properly. Solution to this problem is to incorporates data assimilation (DA) in the model. DA system using Ensemble Transform Kalman Filter (ETKF) has been developed for ROMS model to improve the accuracy of the model forecast. To assimilate data temperature and salinity from ARGO data has been used as observation. Assimilated temperature and salinity without localization shows oscillations compared to the model run without assimilation for India Ocean. Same was also found for u and v-velocity fields. With localization we found that the state variables are diverging within the localization scale.

Development of a regional model for the North Indian Ocean

We have developed a one-way nested Indian Ocean regional model. The model combines the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory's (GFDL) Modular Ocean Model (MOM4p1) at global climate model resolution (nominally one degree), and a regional Indian Ocean MOM4p1 configuration with 25 km horizontal resolution and 1 m vertical resolution near the surface. Inter-annual global simulations with Coordinated Ocean-Ice Reference Experiments (CORE-II) surface forcing over years 1992-2005 provide surface boundary conditions. We show that relative to the global simulation, (i) biases in upper ocean temperature, salinity and mixed layer depth are reduced, (ii) sea surface height and upper ocean circulation are closer to observations, and (iii) improvements in model simulation can be attributed to refined resolution, more realistic topography and inclusion of seasonal river runoff. Notably, the surface salinity bias is reduced to less than 0.1 psu over the Bay of Bengal using relatively weak restoring to observations, and the model simulates the strong, shallow halocline often observed in the North Bay of Bengal. There is marked improvement in subsurface salinity and temperature, as well as mixed layer depth in the Bay of Bengal. Major seasonal signatures in observed sea surface height anomaly in the tropical Indian Ocean, including the coastal waveguide around the Indian peninsula, are simulated with great fidelity. The use of realistic topography and seasonal river runoff brings the three dimensional structure of the East India Coastal Current and West India Coastal Current much closer to observations. As a result, the incursion of low salinity Bay of Bengal water into the southeastern Arabian Sea is more realistic. (C) 2013 Elsevier Ltd. All rights reserved.

Impact of diurnal forcing on intraseasonal sea surface temperature oscillations in the Bay of Bengal

The diurnal cycle is an important mode of sea surface temperature (SST) variability in tropical oceans, influencing air-sea interaction and climate variability. Upper ocean mixing mechanisms are significant at diurnal time scales controlling the intraseasonal variability (ISV) of SST. Sensitivity experiments using an Ocean General Circulation Model (OGCM) for the summer monsoon of the year 2007 show that incorporation of diurnal cycle in the model atmospheric forcings improves the SST simulation at both intraseasonal and shorter time scales in the Bay of Bengal (BoB). The increase in SST-ISV amplitudes with diurnal forcing is approximate to 0.05 degrees C in the southern bay while it is approximate to 0.02 degrees C in the northern bay. Increased intraseasonal warming with diurnal forcing results from the increase in mixed layer heat gain from insolation, due to shoaling of the daytime mixed layer. Amplified intraseasonal cooling is dominantly controlled by the strengthening of subsurface processes owing to the nocturnal deepening of mixed layer. In the southern bay, intraseasonal variability is mainly determined by the diurnal cycle in insolation, while in the northern bay, diurnal cycle in insolation and winds have comparable contributions. Temperature inversions (TI) develop in the northern bay in the absence of diurnal variability in wind stress. In the northern bay, SST-ISV amplification is not as large as that in the southern bay due to the weaker diurnal variability of mixed layer depth (MLD) limited by salinity stratification. Diurnal variability of model MLD is not sufficient to create large modifications in mixed layer heat budget and SST-ISV in the northern bay.

Seasonal Climatologies and Variability of Eastern Tropical Pacific Surface Waters

Interannual variability caused by the El Nino-Southern Oscillation in the eastern tropical Pacific Ocean (ETP) is analogous to seasonal variability of comparable magnitude. Climatological spatial patterns and seasonal variability of physical variables that may affect the ETP ecosystem are presented and discussed. Surface temperature, surface salinity, mixed layer depth, thermocline depth, thermocline strength, and surface dynamic height were derived from bathythermograph, hydrocast, and CTD data. Surface current velocity, divergence, and upwelling velocity were derived from ship drift reports. Surface wind velocity, wind stress, wind divergence, wind stress curl, and Ekman pumping velocity were derived from gridded pseudostress data obtained from Florida State University. Seasonal maps of these variables, and their deviations from the annual mean, show different patterns of variation in Equatorial (S°S-SON) and Tropical Surface Water (SOlS0N). Seasonal shifts in the trade winds, which affect the strength of equatorial upwelling and the North Equatorial Countercurrent, cause seasonal variations in most variables. Seasonal and interannual variability of surface temperature, mixed layer depth, thermocline depth and wind stress were quantified. Surface temperature, mixed layer depth and thermocline depth, but not local wind stress, are less variable in Tropical Surface Water than in Equatorial Surface Water. Seasonal and interannual variability are close to equal in most of the ETP, within factors of 2 or less. (PDF file contains 70 pages.)

Changes in phytoplankton communities and primary production

Lake Victoria is the second largest lake in the world (69000km2) by surface area, but it is the shallowest (69m maximum depth) of the African Great Lakes. It is situated across the equator at an altitude of 1240m and lies in a shallow basin between two uplifted ridges of the eastern and western rift valleys (Beadle 1974). Despite their tropical locations, African lakes exhibit considerable seasonality related to the alteration of warm, wet and cool, dry seasons and the accompanying changes in lucustrine stratification and mixing (Tailing, 1965; 1966; Melack 1979; Hecky& Fee 1981; Hecky& Kling,1981; 1987; Bootsma 1993; Mugidde 1992; 1993). Phytoplankton productivity, biomass and species composition change seasonally in response to variations in light environment and nutrient availability which accompany changes in mixed layer depth and erosion or stabilization of the metalimnion / hypolimnion (Spigel & Coulter 1996; Hecky et al., 1991; Tailing 1987). Over longer, millennial time scales, the phytoplankton communities of the African Great Lakes have responded to variability in the EastAfrican climate (Johnson 1996; Haberyan& Hecky, 1986) which also alters the same ecological factors (Kilham et al., 1986). Recently, over the last few decades, changes in external and or internal factors in Lake Victoria and its basin have had a profound inlluence on the planktic community of this lake (Hecky, 1993; Lipiatou et al., 1996). The lake has experienced 2-10x increases in chlorophyll and 2x increase in primary productivity since Tailing's observations in the early 1960s (Mugidde 1992, 1993). In addition to observed changes in the lake nutrient chemistry (Hecky & Mungoma, 1990; Hecky & Bugenyi 1992; Hecky 1993; Bootsma & Hecky 1993), the deep waters previouslyoxygenated to the sediment surface through most of the year are now regularly anoxic(Hecky et al., 1994).