Processes and boreal summer impacts of the 2004 El Nino Modoki: An AGCM study

The sea surface temperature anomalies (SSTA) of tropical Pacific in the boreal summer of 2004 show a distinct tripolar pattern with warm SSTA in the central tropical Pacific, flanked on both sides by cold SSTA. The distinct conditions during the boreal summer of 2004 and the following winter were catalogued as a new coupled phenomenon named El Niño Modoki in a recent generalized study. The 2004 event is unique in the sense that it occurred without any co-occurring IOD, thereby without any possibility of external modulation of its processes and impacts in the tropics. Using observed data since 1979, we show that the 2004 event indeed involves the distinct equatorial coupled ocean-atmosphere dynamics different from the conventional El Niño. Further, using an AGCM, we confirm that during boreal summer anomalous twin Walker circulation cells associated with the El Niño Modoki SSTA give rise to observed rainfall anomalies in the tropic

Indian Ocean Dipole drives malaria resurgence in East African highlands

Malaria resurgence in African highlands in the 1990s has raised questions about the underlying drivers of the increase in disease incidence including the role of El-Niño-Southern Oscillation (ENSO). However, climatic anomalies other than the ENSO are clearly associated with malaria outbreaks in the highlands. Here we show that the Indian Ocean Dipole (IOD), a coupled ocean-atmosphere interaction in the Indian Ocean, affected highland malaria re-emergence. Using cross-wavelet coherence analysis, we found four-year long coherent cycles between the malaria time series and the dipole mode index (DMI) in the 1990s in three highland localities. Conversely, we found a less pronounced coherence between malaria and DMI in lowland localities. The highland/lowland contrast can be explained by the effects of mesoscale systems generated by Lake Victoria on its climate basin. Our results support the need to consider IOD as a driving force in the resurgence of malaria in the East African highlands

Closing the sea surface mixed layer temperature budget from in situ observations alone: Operation Advection during BoBBLE

Sea surface temperature (SST) is a fundamental driver of tropical weather systems such as monsoon rainfall and tropical cyclones. However, understanding of the factors that control SST variability is lacking, especially during the monsoons when in situ observations are sparse. Here we use a ground-breaking observational approach to determine the controls on the SST variability in the southern Bay of Bengal. We achieve this through the first full closure of the ocean mixed layer energy budget derived entirely from in situ observations during the Bay of Bengal Boundary Layer Experiment (BoBBLE). Locally measured horizontal advection and entrainment contribute more significantly than expected to SST evolution and thus oceanic variability during the observation period. These processes are poorly resolved by state-of-the-art climate models, which may contribute to poor representation of monsoon rainfall variability. The novel techniques presented here provide a blueprint for future observational experiments to quantify the mixed layer heat budget on longer time scales and to evaluate these processes in models

Future changes in tropical cyclone activity in the North Indian Ocean projected by high-resolution MRI-AGCMs

Open Access at publisher's web site: http://www.springerlink.com/content/b682734237171631

Decadal changes of the Western Arabian sea ecosystem

Historical data from oceanographic expeditions and remotely sensed data on outgoing longwave radiation, temperature, wind speed and ocean color in the western Arabian Sea (1950–2010) were used to investigate decadal trends in the physical and biochemical properties of the upper 300 m. 72 % of the 29,043 vertical profiles retrieved originated from USA and UK expeditions. Increasing outgoing longwave radiation, surface air temperatures and sea surface temperature were identified on decadal timescales. These were well correlated with decreasing wind speeds associated with a reduced Siberian High atmospheric anomaly. Shoaling of the oxycline and nitracline was observed as well as acidification of the upper 300 m. These physical and chemical changes were accompanied by declining chlorophyll-a concentrations, vertical macrofaunal habitat compression, declining sardine landings and an increase of fish kill incidents along the Omani coast

Impacts of El Niño Southern Oscillation and Indian Ocean Dipole on dengue incidence in Bangladesh

Dengue dynamics are driven by complex interactions between hosts, vectors and viruses that are influenced by environmental and climatic factors. Several studies examined the role of El Niño Southern Oscillation (ENSO) in dengue incidence. However, the role of Indian Ocean Dipole (IOD), a coupled ocean atmosphere phenomenon in the Indian Ocean, which controls the summer monsoon rainfall in the Indian region, remains unexplored. Here, we examined the effects of ENSO and IOD on dengue incidence in Bangladesh. According to the wavelet coherence analysis, there was a very weak association between ENSO, IOD and dengue incidence, but a highly significant coherence between dengue incidence and local climate variables (temperature and rainfall). However, a distributed lag nonlinear model (DLNM) revealed that the association between dengue incidence and ENSO or IOD were comparatively stronger after adjustment for local climate variables, seasonality and trend. The estimated effects were nonlinear for both ENSO and IOD with higher relative risks at higher ENSO and IOD. The weak association between ENSO, IOD and dengue incidence might be driven by the stronger effects of local climate variables such as temperature and rainfall. Further research is required to disentangle these effects

A recipe for simulating the interannual variability of the Asian summer monsoon and its relation with ENSO

Author Posting. © The Authors, 2006. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Climate Dynamics 28 (2007): 441-460, doi: 10.1007/s00382-006-0190-0.This study investigates how accurately the interannual variability over the Indian Ocean basin and the relationship between the Indian summer monsoon and the El Nino Southern Oscillation (ENSO) can be simulated by different modelling strategies. With a hierarchy of models, from an atmospherical general circulation model (AGCM) forced by observed SST, to a coupled model with the ocean component limited to the tropical Pacific and Indian Oceans, the role of heat fluxes and of interactive coupling is analyzed. Whenever sea surface temperature anomalies in the Indian basin are created by the coupled model, the inverse relationship between the ENSO index and the Indian summer monsoon rainfall is recovered, and it is preserved if the atmospherical model is forced by the SSTs created by the coupled model. If the ocean model domain is limited to the Indian Ocean, changes in the Walker circulation over the Pacific during El Nino years induce a decrease of rainfall over the Indian subcontinent. However the observed correlation between the ENSO and the Indian Ocean Zonal Mode (IOZM) is not properly modelled and the two indices are not significantly correlated, independently on season. Whenever the ocean domain extends to the Pacific, and ENSO can impact both the atmospheric circulation and the ocean subsurface in the equatorial Eastern Indian Ocean, modelled precipitation patterns associated both to ENSO and to the IOZM closely resemble the observations.The experiments described were performed as a contribution to the ENSEMBLES project funded by the European Commission’s 6th Framework Programme, contract number GOCE-CT-2003-505539

Multivariate Prediction of Total Water Storage Changes Over West Africa from Multi-Satellite Data

West African countries have been exposed to changes in rainfall patterns over the last decades, including a significant negative trend. This causes adverse effects on water resources of the region, for instance, reduced freshwater availability. Assessing and predicting large-scale total water storage (TWS) variations are necessary for West Africa, due to its environmental, social, and economical impacts. Hydrological models, however, may perform poorly over West Africa due to data scarcity. This study describes a new statistical, data-driven approach for predicting West African TWS changes from (past) gravity data obtained from the gravity recovery and climate experiment (GRACE), and (concurrent) rainfall data from the tropical rainfall measuring mission (TRMM) and sea surface temperature (SST) data over the Atlantic, Pacific, and Indian Oceans. The proposed method, therefore, capitalizes on the availability of remotely sensed observations for predicting monthly TWS, a quantity which is hard to observe in the field but important for measuring regional energy balance, as well as for agricultural, and water resource management.Major teleconnections within these data sets were identified using independent component analysis and linked via low-degree autoregressive models to build a predictive framework. After a learning phase of 72 months, our approach predicted TWS from rainfall and SST data alone that fitted to the observed GRACE-TWS better than that from a global hydrological model. Our results indicated a fit of 79 % and 67 % for the first-year prediction of the two dominant annual and inter-annual modes of TWS variations. This fit reduces to 62 % and 57 % for the second year of projection. The proposed approach, therefore, represents strong potential to predict the TWS over West Africa up to 2 years. It also has the potential to bridge the present GRACE data gaps of 1 month about each 162days as well as a—hopefully—limited gap between GRACE and the GRACE follow-on mission over West Africa. The method presented could also be used to generate a near real-time GRACE forecast over the regions that exhibit strong teleconnections

Tendencies, variability and persistence of sea surface temperature anomalies

Quantifying global trends and variability in sea surface temperature (SST) is of fundamental importance to understanding changes in the Earth’s climate. One approach to observing SST is via remote sensing. Here we use a 37-year gap-filled, daily-mean analysis of satellite SSTs to quantify SST trends, variability and persistence between 1981-2018. The global mean warming trend is 0.08 K per decade globally, with 95 % of local trends being between -0.1 K and +0.35 K. Excluding perennial sea-ice regions, the mean warming trend is 0.11 K per decade. After removing the long-term trend we calculate the SST power spectra over different time periods. The maximum variance in the SST power spectra in the equatorial Pacific is 1.9 K2 on 1-5 year timescales, dominated by ENSO processes. In western boundary currents characterised by an intense mesoscale activity, SST power on sub-annual timescales dominates, with a maximum variance of 4.9 K2. Persistence timescales tend to be shorter in the summer hemisphere due to the shallower mixed layer. The median short-term persistence length is 11-14 days, found over 71-79 % of the global ocean area, with seasonal variations. The mean global correlation between monthly SST anomalies with a three-month time-lag is 0.35, with statistically significant correlations over 54.0 % of the global oceans, and notably in the northern and equatorial Pacific, and the sub-polar gyre south of Greenland. At six months, the mean global SST anomaly correlation falls to 0.18. The satellite data record enables the detailed characterisation of temporal changes in SST over almost four decades