scholarly journals The Effects of External Forcing and Internal Variability on the Formation of Interhemispheric Sea Surface Temperature Gradient Trends in the Indian Ocean

2017 ◽  
Vol 30 (22) ◽  
pp. 9077-9095 ◽  
Author(s):  
Lu Dong ◽  
Michael J. McPhaden
Keyword(s):  
Indian Ocean ◽  
Climate Models ◽  
Climate Model ◽  
Dominant Role ◽  
Surface Wind ◽  
Internal Variability ◽  
Sea Surface ◽  
External Forcing ◽  
Anthropogenic Aerosol ◽  
The Indian Ocean

Abstract A striking trend of the Indian Ocean interhemispheric gradient in sea surface temperatures (SSTs) developed during the recent global warming hiatus. The contributions of external forcing and internal variability to this trend are examined in forced climate model experiments. Results indicate that the observed negative trend was strong by historical standards and most likely due to internal variability rather than to external forcing. Anthropogenic aerosol forcing favors negative gradient trends, but its effects are countered by greenhouse gas forcing, and both are weak relative to internal variability. The observed interhemispheric gradient trend occurred in parallel with a negative phase of the interdecadal Pacific oscillation (IPO), a linkage that is also found in climate models. However, the physical mechanisms responsible for these gradient trends in models differ from those in ocean reanalysis products. In particular, oceanic processes via an increased Indonesian Throughflow (ITF) transport into the Indian Ocean forced by stronger Pacific trade winds are the principal cause of the observed negative SST gradient trend during 2000–13. In contrast, atmospheric processes via changing surface wind stress over the southern Indian Ocean remotely forced by the IPO appear to play a dominant role in changing the interhemispheric SST gradients in climate models. The models underestimate the magnitude of the IPO and produce changes in the ITF that are too weak owing to their coarse spatial resolution. These model deficiencies may account for the differences between the simulations and observations.

scholarly journals Why Has the Relationship between Indian and Pacific Ocean Decadal Variability Changed in Recent Decades?

2017 ◽  
Vol 30 (6) ◽  
pp. 1971-1983 ◽  
Author(s):  
Lu Dong ◽  
Michael J. McPhaden
Keyword(s):  
Pacific Ocean ◽  
Indian Ocean ◽  
Climate Models ◽  
Climate Model ◽  
Decadal Variability ◽  
Negative Phase ◽  
External Forcing ◽  
Indian Ocean Basin Mode ◽  
The Indian Ocean ◽  
The Relationship

Abstract Both the Indian and Pacific Oceans exhibit prominent decadal time scale variations in sea surface temperature (SST), linked dynamically via atmospheric and oceanic processes. However, the relationship between SST in these two basins underwent a dramatic transformation beginning around 1985. Prior to that, SST variations associated with the Indian Ocean basin mode (IOB) and the interdecadal Pacific oscillation (IPO) were positively correlated, whereas afterward they were much less clearly synchronized. Evidence is presented from both observations and coupled state-of-the-art climate models that enhanced external forcing, particularly from increased anthropogenic greenhouse gases, was the principal cause of this changed relationship. Using coupled climate model experiments, it is shown that without external forcing, the evolution of the IOB would be strongly forced by variations in the IPO. However, with strong external forcing, the dynamical linkage between the IOB and the IPO weakens so that the negative phase IPO after 2000 is unable to force a negative phase IOB-induced cooling of the Indian Ocean. This changed relationship in the IOB and IPO led to unique SST patterns in the Indo-Pacific region after 2000, which favored exceptionally strong easterly trade winds over the tropical Pacific Ocean and a pronounced global warming hiatus in the first decade of the twenty-first century.

scholarly journals Improving the simulation of global aerosol with size-segregated anthropogenic number emissions

2017 ◽  
Author(s):  
Filippo Xausa ◽  
Pauli Paasonen ◽  
Risto Makkonen ◽  
Mikhail Arshinov ◽  
Aijun Ding ◽  
...  
Keyword(s):  
Particle Number ◽  
Climate Models ◽  
Climate Model ◽  
Dominant Role ◽  
Particle Diameter ◽  
Radiation Budget ◽  
Size Distributions ◽  
Anthropogenic Aerosol ◽  
Accumulation Mode ◽  
Climate Interactions

Abstract. Climate models are important tools that are used for generating climate change projections, in which aerosol-climate interactions are one of the main sources of uncertainties. In order to quantify aerosol-radiation and aerosol-cloud interactions, detailed input of anthropogenic aerosol number emissions is necessary. However, the anthropogenic aerosol number emissions are usually converted from the corresponding mass emissions in precompiled emission inventories through a very simplistic method depending uniquely on chemical composition, particle size and density, which are defined for a few very wide main source sectors. In this work, the anthropogenic particle number emissions converted from the AeroCom mass in the ECHAM-HAM climate model were replaced with the recently-formulated number emissions from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS)-model, where the emission number size distributions vary, for example, with respect to the fuel and technology. A special attention in our analysis was put on accumulation mode particles (particle diameter dp > 100 nm) because of (i) their capability of acting as cloud condensation nuclei (CCN), thus forming cloud droplets and affecting Earth's radiation budget, and (ii) their dominant role in forming the coagulation sink and thus limiting the concentration of sub-100 nanometers particles. In addition, the estimates of anthropogenic CCN formation, and thus the forcing from aerosol-climate interactions are expected to be affected. Analysis of global particle number concentrations and size distributions reveal that GAINS implementation increases CCN concentration compared with AeroCom, with regional enhancement factors reaching values as high as 10. A comparison between modeled and observed concentrations shows that the increase in number concentration for accumulation mode particle agrees well with measurements, but it leads to a consistent underestimation of both nucleation mode and Aitken mode (dp > 100 nm) particle number concentrations. This suggests that revisions are needed in the new particle formation and growth schemes currently applied in global modeling frameworks.

scholarly journals Seasonality and Predictability of the Indian Ocean Dipole Mode: ENSO Forcing and Internal Variability

2015 ◽  
Vol 28 (20) ◽  
pp. 8021-8036 ◽  
Author(s):  
Yun Yang ◽  
Shang-Ping Xie ◽  
Lixin Wu ◽  
Yu Kosaka ◽  
Ngar-Cheung Lau ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Internal Variability ◽  
Forced Response ◽  
Sea Surface ◽  
Boreal Summer ◽  
Destructive Interference ◽  
Indian Ocean Basin Mode ◽  
Indian Ocean Dipole Mode ◽  
The Indian Ocean

Abstract This study evaluates the relative contributions to the Indian Ocean dipole (IOD) mode of interannual variability from the El Niño–Southern Oscillation (ENSO) forcing and ocean–atmosphere feedbacks internal to the Indian Ocean. The ENSO forcing and internal variability is extracted by conducting a 10-member coupled simulation for 1950–2012 where sea surface temperature (SST) is restored to the observed anomalies over the tropical Pacific but interactive with the atmosphere over the rest of the World Ocean. In these experiments, the ensemble mean is due to ENSO forcing and the intermember difference arises from internal variability of the climate system independent of ENSO. These elements contribute one-third and two-thirds of the total IOD variance, respectively. Both types of IOD variability develop into an east–west dipole pattern because of Bjerknes feedback and peak in September–November. The ENSO forced and internal IOD modes differ in several important ways. The forced IOD mode develops in August with a broad meridional pattern and eventually evolves into the Indian Ocean basin mode, while the internal IOD mode grows earlier in June, is more confined to the equator, and decays rapidly after October. The internal IOD mode is more skewed than the ENSO forced response. The destructive interference of ENSO forcing and internal variability can explain early terminating IOD events, referred to as IOD-like perturbations that fail to grow during boreal summer. The results have implications for predictability. Internal variability, as represented by preseason sea surface height anomalies off Sumatra, contributes to predictability considerably. Including this indicator of internal variability, together with ENSO, improves the predictability of IOD.

scholarly journals Indian Ocean Dipolelike Variability in the CSIRO Mark 3 Coupled Climate Model

2005 ◽  
Vol 18 (10) ◽  
pp. 1449-1468 ◽  
Author(s):  
Wenju Cai ◽  
Harry H. Hendon ◽  
Gary Meyers
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
Climate Models ◽  
Rossby Waves ◽  
Climate Model ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface

Abstract Coupled ocean–atmosphere variability in the tropical Indian Ocean is explored with a multicentury integration of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 3 climate model, which runs without flux adjustment. Despite the presence of some common deficiencies in this type of coupled model, zonal dipolelike variability is produced. During July through November, the dominant mode of variability of sea surface temperature resembles the observed zonal dipole and has out-of-phase rainfall variations across the Indian Ocean basin, which are as large as those associated with the model El Niño–Southern Oscillation (ENSO). In the positive dipole phase, cold SST anomaly and suppressed rainfall south of the equator on the Sumatra–Java coast drives an anticyclonic circulation anomaly that is consistent with the steady response (Gill model) to a heat sink displaced south of the equator. The northwest–southeast tilting Sumatra–Java coast results in cold sea surface temperature (SST) centered south of the equator, which forces anticylonic winds that are southeasterly along the coast, which thus produces local upwelling, cool SSTs, and promotes more anticylonic winds; on the equator, the easterlies raise the thermocline to the east via upwelling Kelvin waves and deepen the off-equatorial thermocline to the west via off-equatorial downwelling Rossby waves. The model dipole mode exhibits little contemporaneous relationship with the model ENSO; however, this does not imply that it is independent of ENSO. The model dipole often (but not always) develops in the year following El Niño. It is triggered by an unrealistic transmission of the model’s ENSO discharge phase through the Indonesian passages. In the model, the ENSO discharge Rossby waves arrive at the Sumatra–Java coast some 6 to 9 months after an El Niño peaks, causing the majority of model dipole events to peak in the year after an ENSO warm event. In the observed ENSO discharge, Rossby waves arrive at the Australian northwest coast. Thus the model Indian Ocean dipolelike variability is triggered by an unrealistic mechanism. The result highlights the importance of properly representing the transmission of Pacific Rossby waves and Indonesian throughflow in the complex topography of the Indonesian region in coupled climate models.

scholarly journals CORRELATION AND COHERENCE ANALYSIS OF SEA SURFACE TEMPERATURE (SST) DISTRIBUTED BY THE SURFACE WIND IN WEST SUMATERA WATERS

2019 ◽  
Vol 19 (2) ◽  
pp. 81
Author(s):  
Ulung Jantama Wisha ◽  
Rahaden Bagas Hatmaja ◽  
Ivonne Milichristi Radjawane ◽  
Try Al Tanto
Keyword(s):  
Wind Speed ◽  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Sea Surface ◽  
Wavelet Coherence ◽  
Dipole Mode ◽  
The Indian Ocean ◽  
Cross Wavelet

<p class="Section">West Sumatera Waters have a tremendous dynamic in ocean characteristics. It directly faces the Indian Ocean exactly located below the equator. Consequently, West Sumatera waters are influenced by the tropical climatic factors such as monsoons, climate variability, and the Indian Ocean Dipole (IOD), controlling sea surface temperature (SST) fluctuation in the Indian Ocean. This study aims to review the correlation and coherence of SST distributed by surface wind in the West Sumatera waters. Wavelet method (cross wavelet transforms and wavelet coherence) was used to analyze the correlation and coherency between SST and surface wind. The annual variation of SST for 365 days period is the strongest event throughout the year caused by either monsoon or the changes of wind speed in the surface. Otherwise, the strongest intra-seasonal SST variation of 35 - 60 days observed from December 2012 to March 2013. The highest surface wind speed occurs in the southern and western waters. During the positive dipole mode in October 2015, the surface wind speed is slightly high resulting in the SST declination. Nevertheless, during the negative dipole mode in July 2016, the condition is inversely proportional. The surface wind plays a role in the SST distribution of 35 - 60 days period (intra-seasonal variability). Besides, surface wind with 6 months period (semi-annual variability) influences the SST distribution, identified only in the southern waters and the Indian Ocean regions. These conditions predicted as the influence of monsoon.</p><p class="Section"> </p><p class="Section"><em>Sumatera Barat merupakan wilayah perairan yang stategis dimana secara langsung berhadapan dengan Samudera Hindia dan tepat berada pada dibawah Garis Katulistiwa. Oleh karena itu, Perairan Sumatera Barat dipengaruhi oleh faktor-faktor iklim tropis seperti monsun dan variabilitas iklim, sangat terkait dengan Indian Ocean Dipole (IOD) yang mengendalikan fluktuasi suhu permukaan laut (SPL) di Samudera Hindia. Tujuan dari penelitian ini adalah menelaah korelasi dan koherensi antara parameter SPL dan komponen kecepatan angin </em> <em> di perairan Sumatera Barat. Metode wavelet (cross wavelet transform dan wavelet coherence) digunakan untuk menganalisa korelasi dan koherensi dari kedua parameter yang diuji. Variasi tahunan dari SPL pada periode 365 hari merupakan kejadian terkuat sepanjang tahun yang disebabkan oleh monsun atau perubahan pengaruh angin dipermukaan. Sebaliknya, variasi musiman terkuat dari SPL pada periode 35-60 hari ditemukan terjadi pada bulan Desember 2012 hingga Maret 2013. Kecepatan angin tertinggi terjadi di perairan selatan dan barat. Selama dipole mode positif pada bulan Oktober 2015, kecepatan angin permukaan sedikit meningkat yang mengakibatkan penurunan suhu perairan. Namun, selama dipole mode negatif pada bulan Juli 2016, kondisinya berbanding terbalik. Angin permukaan memainkan peran pada peningkatan distribusi suhu permukaan laut pada periode 35-60 hari (variabilistas musiman). Selain itu, angin permukaan dengan periode 6 bulan (tengah tahunan) sangat mempengaruhi distribusi suhu yang teridentifikasi pada wilayah selatan dan Samudera Hindia. Kondisi tersebut diperkirakan sebagai pengaruh dari monsun.</em></p>

scholarly journals Customization and Validation of a Regional Climate Model Using Satellite Data Over East Africa

Atmosphere ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 317
Author(s):  
Masilin Gudoshava ◽  
Fredrick H. M. Semazzi
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
East Africa ◽  
Climate Model ◽  
Lake Victoria ◽  
Regional Climate ◽  
Sea Surface ◽  
Modes Of Variability ◽  
The Indian Ocean ◽  
Short Rains

This study focused on the customization of the fourth generation International Center for Theoretical Physics Regional Climate Model version 4.4 and its ability to reproduce the mean climate and most dominant modes of variability over East Africa. The simulations were performed at a spatial resolution of 25 km for the period 1998–2013. The model was driven by ERA-Interim reanalysis. The customization focus was on cumulus and microphysics schemes during the Short Rains for the year 2000. The best physics combinations were then utilized for the validation studies. The East Africa region and Lake Victoria Basin region are adapted to carry out empirical orthogonal function analysis, during the Short and Long Rains. Tropical Rainfall Measuring Mission data was utilized in the validation of the model. The first mode of variability from the model and observational data during the Short Rains was associated with the warming of the Pacific Ocean and the sea surface temperature gradients over the Indian Ocean. During the Long rains, the inter-annual rainfall variability over the Lake Victoria region was associated with the sea surface temperature anomaly over the Indian Ocean and for the East Africa region the associations were weak. The drivers during the Long Rains over East Africa region were then further investigated by splitting the season to the March–April and May periods. The March–April period was positively correlated to the West Pacific and Indian Ocean dipole index, while May was associated with the Quasi-Biennial Oscillation. In conclusion, although the model can reproduce the dominant modes of variability as in the observational data sets during the Short Rains, skill was lower during the Long Rains.

scholarly journals On Tanzania’s Precipitation Climatology, Variability, and Future Projection

Climate ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 34
Author(s):  
Krishna Borhara ◽  
Binod Pokharel ◽  
Brennan Bean ◽  
Liping Deng ◽  
S.-Y. Simon Wang
Keyword(s):  
Indian Ocean ◽  
Rainy Season ◽  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Precipitation Trend ◽  
Central Pacific ◽  
Maximum Rainfall ◽  
The Indian Ocean ◽  
Increasing Precipitation

We investigate historical and projected precipitation in Tanzania using observational and climate model data. Precipitation in Tanzania is highly variable in both space and time due to topographical variations, coastal influences, and the presence of lakes. Annual and seasonal precipitation trend analyses from 1961 to 2016 show maximum rainfall decline in Tanzania during the long rainy season in the fall (March–May), and an increasing precipitation trend in northwestern Tanzania during the short rainy season in the spring (September–November). Empirical orthogonal function (EOF) analysis applied to Tanzania’s precipitation patterns shows a stronger correlation with warmer temperatures in the western Indian Ocean than with the eastern-central Pacific Ocean. Years with decreasing precipitation in Tanzania appear to correspond with increasing sea surface temperatures (SST) in the Indian Ocean, suggesting that the Indian Ocean Dipole (IOD) may have a greater effect on rainfall variability in Tanzania than the El Niño-Southern Oscillation (ENSO) does. Overall, the climate model ensemble projects increasing precipitation trend in Tanzania that is opposite with the historical decrease in precipitation. This observed drying trend also contradicts a slightly increasing precipitation trend from climate models for the same historical time period, reflecting challenges faced by modern climate models in representing Tanzania’s precipitation.

scholarly journals Two Independent Triggers for the Indian Ocean Dipole/Zonal Mode in a Coupled GCM

2005 ◽  
Vol 18 (17) ◽  
pp. 3428-3449 ◽  
Author(s):  
Albert S. Fischer ◽  
Pascal Terray ◽  
Eric Guilyardi ◽  
Silvio Gualdi ◽  
Pascale Delecluse
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
Indian Ocean Dipole ◽  
El Nino ◽  
Tropical Indian Ocean ◽  
Sea Surface ◽  
Dynamical Response ◽  
Thermocline Depth ◽  
Second Phase ◽  
The Indian Ocean

Abstract The question of whether and how tropical Indian Ocean dipole or zonal mode (IOZM) interannual variability is independent of El Niño–Southern Oscillation (ENSO) variability in the Pacific is addressed in a comparison of twin 200-yr runs of a coupled climate model. The first is a reference simulation, and the second has ENSO-scale variability suppressed with a constraint on the tropical Pacific wind stress. The IOZM can exist in the model without ENSO, and the composite evolution of the main anomalies in the Indian Ocean in the two simulations is virtually identical. Its growth depends on a positive feedback between anomalous equatorial easterly winds, upwelling equatorial and coastal Kelvin waves reducing the thermocline depth and sea surface temperature off the coast of Sumatra, and the atmospheric dynamical response to the subsequently reduced convection. Two IOZM triggers in the boreal spring are found. The first is an anomalous Hadley circulation over the eastern tropical Indian Ocean and Maritime Continent, with an early northward penetration of the Southern Hemisphere southeasterly trades. This situation grows out of cooler sea surface temperatures in the southeastern tropical Indian Ocean left behind by a reinforcement of the late austral summer winds. The second trigger is a consequence of a zonal shift in the center of convection associated with a developing El Niño, a Walker cell anomaly. The first trigger is the only one present in the constrained simulation and is similar to the evolution of anomalies in 1994, when the IOZM occurred in the absence of a Pacific El Niño state. The presence of these two triggers—the first independent of ENSO and the second phase locking the IOZM to El Niño—allows an understanding of both the existence of IOZM events when Pacific conditions are neutral and the significant correlation between the IOZM and El Niño.

scholarly journals Evaluating the Uncertainty Induced by the Virtual Salt Flux Assumption in Climate Simulations and Future Projections

2010 ◽  
Vol 23 (1) ◽  
pp. 80-96 ◽  
Author(s):  
Jianjun Yin ◽  
Ronald J. Stouffer ◽  
Michael J. Spelman ◽  
Stephen M. Griffies
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Ocean Model ◽  
Salt Flux ◽  
Freshwater Flux ◽  
Unexpected Result ◽  
Geophysical Fluid Dynamics Laboratory ◽  
External Forcing ◽  
Future Evolution ◽  
Near Term

Abstract The unphysical virtual salt flux (VSF) formulation widely used in the ocean component of climate models has the potential to cause systematic and significant biases in modeling the climate system and projecting its future evolution. Here a freshwater flux (FWF) and a virtual salt flux version of the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1) are used to evaluate and quantify the uncertainties induced by the VSF formulation. Both unforced and forced runs with the two model versions are performed and compared in detail. It is found that the differences between the two versions are generally small or statistically insignificant in the unforced control runs and in the runs with a small external forcing. In response to a large external forcing, however, some biases in the VSF version become significant, especially the responses of regional salinity and global sea level. However, many fundamental aspects of the responses differ only quantitatively between the two versions. An unexpected result is the distinctly different ENSO responses. Under a strong external freshwater forcing, the great enhancement of the ENSO variability simulated by the FWF version does not occur in the VSF version and is caused by the overexpansion of the top model layer. In summary, the principle assumption behind using virtual salt flux is not seriously violated and the VSF model has the ability to simulate the current climate and project near-term climate evolution. For some special studies such as a large hosing experiment, however, both the VSF formulation and the use of the FWF in the geopotential coordinate ocean model could have some deficiencies and one should be cautious to avoid them.

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