The Indian Ocean SST Link to Solar Induced Chlorophyll Fluorescence Over India During Early Summer Monsoon

This is a maiden attempt to explore the influence of sea surface temperature (SST) variations in the tropical Indian Ocean on the gross primary productivity (GPP) of the terrestrial vegetation of India during the summer monsoon. We studied the productivity of the vegetation across India using solar-induced chlorophyll fluorescence (SIF) as a proxy. Our results demonstrated a strong negative SST–SIF relationship: the productivity decreases (increases) when the SST of the tropical Indian Ocean is higher (lower) than normal. This SST–SIF coupling observed during June can be explained through the atmospheric teleconnections. Positive SST anomalies weaken the land–ocean thermal gradient during the monsoon onset period, reduce the monsoon flow, and hence decrease the moisture transport from the ocean to the Indian mainland. The resultant water stress, along with the high air temperature, leads to a reduction in the GPP. Conversely, negative SST anomalies strengthen the monsoon and increase the availability of moisture for photosynthesis. There is scope for improving regional GPP forecasting studies using the observed SST–SIF relationships.

The influence of pacific winds on ENSO diversity

The differences in ENSO sea surface temperature (SST) spatial patterns, whether centered in the Eastern Pacific (EP), Central Pacific (CP) or in the eastern-central equatorial region (“canonical”) have been associated to differences in atmospheric teleconnections and global impacts. However, predicting different types of ENSO events has proved challenging, highlighting the need for a deeper understanding of their predictability. Given the key role played by wind variations in the development and evolution of ENSO events, this study examines the relationship between the leading modes of Pacific surface wind speed variability and ENSO diversity using three different state-of-the-art wind products, including satellite observations and atmospheric reanalyses. Although previous studies have associated different ENSO precursors to either EP or CP events, our results indicate that the most prominent of those ENSO precursors are primarily related to canonical and CP events, and show little correlation with EP events. The latter are associated with tropical Pacific conditions favoring equatorial westerly wind and precipitation anomalies that extend all the way to the eastern Pacific. Results over the entire twentieth century period versus those during the satellite era also suggest that the influences from the Southern Hemisphere may be more robust than those from the Northern Hemisphere.

Quantifying causal pathways of teleconnections

Teleconnections are sources of predictability for regional weather and climate but the relative contributions of different teleconnections to regional anomalies are usually not understood. While physical knowledge about the involved mechanisms is often available, how to quantify a particular causal pathway from data is usually unclear. Here we argue for adopting a causal inference-based framework in the statistical analysis of teleconnections to overcome this challenge. A causal approach requires explicitly including expert knowledge in the statistical analysis, which allows one to draw quantitative conclusions. We illustrate some of the key concepts of this theory with concrete examples of well-known atmospheric teleconnections. We further discuss the particular challenges and advantages these imply for climate science and argue that a systematic causal approach to statistical inference should become standard practice in the study of teleconnections.

Pacific Meridional Modes without Equatorial Pacific Influence

Investigating Pacific Meridional Modes (PMM) without the influence of tropical Pacific variability is technically difficult if based on observations or fully coupled model simulations due to their overlapping spatial structures. To confront this issue, the present study investigates both North (NPMM) and South PMM (SPMM) in terms of their associated atmospheric forcing and response processes based on a mechanically decoupled climate model simulation. In this experiment, the climatological wind stress is prescribed over the tropical Pacific, which effectively removes dynamically coupled tropical Pacific variability (e.g., the El Niño-Southern Oscillation). Interannual NPMM in this experiment is forced not only by the North Pacific Oscillation, but also by a North Pacific tripole (NPT) pattern of atmospheric internal variability, which primarily forces decadal NPMM variability. Interannual and decadal variability of the SPMM is partly forced by the South Pacific Oscillation. In turn, both interannual and decadal NPMM variability can excite atmospheric teleconnections over the Northern Hemisphere extratropics by influencing the meridional displacement of the climatological intertropical convergence zone throughout the whole year. Similarly, both interannual and decadal SPMM variability can also excite atmospheric teleconnections over the Southern Hemisphere extratropics by extending/shrinking the climatological South Pacific convergence zone in all seasons. Our results highlight a new poleward pathway by which both the NPMM and SPMM feed back to the extratropical climate, in addition to the equatorward influence on tropical Pacific variability.

Role of SST for the predictability of summer atmospheric teleconnections in the Euro-Atlantic region with Self-Organising Maps

<p>We investigate the seasonal predictability of the two dominant atmospheric teleconnections associated with the North Atlantic Jet: the Summer North Atlantic Oscillation (SNAO) and East Atlantic Pattern (EAP). We go beyond standard forecast practices by combining an ensemble predictions system with a machine learning approach. Specifically, we combine on the one hand a 30-member hindcast ensemble initialised every May between 1902 and 2008 in the Max Planck Institute Earth System Model in mixed resolution (MPI-ESM-MR), with on the other hand a neural network-based classifier Self-Organising Maps (SOM) in the ERA-20C reanalysis. We use the SOM to identify a sub-ensemble in which simulated North Atlantic sea surface temperatures (SST) at the initialisation of the prediction system (i.e. April) are linked to atmospheric modes.</p><p>While we find for summer climate at 3-4 months lead time only limited predictive skill in the ensemble mean of MPI-ESM-MR, we find significant predictive skill over many areas in the SOM-based sub-ensemble. Our results suggest that the predictive skill of European summer temperatures can be linked to the predictive skill of SNAO and EAP, which stems in turn from the – with skill predictable - temperature gradient between subpolar and subtropical gyres. We also demonstrate the predictive skill is time dependent, with high skill over the late half of the time series (1955 - 2008) and low skill in the early period (1902 - 1954).</p>

Hydrometeorological Variability and Its Nonstationarity According to the Evolution Pattern of Indian Ocean Dipole over the East Asia Region

In this study, we used statistical models to analyze nonlinear behavior links with atmospheric teleconnections between hydrometeorological variables and Indian Ocean Dipole (IOD) mode over the East Asia (EA) region. The analysis of atmospheric teleconnections was conducted using principal component analysis and singular spectrum analysis techniques. Moreover, the nonlinear lag-time correlations between climate indices and hydrological variables were calculated using mutual information (MI) techniques. The teleconnection-based nonlinear correlation coefficients (CCs) were higher than the linear CCs in each lag time. Additionally, we documented that the IOD has a direct influence on hydro-meteorological variables, such as precipitation within the Korean Peninsula (KP). Moreover, during the warm season (June to September) the variation of hydro-meteorological variables in the KP demonstrated significantly decreasing patterns during positive IOD years and they have neutral conditions during negative IOD years in comparison with long-term normal conditions. Finally, the revealed relationship between climate indices and hydro-meteorological variables and their possible changes will allow better understanding of stakeholder decision-making regarding to manage of freshwater management over the EA region. It can also provide useful data for long-range water resources prediction, to minimize hydrological uncertainties in a changing climate.