An analysis of monthly rainfall and the meteorological conditions associated with the deficient rainfall towards the end of 2017 southwest monsoon season

This paper studies the summer monsoon 2017 and examines the number of parameters which we believe were important in understanding why monsoon failed in second half over India. The list of parameters includes monthly mean or anomalies of the following fields : sea surface temperature, outgoing longwave radiation, stream function of lower and upper atmosphere, velocity potential and monthly and seasonal precipitation. ENSO conditions were mainly neutral with warm ENSO neutral conditions observed in the first half and cool ENSO neutral conditions observed in the second half. As a result, influence on the monsoon from the large scale SST forcing from Pacific Ocean was nearly absent during the season. However, Positive IOD conditions over the Indian Ocean during the monsoon season, particularly during first half of the monsoon were prominent. The transition of warmer than normal SSTs (June and July) to normal SSTs (August) and then becoming cooler than normal SSTs (September) in the equatorial Indian Ocean had a significant influence which lead monsoon to fail in second half.

Tropical Indo-Pacific SST influences on vegetation variability in eastern Africa

Mechanisms by which tropical Pacific and Indian Ocean sea surface temperatures (SST) influence vegetation in eastern Africa have not been fully explored. Here, we use a suite of idealized Earth system model simulations to elucidate the governing processes for eastern African interannual vegetation changes. Our analysis focuses on Tanzania. In the absence of ENSO-induced sea surface temperature anomalies in the Tropical Indian Ocean (TIO), El Niño causes during its peak phase negative precipitation anomalies over Tanzania due to a weakening of the tropical-wide Walker circulation and anomalous descending motion over the Indian Ocean and southeastern Africa. Resulting drought conditions increase the occurrence of wildfires, which leads to a marked decrease in vegetation cover. Subsequent wetter La Niña conditions in boreal winter reverse the phase in vegetation anomalies, causing a gradual 1-year-long recovery phase. The 2-year-long vegetation decline in Tanzania during an ENSO cycle can be explained as a double-integration of the local rainfall anomalies, which originate from the seasonally-modulated ENSO Pacific-SST forcing (Combination mode). In the presence of interannual TIO SST forcing, the southeast African precipitation and vegetation responses to ENSO are muted due to Indian Ocean warming and the resulting anomalous upward motion in the atmosphere.

Antarctic Peninsula warm winters influenced by Tasman Sea temperatures

The Antarctic Peninsula of West Antarctica was one of the most rapidly warming regions on the Earth during the second half of the 20th century. Changes in the atmospheric circulation associated with remote tropical climate variabilities have been considered as leading drivers of the change in surface conditions in the region. However, the impacts of climate variabilities over the mid-latitudes of the Southern Hemisphere on this Antarctic warming have yet to be quantified. Here, through observation analysis and model experiments, we reveal that increases in winter sea surface temperature (SST) in the Tasman Sea modify Southern Ocean storm tracks. This, in turn, induces warming over the Antarctic Peninsula via planetary waves triggered in the Tasman Sea. We show that atmospheric response to SST warming over the Tasman Sea, even in the absence of anomalous tropical SST forcing, deepens the Amundsen Sea Low, leading to warm advection over the Antarctic Peninsula.

Global Teleconnections to the Indian Summer Monsoon in CFSv2 model: Tropics vs. Midlatitude

<p><span xml:lang="EN-US" data-contrast="auto"><span>Traditionally, monsoon teleconnections are measured in terms of the strength of a simultaneous linear relationship. Such associative metrics do not quantify precipitation variations through physical parameters directly related to the moisture budget of the atmosphere. In this study, for the first time, we develop a linear model for the Indian summer monsoon rainfall (ISMR) based on surface pressure over regions surrounding it and sea surface temperature (SST) forcing from tropics and midlatitude. This surface pressure acts as a dynamical link between SST forcing and convective processes over the Indian region, which was missing in previous studies. We also use this novel approach to understand the ISMR prediction skill in the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). We find that the interannual variability of ISMR does not rely solely on tropical processes, but the </span></span><span xml:lang="EN-US" data-contrast="auto"><span>midlatitude </span></span><span xml:lang="EN-US" data-contrast="auto"><span>phenomenon also plays a crucial role in modulating it. The model, however, derived most of its variability from the ENSO mode. The </span></span><span xml:lang="EN-US" data-contrast="none"><span>understated</span></span><span xml:lang="EN-US" data-contrast="auto"><span> midlatitude forcing</span></span><span xml:lang="EN-US" data-contrast="auto"><span> in the model </span></span><span xml:lang="EN-US" data-contrast="auto"><span>can be attributed to</span></span><span xml:lang="EN-US" data-contrast="auto"><span> its</span></span><span xml:lang="EN-US" data-contrast="auto"><span> low prediction skill</span></span><span xml:lang="EN-US" data-contrast="auto"><span>.</span></span><span> </span></p>

Ocean fronts and eddies force atmospheric rivers and heavy precipitation in western North America

Atmospheric rivers (ARs) are responsible for over 90% of poleward water vapor transport in the mid-latitudes and can produce extreme precipitation when making landfall. However, weather and climate models still have difficulty simulating and predicting landfalling ARs and associated extreme precipitation, highlighting the need to better understand AR dynamics. Here, using high-resolution climate models and observations, we demonstrate that mesoscale sea-surface temperature (SST) anomalies along the Kuroshio Extension can exert a remote influence on landfalling ARs and related heavy precipitation along the west coast of North America. Inclusion of mesoscale SST forcing in the simulations results in approximately a 40% increase in landfalling ARs and up to a 30% increase in heavy precipitation in mountainous regions and this remote impact occurs on two-week time scales. The asymmetrical response of the atmosphere to warm vs. cold mesoscale SSTs over the eddy-rich Kuroshio Extension region is proposed as a forcing mechanism that results in a net increase of moisture flux above the planetary boundary layer, prompting AR genesis via enhancing moisture transport into extratropical cyclones in the presence of mesoscale SST forcing.

Tropical Drivers of Interannual Vegetation Variability in Eastern Africa

Mechanisms by which tropical Pacific and Indian Ocean sea surface temperatures influence vegetation in Eastern Africa and which role drought-induced fires play have not been fully explored. Here, we use a suite of idealized Earth system model simulations to elucidate the governing processes for eastern African interannual vegetation changes. Our analysis focuses on Tanzania. In the absence of ENSO-induced sea surface temperature (SST) anomalies in the Tropical Indian Ocean (TIO), El Niño causes during its peak phase negative precipitation anomalies over Tanzania due to a weakening of the tropical-wide Walker circulation and anomalous descending motion over the Indian Ocean and southeastern Africa. Resulting drought conditions increase the occurrence of wildfires, which leads to a marked decrease in vegetation cover. Subsequent wetter La Niña conditions in boreal winter reverse the trend in vegetation, causing a gradual 1-year-long recovery phase. The 2-year-long vegetation response in Tanzania can be explained as a double-integration of the local rainfall anomalies, which originate from the seasonally-modulated ENSO Pacific-SST forcing (Combination mode). In the presence of interannual TIO SST forcing, the southeast African precipitation and vegetation responses to ENSO are muted due to Indian Ocean warming and the resulting anomalous upward motion in the atmosphere.

A Linear Inverse Model of Tropical and South Pacific Climate Variability: Optimal Structure and Stochastic Forcing

A stochastically forced linear inverse model (LIM) of the combined modes of variability from the tropical and South Pacific Oceans is used to investigate the linear growth of optimal initial perturbations and to identify the spatiotemporal features of the stochastic forcing associated with the atmospheric Pacific–South American patterns 1 and 2 (PSA1 and PSA2). Optimal initial perturbations are shown to project onto El Niño–Southern Oscillation (ENSO) and South Pacific decadal oscillation (SPDO), where the inclusion of subsurface South Pacific Ocean temperature variability significantly increases the multiyear linear predictability of the deterministic system. We show that the optimal extratropical sea surface temperature (SST) precursor is associated with the South Pacific meridional mode, which takes from 7 to 9 months to linearly evolve into the final ENSO and SPDO peaks in both the observations and as simulated in an atmosphere-forced ocean model. The optimal subsurface precursor resembles its peak phase, but with a weak amplitude, representing oceanic Rossby waves in the extratropical South Pacific. The stochastic forcing is estimated as the residual by removing the deterministic dynamics from the actual tendency under a centered difference approximation. The resulting stochastic forcing time series satisfies the Gaussian white noise assumption of the LIM. We show that the PSA-like variability is strongly associated with stochastic SST forcing in the tropical and South Pacific Oceans and contributes not only to excite the optimal initial perturbations associated with ENSO and the SPDO but in general to activate the entire stochastic SST forcing, especially in austral summer.

ENSO Precipitation Anomalies along the Equatorial Pacific: Moist Static Energy Framework Diagnostics

With the recognition that equatorial Pacific precipitation anomalies are fundamental to global teleconnections during ENSO winters, the present research applies vertically integrated moist static energy (MSE) budget analysis to historical simulations of CMIP5 models. Process-based assessment is carried out to understand if the models capture the differing processes that account for regional precipitation anomalies along the equatorial Pacific and to isolate a few leading processes that account for the diversified precipitation response to similar SST forcing and vice versa. To assess SST biases in CMIP5, analysis is also carried out in AMIP5 solutions. Diagnostics reveal that models have limitations in representing the “sign” of MSE sources and sinks and, even if they do, compensating errors dominate the budget. The diverse response in precipitation depends on model parameterizations that determine anomalous net radiative flux divergence in the column, free troposphere moisture, and MSE export out of the column, although these processes are not independent. Diagnostics derived from AMIP5 solutions support the findings from CMIP5. The implication is that biases in representing any one of these processes are expected to imprint on others, acknowledging the tight connections among moisture, convection, and radiation. CMIP5 models have limitations in representing the basic states in SST and precipitation over the Niño-3.4 region, and the different convective regimes over the equatorial central and eastern Pacific regions with implications for ENSO. Study limitations are that MSE sources/sinks depend on parameterizations and their interactions, making it difficult to isolate one particular process for attribution. Budgets estimated from monthly anomalies do not capture contributions from high-frequency variability that are vital in closing the budgets.

Ocean Fronts and Eddies Remotely Forcing Atmospheric Rivers and Heavy Precipitation

Atmospheric rivers (ARs) are responsible for over 90% of poleward water vapor transport in the midlatitudes and can produce extreme precipitation when they make landfall1-2. However, despite of recent improvements, weather and climate models still have difficulty simulating and predicting the timing and location of landfalling ARs and associated extreme precipitation3-5, highlighting the need to better understand AR dynamics. Here, using high-resolution climate models and observations, we demonstrate for the first time that mesoscale sea-surface temperature (SST) anomalies associated with the Kuroshio front and eddies can exert a remote influence on landfalling ARs and related heavy precipitation along the West Coast of North America. Inclusion of the mesoscale SST forcing in the simulations results in approximately a 40% increase in landfalling ARs and up to a 30% increase in heavy precipitation in mountainous regions. The modeling results further show that this remote impact occurs within two weeks, implying the potential influence of the dynamical processes on AR predictability at subseasonal-to-seasonal time scales. A proposed mechanism for the influence of mesoscale SST forcing on ARs is the asymmetrical response of the atmosphere to warm vs. cold mesoscale SSTs over the eddy-rich Kuroshio Extension region, which results in a net increase of moisture flux above the planetary boundary layer, prompting AR genesis via enhancing moisture transport into extratropical cyclones in the presence of mesoscale SST forcing.