Oceanic Teleconnections Research Articles

The relationship between teleconnections, surface temperature, and cold air outbreaks

AbstractCold air outbreaks (CAOs) are extreme events that can negatively impact the agricultural industry, human health, and cause widespread power outages from increased energy consumption. Increasing the predictability of CAOs is critical to limiting the adverse impacts on society, but skilful predictions rely on well‐defined mechanisms of causation. To improve the understanding of CAO mechanisms, this study examines the relationship between atmospheric and oceanic teleconnection indices and CAOs in the Northern Hemisphere (NH) during two distinct periods, 1979–1998 and 1999–2018. Changes in the relationship between CAOs and teleconnections during these two periods are calculated and used to determine the teleconnections that currently have the strongest relationship with CAOs across the NH. Several relationships were found to no longer be significant while several other significant relationships have emerged, particularly with the Tropical Northern Hemisphere (TNH) pattern. Furthermore, upstream teleconnections, as opposed to downstream teleconnections, were generally found to have a stronger relationship with CAOs. The East Pacific Oscillation and East Pacific/North Pacific pattern were found to have the strongest relationship with CAOs in the eastern U.S. and Alaska, while the Arctic Oscillation, North Atlantic Oscillation, Greenland Blocking Index, and Scandinavian pattern have the strongest relationship with CAOs in Eurasia.

Air‐Sea Interaction in the Western Tropical Pacific and its Impact on Asymmetry of the Ningaloo Niño/Niña

AbstractNingaloo Niño/Niña is the dominant interannual sea surface temperature (SST) variability off Western Australia with the former typically stronger than the latter. Although a recent study suggested that oceanic teleconnections from the Pacific partly contribute to the amplitude asymmetry, this seems counterintuitive as La Niña, which often induces the Ningaloo Niño, is generally weaker than El Niño. Here, mechanisms of the amplitude asymmetry in the oceanic teleconnection are investigated by analyzing reanalysis data and conducting ocean model simulations. Sensitivity experiments using a linear continuously stratified model reveal that stronger easterly wind anomalies in the western equatorial Pacific contribute to the stronger oceanic teleconnection during the Ningaloo Niño. Furthermore, a mixed layer heat budget analysis with a regional ocean model shows that negatively skewed SST anomalies in the central equatorial Pacific related to the skewed wind anomalies in the western equatorial Pacific, are mainly induced by vertical advection/diffusion and entrainment.

Snowfall and snow cover evolution in the Eastern Pre-Pyrenees (NE Iberian Peninsula)

Snow cover has significant impacts on geoecological dynamics as well as on socio-economical systems. An accurate quantification of snow precipitation patterns in mountain regions is needed to better understand the spatio-temporal implications of snow cover. The objective of this work is to characterize the patterns of solid precipitation and snow cover in two high Mediterranean massifs. To this purpose, we analyse instrumental data series of snowfall and snow depth of Port del Comte (2316 m a.s.l.) and Cadí-Nord (2134 m). Both stations are situated in the eastern Pre-Pyrenees and include 14 consecutive snow seasons from November to May, allowing to (i) explore the dependence of the main drivers of snowpack: temperature and snowfall; (ii) find out the most frequent circulation weather types associated with high intensity snowfall events, and finally (iii) investigate the role of the North Atlantic Oceanic (NAO) teleconnection pattern explaining snow cover evolution during the winter season. Data show that snowfall is controlled by similar weather types in both stations that resulted in similar snowfall averages: 205 cm and 258 cm at Port del Comte and Cadí-Nord, respectively. Nevertheless, local factors interfere with the amount of snow depth recorded, which is moderately different between stations. Whereas Cadí-Nord records a seasonal mean of 66 cm, Port del Comte records a smaller quantity of 25 cm with a high interannual and seasonal variability. In fact, snowfall recurrence, snow amount or duration in the ground is considerably variable among years (CV>20). In these stations, snow cover duration is determined by the precipitation in the form of snow falling during the previous months. Snowfalls in moderate to severe episodes (>15 cm in 24 h) are mainly driven by Atlantic flows, mostly from NW. In addition, NAO pattern is negatively correlated with snowfall in November and December months (R>-0.50), showing a weaker and not statistically significant correlation during the rest of the winter season.

Performance of the Taiwan Earth System Model in Simulating Climate Variability Compared With Observations and CMIP6 Model Simulations

AbstractThis study evaluates the performance of the Taiwan Earth System Model version 1 (TaiESM1) in simulating the observed climate variability in the historical simulation of the Coupled Model Intercomparison Phase 6 (CMIP6). TaiESM1 is developed on the basis of the Community Earth System Model version 1.2.2, with the inclusion of several new physical schemes and improvements in the atmosphere model. The new additions include an improved triggering function in the cumulus convection scheme, a revised distribution‐based formula in the cloud fraction scheme, a new aerosol scheme, and a unique scheme for three‐dimensional surface absorption of shortwave radiation that accounts for the influence of complex terrains. In contrast to the majority of model evaluation processes, which focus mainly on the climatological mean, this evaluation focuses on climate variability parameters, including the diurnal rainfall cycle, precipitation extremes, synoptic eddy activity, intraseasonal fluctuation, monsoon evolution, and interannual and multidecadal atmospheric and oceanic teleconnection patterns. A series of intercomparisons between the simulations of TaiESM1 and CMIP6 models and observations indicate that TaiESM1, a participating model in CMIP6, can realistically simulate the observed climate variability at various time scales and are among the leading CMIP6 models in terms of many key climate features.

Identification of atmospheric and oceanic teleconnection patterns in a 20-year global data set of the atmospheric water vapour column measured from satellites in the visible spectral range

Abstract. We used a global long-term (1995–2015) data set of total column water vapour (TCWV) derived from satellite observations to quantify to which extent the temporal patterns of various teleconnections can be identified in this data set. To our knowledge, such a comprehensive global TCWV data set was rarely used for teleconnection studies. One important property of the TCWV data set is that it is purely based on observational data. We developed a new empirical method to decide whether a teleconnection index is significantly detected in the global data set. We compared our new method to well-established hypothesis tests and found good agreement with the results of our approach. Based on our empirical method more than 40 teleconnection indices were significantly detected in the global TCWV data set derived from satellite observations. In addition to the satellite data we also applied our method to other global data sets derived from ERA-Interim. One important finding is that the spatial patterns obtained for the ERA TCWV data are very similar to the observational TCWV data set indicating a high consistency between the satellite and ERA data. Moreover, similar results are also found for two selections of ERA data (either all data or mainly clear-sky data). This finding indicates that the clear-sky bias of the satellite data set is negligible for the results of this study. However, for some indices, also systematic differences in the spatial patterns between the satellite and model data set were found probably indicating possible shortcomings in the model data. For most “traditional” teleconnection data sets (surface temperature, surface pressure, geopotential heights and meridional winds at different altitudes) a smaller number of significant teleconnection indices was found than for the TCWV data sets, while for zonal winds at different altitudes, the number of significant teleconnection indices (up to > 50) was higher. The strongest teleconnection signals were found in the data sets of tropospheric geopotential heights and surface pressure. In all global data sets, no “other indices” (solar variability, stratospheric AOD or hurricane frequency) were significantly detected. Since many teleconnection indices are strongly correlated, we also applied our method to a set of orthogonalised indices, which represent the dominant independent temporal teleconnection patterns. The number of significantly detected orthogonalised indices (20) was found to be much smaller than for the original indices (42). Based on the orthogonalised indices we derived the global spatial distribution of the cumulative effect of teleconnections. The strongest effect on the TCWV is found in the tropics and high latitudes.

What Determines the Lagged ENSO Response in the South‐West Indian Ocean?

AbstractOceanic Rossby waves can propagate climate signals over considerable distances over long timescales. Using a long simulation from a coupled climate model, we examine oceanic and mixed atmosphere‐ocean teleconnections to the south‐western Indian Ocean (SWIO) associated with Rossby waves excited by the El Niño‐Southern Oscillation (ENSO). Reconstruction of propagating ENSO‐induced sea‐level anomalies from the simulation using an optimized linear wave model with dissipation highlights the prominent role of baroclinic, rather than barotropic, Rossby waves in modulating sea‐surface heights. Between 9.5° and 18.5°S, El Niño‐associated anomalous anticyclonic wind‐stress fields initiate downwelling Rossby waves, potentially influencing SWIO regional climate around 1–4 seasons after El Niño peak, while also destructively interfering with upwelling waves triggered on the eastern boundary by oceanic teleconnections. Further south, weaker ENSO winds, dissipation, non‐linear processes, and interference from higher‐mode Rossby waves limit ENSO influences in the SWIO. In the model, ENSO‐associated predictability is therefore constrained by the “atmospheric” rather than “oceanic” bridge.

Effects of Atlantic and Pacific Ocean Teleconnections on Corn Yield East of Puebla, Mexico: Case Studies

Ocean-atmospheric interactions have effects at different scales; forming microclimates, which can explain variations with climatic or natural anomalies, between meteorological processes. This research analyzes and identifies the relationship of the teleconnection hydrometeorological effects, which determine the distribution of precipitation in corn yield. The data were used from a semi-structured interview directed to corn producers, where seven years of case studies were identified for the eastern region of the state of Puebla, Mexico. The Graphics were made with “pentad scale distribution”. The results show the importance of geographical location for agricultural activities in relation to a valley with altitudinal gradient. In addition, the corn growth cycle is associated with tropical disturbances from east Puebla region as well as Hurricane activity. It was identified that the relationship of teleconnections and the distribution of rainfall are main factors that influence in the development good or bad of corn, showed in the yields, where the different phases of ENSO (EL NIÑO Southern Oscillation) have a differentiated impact on the availability of precipitation in this case studies of the present investigation.

Changes in summer precipitation variability in central Brazil over the past eight decades

AbstractCentral Brazil hydroclimate is in the core region of the South American monsoon system. Thus, understanding precipitation variability in this area is crucial not only for the prediction of extreme events such as droughts and floods, but also for water resources management. Ocean teleconnections influence central Brazil precipitation from intraseasonal to interdecadal frequencies, in both linear and nonlinear ways, mainly during the austral summer. Pacific Ocean climate modes can influence South American precipitation, but how its variability changes over time is still a theme of scientific debate. Here we examined the influence of Pacific variability on summer precipitation in central Brazil during the last eight decades. We applied nonparametric spectral methods to four different observational datasets, and to AMIP‐type precipitation outputs from the Laboratoire de Météorologie Dynamique zoom model (LMDZ) in Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6) contributions of the Institut Pierre Simon Laplace (IPSL) coupled model. Our results showed an increase in amplitude and frequency of summer precipitation variability after the 1970s climate transition. Spectral analysis associated these changes to a transition in Pacific Ocean influence to central Brazil precipitation, from PDO‐ to El Niño–Southern Oscillation (ENSO)‐related variability after the 1970s climate transition. Composite analysis suggests these changes are related to teleconnection patterns between the Pacific Ocean and South America precipitation.

Coherent Streamflow Variability in Monsoon Asia Over the Past Eight Centuries—Links to Oceanic Drivers

AbstractThe Monsoon Asia region is home to ten of the world's biggest rivers, supporting the lives of 1.7 billion people who rely on streamflow for water, energy, and food. Yet a synthesized understanding of multicentennial streamflow variability for this region is lacking. To fill this gap, we produce the first large scale streamflow reconstruction over Monsoon Asia (62 stations in 16 countries, 813 years of mean annual flow). In making this reconstruction, we develop a novel, automated, climate‐informed, and dynamic reconstruction framework that is skillful over most of the region. We show that streamflow in Monsoon Asia is spatially coherent, owing to common drivers from the Pacific, Indian, and Atlantic Oceans. We also show how these oceanic teleconnections change over space and time. By characterizing past and present hydroclimatic variability, we provide a platform for assessing the impact of future climatic changes and informing water management decisions.

A novel non-homogeneous hidden Markov model for simulating and predicting monthly rainfall

Monthly-to-seasonal precipitation forecasts are important in water resource management. Hidden Markov models (HMM) are widely applied in precipitation simulation due to its simplicity and advancements in associated computing techniques. HMMs, however, lack the flexibility to accommodate external factors in the dynamics. In this study, we consider a novel semiparametric Bayesian non-homogeneous hidden Markov model (BNHMM) that can explicitly incorporate the effects of observed covariates, e.g., climate index, on the state transition probabilities as well as the observation emission distributions. The proposed approach is tested for three rainfall stations in the service area of Tampa Bay Water, a regional water supply agency in the Southeastern United States. The BNHMM is first examined to simulate historical monthly rainfall data from the period 1979 to 2016. It is then evaluated in a retrospective mode to generate 3-month-ahead precipitation forecasts. Results indicate that the proposed BNHMM can capture historical rainfall properties well, and it is a promising alternative in providing operational rainfall forecasts. Although large-scale atmospheric and oceanic teleconnections, e.g., ENSO, have a strong influence in regional rainfall at the seasonal time scale, especially for the winter and early spring; its influence on monthly scale rainfall is limited. Potential improvement in forecasting performance is also discussed.

Classification of Clustered Snow Off Dates Over British Columbia, Canada, from Mean Sea Level Pressure

ABSTRACT Atmosphere–ocean teleconnections influence the accumulation and melt of snow in western Canada and can be useful in seasonal forecasting of snowmelt and runoff. Interannual variation in these atmosphere–ocean modes has been shown to influence the accumulation and melt of snow within British Columbia (BC), Canada. We investigate fall mean sea level pressure (MSLP) globally as a predictor of remotely sensed snowmelt dates within BC. We use the last day of continuous snow cover () detected from time series satellite imagery acquired by the Moderate Resolution Imaging Spectroradiometer for the hydrological years 2000–2018. It has been shown that is correlated with continuous snow duration and is also of interest to seasonal forecasters. Global MSLP from the Fifth major global reanalysis produced by the European Centre for Medium-range Weather Forecasts was obtained over hydrological years 1979–2018. An S-mode (time versus location) principal component analysis was carried out on both datasets. The principal component scores were grouped using a k-means clustering routine. Using evolutionary feature selection, the subset of MSLP principal components that provided good linear discrimination of the clusters were found. We explore the atmospheric MSLP principal components that influence the timing of snowmelt over BC and use them to predict the clusters at a seasonal lead time.

Drivers of Subsurface Temperature Variability in the Northern California Current

AbstractJISAO's Seasonal Coastal Ocean Prediction of the Ecosystem (J‐SCOPE) was developed to carry out experimental seasonal forecasts of ocean conditions in the Northern California Coastal System (N‐CCS). This system relies on NOAA's Coupled Forecast System (CFS) global climate model to provide initial and boundary conditions for dynamical downscaling with a high‐resolution numerical ocean model. Experiments with J‐SCOPE show that the bottom temperature on the shelf is more predictable than the sea surface temperature (SST) on seasonal time scales. While seasonal forecasts have been shown to have positive skill in terms of SST for the CCS due to El Niño‐Southern Oscillation (ENSO), the mechanism(s) responsible for subsurface predictability in the N‐CCS have yet to be determined. This study quantifies the relative importance of North Pacific and Tropical Pacific properties in determining the variations in temperatures at depth (TDs) on the N‐CCS shelf. A multivariable linear regression (MLR) model with selected predictors explains almost 83% of the N‐CCS TD variability with oceanic teleconnections from the North Pacific dominating the variance. The N‐CCS TD is related to (i) coastally trapped waves (CTWs) related to ENSO, originating in Tropical Pacific, (ii) west‐central Pacific spice anomalies, (iii) seasonal Pacific Decadal Oscillation (PDO) variation, and a more local influence from (iv) anomalies south of N‐CCS, originating in North Pacific. ENSO and CTW can each impact the depth of the California Undercurrent (CUC) core with the latter most prominently following ENSO events. The results on potential sources of predictability are relevant to the continued development of current seasonal forecasting efforts off the U.S. West coast.

Boreal-winter teleconnections with tropical Indo-Pacific rainfall in HighResMIP historical simulations from the PRIMAVERA project

This study investigates how teleconnections linking tropical rainfall anomalies and wintertime circulation in the northern extra-tropics are represented in historical simulations for the period 1950–2010 run by partners of the EU-funded PRIMAVERA project, following the HighResMIP protocol of CMIP6. The analysis focusses on teleconnections from the western/central Indian Ocean in mid-winter and from the NINO4 region in both the early and the late part of winter; this choice is justified by a substantial change in the relationship between ENSO and the North Atlantic Oscillation (NAO) in the two parts of the season. Model results for both coupled integrations and runs with prescribed sea-surface temperature (SST) are validated against data from the latest ECMWF 20th-century re-analysis, CERA20C. Simulations from six modelling groups are considered, comparing the impact of increasing atmospheric resolution in runs with prescribed SST, and of moving from uncoupled to coupled simulations in the high-resolution version of each model. Single runs were available for each model configurations at the time of writing, with one centre (ECMWF) also providing a 6-member ensemble. Results from this ensemble are compared with those of a 6-member multi-model ensemble (MME) formed by including one simulation from each model. Using only a single historical simulation from each model configuration, it is difficult to detect a consistent change in the fidelity of model-generated teleconnections when either atmospheric resolution is increased or ocean coupling is introduced. However, when simulations from six different models are pooled together in the MME, some improvements in teleconnection patterns can be seen when moving from uncoupled to coupled simulations. For the ECMWF ensemble, improvements in the coupled simulations are only apparent for the late-winter NINO4 teleconnection. While the Indian Ocean teleconnection and the late-winter NINO4 teleconnection appear equally robust in the re-analysis record, the latter is well simulated in the majority of both uncoupled and coupled runs, while the former is reproduced with (generally) much larger errors, and a high degree of variability between individual models and ensemble members. Most of the simulations with prescribed SST fail to produce a realistic estimate of multi-decadal changes between the first and the second part of the 60-year record. This is (at least partially) due to their inability to simulate an Indian Ocean rainfall change which, in observations, has a zonal gradient out of phase with SST changes. In coupled runs, at least one model run with both realistic teleconnections and a good simulation of the inter-decadal pattern of Indian Ocean rainfall also shows a realistic NAO signal in extratropical multi-decadal variability.

Contribution of oceanic wave propagation from the tropical Pacific to asymmetry of the Ningaloo Niño/Niña

Ningaloo Nino/Nina is the dominant mode of interannual variability of sea surface temperature (SST) in the southeastern Indian Ocean. According to previous studies, both local air-sea interaction and remote forcing contribute to generation and amplification of the Ningaloo Nino/Nina. The latter forcing includes the atmospheric teleconnection and oceanic wave propagation through the Indonesian archipelago, mainly associated with the El Nino/Southern Oscillation (ENSO). One of the most important characteristics of the Ningaloo Nino/Nina is their asymmetry; the Ningaloo Nino is stronger than the Ningaloo Nina. Using a regional ocean modeling system (ROMS), the impact of oceanic wave propagation on the amplitude and asymmetry of SST anomalies associated with the Ningaloo Nino/Nina is investigated. For these purposes, a sensitivity experiment in which oceanic lateral boundary conditions are replaced by the monthly climatology is conducted. It is shown that the oceanic teleconnection transmitted from the western tropical Pacific can explain about 30% of the observed amplitude asymmetry in SST anomalies. Results from composite and heat budget analyses suggest that coastal downwelling (upwelling) Kelvin waves from the western tropical Pacific associated with La Nina (El Nino) that often co-occurs with the Ningaloo Nino (Nina) are stronger (weaker) and contribute to the asymmetry.

Trends and Extremes of Drought Episodes in Vietnam Sub-Regions during 1980–2017 at Different Timescales

This study investigated the temporal occurrence of dry conditions in the seven climatic sub-regions of Vietnam during the 1980–2017 period. This assessment was performed using the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) at 1 to 24 months timescales. Results show that the main periods of extreme drought occurred simultaneously throughout the country in 1992–1993 and 2003–2004, except for 2015–2016, when it was not identified in the southern region. In addition, a slight temporal lag was identified latitudinally (north–south) at the beginning of dry conditions, revealing the largest difference between the northern and southern regions. A positive trend in the time series of both indices (SPEI and SPI) prevailed in all sub-regions, with the SPEI minus SPI difference always being negative, suggesting the importance of temperature and evapotranspiration for this trend. Further detailed analyses were then performed using SPEI at 1-month and 12-months timescales for all climate sub-regions, as well as the main indicators to characterize duration and severity. Results show that the number of drought episodes did not vary much between regions, but they did vary in duration and severity at the annual scale. Moreover, changes in the soil root zone are largely associated with dry and wet conditions not only from season to season, but also in longer accumulation periods and more strongly in the northern regions of Vietnam. Indeed, a study of the most severe drought episodes also revealed the occurrence of negative anomalies of the root-soil moisture in the subsequent four or more months. Dynamic atmospheric conditions associated with the peak of most severe drought episodes show the crucial role of subsidence of dry air in the middle and high atmosphere, which prevents convection in the lower troposphere. Finally, the linkages between drought conditions in Vietnam and large-scale atmospheric and oceanic teleconnection patterns were revealed to be quite different among northern and southern sub-regions. During the positive phase of El Niño–Southern Oscillation (ENSO), drought episodes at different timescales were identified in the southern climate sub-regions, while the negative phase was associated with drought conditions in the northern regions.

El Niño–Southern Oscillations and Pacific Decadal Oscillation as Drivers of the Decadal Dynamics of Benthic Macrofauna in Two Subtropical Estuaries (Southern Brazil)

The El Nino–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) are large-scale climatic phenomena affecting atmospheric and oceanic teleconnections, and thus triggering weather events at different temporal and spatial scales, both in tropical and extratropical areas. During 11 years (2007–2017), the influence of ENSO events (El Nino, La Nina and neutral), ENSO types (canonical and Modoki) and PDO phases (cold and warm) on meteorological conditions and macrobenthic invertebrates were analyzed in two distinct (tide-dominated and river-dominated) subtropical estuaries of Southern Brazil. The estuarine macrobenthic communities differed markedly, with higher species richness in the tide-dominated estuary (146 taxa) than river-dominated (44). We showed that long-term variability of benthic macrofauna in both estuaries was strongly influenced by the PDO and ENSO events. However, the signs of PDO and ENSO effects differed between the estuaries. While the main modulating force of the decadal variability of the macrofauna of the tide-dominated estuary was the PDO (19%), the river-dominated estuary was primarily influenced by the ENSO (9%). Besides, PDO and ENSO teleconnections have combined effects, with higher macrofauna dissimilarities during constructive periods (PDO Positive/EL Nino vs. PDO Negative/La Nina). Our findings indicate that: (1) The effects of the ENSO on coastal areas are dependent of the spatial scale and the intrinsic characteristics of each estuary; (2) Studies relating ENSO and biodiversity should consider the ENSO type (Modoki and canonical) and interdecadal modes, such as PDO, because the location of the warm pools and the intensity of induced heating affect the atmospheric teleconnections.

The Relationship between the Wintertime Cold Extremes over East Asia with Large-Scale Atmospheric and Oceanic Teleconnections

The influence of large-scale teleconnection patterns, Western Pacific (WP), Arctic Oscillation (AO) and El Niño-Southern Oscillation (ENSO), on the minimum surface air temperature (Tmin) anomalies and extremes over East Asia during the boreal winter from 1979 to 2017 were investigated by the composite analysis in terms of atmospheric and oceanic processes. The relationship between the Tmin and the geopotential height at 500 hPa (Z500) as well as sea surface temperature (SST) were first examined. Then we explored and estimated the contribution of the teleconnection patterns to the occurrence of extremely cold days and months quantitatively, and discussed other key factors in relation to the cold extremes. The WP and AO patterns play an important part in the prevalence of significant Tmin variability, whereas the effect of ENSO is relatively weak. Most of the cold extremes tend to appear in the negative phase of teleconnections, while there some extremes that occur in the opposite phase. In addition, the extreme months are more related to the preferred phase of the dominant pattern when compared to days. We conclude that the daily extremes are primarily triggered by the local-synoptic atmospheric circulations embedded in the large-scale teleconnection patterns, while the monthly extremes have a closer relationship with these low-frequency patterns.

Impact of convective parameterization on the seasonal prediction skill of Indian summer monsoon

The sensitivity of seasonal predictions of the Indian summer monsoon (ISM) to convection parameterization schemes (CPS) is studied using 37 years of hindcast experiments. The predictions are quite sensitive to changes in these schemes and improve the skill by 18–28%. Though the mean state circulation and rainfall over India improves, the sea surface temperature (SST) biases increase in the sensitivity experiments compared to the control run. The ability of the model to realistically capture the teleconnections associated with monsoon such as the El-Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) also appears to change with different CPS. It is found that the suitability of a CPS for ISM in the Climate Forecast System version 2 (CFSv2) stems from its ability to capture cloud fractions realistically and keep the SST biases to a minimum. The revised Simplified-Arakawa–Schubert (SAS2, Han and Pan in Weather Forecast 26:520–533. https://doi.org/10.1175/waf-d-10-05038.1 , 2011) scheme gives better prediction skill for ISM compared to the skill score obtained from SAS2 with shallow convection (SAS2sc) primarily because it simulates realistic clouds, without aggravating the SST biases, particularly in the tropical Pacific Ocean, and captures the Indian Ocean teleconnections realistically. SAS2sc significantly under-estimates the low-level clouds over global equatorial region, despite simulating better mid and high-level clouds, higher Nino 3.4 skill, and better inter-annual variability of ISM. The cold SST bias in the tropical basins is large in SAS2sc. Therefore, to exploit the merits of SAS2sc, unrealistic suppression of low clouds needs to be addressed, and the cold SST biases need to be minimized.

Modelling the impacts of climate change on riverine thermal regimes in western Canada\u2019s largest Pacific watershed

Quantification of climate change impacts on the thermal regimes of rivers in British Columbia (BC) is crucial given their importance to aquatic ecosystems. Using the Air2Stream model, we investigate the impact of both air temperature and streamflow changes on river water temperatures from 1950 to 2015 across BC’s 234,000 km2 Fraser River Basin (FRB). Model results show the FRB’s summer water temperatures rose by nearly 1.0 °C during 1950–2015 with 0.47 °C spread across 17 river sites. For most of these sites, such increases in average summer water temperature have doubled the number of days exceeding 20 °C, the water temperature that, if exceeded, potentially increases the physiological stress of salmon during migration. Furthermore, river sites, especially those in the upper and middle FRB, show significant associations between Pacific Ocean teleconnections and regional water temperatures. A multivariate linear regression analysis reveals that air temperature primarily controls simulated water temperatures in the FRB by capturing ~80% of its explained variance with secondary impacts through river discharge. Given such increases in river water temperature, salmon returning to spawn in the Fraser River and its tributaries are facing continued and increasing physical challenges now and potentially into the future.

Tropical Teleconnections to Antarctic Sea Ice During Austral Spring 2016 in Coupled Pacemaker Experiments

AbstractFollowing a multidecade increase, Antarctic sea ice declined drastically during austral spring 2016. Suggested causes of the sea ice decline include lingering effects of the 2015/2016 extreme El Niño and a tropical Indian Ocean teleconnection to high‐latitude atmospheric circulation. Here, we conduct pacemaker experiments using a full coupled climate model forced with observed tropical sea surface temperature to examine the impact of the Indian and Pacific Oceans on southern high latitudes during spring 2016. Our experiments suggest that a Rossby wave teleconnection from the tropical Indian Ocean contributed to the sea ice decline during spring 2016, with less influence from the Pacific Ocean. However, we find considerable spread in the magnitude of sea ice anomalies across ensemble members, suggesting that while an Indian Ocean teleconnection likely played a role, intrinsic atmospheric variability and high‐latitude ocean conditions may also have been important in driving the observed 2016 spring sea ice decline.