Atmospheric teleconnection mechanisms of extratropical North Atlantic SST influence on Sahel rainfall

Extratropical North Atlantic cooling has been tied to droughts over the Sahel in both paleoclimate observations and modeling studies. This study, which uses an atmospheric general circulation model (GCM) coupled to a slab ocean model that simulates this connection, explores the hypothesis that the extratropical North Atlantic cooling causes the Sahel droughts via an atmospheric teleconnection mediated by tropospheric cooling. The drying is also produced in a regional climate model simulation of the Sahel when reductions in air temperature (and associated geopotential height and humidity changes) from the GCM simulation are imposed as the lateral boundary conditions. This latter simulation explicitly demonstrates the central role of tropospheric cooling in mediating the atmospheric teleconnection from extratropical North Atlantic cooling. Diagnostic analyses are applied to the GCM simulation to infer teleconnection mechanisms. An analysis of top of atmosphere radiative flux changes diagnosed with a radiative kernel technique shows that extratropical North Atlantic cooling is augmented by a positive low cloud feedback and advected downstream, cooling Europe and North Africa. The cooling over North Africa is further amplified by a reduced greenhouse effect from decreased atmospheric specific humidity. A moisture budget analysis shows that the direct moisture effect and monsoon weakening, both tied to the ambient cooling and resulting circulation changes, and feedbacks by vertical circulation and evaporation augment the rainfall reduction. Cooling over the Tropical North Atlantic in response to the prescribed extratropical cooling also augments the Sahel drying. Taken together, they suggest a thermodynamic pathway for the teleconnection. The teleconnection may also be applicable to understanding the North Atlantic influence on Sahel rainfall over the twentieth century

High-resolution tropical channel model simulations of tropical cyclone climatology and intraseasonal-to-interannual variability

We tailored a tropical channel configuration of the Weather Research and Forecasting (WRF) Model to study tropical cyclone (TC) activity and associated climate variabilities. This tropical channel model (TCM) covers from 308S to 508N at 27-km horizontal resolution, with physics parameterizations carefully selected to achieve more realistic simulations of TCs and large-scale climate mean states. We performed 15-member ensembles of retrospective simulations from 1982 to 2016 hurricane seasons. A thorough comparison with observations demonstrates that the TCM yields significant skills in simulating TC activity climatology and variabilities in each basin, as well as TC physical structures. The correlation of the ensemble averaged accumulated cyclone energy (ACE) with observations in the western North Pacific (WNP), eastern North Pacific (ENP), and North Atlantic (NAT) is 0.80, 0.64, and 0.61, respectively, but is insignificant in the north Indian Ocean (NIO). Moreover, the TCM-simulated modulations of El Niño–Southern Oscillation (ENSO) and the Madden–Julian oscillation (MJO) on the large-scale environment and TC genesis also agree well with observations. To examine the TCM’s potential for seasonal TC prediction, the model is used to forecast the 2017 and 2018 hurricane seasons, using bias-corrected sea surface temperatures (SSTs) from the CFSv2 seasonal prediction results. The TCM accurately predicts the hyperactive 2017 NAT hurricane season and near-normal WNP and ENP hurricane seasons when initialized in May. In addition, the TCM accurately predicts TC activity in the NAT and WNP during the 2018 season, but underpredicts ENP TC activity, in association with a poor ENSO forecast

Maximizing ENSO as a source of western US hydroclimate predictability

Until recently, the El Niño–Southern Oscillation (ENSO) was considered a reliable source of winter precipitation predictability in the western US, with a historically strong link between extreme El Niño events and extremely wet seasons. However, the 2015–2016 El Niño challenged our understanding of the ENSO-precipitation relationship. California precipitation was near-average during the 2015–2016 El Niño, which was characterized by warm sea surface temperature (SST) anomalies of similar magnitude compared to the extreme 1997–1998 and 1982–1983 El Niño events. We demonstrate that this precipitation response can be explained by El Niño’s spatial pattern, rather than internal atmospheric variability. In addition, observations and large-ensembles of regional and global climate model simulations indicate that extremes in seasonal and daily precipitation during strong El Niño events are better explained using the ENSO Longitude Index (ELI), which captures the diversity of ENSO’s spatial patterns in a single metric, compared to the traditional Niño3.4 index, which measures SST anomalies in a fixed region and therefore fails to capture ENSO diversity. The physically-based ELI better explains western US precipitation variability because it tracks the zonal shifts in tropical Pacific deep convection that drive teleconnections through the response in the extratropical wave-train, integrated vapor transport, and atmospheric rivers. This research provides evidence that ELI improves the value of ENSO as a predictor of California’s seasonal hydroclimate extremes compared to traditional ENSO indices, especially during strong El Niño events

Selecting CMIP5 GCMs for downscaling over multiple regions

The unprecedented availability of 6-hourly data from a multi-model GCM ensemble in the CMIP5 data archive presents the new opportunity to dynamically downscale multiple GCMs to develop high-resolution climate projections relevant to detailed assessment of climate vulnerability and climate change impacts. This enables the development of high resolution projections derived from the same set of models that are used to characterise the range of future climate changes at the global and large-scale, and as assessed in the IPCC AR5. However, the technical and human resource required to dynamically-downscale the full CMIP5 ensemble are significant and not necessary if the aim is to develop scenarios covering a representative range of future climate conditions relevant to a climate change risk assessment. This paper illustrates a methodology for selecting from the available CMIP5 models in order to identify a set of 8–10 GCMs for use in regional climate change assessments. The selection focuses on their suitability across multiple regions—Southeast Asia, Europe and Africa. The selection (a) avoids the inclusion of the least realistic models for each region and (b) simultaneously captures the maximum possible range of changes in surface temperature and precipitation for three continental-scale regions. We find that, of the CMIP5 GCMs with 6-hourly fields available, three simulate the key regional aspects of climate sufficiently poorly that we consider the projections from those models ‘implausible’ (MIROC-ESM, MIROC-ESM-CHEM, and IPSL-CM5B-LR). From the remaining models, we demonstrate a selection methodology which avoids the poorest models by including them in the set only if their exclusion would significantly reduce the range of projections sampled. The result of this process is a set of models suitable for using to generate downscaled climate change information for a consistent multi-regional assessment of climate change impacts and adaptation

Decadal predictions with the HiGEM high resolution global coupled climate model: description and basic evaluation

This paper describes the development and basic evaluation of decadal predictions produced using the HiGEM coupled climate model. HiGEM is a higher resolution version of the HadGEM1 Met Office Unified Model. The horizontal resolution in HiGEM has been increased to 1.25◦ × 0.83◦ in longitude and latitude for the atmosphere, and 1/3◦ × 1/3◦ globally for the ocean. The HiGEM decadal predictions are initialised using an anomaly assimilation scheme that relaxes anomalies of ocean temperature and salinity to observed anomalies. 10 year hindcasts are produced for 10 start dates (1960, 1965,..., 2000, 2005). To determine the relative contributions to prediction skill from initial conditions and external forcing, the HiGEM decadal predictions are compared to uninitialised HiGEM transient experiments. The HiGEM decadal predictions have substantial skill for predictions of annual mean surface air temperature and 100 m upper ocean temperature. For lead times up to 10 years, anomaly correlations (ACC) over large areas of the North Atlantic Ocean, the Western Pacific Ocean and the Indian Ocean exceed values of 0.6. Initialisation of the HiGEM decadal predictions significantly increases skill over regions of the Atlantic Ocean,the Maritime Continent and regions of the subtropical North and South Pacific Ocean. In particular, HiGEM produces skillful predictions of the North Atlantic subpolar gyre for up to 4 years lead time (with ACC > 0.7), which are significantly larger than the uninitialised HiGEM transient experiments

A recent increase in global wave power as a consequence of oceanic warming

Wind-generated ocean waves drive important coastal processes that determine flooding and erosion. Ocean warming has been one factor affecting waves globally. Most studies have focused on studying parameters such as wave heights, but a systematic, global and long-term signal of climate change in global wave behavior remains undetermined. Here we show that the global wave power, which is the transport of the energy transferred from the wind into sea-surface motion, has increased globally (0.4% per year) and by ocean basins since 1948. We also find long-term correlations and statistical dependency with sea surface temperatures, globally and by ocean sub-basins, particularly between the tropical Atlantic temperatures and the wave power in high south latitudes, the most energetic region globally. Results indicate the upper-ocean warming, a consequence of anthropogenic global warming, is changing the global wave climate, making waves stronger. This identifies wave power as a potentially valuable climate change indicator.Funding for this project was partly provided by RISKOADAPT (BIA2017-89401-R) Spanish Ministry of Science, Innovation and Universities and the ECLISEA project part of the Horizon 2020 ERANET ERA4CS (European Research Area for Climate Services) 2016 Call

Whether weather matters: Evidence of association between in utero meteorological exposures and foetal growth among Indigenous and non-Indigenous mothers in rural Uganda

Pregnancy and birth outcomes have been found to be sensitive to meteorological variation, yet few studies explore this relationship in sub-Saharan Africa where infant mortality rates are the highest in the world. We address this research gap by examining the association between meteorological factors and birth weight in a rural population in southwestern Uganda. Our study included hospital birth records (n = 3197) from 2012 to 2015, for which we extracted meteorological exposure data for the three trimesters preceding each birth. We used linear regression, controlling for key covariates, to estimate the timing, strength, and direction of meteorological effects on birth weight. Our results indicated that precipitation during the third trimester had a positive association with birth weight, with more frequent days of precipitation associated with higher birth weight: we observed a 3.1g (95% CI: 1.0–5.3g) increase in birth weight per additional day of exposure to rainfall over 5mm. Increases in average daily temperature during the third trimester were also associated with birth weight, with an increase of 41.8g (95% CI: 0.6–82.9g) per additional degree Celsius. When the sample was stratified by season of birth, only infants born between June and November experienced a significant associated between meteorological exposures and birth weight. The association of meteorological variation with foetal growth seemed to differ by ethnicity; effect sizes of meteorological were greater among an Indigenous subset of the population, in particular for variation in temperature. Effects in all populations in this study are higher than estimates of the African continental average, highlighting the heterogeneity in the vulnerability of infant health to meteorological variation in different contexts. Our results indicate that while there is an association between meteorological variation and birth weight, the magnitude of these associations may vary across ethnic groups with differential socioeconomic resources, with implications for interventions to reduce these gradients and offset the health impacts predicted under climate change

The South Atlantic Anticyclone as a key player for the representation of the tropical Atlantic climate in coupled climate models

The key role of the South Atlantic Anticyclone (SAA) on the seasonal cycle of the tropical Atlantic is investigated with a regionally coupled atmosphere–ocean model for two different coupled domains. Both domains include the equatorial Atlantic and a large portion of the northern tropical Atlantic, but one extends southward, and the other northwestward. The SAA is simulated as internal model variability in the former, and is prescribed as external forcing in the latter. In the first case, the model shows significant warm biases in sea surface temperature (SST) in the Angola-Benguela front zone. If the SAA is externally prescribed, these biases are substantially reduced. The biases are both of oceanic and atmospheric origin, and are influenced by ocean–atmosphere interactions in coupled runs. The strong SST austral summer biases are associated with a weaker SAA, which weakens the winds over the southeastern tropical Atlantic, deepens the thermocline and prevents the local coastal upwelling of colder water. The biases in the basins interior in this season could be related to the advection and eddy transport of the coastal warm anomalies. In winter, the deeper thermocline and atmospheric fluxes are probably the main biases sources. Biases in incoming solar radiation and thus cloudiness seem to be a secondary effect only observed in austral winter. We conclude that the external prescription of the SAA south of 20°S improves the simulation of the seasonal cycle over the tropical Atlantic, revealing the fundamental role of this anticyclone in shaping the climate over this region