Hadley Centre Sea Ice Research Articles

Decadal difference in influential factors for interannual variations of winter Tibetan Plateau snow

Using the monthly data of the number of days covered by snow (SCD) at meteorological stations, the NCEP-NCAR atmospheric reanalysis, and the Hadley Centre Sea Ice and Sea Surface Temperature dataset during 1973–2019, we investigate the influential factors for interannual variations of winter SCD in the central-eastern Tibetan Plateau (hereafter called the TP) and their decadal difference. The results show that the winter TP SCD exhibits a decadal shift from a positive phase to a negative phase around the late 1990s. Concurrent with this decadal shift, the dominant influential factor for the interannual variability of the winter TP SCD has an alternation from the tropical ocean to the Arctic signal. Before the late 1990s, the winter TP SCD is closely related with the synergistic effects from the tropical central-eastern Pacific (TCEP) and the tropical eastern Indian Ocean (TEIO) along the tropical ocean-TP path, while it is closely related with the AO along the Arctic-TP path since the late 1990s. Different from the significantly weakened interannual fluctuation of the TEIO and TCEP SSTs, the interannual fluctuation of the AO show a remarkably strengthening trend in the recent 20 years. The strengthened Arctic signal could exert a strong influence on the TP SCD through a wave train that goes along the path from the Greenland and adjacent areas to the TP via the extratropical Atlantic Ocean and the middle-high latitudes of Eurasia. The opposite trends in the interannual fluctuation intensities of the tropical SST and AO may lead to a larger contribution of the Arctic signal to the interannual variability of the winter TP snow in the recent 20 years.

Impacts of large scale climate drivers on precipitation in Sindh, Pakistan using machine learning techniques

Sindh province of Pakistan has a long history of severe droughts. Several large scale climate drivers (LSCD) are known for their effect on precipitation worldwide but studies in the Sindh region are missing; wide variety of LSCDs and lagged associative information. This study aimed to identify the significant LSCDs in Sindh province of Pakistan and improve the forecast skill of monthly precipitation by employing the principal component analysis (PCA), artificial neural network (ANN), Bayesian regularization neural network (BRNN), and multiple regression analysis (MRA), while considering the 12 months lagged LSCDs such as Nino-1+2, Nino-3, Nino-3.4, Nino-4, Quasi-Biennial Oscillation (QBO) at 30 and 50hPa (QBOI and QBOII), sea surface temperature (SST), 2m air temperature (T2M), 500 hPa and 850 hPa geopotential heights (H500 and H850), surface and 500 hPa zonal velocity (SU and U500), latent and sensible heat fluxes over land (LHFOL and SHFOL), and surface specific humidity (SSH). Global Land Data Assimilation System (GLDAS), Tropical Rainfall Measuring Mission (TRMM), ModernEra Retrospective Analysis for Research and Application (MERRA-2), NOAA, Freie University Berlin, and Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) datasets were used. Results manifested that significant LSCDs with 99% confidence level were SU, U500, T2M, SST, SHFOL, LHFOL, SSH, and H850. During test period, compared with MR models of 0.39 to 0.64 and principal components of 0.31 to 0.57, the ANN and BRNN models had better predictive skills with correlation coefficients of 0.57 to 0.83 and 0.52 to 0.76, respectively. It can be concluded that the ANN and BRNN models enable us to predict monthly precipitation in Sindh region with lagged LSCDs.

Seasonal extrema of sea surface temperature in CMIP6 models

Abstract. CMIP6 model sea surface temperature (SST) seasonal extrema averaged over 1981–2010 are assessed against the World Ocean Atlas (WOA18) observational climatology. We propose a mask to identify and exclude regions of large differences between three commonly used climatologies (WOA18, WOCE-Argo Global Hydrographic climatology (WAGHC) and the Hadley Centre Sea Ice and Sea Surface Temperature data set (HadISST)). The biases in SST seasonal extrema are largely consistent with the annual mean SST biases. However, the amplitude and spatial pattern of SST bias vary seasonally in the 20 CMIP6 models assessed. Large seasonal variations in the SST bias occur in eastern boundary upwelling regions, polar regions, the North Pacific and the eastern equatorial Atlantic. These results demonstrate the importance of evaluating model performance not simply against annual mean properties. Models with greater vertical resolution in their ocean component typically demonstrate better representation of SST extrema, particularly seasonal maximum SST. No significant relationship of SST seasonal extrema with horizontal ocean model resolution is found.

Representation of Lake–Atmosphere Interactions and Lake-Effect Snowfall in the Laurentian Great Lakes Basin among HighResMIP Global Climate Models

Abstract Credible modeling, tools, and guidance, regarding the changing Laurentian Great Lakes and the climatic impacts, are needed by local decision-makers to inform their management and planning. The present study addresses this need through a model evaluation study of the representation of lake–atmosphere interactions and resulting lake-effect snowfall in the Great Lakes region. Analysis focuses on an extensive ensemble of 74 historical simulations generated by 23 high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP). The model assessment addresses the modeling treatment of the Great Lakes, the spatial distribution and seasonality of climatological snowfall, the seasonal cycle of lake-surface temperatures and overlake turbulent fluxes, and the lake-effect ratio between upwind and downwind precipitation. A deeper understanding of model performance and biases is achieved by partitioning results between HighResMIP GCMs that are 1) coupled to 1D lake models versus GCMs that exclude lake models, 2) between prescribed-ocean model configurations versus fully coupled configurations, and 3) between deep Lake Superior versus relatively shallow Lake Erie. While the HighResMIP GCMs represent the Great Lakes by a spectrum of approaches that include land grid cells, ocean grid cells (with lake surface temperature and ice cover boundary conditions provided by the Met Office Hadley Center Sea Ice and Sea Surface Temperature Dataset), and 1D lake models, the current investigation demonstrates that none of these rudimentary approaches adequately represent the complex nature of seasonal lake temperature and ice cover evolution and its impact on lake–atmosphere interactions and lake-effect precipitation in the Great Lakes region. Significance Statement The purpose of this study is to evaluate the capability of high-resolution global climate models to simulate lake–atmosphere interactions and lake-effect snowfall in the Great Lakes region, given the critical influence of the lakes on regional climate and vast societal and environmental impacts of lake-effect snowfall. It is determined that the models inadequately represent lake temperatures and ice cover, often leading to insufficient annual snowfall in the lake-effect zones. More advanced, three-dimensional lake models need to be coupled to climate models to support greater credibility in regional lake and climate simulations and future climate projections.

Possible Lagged Impact of the Arctic Sea Ice in Barents–Kara Seas on June Precipitation in Eastern China

Based on the Hadley Centre sea ice concentration, the ERA5 reanalysis, and three precipitation datasets, the possible lagged impact of the Barents–Kara sea ice on June rainfall across China is investigated. Using the singular value decomposition, it is revealed that the state of sea ice concentration in Barents–Kara Seas from November to December is closely related to regional precipitation in June, which is most evident across the Yangtze–Huai Rivers Valley and South China. Possible pathways from preceding Arctic sea ice concentration to June precipitation are examined and discussed. First, the sea ice concentration usually has a long memory, which exerts a long-lasting and lagged impact, although the sea ice anomaly amplitude gradually weakens from early winter to early summer. Second, an increase in Barents–Kara sea ice usually corresponds to a stronger stratospheric polar vortex in midwinter by suppressing extratropical wave activities, which is projected to the positive phase of northern annular mode (NAM). Strong vortex gradually recovers to its normal state and even weakens in spring, which corresponds to the negative NAM response from spring to early summer. Third, the stratospheric anomalies associated with the Barents–Kara sea ice variations propagate downward. Due to the out-of-phase relationship between the lower and upper stratospheric circulation anomalies after midwinter, westerly anomalies in midwinter are followed by easterly anomalies in later months in the circumpolar region, consistent with the positive NAM response in midwinter, negative NAM response in spring, and a wave train-like response in early summer to Barents–Kara sea ice increase (and vice versa). The observed lagged impact of Barents–Kara sea ice on China rainfall in June is limitedly simulated in the ten CMIP6 models used in this study.

Influence of SST in Low Latitudes on the Arctic Warming and Sea Ice

Global climate models, focused on projecting anthropogenic warming, have not detected an increase in sea surface temperature (SST) at low latitudes comparable to the observed one. This appears to be one reason for the discrepancy between the model estimates of warming and reduction of the sea ice extent in the Arctic and the observed changes in the climate system. In previous studies, it was shown that short-term manifestations of the impact of low latitudes on the Arctic climate were identified in 2–3 weeks as a result of strengthening of atmospheric circulation patterns. In this paper, for the first time, a climatic relationship was established among an increase in SST, air temperature, and water vapor content at low latitudes, and a decrease in sea ice extent in the Arctic. ECMWF Re-Analysis data (ERA-Interim, ERA5), Hadley Centre Sea Ice and Sea Surface Temperature data set (HadISST), sea ice archives of the World Centers NSIDC (USA), and Arctic and Antarctic Research Institute (Russia), observations of water temperature in the Kola section (33°30’ E), calculated sea ice parameters using the Arctic and Antarctic Research Institute coupled ice-ocean circulation model (AARI–IOCM). Methods of multivariate correlation analysis, calculating spectra and coherence, and creating correlation graphs were used to obtain the results. For the first time, estimates of the effect of heat transport from low to high latitudes on climate change and sea ice extent in the Arctic over the past 40 years have been obtained, explaining a significant part of their variability. The increase in heat transport is affected by an increase in SST at low latitudes, where a significant part of the solar heat is accumulated. Due to the increase in SST, the amount of heat transported by the ocean and the atmosphere from low latitudes to the Arctic increases, leading to an increase in the air temperature, water vapor content, downward longwave radiation at high latitudes, and a decrease in the thickness and extent of winter sea ice. Potential topics include, but are not limited to: the role of heat and moisture transport in the Arctic warming, effect of SST at low latitudes on transports, linkage of warming in low latitudes and in shrinking of the Arctic sea ice.

Experience of evaluation of the array of ice data based on the annual course of insolation at the upper boundary of the atmosphere

This article examines the reliability of ice data presented in the HadISST1 database (Hadley Centre Sea Ice and Sea Surface Temperature data set) of Hadley Meteorological Center (Hadley Centre for Climate Prediction and Research, Met Office, UK). The criterion for the reliability of HadISST1 database on the Northern hemisphere serves the average multiyear annual course of insolation in the Northern Hemisphere and the average multiyear annual course of insolation in 5-degree latitudinal zones at the upper boundary of the atmosphere, phase-shifted by two and three months to the past. It is revealed that the representative criterion for assessing the reliability of the business database is the average multiyear course of insolation in 5-degree latitudinal zones shifted by two months to the past. Evaluation of the data array on the Northern Hemisphere on the basis of the selected criterion demonstrates the overall high reliability of ice data reflected therein. However, there are two areas that differ in the degree of reliability of the presented data: 1) pack, drift ice with high negative values of the correlation coefficient; 2) coastal zone, in which the correlation is virtually absent (shore ice and flaw leads). The weak (or absent) correlation is observed over a significant length of the coastal zone in the Arctic Ocean, as well as in the straits and bays of the Canadian Arctic Archipelago. It is established hat the correlation coefficient of the annual course of the ice flow in the cells of the array of size 1 with the annual course of insolation of the Northern Hemisphere and the corresponding 5-degree latitudinal zones increases from the past to the present. This indicates the need for the correction of ice data in the early time range of the array (1901–1978), which precedes the time of the beginning of satellite observations.

Sea Surface Temperature Variability on the SE‐Greenland Shelf (1796–2013 CE) and Its Influence on Thrym Glacier in Nørre Skjoldungesund

AbstractHeat transport via ocean currents can affect the melting of marine‐terminating glaciers in Greenland. Studying past changes of marine‐terminating glaciers allows assessing the regional sensitivity of the Greenland Ice Sheet to ocean temperature changes in the context of a warming ocean. Here, we present a high‐resolution multiproxy marine sediment core study from Skjoldungen Fjord, close to the marine‐terminating Thrym Glacier. Grain‐size data are obtained to reconstruct the calving activity of Thrym Glacier; sortable silt is used as a proxy for fjord water circulation, and sea surface temperatures (SSTs) are reconstructed from alkenone paleothermometry (Uk'37). Measurements of 210Pb, 137Cs, and 14C indicate that the core covers the past 220 years (1796–2013 CE). Comparisons with modeled SST data (Hadley Centre Sea Ice and SST) and instrumental temperatures (International Council for the Exploration of the Sea) suggest that the SST proxy record reflects temperature variability of the surface waters over the shelf and that alkenones are advected into the fjord. Additionally, average temperatures and the amplitude of fluctuations are influenced by alkenones advected from upstream the Irminger Current. We find that the SST record compares well with other alkenone‐based reconstructions from SE‐Greenland and thus features regional shelf water variability. The calving activity as well as the terminus position of Thrym Glacier did not seem to respond to the SST variability. Limited ice‐ocean interactions owing to the specific setting of the glacier would explain this. Instead, the fjord circulation may have been influenced by enhanced meltwater production as well as to larger scale changes in the Atlantic Meridional Overturning Circulation.

The impact of north tropical Atlantic sea surface temperature anomalies in the ensuing spring of El Niño on the tropical Indian Ocean and Northwest Pacific

AbstractBased on the fifth generation reanalysis of European Centre for Medium–Range Weather Forecasts (ECMWF), Hadley Centre sea ice and sea surface temperature data, and ENSEMLES hindcasts, the impact of north tropical Atlantic (NTA) sea surface temperature (SST) anomalies in the ensuing spring of El Niño on the tropical Indian Ocean (TIO) and Northwest Pacific (NWP) is investigated using composites, singular value decomposition, and correlations. The anomalous SST warming in the NTA region in the decay spring of El Niño leads to a Gill‐type response of the overlying atmosphere in spring–summer. The Kelvin wave over the TIO stimulated by the NTA warming causes the anomalous easterlies in the regions of TIO and NWP, thereby the strengthening of the NWP subtropical anticyclone (NWPSA). The NTA SST warming also forces a local ascending motion, leading to a downward branch over the NWP region. This descent gives rise to the TIO‐NWP low‐level easterly anomalies and an intensification of the NWPSA. The anomalous easterly weakens the background southwesterly monsoon, accompanied by the increased atmospheric boundary layer specific humidity caused by the troposphere warming, suppressing upward latent heat fluxes, finally contributing to the North Indian Ocean (NIO) warming in summer. This indicates that the second warming of the NIO region in the following summer of El Niño may be partially attributed to the NTA warming in the ensuing spring of El Niño. This study improves our understanding of the impact of the NTA SST anomalies in the El Niño decay spring on the TIO and NWP regions, and emphasizes the importance of the NTA region in the pantropical inter‐basin interactions.

New Evidence of Mediterranean Climate Change and Variability from Sea Surface Temperature Observations

Estimating long-term modifications of the sea surface temperature (SST) is crucial for evaluating the current state of the oceans and to correctly assess the impact of climate change at regional scales. In this work, we analyze SST variations within the Mediterranean Sea and the adjacent Northeastern Atlantic box (west of the Strait of Gibraltar) over the last 37 years, by using a satellite-based dataset from the Copernicus Marine Environment Monitoring Service (CMEMS). We found a mean warming trend of 0.041 ± 0.006 ∘ C/year over the whole Mediterranean Sea from 1982 to 2018. The trend has an uneven spatial pattern, with values increasing from 0.036 ± 0.006 ∘ C/year in the western basin to 0.048 ± 0.006 ∘ C/year in the Levantine–Aegean basin. The Northeastern Atlantic box and the Mediterranean show a similar trend until the late 1990s. Afterwards, the Mediterranean SST continues to increase, whereas the Northeastern Atlantic box shows no significant trend, until ~2015. The observed change in the Mediterranean Sea affects not only the mean trend but also the amplitude of the Mediterranean seasonal signal, with consistent relative increase and decrease of summer and winter mean values, respectively, over the period considered. The analysis of SST changes occurred during the “satellite era” is further complemented by reconstructions also based on direct in situ SST measurements, i.e., the Extended Reconstructed SST (ERSST) and the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST), which go back to the 19th century. The analysis of these longer time series, covering the last 165 years, indicates that the increasing Mediterranean trend, observed during the CMEMS operational period, is consistent with the Atlantic Multidecadal Oscillation (AMO), as it closely follows the last increasing period of AMO. This coincidence occurs at least until 2007, when the apparent onset of the decreasing phase of AMO is not seen in the Mediterranean SST evolution.

West African Monsoon: current state and future projections in a high-resolution AGCM

The West African Monsoon (WAM) involves the interaction of multi-scale processes ranging from planetary to cumulus scales, which makes it challenging for coarse resolution General Circulation Models to accurately simulate WAM. The present study evaluates the ability of the high-resolution (sim 25 km) Atmospheric General Circulation Model HiRAM to simulate the WAM and to analyze its future projections by the end of the 21st century. For the historical period, two AMIP-type simulations were conducted, one forced with observed SST from Hadley Center Sea Ice and Sea Surface Temperature dataset and the other forced with SST from the coarse resolution Earth System Model (ESM2M), which is the parent model of HiRAM, i.e. both models have the same dynamical core and similar physical parameterizations. The future projection, using the Representative Concentration Pathway 8.5 and SST from ESM2M is also conducted. A process-based evaluation is carried out to elucidate HiRAM’s ability to represent the key processes and multiscale dynamic features those define the WAM circulation. Compared to ESM2M, HiRAM better represents most of the key circulation elements at different scales, and thus more accurately represents the intensity and spatial distribution of the WAM rainfall. The position of the African easterly jet is considerably improved in HiRAM simulations, leading to the improved positioning of the WAM rainbelt and the two-cell structure of convection. The future projection of the WAM exhibits warming over the entire domain, decreasing precipitation over the southern Sahel, and increase of precipitation over the western Sahara.

An observational study of the variability of East African rainfall with respect to sea surface temperature and soil moisture

Rainfall from the October–November–December (OND) short rains season over East Africa (EA, 5°S–20°N, 28–52°E) were analysed during the 1983–2010 period using state‐of‐the‐art observational datasets. Links among satellite‐derived rainfall (Climate Hazards group InfraRed Precipitation with Station data, CHIRPS), sea surface temperature (Hadley Centre Sea ice and Sea Surface Temperature, HadISST1‐SST), soil moisture (Climate Change Initiative, CCI‐SM), and dynamical variables (European Centre for Medium‐Range Weather Forecasts Re‐Analysis, ERA‐Interim) are investigated to disentangle their specific role in shaping the rainfall variability over the region. In general, interannual rainfall variability is highest in the area during OND. Empirical orthogonal function (EOF) analysis is applied to the rainfall dataset to extract the dominant spatial and temporal patterns of variability. Results show that the rainfall variability is directly influenced by the SST variability in the Indian Ocean (Indian Ocean Dipole, IOD) and in the Pacific Ocean (El Niño–Southern Oscillation, ENSO), and by the local SM. The strong positive correlation (0.78) between EA short rain index and the IOD index indicates that the positive‐phase IOD (IOD+) plays a dominant role in driving OND rainfall. Moreover, IOD+ usually coincides with El Niño events and becomes stronger as the intensity of El Niño increases for years of joint events, and the Walker circulation is shifted accordingly. Furthermore, El Niño alone brings a reduction of rainfall over EA. The physical mechanism explaining the IOD+ link to EA rainfall consists of a Gill‐type response to warm western Indian Ocean SST anomalies that induces anomalous low‐level easterlies over the IO and leads to moisture convergence over EA. In general, the response of rainfall is opposite during the negative phase of the events (IOD− and La Niña).

Evaluating SST Analyses with Independent Ocean Profile Observations

The difficulty in effectively evaluating sea surface temperature (SST) analyses is finding independent observations, since most available observations have been used in the SST analyses. In this study, the ocean profile measurements [from reverse thermometer, CTD, mechanical bathythermograph (MBT), and XBT] above 5-m depth over 1950–2016 from the World Ocean Database (WOD) are used (data labeled pSSTW). The biases of MBT and XBT are corrected based on currently available algorithms. The bias-corrected pSSTW over 1950–2016 and satellite-based SST from the European Space Agency (ESA) Climate Change Initiative (CCI) over 1992–2010 are used to evaluate commonly available SST analyses. These SST analyses are the Extended Reconstructed SST (ERSST), versions 5, 4, and 3b, the Met Office Hadley Centre Sea Ice and SST dataset (HadISST), and the Japan Meteorological Administration (JMA) Centennial In Situ Observation-Based Estimates of SST version 2.9.2 (COBE-SST2). Our comparisons show that the SST from COBE-SST2 is the closest to pSSTW and CCI in most of the Pacific, Atlantic, and Southern Oceans, which may result from its unique bias correction to ship observations. The SST from ERSST version 5 is more consistent with pSSTW than its previous versions over 1950–2016, and is more consistent with CCI than its previous versions over 1992–2010. The better performance of ERSST version 5 over its previous versions is attributed to its improved bias correction applied to ship observations with a baseline of buoy observations, and is seen in most of the Pacific and Atlantic.

Response of North Pacific and North Atlantic decadal variability to weak global warming

The Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Variability (AMV) are the two dominant low-frequency modes in the climate system. This research focused on the response of these two modes under weak global warming. Observational data were derived from the Hadley Center Sea Ice and Sea Surface Temperature dataset (HadISST) and coupled model outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Changes in PDO and AMV were examined using four models (bcc-csm1-1, CCSM4, IPSL-CM5A-LR, and MPI-ESM-LR) with long weak global warming scenarios (RCP2.6). These models captured the two low-frequency modes in both pre-industrial run and RCP2.6 run. Under weak global warming, the time scales of PDO and AMV significantly decreased while the amplitude only slightly decreased. Interestingly, the standard deviation of the North Pacific sea surface temperature anomaly (SSTA) decreased only in decadal time scale, and that of the North Atlantic SSTA decreased both in interannual and decadal time scales. The coupled system consists of a slow ocean component, which has a decadal time scale, and a fast atmospheric component, which is calculated by subtracting the decadal from the total. Results suggest that under global warming, PDO change is dominated by ocean dynamics, and AMV change is dominated by ocean dynamics and stochastic atmosphere forcing.

On the relationship between the early spring Indian Ocean's sea surface temperature (SST) and the Tibetan Plateau atmospheric heat source in summer

Abstract In this study, we evaluated the effects of springtime Indian Ocean's sea surface temperature (SST) on the Tibetan Plateau's role as atmospheric heat source (AHS) in summer. The SST data of the National Oceanic and Atmospheric Administration (NOAA), European Centre for Medium-Range Weather Forecasts (ECMWF) and the Hadley Centre Sea Ice and Sea Surface Temperature data set (HadISST) and the reanalysis data of the National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) for 33 years (from 1979 to 2011) were used to analyze the relationship between the Indian Ocean SST and the Tibetan Plateau's AHS in summer, using the approaches that include correlation analysis, and lead–lag analysis. Our results show that some certain strong oceanic SSTs affect the summer plateau heat, specially finding that the early spring SSTs of the Indian Ocean significantly affect the plateau's ability to serve as a heat source in summer. Moreover, the anomalous atmospheric circulation and transport of water vapor are related to the Plateau heat variation.

Improved decadal climate prediction in the North Atlantic using EnOI-assimilated initial condition

Decadal prediction experiments of Beijing Climate Center climate system model version 1.1 (BCC-CSM1.1) participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation (SODA) reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature (SST) of the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation (EnOI). Then a suite of decadal re-forecasts launched annually over the period 1961–2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal oscillation (AMO), which is consistent with the better skill of Atlantic meridional overturning circulation (AMOC) predicted by the re-forecasts. We conclude that the EnOI assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.

Ship accessibility predictions for the Arctic Ocean based on IPCC CO2 emission scenarios

Changes in the extent of Arctic sea ice, which have resulted from climate change, offer new opportunities to use the Northern Sea Route (NSR) and Northwest Passage (NWP) for shipping. However, choosing to navigate the Arctic Ocean remains challenging due to the limited accessibility of ships and the balance between economic gain and potential risk. As a result, more precise and detailed information on both weather and sea ice change in the Arctic are required. In this study, a high-resolution global AGCM was used to provide detailed information on the extent and thickness of Arctic sea ice. For this simulation, we have simulated the AMIP-type simulation for the present-day climate during 31 years from 1979 to 2009 with observed SST and Sea Ice concentration. For the future climate projection, we have performed the historical climate during 1979-2005 and subsequently the future climate projection during 2010-2099 with mean of four CMIP5 models due to the two Representative Concentration Pathway scenarios (RCP 8.5 and RCP 4.5). First, the AMIP-type simulation was evaluated by comparison with observations from the Hadley Centre sea-ice and Sea Surface Temperature (HadlSST) dataset. The model reflects the maximum (in March) and minimum (in September) sea ice extent and annual cycle. Based on this validation, the future sea ice extents show the decreasing trend for both the maximum and minimum seasons and RCP 8.5 shows more sharply decreasing patterns of sea ice than RCP 4.5. Under both scenarios, ships classified as Polar Class (PC) 3 and Open-Water (OW) were predicted to have the largest and smallest number of ship-accessible days (in any given year) for the NSR and NWP, respectively. Based on the RCP 8.5 scenario, the projections suggest that after 2070, PC3 and PC6 vessels will have year-round access across to the Arctic Ocean. In contrast, OW vessels will continue to have a seasonal handicap, inhibiting their ability to pass through the NSR and NWP.

Intrareef variations in Li/Mg and Sr/Ca sea surface temperature proxies in the Caribbean reef‐building coral Siderastrea siderea

Caribbean sea surface temperatures (SSTs) have increased at a rate of 0.2°C per decade since 1971, a rate double that of the mean global change. Recent investigations of the coral Siderastrea siderea on the Belize Mesoamerican Barrier Reef System (MBRS) have demonstrated that warming over the last 30 years has had a detrimental impact on calcification. Instrumental temperature records in this region are sparse, making it necessary to reconstruct longer SST records indirectly through geochemical temperature proxies. Here we investigate the skeletal Sr/Ca and Li/Mg ratios of S. siderea from two distinct reef zones (forereef and backreef) of the MBRS. Our field calibrations of S. siderea show that Li/Mg and Sr/Ca ratios are well correlated with temperature, although both ratios are 3 times more sensitive to temperature change in the forereef than in the backreef. These differences suggest that a secondary parameter also influences these SST proxies, highlighting the importance for site- and species-specific SST calibrations. Application of these paleothermometers to downcore samples reveals highly uncertain reconstructed temperatures in backreef coral, but well-matched reconstructed temperatures in forereef coral, both between Sr/Ca-SSTs and Li/Mg-SSTs, and in comparison to the Hadley Centre Sea Ice and Sea Surface Temperature record. Reconstructions generated from a combined Sr/Ca and Li/Mg multiproxy calibration improve the precision of these SST reconstructions. This result confirms that there are circumstances in which both Li/Mg and Sr/Ca are reliable as stand-alone and combined proxies of sea surface temperature. However, the results also highlight that high-precision, site-specific calibrations remain critical for reconstructing accurate SSTs from coral-based elemental proxies.

Secular spring rainfall variability at local scale over Ethiopia: trend and associated dynamics

Spring rainfall secular variability is studied using observations, reanalysis, and model simulations. The joint coherent spatio-temporal secular variability of gridded monthly gauge rainfall over Ethiopia, ERA-Interim atmospheric variables and sea surface temperature (SST) from Hadley Centre Sea Ice and SST (HadISST) data set is extracted using multi-taper method singular value decomposition (MTM-SVD). The contemporaneous associations are further examined using partial Granger causality to determine presence of causal linkage between any of the climate variables. This analysis reveals that only the northwestern Indian Ocean secular SST anomaly has direct causal links with spring rainfall over Ethiopia and mean sea level pressure (MSLP) over Africa inspite of the strong secular covariance of spring rainfall, SST in parts of subtropical Pacific, Atlantic, Indian Ocean and MSLP. High secular rainfall variance and statistically significant linear trend show consistently that there is a massive decline in spring rain over southern Ethiopia. This happened concurrently with significant buildup of MSLP over East Africa, northeastern Africa including parts of the Arabian Peninsula, some parts of central Africa and SST warming over all ocean basins with the exception of the ENSO regions. The east-west pressure gradient in response to the Indian Ocean warming led to secular southeasterly winds over the Arabian Sea, easterly over central Africa and equatorial Atlantic. These flows weakened climatological northeasterly flow over the Arabian Sea and southwesterly flow over equatorial Atlantic and Congo basins which supply moisture into the eastern Africa regions in spring. The secular divergent flow at low level is concurrent with upper level convergence due to the easterly secular anomalous flow. The mechanisms through which the northwestern Indian Ocean secular SST anomaly modulates rainfall are further explored in the context of East Africa using a simplified atmospheric general circulation model (AGCM) coupled to mixed-layer oceanic model. The rainfall anomaly (with respect to control simulation), forced by the northwestern Indian Ocean secular SST anomaly and averaged over the 30-year period, exhibits prevalence of dry conditions over East and equatorial Africa in agreement with observation. The atmospheric response to secular SST warming anomaly led to divergent flow at low levels and subsidence at the upper troposphere over regions north of 5° S on the continent and vice versa over the Indian Ocean. This surface difluence over East Africa, in addition to its role in suppressing convective activity, deprives the region of moisture supply from the Indian Ocean as well as the Atlantic and Congo basins.

Long-Range Correlations of Global Sea Surface Temperature.

Scaling behaviors of the global monthly sea surface temperature (SST) derived from 1870–2009 average monthly data sets of Hadley Centre Sea Ice and SST (HadISST) are investigated employing detrended fluctuation analysis (DFA). The global SST fluctuations are found to be strong positively long-range correlated at all pertinent time-intervals. The value of scaling exponent is larger in the tropics than those in the intermediate latitudes of the northern and southern hemispheres. DFA leads to the scaling exponent α = 0.87 over the globe (60°S~60°N), northern hemisphere (0°N~60°N), and southern hemisphere (0°S~60°S), α = 0.84 over the intermediate latitude of southern hemisphere (30°S~60°S), α = 0.81 over the intermediate latitude of northern hemisphere (30°N~60°N) and α = 0.90 over the tropics 30°S~30°N [fluctuation F(s) ~ sα], which the fluctuations of monthly SST anomaly display long-term correlated behaviors. Furthermore, the larger the standard deviation is, the smaller long-range correlations (LRCs) of SST in the corresponding regions, especially in three distinct upwelling areas. After the standard deviation is taken into account, an index χ = α * σ is introduced to obtain the spatial distributions of χ. There exists an obvious change of global SST in central east and northern Pacific and the northwest Atlantic. This may be as a clue on predictability of climate and ocean variabilities.