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From January through March 2017, a series of extreme precipitation events occurred in coastal Peru, causing severe floods with hundreds of human casualties and billions of dollars in economic losses. The extreme precipitation was a result of unusually strong recurrent patterns of atmospheric and oceanic conditions, including extremely warm coastal sea surface temperatures (SST) and weakened trade winds. These climatic features and their causal relationship with the Peruvian precipitation were examined. Diagnostic analysis and model experiments suggest that an atmospheric forcing in early 2017, which was moderately linked to the Trans-Niño Index (TNI), initiated the local SST warming along coastal Peru that later expanded to the equator. In January 2017, soil moisture was increased by an unusual expansion of Amazonian rainfall. By March, localized and robust SST warming provided positive feedback to the weakening of the trade winds, leading to increased onshore wind and a subsequent enhancement in rainfall. The analysis points to a tendency towards more frequent and stronger variations in the water vapor flux convergence along the equator, which is associated with the increased precipitation in coastal Peru.

International audience; The observation and simulation of the variability of coastal sea level are impacted by various uncertainties, such as measurement errors and sampling biases, unresolved processes , and model and forcing biases. Ocean model simulations suggest that another uncertainty should be taken into account for the attribution of sea-level changes. Global ocean simulations indeed show that resolving mesoscale turbulence (even partly) promotes the emergence of low-frequency (LF) chaotic intrinsic variability (CIV) which causes substantial random fluctuations of sea level up to multiple decades in eddy-active regions of the world ocean. This random LFCIV is superimposed on the atmospherically forced (or simply "forced") fluctuations, which are directly controlled by the atmospheric variability. We show from a large ensemble of global oceanic hindcasts that this multi-decadal LFCIV leaves a substantial imprint on the long-term trends (1993-2015) of coastal sea level: over 17-20% of the global ocean coastal area, in particular along the coastlines of the northwestern Pacific and Indian Oceans, and around the Gulf of Mexico, random sea-level trends may blur their atmospherically forced counterpart, such that simulated (and potentially observed) coastal sea-level trends cannot be unambiguously attributed to atmospheric or anthropic causes. The steric and manometric sea-level change contributions of these uncertainties are discussed, suggesting that they mostly come from the manometric sea-level trends near the coasts.

Sea level has risen significantly in the recent decades and is expected to rise further based on recent climate projections. Ocean reanalyses that synthetize information from observing networks, dynamical ocean general circulation models, and atmospheric forcing data offer an attractive way to evaluate sea level trend and variability and partition the causes of such sea level changes at both global and regional scales. Here, we review recent utilization of reanalyses for steric sea level trend investigations. State-of-the-science ocean reanalysis products are then used to further infer steric sea level changes. In particular, we used an ensemble of centennial reanalyses at moderate spatial resolution (between 0.5 &times, 0.5 and 1 &times, 1 degree) and an ensemble of eddy-permitting reanalyses to quantify the trends and their uncertainty over the last century and the last two decades, respectively. All the datasets showed good performance in reproducing sea level changes. Centennial reanalyses reveal a 1900&ndash, 2010 trend of steric sea level equal to 0.47 &plusmn, 0.04 mm year&minus, 1, in agreement with previous studies, with unprecedented rise since the mid-1990s. During the altimetry era, the latest vintage of reanalyses is shown to outperform the previous ones in terms of skill scores against the independent satellite data. They consistently reproduce global and regional upper ocean steric expansion and the association with climate variability, such as ENSO. However, the mass contribution to the global mean sea level rise is varying with products and its representability needs to be improved, as well as the contribution of deep and abyssal waters to the steric sea level rise. Similarly, high-resolution regional reanalyses for the European seas provide valuable information on sea level trends, their patterns, and their causes.

nterannual variability of Ocean Heat Content (OHC) is intimately linked to ocean water mass changes. Water mass characteristics are imprinted at the ocean surface and are modulated by climate variability on interannual to decadal time scales. In this study, we investigate the water mass change and their variability using an isopycnal decomposition of the OHC. For that purpose, we address the thickness and temperature changes of these water masses using both individual temperature‐salinity profiles and optimal interpolated products from Argo data. Isopycnal decomposition allows us to characterize the water masses interannual variability and decadal trends of volume and OHC. During the last decade (2006–2015), much of interannual and decadal warming is associated with Southern Hemisphere Subtropical Mode Water (STMW) and Subantarctic Mode Water (SAMW), particularly in the South Pacific Eastern Subtropical Mode Water (SPESTMW), the Southeastern Indian Subantarctic Mode Water (SEISAMW) and the Southern Pacific SAMW (SPSAMW). In contrast, Antarctic Intermediate Water (AAIW) in the Southern Hemisphere and North Atlantic STMW (NASTMW) in the Northern Hemisphere have cooled. This OHC interannual variability is mainly explained by volume (or mass) changes of water masses related to the isopycnal heaving. The forcing mechanisms and interior dynamics of water masses are discussed in the context of the wind stress change and ocean adjustment occurring at interannual time scale. Key points Upper global Ocean mode water are the hot spots of 2006‐2015 ocean heat trend Southern hemisphere mode water gained volume and buoyancy over 2006‐2015 Wind forcing and oceanic adjustment may partly explain the interannual mode water volume change

This study analyzes the atmospheric forcing of upwelling occurrence along differently oriented coastlines of the southern Baltic Sea basin. The mean daily sea surface temperature (SST) data from the summer seasons (June&ndash, August) of the years 1982&ndash, 2017 made the basis for the detection of upwelling cases. For the atmospheric part of the analysis, monthly indices of four macroscale circulation patterns were used: North Atlantic Oscillation (NAO), Scandinavian (SCAND), East Atlantic (EA) and East Atlantic/Western Russia (EATL/WRUS). In order to identify the local airflows and wind conditions, zonal and meridional regional circulation indices were constructed and introduced to the analysis. Within the southern Baltic Sea basin, upwelling occurs most frequently along the zonally oriented southern coasts of Sweden, and least frequently along the southern (Polish) and eastern (Lithuanian-Latvian) coasts. Among the macroscale circulation patterns, the SCAND has the strongest impact on the horizontal flow of surface sea waters in the southern Baltic, which triggers upwelling. The summer NAO and EA appeared to have a weak effect on upwelling occurrence, and EATL/WRUS have the smallest impact. Local circulation indices allowed us to recognize the atmospheric control of upwelling frequency better than the indices of the macroscale patterns. Anomalies in upwelling frequency are their highest at the positive/negative phase of the zonal circulation, particularly along the southern and eastern coast of the southern Baltic Sea basin.

Purpose. The purpose of the paper is to assess quality of meteorological information for the Azov–Black Sea basin derived from the ERA-Interim reanalysis (the European Centre for Medium-Range Weather Forecasts), and to examine possibility of using the obtained data for presetting atmospheric forcing in the numerical hydrodynamic model of the Black and Azov seas. Methods. The analysis is based on comparison of the annual average ERA-Interim fields with the measurement data on the atmospheric circulation parameters represented in hydrometeorological atlases. The most significant discrepancies between the ERA-Interim fields and the data of climatic arrays are noted and, consequently, the discrepancy-related potential errors arising in reproducing water circulation in the indicated seas are considered. Results and Conclusions. The comparative analysis showed that, for a number of the parameters, the reanalysis data were in qualitative agreement with the measurements. The highest discrepancies (up to 70%) were revealed in the precipitation field nearby the Caucasian coast in autumn. Such an error in the boundary conditions can negatively affect both the sea surface salinity distribution in the numerical modeling and, therefore, reproduction of thermohaline circulation in this region of the sea. A significant error in the results of numerical modeling can also be induced by the discrepancies in the wind fields. In the ERA-Interim data, the wind speed module is generally understated by 7% over the whole Black Sea in a spring-summer period, and by 20–25% in the Azov Sea throughout a year. The direction of the resultant wind is the most distorted in summer, whereas in winter, the deviations are significant only in the southeastern part of the Black Sea. The best agreement is observed between the temperature and air humidity fields, and the climatic arrays’ data: the discrepancies between the values of these parameters are minimal.

Purpose. The process of the upper layer mixing in the western Black Sea during the heightened heat flux from its surface in the winter season is studied. The mechanism forming average temperature both in the upper mixed layer and in the layer below the lower boundary in the seasonal thermocline is analyzed. Methods and Results. Measurements of the thermistor chain drifters as well as the MERRA reanalysis data and the simulation results of the regional model RegCM4 which included the ERA-Interim reanalysis (2012–2014) data as the input information, were involved in the calculations. It is revealed that growth of the wind speed and the total heat flux from the sea surface was accompanied by increase of the current velocity that resulted in intensification of turbulent mixing in the upper layer (40–50 m depth) and lowering of its average temperature. It is also found out that increase of the current velocity was followed by deepening of the seasonal thermocline and cold intermediate layer; whereas its decrease contributed to elevation of cold waters from the lower boundary of the upper mixed layer to the smaller depths. At the same time, diminution of the cold intermediate layer depth was observed. At lowering of the current velocity, this resulted in decrease of the upper mixed layer average temperature, and growth of the temperature in the layer below the seasonal thermocline. Conclusions. The current velocity intensification induces deepening of the seasonal thermocline and the cold intermediate layer; whereas its decrease promotes elevation of these layers to smaller depths. This process results in lowering of the upper mixed layer average temperature.

Purpose. The aim of the paper was to compare the results of numerical experiments on reconstructing seasonal thermal evolution of the sea ice thickness with the data of in situ observations of the ice state in the northeastern part of the Taganrog Bay. Methods and Results. Characteristics of the ice state in the northeastern part of the Taganrog Bay were studied using the previously developed thermodynamical model of sea ice. The data of the European Center for Medium-Range Weather Forecasts ERA-Interim, regional prognostic model SKIRON and the array of daily eight (with 3-hour intervals) observations of the basic meteorological parameters (All-Russian Research Institute of Hydrometeorological Information – World Data Center (RIHMI – WDC)) obtained at the meteorological station Taganrog, were used in the numerical experiments as the atmospheric forcing. The modeling results were compared with the in situ data for the winter seasons in 2007/2008–2010/2011. It is shown that the characteristics of the snow-ice cover resulted from application of various meteorological data as the external forcing, can be significantly different. Conclusions. The highest similarity between the modeled ice thickness seasonal variation and the one reconstructed using the observations data was obtained at applying the RIHMI – WDC data array. In this case, both thickness and the basic stages of the snow-ice cover evolution in the Taganrog Bay were adequately reproduced in the model. As compared to the in situ data, the results of the models based on the SKIRON and ERA-Interim data were mainly overestimating and underestimating, respectively. It is related, to a great extent, to determination of the precipitation amount, the prognostic values of which in ERA-Interim are higher than those in SKIRON. However, even in the calculations taking no account of atmospheric precipitation or in those for the ice seasons when the atmospheric precipitation is very insignificant, the SKIRON based model provides the higher values of ice thickness than the values resulted from the ERA-Interim based model. Analysis of the modeling results shows that adequate reconstruction of the ice state characteristics in the Azov Sea requires preliminary setting of the thermodynamic model depending on the chosen data array used as the atmospheric forcing.

The contribution of high-frequency wind to the Peruvian upwelling system during 2014&ndash, 2016 was studied using the Regional Ocean Modeling System (ROMS), forced by four different temporal resolution (six-hourly, daily, weekly, and monthly) wind forcing. A major effect of the high-frequency wind is its warming of the water at all depths along the Peruvian coast. The mechanism for the temperature changes induced by high-frequency wind forcing was analyzed through heat budget analysis, which indicated a three-layer structure. Vertical advection plays a leading role in the warming of the mixed layer (0&ndash, 25 m), and enhanced vertical mixing balances the warming effect. Analysis suggests that around the depths of 25&ndash, 60 m, vertical mixing warms the water by bringing heat from the surface to deeper depths. In waters deeper than 60 m, the effect of vertical mixing is negligible. The differences among the oceanic responses in the sensitivity experiments suggest that wind forcing containing variabilities at higher than synoptic frequencies must be included in the atmospheric forcing in order to properly simulate the Peru upwelling system.

Marine-terminating glaciers in the Canadian Arctic Archipelago have retreated in response to atmospheric, not oceanic, warming., The Canadian Arctic Archipelago contains >300 glaciers that terminate in the ocean, but little is known about changes in their frontal positions in response to recent changes in the ocean-climate system. Here, we examine changes in glacier frontal positions since the 1950s and investigate the relative influence of oceanic temperature versus atmospheric temperature. Over 94% of glaciers retreated between 1958 and 2015, with a region-wide trend of gradual retreat before ~2000, followed by a fivefold increase in retreat rates up to 2015. Retreat patterns show no correlation with changes in subsurface ocean temperatures, in clear contrast to the dominance of ocean forcing in western Greenland and elsewhere. Rather, significant correlations with surface melt indicate that increased atmospheric temperature has been the primary driver of the acceleration in marine-terminating glacier frontal retreat in this region.

Winter data of surface ocean temperature (SST), salinity (SSS) and CO2 fugacity (fCO(2)) collected on the VOS M/V Nuka Arctica in the subpolar North Atlantic between 2004 and 2017 are used to establish trends, drivers, and interannual variability. Over the period, waters cooled and freshened, and the fCO(2) increased at a rate similar to the atmospheric CO2 growth rate. When accounting for the freshening, the inferred increase in dissolved inorganic carbon (DIC) was found to be approximately twice that expected from atmospheric CO2 alone. This is attributed to the cooling. In the Irminger Sea, fCO(2) exhibited additional interannual variations driven by atmospheric forcing through winter mixing. As winter fCO(2) in the region is close to the atmospheric, the subpolar North Atlantic has varied between being slightly supersaturated and slightly undersaturated over the investigated period.

A performance study of seven regional ocean configurations based on NEMO has been carried out for the Adriatic Sea over a common period (1980–2012). Assessed models differ in resolution, model physics, atmospheric forcing (forced vs. coupled models) and river discharges imposed within the Adriatic Sea. Models have been evaluated on the long-term temperature and salinity measurements in all of the Adriatic sub-basins, in particular within dense water collectors (Jabuka Pit and South Adriatic Pit) and dense water formation sites (northern and southern Adriatic). Adriatic-wide salinity content is mostly linked to the proper introduction of the overall water budget, rather than to the local river forcing. Forced models mostly overestimate temperature and salinity values. On average, coupled models better reproduce the thermohaline properties and processes, in particular the Adriatic-Ionian Bimodal Oscillating System (BiOS) reversals and its decadal variability. Wintertime heat losses are playing major role in defining the Adriatic Deep Water (ADW) transport rates in coupled models, while in forced models preconditioning in salinity is the most important factor. Further on, increase of resolution of the atmospheric forcing results in more realistic ocean behaviour, including dense water formation (DWF) in the complex coastal northern Adriatic. However, all models have large temperature biases and lower deep stratification at the dense water collector sites, indicating overall underrepresentation of the Adriatic DWF. Consequently, mixed-layer depth in the southern Adriatic is overestimated, reaching the bottom during some years. Ocean model resolution and river forcing seem to play a second-order role in defining the overall Adriatic-Ionian thermohaline properties, while inclusion of aerosol trend only slightly modified the BiOS reproduction., One simulation was performed using HPC resources from GENCI-[TGCC/CINES/IDRIS], Grant 0227). AVISO+ product were downloaded from https://www.aviso.altimetry.fr. This work is a part of the Med-CORDEX initiative (www.medcordex.eu) and a contribution to the MISTRALS/HyMeX programme. The support from Croatian Science Foundation is acknowledged through projects ADIOS [HRZZ grant IP-06-2016-1955] and SCOOL [HRZZ grant IP-2014-09-5747].

International audience; The analyses using reanalysis data and one-dimensional ocean model during the past decades (1963-2012) revealed that the epoch-dependent refreshening and reemergence mechanisms alternatively influenced the winter sea surface temperature (SST) in the Kuroshio recirculation gyre region. During 1971-1985, the refreshening mechanism due to the strong East Asian winter monsoon significantly contributed to the interannual winter SST variability, consistent with previous works. In contrast, the spring-initiated reemergence process better explains the winter SST variability for 1991-2005, a period corresponding to a declined winter monsoon. The classical winter-to-winter reemergence did not occur during either studied period; thus, the observed spring-to-winter reemergence is an original feature in the Kuroshio recirculation gyre region. The winter monsoon-related strong atmospheric forcing and prominent year-to-year variability of spring SST are important prerequisites for the regional refreshening and reemergence of the winter SST anomaly, respectively.

The scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we assimilate a state-of-the-art terrestrial water storage product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA's Catchment land surface model (CLSM) at the global scale, with the goal of generating groundwater storage time series that are useful for drought monitoring and other applications. Evaluation using in situ data from nearly 4,000 wells shows that GRACE data assimilation improves the simulation of groundwater, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The biggest improvements are observed in regions with large interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. The positive impacts of GRACE data assimilation are further demonstrated using observed low-flow data. CLSM and GRACE data assimilation performance is also examined across different permeability categories. The evaluation reveals that GRACE data assimilation fails to compensate for the lack of a groundwater withdrawal scheme in CLSM when it comes to simulating realistic groundwater variations in regions with intensive groundwater abstraction. CLSM-simulated groundwater correlates strongly with 12-month precipitation anomalies in low-latitude and midlatitude areas. A groundwater drought indicator based on GRACE data assimilation generally agrees with other regional-scale drought indicators, with discrepancies mainly in their estimated drought severity.

Historical ocean reanalyses combine ocean general circulation models with data assimilation schemes that ingest rescued observations. They can be used as a tool to investigate long-term changes in the ocean climate. However, large uncertainties, due to the poorly developed atmospheric and oceanic observing networks in early periods, still remain. Thus, detailed studies to assess the uncertainty and its time dependency are required to quantify the feasibility of historical ocean reanalyses for climate change assessment. In this work, we estimate the ocean heat content variability from a set of ocean reanalyses that cover the period 1900–2010. The ocean reanalyses include realizations forced by two different atmospheric reanalyses (20CRv2 and ERA-20C), combined with different data assimilation strategies, in the attempt to evaluate the relative weight of the atmospheric forcing and observation uncertainties on the resulting ocean heat content estimates. Results suggest that even when observing networks are poor, the observations are able to shape the upper ocean heat content variability, in terms of long-term trends and reproduction of individual warming/cooling events related to volcanic eruptions. The assimilation of in-situ profiles has an effect even on the sea surface temperature variability and is able to constrain the top 700 m heat content since the 1950s with respect to the uncertainty borne by the atmospheric forcing. The vertical propagation of the upper ocean observational information is however slow (with typically decadal time scale). Consequently, the total column heat content is constrained by observations only in the latest two decades. We conclude that upper ocean heat content diagnostics from historical ocean reanalyses bear the climate change signature and may be considered for long-term studies when complemented by proper uncertainty estimation.

Running ensemble of reanalyses or forecasts has proved successful at improving their performances, despite the cost. Generating ensemble simulations requires generating perturbations within the models, and for the assimilated observations and subsidiary conditions. This paper proposes a statistical model to generate atmospheric forcing random perturbations in a flexible and cheap way, for all the variables required to calculate bulk formulae. The training data are a ten-year set of differences between ERA-INTERIM (from ECMWF) and MERRA (from NASA) atmospheric forcing fields, unbiased with a high-pass filter. The model is designed to generate global spatially-varying multi-variate and unbiased perturbations with consistent spatial structures. Based on linear regressions, the model allows for regression coefficients and residual standard deviations to vary with the time of the year. Once defined, the model does not rely on any other external data to generate the perturbations, and can hence be used on- or off-line in the goal of seeding the ensemble more appropriately. Once designed, the model has been validated by comparing three years of generated perturbations to three years of differences between the reanalyses out of the training period. Statistical tests show that the distributions of the sets comply reasonably well, except for precipitation and snow. The major issues come from regions with high kurtosis or where no clear patterns can be established. In terms of structure, the perturbation standard deviation of both sets show similar patterns for all variables.

Climate change and increased coastal urbanization are causing low-lying coastlines to become increasingly susceptible to the threat of extreme water levels and coastal flooding. Robust decision-making on adaptation in the coastal zone, based on reliable ocean-modelling tools, is therefore crucially contingent on accurate assessments of current and future storm surge hazards. This accuracy relies considerably on the quality of the wind forcing used in the ocean models. In this paper, we use a high-resolution, regional 3D ocean model (HBM) covering the North Sea and Baltic Sea to simulate extreme water levels during three extreme storm surge events with different dynamics and patterns, in order to assess their impacts along Denmark’s coastlines, which are of varying levels of complexity. We demonstrate that the model is able to reproduce the observed extreme high-water levels accurately, indicating that the system is well suited for producing simulations of present and future projections of extreme storm surges with high resulting impacts and damage potentials. Additionally, we quantify the level at which acknowledged deficiencies in the otherwise most suitable atmospheric forcing data set influence the results of the storm surge simulations. We found that reducing the temporal resolution of the forcing data – that is, replacing two out of every six time stamps with linearly interpolated values – is preferable to using the original forcing data set when recurring noise is present in these time stamps. As a result, for given storm surge events, and depending on the stage reached in the storm’s evolution, mean absolute errors can be reduced by 4.5 cm. This emphasizes the importance of considering such model fluctuations when coupling high-resolution atmosphere and ocean models.

Aerosol optical and radiative properties, measured with the ground based sun-sky radiometer (under AERONET), were explored at Kanpur in the central and Gandhi College (Ballia) in the Eastern Indo-Gangetic Plain (IGP) in Northern India during January to July 2019 (non-lockdown) and 2020 (lockdown). This year 2020 is marked an overall reduction of 15.79% and 3.39% in aerosol optical depth (AOD) than year 2019 at Kanpur and Gandhi College respectively. Lockdown 1 (23rd March to 14th April 2020) showed a reduction of 52.52% and 42.22% in AOD compared to pre-lockdown condition at Kanpur and Gandhi College respectively. Higher values of angstrom exponent measured at Eastern region (1.13 ± 0.17) than central region (0.97 ± 0.26) indicating the dominance of fine particles at Gandhi College. There was an overall reduction of 1.31% in single scattering albedo (SSA) at Kanpur while 4.34% reduction was observed at Gandhi College in year 2020 than 2019. The resultant atmospheric forcing and heating rate shows 11.86% reduction at Kanpur while 35.27% increase at Gandhi College during the lockdown period in 2020 compared to 2019. However, these values were found to decrease by 23.48% and 15.07% at Kanpur and Gandhi College respectively during the strict lockdown period compared to year 2019.

NCEP/NCAR reanalysis data for the period of 1948–2017 were used to study the multidecadal variability of the hydrometeorological parameters (thermal, dynamic and humidity) in the Caspian Sea region. Polynomial approximations of the time series of the annual mean values indicated the non-linear nature and periodicity of the long-term variability of considered parameters. Three temporal intervals of duration 10–25 years with multidirectional trends of parameters changes are detected, which is considered as a manifestation of multidecadal variability. The North-Eastern wind regime prevails over the sea basin, with the major portion of heat advection into the region provided by zonal (Eastern) transport. Phases of air warming/cooling coincide with a weakening/strengthening of the Eastern wind transport. The time lag between the shift of dynamic and thermal (as well as humidity) regimes is about 6–8 years suggesting a leading role of the large-scale atmospheric forcing variations in the regional variability of thermal and humidity parameters. Specific humidity is positively correlated with air temperature and decreases/increases during periods of cooling/warming. In contrast, relative humidity and precipitation rate variations are negatively correlated with air temperature trends. Intensification of Eastern transport and associated cooling over the Caspian Sea coincide with a situation when the North Atlantic Oscillation (NAO) index decreases to negative values, and the East Atlantic-West Russian pattern (EAWR) index is significantly positive. On the contrary, weakening of the Eastern transport and warming occur during a period of sharp strengthening of the NAO, coinciding with strongly negative values of the EAWR index.

In recent decades, the global warming drives the huge ice sheet melting in northern hemisphere. Previous studies on long-term melting rates of Greenland have basically reached agreement, but there is still a lack of the knowledge of the pattern the short-term ice mass change, makes it difficult to fulfill the understanding of the mechanism of the ice sheet. In this study, we used Gravity Recovery and Climate Experiment (GRACE) RL06 data to derive the time series of mass variation of Greenland Ice Sheet (GrIS), from January 2003 to December 2015. We derived the short-term mass change rate during 2003-2015 and found that the GrIS has experienced four melting stages, i.e., a steady melting (-204.4 Gt/yr) phase form 2003 to 2009, an abrupt accelerating (-384.6 Gt/yr) phase form 2010 to 2012, an abnormal pause (+24.8 Gt/yr) year in 2013 and a recovering (-207.3 Gt/yr) phase from 2014 to 2015. In addition, using ensemble empirical mode decomposition (EEMD), the high frequency signal has been removed and the annual mass change has been studied, which shows inter-annual variability. Meanwhile, we correlated the annual mass change with the Greenland Blocking Index (GBI) and North Atlantic Oscillation (NAO) during summertime and the correlation for 2003-2015 was found at r=-0.63 between the summer GBI and the annual mass change, while r=0.57 between summer NAO and the annual mass change. Our results indicate that the short-term mass change of GrIS mainly forced by atmospheric variability.

Two historical ocean reanalyses that cover the period from 1900 to 2010 are performed. One ocean reanalysis (CHOR_AS) assimilates both SST and vertical profile data with a 3D-var assimilation scheme, while the other one (CHOR_RL) assimilates vertical profile data, but is nudged to monthly HadISST reconstructed fields. The reanalyses are thus designed to investigate the impact of different strategies for constraining the SST in long-term assimilation experiments and the feasibility of assimilating subsurface observations in the same kind of experiments. The atmospheric forcing comes from the ensemble mean of the 20th Century Reanalysis version 2(20CRv2). Due to biases particularly large at high latitudes, corrections are applied to the atmospheric forcing, based on the comparison with ERA-Interim during the overlapped period. In general, these ocean reanalyses capture trends and variability of key ocean parameters. A warm bias of SST in CHOR_AS in the first half of the century leads to incorrect long-term trends. However, SST anomalies in both CHOR_AS and CHOR_RL are realistically captured. Heat contents at 0-300 m, 0-700 m and 0-2000 m have an increasing trend in both CHOR_RL and CHOR_AS, consistent with available datasets for the second half of the century. In order to reproduce realistic mass transport, mixed layer depth and eddy kinetic energy, it is necessary to assimilate vertical profile data, although this leads to some discontinuities in the reanalysis time series. Based on these findings, we suggest ideas for the requirements of future historical ocean reanalyses, such as related to the necessity of applying bias correction and minimize the effects of the observing network discontinuities. Meanwhile, the comparison between CHOR_RL and CHOR_AS shows that both direct assimilation and nudging scheme have their advantages and disadvantages. A combination of these two schemes is desirable in future work.

There is a large uncertainty of snow water equivalent (SWE) in reanalyses and the Global Land Data Assimilation System (GLDAS), but the primary reason for this uncertainty remains unclear. Here several reanalysis products and GLDAS with different land models are evaluated and the primary reason for their deficiencies are identified using two high-resolution SWE datasets, including the Snow Data Assimilation System product and a new dataset for SWE and snowfall for the conterminous United States (CONUS) that is based on PRISM precipitation and temperature data and constrained with thousands of point snow observations of snowfall and snow thickness. The reanalyses and GLDAS products substantially underestimate SWE in the CONUS compared to the high-resolution SWE data. This occurs irrespective of biases in atmospheric forcing information or differences in model resolution. Furthermore, reanalysis and GLDAS products that predict more snow ablation at near-freezing temperatures have larger underestimates of SWE. Since many of the products do not assimilate information about SWE and snow thickness, this indicates a problem with the implementation of land models and pinpoints the need to improve the treatment of snow ablation in these systems, especially at near-freezing temperatures.

Two techniques for perturbing surface initial conditions in the regional ensemble system Aire Limitée Adaptation Dynamique Développement International-Limited Area Ensemble Forecasting (ALADIN-LAEF) are presented and investigated in this paper. The first technique is the noncycling surface breeding (NCSB), which combines short-range surface forecasts driven by perturbed atmospheric forcing and the breeding method for generating the perturbations on surface initial conditions. The second technique, which is currently used in the ALADIN-LAEF operational version, applies an ensemble of surface data assimilations (ESDA) in which the observations are randomly perturbed. Both techniques are evaluated over a two-month period from late spring to summer. The results show that the evaluation is more favorable to ESDA. In general, the ensemble forecasts of the observed near-surface meteorological variables (screen-level variables) of ESDA are more skillful than NCSB, in particular for 2-m temperature they are statistically more consistent and reliable. A slightly better statistical reliability for 2-m relative humidity and 10-m wind has been found as well. This could be attributed to the introduction of surface data assimilation in ESDA, which provides more accurate surface initial conditions. Moreover, the observation perturbation in ESDA helps to better estimate the initial condition uncertainties. For the forecast of precipitation and the upper-air variables in the lower troposphere, both ESDA and NCSB perform very similarly, having neutral impact.

Deep convection is presumed to be vital for the North Atlantic Meridional Overturning Circulation,even though observational evidence for the link remains inconclusive. Modeling studies have suggested thatconvection will weaken as a result of enhanced freshwater input. The emergence of anomalously low seasurface temperature in the subpolar North Atlantic has led to speculation that this process is already at work.Hereweshow that strong atmospheric forcing in the winter of 2014–2015, associated with a high North AtlanticOscillation (NAO) index, produced record mixed layer depths in the Irminger Sea. Local mixing removed thestratification of the upper 1400mand ventilated the basin to middepths resembling a state similar to themid-1990s when a positive NAO also prevailed. We show that the strong local atmospheric forcing ispredominantly responsible for the negative sea surface temperature anomalies observed in the subpolar NorthAtlantic in 2015 and that there is no evidence of permanently weakened deep convection.

High-resolution satellite sea surface temperature measurements (PATHFINDER dataset) indicate that the fronts at the boundary of the East China Sea (Taiwan front, Kuroshio frontal zone, and South Korean coastal front) appear as a unified dominating frontal structure when climatological averaging is applied. This structure is about 1200 km in length, spreads over the continental shelf from Taiwan to the Tsushima Islands, and separates productive seawaters from the oligotrophic oceanic waters. The Kuroshio frontal zone, incorporated into this structure, reveals interannual variability with periods consistent with El Nino–Southern Oscillation (4–5 years).

A numerical simulation using the Regional Ocean Modeling System (ROMS) indicates that there was significant interannual-to-interpentadal variability of along-shelf transport and water properties over the Middle Atlantic Bight (MAB) from 2004 to 2013. To examine the relative contribution from local atmospheric forcing versus remote oceanic open boundary forcing to such low-frequency variability, we implement a suite of process oriented numerical experiments. Results show that the interannual variability is dominated by remote forcing from the open boundaries of the region rather than by local atmospheric forcing. The penetration of the Labrador Current into the region contributes to a significant increase of along-shelf transport in the winters of 2009 and 2010. By contrast, the anti-cyclonic mesoscale eddies associated with the Gulf Stream decrease the background along-shelf jet and, in certain cases, even reverse the along-shelf transport. In addition, the along-shelf transport appears to possess an interpentadal variation, i.e., weaker during 2004–2008 but stronger during 2009–2013, which is found caused by the migration of the Gulf Stream.

The 2010 Deepwater Horizon oil spill in the Gulf of Mexico (GoM) was an environmental disaster, which highlighted the urgent need to predict the transport and dispersion of hydrocarbon. Although the variability of the atmospheric forcing plays a major role in the upper ocean circulation and transport of the pollutants, the air-sea interaction on various time scales is not well understood. This study provides a comprehensive overview of the atmospheric forcing and upper ocean response in the GoM from seasonal to diurnal time scales, using climatologies derived from long-term observations, in situ observations from two field campaigns, and a coupled model. The atmospheric forcing in the GoM is characterized by striking seasonality. In the summer, the time-average large-scale forcing is weak, despite occasional extreme winds associated with hurricanes. In the winter, the atmospheric forcing is much stronger, and dominated by synoptic variability on time scales of 3–7 days associated with winter storms and cold air outbreaks. The diurnal cycle is more pronounced during the summer, when sea breeze circulations affect the coastal regions and nighttime wind maxima occur over the offshore waters. Realtime predictions from a high-resolution atmosphere-wave-ocean coupled model were evaluated for both summer and winter conditions during the Grand LAgrangian Deployment (GLAD) in July–August 2012 and the Surfzone Coastal Oil Pathways Experiment (SCOPE) in November–December 2013. The model generally captured the variability of atmospheric forcing on all scales, but suffered from some systematic errors.

High-resolution satellite sea surface temperature (SST) measurements (PATHFINDER dataset) have been used to confirm an existence of persistent thermal frontal zones in the Black Sea. Fronts have been revealed in the winter season between the intensively cooling shallow northwestern area and warmer waters of central part, and in spring-summer season between the actively warming waters of the southeastern part and cooler central area. Interannual and quasi-decadal variability of the northwestern front have been documented, as well as a high negative correlation of its intensity with the winter-mean SST.

We quantify differences in ocean model simulations derived solely from atmospheric uncertainties and investigate how they relate to overall model errors as inferred from comparisons with data. For this purpose, we use a global configuration of the MITgcm to simulate 4 ocean solutions for 2000–2009 using 4 reanalysis products (JRA-25, MERRA, CFSR and ERA-Interim) as atmospheric forcing. The simulations are compared against observations and against each other for selected variables (temperature, sea-level, sea-ice, streamfunctions, meridional heat and freshwater transports). Forcing-induced differences are comparable in magnitude to model-observation misfits for most near-surface variables in the tropics and sub-tropics, but typically smaller at higher latitudes and polar regions. Forcing-derived differences are expectedly largest near the surface and mostly limited to the upper 1000 m but can also be seen as deep as 4000 m, especially in regions of deep water formation. Errors are not necessarily local in nature and can be advected to different basins. Results indicate that while forcing adjustments might suffice in optimization procedures of near-surface fields and at low-to-mid latitudes, other control parameters are likely needed elsewhere. Forcing-induced differences can be dominated by large spatial scales and specific time scales (e.g. annual), and thus appropriate error covariances in space and time need to be considered in optimization methodologies.

The temporal and spatial fluctuations of sea surface temperature (SST) and chlorophyll a (Chla) levels due to atmospheric forcing in Mexico’s third largest tropical coastal lagoon (Tamiahua Lagoon), located in the western Gulf of Mexico, was examined from July 2002 to May 2012. The main hypothesis of this study is that SST and Chla levels are modulated by the exchange of heat fluxes from the atmosphere and by rainfall (river runoff). The atmosphere supplies heat (555.05 ± 42.31 W m–2) to Tamiahua Lagoon, which implies that the temperature of the lagoon over the period analyzed (~27 oC) was higher than normal in the coastal zone. Precipitation regulates Chla levels during the rainy season because the cross-correlation values were high (r > 0.61) and the phase lag of the rainy season with the Chla time series was typically 0 to –1 month. El Nino/Southern Oscillation phases affected the rainfall patterns and, thus, Chla concentrations in the lagoon. As expected, the lagoon showed eutrophic conditions throughout the year (Chla concentrations >5 mg m–3), with maximum values in the summer, when warm and wet conditions prevail. The annual scale is responsible for most of the variability in the two data sets. Seasonally, both oceanographic data sets showed three different water types, which, in both cases, were more variable at the southern and northern inlets and more homogenous in the central part of the lagoon. Las fluctuaciones espaciales y temporales de la temperatura superficial del mar (TSM) y las concentraciones de clorofila a (Chla) debidas a forzamientos atmosfericos en la tercer laguna costera tropical mas grande de Mexico (laguna de Tamiahua), localizada en el oeste del golfo de Mexico, fueron estudiadas de julio de 2000 a mayo de 2012. La principal hipotesis de este estudio es que la TSM y las concentraciones de Chla son moduladas por el intercambio de calor de la atmosfera y por la lluvia (descarga de rios). La atmosfera introduce calor (555.05 ± 42.31 W m–2) a la laguna de Tamiahua, lo cual implica que la temperatura de la laguna durante el periodo analizado (~27 oC) fue mayor que la observada en la zona costera. La precipitacion regula las concentraciones de Chla durante la temporada de lluvias porque los valores de las correlaciones cruzadas entre ambos parametros fueron altos (r > 0.61) y la fase de retardo de la temporada de lluvias con las series de tiempo de la Chla generalmente fue de 0 a –1 mes. Las fases de El Nino/Oscilacion del Sur afectaron los patrones de lluvia y, por lo tanto, las concentraciones de Chla en la laguna. La laguna muestra condiciones eutroficas a lo largo del ano (concentraciones de Chla >5 mg m–3), con valores maximos en verano, cuando las condiciones son calidas y humedas. La escala anual es responsable de la mayor variabilidad en ambos conjuntos de datos. Estacionalmente, ambos conjuntos de datos oceanograficos muestran tres diferentes tipos de agua, los cuales, para ambos conjuntos de datos, fueron mas variables en las entradas de la zona sur y norte y fueron mas homogeneas en la region central de la laguna.

Radar altimetry, when corrected for tides, atmospheric forcing of the sea surface, and the effects of density variations and mean and time-variable currents, provides an along-track realization of the marine geoid. In this study we investigate whether and how such an ‘altimetric-hydrodynamic’ geoid over the North Sea can serve for validating satellite-gravimetric geoids. Our results indicate that, using ERS-2 and ENVISAT along-track altimetry and water levels from the high-resolution operational circulation model BSHcmod, we do find distinct differences in RMS fits for various state-of-the art satellite-only models (beyond degree 145 for GRACE-only, and beyond degree 185 for GOCE models) and for combined geoid models, very similar as seen in GPS-levelling validations over land areas. We find that, at spectral resolution of up to about 200, an RMS fit as low as about 7 cm can be obtained for the most recent GOCE-derived models such as GOCO05S. This is slightly above what we expect from budgeting in...

To investigate the impact of radiosonde data on the sea-ice forecast in the Northern Sea Route during an extremely developed cyclone on 6 August 2012, a series of numerical experiments were conducted using an ice-ocean coupled model with fine horizontal resolution (approximately 2.5 km). The atmospheric forcing data used for the model were forecast data with (CTL) and without (OSE) initialization by radiosonde data over the Fram Strait, obtained by the German R/V Polarstern, and the European Centre for Medium-Range Weather Forecasts Interim reanalysis data. All numerical experiments were run from 06:00 UTC on 3 August 2012 to 00:00 UTC on 8 August 2012 with an initial sea-ice concentration and thickness derived from the Advanced Microwave Scanning Radiometer 2 satellite data. The root-mean-square error and correlation coefficient for the sea-ice distribution showed that the CTL simulation predicted better the sea-ice distribution in the Northern Sea Route than the OSE simulation. This occurred in particular from 6 to 7 August when the cyclone became strong. The thermodynamic processes resulted in the difference in the sea-ice thickness due to changes in the vertical energy fluxes. However, the differences in the sea-ice concentration and velocity were caused mainly by the dynamics, particularly the difference in wind fields, rather than the thermodynamics. These results suggest that radiosonde data are effective in improving the forecast accuracy of the sea-ice distribution. Therefore, errors in the weather forecast data would have a substantial impact on the safety of ship navigation and the sea-ice distribution.

The aim of this study was to investigate the variability of the water exchanges in the Curonian Lagoon based on the hydraulic regime and the atmospheric forcings. A finite element hydrodynamic model has been applied to the Curonian Lagoon to simulate the circulation patterns for ten years. With the help of a transport-diffusion model the salinity distribution and the renewal times of the Curonian Lagoon have been investigated when forced by river runoff, wind and Baltic Sea level fluctuations. The hydrodynamic model has been validated using in situ salinity measurements. Model results show that the variability depends mainly on seasonal changes in hydrographic forcing and on the dominant wind regimes that prevail over the Curonian Lagoon. Exchanges between the southern and the northern part of the lagoon are mostly depended on the wind forcing and are much less influenced by the river discharge. However, when looking at the water renewal time, the most important factor is the river discharge into the lagoon. Other physical forcings are only marginally determining the renewal time, and not even ice cover is able to influence it. Even if ice cover is strongly inhibiting the exchanges between southern and northern lagoon, it is basically not able to change the absolute value of the renewal times.

Global satellite sea surface temperature (SST) measurements and NCEP/NCAR reanalysis wind data for the period of 1982–2009 have been used to study the relationship between long-term variability of oceanic frontal zones (OFZ) and large-scale atmospheric forcing. Statistically significant positive correlations between the maximum magnitude of the meridional gradient of zonally averaged SST and meridional shear of zonal wind (which is an estimate of the Ekman convergence intensity) were found for all subpolar and subtropical OFZ of the World Ocean. Variability of the latitudinal position of OFZ cores may be associated with Ekman advection variability due to zonal wind variations. Strengthening of zonal wind results in a shift of subpolar OFZ cores to the south/north in the Northern/Southern hemispheres.

Large-scale patterns of positive temperature anomalies persisted throughout the surface waters of the North Pacific Ocean during 2014–2015. In the Southern California Current System, measurements by our sustained network of underwater gliders reveal the coastal effects of the recent warming. Regional upper ocean temperature anomalies were greatest since the initiation of the glider network in 2006. Additional observed physical anomalies included a depressed thermocline, high stratification, and freshening; induced biological consequences included changes in the vertical distribution of chlorophyll fluorescence. Contemporaneous surface heat flux and wind strength perturbations suggest that local anomalous atmospheric forcing caused the unusual oceanic conditions.

Uncertainty in continental shelf air-sea CO2 fluxes motivated us to investigate the impact of interannual and seasonal variabilities in atmospheric forcing on the capacity of three shelf regions along the U.S. eastern continental shelf to act as a sink or source of atmospheric CO2. Our study uses a coupled biogeochemical-circulation model to simulate scenarios of “present-day” and “future-perturbed” mesoscale forcing variability. Overall, the U.S. eastern continental shelf acts as a sink for atmospheric CO2. There is a clear gradient in air-sea CO2 flux along the shelf region, with estimates ranging from −0.6 Mt C yr−1 in the South Atlantic Bight (SAB) to −1.0 Mt C yr−1 in the Mid-Atlantic Bight (MAB) and −2.5 Mt C yr−1 in the Gulf of Maine (GOM). These fluxes are associated with considerable interannual variability, with the largest interannual signal exhibited in the Gulf of Maine. Seasonal variability in the fluxes is also evident, with autumn and winter being the strongest CO2 sink periods and summer months exhibiting some outgassing. In our future-perturbed scenario spatial differences tend to cancel each other out when the fluxes are integrated over the MAB and GOM, resulting in only minor differences between future-perturbed and present-day air-sea CO2 fluxes. This is not the case in the SAB where the position of the along-shelf gradient shifts northward and the SAB becomes a source of CO2 to the atmosphere (0.7 Mt C yr−1) primarily in response to surface warming. Our results highlight the importance of temperature in regulating air-sea CO2 flux variability.

A series of meteotsunamis hit a few locations in the Mediterranean and Black Seas during 22– 27 June 2014. Meteot- sunamis were particularly numerous on 25 and 26 June in the Adriatic Sea, where at least six harbours and bays were stricken by ˇ powerful waves: strongest events occurred in Vela Luka (Korcula Island), a known meteotsunami hot-spot, where waves reached ˇ height of *3 m, and in Rijeka dubrovacka Bay, where strong *5 m/s currents accompanied *2.5 m high waves. Inten- sification of high-frequency sea level activity was observed at both the eastern and western Adriatic tide gauge stations, with maximum recorded wave heights reaching *68 cm (Ortona, Italy). A series of individual air pressure disturbances characterized by pronounced rates of air pressure change (up to 2.4 hPa/5 min), limited spatial extent (*50 km) and high temporal variability, propagated over the Adriatic on 2 days in question. Numerical hydrodynamic model SCHISM forced by measured and idealised air pressure distur- bances was utilised to reproduce the observed Adriatic sea level response. Several important conclusions were reached: (1) meteotsunamis occurring at various parts of the coast were gen- erated by different atmospheric air pressure disturbances ; (2) topographic influence can be removed from sea level spectra by computing spectral signal- to-background ratios ; the result, being related to the external forcing, resembles atmospheric pressure spectra ; (3) sea response is strongly dependant on details of atmospheric forcing ; and (4) over complex bathymetries, like the middle and south Adriatic ones, numerous effects, including Proudman resonance, edge waves, strong topographical enhance- ment and refractions on the islands placed on the pathway of atmospheric disturbances should be taken into account to fully understand meteotsunami generation and dynamics. An in- depth numerical study is planned to supplement the latter conclusion and to quantify contribution of each process.

The Community Land Model version 3.5 is driven by an observation-based meteorological dataset to simulate soil moisture over China for the period 1951–2008. A method for identifying the patterns of interannual variability that arise from slow (potentially predictable) and intraseasonal (unpredictable) variability is also applied; this allows identification of the sources of the predictability of seasonal soil moisture in China, during March–April–May (MAM), June–July–August (JJA), September–October–November (SON) and December–January–February (DJF). The potential predictability (slow-to-total) of the soil moisture above 1 m is high, with lowest value of 0.76 in JJA and highest value of 0.94 in DJF. The spatial distribution of the potential predictability comprises a northwest–southeast gradient, with a minimum center over East China and a maximum center over the northwest. The most important source of predictability is from the soil moisture persistence, which generally accounts for more than 50 % of the variability in soil moisture. The SSTs in the Indian Ocean, the North Atlantic and the eastern tropical Pacific Oceans are also identified as important sources of variability in the soil moisture, during MAM, JJA and SON/DJF, respectively. In addition, prolonged linear trends in each season are an important source. Using the slow principal component time series as predictands, a statistical scheme for the seasonal forecasting of soil moisture across China is developed. The prediction skills, in terms of the percentage of explained variance for the verification period (1992–2008), are 59, 51, 62 and 77 % during MAM–DJF, respectively. This is considerably higher than a normal grid prediction scheme.

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemble forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.

This study investigates the chemical composition of PM 10 aerosols at Varanasi, in the central Indo-Gangetic Plain (IGP) during April to July 2011, with emphasis on examining the contribution of elemental carbon (EC) to the estimates of direct aerosol radiative effect (DARE). PM 10 samples are analysed for carbonaceous aerosols (Organic Carbon, OC and EC) and water-soluble ionic species (WSIS: Cl − , SO 4 2− , NO 3 − , PO 4 2− NH 4 + , Na + , K + , Mg 2+ and Ca 2+ ) and several diagnostic ratios (OC/EC, K + /EC, etc) have been also used for studying the aerosol sources at Varanasi. PM 10 mass concentration varies between 53 and 310 μg m −3 (mean of 168 ± 73 μg m −3 ), which is much higher than the National and International air quality standards. The OC mass concentration varies from 6 μg m −3 to 24 μg m −3 (mean of 12 ± 5 μg m −3 ; 7% of PM 10 mass), whereas EC ranges between 1.0 and 14.3 μg m −3 (4.4 ± 3.9 μg m −3 ; ∼3% of PM 10 mass). The relative low OC/EC of 3.9 ± 2.0 and strong correlation (R 2 = 0.82) between them suggest the dominance of primary carbonaceous aerosols. The contribution of WSIS to PM 10 is found to be ∼12%, out of which ∼57% and 43% are anions and cations, respectively. The composite DARE estimates via SBDART model reveal significant radiative effect and atmospheric heating rates (0.9–2.3 K day −1 ). Although the EC contributes only ∼3% to the PM 10 mass, its contribution to the surface and atmospheric forcing is significantly high (37–63% and 54–77%, respectively), thus playing a major role in climate implications over Varanasi.

We show two major modes of East Asian marine heatwaves (MHWs) associated with two contrasting sea surface temperature patterns over the subtropical western North Pacific (WNP). In the first MHW mode, ocean warming over East Asia occurs along with the subtropical WNP from the earlier winter by an El Niño-Southern Oscillation. The basin-wide ocean warming is finally intensified to an extreme warming state around East Asia, where a high-pressure region in zonal waves across the Eurasian continent passes. In contrast, at the early stage, the second MHW mode is unfavorable with ocean cooling. However, MHWs over East Asia occur due to a significant intensification of a zonally elongated high-pressure zone in response to anomalous subtropical convection in addition to mid-latitude zonal waves. Due to the importance of persistent ocean warming as well as immediate atmospheric forcing, MHW inducible oceanic and atmospheric interactions are clearly distinguishable from those of atmospheric heatwaves.

Natural and artificial systems containing water resources that have different salinities can be used to generate salinity-gradient energy (SGE). In this paper, the feasibility of implementing SGE in hypersaline coastal lagoons is addressed, taking the coastal lagoon La Carbonera in Yucatan, Mexico, as an exemplary case. A realistic approach to the exploitation conditions and potential that could occur in a SGE plant in these ecosystems is presented. We first analyzed the variability of salinity and temperature in the three characteristic zones of the coastal lagoon and the correlation of these variables with atmospheric forcing. This was done using 1 year records of in situ measurements. Then the theoretical potential for SGE and the intra-annual variability of that potential were assessed considering the three possible harvesting configurations of mixing among fresh, sea, and hypersaline water. Results show that the thermohaline structure may vary significantly for the three locations at different time scales (diurnal to seasonal) depending on the tides, winds, air temperature, atmospheric pressure, and solar radiation. That suggests that the highest annual energy yield would be obtained from alternating throughout the year among the mixing configurations, depending on the specific seasonal thermohaline structure of the lagoon.

An early warning system for drought events can provide valuable information for decision makers dealing with water resources management and international aid. However, predicting such extreme events is still a big challenge. In this study, we compare two approaches for drought predictions based, respectively, on forecasted precipitation derived from the extended ENSemble system of the ECMWF, and on forecasted Monthly Occurrence Anomaly of Weather Regimes (MOAWRs) also derived from the ECMWF model. Results show that the MOAWRs approach outperforms the one based on forecasted precipitation in winter in the northern and eastern parts of the European continent, where more than 65 % of droughts are detected one month in advance. While, the approach based on forecasted precipitation achieves better performance in predicting drought events in central and eastern Europe in both spring and summer, when the local atmospheric forcing could be the key driver of the precipitation. Sensitivity tests also reveal the challenges in predicting small-scales and onset drought events at longer lead times. Finally, in most of the cases, the ENSemble system of the ECMWF successfully represents the observed large scale atmospheric patterns, depicted by the MOAWRs, associated with drought events over Europe.

Twenty years of in situ soil moisture data from more than 300 stations located in China are used to perform an evaluation of two surface soil moisture datasets: a microwave-based multi-satellite product (ECV-SM) and the land surface model simulation from the Community Land Model 4.5 (CLM4.5). Both soil moisture products generally show a good agreement with in situ observations. The ECV-SM product has a low bias, with a root mean square difference (RMSD) of 0.075 m3 m-3, but shows a weak correlation with in situ observations (R = 0.41). In contrast, the CLM4.5 simulation, forced by an observation-based atmospheric forcing data, produces better temporal variation of surface soil moisture (R = 0.52), but shows a clear overestimation (bias = 0.05 m3 m-3) and larger RMSD (0.09 m3 m-3), especially in eastern China, caused by inaccurate descriptions of soil characteristics. The ECV-SM product is more likely to be superior in semi-arid regions, mainly because of the accurate retrievals and high observation density, but inferior over areas covered by dense vegetation. Furthermore, it shows a stable to slightly increasing performance in China, except for a decrease during the 2007–2010 blending period. Results from this study can provide comprehensive insight into the performances of the two soil moisture datasets in China, which will be useful for their improvements in merging algorithms or model simulations and for applications in soil moisture data assimilation.

Despite distinct geographic distributions of top-of-the-atmosphere radiative forcing, anthropogenic greenhouse gases and aerosols have been found to produce similar patterns of climate response in atmosphere-and-ocean coupled climate model simulations. Understanding surface energy flux changes, a crucial pathway by which atmospheric forcing is communicated to the ocean, is a vital bridge to explaining the similar full atmosphere-and-ocean responses to these disparate forcings. Here we analyze the fast, atmosphere-driven change in surface energy flux caused by present-day greenhouse gases vs aerosols to elucidate its role in shaping the subsequent slow, coupled response. We find that the surface energy flux response patterns achieve roughly two-thirds of the anti-correlation seen in the fully coupled response, driven by Rossby waves excited by symmetric changes to the land–sea contrast. Our results suggest that atmosphere and land surface processes are capable of achieving substantial within-hemisphere homogenization in the climate response to disparate forcers on fast, societally-relevant timescales., Anthropogenic aerosol and greenhouse gas concentrations are spatially uncorrelated, but the climate response to each shows a similar spatial pattern. Here the authors show that two-thirds of the spatial similarity in the full response manifests through fast-acting atmosphere and land surface processes alone.