Coupled Ocean Atmosphere System Research Articles

Diurnal to interannual variability of low‐level cloud cover over western equatorial Africa in May–October

AbstractThis study examines the diurnal to interannual variations of the stratiform cloud cover in May–October (1971–2019) from a 3‐hourly station database and from ERA5 reanalyses over western equatorial Africa (WEA). The main diurnal variations of the local‐scale fraction and genus of stratiform clouds are synthesized into three canonical diurnal types (i.e., “clear,” “clear afternoon,” “cloudy” days). The interannual variations of frequencies of the three diurnal types during the cloudiest months (JJAS) are mostly associated with two main mechanisms: a meridional shallow overturning cell associating more “cloudy” and less “clear” and “clear afternoon” days to anomalous southerlies below 900 hPa over and around WEA, anomalous ascent around 5°–7°N, anomalous northerlies between 875 and 700 hPa, and anomalous subsidence over the equatorial Atlantic. This circulation is strongly related to interannual variations of the equatorial Atlantic upwelling (i.e., more clouds when the upwelling is strong) associated with a meridional shift of the Intertropical Convergence Zone over the Tropical Atlantic and adjacent continents. The second mechanism operates mostly in the zonal direction and involves again the coupled ocean–atmosphere system over the equatorial Atlantic, but also the remote El Niño–Southern Oscillation (ENSO). An anomalously cold equatorial Atlantic drives increased low‐level westerlies toward the Congo Basin. Warm ENSO events promote broad warm and easterly anomalies in the middle and upper troposphere, which increase the local static stability, and thus the local stratiform cloud cover over WEA. The present study suggests new mechanisms responsible for interannual variations of stratiform clouds in WEA, thus providing avenues of future research regarding the stability of the stratiform cloud deck under the ongoing differential warming of tropical ocean and land masses.

Changing Water Cycle under a Warming Climate: Tendencies in the Carpathian Basin

In this mini-review, we present evidence from the vast literature that one essential part of the coupled atmosphere–ocean system that makes life on Earth possible, the water cycle, is exhibiting changes along with many attributes of the global climate. Our starting point is the 6th Assessment Report of the IPCC, which appeared in 2021, where the almost monograph-size Chapter 8, with over 1800 references, is devoted entirely to the water cycle. In addition to listing the main observations on the Earth globally, we focus on Europe, particularly on the Carpathian (Pannonian) Basin. We collect plausible explanations of the possible causes behind an observably accelerating and intensifying water cycle. Some authors still suggest that changes in the natural boundary conditions, such as solar irradiance or Earth’s orbital parameters, explain the observations. In contrast, most authors attribute such changes to the increasing greenhouse gas concentrations since the industrial revolution. The hypothesis being tested, and which has already yielded convincing affirmative answers, is that the hydrological cycle intensifies due to anthropogenic impacts. The Carpathian Basin, a part of the Danube watershed, including the sub-basin of the Tisza River, is no exception to these changes. The region is experiencing multiple drivers contributing to alterations in the water cycle, including increasing temperatures, shifting precipitation regimes, and various human impacts.

Satellite retrieval of the linear polarization components of the water-leaving radiance in open oceans.

Atmospheric correction (AC) of polarized radiances acquired by polarization satellite sensors, remains a challenge due to the complex radiative transfer processes of the coupled ocean-atmosphere system. In this study, we proposed an innovative polarized AC algorithm built on the near-infrared band (PACNIR) with an emphasis on the retrieval of the linear polarization components of the water-leaving radiance in clear open oceans. This algorithm was based on the black ocean assumption in the near-infrared band and fitted polarized radiance measurements along multiple observation directions with nonlinear optimized processing. Our retrieval algorithm notably inverted the linearly polarized components of the water-leaving radiance and aerosol parameters. Compared with that of the simulated linear polarization components of the water-leaving radiance via the vector radiative transfer model for the studied sea regions, the mean absolute error of the PACNIR-retrieved linearly polarized components (nQw and nUw) exhibited a magnitude of 10-4, while the magnitude of that of the simulated nQw and nUw data was 10-3. Moreover, the PACNIR-retrieved aerosol optical thicknesses at 865 nm exhibited a mean absolute percentage error of approximately 30% relative to in situ values obtained from Aerosol Robotic Network-Ocean Color (AERONET-OC) sites. The PACNIR algorithm could facilitate AC of the polarized data provided by the next generation of multiangle polarization satellite ocean color sensors.

SCIATRAN software package (V4.6): update and further development of aerosol, clouds, surface reflectance databases and models

Abstract. Since the initiation of development at the Institute of Environmental Physics (IUP), University of Bremen, in 1994, the radiative transfer model SCIATRAN (formerly GOMETRAN) has been continuously improved and new versions have been released (Rozanov et al., 1997, 2002, 2005, 2014, 2017). In the course of development, the SCIATRAN software package became capable of simulating radiative transfer processes through the Earth's atmosphere or coupled atmosphere–ocean system with a variety of approaches to treat the sphericity of the atmosphere (plane-parallel, pseudo-spherical, approximately spherical and full-spherical solutions) in both scalar and vector modes. Supported by a variety of built-in databases and parameterizations, these capabilities made SCIATRAN widely used for various remote-sensing applications related to the retrieval of atmospheric trace gases and characteristics of aerosols, clouds and surfaces. This paper presents an overview of the cloud, aerosol and surface (CAS) databases and models implemented in the SCIATRAN software package (V4.6) and provides some recommendations on their usage. The new implementations offer potential users a flexible interface to perform radiative transfer simulations: (1) accounting for multilayer liquid water, ice and mixed-phase clouds; (2) employing typical aerosol-type parameterizations (including vertical variability) used in the satellite and model communities as well as updated databases; (3) including various surface bidirectional reflectance distribution function (BRDF) and albedo models for land, vegetation, ocean, snow and melt ponds on sea ice. The most recent version of the radiative transfer model SCIATRAN is freely available at the website of the IUP, University of Bremen: http://www.iup.physik.uni-bremen.de/sciatran (last access: November 2022).

The Impact of Southern Ocean Topographic Barriers on the Ocean Circulation and the Overlying Atmosphere

Abstract Southern Ocean bathymetry constrains the path of the Antarctic Circumpolar Current (ACC), but the bathymetric influence on the coupled ocean–atmosphere system is poorly understood. Here, we investigate this impact by respectively flattening large topographic barriers around the Kerguelen Plateau, Campbell Plateau, Mid-Atlantic Ridge, and Drake Passage in four simulations in a coupled climate model. The barriers impact both the wind and buoyancy forcing of the ACC transport, which increases by between 4% and 14% when barriers are removed individually and by 56% when all barriers are removed simultaneously. The removal of Kerguelen Plateau bathymetry increases convection south of the plateau and the removal of Drake Passage bathymetry reduces convection upstream in the Ross Sea. When the barriers are removed, zonal flattening of the currents leads to sea surface temperature (SST) anomalies that strongly correlate to precipitation anomalies, with correlation coefficients ranging between r = 0.92 and r = 0.97 in the four experiments. The SST anomalies correlate to the surface winds too in some locations. However, they also generate circumpolar waves of sea level pressure (SLP) anomalies, which induce remote wind speed changes that are unconnected to the underlying SST field. The meridional variability in the wind stress curl contours over the Mid-Atlantic Ridge, the Kerguelen Plateau, and the Campbell Plateau disappears when these barriers are removed, confirming the impact of bathymetry on surface winds. However, bathymetry-induced wind changes are too small to affect the overall wave-3 asymmetry in the Southern Hemisphere westerlies. Removal of Southern Hemisphere orography is also inconsequential to the wave-3 pattern. Significance Statement Several studies in the past have pointed to the controlling effect of bathymetry on currents in the Southern Ocean circulation, but a clear idea of the importance of the major topographic barriers in the Southern Ocean is lacking. By removing these barriers systematically in a coupled climate model, we can evaluate their impact on several important components of the climate system, such as the Antarctic Circumpolar Current (ACC) pathways and strength, Antarctic Bottom Water formation, sea surface temperature, overlying winds, air–sea fluxes, and even precipitation. This helps in our understanding of what controls the pathways of the ACC and how much it matters for climate.

Multiscale variability of China’s historical flood/drought index and precipitation teleconnections with ENSO using wavelet analyses

Studies of the low-frequency variabilities of key climate variables are often handicapped by the limited length of available instrumental observations. To tackle this, the use of a set of historical flood/drought index (FDI) spanning from AD 1470 to 2000 for 120 sites in China has been made to investigate the multiscale temporal variability of annual precipitation by applying wavelet methods. The analyses reveal oscillating components of the FDI time series from the decadal to multi-decadal, and to the quasi-centennial range, as well as in the interannual range. Furthermore, the relationships of the FDI with the dominant mode of oscillations in the coupled ocean–atmosphere system, i.e., the El Niño-Southern Oscillation (ENSO) index, on a range of time scales have been probed by cross wavelet transform and wavelet coherence methods. Statistically significant coherence between FDI and ENSO index time series has been found for regions in eastern China south of the Yangtze River (inclusive) at the decadal to multi-decadal time scale (10- to 50-yr) after 1750, as well as for north China on the 10- to 30-year range in the eighteenth century. The FDI is less coherent with the ENSO index for other regions of China. The results of the present study may add to our understanding of the connections between long-term changes of annual precipitation and large-scale oscillations in the coupled ocean–atmosphere system, and provide a scientific basis for developing policies to adapt to future changes in water abundance.

Development of a forecast-oriented kilometre-resolution ocean–atmosphere coupled system for western Europe and sensitivity study for a severe weather situation

Abstract. To improve high-resolution numerical environmental prediction, it is essential to represent ocean–atmosphere interactions properly, which is not the case in current operational regional forecasting systems used in western Europe. The objective of this paper is to present a new forecast-oriented coupled ocean–atmosphere system. This system uses the state-of-the-art numerical models AROME (cy43t2) and NEMO (v3.6) with a horizontal resolution of 2.5 km. The OASIS coupler (OASIS3MCT-4.0), implemented in the SurfEX surface scheme and in NEMO, is used to perform the communications between models. A sensitivity study of this system is carried out using 7 d simulations from 12 to 19 October 2018, characterized by extreme weather events (storms and heavy precipitation) in the area of interest. Comparisons with in situ and L3 satellite observations show that the fully coupled simulation reproduces the spatial and temporal evolution of the sea surface temperature and 10 m wind speed quantitatively well. Sensitivity analysis of ocean–atmosphere coupling shows that the use of an interactive and high-resolution sea surface temperature (SST), in contrast to actual numerical weather prediction (NWP) where SST is constant, modifies the atmospheric circulation and the location of heavy precipitation. Simulated oceanic fields show a large sensitivity to coupling when compared to the operational ocean forecast. The comparison to two distinct forced ocean simulations highlights that this sensitivity is mainly controlled by the change in the atmospheric model used to drive NEMO (AROME vs. IFS operational forecast), and less by the interactive air–sea exchanges. In particular, the oceanic boundary layer depths can vary by more than 40 % locally, between the two ocean-only experiments. This impact is amplified by the interactive coupling and is attributed to positive feedback between sea surface cooling and evaporation.

An ensemble neural network atmospheric correction for Sentinel-3 OLCI over coastal waters providing inherent model uncertainty estimation and sensor noise propagation

Accurate atmospheric correction (AC) is a prerequisite for quantitative ocean colour remote sensing and remains a challenge in particular over coastal waters. Commonly AC algorithms are validated by establishing a mean retrieval error from match-up analysis, which compares the satellite-derived surface reflectance with concurrent ground radiometric observations. Pixel-based reflectance uncertainties however, are rarely provided by AC algorithms and those for the operational Ocean and Land Colour Instrument (OLCI) marine reflectance product are not yet recommended for use. AC retrieval errors and uncertainties directly determine the quality with which ocean colour products can be estimated from the marine surface reflectance. Increasingly there is also the need for reflectance uncertainty products to be used as data assimilation inputs into biogeochemical models.This paper describes the development of a new coastal AC algorithm for Sentinel-3 OLCI that provides pixel-based estimation of the inherent model inversion uncertainty and sensor noise propagation. The algorithm is a full-spectral model-based inversion of radiative transfer (RT) simulations in a coupled atmosphere–ocean system using an ensemble of artificial neural networks (ANN) that were initialized differently during the training process, but composed of the same network architecture. The algorithm has been validated against in-situ radiometric observations across a wide range of optical water types, and has been compared with the latest EUMETSAT operational Level 2 processor IPF-OL-2 v7.01.In this analysis we found that the ensemble ANN showed improved performance over the operational Level 2 processor with a band-averaged (412–708 nm) mean absolute percentage error (MAPE) of 16% compared to 37% and a four-times lower band-averaged bias of -0.00045 sr-1.In the ensemble inversion process we account for three uncertainty components: (1) the total model variance that describes the variance of the data from the different ANNs, (2) the prediction variance of the mean, which is based on calculations of the RT simulations and (3) the instrument noise variance of the mean by propagating the OLCI spectral signal-to-noise ratios (SNR). To study algorithm performance and to quantify the contribution of the different uncertainty components to the total uncertainty, we applied the algorithm to an optically complex full resolution (FR) test scene covering coastal waters of the Great Barrier Reef, Australia. The uncertainties associated with the instrument noise variance were found to be two orders of magnitude lower than the uncertainty components of the prediction and total model variances. The overall largest uncertainty component in our uncertainty framework is attributed to the total model inversion error from averaging the responses of the slightly different adapted networks in the ensemble. The algorithm is made publicly available as a Python/C plugin for the Sentinel Application Platform (SNAP).

Multiscale fractal dimension analysis of a reduced order model of coupled ocean–atmosphere dynamics

Abstract. Atmosphere and ocean dynamics display many complex features and are characterized by a wide variety of processes and couplings across different timescales. Here we demonstrate the application of multivariate empirical mode decomposition (MEMD) to investigate the multivariate and multiscale properties of a reduced order model of the ocean–atmosphere coupled dynamics. MEMD provides a decomposition of the original multivariate time series into a series of oscillating patterns with time-dependent amplitude and phase by exploiting the local features of the data and without any a priori assumptions on the decomposition basis. Moreover, each oscillating pattern, usually named multivariate intrinsic mode function (MIMF), represents a local source of information that can be used to explore the behavior of fractal features at different scales by defining a sort of multiscale and multivariate generalized fractal dimensions. With these two complementary approaches, we show that the ocean–atmosphere dynamics presents a rich variety of features, with different multifractal properties for the ocean and the atmosphere at different timescales. For weak ocean–atmosphere coupling, the resulting dimensions of the two model components are very different, while for strong coupling for which coupled modes develop, the scaling properties are more similar especially at longer timescales. The latter result reflects the presence of a coherent coupled dynamics. Finally, we also compare our model results with those obtained from reanalysis data demonstrating that the latter exhibit a similar qualitative behavior in terms of multiscale dimensions and the existence of a scale dependency of the statistics of the phase-space density of points for different regions, which is related to the different drivers and processes occurring at different timescales in the coupled atmosphere–ocean system. Our approach can therefore be used to diagnose the strength of coupling in real applications.

Subsurface Oceanic Structure Associated With Atmospheric Convectively Coupled Equatorial Kelvin Waves in the Eastern Indian Ocean

AbstractAtmospheric convectively coupled equatorial Kelvin waves (CCKWs) are a major tropical weather feature strongly influenced by ocean–atmosphere interactions. However, prediction of the development and propagation of CCKWs remains a challenge for models. The physical processes involved in these interactions are assessed by investigating the oceanic response to the passage of CCKWs across the eastern Indian Ocean and Maritime Continent using the NEMO ocean model analysis with data assimilation. Three‐dimensional life cycles are constructed for “solitary” CCKW events. As a CCKW propagates over the eastern Indian Ocean, the immediate thermodynamic ocean response includes cooling of the ocean surface and subsurface, deepening of the mixed layer depth, and an increase in the mixed layer heat content. Additionally, a dynamical downwelling signal is observed two days after the peak in the CCKW westerly wind burst, which propagates eastward along the Equator and then follows the Sumatra and Java coasts, consistent with a downwelling oceanic Kelvin wave with an average phase speed of 2.3 m s−1. Meridional and vertical structures of zonal velocity anomalies are consistent with this framework. This dynamical feature is consistent across distinct CCKW populations, indicating the importance of CCKWs as a source of oceanic Kelvin waves in the eastern Indian Ocean. The subsurface dynamical response to the CCKWs is identifiable up to 11 days after the forcing. These ocean feedbacks on time scales longer than the CCKW life cycle help elucidate how locally driven processes can rectify onto longer time‐scale processes in the coupled ocean–atmosphere system.

Development of a coupled atmosphere–ocean typhoon regional assimilation and prediction system for operational typhoon forecasting by the Chinese Academy of Meteorological Sciences—part I: experiments of Western North Pacific typhoons in 2016

Typhoons can interact intensely with oceans, and the atmosphere–ocean interaction has an enormous impact on the intensity and structure of typhoons. To consider the impact of typhoon–ocean interactions, a regional coupled atmosphere–ocean system for operational forecasting of Western North Pacific typhoons is established in this paper based on a public coupled atmosphere–ocean framework and in accordance with the operational typhoon forecasting conditions and system settings of the Chinese Academy of Meteorological Sciences. The new coupled system is fully validated and used for hindcasting experiments on all typhoons in 2016. The results show that the computational cost associated with the proposed coupled system is approximately 5.33 times that of the atmosphere-only system. A comparison of the hindcasts of the 2016 typhoons using the atmosphere-only system and the proposed coupled system reveals that the use of the coupled system can obviously reduce the forecasted intensity error by approximately 10–20% but not the typhoon track error. In addition, some of the intrinsic structural characteristics of typhoons influence the effectivity of the coupled system. Specifically, when typhoons have a high intensity and a low translational speed, move in an East-West or turning direction, and are at 20°N–25°N latitude, the forecasts can be relatively significantly improved by the coupled system; otherwise, the improvement is not obvious.

Use of A Neural Network-Based Ocean Body Radiative Transfer Model for Aerosol Retrievals from Multi-Angle Polarimetric Measurements

For aerosol retrieval from multi-angle polarimetric (MAP) measurements over the ocean it is important to accurately account for the contribution of the ocean-body to the top-of-atmosphere signal, especially for wavelengths <500 nm. Performing online radiative transfer calculations in the coupled atmosphere ocean system is too time consuming for operational retrieval algorithms. Therefore, mostly lookup-tables of the ocean body reflection matrix are used to represent the lower boundary in an atmospheric radiative transfer model. For hyperspectral measurements such as those from Spectro-Polarimeter for Planetary Exploration (SPEXone) on the NASA Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) mission, also the use of look-up tables is unfeasible because they will become too big. In this paper, we propose a new method for aerosol retrieval over ocean from MAP measurements using a neural network (NN) to model the ocean body reflection matrix. We apply the NN approach to synthetic SPEXone measurements and also to real data collected by SPEX airborne during the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. We conclude that the NN approach is well capable for aerosol retrievals over ocean, introducing no significant error on the retrieved aerosol properties

Radiometric Sensitivity and Signal Detectability of Ocean Color Satellite Sensor Under High Solar Zenith Angles

New generation ocean color imagers on geostationary orbits are designed to provide a much higher temporal resolution along with enhanced spatial and spectral resolutions that will open up obvious opportunities for improving the sampling frequency and resolving diurnal variability of phytoplankton and other biogeochemical properties in dynamic coastal waters. Despite the capabilities of such new generation sensors to detect the diurnal cycles of various ocean phenomena, there is a lack of knowledge on their radiometric sensitivity and signal detectability for observing the ocean color at morning or evening hours. This paper aims to explore the capability of geostationary satellite ocean color sensor for detecting ocean biogeochemical properties [chlorophyll (CHL); total suspended matter (TSM); colored dissolved organic matter (CDOM)] under high solar zenith angles (SZAs). The analysis is based upon simulations from the vector radiative transfer model for the coupled ocean–atmosphere system (PCOART-SA), which considers the earth curvature effects. The unitless differential signal-to-noise ratio ( $\Delta $ SNR) is used as a discriminant parameter to indicate the radiometric sensitivity to variation of different biogeochemical properties. The results showed that the SZAs have a significant impact on the signal detectability for CHL variation. For typical shelf water (CHL $= 1\,\,\mu \text{g}$ /L, TSM = 1 mg/L, CDOM = 0.15 m−1), with the typical observation zenith angle (OZA) = 30°, changes on the order of $\Delta $ CHL $= 0.024\,\,\mu \text{g}$ /L (2.4% to background CHL) were detectable when SZA = 30°; when SZA > 75°, the detectable minimal $\Delta $ CHL increased to $0.77~\mu \text{g}$ /L (77%), indicating the difficulty of detecting CHL under high SZA. For CDOM, the detectability of changes ( $\Delta $ CDOM) was also found to be closely related to the SZAs, i.e., changes on the order of ten times depending on the SZA conditions. However, even under extremely high SZA conditions (SZA = 80°, OZA = 30°), $\Delta $ CDOM = 0.007 m−1 which is about 4.7% of the background CDOM was still detectable at 412 nm. On the other hand, under high SZA conditions (SZA = 80°, OZA = 30°), $\Delta $ TSM = 0.211 mg/L (2.1% to the background TSM) was also detectable. Overall, our results indicate that under high SZAs conditions, the geostationary satellite ocean color sensor may experience difficulty in detecting a slight change in CHL variation in productive waters, but it still can detect small changes in TSM and CDOM contents despite a reduced sensitivity at the steeper SZAs.

Assessment of ocean analysis and forecast from an atmosphere–ocean coupled data assimilation operational system

Abstract. The development of coupled atmosphere–ocean prediction systems with utility on short-range numerical weather prediction (NWP) and ocean forecasting timescales has accelerated over the last decade. This builds on a body of evidence showing the benefit, particularly for weather forecasting, of more correctly representing the feedbacks between the surface ocean and atmosphere. It prepares the way for more unified prediction systems with the capability of providing consistent surface meteorology, wave and surface ocean products to users for whom this is important. Here we describe a coupled ocean–atmosphere system, with weakly coupled data assimilation, which was operationalised at the Met Office as part of the Copernicus Marine Environment Service (CMEMS). We compare the ocean performance to that of an equivalent ocean-only system run at the Met Office and other CMEMS products. Sea surface temperatures in particular are shown to verify better than in the ocean-only systems, although other aspects including temperature profiles and surface currents are slightly degraded. We then discuss the plans to improve the current system in future as part of the development of a “coupled NWP” system at the Met Office.

Moisture Sources for East Asian Precipitation: Mean Seasonal Cycle and Interannual Variability

ABSTRACT This study investigates the moisture sources that supply East Asian (EA) precipitation and their interannual variability. Moisture sources are tracked using the Water Accounting Model-2layers (WAM-2layers), based on the Eulerian framework. WAM-2layers is applied to five subregions over EA, driven by the ERA-Interim reanalysis from 1979 to 2015. Due to differences in regional atmospheric circulation and in hydrological and topographic features, the mean moisture sources vary among EA subregions. The tropical oceanic source dominates southeastern EA, while the extratropical continental source dominates other EA subregions. The moisture sources experience large seasonal variations, due to the seasonal cycle of the EA monsoon, the freeze–thaw cycle of the Eurasian continent, and local moisture recycling over the Tibetan Plateau. The interannual variability of moisture sources is linked to interannual modes of the coupled ocean–atmosphere system. The negative phase of the North Atlantic Oscillation increases moisture transport to northwestern EA in winter by driving a southward shift in the midlatitude westerly jet over the Mediterranean Sea, the Black Sea, and the Caspian Sea. Atmospheric moisture lifetime is also reduced due to the enhanced westerlies. In summers following El Niños, an anticyclonic anomaly over the western North Pacific increases moisture supplied from the South China Sea to the southeastern EA and shortens the traveling distance. A stronger Somali Jet in summer increases moisture to the Tibetan Plateau and therefore increases precipitation over the eastern Tibetan Plateau. The methods and findings in this study can be used to evaluate hydrological features in climate simulations.

The coupled ocean–atmosphere hydrologic cycle

The freshwater cycle has in the present study been traced as one integrated process in the coupled ocean–atmosphere system for both present and possible future climates simulated with an Earth-System Model. A method based on water-mass conservation was used in order to calculate mass fluxes of water from regions of evaporation to regions of precipitation. These fluxes include not only advection of moisture by the winds but also the vertical water-mass transport due to precipitation forming hence a mass-conserved 3D water-mass transport field. Six atmospheric hydrological cells were revealed, which cross the sea surface, where they join the oceanic overturning circulation. These atmospheric water cells can be interpreted as an extension of the oceanic overturning circulation, since the otherwise open ocean streamlines at the surface continue into the atmosphere due to evaporation and back into the ocean due to precipitation. Although these atmospheric water cells are related to the usual air cells, they are only half part of the coupled water cells and located differently. The future-climate scenario shows that the mid- and high-latitude atmospheric water-mass cells will transport more moisture towards the poles as well as increase of the northward cross-Equatorial atmospheric water-mass transport.

50 Years of Satellite Remote Sensing of the Ocean

AbstractThe development of the technologies of remote sensing of the ocean was initiated in the 1970s, while the ideas of observing the ocean from space were conceived in the late 1960s. The first global view from space revealed the expanse and complexity of the state of the ocean that had perplexed and inspired oceanographers ever since. This paper presents a glimpse of the vast progress made from ocean remote sensing in the past 50 years that has a profound impact on the ways we study the ocean in relation to weather and climate. The new view from space in conjunction with the deployment of an unprecedented amount of in situ observations of the ocean has led to a revolution in physical oceanography. The highlights of the achievement include the description and understanding of the global ocean circulation, the air–sea fluxes driving the coupled ocean–atmosphere system that is most prominently illustrated in the tropical oceans. The polar oceans are most sensitive to climate change with significant consequences, but owing to remoteness they were not accessible until the space age. Fundamental discoveries have been made on the evolution of the state of sea ice as well as the circulation of the ice-covered ocean. Many surprises emerged from the extraordinary accuracy and expanse of the space observations. Notable examples include the determination of the global mean sea level rise as well as the role of the deep ocean in tidal mixing and dissipation.

Precipitation Sensitivity to Local Variations in Tropical Sea Surface Temperature

AbstractThe driving of tropical precipitation by the variability of the underlying sea surface temperature (SST) plays a critical role in the atmospheric general circulation. To assess the precipitation sensitivity to SST variability, it is necessary to observe and understand the relationship between precipitation and SST. However, the precipitation–SST relationships from any coupled atmosphere–ocean system can be difficult to interpret given the challenge of disentangling the SST-forced atmospheric response and the atmospheric intrinsic variability. This study demonstrates that the two components can be isolated using uncoupled atmosphere-only simulations, which extract the former when driven by time-varying SSTs and the latter when driven by climatological SSTs. With a simple framework that linearly combines the two types of uncoupled simulations, the coupled precipitation–SST relationships are successfully reproduced. Such a framework can be a useful tool for quantitatively diagnosing tropical air–sea interactions. The precipitation sensitivity to SST variability is investigated with the use of uncoupled simulations with prescribed SST anomalies, where the influence of atmospheric intrinsic variability on SST is deactivated. Through a focus on local precipitation–SST relationships, the precipitation sensitivity to local SST variability is determined to be predominantly controlled by the local background SST. In addition, the strength of the precipitation response increases monotonically with the local background SST, with a very sharp growth at high SSTs. These findings are supported by basic principles of moist static stability, from which a simple formula for precipitation sensitivity to local SST variability is derived.

Spatial Variability in Seasonal Prediction Skill of SSTs: Inherent Predictability or Forecast Errors?

Seasonal prediction skill of SSTs from coupled models has considerable spatial variations. In the tropics, SST prediction skill in the tropical Pacific clearly exceeds prediction skill over the Atlantic and Indian Oceans. Such skill variations can be due to spatial variations in observing system used for forecast initializations or systematic errors in the seasonal prediction systems, or they could be a consequence of inherent properties of the coupled ocean–atmosphere system leaving a fingerprint on the spatial structure of SST predictability. Out of various alternatives, the spatial variability in SST prediction skill is argued to be a consequence of inherent characteristics of climate system. This inference is supported based on the following analyses. SST prediction skill is higher over the regions where coupled air–sea interactions (or Bjerknes feedback) are inferred to be stronger. Coupled air–sea interactions, and the longer time scales associated with them, imprint longer memory and thereby support higher SST prediction skill. The spatial variability of SST prediction skill is also consistent with differences in the ocean–atmosphere interaction regimes that distinguish between whether ocean drives the atmosphere or atmosphere drives the ocean. Regions of high SST prediction skill generally coincide with regions where ocean forces the atmosphere. Such regimes correspond to regions where oceanic variability is on longer time scales compared to regions where atmosphere forces the ocean. Such regional differences in the spatial characteristics of ocean–atmosphere interactions, in turn, also govern the spatial variations in SST skill, making spatial variations in skill an intrinsic property of the climate system and not an artifact of the observing system or model biases.

The role of potential vorticity anomalies in the Somali Jet on Indian Summer Monsoon Intraseasonal Variability

The climate of the Indian subcontinent is dominated by rainfall arising from the Indian summer monsoon (ISM) during June to September. Intraseasonal variability during the monsoon is characterized by periods of heavy rainfall interspersed by drier periods, known as active and break events respectively. Understanding and predicting such events is of vital importance for forecasting human impacts such as water resources. The Somali Jet is a key regional feature of the monsoon circulation. In the present study, we find that the spatial structure of Somali Jet potential vorticity (PV) anomalies varies considerably during active and break periods. Analysis of these anomalies shows a mechanism whereby sea surface temperature (SST) anomalies propagate north/northwestwards through the Arabian Sea, caused by a positive feedback loop joining anomalies in SST, convection, modification of PV by diabatic heating and mixing in the atmospheric boundary layer, wind-stress curl, and ocean upwelling processes. The feedback mechanism is consistent with observed variability in the coupled ocean–atmosphere system on timescales of approximately 20 days. This research suggests that better understanding and prediction of monsoon intraseasonal variability in the South Asian monsoon may be gained by analysis of the day-to-day dynamical evolution of PV in the Somali Jet.