Atmosphere Interactions Research Articles

Evaluation of Hub‐Height Wind Forecasts Over the New York Bight

ABSTRACTAs offshore wind energy development accelerates in the United States, it is important to assess the accuracy of hub‐height wind forecasts from numerical weather prediction models over the ocean. Leveraging approximately 2 years of Doppler lidar observations from buoys in the New York Bight, we evaluate 80‐m wind speed forecasts from two weather models: the High‐Resolution Rapid Refresh (HRRR) atmospheric model and the Global Forecast System (GFS) coupled atmosphere‐ocean model. These models have different horizontal grid spacing, vertical layering, initialization methods, and parameterizations of boundary layer mixing and surface–atmosphere interactions. Despite these differences, the models demonstrate similar and highly skillful short‐term forecasts at three measurement sites. At the Hudson Southwest location that provides a full year of data, their performance is statistically indistinguishable: root mean square error (RMSE) = 2.1 m/s and the Pearson correlation coefficient for 24‐h forecasts of both models, and RMSE = 2.6 m/s and 0.83 for 48‐h forecasts. Twenty‐four‐hour forecasts also exhibit skill in predicting quiescent winds and winds associated with maximum turbine power. By Day 10, GFS forecasts on average have almost no skill. The short‐term forecast skill by the HRRR and GFS does not strongly depend on season or time of day, yet we find some dependence of the models' performance on near‐surface stability. Additionally, 4‐ to 14‐day forecasts by the GFS exhibit lower RMSE during summer relative to other seasons. The high skill of the HRRR and GFS short‐term forecasts establishes confidence in their utility for offshore wind energy maintenance and operation.

An Ethnographic Study Concerning the Implementation of Education on Ageing for Older Adults with Mild Intellectual Disability: The Perspective of the Educators.

Despite the fact that longevity in people with intellectual disability has increased at least as much as in the general population, there is a dearth of interventions related to ageing for these older people. Therefore, this study investigated educators' implementation strategies in a new tailor-designed educational intervention with the goal of supporting the process of ageing for people with mild intellectual disability. An ethnographic research design was employed, including participant observations, field notes, and 15 ad hoc interviews with educators, spread over two years in four towns. The strategies used for facilitating learning about ageing were expressed in the two themes promoting social togetherness through everyone's participation and learning together and from each other through recognition and consolidation. These strategies were applied to create a learning environment characterised by a good atmosphere and respectful interaction. Learning together involved consolidation through repetition, group discussions, the use of visual learning materials, and study visits. This new educational intervention about ageing is promising, but less resource-intensive interventions should also be developed and preferably integrated into the disability service. Before concluding whether this education supports the ageing process, it needs to be evaluated from the perspective of people with intellectual disability.

Spatial-temporal variations in evapotranspiration across the continental United States: An atmospheric water balance perspective

Accurate estimation of terrestrial evapotranspiration (ET) is crucial for understanding land–atmosphere interactions, but is challenging on the regional scales. The water balance approach, including terrestrial and atmospheric water balance (TWB and AWB), provides a simple tool for estimating regional ET. This study estimated ET values based on the AWB approach (ETAWB) over the continental United States (CONUS) for the period 1979–2021. Validations using TWB-based ET estimates (ETTWB) suggest that ETAWB is accurate. ETAWB demonstrates comparable interannual variability with the other three long-term ET products over the CONUS and is consistent with ETTWB in the majority of basins. The 43-year CONUS averaged ETAWB is 548 ± 26 mm/year, with higher values in the eastern region and the coastal regions in the western CONUS, and lower values in the western arid regions. During 1979–2021, increasing trends of ETAWB are observed in the eastern CONUS, while decreasing trends occurred in the western regions. The intercomparison between ETAWB, GLEAM, Noah, and ERA5 illustrates similar spatial patterns and linear trends. In the water-limited arid basins, ETAWB anomalies over time show strong agreements with precipitation anomalies. The results of this study indicate that the AWB approach provides reasonable regional-to-continental terrestrial ET estimates over the CONUS, serving as a reference for hydrological and climatic modeling.

Relationships among soil moisture at various depths under diverse climate, land cover and soil texture

Soil moisture is an important component of the hydrological cycle and a key mediator between land surface and atmospheric interactions. Although substantial progress has been made in remote sensing of soil moisture at different spatial scales, the shallow penetration depth of remote sensors greatly limits their utility for applications in meteorological modelling and hydrological studies where the critical variable of interest is the root-zone soil moisture content. Therefore, this study assesses the relationship between soil moisture at the surface (10 cm) and in lower soil layers (20, 40, 60, 80, 100, and 120 cm) under varying climates, soils, and crop types. Cross-correlation analysis is applied to daily in-situ soil moisture measurements from 4712 locations in agricultural lands across the contiguous United States. Our analysis demonstrates that zero-day lag always produced the highest correlation between 10 cm soil moisture and soil moisture in the lower layers. In addition, a positive and strong relationship between 10 and 20 cm soil moisture (r = 0.84) was observed, while the relationships between 10 and 40 cm soil moisture were moderate (r = 0.52). The decline in cross-correlation continued to the deeper soil layers, which indicated that, on a daily timescale, the surface soil moisture gradually becomes decoupled with soil moisture at greater depths. Therefore, our research suggests that the estimation of soil moisture in the soil layers up to 40 cm based on surface soil moisture is most promising. However, the influence of climate, crop type, and soil texture on the strength of relationships between surface and lower layers makes the prediction difficult. The comparatively weak relationship between precipitation and soil moisture (0.09–0.32), as well as the relationship between reference evapotranspiration (ETo) and soil moisture (−0.19–0.18), in this study can be attributed to scale mismatching from different data sources.

Operational Forest-Fire Spread Forecasting Using the WRF-SFIRE Model

In the present research, the open-source WRF-SFIRE model has been used to carry out surface forest fire spread forecasting in the North Sikkim region of the Indian Himalayas. Global forecast system (GFS)-based hourly forecasted weather model data obtained through the National Centers for Environmental Prediction (NCEP) at 0.25 degree resolution were used to provide the initial conditions for running WRF-SFIRE. A landuse–landcover map at 1:10,000 scale was used to define fuel parameters for different vegetation types. The fuel parameters, i.e., fuel depth and fuel load, were collected from 23 sample plots (0.1 ha each) laid down in the study area. Samples of different categories of forest fuels were measured for their wet and dry weights to obtain the fuel load. The vegetation specific surface area-to-volume ratio was referenced from the literature. The atmospheric data were downscaled using nested domains in the WRF model to capture fire–atmosphere interactions at a finer resolution (40 m). VIIRS satellite sensor-based fire alert (375 m spatial resolution) was used as ignition initiation point for the fire spread forecasting, whereas the forecasted hourly weather data (time synchronized with the fire alert) were used for dynamic forest-fire spread forecasting. The forecasted burnt area (1.72 km2) was validated against the satellite-based burnt area (1.07 km2) obtained through Sentinel 2 satellite data. The shapes of the original and forecasted burnt areas matched well. Based on the various simulation studies conducted, an operational fire spread forecasting system, i.e., Sikkim Wildfire Forecasting and Monitoring System (SWFMS), has been developed to facilitate firefighting agencies to issue early warnings and carry out strategic firefighting.

Intermediate E-F layer dynamics study in the Brazilian low-latitude sector: observational data and simulations

This study investigates the downward motion of Intermediate E-F Layers (ILs) in the Brazilian low latitude sector through observation and modeling. Ionosonde data from São José dos Campos (SJC) and Palmas (PAL) were analyzed to investigate the seasonal variation of the IL parameters, including the virtual height (h'IL) and the top frequency (ftIL). The ILs primarily originated from F layer detachment followed by downward motion, peaking before 11 LT and disappearing well before sunset. Daily height variability ranged between 130 and 190 km, with peak frequencies around 4–5 MHz. Using meteor radar data as input, the Ionospheric E-region Model (MIRE) simulated diurnal and semidiurnal tides to analyze neutral wind effects on ILs descent. Model simulations for SJC (October 2008) and PAL (April and June 2009) revealed distinct wind oscillations influencing IL dynamics at heights below 140 km. In SJC, meridional wind shears controlled IL descent, with possible zonal wind interactions weakening ILs. Conversely, in PAL during April 2009, both zonal and meridional winds contributed to IL formation and altitude descent. However, discrepancies between observed and modeled descent rates suggest the need for considering additional atmospheric wave interactions in future modeling studies. June 2009 over PAL presented unique IL behavior, exhibiting a lower observed decay rate and daily height oscillations potentially linked to local modulations. Meanwhile, MIRE indicated that meridional wind shearing predominantly controlled IL descent in the morning, with zonal wind becoming relevant post-midday. These findings enhance our understanding of IL dynamics and their atmospheric drivers.

Neutrino oscillations with atmospheric neutrinos at large liquid argon TPCs

We propose to study atmospheric neutrino interactions with a unique event topology to distinguish neutrinos and anti-neutrinos using a liquid argon time projection chamber in an experiment such as DUNE. The detection of charged-current 1 proton (CC1P) and charged-current no proton (CC0P) events will allow us to access neutrino oscillation physics complementary to accelerator-based beam neutrinos. Assuming maximal CP violation (δCP= π/2) as the true hypothesis, our analysis shows that it is possible to disfavour CP conservation δCP=0 (or π) with more than 2σ (≈ 1.6σ) with a data sample of 140 kt-yr of atmospheric neutrinos in the DUNE detector. Our analysis also shows that assuming normal mass-ordering as the true hypothesis, the sensitivity to the opposite mass-ordering can be disfavoured with a significance close to 4σ and an octant of θ23 sensitivity with more than 2σ both for a true lower octant (θ23=41∘) and higher octant (θ23=49∘) value.

Assessing the Convective Environment over Irrigated and Nonirrigated Land Use with Land–Atmosphere Coupling Metrics: Results from GRAINEX

Abstract Land-use land-cover change affects weather and climate. This paper quantifies land–atmosphere interactions over irrigated and nonirrigated land uses during the Great Plains Irrigation Experiment (GRAINEX). Three coupling metrics were used to quantify land–atmosphere interactions as they relate to convection. They include the convective triggering potential (CTP), the low-level humidity index (HIlow), and the lifting condensation level (LCL) deficit. These metrics were calculated from the rawinsonde data obtained from the Integrated Sounding Systems (ISSs) for Rogers Farm and York Airport along with soundings launched from the three Doppler on Wheels (DOW) sites. Each metric was categorized by intensive observation period (IOP), cloud cover, and time of day. Results show that with higher CTP, lower HIlow, and lower LCL deficit, conditions were more favorable for convective development over irrigated land use. When metrics were grouped and analyzed by IOP, compared to nonirrigated land use, HIlow was found to be lower for irrigated land use, suggesting favorable conditions for convective development. Furthermore, when metrics were grouped and analyzed by clear and nonclear days, CTP values were higher over irrigated cropland than nonirrigated land use. In addition, compared to nonirrigated land use, the LCL deficit during the peak growing season was lower over irrigated land use, suggesting a favorable condition for convection. It is found that with the transition from the early summer to the mid/peak summer and increased irrigation, the environment became more favorable for convective development over irrigated land use. Finally, it was found that regardless of background atmospheric conditions, irrigated land use provided a favorable environment for convective development.

How Much Does Land–Atmosphere Coupling Influence Summertime Temperature Variability in the Western United States?

Abstract Interannual fluctuations in average summertime temperatures across the western United States are captured by a leading empirical orthogonal function that explains over 50% of the total observed variance. In this paper, we explain the origins of this pattern of interannual temperature variability by examining soil moisture–temperature coupling that acts across seasons in observations and climate models. We find that a characteristic pattern of coupled temperature–soil moisture climate variability accounts for 34% of the total observed variance in summertime temperature across the region. This pattern is reproduced in state-of-the-art global climate models, where experiments that eliminate soil moisture variability reduce summertime average temperature variance by a factor of 3 on average. We use an idealized model of the coupled atmospheric boundary layer and underlying land surface to demonstrate that feedbacks between soil moisture, boundary layer relative humidity, and precipitation can explain the observed relations between springtime soil moisture and summertime temperature. Our results suggest that antecedent soil moisture conditions and subsequent land–atmosphere interactions play an important role in interannual summertime temperature variability in the western United States; soil moisture variations cause distal temperature anomalies and impart predictability at time scales longer than one season. Our results indicate that 40% of the observed warming trend across the western United States since 1981 has been driven by wintertime precipitation trends in the U.S. southwest. Significance Statement Year-to-year fluctuations in summertime temperatures have a large impact on drought, wildfire, and extreme heat across the Western United States. We find strong evidence that soil moisture deficits in the preceding spring may be the primary driver of higher-than-average summer temperatures in this region. Our results suggest that memory in the water cycle may lead to greater predictability in the climate system from season to season and that trends in southwest precipitation have exerted a considerable influence on observed warming over the past 40 years.

Toward User-Friendly All-Sky Surface Longwave Downward Radiation from Space: General Scheme and Product

Abstract Longwave downward radiation (LWDR) is an important driving parameter in climate and hydrological models. Compared to traditional ground-based measurements, remote sensing has unique advantages in estimating global LWDR. However, for current remote sensing missions, as the typical available satellite-derived LWDR product with global coverage and hourly temporal resolution, the Clouds and the Earth’s Radiant Energy System-Synoptic (CERES-SYN) top of atmosphere and surface fluxes and clouds has a low spatial resolution (1° × 1°). There is still much room for improvement of the existing remote sensing LWDR products in terms of accuracy, spatiotemporal resolutions, and the ability to explain and quantify the changes of longwave radiation at various scales. To overcome these limitations, this paper developed a new global LWDR product with improved accuracy (RMSE < 30 W m−2 over the globe), high temporal resolution (hourly), and spatial resolution (5 km) based on Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. It serves as a LWDR product within the Long-term Earth System spatiotemporally Seamless Radiation budget dataset (referred to as LessRad). As the first long-term high-resolution, spatiotemporally continuous LWDR product (2002–22, 1 h, 5 km), the LessRad reveals its advantages in studying the spatiotemporal variability of LWDR on finer scales. It also provides a valuable data source for various applications, such as analyzing land–atmosphere interactions and quantifying climate feedback, and thus is potentially helpful for understanding Earth’s energy budget and dynamics.

Dataset of spatially extensive long-term quality-assured land–atmosphere interactions over the Tibetan Plateau

Dataset of spatially extensive long-term quality-assured land–atmosphere interactions over the Tibetan Plateau

The biogeophysical impacts of land cover changes in Northern Hemisphere permafrost regions

The permafrost zone in the Northern Hemisphere has experienced substantial land cover changes (LCCs) in recent decades, resulting in significant impacts on climate and ecosystems by regulating land–atmosphere interactions, energy, water fluxes, and carbon exchange. However, the response of LCCs to climate change is highly variable, especially in terms of biogeophysical effects in high latitude regions. The goal of this study therefore is to quantify the biogeophysical effects of LCCs in Northern Hemisphere permafrost regions. We combine land cover and climate data and separate natural and biogeophysical impacts of LCCs to estimate the contribution on the surface and shallow soil temperatures. From 2001 to 2020, approximately 26 % of the permafrost zone experienced LCCs. LCCs caused a decrease in albedo (−0.15 ± 1.03 %) and an increase in snow depth (2.04 ± 31.96 cm), evapotranspiration (2.19 ± 11.37 mm), and surface heat flux (0.09 ± 1.36 W/m2), resulting in an increase in temperatures: 0.03 ± 0.42 K (surface temperature), 0.07 ± 0.46 K (0–10 cm soil temperature), 0.07 ± 0.45 K (10–100 cm soil temperature), and 0.06 ± 0.43 K (100–200 cm soil temperature), which could increase the risk of permafrost degradation. Seasonally, LCCs exacerbate the temperature difference between winter and summer. Albedo dominates surface temperature changes, with about 87.5 % of surface temperature changes coinciding with albedo changes. Soil temperatures are regulated by snowpack and surface heat fluxes, in addition to albedo.

Enhancing water-carbon fluxes and yield predictions of winter wheat using irrigation and data assimilation techniques in a land surface model

Croplands are essential to land–atmosphere interactions and have a great impact on water balance, carbon fluxes, regional weather and climate, and food supply. This study utilized the Noah-MP land surface model, enhanced by a dynamic crop growth process known as Noah-MP-Crop, and employed a multi-pass data assimilation scheme (MLDAS) to assimilate leaf area index, surface soil moisture, and solar-induced chlorophyll fluorescence into the model for refining model’s simulations of land state variables (soil moisture and leaf biomass) and optimize the model vegetation parameters [specific leaf area (SLA) and maximum carboxylation rate normalized to 25 °C (Vcmax25)]. In conjunction with the irrigation module in this model, four experiments were conducted at the local observation-site scale to estimate and validate water-carbon fluxes [actual evapotranspiration (ETa) and gross primary productivity (GPP)] and crop yield within the winter wheat growing phase, which included open-loop simulation with and without irrigation (OLirr and OL), data assimilation with and without irrigation (DAirr and DA), separately. In-situ observations from the Yucheng Station in 2006 were used to evaluate these four experiments. Results indicated that the combined experiment (DAirr) provided the best agreement with the observed ETa, GPP, and yield. This superior performance is mainly attributed to the accurate vegetation information and soil moisture profile provided by the combined experiments with the model. Results indicated that the DAirr experiment performed better than the OL experiment in ETa estimation, with a higher correlation coefficient (R) of 0.85 compared to 0.71, a reduced root mean square error (RMSE) from 1.51 to 1.06 mm day−1, a lower normalized RMSE (NRMSE) from 43.21 % to 23.39 %, and a decreased mean absolute error (MAE) from 1.16 to 0.78 mm day−1. Similarly, DAirr increased R from 0.71 to 0.87 and cut down RMSE (MAE) from 5.81 (4.32) to 3.48 (2.26) g m−2 day−1 and NRMSE from 70.39 % to 18.20 % for GPP estimation. Moreover, winter wheat yield from DAirr (770.9 g m−2) agreed better with ground measurements (819.7 g m−2) than that from OL (400.6 g m−2). Additionally, results revealed that assimilating all three variables simultaneously is superior to single-variable assimilation and significantly outperforms the OL approach. All in all, this study has provided initial insights into the feasibility of assimilating three variables at the site scale into the model for improving the estimation accuracy of water-carbon fluxes and winter wheat yield, which laid a foundation for subsequent regional simulations.

Future fire events are likely to be worse than climate projections indicate – these are some of the reasons why

Background Climate projections signal longer fire seasons and an increase in the number of dangerous fire weather days for much of the world including Australia. Aims Here we argue that heatwaves, dynamic fire–atmosphere interactions and increased fuel availability caused by drought will amplify potential fire behaviour well beyond projections based on calculations of afternoon forest fire danger derived from climate models. Methods We review meteorological dynamics contributing to enhanced fire behaviour during heatwaves, drawing on examples of dynamical processes driving fire behaviour during the Australian Black Summer bushfires of 2019–20. Results Key dynamical processes identified include: nocturnal low-level jets, deep, unstable planetary boundary layers and fire–atmosphere coupling. Conclusions The future scenario we contend is long windows of multi-day fire events where overnight suppression is less effective and fire perimeters will expand continuously and aggressively over multiple days and nights. Implications Greater overnight fire activity and multi-day events present strategic and tactical challenges for fire management agencies including having to expand resourcing for overnight work, manage personnel fatigue and revise training to identify conditions conducive to unusually active fire behaviour overnight. Effective messaging will be critical to minimise accidental fire ignition during heatwaves and to alert the community to the changing fire environment

Impact of a fresh-core mesoscale eddy in modulating oceanic response to a Madden-Julian Oscillation

Theories of ocean–atmosphere interaction during a Madden–Julian Oscillation (MJO) are generally based on a thermodynamic model with surface fluxes dictating changes in sea surface temperature. Evidence from a two month ocean glider deployment in early 2019 in the southeast Indian Ocean suggests the impact of mesoscale dynamics on upper-ocean stratification likely affects ocean–atmosphere interaction at MJO scales. Until mid-February, local surface fluxes consistent with a convectively suppressed MJO phase drove near-surface ocean evolution. With the advection of a fresh-core eddy to the glider location in late February, ocean dynamics then becomes an additional driver of this evolution by modulating local stratification and generating a barrier layer of ≈12 m thickness for 10 days. One-dimensional modelling experiments based on the ocean and atmospheric conditions experienced during our sampling period show that the ocean subsurface structure within the eddy induce changes in SST of physical significance for ocean-atmosphere interaction. Moreover, results also suggest that the presence of a thick eddy-induced barrier layer during the MJO suppressed phase modulates the magnitude of temperature anomalies forced by surface fluxes during the following enhanced MJO phase. As eddies are abundant in this area, their dynamics must be considered to correctly represent SST variability for MJO modelling.

Numerical assessment of changes in land–atmosphere interactions during the rainy season in South America using an updated vegetation map

AbstractLand Use and Land Cover Change (LULCC) is a key driver of changes in land–atmosphere interactions, playing an essential role in climate and weather patterns in South America (SA). This study used a modelling approach to assess the land–atmosphere changes introduced by LULCC over the Brazilian territory. Numerical experiments of early (2006), neutral (2004) and late (2008) rainy season onset years were performed in the Integrated BIosphere Simulator (IBIS) to assess the land‐surface parameters, and in Brazilian Atmospheric Model (BAM) to assess the atmospheric variables. The models were run with a natural (NAT) vegetation map and an updated (UP) vegetation map, which incorporated realistic Brazil deforestation up to the early 2000s. The differences between the two maps were particularly larger over 25°–15°S and 50°–40°W, where the Atlantic Forest and Cerrado biomes were replaced by pasture. IBIS experiments showed that over the area of larger LULCC there was an increase in albedo of up to 8% while reductions in net radiation, surface heat fluxes, surface temperature and surface roughness were noticed. Land–atmosphere feedbacks assessed with BAM experiments showed that LULCC contributed to a drier and colder (stable) atmosphere over central‐east SA that opposes the necessary conditions for the rainy season onset. The changes included increases in surface pressure and low‐level wind associated with reductions in 2 m temperature and surface roughness. These changes contributed to decrease the cloud formation and less precipitation in all three rainy season onset years, but particularly in the late rainy season onset year during September–October–November (SON). The atmospheric changes induced by LULCC show a pattern of dry atmosphere (reduced precipitation), similar to those of late onset years, and indicate that LULCC enhances the late rainy season onset condition over central‐east SA. Additionally, this study highlights the importance of considering up‐to‐date vegetation maps because these changes significantly affect both surface and atmospheric variables.

Evaluation of Two Satellite Surface Solar Radiation Products in the Urban Region in Beijing, China

Surface solar radiation, as a primary energy source, plays a pivotal role in governing land–atmosphere interactions, thereby influencing radiative, hydrological, and land surface dynamics. Ground-based instrumentation and satellite-based observations represent two fundamental methodologies for acquiring solar radiation information. While ground-based measurements are often limited in availability, high-temporal- and spatial-resolution, gridded satellite-retrieved solar radiation products have been extensively utilized in solar radiation-related studies, despite their inherent uncertainties in accuracy. In this study, we conducted an evaluation of the accuracy of two high-resolution satellite products, namely Himawari-8 (H8) and Moderate Resolution Imaging Spectroradiometer (MODIS), utilizing data from a newly established solar radiation observation system at the Beijing Normal University (BNU) station in Beijing since 2017. The newly acquired measurements facilitated the generation of a firsthand solar radiation dataset comprising three components: Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), and Diffuse Horizontal Irradiance (DHI). Rigorous quality control procedures were applied to the raw minute-level observation data, including tests for missing data, the determination of possible physical limits, the identification of solar tracker malfunctions, and comparison tests (GHI should be equivalent to the sum of DHI and the vertical component of the DNI). Subsequently, accurate minute-level solar radiation observations were obtained spanning from 1 January 2020 to 22 March 2022. The evaluation of H8 and MODIS satellite products against ground-based GHI observations revealed strong correlations with R-squared (R2) values of 0.89 and 0.81, respectively. However, both satellite products exhibited a tendency to overestimate solar radiation, with H8 overestimating by approximately 21.05% and MODIS products by 7.11%. Additionally, solar zenith angles emerged as a factor influencing the accuracy of satellite products. This dataset serves as crucial support for investigations of surface solar radiation variation mechanisms, future energy utilization prospects, environmental conservation efforts, and related studies in urban areas such as Beijing.

Asian monsoonal temperature and environmental changes since the penultimate deglaciation as revealed by alkenones and alkanes in sediments from the northern South China Sea

A new alkenone sea surface temperature (SST) record from the South China Sea (SCS) over the last 170 ka has been reported here. Our analysis of magnetic susceptibility and AMS 14C dating on the top portion of the core suggests that this record dates to the Marine Isotope Stage (MIS) 6. As indicated in Termination I and II, SST changes are correlated with clear glacial/interglacial cycles and likely dominated by atmospheric CO2 and Western Pacific Warm Pool temperature changes. But the two Terminations were different in magnitude. In Termination I, the minimum and maximum SSTs are 24.5 °C and 27.5 °C, respectively, showing a smaller rise (3 °C) than in Termination II (24–28.3 °C). The n-alkane indices, such as average chain length (ACL) and carbon preference index (CPI), exhibited high/low values during glacial/interglacial periods, and possible more arid climate during MIS 6 than MIS 2. During Termination II, the maximum surface warming in the SCS is accompanied by a progressive lag of approximately 7000 years in relation to maximum summer insolation until Termination I, when they are nearly synchronous. According to the study, SSTs are continuously changing and are influenced by solar insolation, global ice volume changes, and ocean–atmosphere interactions across hemispheres.

Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN

Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.

Atmosphere and ocean interactions

The nature and extent of the main interactions between the Earth’s atmosphere and the ocean are briefly reviewed, introducing the main properties of these two planetary systems, the hierarchy of timescales and spatial scales characterizing their processes, and the main mechanisms involved. To clarify these mechanisms, a few examples of exchanges of momentum, energy, and mass exchanges are briefly outlined. The paper aims at stimulating students to discover the fascinating interplay among two of the most relevant components of our planet, such as the atmosphere and the ocean, and suggests resources for further exploration.Graphical abstract