Diurnal Signal Research Articles

Modulation of diurnal variation in rainfall associated with tropical cyclones over the East Asia–Western North Pacific region by environmental vertical wind shear

AbstractVertical wind shear (VWS), as an important dynamic factor influencing tropical cyclone rainfall (TCR), has a remarkable diurnal cycle of variation over the East Asia–western North Pacific region. The magnitude of tropical cyclone (TC)‐experienced VWS has enhanced amplitude but different phases over the South China Sea (SCS) and coastal East China (CEC) compared with that over the open ocean. Diurnal variation in TCR over the SCS shows statistically significant correlation with that of VWS. The convection concentrated in the downshear‐left quadrant strengthens markedly when VWS becomes large, thereby delaying the peak rainfall in the inner core of the TC and enhancing the amplitude of the diurnal cycle of TCR at ~09 local standard time. Over CEC, the diurnal signal of TCR is very weak but statistically significant in the downshear‐left and upshear‐right quadrants with opposite phase, illustrating the change in asymmetry of the spatial distribution of TCR induced by the large VWS diurnal cycle. The findings of this study could provide reference for improved forecasting of TCR on the fine temporal scale.

Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites

Abstract. This comprehensive study analyzed aerosol products from six low-Earth orbit (LEO) and geostationary Earth orbit (GEO) sensors. LEO sensors like the MODerate resolution Imaging Spectroradiometer (MODIS) and VIsible InfraRed Suite (VIIRS) provide one to two daily global measurements, while GEO sensors (Advanced Himawari Imager: AHI, Advanced Baseline Imager: ABI) offer high-frequency data (∼ 10 min) over specific regions. The combination of LEO and GEO capabilities offers expanded coverage of the global aerosol system if aerosol retrievals are applied consistently across all sensors and packaged in an easy-to-use product. The Dark Target aerosol retrieval algorithm was applied to the six sensors, and the resulting Level 2 aerosol optical depth (AOD) products were gridded and merged into a Level 3 quarter-degree latitude–longitude grid with a 30 min temporal resolution, providing the necessary consistency and packaging. Validation of this packaged Level 3 AOD product against Aerosol Robotics NETwork (AERONET) measurements across global locations showcased the merged product's robustness with a correlation coefficient of 0.83, revealing a global mean bias of approximately ±0.05, with 65.5 % of retrievals falling within an expected uncertainty range, underlining the reliability of the dataset. The new gridded Level 3 dataset significantly improved daily global coverage to nearly 45 %, overcoming the limitations of individual sensors, which typically range from 12 % to 25 %. Furthermore, this merged dataset approximates the diurnal cycle of AOD observed by AERONET, thus offering insights into diurnal signatures retrieved elsewhere. The resulting dataset's high spatiotemporal resolution and improved global coverage, especially in regions covered by GEO sensors (Americas and Asia), make it a valuable tool for diverse applications. Tracking aerosol transport from phenomena like wildfires and dust storms is gaining precision, enabling enhanced air quality forecasting and hindcasting. Additionally, the study positions the merged dataset as a significant asset for evaluating and intercomparing regional or global model simulations, which was previously unattainable in such a gridded format. The dataset and fusion framework layout in this study have the potential to include data from recently (future) launched other GEO (FCI, AMI) and LEO (PACE, VIIRS-JPSS) sensors.

Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager

Abstract. Originally developed for the moderate resolution imaging spectroradiometer (MODIS) in polar, sun-synchronous low earth orbit (LEO), the Dark Target (DT) aerosol retrieval algorithm relies on the assumption of a surface reflectance parameterization (SRP) over land surfaces. Specifically for vegetated and dark-soiled surfaces, values of surface reflectance in blue and red visible-wavelength bands are assumed to be nearly linearly related to each other and to the value in a shortwave infrared (SWIR) wavelength band. This SRP also includes dependencies on scattering angle and a normalized difference vegetation index computed from two SWIR bands (NDVISWIR). As the DT retrieval algorithm is being ported to new sensors to continue and expand the aerosol data record, we assess whether the MODIS-assumed SRP can be used for these sensors. Here, we specifically assess SRP for the Advanced Baseline Imager (ABI) aboard the Geostationary Operational Environmental Satellite (GOES)-16/East (ABIE). First, we find that using MODIS-based SRP leads to higher biases and artificial diurnal signatures in aerosol optical depth (AOD) retrievals from ABIE. The primary reason appears to be that the geostationary orbit (GEO) encounters an entirely different set of observation geometry than does LEO, primarily with regard to solar angles coupled with fixed-view angles. Therefore, we have developed a new SRP for GEO that draws the angular shape of the surface bidirectional reflectance. We also introduce modifications to the parameterization of both red–SWIR and blue–red spectral relationships to include additional information. The revised red–SWIR SRP includes the solar zenith angle, NDVISWIR, and land-type percentage from an ancillary database. The blue–red SRP adds dependencies on the scattering angle and NDVISWIR. The new SRPs improve the AOD retrieval of ABIE in terms of overall less bias and mitigation of the overestimation around local noon. The average bias of the DT AOD compared to the Aerosol Robotic Network (AERONET) AOD shows a reduction from 0.08 to 0.03, while the bias of local solar noon decreases from 0.12 to 0.03. The agreement between the DT and AERONET AOD is established through a regression slope of 1.06 and a y intercept of 0.01 with a correlation coefficient of 0.74. By using the new SRP, the percentage of data falling within the expected error range (±0.05 % + 15 %) is notably increased from 54 % to 78 %.

Towards Improved Quality Control of In Situ Sea Surface Temperatures from Drifting and Moored Buoys in the NOAA iQuam System

The NOAA in situ Sea Surface Temperature (SST) Quality Monitor (iQuam) online system collects in situ SSTs from various sources, performs quality control (QC), and provides QC’ed data to users. Like many other in situ QCs, the iQuam QC employs comparisons with Level 4 SST analysis. However, the current daily L4 analyses do not capture the diurnal cycle, nor do they resolve the fine structure of SST in dynamic areas. As a result, high-quality in situ SSTs significantly deviating from the L4 SST may be rejected. This paper discusses the new Diurnal Reference Check (DRC), which addresses overscreening for buoys whose sampling frequency is sufficient for resolving the diurnal cycle. The DRC separates records from individual buoys into 24-h segments and characterizes each segment with the median nighttime (MNT) SST and the amplitude of the diurnal signal (ADS). The segment is rejected if the ADS is unrealistically large or if the difference between the MNT and L4 SST exceeds a geographically dependent threshold. The outliers are further screened out by comparison of individual in situ SSTs with the MNT. All thresholds are determined from the analysis of matchups with reprocessed NOAA SSTs from multiple low-orbiting satellites. The satellite matchups are also used to validate the QC results. The DRC minimizes the overscreening, increases the number of high-quality in situ data by ~5%, and reduces the QC reliance on the L4 analysis. In addition, a new retrospective satellite-based quality check is introduced to identify matchups, which are most useful for training SST algorithms and validation of reprocessed satellite data.

Untangling the effects of seasonality and stream channel erosion on the runoff composition in a previously burned mountain catchment

AbstractStream channel incision and deposition are common after wildfire, and after these geomorphic changes occur, they may impact runoff mechanisms and the composition of pre‐event and event water in runoff. To investigate this, we monitored discharge and electrical conductivity at six nested sites within a 15.5 km2 watershed in the northern Colorado Front Range that had burned several years prior, and then experienced large flooding and well‐documented and significant channel erosion and deposition in the following years. Over the study period, which occurs 3 years after the fire, and 2 years after the beginning of significant geomorphic changes, the watershed experienced seven precipitation events. For each hydrograph, we separate baseflow from runoff using a new method to characterize and account for the strong diurnal signal in the baseflow. Electrical conductivity is used as a tracer in a two‐component end‐member mixing analysis to separate the event hydrographs into event and pre‐event water. Correlation coefficients were computed between key variables of the hydrologic response (such as runoff ratio, volumes of event and pre‐event water) to storm and basin characteristics (including stream channel erosion/deposition, fraction of high/moderate burn severity, precipitation intensity and antecedent precipitation). The strength and significance of correlations was found to vary seasonally. In the early season, event and pre‐event volumes did not vary significantly with basin or storm characteristics. In the late season, antecedent precipitation correlated with a decrease in event runoff (R2 = 0.34) and total runoff (R2 = 0.40), increased precipitation intensity correlated with an increase in event runoff (R2 = 0.48) and local erosion correlated with an increase in pre‐event runoff (R2 = 0.60) and total runoff (R2 = 0.53). We hypothesize that the difference in correlations between early season and late season is due seasonal variations in the groundwater table gradient. These findings indicate that seasonality and postfire stream channel erosion influence the makeup of runoff response.

Continuous ground monitoring of vegetation optical depth and water content with GPS signals

Abstract. Satellite microwave remote sensing techniques can be used to monitor vegetation optical depth (VOD), a metric which is directly linked to vegetation biomass and water content. However, these large-scale measurements are still difficult to reference against either rare or not directly comparable field observations. So far, in situ estimates of canopy biomass or water status often rely on infrequent and time-consuming destructive samples, which are not necessarily representative of the canopy scale. Here, we present a simple technique based on Global Navigation Satellite Systems (GNSS) with the potential to bridge this persisting scale gap. Because GNSS microwave signals are attenuated and scattered by vegetation and liquid water, placing a GNSS sensor under a vegetated canopy and measuring changes in signal strength over time can provide continuous information about VOD and thus on vegetation biomass and water content. We test this technique at a forested site in southern California for a period of 8 months. We show that variations in GNSS signal-to-noise ratios reflect the overall distribution of biomass density in the canopy and can be monitored continuously. For the first time, we show that this technique can resolve diurnal variations in VOD and canopy water content at hourly to sub-hourly time steps. Using a model of canopy transmissivity to assess these diurnal signals, we find that temperature effects on the vegetation dielectric constant, and thus on VOD, may be non-negligible at the diurnal scale or during extreme events like heat waves. Sensitivity to rainfall and dew deposition events also suggests that canopy water interception can be monitored with this approach. The technique presented here has the potential to resolve two important knowledge gaps, namely the lack of ground truth observations for satellite-based VOD and the need for a reliable proxy to extrapolate isolated and labor-intensive in situ measurements of biomass, canopy water content, or leaf water potential. We provide recommendations for deploying such off-the-shelf and easy-to-use systems at existing ecohydrological monitoring networks such as FluxNet or SapfluxNet.

Avian navigation: the geomagnetic field provides compass cues but not a bicoordinate "map" plus a brief discussion of the alternative infrasound direction-finding hypothesis.

The geomagnetic field (GMF) is a worldwide source of compass cues used by animals and humans alike. The inclination of GMF flux lines also provides information on geomagnetic latitude. A long-disputed question, however, is whether horizontal gradients in GMF intensity, in combination with changes in inclination, provide bicoordinate "map" information. Multiple sources contribute to the total GMF, the largest of which is the core field. The ubiquitous crustal field is much less intense, but in both land and marine settings is strong enough at low altitudes (< 700m; sea level) to mask the core field's weak N-S intensity gradient (~ 3-5 nT/km) over 10s to 100s of km. Non-orthogonal geomagnetic gradients, the lack of consistent E-W gradients, and the local masking of core-field intensity gradients by the crustal field, therefore, are grounds for rejection of the bicoordinate geomagnetic "map" hypothesis. In addition, the alternative infrasound direction-finding hypothesis is briefly reviewed. The GMF's diurnal variation has long been suggested as a possible Zeitgeber (timekeeper) for circadian rhythms and could explain the GMF's non-compass role in the avian navigational system. Requirements for detection of this weaker diurnal signal (~ 20-50 nT) might explain the magnetic alignment of resting and grazing animals.

Satellite solar-induced chlorophyll fluorescence tracks physiological drought stress development during 2020 southwest US drought.

Monitoring and estimating drought impact on plant physiological processes over large regions remains a major challenge for remote sensing and land surface modeling, with important implications for understanding plant mortality mechanisms and predicting the climate change impact on terrestrial carbon and water cycles. The Orbiting Carbon Observatory 3 (OCO-3), with its unique diurnal observing capability, offers a new opportunity to track drought stress on plant physiology. Using radiative transfer and machine learning modeling, we derive a metric of afternoon photosynthetic depression from OCO-3 solar-induced chlorophyll fluorescence (SIF) as an indicator of plant physiological drought stress. This unique diurnal signal enables a spatially explicit mapping of plants' physiological response to drought. Using OCO-3 observations, we detect a widespread increasing drought stress during the 2020 southwest US drought. Although the physiological drought stress is largely related to the vapor pressure deficit (VPD), our results suggest that plants' sensitivity to VPD increases as the drought intensifies and VPD sensitivity develops differently for shrublands and grasslands. Our findings highlight the potential of using diurnal satellite SIF observations to advance the mechanistic understanding of drought impact on terrestrial ecosystems and to improve land surface modeling.

The core metabolome and root exudation dynamics of three phylogenetically distinct plant species

Root exudates are plant-derived, exported metabolites likely shaping root-associated microbiomes by acting as nutrients and signals. However, root exudation dynamics are unclear and thus also, if changes in exudation are reflected in changes in microbiome structure. Here, we assess commonalities and differences between exudates of different plant species, diurnal exudation dynamics, as well as the accompanying methodological aspects of exudate sampling. We find that exudates should be collected for hours rather than days as many metabolite abundances saturate over time. Plant growth in sterile, nonsterile, or sugar-supplemented environments significantly alters exudate profiles. A comparison of Arabidopsis thaliana, Brachypodium distachyon, and Medicago truncatula shoot, root, and root exudate metabolite profiles reveals clear differences between these species, but also a core metabolome for tissues and exudates. Exudate profiles also exhibit a diurnal signature. These findings add to the methodological and conceptual groundwork for future exudate studies to improve understanding of plant-microbe interactions.

Wavelet Analysis on Groundwater, Surface-Water Levels and Water Temperature in Doñana National Park (Coastal Aquifer in Southwestern Spain)

The Doñana National Park (DNP) is a protected area with water resources drastically diminishing due to the unsustainable extraction of groundwater for agricultural irrigation and human consumption of a nearby coastal city. In this study, we explore the potential of wavelet analysis applied to high-temporal-resolution groundwater-and-surface-water time series of temporary coastal ponds in the DNP. Wavelet analysis was used to measure the frequency of changes in water levels and water temperature, both crucial to our understanding of complex hydrodynamic patterns. Results show that the temporary ponds are groundwater-dependent ecosystems of a through-flow type and are still connected to the sand-dune aquifer, regardless of their hydrological affection, due to groundwater withdrawal. These ponds, even those most affected by pumping in nearby drills, are not perched over the saturated zone. This was proven by the evidence of a semi-diurnal (i.e., 6 h) signal in the surface-level time series of the shallow temporary ponds. This signal is, at the same time, related to the influence of the tides affecting the coastal sand-dune aquifer. Finally, we detected other hydrological processes that affect the ponds, such as evaporation and evapotranspiration, with a clear diurnal (12 h) signal. The maintenance of the ecological values and services to the society of this emblematic wetland is currently in jeopardy, due to the effect of the groundwater abstraction for irrigation. The results of this study contribute to the understanding of the behavior of these fragile ecosystems of DNP, and will also contribute to sound-integrated water-resource management.

Observations of Ionospheric Clutter at Near Equatorial High Frequency Radar Stations

The temporal variation of received clutter and noise at a pair of oceanographic high frequency radars (HFR) operating near the geomagnetic equator in the Republic of Palau is investigated. Oceanographic HFRs process range-gated Doppler spectra from groundwave signals that are backscattered from the ocean’s surface to derive maps of ocean currents. The range performance of the radars exhibited a regular diurnal signal which is determined to be a result of both ionospheric clutter and noise. The increased Clutter plus Noise Floor (C+NF) decreases the Signal to Clutter plus Noise Ratio (SCNR) which, in turn, reduces the range and quality of ocean surface current measurement. Determining the nature and origin of this degradation is critical to QA/QC of existing HFR deployments as well as performance predictions of future installations. Nighttime impacts are most severe and negatively affect ocean surface current measurements as low SCNR is found to extend across the Doppler spectra at all ranges, challenging the ability of HFR to map the ocean surface current. Daytime degradation is less severe and presents itself in a way consistent with independent observations of ionospheric clutter, specifically the diurnal temporal pattern and range where the C+NF features occur. A timeseries analysis of SCNR and C+NF is pursued to understand this relationship using received range-dependent Doppler spectra and C+NF features using image segmentation techniques. Clutter plus noise features are classified into daytime, nighttime, and no-noise feature types. The diurnal structure and variability of these features are examined, and the occurrences of each feature type are calculated. The occurrences are compared with space weather indices including a measure of geomagnetic activity, namely the EE (Equatorial Electro Jet) index (determined from magnetometers measuring the earth’s magnetic field), as well as solar impacts using the F10.7 solar radio clutter index to assess the relationship of ionospheric conditions with HFR ocean surface current measurement.

A regional classification of time spectral amplitudes in total electron content: Southeastern United States during solar cycle 24

To investigate the meso-scale structure (100 s of km) of the ionosphere at mid-latitudes, the spectral properties in calculated total electron content (TEC) at a cluster of GPS receivers in and around Florida are analyzed. The ionosphere does not respond exactly the same to periodic solar driving at different locations around the planet, due to the complex electrodynamic interactions of the coupled magnetosphere-ionosphere system. Therefore, at each GPS receiver in the cluster we compare spatio-temporal variations of the spectral amplitudes for diurnal, solar rotation, and seasonal oscillations. The amplitudes for these dominant oscillations are organized with respect to magnetic latitude of the receiver. A low-latitude and high-latitude station are also included to put the mid-latitude ionospheric response into a global context. The amplitudes of diurnal, seasonal, and solar rotation signals are well ordered by magnetic latitude, superposed with meso-scale deviations between stations separated by ∼100s of km. The results suggest that spatio-temporal variations of spectral amplitudes in the mid-latitude ionosphere are not dominated by a single process. This conclusion is based on our finding that at high latitude, the shape of the diurnal signal varies significantly less with solar activity compared to low- and mid-latitudes, and additionally, that the ratio of annual to semi-annual amplitudes fluctuates around 1 with time and from station-to-station only at mid-latitudes.

Interpreting Sentinel-1 SAR Backscatter Signals of Snowpack Surface Melt/Freeze, Warming, and Ripening, through Field Measurements and Physically-Based SnowModel

The transition of a cold winter snowpack to one that is ripe and contributing to runoff is crucial to gauge for water resource management, but is highly variable in space and time. Snow surface melt/freeze cycles, associated with diurnal fluctuations in radiative inputs, are hallmarks of this transition. C-band synthetic aperture radar (SAR) reliably detects meltwater in the snowpack. Sentinel-1 (S1) C-band SAR offers consistent acquisition patterns that allow for diurnal investigations of melting snow. We used over 50 snow pit observations from 2020 in Grand Mesa, Colorado, USA, to track temperature and wetness in the snowpack as a function of depth and time during snowpack phases of warming, ripening, and runoff. We also ran the physically-based SnowModel, which provided a spatially and temporally continuous independent indication of snowpack conditions. Snowpack phases were identified and corroborated by comparing field measurements with SnowModel outputs. Knowledge of snowpack warming, ripening, and runoff phases was used to interpret diurnal changes in S1 backscatter values. Both field measurements and SnowModel simulations suggested that S1 SAR was not sensitive to the initial snowpack warming phase on Grand Mesa. In the ripening and runoff phases, the diurnal cycle in S1 SAR co-polarized backscatter was affected by both surface melt/freeze as well as the conditions of the snowpack underneath (ripening or ripe). The ripening phase was associated with significant increases in morning backscatter values, likely due to volume scattering from surface melt/freeze crusts, as well as significant decreases in evening backscatter values associated with snowmelt. During the runoff phase, both morning and evening backscatter decreased compared to reference values. These unique S1 diurnal signatures, and their interpretations using field measurements and SnowModel outputs, highlight the capacities and limitations of S1 SAR to understand snow surface states and bulk phases, which may offer runoff forecasting or energy balance model validation or parameterization, especially useful in remote or sparsely-gauged alpine basins.

Diurnal Variability in EMIRS Daytime Observations of Water Ice Clouds During Mars Aphelion‐Season

AbstractDiurnal analyses of water ice cloud optical depths retrieved from thermal infrared spectra by the Emirates Mars Infrared Spectrometer showed changing cloud abundance throughout the Martian day. Observations began with the start of the Emirates Mars Mission science phase near the beginning of aphelion‐season in Mars Year 36 and included the prominent aphelion cloud belt (ACB) and orographic clouds in the vicinity of volcanoes. A midday minimum with higher morning and afternoon optical depths was typical for the ACB, though with considerable spatial variability in this diurnal pattern. Clouds near volcanoes reached a minimum before local noon and tended to increase in abundance throughout the afternoon. Comparisons against the Laboratoire de Météorologie Dynamique global circulation model showed analogous spatial patterns in the diurnal signal, which suggested thermal tides and topographic effects to be the predominant drivers of ACB variability, while more localized circulations affected volcano clouds.

Currents generated by the sea breeze in the southern Caspian Sea

Abstract. The sea breeze system is the dominant atmospheric forcing at high frequency in the southern Caspian Sea. Here, we describe and interpret current meter observations on the continental margins of the southern Caspian from 2012 to 2013 to identify and characterize the water column's response to the sea breeze system. Time series analysis provides evidence for diurnal baroclinic current signals of O(0.02 m s−1) and surface height changes of O(0.03 m). A two-layer model, including interfacial and bottom friction, is developed to further investigate the sea breeze response. This model is able to reproduce the structure, amplitudes, and phases of observed diurnal current fluctuations, explaining half of the variance in observational current response at frequencies at 1 cpd and higher. The sea breeze response thus results in a “tide-like” daily cycle, which is actually linked to the local forcing all along the southern Caspian coast.

Bias Correction of Mixed Distributions of Temperature with Strong Diurnal Signal

Abstract The performance of first-moment and full-distribution bias-correction methods of monthly temperature distributions for seasonal prediction is analyzed by comparing two approaches: the standard all-in-data procedure and the 6-hourly stratification of data. Five models are applied to remove the systematic errors of the CFSv2 forecasts of temperature for the rainy season in the Ethiopian Blue Nile River basin domain. Using deterministic evaluation measures, it is found that the stratification marginally increases the forecast skill especially in regions where the data distribution of temperature is prominently multimodal. The improvement may be attributed to a split of the mixed distribution into a set of unimodal distributions. A necessary condition for this splitting into unimodal distributions is that the amplitude of the diurnal cycle be larger than the interannual variability in the sample. The maximum improvement of stratification is achieved by the first-moment correction model. Significance Statement This paper evaluates bias-correction methods of monthly forecast distributions of temperature to improve seasonal forecast skill. It is found that marginal skill is gained when bias correction of the diurnal cycle is performed. This paper contributes to the discussion on the value of subdaily model output data.

Diagnoses of Antarctic Inland Water Cycle Regime: Perspectives From Atmospheric Water Vapor Isotope Observations Along the Transect From Zhongshan Station to Dome A

Water stable isotopes are crucial for paleoclimate reconstruction and water cycle tracing in Antarctica. Accurate measurement of atmospheric water vapor isotopic composition of hydrogen and oxygen is required urgently for understanding the processes controlling the atmosphere–snow interaction and associated isotope fractionation. This study presents in situ real-time measurements of water vapor isotopes along the transect from Zhongshan Station to Dome Argus (hereafter Dome A) in East Antarctica for the first time. The results reveal that the surface vapor stable isotopes of δ18O and δ D showed a gradual decreasing trend in the interior plateau region with the distance away from the coast, with significant δ18O-temperature correlation gradient of 1.61‰°/C and δ18O-altitude gradient of –2.13‰/100 m. Meanwhile, d-excess gradually arises with elevation rise. Moreover, the spatial variation of vapor isotopic composition displays three different characters implying different atmosphere circulation backgrounds controlling the inland water cycle; it can be divided as the coastal steep area below 2,000 m, a vast inland area with an elevation varied between 2,000 and 3,000 m, and high central plateau. Thirdly, observed high inland Antarctica water vapor d-excess quantitatively confirms stratosphere air intrusion and vapor derived from low latitudes by Brewer–Dobson circulation. Finally, the diurnal cycle signals of interior area water vapor isotopes δ18O, δ D, and air temperature highlighted the substantial domination of the supersaturation sublimation/condensation effect in inland, and this suggests that fractionation occurs during sublimation and vapor–snow exchanges should no longer be considered insignificant for the isotopic composition of near-surface snow in Antarctica.

Is There an Outward Propagating Diurnal Signal in the Precipitation of Tropical Cyclones?

AbstractDiurnal pulse (outward propagating signal) is a prominent feature in tropical cyclones (TCs) and closely related to TC structure and intensity. It is elusive whether the diurnal pulse is deep convectively coupled and what is the influence on (daily) mean TC structure. This study addresses these outstanding problems using long‐term satellite precipitation, infrared, and microwave data. Diurnal pulse of precipitation occurs in ∼50% TC days, and the frequency increases with TC intensity. The precipitation, cold clouds, and microwave‐based deep convection of active precipitation pulses show significant outward‐propagating or phase‐delaying diurnal features, indicating deep convective coupling in these pulsing events. Nearly half of the diurnal pulses have cloud and precipitation coupled, but the coupling frequency is reduced (20%–30%) at the later stage (12–15 hr) of long‐duration pulses. Daily mean precipitation, cloud top height, and microwave ice scattering are markedly enhanced in TCs with precipitation pulse, compared to TCs without precipitation pulse.

Removing Diurnal Signals and Longer Term Trends From Electron Flux and ULF Correlations: A Comparison of Spectral Subtraction, Simple Differencing, and ARIMAX Models

AbstractSimultaneously cycling space weather parameters may show high correlations even if there is no immediate relationship between them. We successfully remove diurnal cycles using spectral subtraction, and remove both diurnal and longer cycles (e.g., the 27 days solar cycle) with a difference transformation. Other methods of diurnal cycle removal (daily averaging, moving averages [MAs], and simpler spectral subtraction using regression) are less successful at removing cycles. We apply spectral subtraction (a finite impulse response equiripple bandstop filter) to hourly electron flux (Los Alamos National Laboratory satellite data) and a ground‐based ULF index to remove a 24 hr noise signal. This results in smoother time series appropriate for short‐term (approximately &lt; 1 week) correlation and observational studies. However, spectral subtraction may not remove longer cycles such as the 27 days and 11 yr solar cycles. A differencing transformation (yt – yt−24) removes not only the 24 hr noise signal but also the 27 days solar cycle, autocorrelation, and longer trends. This results in a low correlation between electron flux and the ULF index over long periods of time (maximum of 0.1). Correlations of electron flux and the ULF index with solar wind velocity (differenced at yt – yt−1) are also lower than previously reported (≤0.1). An autoregressive, MA transfer function model (ARIMAX) shows that there are significant cumulative effects of solar wind velocity on ULF activity over long periods, but correlations of velocity and ULF waves with flux are only seen over shorter time spans of more homogeneous geomagnetic activity levels.

Annual Modulation of Diurnal Winds in the Tropical Oceans

Projections of future climate are sensitive to the representation of upper-ocean diurnal variability, including the diurnal cycle of winds. Two different methods suitable for time series with missing data are used here to characterize how observed diurnal winds vary over the year. One is based on diurnal composites of mooring data, and the other is based on harmonic analysis via a least squares fit and is able to isolate annual (i.e., 1 cycle per year) modulation of diurnal variability. Results show that the diurnal amplitude in meridional winds is larger than in zonal winds and peaks in the tropical Pacific, where diurnal variability in zonal winds is overall weaker compared to other basins. Furthermore, the amplitude and phasing of diurnal winds in the tropical oceans are not uniform in time, with overall larger differences through the year in the meridional component of tropical winds. Estimating the annual modulation of the diurnal signal implies resolving both the diurnal energy peak and also the modulation of this peak by the annual cycle. This leads to a recommendation for sampling at least 6 times per day and for a duration of at least 3 years.