Which varies more diurnally

There has been an increased awareness of the potential impact of the diurnal cycle when interpreting measurements of stratospheric ozone at altitudes in the mid- to upper stratosphere.

This climatology can be applied to a wide range of ozone data analyses, including data intercomparisons, data merging and the analysis of data from a single platform in a non-sun-synchronous orbit.

We evaluate the diurnal climatology by comparing mean differences between ozone measurements made at different local solar times to the differences predicted by the diurnal model. These results compare well with previous modeling simulations and are supported by similar size variations in satellite observations. We present several example applications of the climatology in currently relevant data studies.

Frith, S. Stratospheric ozone has been an environmental concern since the suggestion 45 years ago that anthropogenic chemicals collectively known as ozone depleting substances; ODSs released into the atmosphere could destroy ozone Stolarski and Cicerone, ; Molina and Rowland, Since that time, our understanding of ozone chemistry and dynamics has vastly evolved, and high quality satellite and ground-based observations of ozone have been key to that evolution.

These observations were used to quantify ozone loss during the s and early s and are now being used to quantify the turn around and expected increase in ozone after the ban of many ODSs.

However, the slow decline in these chemicals, resulting from their long atmospheric lifetimes and the staged reduction of their use through the Montreal Protocol and subsequent amendments, means that the ozone recovery rate will be much slower than the loss rate. Therefore, observations must be sufficiently stable to resolve these small changes in time. Furthermore, measurements from more than one source are required to provide adequate spatial and temporal coverage to evaluate the full range of effects of ODSs on ozone, such that data must be consistent across multiple observation platforms.

Intercomparison of ozone observations from satellite and ground-based data sources is key to validating independent measurements and maintaining high quality data records. With the need for more stable long-term records, we must consider ever-smaller sources of variability. One such variation is the diurnal cycle in ozone, which had generally been considered small enough to be inconsequential in the middle stratosphere, although the large variations in the upper stratosphere and mesosphere are well known e.

Ground-based microwave radiometers have been used to analyze the ozone diurnal cycle at particular locations from the tropics to the Northern Hemisphere mid- and high latitudes i. Satellite data provide a more global view of the diurnal cycle. Thus, it takes averaging over many years or other statistical techniques to isolate the diurnal variations from other sources of variability e.

In addition, these missions do not provide full global coverage. Parrish et al. Here, we expand on those results, analyzing the model diurnal cycle against available measurements over a range of latitudes. As in Parrish et al. In this work, we do not focus on the chemical and dynamical mechanisms of the ozone diurnal cycle but rather on the validity of the model-derived diurnal climatology as a tool for data analysis. The paper is divided into the following sections: in Sect. The model is run on 72 pressure levels with a model top at 0.

Note that we sample model output from 3 consecutive days in UTC to get a full local solar time diurnal cycle at each longitude. We then average the diurnal cycles at each longitude to get a daily zonal mean diurnal cycle, and we subsequently average over available days for each month. We note that GDOC can be renormalized to any reference time as is most appropriate for a given analysis. Uncertainty estimates for GDOC should be based on the standard error of the mean SEM of the model output averaged to construct the climatology.

The model ozone fields are spatially and temporally correlated, so the true number of independent data points is much lower. To estimate the actual number of independent data points, we compute longitudinally lagged correlations at each grid point on a given day and assume that the data points are independent when the lagged correlation drops below a threshold value.

Based on this analysis see Fig. Test climatologies from the additional model simulations are representative of different years but are constructed in the same manner. We use ozone observations from multiple data sources to test GDOC in a variety of circumstances.

Table 1 shows the salient characteristics of the data sets used in this analysis and appropriate references for more information on each instrument. Table 1 Ozone observations and corresponding measurement times. Although UARS MLS also samples the diurnal cycle over an extended period, the geophysical variability is largely removed in the 9-year average by month and the error bars capture the remaining variability. In this work, we use UARS MLS data for qualitative comparisons only; thus, we do not apply a more rigorous analysis to isolate the diurnal cycle.

We first show several examples of GDOC, highlight some of the salient features and compare generally to past studies. Figure 1 shows GDOC, normalized to the value at midnight, as a function of hour of the day and pressure for four latitude bands and months.

The ratio is shown with a contour interval of 0. Here, the most obvious feature is the low ozone during the day in the lower mesosphere, the well-known mesospheric ozone diurnal cycle e.

There is very little, if any, variation in the nighttime values at these altitudes. Results in this latitude band correspond to previous results shown in Parrish et al.

The predawn and early morning diurnal ozone decrease is larger in January, as was seen by Parrish et al. The contour interval is 0. The climatology is shown at levels from 50 to 0. Seasons are represented by monthly output in March, June, September and December. The error bars are 2SEM, as described in the text.

The model uncertainty is largest in winter, when the day-to-day and longitudinal variability of model ozone is greatest.

Compared to the March subtropical climatology in Fig. Here we determine global spatial variation in the difference in the mean annual rate at which near-surface daytime maximum and night-time minimum temperatures and mean daytime and mean night-time cloud cover, specific humidity and precipitation have changed over land. For the years , we derived hourly climate data and assigned each hour as occurring during daylight or darkness.

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Webster , P. Clayson , and J. Curry , : Clouds, radiation, and the diurnal cycle of sea surface temperature in the tropical western Pacific. Wheeler , M. Hendon , : An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Wielicki , B. Barkstrom , E. Harrison , R. Lee , G. Smith , and J. Woolnough , S. Vitart , and M. Young , D. Minnis , D. Doelling , G. Gibson , and T. Zhao , C. Li , and T. Zhao , N. Nasuno , : How does the air—sea coupling frequency affect convection during the MJO passage?

Shallow coastal or land areas are left blank. The number of samples, mean, and standard deviation for each MJO phase are shown to the right of e. Valid values beyond the plot range are accumulated in the nearest bin. White lines represent bad or missing data. Colors represent approximate MJO phase color from Fig. Standard errors are displayed as error bars.

The suppressed phase diurnal cycle composited by dSST percentiles: 0th—25th red line , 25th—50th green line , 50th—75th blue line , 75th—th orange line , and 0th—th black line of variables from Fig. The anomalous evolution of the variables from Fig. The suppressed phase diurnal cycle composited by dSST percentiles: 0th—25th red line , 25th—50th green line , 50th—75th blue line , 75th—th orange line , and 0th—th black line of a high cloud cover, b middle cloud cover, c low cloud cover, and d total cloud cover.

The suppressed phase composite heating rate diurnal cycle of a difference in clear-sky net between the high- and low-dSST bins, b difference in cloud net between the high- and low-dSST bins, c all-sky net for the high-dSST bin, and d all-sky net for the low-dSST bin.

Values outside the range are filled gray. The suppressed phase diurnal cycle composited by dSST percentiles: 0th—25th red line , 25th—50th green line , 50th—75th blue line , 75th—th orange line , and 0th—th black line of a residual moistening rate using ERA5 physics and dynamics, b residual moistening rate using MERRA-2 physics and dynamics, c ERA-5 residual model error, and d MERRA-2 residual model error.

A1 composited by dSST percentile bins left to right columns 14 days before and after the start of the transition phase vertical black line. Diurnal air—sea coupling affects climate modes such as the Madden—Julian oscillation MJO via the regional moist static energy budget.

Prior to MJO initiation, large-scale subsidence increases decreases surface shortwave insolation winds. These act in concert to significantly warm the uppermost layer of the ocean over the course of a single day and the ocean mixed layer over the course of 1—2 weeks. Here, we provide an integrated analysis of multiple surface, top-of-atmosphere, and atmospheric column observations to assess the covariability related to regions of strong diurnal sea surface temperature dSST warming over 44 MJO events between and to assess their role in MJO initiation.

Diurnally developing moisture convergence, only modestly weaker evaporation, and diurnal minimum precipitation act to locally enhance moistening over broad regions of enhanced diurnal warming, which rectifies onto the larger scale.

Field campaign ship and sounding data corroborate that strong dSST periods are associated with reduced middle-tropospheric humidity and larger diurnal amplitudes of surface warming, evaporation, instability, and column moistening. Further, we find greater daytime increases in low cloud cover and evidence of enhanced radiative destabilization for the top 50th dSST percentile.

Together, these results support that dSST warming acts in concert with large-scale dynamics to enhance moist static energy during the suppressed to active phase transition of the MJO. Denotes content that is immediately available upon publication as open access.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy www. Air—sea coupling on diurnal time scales affects climate modes such as the Madden—Julian oscillation MJO.

Air—sea interactions include fluxes of energy radiation, latent heat, and sensible heat , water mass precipitation and evaporation , momentum via wind stress and surface drag , and chemical and biological constituents DeMott et al. A fusion of datasets derived from modern satellite instruments enables the long-term study of the diurnal cycle of air—sea interactions over the tropical Indian Ocean prior to MJO onset in order to elucidate its influence on MJO initiation.

Combined with a reduction in upper ocean mixing associated with the quiescent flow, solar radiation can significantly warm the uppermost layer of the ocean over the course of a single day. As a result, diurnal warm layers DWLs are commonly imprinted on the sea surface temperature SST measurements over the tropical Indian Ocean, especially 1—2 weeks prior to MJO onset when favorable environmental conditions persist. The ocean surface layer upper few meters commonly warms by 1—2 K up to 5 K between the morning and early evening depending on wind speed, cloud cover, and ocean mixing Webster et al.

We refer to this period of enhanced subsidence prior to the development of widespread precipitating conditions as the suppressed phase throughout this paper; a more rigorous definition based on the MJO index is provided subsequently. Recent observational studies highlight the importance of DWLs in increasing the regional moist static energy MSE during the transition from the MJO suppressed phase to active phase Ruppert and Johnson ; Ruppert Modeling studies corroborate the importance of including diurnal air—sea coupling showing that MJO forecast skill improves when properly resolving the diurnal cycle of upper-ocean heat transfer Woolnough et al.

Specifically, models better simulate MJO propagation and active phase strength when including this coupling Klingaman and Woolnough Bernie et al. DeMott et al. The approach above may underestimate the impact of ocean feedbacks on the MJO because it is unable to resolve boundary layer convergence driven by SST gradients. The small 0. Several springs in southern Mexico states of Tabasco and Chiapas are fed by sulfidic groundwater aquifers with high concentrations of hydrogen-sulfide H 2 S generated from volcanic deposits and bacterial sulfate reduction e.

A previous study characterized it as a freshwater habitat with high temperatures and sulfide content, low oxygen and pH, and high conductivity, which showed little temporal variation across years T: Most notably, fish spend a majority of their time performing aquatic surface respiration ASR , but frequently dive to engage in benthic foraging as well as aggressive or reproductive activities under water Tobler et al. Fish also dive in response to predation Lukas et al.

Main predators in this system consist of fish-eating birds such as kingfishers, herons and egrets Supplementary Table 1 , Riesch et al. To allow for higher temporal resolution we based our investigations at a single, representative site exposed to moderate to high levels of sulfidic and hypoxic stress refer to site 1 in Culumber et al.

Additionally, this site allowed for access during all sampling times and fish and birds were already habituated to a degree of human presence. To explore whether the observed diurnal differences in fish behavior are driven by physicochemical water conditions and how they link to predator activity, we conducted two field surveys and one laboratory experiment.

During one field season subsequently termed field survey I , we first quantified how variable physicochemical water conditions were throughout the day.

To link observations from both surveys, they were carried out at the same location and followed the same regimen by sampling each morning — , midday — and afternoon — for six subsequent days. Surveys were matched for season i. Due to the spatial dynamics of predator-prey interactions, observations on water chemistry, fish and bird behavior were performed on slightly different spatial scales.

While fish were clearly clustered in shoals with very little movement between, avian predators were much more mobile. Fish observations were based on a focal shoal, which reliably built up at the same location every day crossing the Survey I transect; Supplementary Video.

Ultimately, this approach did not allow for abiotic and biotic observations to be directly linked, nor for the behavior of individual prey to be correlated with a single predator. Figure 1. Shown are multiple measurements gray , which were sample-pooled for analysis black. Letters indicate results from post hoc pairwise comparisons.

The dashed line indicates a laboratory-established threshold at which Poecilia sulphuraria predominantly performed aquatic surface respiration ASR 50 ; see results below. However, fish would interrupt ASR and drop below the surface for voluntary dives [i. To the human eye, these individuals were more conspicuous and their trajectory through the water column could be easily followed until they resurfaced again. While dive duration can merely present an inverse proxy of ASR tendency, we argue that it is a conservative assessment, considering that many individuals did not leave the surface at all when DO levels were low see also Supplementary Video.

Lastly, to corroborate some of the above observations in a controlled laboratory experiment, we explored the proportion of time sulphur mollies spent performing ASR as well as the number and duration of dives at different dissolved oxygen levels without the confounding effects of variation in water chemistry or predator activity. It also allowed us to validate our ASR proxy by verifying that fish did not compensate shorter lasting dives by diving more often.

In their natural habitats sulphur mollies perform ASR in large groups. Such high social tendency has also been reported for sulfidic surface ecotypes of the closely related P. We therefore chose to test fish in groups. In nature, some individuals likely have to make compromises by surfacing earlier or later than they need to conform with group behavior. It is conceivable that a similar effect occurred in our experiment, so that some individuals possibly due to differences in personality or metabolic demand may have triggered the response of the entire group Kramer and Graham, ; Chapman and Chapman, ; Borowiec et al.

We are thus confident that our setup enabled us to gain biologically most relevant data on the DO thresholds for ASR behavior. At each sampling, we took multiple measurements of water temperature, dissolved oxygen DO , pH and electrical conductivity EC , and — due to logistical constraints — one sulfide sample along a cross section of the sulfidic stream.

With a width of 5. For the quantification of total free sulfides i. The first 1 ml sample was discarded to clear the tubing and the subsequent 0. The total sulfide concentration was immediately analyzed by cuvette test Hach Lange LCK using a spectrophotometer Hach Lange DR with automated recognition of the measurement program and internal calibration. We assessed fish behavior using a focal animal sampling approach see Tobler et al.

An observer i. Twenty diving fish of similar size were chosen randomly from a focal shoal and observed from the moment they initiated diving until they resurfaced to calculate the mean dive duration. In rare cases, observations had to be terminated and repeated because a disturbance occurred during the diving period e. We assessed bird activity prior to any fish observations to minimize disturbances caused by human activity.

We made observations from a natural hide alongside the stream using binoculars. Three observers recorded all sightings of piscivorous birds in the predefined study area within a min period. Observers were versed in identifying the bird species previously described to predate on P.

For each bird, we determined species to lowest feasible taxonomical level , entry and exit times, as well as the number of attacks launched. Given the highly stochastic nature of predation in time and space, we selected two measures of bird activity that we deemed robust against differences in predator abundance and species differences in foraging styles.

We calculated presence time as the mean time piscivorous birds spent in the study area excluding mere fly-throughs, i. We exposed fish to dissolved oxygen concentrations ranging from near-anoxic to normoxic conditions 0.

Due to logistical restraints field lab in tropical climate , water temperature could not be controlled completely. As a consequence, we assigned fish post hoc to one of two temperature regimes Both temperatures are ecologically relevant as they represent the daily variations commonly experienced by the species between morning and afternoon.

We collected fish and water for the experiment from the same site previously used in Survey I and II. Fish were left to habituate in insulated coolers for at least 1 h without external disturbance. During habituation, fish were held in aerated water from the nearest freshwater source 5. Treatment water was aerated to the desired DO level under constant mixing. DO and temperature were monitored with a multiprobe OxyGuard Polaris 2 directly prior and after each trial to calculate a mean treatment value.

Water was exchanged after each trial and testing was done under natural light. We tested fish in groups of five adults visually matched for size. As part of the acclimation protocol, we did not analyze the first 5 min of each trial to ensue fish had recovered from handling and resumed swimming. We quantified the cumulative time spent at the surface by all five fish see Video analysis and calculated a percentage surface time.

We analyzed videos obtained from the lab experiment using EthoVision 12 Noldus Information Technology. As a prerequisite for ASR, fish need to have direct surface contact, but experiments on another poeciliid P. We note that this approach may slightly overestimate ASR duration e. In order to make both field surveys comparable, it was necessary to reduce some information of the obtained variables for statistical analyses.

Multiple measurements taken during a single sampling were pooled into one mean score sample pooling. We tested for temporal variation in all parameters of interest by performing separate generalized linear regressions package lme4 ; Bates et al.

Regressions of dive duration and predator presence time were performed with Gaussian error structure. We assumed predator attacks to be approximately Poisson distributed. Models were validated by visual inspection of the residuals. Significance of coefficients was evaluated via Likelihood-Ratio tests. We further explored the association between parameters cor.

For prey and predator behavior, we used Mann-Kendall rank correlations, which are robust against outliers and appropriate for small sample sizes. To explore the relationship between oxygen and aquatic surface respiration of P. To account for an effect of test temperature, half of the models included the parameter but did no interactions due to the sample size. We fitted all models with binomial logit-normal error structure glmer function in package lme4 ; Bates et al.

In addition, we used multimodel inference to compare the relative importance of main effects i. Estimations of half-maximal DO concentration ASR 50 for both temperature regimes were done on the basis of the global model. Lastly, the more controlled laboratory experiment allowed us to validate our proxy of dive duration Survey II using direct measurements of ASR surface time.

We first tested for differences in both number and duration of dives tested either above or below the established ASR 50 threshold using Wilcoxon Signed-Ranks tests.

We then estimated a Spearman correlation between surface time and dive duration cor. Overall, the study site exhibited high temperatures, high concentrations of sulfides especially H 2 S , high specific conductivity, as well as low dissolved oxygen concentrations and low pH Table 1.

While mornings were associated with temperatures below Dissolved sulfide concentrations showed considerable variation between samplings Figure 1C. Table 1. Fish frequently surfaced during mornings, middays and afternoons, but continuously aggregated at the surface toward the later parts of the day Figure 2A and Supplementary Video. Fish performed occasional voluntary dives i. Dives lasted significantly longer during mornings than later in the day Figure 2B.

Figure 2. A During daytime hours, sulphur mollies spent large amounts of time at the surface performing aquatic surface respiration, often resulting in densely-packed shoals. Shown are measurements gray , which were sample-pooled for analysis black. Activity of avian predators was generally high. Within 8. Periods of short dives and an associated extension of surface time were associated with high activity of avian predators.