Fine Scale Baleen Whale Behavior Observed via Tagging Over Daily Time Scales

2012 ◽  
Author(s):  
Mark Baumgartner
Keyword(s):  
Time Scales ◽  
Fine Scale ◽  
Baleen Whale ◽  
Daily Time

Projected changes in extreme precipitation at sub-daily and daily time scales

2019 ◽  
Vol 182 ◽  
pp. 103004 ◽  
Author(s):  
Alex Morrison ◽  
Gabriele Villarini ◽  
Wei Zhang ◽  
Enrico Scoccimarro
Keyword(s):  
Time Scales ◽  
Extreme Precipitation ◽  
Projected Changes ◽  
Daily Time

scholarly journals Sub-daily runoff simulations with parameters inferred at the daily time scale

2015 ◽  
Vol 12 (8) ◽  
pp. 7437-7467 ◽  
Author(s):  
J. E. Reynolds ◽  
S. Halldin ◽  
C. Y. Xu ◽  
J. Seibert ◽  
A. Kauffeldt
Keyword(s):  
Time Series ◽  
Numerical Method ◽  
Time Scales ◽  
Time Scale ◽  
Input Data ◽  
Flood Forecasting ◽  
Euler Method ◽  
Time Stepping ◽  
Parameter Values ◽  
Daily Time

Abstract. Concentration times in small and medium-sized watersheds (~ 100–1000 km2) are commonly less than 24 h. Flood-forecasting models then require data at sub-daily time scales, but time-series of input and runoff data with sufficient lengths are often only available at the daily time scale, especially in developing countries. This has led to a search for time-scale relationships to infer parameter values at the time scales where they are needed from the time scales where they are available. In this study, time-scale dependencies in the HBV-light conceptual hydrological model were assessed within the generalized likelihood uncertainty estimation (GLUE) approach. It was hypothesised that the existence of such dependencies is a result of the numerical method or time-stepping scheme used in the models rather than a real time-scale-data dependence. Parameter values inferred showed a clear dependence on time scale when the explicit Euler method was used for modelling at the same time steps as the time scale of the input data (1–24 h). However, the dependence almost fully disappeared when the explicit Euler method was used for modelling in 1 h time steps internally irrespectively of the time scale of the input data. In other words, it was found that when an adequate time-stepping scheme was implemented, parameter sets inferred at one time scale (e.g., daily) could be used directly for runoff simulations at other time scales (e.g., 3 or 6 h) without any time scaling and this approach only resulted in a small (if any) model performance decrease, in terms of Nash–Sutcliffe and volume-error efficiencies. The overall results of this study indicated that as soon as sub-daily driving data can be secured, flood forecasting in watersheds with sub-daily concentration times is possible with model-parameter values inferred from long time series of daily data, as long as an appropriate numerical method is used.

scholarly journals Comparison of Global Precipitation Estimates across a Range of Temporal and Spatial Scales

2016 ◽  
Vol 29 (21) ◽  
pp. 7773-7795 ◽  
Author(s):  
Maria Gehne ◽  
Thomas M. Hamill ◽  
George N. Kiladis ◽  
Kevin E. Trenberth
Keyword(s):  
Time Scales ◽  
Large Scale ◽  
Global Climate ◽  
Spatial Scales ◽  
Rain Gauge ◽  
Random Errors ◽  
Climate Data ◽  
Precipitation Estimates ◽  
Global Precipitation ◽  
Daily Time

Abstract Characteristics of precipitation estimates for rate and amount from three global high-resolution precipitation products (HRPPs), four global climate data records (CDRs), and four reanalyses are compared. All datasets considered have at least daily temporal resolution. Estimates of global precipitation differ widely from one product to the next, with some differences likely due to differing goals in producing the estimates. HRPPs are intended to produce the best snapshot of the precipitation estimate locally. CDRs of precipitation emphasize homogeneity over instantaneous accuracy. Precipitation estimates from global reanalyses are dynamically consistent with the large-scale circulation but tend to compare poorly to rain gauge estimates since they are forecast by the reanalysis system and precipitation is not assimilated. Regional differences among the estimates in the means and variances are as large as the means and variances, respectively. Even with similar monthly totals, precipitation rates vary significantly among the estimates. Temporal correlations among datasets are large at annual and daily time scales, suggesting that compensating bias errors at annual and random errors at daily time scales dominate the differences. However, the signal-to-noise ratio at intermediate (monthly) time scales can be large enough to result in high correlations overall. It is shown that differences on annual time scales and continental regions are around 0.8 mm day−1, which corresponds to 23 W m−2. These wide variations in the estimates, even for global averages, highlight the need for better constrained precipitation products in the future.

scholarly journals The contribution of coral reef-derived dimethyl sulfide to aerosol burden over the Great Barrier Reef: a modelling study

2021 ◽  
Author(s):  
Sonya Fiddes ◽  
Matthew Woodhouse ◽  
Steve Utembe ◽  
Robyn Schofield ◽  
Joel Alroe ◽  
...  
Keyword(s):  
Coral Reef ◽  
Great Barrier Reef ◽  
Time Scales ◽  
Dimethyl Sulfide ◽  
Regional Scale ◽  
Cloud Formation ◽  
Barrier Reef ◽  
Anthropogenic Aerosol ◽  
Daily Time

Abstract. Coral reefs have been found to produce the sulfur compound dimethyl sulfide (DMS), a climatically relevant aerosol precursor predominantly associated with phytoplankton. Until recently, the role of coral reef-derived DMS within the climate system had not been quantified. A study preceding the present work found that DMS produced by corals had negligible long-term climatic forcing at the global-regional scale. However, at sub-daily time scales more typically associated with aerosol and cloud formation, the influence of coral reef-derived DMS on local aerosol radiative effects remains unquantified. The Weather Research and Forecasting – chemistry model (WRF-Chem) has been used in this work to study the role of coral reef-derived DMS at sub-daily time scales for the first time. WRF-Chem was run to coincide with an October 2016 field campaign over the Great Barrier Reef, Queensland, Australia, against which the model was evaluated. After updating the DMS surface water climatology, the model reproduced DMS and sulfur concentrations well. The inclusion of coral reef-derived DMS resulted in no significant change in sulfate aerosol mass or total aerosol number. Subsequently, no direct or indirect aerosol effects were detected. The results suggest that the co-location of the Great Barrier Reef with significant anthropogenic aerosol sources along the Queensland coast prevents coral reef derived-aerosol from having a modulating influence on local aerosol burdens in the current climate.

scholarly journals Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales

2017 ◽  
Vol 193 ◽  
pp. 36-49 ◽  
Author(s):  
Pari-Sima Katiraie-Boroujerdy ◽  
Ata Akbari Asanjan ◽  
Kuo-lin Hsu ◽  
Soroosh Sorooshian
Keyword(s):  
Time Scales ◽  
Precipitation Estimates ◽  
Daily Time

On the Application of the Priestley–Taylor Relation on Sub-daily Time Scales

2015 ◽  
Vol 156 (3) ◽  
pp. 489-499 ◽  
Author(s):  
Xiaofeng Guo ◽  
Heping Liu ◽  
Kun Yang
Keyword(s):  
Time Scales ◽  
Daily Time

How Important Is Air–Sea Coupling in ENSO and MJO Evolution?

2009 ◽  
Vol 22 (11) ◽  
pp. 2958-2977 ◽  
Author(s):  
Matthew Newman ◽  
Prashant D. Sardeshmukh ◽  
Cécile Penland
Keyword(s):  
Time Scales ◽  
Evolution Operator ◽  
Power Spectra ◽  
Dynamical Evolution ◽  
Atmospheric Variability ◽  
Basic Premise ◽  
Strongly Coupled ◽  
Dominant Period ◽  
Linear Inverse Model ◽  
Daily Time

Abstract The effect of air–sea coupling on tropical climate variability is investigated in a coupled linear inverse model (LIM) derived from the simultaneous and 6-day lag covariances of observed 7-day running mean departures from the annual cycle. The model predicts the covariances at all other lags. The predicted and observed lag covariances, as well as the associated power spectra, are generally found to agree within sampling uncertainty. This validates the LIM’s basic premise that beyond daily time scales, the evolution of tropical atmospheric and oceanic anomalies is effectively linear and stochastically driven. It also justifies a linear diagnosis of air–sea coupling in the system. The results show that air–sea coupling has a very small effect on subseasonal atmospheric variability. It has much larger effects on longer-term variability, in both the atmosphere and the ocean, including greatly increasing the amplitude of ENSO and lengthening its dominant period from 2 to 4 years. Consistent with these results, the eigenvectors of the system’s dynamical evolution operator also separate into two distinct, but nonorthogonal, subspaces: one governing the nearly uncoupled subseasonal dynamics and the other governing the strongly coupled longer-term dynamics. These subspaces arise naturally from the LIM analysis; no bandpass frequency filtering need be applied. One implication of this remarkably clean separation of the uncoupled and coupled dynamics is that GCM errors in anomalous tropical air–sea coupling may cause substantial errors on interannual and longer time scales but probably not on the subseasonal scales associated with the MJO.

scholarly journals Response of water use efficiency to summer drought in boreal Scots pine forests in Finland

2016 ◽  
Author(s):  
Yao Gao ◽  
Tiina Markkanen ◽  
Mika Aurela ◽  
Ivan Mammarella ◽  
Tea Thum ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Use Efficiency ◽  
Water Use ◽  
Time Scales ◽  
Scots Pine ◽  
Land Surface ◽  
Summer Drought ◽  
Ecosystem Level ◽  
Use Efficiency ◽  
Daily Time

Abstract. The influence of drought on plant functioning has received considerable attention in recent years, although our understanding of the response of carbon and water coupling in terrestrial ecosystems remains unclear. In this study, we investigated the response of water use efficiency to summer drought in boreal forests at daily time scales mainly using eddy covariance flux data. In addition, simulation results from the JSBACH land surface model were evaluated against the observed results. Two Scots pine (Pinus sylvestris) sites at Hyytiälä (southern Finland) and Sodankylä (northern Finland) were used in the study. Based on observed data, the ecosystem level water use efficiency (EWUE) showed a decrease only during a severe soil moisture drought at Hyytiälä, whereas the inherent water use efficiency (IWUE) increased when there was a severe soil moisture drought at Hyytiälä and a moderate soil moisture drought at Sodankylä. This indicates a decrease in surface conductance at the ecosystem level, but the decrease in evapotranspiration (ET) was alleviated because of the increased vapor pressure deficit (VPD) during drought. Moreover, the changes in IWUE implied that Scots pine has weaker response to drought in the southern site than in the northern site. Thus, IWUE is a more appropriate metric than EWUE for capturing the impact of soil moisture drought on plant functioning at daily time scales. In general, the results from transpiration based ecosystem level water use efficiency (EWUEt) and IWUE, and the transpiration based inherent water use efficiency (IWUEt) from JSBACH simulations were similar to the observed results. The deviated groups of gross primary production (GPP) and evapotranspiration (ET) under severe soil moisture drought in observed data at Hyytiälä were also successfully captured in the simulated results. However, deficiencies in the model were clearly seen by the limitation effect of air humidity on stomatal conductance in observed data. Our study provides a deeper understanding of carbon and water dynamics in the major boreal ecosystem. These findings highlight the importance of choosing a suitable plant functioning indicator when investigating the effects of drought, and suggest possible improvements to land surface models, which play an important role in the prediction of biosphere-atmosphere feedbacks in the climate system.

scholarly journals Solving Richards Equation for snow improves snowpack meltwater runoff estimations in detailed multi-layer snowpack model

2014 ◽  
Vol 8 (1) ◽  
pp. 257-274 ◽  
Author(s):  
N. Wever ◽  
C. Fierz ◽  
C. Mitterer ◽  
H. Hirashima ◽  
M. Lehning
Keyword(s):  
Water Balance ◽  
Snow Cover ◽  
Time Scales ◽  
Hydrological Cycle ◽  
Computational Cost ◽  
Richards Equation ◽  
Positive Energy ◽  
Meltwater Runoff ◽  
Physically Based ◽  
Daily Time

Abstract. The runoff from a snow cover during spring snowmelt or rain-on-snow events is an important factor in the hydrological cycle. In this study, three water balance schemes for the 1 dimensional physically-based snowpack model SNOWPACK are compared to lysimeter measurements at two alpine sites with a seasonal snow cover, but with different climatological conditions: Weissfluhjoch (WFJ) and Col de Porte (CDP). The studied period consists of 14 and 17 yr, respectively. The schemes include a simple bucket-type approach, an approximation of Richards Equation (RE), and the full RE. The results show that daily sums of snowpack runoff are strongly related to a positive energy balance of the snow cover and therefore, all water balance schemes show very similar performance in terms of Nash-Sutcliffe efficiency (NSE) coefficients (around 0.63 and 0.72 for WFJ and CDP, respectively) and r2 values (around 0.83 and 0.72 for WFJ and CDP, respectively). An analysis of the runoff dynamics over the season showed that the bucket-type and approximated RE scheme release meltwater slower than in the measurements, whereas RE provides a better agreement. Overall, solving RE for the snow cover yields the best agreement between modelled and measured snowpack runoff, but differences between the schemes are small. On sub-daily time scales, the water balance schemes behave very differently. In that case, solving RE provides the highest agreement between modelled and measured snowpack runoff in terms of NSE coefficient (around 0.48 at both sites). At WFJ, the other water balance schemes loose most predictive power, whereas at CDP, the bucket-type scheme has an NSE coefficient of 0.39. The shallower and less stratified snowpack at CDP likely reduces the differences between the water balance schemes. Accordingly, it can be concluded that solving RE for the snow cover improves several aspects of modelling snow cover runoff, especially for deep, sub-freezing snow covers and in particular on the sub-daily time scales. The additional computational cost was found to be in the order of a factor of 1.5–2.

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