scholarly journals Versatile Harmonic Tidal Analysis: Improvements and Applications

2009 ◽  
Vol 26 (4) ◽  
pp. 806-817 ◽  
Author(s):  
M. G. G. Foreman ◽  
J. Y. Cherniawsky ◽  
V. A. Ballantyne
Keyword(s):  
Time Series ◽  
Input Data ◽  
Computer Software ◽  
Temperature Time Series ◽  
Correlation Matrices ◽  
Ocean Sciences ◽  
Harmonic Tidal Analysis ◽  
Direct Incorporation ◽  
Temperature Time ◽  
Selection Of

Abstract New computer software that permits more versatility in the harmonic analysis of tidal time series is described and tested. Specific improvements to traditional methods include the analysis of randomly sampled and/or multiyear data; more accurate nodal correction, inference, and astronomical argument adjustments through direct incorporation in the least squares matrix; multiconstituent inferences from a single reference constituent; correlation matrices and error estimates that facilitate decisions on the selection of constituents for the analysis; and a single program that analyzes one- or two-dimensional time series. This new methodology is evaluated through comparisons with results from old techniques and then applied to two problems that could not have been accurately solved with older software. They are (i) the analysis of ocean station temperature time series spanning 25 yr, and (ii) the analysis of satellite altimetry from a ground track whose proximity to land has led to significant data dropout. This new software is free as part of the Institute of Ocean Sciences (IOS) Tidal Package and can be downloaded, along with sample input data and an explanatory readme file.

scholarly journals Effect of meteorological forcing and snow model complexity on hydrological simulations in the Sieber catchment (Harz Mountains, Germany)

2014 ◽  
Vol 18 (11) ◽  
pp. 4703-4720 ◽  
Author(s):  
K. Förster ◽  
G. Meon ◽  
T. Marke ◽  
U. Strasser
Keyword(s):  
Time Series ◽  
Energy Balance ◽  
Input Data ◽  
Temperature Time Series ◽  
Catchment Scale ◽  
Harz Mountains ◽  
Temperature Index ◽  
Meteorological Input ◽  
Temperature Time ◽  
Precipitation And Temperature

Abstract. Detailed physically based snow models using energy balance approaches are spatially and temporally transferable and hence regarded as particularly suited for scenario applications including changing climate or land use. However, these snow models place high demands on meteorological input data at the model scale. Besides precipitation and temperature, time series of humidity, wind speed, and radiation have to be provided. In many catchments these time series are rarely available or provided by a few meteorological stations only. This study analyzes the effect of improved meteorological input on the results of four snow models with different complexity for the Sieber catchment (44.4 km2) in the Harz Mountains, Germany. The Weather Research and Forecast model (WRF) is applied to derive spatial and temporal fields of meteorological surface variables at hourly temporal resolution for a regular grid of 1.1 km × 1.1 km. All snow models are evaluated at the point and the catchment scale. For catchment-scale simulations, all snow models were integrated into the hydrological modeling system PANTA RHEI. The model results achieved with a simple temperature-index model using observed precipitation and temperature time series as input are compared to those achieved with WRF input. Due to a mismatch between modeled and observed precipitation, the observed melt runoff as provided by a snow lysimeter and the observed streamflow are better reproduced by application of observed meteorological input data. In total, precipitation is simulated statistically reasonably at the seasonal scale but some single precipitation events are not captured by the WRF data set. Regarding the model efficiencies achieved for all simulations using WRF data, energy balance approaches generally perform similarly compared to the temperature-index approach and partially outperform the latter.

scholarly journals The effect of streambed heterogeneity on groundwater-surface water exchange fluxes inferred from temperature time series

2015 ◽  
Vol 51 (1) ◽  
pp. 198-212 ◽  
Author(s):  
Dylan J. Irvine ◽  
Roger H. Cranswick ◽  
Craig T. Simmons ◽  
Margaret A. Shanafield ◽  
Laura K. Lautz
Keyword(s):  
Time Series ◽  
Surface Water ◽  
Water Exchange ◽  
Temperature Time Series ◽  
Temperature Time ◽  
Streambed Heterogeneity

scholarly journals The Simulation of Daily Temperature Time Series from GCM Output. Part I: Comparison of Model Data with Observations

1997 ◽  
Vol 10 (10) ◽  
pp. 2497-2513 ◽  
Author(s):  
J. P. Palutikof ◽  
J. A. Winkler ◽  
C. M. Goodess ◽  
J. A. Andresen
Keyword(s):  
Time Series ◽  
Temperature Time Series ◽  
Daily Temperature ◽  
Model Data ◽  
Temperature Time

The Use of Satellite TIR Time Series for Thermal Anomalies’ Detection on Natural and Urban Areas

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Malvina Silvestri ◽  
Federico Rabuffi ◽  
Massimo Musacchio ◽  
Sergio Teggi ◽  
Maria Fabrizia Buongiorno
Keyword(s):  
Time Series ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Urban Areas ◽  
Temperature Time Series ◽  
Campi Flegrei ◽  
Thermal Anomalies ◽  
Pca Method ◽  
Temperature Time

In this work, the land surface temperature time series derived using Thermal InfraRed (TIR) satellite data offers the possibility to detect thermal anomalies by using the PCA method. This approach produces very detailed maps of thermal anomalies, both in geothermal areas and in urban areas. Tests were conducted on the following three Italian sites: Solfatara-Campi Flegrei (Naples), Parco delle Biancane (Grosseto) and Modena city.

Long-term variability of the temperature time series recorded in Lisbon

2009 ◽  
Vol 36 (3) ◽  
pp. 323-337 ◽  
Author(s):  
João Santos ◽  
Solange Leite
Keyword(s):  
Time Series ◽  
Temperature Time Series ◽  
Temperature Time
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