Application of a Statistical Interpolation Method to Correct Extreme Values in High-Resolution Gridded Climate Variables

2015 ◽  
Vol 6 (4) ◽  
pp. 331 ◽  
Author(s):  
Yeo min Jeong ◽  
Hyung-Il Eum
Keyword(s):  
High Resolution ◽  
Extreme Values ◽  
Interpolation Method ◽  
Climate Variables ◽  
Statistical Interpolation

scholarly journals Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim

2017 ◽  
Vol 21 (4) ◽  
pp. 2187-2201 ◽  
Author(s):  
Pere Quintana-Seguí ◽  
Marco Turco ◽  
Sixto Herrera ◽  
Gonzalo Miguez-Macho
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Interpolation Method ◽  
Rain Gauge ◽  
Surface Model ◽  
Low Resolution ◽  
Precipitation Events

Abstract. Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980–2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.

scholarly journals The use of LIDAR as a data source for digital elevation models – a study of the relationship between the accuracy of digital elevation models and topographical attributes in northern peatlands

2011 ◽  
Vol 8 (3) ◽  
pp. 5497-5522 ◽  
Author(s):  
A. Hasan ◽  
P. Pilesjö ◽  
A. Persson
Keyword(s):  
High Resolution ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
Drainage Area ◽  
Absolute Deviation ◽  
Weighting Method ◽  
Dem Resolution ◽  
Coarse Resolution ◽  
Digital Elevation ◽  
Topographical Attributes

Abstract. It is important to study the factors affecting estimates of wetness since wetness is crucial in climate change studies. The availability of digital elevation models (DEMs) generated with high resolution data is increasing, and their use is expanding. LIDAR earth elevation data have been used to create several DEMs with different resolutions, using various interpolation parameters, in order to compare the models with collected surface data. The aim is to study the accuracy of DEMs in relation to topographical attributes such as slope and drainage area, which are normally used to estimate the wetness in terms of topographic wetness indices. Evaluation points were chosen from the high-resolution LIDAR dataset at a maximum distance of 10 mm from the cell center for each DEM resolution studied, 0.5, 1, 5, 10, 30 and 90 m. The interpolation method used was inverse distance weighting method with four search radii: 1, 2, 5 and 10 m. The DEM was evaluated using a quantile-quantile test and the normalized median absolute deviation. The accuracy of the estimated elevation for different slopes was tested using the DEM with 0.5 m resolution. Drainage areas were investigated at three resolutions, with coinciding evaluation points. The ability of the model to generate the drainage area at each resolution was obtained by pairwise comparison of three data subsets. The results show that the accuracy of the elevations obtained with the DEM model are the same for different resolutions, but vary with search radius. The accuracy of the values (NMAD of errors) varies from 29.7 mm to 88.9 mm, being higher for flatter areas. It was also found that the accuracy of the drainage area is highly dependent on DEM resolution. Coarse resolution yielded larger estimates of the drainage area but lower slope values. This may lead to overestimation of wetness values when using a coarse resolution DEM.

High-Resolution Digital Elevation and Bathymetry Model for Tsunami Run-Up and Inundation Simulation in Penang

2019 ◽  
Vol 13 (05n06) ◽  
pp. 1941001
Author(s):  
Su Yean Teh ◽  
Hock Lye Koh ◽  
Yong Hui Lim
Keyword(s):  
High Resolution ◽  
Indian Ocean ◽  
Sea Level ◽  
Interpolation Method ◽  
Topographic Maps ◽  
Seamless Integration ◽  
Topographic Data ◽  
Digital Elevation ◽  
Run Up ◽  
Tsunami Run Up

Many beaches in Penang island were severely inundated by the 26 December 2004 Indian Ocean mega tsunami with 57 deaths recorded. It is anticipated that the next big tsunami will cause even more damages to beaches in Penang. Hence, developing community resilience against the risks of the next tsunami is essential. Resilience entails many interlinked components, beginning with a good understanding of the inundation scenarios critical to community evacuation and resilience preparation. Inundation scenarios are developed from tsunami simulations involving all three phases of tsunami generation, propagation and run-up. Accurate and high-resolution bathymetric–topographic maps are essential for simulations of tsunami wave inundation along beaches. Bathymetric maps contain information on the depths of landforms below sea level while topographic maps reveal the elevation of landforms above sea level. Bathymetric and topographic datasets for Malaysia are, however, currently not integrated and are available separately and in different formats, not suitable for inundation simulations. Bathymetric data are controlled by the National Hydrographic Centre (NHC) of the Royal Malaysian Navy while topographic data are serviced by the Department of Survey and Mapping Malaysia (JUPEM). It is highly desirable to have seamless integration of high-resolution bathymetric and topographic data for tsunami simulations and for other scientific studies. In this paper, we develop a robust method for integrating the NHC bathymetric and JUPEM topographic data into a regularly-spaced grid system essential for tsunami simulation. A primary objective of this paper is to develop the best Digital Elevation and Bathymetry Model (DEBM) for Penang based upon the most suitable and accurate interpolation method for integrating bathymetric and topographic data with minimal interpolation errors. We analyze four commonly used interpolation methods for generating gridded topographic and bathymetric surfaces, namely (i) Kriging, (ii) Multiquadric (MQ), (iii) Thin Plate Spline (TPS) and (iv) Inverse Distance to Power (IDP). The study illustrated that the Kriging interpolation method produces an integrated bathymetric and topographic surface that best approximates the admiralty nautical chart of Penang essential for tsunami run-up and inundation simulations. Tsunami inundation scenarios critical to risk analysis and mitigation could then be developed using this DEBM for various earthquake scenarios, as presented in this paper for the 2004 Indian Ocean Tsunami.

scholarly journals A Fast 4K Video Frame Interpolation Using a Multi-Scale Optical Flow Reconstruction Network

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1251 ◽  
Author(s):  
Ahn ◽  
Jeong ◽  
Kim ◽  
Kwon ◽  
Yoo
Keyword(s):  
High Resolution ◽  
Optical Flow ◽  
State Of The Art ◽  
Interpolation Method ◽  
Video Frame ◽  
Frame Interpolation ◽  
Multi Scale ◽  
Reconstruction Scheme ◽  
Flow Reconstruction

Recently, video frame interpolation research developed with a convolutional neural network has shown remarkable results. However, these methods demand huge amounts of memory and run time for high-resolution videos, and are unable to process a 4K frame in a single pass. In this paper, we propose a fast 4K video frame interpolation method, based upon a multi-scale optical flow reconstruction scheme. The proposed method predicts low resolution bi-directional optical flow, and reconstructs it into high resolution. We also proposed consistency and multi-scale smoothness loss to enhance the quality of the predicted optical flow. Furthermore, we use adversarial loss to make the interpolated frame more seamless and natural. We demonstrated that the proposed method outperforms the existing state-of-the-art methods in quantitative evaluation, while it runs up to 4.39× faster than those methods for 4K videos.

Evaluation of trends in extreme temperatures simulated by HighResMIP models across Europe

2020 ◽  
Author(s):  
Gerard van der Schrier ◽  
Antonello Squintu ◽  
Else van den Besselaar ◽  
Eveline van der Linden ◽  
Enrico Scoccimarro ◽  
...  
Keyword(s):  
High Resolution ◽  
Western Europe ◽  
Extreme Values ◽  
Maximum Temperature ◽  
Western Balkans ◽  
North West ◽  
The Balkans ◽  
The North ◽  
Summer Maximum ◽  
Maximum Temperatures

<p>The comparison of simulated climate with observed daily values allows to assess their reliability and the soundness of their projections on the climate of the future. Frequency and amplitude of extreme events are fundamental aspects that climate simulations need to reproduce. In this work six models developed within the High Resolution Model Intercomparison Project are compared over Europe with the homogenized version of the observational E-OBS gridded dataset. This is done by comparing averages, extremes and trends of the simulated summer maximum temperature and winter minimum temperatures with the observed ones.</p><p>Extreme values have been analyzed making use of indices based on the exceedances of percentile-based thresholds. Winter minimum temperatures are generally underestimated by models in their averages (down to -4 deg. C of difference over Italy and Norway) while simulated trends in averages and extreme values are found to be too warm on western Europe and too cold on eastern Europe (e.g. up to a difference of -4% per decade on the number of Cold Nights over Spain). On the other hand the models tend to underestimate summer maximum temperatures averages in Northern Europe and overestimate them in the Mediterranean areas (up to +5 deg. C over the Balkans). The simulated trends are too warm on the North West part and too cold on the South East part of Europe (down to -3%/dec. on the number of Warm Days over Italy and Western Balkans).</p><p>These results corroborate the findings of previous studies about the underestimation of the warming trends of summer temperatures in Southern Europe, where these are more intense and have more impacts.  A comparison of the high resolution models  with the corresponding version in CMIP5 has been performed comparing the absolute biases of extreme values trends. This has shown a slight improvement for the simulation of winter minimum temperatures, while no signs of significant progresses have been found for summer maximum temperatures.</p>

EMO-5: Copernicus pan-European high-resolution meteorological data set for large-scale hydrological modelling

2020 ◽  
Author(s):  
Vera Thiemig ◽  
Peter Salamon ◽  
Goncalo N. Gomes ◽  
Jon O. Skøien ◽  
Markus Ziese ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Large Scale ◽  
Interpolation Method ◽  
Meteorological Data ◽  
Hydrological Modelling ◽  
Data Set ◽  
Average Temperature ◽  
Time Period ◽  
Meteorological Observations

<p>We present EMO-5, a Pan-European high-resolution (5 km), (sub-)daily, multi-variable meteorological data set especially developed to the needs of an operational, pan-European hydrological service (EFAS; European Flood Awareness System). The data set is built on historic and real-time observations coming from 18,964 meteorological in-situ stations, collected from 24 data providers, and 10,632 virtual stations from four high-resolution regional observational grids (CombiPrecip, ZAMG - INCA, EURO4M-APGD and CarpatClim) as well as one global reanalysis product (ERA-Interim-land). This multi-variable data set covers precipitation, temperature (average, min and max), wind speed, solar radiation and vapor pressure; all at daily resolution and in addition 6-hourly resolution for precipitation and average temperature. The original observations were thoroughly quality controlled before we used the Spheremap interpolation method to estimate the variable values for each of the 5 x 5 km grid cells and their affiliated uncertainty. EMO-5 v1 grids covering the time period from 1990 till 2019 will be released as a free and open Copernicus product mid-2020 (with a near real-time release of the latest gridded observations in future). We would like to present the great potential EMO-5 holds for the hydrological modelling community.</p><p> </p><p>footnote: EMO = European Meteorological Observations</p>

scholarly journals High‐resolution temperature climatology for Italy: interpolation method intercomparison

2013 ◽  
Vol 34 (4) ◽  
pp. 1278-1296 ◽  
Author(s):  
M. Brunetti ◽  
M. Maugeri ◽  
T. Nanni ◽  
C. Simolo ◽  
J. Spinoni
Keyword(s):  
High Resolution ◽  
Interpolation Method
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