scholarly journals Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5

2021 ◽  
Author(s):  
Navid Ghajarnia ◽  
Mahdi Akbari ◽  
Peyman Saemian ◽  
Mohammad Reza Ehsani ◽  
Seyed-Mohammad Hosseini-Moghari ◽  
...  
Keyword(s):  
Observational Data ◽  
Model Development ◽  
Decomposition Methods ◽  
Global Scale ◽  
Skill Scores ◽  
Precipitation Estimates ◽  
Using Data ◽  
Annual Scale ◽  
Error Decomposition ◽  
Hydrological Applications

ECMWF Reanalysis (ERA), one of the most widely used precipitation products, has evolved over time from ERA-40 to ERA-20CM, ERA-20C, ERA-Interim, and ERA5. Studies evaluating the performance of individual ERA precipitation products cannot adequately assess the evolution in the products. Therefore, we compared the performance of five successive ERA precipitation products using data at daily, monthly, and annual scale (1980-2018) from more than 2100 precipitation gauges in Iran, and applied various statistical and categorical metrics and error decomposition methods. The results indicated that ERA-40 performed worst, followed by ERA-20CM, which showed only minor improvements over ERA-40. ERA-20C considerably outperformed its predecessors, benefiting from assimilation of observational data. Although several previous studies have reported full superiority of ERA5 over ERA-Interim, our results revealed several shortcomings compared with ERA-Interim, in ERA5 precipitation estimates for Iran. Both ERA-Interim and ERA5 performed best overall, with ERA-Interim showing better statistical and categorical skill scores, and ERA5 performing better in estimating extreme precipitations. These results suggest that the accuracy of ERA precipitation products improved from ERA-40 to ERA-Interim, but not consistently from ERA-Interim to ERA5. These findings are useful for model development at global scale and for hydrological applications in Iran.

scholarly journals Temporal disaggregation of satellite-derived monthly precipitation estimates and the resulting propagation of error in partitioning of water at the land surface

2001 ◽  
Vol 5 (1) ◽  
pp. 27-38 ◽  
Author(s):  
S.A. Margulis ◽  
D. Entekhabi
Keyword(s):  
Land Surface ◽  
Error Propagation ◽  
Temporal Structure ◽  
Low Earth Orbit ◽  
Monthly Precipitation ◽  
Monthly Scale ◽  
Precipitation Estimates ◽  
Temporal Disaggregation ◽  
Using Data ◽  
Hydrological Applications

Abstract. Global estimates of precipitation can now be made using data from a combination of geosynchronous and low earth-orbit satellites. However, revisit patterns of polar-orbiting satellites and the need to sample mixed-clouds scenes from geosynchronous satellites leads to the coarsening of the temporal resolution to the monthly scale. There are prohibitive limitations to the applicability of monthly-scale aggregated precipitation estimates in many hydrological applications. The nonlinear and threshold dependencies of surface hydrological processes on precipitation may cause the hydrological response of the surface to vary considerably based on the intermittent temporal structure of the forcing. Therefore, to make the monthly satellite data useful for hydrological applications (i.e. water balance studies, rainfall-runoff modelling, etc.), it is necessary to disaggregate the monthly precipitation estimates into shorter time intervals so that they may be used in surface hydrology models. In this study, two simple statistical disaggregation schemes are developed for use with monthly precipitation estimates provided by satellites. The two techniques are shown to perform relatively well in introducing a reasonable temporal structure into the disaggregated time series. An ensemble of disaggregated realisations was routed through two land surface models of varying complexity so that the error propagation that takes place over the course of the month could be characterised. Results suggest that one of the proposed disaggregation schemes can be used in hydrological applications without introducing significant error. Keywords: precipitation, temporal disaggregation, hydrological modelling, error propagation

scholarly journals Global‐ and Local‐Scale High‐Resolution Event Catalogs for Algorithm Testing

2019 ◽  
Author(s):  
Lisa Linville ◽  
Ronald Chip Brogan ◽  
Christopher Young ◽  
Katherine Anderson Aur
Keyword(s):  
Global Scale ◽  
Local Scale ◽  
Algorithm Performance ◽  
Directional Information ◽  
Event Sequences ◽  
University Of Utah ◽  
International Monitoring ◽  
Using Data ◽  
The University ◽  
Global And Local

ABSTRACT During the development of new seismic data processing methods, the verification of potential events and associated signals can present a nontrivial obstacle to the assessment of algorithm performance, especially as detection thresholds are lowered, resulting in the inclusion of significantly more anthropogenic signals. Here, we present two 14 day seismic event catalogs, a local‐scale catalog developed using data from the University of Utah Seismograph Stations network, and a global‐scale catalog developed using data from the International Monitoring System. Each catalog was built manually to comprehensively identify events from all sources that were locatable using phase arrival timing and directional information from seismic network stations, resulting in significant increases compared to existing catalogs. The new catalogs additionally contain challenging event sequences (prolific aftershocks and small events at the detection and location threshold) and novel event types and sources (e.g., infrasound only events and long‐wall mining events) that make them useful for algorithm testing and development, as well as valuable for the unique tectonic and anthropogenic event sequences they contain.

Merits and caveats of propensity scores to adjust for confounding

2018 ◽  
Vol 34 (10) ◽  
pp. 1629-1635 ◽  
Author(s):  
Edouard L Fu ◽  
Rolf H H Groenwold ◽  
Carmine Zoccali ◽  
Kitty J Jager ◽  
Merel van Diepen ◽  
...  
Keyword(s):  
Risk Factors ◽  
The Netherlands ◽  
Health Outcomes ◽  
Observational Data ◽  
Propensity Scores ◽  
Cooperative Study ◽  
Dialysis Patients ◽  
Proper Understanding ◽  
The Past ◽  
Using Data

Abstract Proper adjustment for confounding is essential when estimating the effects of treatments or risk factors on health outcomes in observational data. To this end, various statistical methods have been developed. In the past couple of years, the use of propensity scores (PSs) to control for confounding has increased. Proper understanding of this method is necessary to critically appraise research in which it is applied. In this article, we provide an overview of PS methods, explaining their concept, advantages and possible disadvantages. Furthermore, the use of PS matching, PS adjustment and PS weighting is illustrated using data from the Netherlands Cooperative Study on the Adequacy of Dialysis (NECOSAD) cohort of dialysis patients.

Editorial overview: Water quality: A new challenge for global scale model development and application

2019 ◽  
Vol 36 ◽  
pp. A1-A5 ◽  
Author(s):  
Nynke Hofstra ◽  
Carolien Kroeze ◽  
Martina Flörke ◽  
Michelle TH van Vliet
Keyword(s):  
Water Quality ◽  
Model Development ◽  
Global Scale ◽  
Scale Model

scholarly journals Very Short-Term Surface Solar Irradiance Forecasting Based On FengYun-4 Geostationary Satellite

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2606 ◽  
Author(s):  
Liwei Yang ◽  
Xiaoqing Gao ◽  
Jiajia Hua ◽  
Pingping Wu ◽  
Zhenchao Li ◽  
...  
Keyword(s):  
Solar Irradiance ◽  
Near Infrared ◽  
Motion Vector ◽  
Skill Score ◽  
Geostationary Satellite ◽  
Short Term ◽  
Direct Normal Irradiance ◽  
Skill Scores ◽  
Meteorological Observatory ◽  
Using Data

An algorithm to forecast very short-term (30–180 min) surface solar irradiance using visible and near infrared channels (AGRI) onboard the FengYun-4A (FY-4A) geostationary satellite was constructed and evaluated in this study. The forecasting products include global horizontal irradiance (GHI) and direct normal irradiance (DNI). The forecast results were validated using data from Chengde Meteorological Observatory for four typical months (October 2018, and January, April, and July 2019), representing the four seasons. Particle Image Velocimetry (PIV) was employed to calculate the cloud motion vector (CMV) field from the satellite images. The forecast results were compared with the smart persistence (SP) model. A seasonal study showed that July and April forecasting is more difficult than during October and January. For GHI forecasting, the algorithm outperformed the SP model for all forecasting horizons and all seasons, with the best result being produced in October; the skill score was greater than 20%. For DNI, the algorithm outperformed the SP model in July and October, with skill scores of about 12% and 11%, respectively. Annual performances were evaluated; the results show that the normalized root mean square error (nRMSE) value of GHI for 30–180 min horizon ranged from 26.78% to 36.84%, the skill score reached a maximum of 20.44% at the 30-min horizon, and the skill scores were all above 0 for all time horizons. For DNI, the maximum skill score was 6.62% at the 180-min horizon. Overall, compared with the SP model, the proposed algorithm is more accurate and reliable for GHI forecasting and slightly better for DNI forecasting.

scholarly journals Evaluation of the Sensitivity of SMOS L-VOD to Forest Above-Ground Biomass at Global Scale

2020 ◽  
Vol 12 (9) ◽  
pp. 1450
Author(s):  
Arnaud Mialon ◽  
Nemesio J. Rodríguez-Fernández ◽  
Maurizio Santoro ◽  
Sassan Saatchi ◽  
Stéphane Mermoz ◽  
...  
Keyword(s):  
Large Scale ◽  
Correlation Coefficients ◽  
Global Scale ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Northern Latitudes ◽  
Ocean Salinity ◽  
Good Proxy ◽  
Using Data ◽  
The Tropics

The present study evaluates the L band Vegetation Optical Depth (L-VOD) derived from the Soil Moisture and Ocean Salinity (SMOS) satellite to monitor Above Ground Biomass (AGB) at a global scale. Although SMOS L-VOD has been shown to be a good proxy for AGB in Africa and Tropics, little is known about this relationship at large scale. In this study, we further examine this relationship at a global scale using the latest AGB maps from Saatchi et al. and GlobBiomass computed using data acquired during the SMOS period. We show that at a global scale the L-VOD from SMOS is well-correlated with the AGB estimates from Saatchi et al. and GlobBiomass with the Pearson’s correlation coefficients (R) of 0.91 and 0.94 respectively. Although AGB estimates in Africa and the Tropics are well-captured by SMOS L-VOD (R > 0.9), the relationship is less straightforward for the dense forests over the northern latitudes (R = 0.32 and 0.69 with Saatchi et al. and GlobBiomass respectively). This paper gives strong evidence in support of the sensitivity of SMOS L-VOD to AGB estimates at a globale scale, providing an interesting alternative and complement to exisiting sensors for monitoring biomass evolution. These findings can further facilitate research on biomass now that SMOS is providing more than 10 years of data.

Testing the efficiency of global-scale conservation planning by using data on Andean amphibians

2001 ◽  
pp. 50-78
Author(s):  
Don R. Church ◽  
Claude Gascon ◽  
Megan Van Fossen ◽  
Grisel Velasquez ◽  
Luis A. Solorzano
Keyword(s):  
Conservation Planning ◽  
Global Scale ◽  
Using Data

Marine dinocysts, acritarchs and less well-known NPP: tintinnids, ostracod and foraminiferal linings, copepod and worm remains

2020 ◽  
pp. SP511-2020-55
Author(s):  
P. J. Mudie ◽  
F. Marret ◽  
P. R. Gurdebeke ◽  
J. D. Hartman ◽  
P. C. Reid
Keyword(s):  
Global Scale ◽  
Laboratory Culture ◽  
Trophic Relationships ◽  
Marine Biodiversity ◽  
Polar Regions ◽  
Egg Capsules ◽  
Resting Cysts ◽  
Ocean Carbon ◽  
Copepod Eggs ◽  
Annual Scale

AbstractNine non-pollen palynomorph (NPP) groups occur in Quaternary marine and brackish water sediments; these groups represent various planktonic or micro- to macrobenthic organisms. Some extant NPP were previously classified as fossil Acritarcha, Chitinozoa or scolecodonts. We refer to reviews of these fossils and their applications for Paleozoic-Mesozoic biostratigraphy and palaeoecology but focus on extant marine NPP that can be studied by laboratory culture, genetics or micro-geochemical methods. Marine NPP include resting cysts of planktonic dinoflagellates and prasinophytes, tintinnids and other cilates, copepod eggs and skeletal remains, and various microzoobenthos: microforaminiferal organic linings, ostracod mandibles and carapace linings, various worm egg capsules and mouthparts. New micro-Fourier Transform Infrared spectroscopy spectra suggest the probable affinities of the tintinnid cyst type P and Beringiella. Our applications in marine biodiversity and provincialism studies emphasize under-studied polar regions and neglected ice-algae nano-plankton, and compare climate-based NPP distributions to Ocean Biogeographic Information System realms. Trophic relationships are outlined using sediment-trap studies. Seasonal to annual-scale investigations of palaeoproduction provide new perspectives on ocean carbon budgets during times of rapid climate change and atmospheric carbon increase. More taxonomic and source-linkage studies of non-dinocyst marine NPP are needed but we outline potentials for studies of hemispheric or global-scale shifts in marine food webs as driven by ocean warming.

scholarly journals Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Donglai Jiao ◽  
Nannan Xu ◽  
Fan Yang ◽  
Ke Xu
Keyword(s):  
Observational Data ◽  
Correlation Coefficient ◽  
Global Scale ◽  
Precipitation Trend ◽  
Strongly Correlated ◽  
Precipitation Data ◽  
Weather Forecasts ◽  
Fifth Generation ◽  
Data Assessment ◽  
Long Time

AbstractERA5 is the latest fifth-generation reanalysis global atmosphere dataset from the European Centre for Medium-Range Weather Forecasts, replacing ERA-Interim as the next generation of representative satellite-observational data on the global scale. ERA5 data have been evaluated and applied in different regions, but the performances are inconsistent. Meanwhile, there are few precise evaluations of ERA5 precipitation data over long time series have been performed in Chinese mainland. This study evaluates the temporal-spatial performance of ERA5 precipitation data from 1979 to 2018 based on gridded-ground meteorological station observational data across China. The results showed that ERA5 data could capture the annual and seasonal patterns of observed precipitation in China well, with correlation coefficient values ranging from 0.796 to 0.945, but ERA5 slightly overestimated precipitation in the summer. Nonetheless, the results also showed that the accuracy of the precipitation products was strongly correlated with topographic distribution and climatic divisions. The performance of ERA5 shows spatial inherently across China that the highest correlation coefficient values locate in eastern, Northwestern and North China and the lowest biases locate in Southeast China. This study provides a reliable data assessment of the ERA5 data and precipitation trend analyses in China. The results provide accuracy references for the further use of precipitation satellite data for hydrological calculations and climate numerical simulations.

scholarly journals Assessing Reseller Performance from the Perspective of the Supplier

1992 ◽  
Vol 29 (2) ◽  
pp. 238-253 ◽  
Author(s):  
Nirmalya Kumar ◽  
Louis W. Stern ◽  
Ravi S. Achrol
Keyword(s):  
Construct Validity ◽  
Organizational Effectiveness ◽  
Reliability And Validity ◽  
Global Scale ◽  
Different Types ◽  
Using Data

The objective of the authors’ study was to develop a reliable and valid scale to assess reseller performance from the perspective of the supplier. To specify the domain of reseller performance, four different conceptualizations of organizational effectiveness were explored, leading to the identification of eight facets of reseller performance. Using data collected on the resellers of two different suppliers, the authors investigated the reliability and validity of three different types of scales—facet, composite, and global. Results indicate that two composite scales, a 5-item global scale, and seven 3-item facet scales have acceptable levels of reliability, construct validity, and generalizability.

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