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Lukens, Katherine E., and Ernesto Hugo Berbery. "Winter Storm Tracks and Related Weather in the NCEP Climate Forecast System Weeks 3–4 Reforecasts for North America." Weather and Forecasting 34, no. 3 (June 1, 2019): 751–72. http://dx.doi.org/10.1175/waf-d-18-0113.1.
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Abstract This article examines to what extent the NCEP Climate Forecast System (CFS) weeks 3–4 reforecasts reproduce the CFS Reanalysis (CFSR) storm-track properties, and if so, whether the storm-track behavior can contribute to the prediction of related winter weather in North America. The storm tracks are described by objectively tracking isentropic potential vorticity (PV) anomalies for two periods (base, 1983–2002; validation, 2003–10) to assess their value in a more realistic forecast mode. Statistically significant positive PV biases are found in the storm-track reforecasts. Removal of systematic errors is found to improve general storm-track features. CFSR and Reforecast (CFSRR) reproduces well the observed intensity and spatial distributions of storm-track-related near-surface winds, with small yet significant biases found in the storm-track regions. Removal of the mean wind bias further reduces the error on average by 12%. The spatial distributions of the reforecast precipitation correspond well with the reanalysis, although significant positive biases are found across the contiguous United States. Removal of the precipitation bias reduces the error on average by 25%. The bias-corrected fields better depict the observed variability and exhibit additional improvements in the representation of winter weather associated with strong-storm tracks (the storms with more intense PV). Additionally, the reforecasts reproduce the characteristic intensity and frequency of hazardous strong-storm winds. The findings suggest a potential use of storm-track statistics in the advancement of subseasonal-to-seasonal weather prediction in North America.
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Guan, Yuanhong, Jieshun Zhu, Bohua Huang, Zeng-Zhen Hu, and James L. Kinter III. "South Pacific Ocean Dipole: A Predictable Mode on Multiseasonal Time Scales." Journal of Climate 27, no. 4 (February 10, 2014): 1648–58. http://dx.doi.org/10.1175/jcli-d-13-00293.1.
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Abstract Evaluating the climate hindcasts for 1982–2009 from the NCEP CFS Reanalysis and Reforecast (CFSRR) project using the Climate Forecast System, version 2 (CFSv2), this study identifies substantial areas of high prediction skill of the sea surface temperature (SST) in the South Pacific. The skill is the highest in the extratropical oceans on seasonal-to-interannual time scales, and it is only slightly lower than that for the El Niño–Southern Oscillation (ENSO). Two regions with the highest prediction skills in the South Pacific in both the CFSv2 and persistence hindcasts coincide with the active centers of opposite signs in the South Pacific Ocean dipole (SPOD) mode, a seesaw between the subtropical and extratropical SST in the South Pacific with a strong phase locking to austral summer. Interestingly, the CFSv2 prediction exhibits skillful predictions made three seasons ahead, more superior to the persistence forecast, suggesting significant dynamical predictability of the SPOD. An austral “spring predictability barrier” is noted in both the dynamical and persistence hindcasts. An analysis of the observational and model data suggests that the SPOD mode is significantly associated with ENSO, as an oceanic response to the atmospheric planetary wave trains forced by the anomalous atmospheric heating in the western Pacific. Although previous studies have demonstrated that the pattern of subtropical SST dipole is ubiquitous in the Southern Ocean, the SPOD has been least known and studied, compared with its counterparts in the south Indian and Atlantic Oceans. Since the SPOD is the most predictable oceanic mode in the whole Southern Hemisphere, its climate effects for local and remote regions should be further studied.
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Guan, Hong, and Yuejian Zhu. "Development of Verification Methodology for Extreme Weather Forecasts." Weather and Forecasting 32, no. 2 (February 22, 2017): 479–91. http://dx.doi.org/10.1175/waf-d-16-0123.1.
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Abstract In 2006, the statistical postprocessing of the National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS) and North American Ensemble Forecast System (NAEFS) was implemented to enhance probabilistic guidance. Anomaly forecasting (ANF) is one of the NAEFS products, generated from bias-corrected ensemble forecasts and reanalysis climatology. The extreme forecast index (EFI), based on a raw ensemble forecast and model-based climatology, is another way to build an extreme weather forecast. In this work, the ANF and EFI algorithms are applied to extreme cold temperature and extreme precipitation forecasts during the winter of 2013/14. A highly correlated relationship between the ANF and EFI allows the determination of two sets of thresholds to identify extreme cold and extreme precipitation events for the two algorithms. An EFI of −0.78 (0.687) is approximately equivalent to a −2σ (0.95) ANF for the extreme cold event (extreme precipitation) forecast. The performances of the two algorithms in forecasting extreme cold events are verified against analysis for different model versions, reference climatology, and forecasts. The verification results during the winter of 2013/14 indicate that ANF forecasts more extreme cold events with a slightly higher skill than EFI. The bias-corrected forecast performs much better than the raw forecast. The current upgrade of the GEFS has a beneficial effect on the extreme cold weather forecast. Using the NCEP Climate Forecast System Reanalysis and Reforecast (CFSRR) as a climate reference gives a slightly better score than the 40-yr reanalysis. The verification methodology is also extended to an extreme precipitation case, showing a broad potential use in the future.
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Slater, Andrew G. "Surface Solar Radiation in North America: A Comparison of Observations, Reanalyses, Satellite, and Derived Products*." Journal of Hydrometeorology 17, no. 1 (December 29, 2015): 401–20. http://dx.doi.org/10.1175/jhm-d-15-0087.1.
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Abstract Observations of daily surface solar or shortwave radiation data from over 4000 stations have been gathered, covering much of the continental United States as well as portions of Alberta and British Columbia, Canada. The quantity of data increases almost linearly from 1998, when only several hundred stations had data. A quality-control procedure utilizing threshold values along with computing the clear-sky radiation envelope for individual stations was implemented to both screen bad data and rescue informative data. Over two-thirds of the observations are seen as acceptable. There are 15 different surface solar radiation products assessed relative to observations, including reanalyses [Twentieth-Century Reanalysis (20CR), CFS Reanalysis and Reforecast (CFSRR), ERA-Interim, Japanese 55-year Reanalysis Project (JRA-55), MERRA, NARR, and NCEP–NCAR Reanalysis 1 (NCEP-1)], derived products [observations from the CRU and NCEP-1 (CRU–NCEP); Daily Surface Weather and Climatological Summaries (Daymet); Global Land Data Assimilation System, version 1 (GLDAS-1); Global Soil Wetness Project Phase 3 (GSWP3); Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP); and phase 2 of the North American Land Data Assimilation System (NLDAS-2)], and two satellite products (CERES and GOES). All except the CERES product have daily or finer temporal resolution. The RMSE of spatial biases is greater than 18 W m−2 for 13 of the 15 products over the summer season (June–August). None of the daily resolution products fulfill all three desirable criteria of low (<5%) annual or seasonal bias, high correlation with observed cloudiness, and correct distribution of clear-sky radiation. Some products display vestiges of underlying algorithm issues [e.g., from the Mountain Microclimate Simulation Model, version 4.3 (MTCLIM 4.3)] or bias-correction methods. A new bias-correction method is introduced that preserves clear-sky radiation values and better replicates cloudiness statistics. The current quantity of data over the continental United States suggests that a solar radiation product based on, or enhanced with, observations is feasible.
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Burger, J. H., and W. D. Hamman. "The relationship between the accounting sustainable growth rate and the cash flow sustainable growth rate." South African Journal of Business Management 30, no. 4 (December 31, 1999): 101–9. http://dx.doi.org/10.4102/sajbm.v30i4.761.
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The accounting sustainable growth rate is used by financial managers and bankers to determine possible financing needs and investment opportunities for companies. However, the authors contend that as this rate is based upon accrual figures that do not reflect the cash position of a company, it could lead to situations in which the company could grow itself into cash problems. In this regard they suggest a cash flow sustainable growth rate (CFSGR), which is defined as the rate at which the company can grow whilst still maintaining a target cash balance in the balance sheet. The relationship between the accounting SGR and CFSGR is then investigated. The authors found that while the accounting SGR is not affected by the non-cash components of working capital, nor by any changes in the non-cash components of working capital, the CFSGR is. Both rates are influenced by the profitability of the company. The accounting SGR is influenced by the growth in sales, while CFSGR is not. The authors do not contend that the CFSGR should replace the accounting SGR, but that it is in the company's best interest to take cognizance of the CFSGR and its implications for the company's growth and cash position.
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Gu, Pengfei, Yongxiang Wu, Guodong Liu, Chengcheng Xia, Gaoxu Wang, Jing Xia, Ke Chen, Xiaohua Huang, and Daiyuan Li. "Application of meteorological element combination-driven SWAT model based on meteorological datasets in alpine basin." Water Supply 22, no. 3 (November 22, 2021): 3307–24. http://dx.doi.org/10.2166/ws.2021.397.
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Abstract Thus far, reanalysis-based meteorological products have drawn little attention to the influence of meteorological elements of products on hydrological modeling. This study aims to evaluate the hydrological application potential of the precipitation, temperature, and solar radiation of the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR) in an alpine basin. The precipitation, temperature, and solar radiation of the gauge-observed meteorological dataset (GD), CFSR, and CMADS were cross-combined, and 20 scenarios were constructed to drive the SWAT model. From the comprehensive comparisons of all scenarios, we drew the following conclusions: (1) among the three meteorological elements, precipitation has the greatest impact on the simulation results, and using GD precipitation from sparse stations yielded better performance than CMADS and CFSR; (2) although the SWAT modeling driven by CMADS and CFSR performed poorly, with CMADS underestimation and CFSR overestimation, the temperature and solar radiation of CMADS and CFSR can be an alternative data source for streamflow simulation; (3) models using GD precipitation, CFSR temperature, and CFSR solar radiation as input yielded the best performance in streamflow simulation, suggesting that these data sources can be applied to this data-scarce alpine region.
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Afonso, João Maria de Sousa, Natalia Fedorova, Vladimir Levit, and Lianet Hernández Pardo. "Estudo de baixa visibilidade no aeroporto de Porto Alegre: Simulação numérica com o modelo PAFOG." Revista Ibero-Americana de Ciências Ambientais 10, no. 6 (November 5, 2019): 114–30. http://dx.doi.org/10.6008/cbpc2179-6858.2019.006.0011.
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A elaboração deste trabalho foi motivada pela carência de um método eficaz de previsão de visibilidade no aeroporto Salgado Filho (Porto Alegre, RS). Os objetivos principais são: 1) simular, usando o modelo PAFOG, os eventos de visibilidade baixa causados por nevoeiros de radiação no aeroporto de Porto Alegre nos anos 2008 e 2009 e 2) avaliar os resultados das simulações inicializadas com diferentes fontes de dados. Perfis verticais de radiossondagem e de dados de previsão (CFSR-2) do modelo CFSR foram utilizados para as inicializações do modelo. Nas inicializações foram utilizados dados de superfície com as duas fontes. Variáveis na camada limite (CL) foram calculadas com dados do modelo CFSR (análise CFSR-1 e CFSR-2). Os dados de altitude foram obtidos de radiossonda e CFSR-2 (resolução 0,5°). Foram selecionados todos (13) casos de nevoeiros de radiação nas horas de observação de radiossondagem. Foram analisadas as condições físicas da baixa troposfera: 1) analise sinótica e de meso escala com produtos de reanálise do NCEP e CFSR-1 com 2,5° e satélite GOES-12; 2) dinâmica acima da CL com CFSR-1 e CFSR-2 com 0,5°, e 3) perfil vertical de umidade relativa (UR) com radiossondagem e produtos do CFSR-2 com 0,5°. Foram feitas 25 inicializações com perfis de radiossondagem e 48 com perfis do CFRS-2 com antecedência de até 22h. Nos horários das inicializações as análises sinótica, dinâmica e de perfil de UR mostraram condições favoráveis ao uso do PAFOG. Em algumas situações foram detectados erros da extrapolação do ponto de orvalho com os perfis do CFSR-2. A influência das extremidades de Sistemas Frontais (SF) em algumas inicializações gerou vento geostrófico superior ao limite suportado pelo modelo PAFOG. Com perfis do CFSR-2 o PAFOG acertou visibilidade de nevoeiro em 36 simulações e não acertou em 12 (em 10 devido aos erros na extrapolação de UR e em 2 devido a influência de SF). Com o CFSR-2 as melhores simulações foram inicializadas às 1200UTC do dia anterior ao evento e às 0000UTC do dia do evento. Com perfis de radiossonda o PAFOG acertou visibilidade de nevoeiro em 22 simulações e não em 3. Os resultados mostraram um grande potencial do uso do PAFOG para a previsão de nevoeiros no aeroporto Salgado Filho, porém, também mostraram necessidade para adaptar o modelo às condições climáticas da região.
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Ostrowski, Krzysztof. "Does the Carbon Fibre Coating Reinforcement Have an Influence on the Bearing Capacity of High-Performance Self-Compacting Fibre-Reinforced Concrete?" Materials 12, no. 24 (December 5, 2019): 4054. http://dx.doi.org/10.3390/ma12244054.
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This study investigated the impact of the location of a carbon fibre coated reinforcement ring (CFCRr) inside the structure of high-performance self-compacting fibre-reinforced concrete (HPSCFRC). Nowadays, cement matrix is considered as an alternative binder when reinforcing concrete structures with composite materials. Due to the plastic behavior of composite structures at relatively low temperatures when carbon fibres are reinforced with epoxy resin, the author attempted to locate carbon fibres inside a concrete structure. Thanks to this, the reinforcement will be less vulnerable to high temperatures (during a fire) and more compatible with concrete. The fibres act as a perimeter reinforcement that is compatible with the concrete mixture. The position of the CFCRr in the structure of concrete has an influence on the load capacity, stiffness and stress-strain behavior of concrete elements. The research was conducted on circular shape short concrete columns and tested under axial compression. The results demonstrated that by including CFCRr inside a concrete specimen, the maximum compressive strength decreases with an increase in the number of composite rings and a greater distance from the vertical axis of symmetry to the edge of the element. It has been proven in these studies that carbon fibres do not have good adhesive properties between CFCRr and a concrete mixture. As a result of this phenomenon, a shear surface is created, which leads to crack propagation along the CFCRr. Therefore, the presented idea of an internal CFCRr should not be used when designing new concrete structures.
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Afonso, João Maria de Sousa, Vladimir Levit, and Natalia Fedorova. "Estudo de baixa visibilidade no aeroporto de Porto Alegre: processos sinóticos e termodinâmicos." Revista Ibero-Americana de Ciências Ambientais 10, no. 6 (November 5, 2019): 131–45. http://dx.doi.org/10.6008/cbpc2179-6858.2019.006.0012.
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O nevoeiro é um fenômeno associado a redução da visibilidade, causando prejuízos em diversos sectores socioeconômicos no estado do Rio Grande do Sul, influenciando principalmente no encerramento das atividades aeroportuárias. Os objetivos principais são: 1) classificar os tipos de nevoeiros em Porto Alegre em um período de 2 anos (2008-2009) a partir da análise dos processos sinóticos e termodinâmicos e 2) avaliar o comportamento de produtos de reanálise do NCEP, reanalise (CFSR-1) e previsão (CFSR-2) do CFSR nas situações de formação de nevoeiro de radiação. Variáveis meteorológicas da estação de superfície do aeroporto foram utilizadas para: 1) o estudo de frequência de nevoeiros e 2) a análise das condições de formação dos nevoeiros. Os sistemas sinóticos atuantes durante os eventos de nevoeiros foram analisados utilizando diversos produtos de reanálise do NCEP e do CFSR e imagens de satélite GOES-12. As condições termodinâmicas foram analisadas usando dados de radiossondagem e perfis plotados com o produto CFSR-1 e CFSR-2. Foram encontrados 82 casos de nevoeiros com duração entre 10 minutos e 11 horas, ocorrendo principalmente no outono e no inverno. Um único caso ocorreu com chuva. A análise sinotica foi elaborada para os 23 casos que ocorreram no horário de observação de radiossondagem. O estudo dos processos sinóticos mostrou que 13 eventos foram nevoeiros de radiação e 10 frontais. Os perfis do CFSR-1 mostraram camada úmida entre 1000-950hPa, com umidade de 86-89%. Os perfis do CFSR-2 mostraram camada úmida entre a altura 2m até o nível de 950hPa com umidade de 80-96.9%. No geral, os perfis de toda a troposfera acima desses níveis foram típicos para os casos de nevoeiros radiação, com baixa umidade e inversões de subsidência. Concluímos que 1) a situação sinóptica foi apresentada semelhante pelo NCEP e o CFSR, 2) os perfis do CFSR mostram a estrutura da troposfera típica para os eventos de nevoeiro de radiação, excluindo a camada superficial.
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Bapat, P. M., and L. L. Tavlarides. "Mass transfer in a liquid-liquid CFSTR." AIChE Journal 31, no. 4 (April 1985): 659–66. http://dx.doi.org/10.1002/aic.690310416.
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Roth, Vincent, and Tatenda Lemann. "Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands." Hydrology and Earth System Sciences 20, no. 2 (March 1, 2016): 921–34. http://dx.doi.org/10.5194/hess-20-921-2016.
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Abstract. Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.
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Roth, V., and T. Lemann. "Comparing CFSR and conventional weather data for discharge and sediment loss modelling with SWAT in small catchments in the Ethiopian Highlands." Hydrology and Earth System Sciences Discussions 12, no. 10 (October 27, 2015): 11053–82. http://dx.doi.org/10.5194/hessd-12-11053-2015.
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Abstract. Accurate rainfall data are the key input parameter for modelling river discharge and sediment loss. Remote areas of Ethiopia often lack adequate precipitation data and where it is available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and sediment loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 102 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed sediment loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Sediment loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and sediment loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.
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Silva, Viviane B. S., Vernon E. Kousky, and R. Wayne Higgins. "Daily Precipitation Statistics for South America: An Intercomparison between NCEP Reanalyses and Observations." Journal of Hydrometeorology 12, no. 1 (February 1, 2011): 101–17. http://dx.doi.org/10.1175/2010jhm1303.1.
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Abstract In this study, the authors document the extent to which the precipitation statistics of the new CFS reanalysis (CFSR) represent an improvement over the earlier reanalyses: the NCEP–NCAR reanalysis (R1) and the NCEP–DOE Second Atmospheric Model Intercomparison Project (AMIP-II) reanalysis (R2). An intercomparison between the CFSR, R1, R2, and observations over South America was made for the period 1979–2006. The CFSR shows notable improvements in the large-scale precipitation patterns compared with the previous reanalyses (R1 and R2). In spite of these improvements, the CFSR has substantial biases in intensity and frequency of occurrence of rainfall events. Over west-central Brazil, the core region of the South American monsoon system (SAMS), the CFSR displays a dry bias during the onset phase of the SAMS wet season and a wet bias during the peak and decay phases of the SAMS wet season. The CFSR also displays a dry bias along the South American coast near the mouth of the Amazon and along the east coast of northeastern Brazil. A wet bias exists in all seasons over southeast Brazil and over the Andes Mountains.
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Roth, V., and T. Lemann. "Comparing CFSR and conventional weather data for discharge and sediment loss modelling with SWAT in small catchments in the Ethiopian Highlands." Hydrology and Earth System Sciences Discussions 12, no. 2 (February 18, 2015): 2113–53. http://dx.doi.org/10.5194/hessd-12-2113-2015.
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Abstract. Accurate rainfall data is the key input parameter for modelling river discharge and sediment loss. Remote areas of Ethiopia often lack adequate precipitation data and where it is available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2010. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and sediment loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 102 to 477 ha. Uncalibrated simulation results were compared to observed river discharge and observed sediment loss over a period of 25 years. The conventional weather data resulted in satisfactory discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for two of three gauging stations. Sediment loss simulation with conventional weather inputs yielded satisfactory outputs for all three watersheds, while the CFSR weather input resulted in one very good result and two unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and sediment loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should only be used with caution in remote areas with no conventional weather data and might be better adapted to larger watersheds than the ones used in this study.
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Zhang, Limin, Xianyong Meng, Hao Wang, Mingxiang Yang, and Siyu Cai. "Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China." Water 12, no. 4 (April 1, 2020): 996. http://dx.doi.org/10.3390/w12040996.
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Reanalysis datasets can provide alternative and complementary meteorological data sources for hydrological studies or other scientific studies in regions with few gauge stations. This study evaluated the accuracy of two reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR), against gauge observations (OBS) by using interpolation software and statistical indicators in Northeast China (NEC), as well as their annual average spatial and monthly average distributions. The reliability and applicability of the two reanalysis datasets were assessed as inputs in a hydrological model (SWAT) for runoff simulation in the Hunhe River Basin. Statistical results reveal that CMADS performed better than CFSR for precipitation and temperature in NEC with the indicators closer to optimal values (the ratio of standard deviations of precipitation and maximum/minimum temperature from CMADS were 0.92, 1.01, and 0.995, respectively, while that from CFSR were 0.79, 1.07, and 0.897, respectively). Hydrological modelling results showed that CMADS + SWAT and OBS + SWAT performed far better than CFSR + SWAT on runoff simulations. The Nash‒Sutcliffe efficiency (NSE) of CMADS + SWAT and OBS + SWAT ranged from 0.54 to 0.95, while that of CFSR + SWAT ranged from −0.07 to 0.85, exhibiting poor performance. The CMADS reanalysis dataset is more accurate than CFSR in NEC and is a suitable input for hydrological simulations.
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Liu, Jun, Donghui Shanguan, Shiyin Liu, and Yongjian Ding. "Evaluation and Hydrological Simulation of CMADS and CFSR Reanalysis Datasets in the Qinghai-Tibet Plateau." Water 10, no. 4 (April 20, 2018): 513. http://dx.doi.org/10.3390/w10040513.
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Multisource reanalysis datasets provide an effective way to help us understand hydrological processes in inland alpine regions with sparsely distributed weather stations. The accuracy and quality of two widely used datasets, the China Meteorological Assimilation Driving Datasets to force the SWAT model (CMADS), and the Climate Forecast System Reanalysis (CFSR) in the Qinghai-Tibet Plateau (TP), were evaluated in this paper. The accuracy of daily precipitation, max/min temperature, relative humidity and wind speed from CMADS and CFSR are firstly evaluated by comparing them with results obtained from 131 meteorological stations in the TP. Statistical results show that most elements of CMADS are superior to those of CFSR. The average correlation coefficient (R) between the maximum temperature and the minimum temperature of CMADS and CFSR ranged from 0.93 to 0.97. The root mean square error (RMSE) for CMADS and CFSR ranged from 3.16 to 3.18 °C, and ranged from 5.19 °C to 8.14 °C respectively. The average R of precipitation, relative humidity, and wind speed for CMADS are 0.46; 0.88 and 0.64 respectively, while they are 0.43, 0.52, and 0.37 for CFSR. Gridded observation data is obtained using the professional interpolation software, ANUSPLIN. Meteorological elements from three gridded data have a similar overall distribution but have a different partial distribution. The Soil and Water Assessment Tool (SWAT) is used to simulate hydrological processes in the Yellow River Source Basin of the TP. The Nash Sutcliffe coefficients (NSE) of CMADS+SWAT in calibration and validation period are 0.78 and 0.68 for the monthly scale respectively, which are better than those of CFSR+SWAT and OBS+SWAT in the Yellow River Source Basin. The relationship between snowmelt and other variables is measured by GeoDetector. Air temperature, soil moisture, and soil temperature at 1.038 m has a greater influence on snowmelt than others.
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Worqlul, A. W., B. Maathuis, A. A. Adem, S. S. Demissie, S. Langan, and T. S. Steenhuis. "Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia." Hydrology and Earth System Sciences 18, no. 12 (December 5, 2014): 4871–81. http://dx.doi.org/10.5194/hess-18-4871-2014.
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Abstract. Planning for drought relief and floods in developing countries is greatly hampered by the lack of a sufficiently dense network of weather stations measuring precipitation. In this paper, we test the utility of three satellite products to augment the ground-based precipitation measurement to provide improved spatial estimates of rainfall. The three products are the Tropical Rainfall Measuring Mission (TRMM) product (3B42), Multi-Sensor Precipitation Estimate–Geostationary (MPEG) and the Climate Forecast System Reanalysis (CFSR). The accuracy of the three products is tested in the Lake Tana basin in Ethiopia, where 38 weather stations were available in 2010 with a full record of daily precipitation amounts. Daily gridded satellite-based rainfall estimates were compared to (1) point-observed ground rainfall and (2) areal rainfall in the major river sub-basins of Lake Tana. The result shows that the MPEG and CFSR satellites provided the most accurate rainfall estimates. On average, for 38 stations, 78 and 86% of the observed rainfall variation is explained by MPEG and CFSR data, respectively, while TRMM explained only 17% of the variation. Similarly, the areal comparison indicated a better performance for both MPEG and CFSR data in capturing the pattern and amount of rainfall. MPEG and CFSR also have a lower root mean square error (RMSE) compared to the TRMM 3B42 satellite rainfall. The bias indicated that TRMM 3B42 was, on average, unbiased, whereas MPEG consistently underestimated the observed rainfall. CFSR often produced large overestimates.
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Worqlul, A. W., B. Maathuis, A. A. Adem, S. S. Demissie, S. Langan, and T. S. Steenhuis. "Comparison of TRMM, MPEG and CFSR rainfall estimation with the ground observed data for the Lake Tana Basin, Ethiopia." Hydrology and Earth System Sciences Discussions 11, no. 7 (July 14, 2014): 8013–38. http://dx.doi.org/10.5194/hessd-11-8013-2014.
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Abstract. Planning of drought relief and floods in developing countries is greatly hampered by lack of a sufficiently dense network of weather station measuring precipitation. In this paper we test the utility of three satellite products to augment the ground based precipitation measurement to provide improved spatial estimates of rainfall. The three products are: Tropical Rainfall Measuring Mission (TRMM) product (3B42), Multi-Sensor Precipitation Estimate-Geostationary (MPEG) and Climate Forecast System Reanalysis (CFSR). The accuracy of three products is tested in the Lake Tana Basin in Ethiopia where in 2010 38 weather stations were available with a full record of daily precipitation amounts. Daily grid satellite based rainfall estimates were compared to: (1) point observed ground rainfall (2) areal rainfall in the major river sub-basins of Lake Tana. The result shows that, the MPEG and CFSR satellite provided most accurate rainfall estimates. On the average for 38 stations 78 and 86% of the observed rainfall variation is explained by MPEG and CFSR data respectively while TRIMM explained only 17% of the variation. Similarly, the areal comparison indicated a better performance for both MPEG and CFSR data in capturing the pattern and amount of rainfall. MPEG and CFSR have also a lower RMSE compared to the TRMM satellite rainfall. The Bias indicated that, the MPEG is consistent in underestimating the observed rainfall while the TRMM and CFSR were not consistent; they overestimated for some and underestimated for the others.
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Meng, Jesse, Rongqian Yang, Helin Wei, Michael Ek, George Gayno, Pingping Xie, and Kenneth Mitchell. "The Land Surface Analysis in the NCEP Climate Forecast System Reanalysis." Journal of Hydrometeorology 13, no. 5 (October 1, 2012): 1621–30. http://dx.doi.org/10.1175/jhm-d-11-090.1.
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Abstract The NCEP Climate Forecast System Reanalysis (CFSR) uses the NASA Land Information System (LIS) to create its land surface analysis: the NCEP Global Land Data Assimilation System (GLDAS). Comparing to the previous two generations of NCEP global reanalyses, this is the first time a coupled land–atmosphere data assimilation system is included in a global reanalysis. Global observed precipitation is used as direct forcing to drive the land surface analysis, rather than the typical reanalysis approach of using precipitation assimilating from a background atmospheric model simulation. Global observed snow cover and snow depth fields are used to constrain the simulated snow variables. This paper describes 1) the design and implementation of GLDAS/LIS in CFSR, 2) the forcing of the observed global precipitation and snow fields, and 3) preliminary results of global and regional soil moisture content and land surface energy and water budgets closure. With special attention made during the design of CFSR GLDAS/LIS, all the source and sink terms in the CFSR land surface energy and water budgets can be assessed and the total budgets are balanced. This is one of many aspects indicating improvements in CFSR from the previous NCEP reanalyses.
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Alemayehu, Tadesse, Fidelis Kilonzo, Ann van Griensven, and Willy Bauwens. "Evaluation and application of alternative rainfall data sources for forcing hydrologic models in the Mara Basin." Hydrology Research 49, no. 4 (November 14, 2017): 1271–82. http://dx.doi.org/10.2166/nh.2017.081.
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Abstract Accurate and spatially distributed rainfall data are crucial for a realistic simulation of the hydrological processes in a watershed. However, limited availability of observed hydro-meteorological data often challenges the rainfall–runoff modelling efforts. The main goal of this study is to evaluate the Climate Forecast System Reanalysis (CFSR) and Water and Global Change (WATCH) rainfall by comparing them with gauge observations for different rainfall regimes in the Mara Basin (Kenya/Tanzania). Additionally, the skill of these rainfall datasets to simulate the observed streamflow is assessed using the Soil and Water Assessment Tool (SWAT). The daily CFSR and WATCH rainfall show a poor performance (up to 52% bias and less than 0.3 correlation) when compared with gauge rainfall at grid and basin scale, regardless of the rainfall regime. However, the correlations for both CFSR and WATCH substantially improve at monthly scale. The 95% prediction uncertainty (95PPU) of the simulated daily streamflow, as forced by CFSR and WATCH rainfall, bracketed more than 60% of the observed streamflows. We however note high uncertainty for the high flow regime. Yet, the monthly and annual aggregated CFSR and WATCH rainfall can be a useful surrogate for gauge rainfall data for hydrologic application in the study area.
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Mo, Kingtse C., Lindsey N. Long, Youlong Xia, S. K. Yang, Jae E. Schemm, and Michael Ek. "Drought Indices Based on the Climate Forecast System Reanalysis and Ensemble NLDAS." Journal of Hydrometeorology 12, no. 2 (April 1, 2011): 181–205. http://dx.doi.org/10.1175/2010jhm1310.1.
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Abstract Drought indices derived from the Climate Forecast System Reanalysis (CFSR) are compared with indices derived from the ensemble North American Land Data Assimilation System (NLDAS) and the North American Regional Reanalysis (NARR) over the United States. Uncertainties in soil moisture, runoff, and evapotranspiration (E) from three systems are assessed by comparing them with limited observations, including E from the AmeriFlux data, soil moisture from the Oklahoma Mesonet and the Illinois State Water Survey, and streamflow data from the U.S. Geological Survey (USGS). The CFSR has positive precipitation (P) biases over the western mountains, the Pacific Northwest, and the Ohio River valley in winter and spring. In summer, it has positive biases over the Southeast and large negative biases over the Great Plains. These errors limit the ability to use the standardized precipitation indices (SPIs) derived from the CFSR to measure the severity of meteorological droughts. To compare with the P analyses, the Heidke score for the 6-month SPI derived from the CFSR is on average about 0.5 for the three-category classification of drought, floods, and neutral months. The CFSR has positive E biases in spring because of positive biases in downward solar radiation and high potential evaporation. The negative E biases over the Great Plains in summer are due to less P and soil moisture in the root zone. The correlations of soil moisture percentile between the CFSR and the ensemble NLDAS are regionally dependent. The correlations are higher over the area east of 100°W and the West Coast. There is less agreement between them over the western interior region.
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Dao, Duy Minh, Jianzhong Lu, Xiaoling Chen, Sameh A. Kantoush, Doan Van Binh, Phamchimai Phan, and Nguyen Xuan Tung. "Predicting Tropical Monsoon Hydrology Using CFSR and CMADS Data over the Cau River Basin in Vietnam." Water 13, no. 9 (May 8, 2021): 1314. http://dx.doi.org/10.3390/w13091314.
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To improve knowledge of this matter, the potential application of two gridded meteorological products (GMPs), the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) and Climate Forecast System Reanalysis (CFSR), are compared for the first time with data from ground-based meteorological stations over 6 years, from 2008 to 2013, over the Cau River basin (CRB), northern Vietnam. Statistical indicators and the Soil and Water Assessment Tool (SWAT) model are employed to investigate the hydrological performances of the GMPs against the data of 17 rain gauges distributed across the CRB. The results show that there are strong correlations between the temperature reanalysis products in both CMADS and CFSR and those obtained from the ground-based observations (the correlation coefficients range from 0.92 to 0.97). The CFSR data overestimate precipitation (percentage bias approximately 99%) at both daily and monthly scales, whereas the CMADS product performs better, with obvious differences (compared to the ground-based observations) in high-terrain areas. Regarding the simulated river flows, CFSR-SWAT produced “unsatisfactory”, while CMADS-SWAT (R2 > 0.76 and NSE > 0.78) performs better than CFSR-SWAT on the monthly scale. This assessment of the applicative potential of GMPs, especially CMADS, may further provide an additional rapid alternative for water resource research and management in basins with similar hydro-meteorological conditions.
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Wang, Jiande, Wanqiu Wang, Xiouhua Fu, and Kyong-Hwan Seo. "Tropical intraseasonal rainfall variability in the CFSR." Climate Dynamics 38, no. 11-12 (May 11, 2011): 2191–207. http://dx.doi.org/10.1007/s00382-011-1087-0.
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Gulakhmadov, Aminjon, Xi Chen, Manuchekhr Gulakhmadov, Zainalobudin Kobuliev, Nekruz Gulahmadov, Jiabin Peng, Zhengyang Li, and Tie Liu. "Evaluation of the CRU TS3.1, APHRODITE_V1101, and CFSR Datasets in Assessing Water Balance Components in the Upper Vakhsh River Basin in Central Asia." Atmosphere 12, no. 10 (October 12, 2021): 1334. http://dx.doi.org/10.3390/atmos12101334.
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In this study, the applicability of three gridded datasets was evaluated (Climatic Research Unit (CRU) Time Series (TS) 3.1, “Asian Precipitation—Highly Resolved Observational Data Integration Toward the Evaluation of Water Resources” (APHRODITE)_V1101, and the climate forecast system reanalysis dataset (CFSR)) in different combinations against observational data for predicting the hydrology of the Upper Vakhsh River Basin (UVRB) in Central Asia. Water balance components were computed, the results calibrated with the SUFI-2 approach using the calibration of soil and water assessment tool models (SWAT–CUP) program, and the performance of the model was evaluated. Streamflow simulation using the SWAT model in the UVRB was more sensitive to five parameters (ALPHA_BF, SOL_BD, CN2, CH_K2, and RCHRG_DP). The simulation for calibration, validation, and overall scales showed an acceptable correlation between the observed and simulated monthly streamflow for all combination datasets. The coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) showed “excellent” and “good” values for all datasets. Based on the R2 and NSE from the “excellent” down to “good” datasets, the values were 0.91 and 0.92 using the observational datasets, CRU TS3.1 (0.90 and 0.90), APHRODITE_V1101+CRU TS3.1 (0.74 and 0.76), APHRODITE_V1101+CFSR (0.72 and 0.78), and CFSR (0.67 and 0.74) for the overall scale (1982–2006). The mean annual evapotranspiration values from the UVRB were about 9.93% (APHRODITE_V1101+CFSR), 25.52% (APHRODITE_V1101+CRU TS3.1), 2.9% (CFSR), 21.08% (CRU TS3.1), and 27.28% (observational datasets) of annual precipitation (186.3 mm, 315.7 mm, 72.1 mm, 256.4 mm, and 299.7 mm, out of 1875.9 mm, 1236.9 mm, 2479 mm, 1215.9 mm, and 1098.5 mm). The contributions of the snowmelt to annual runoff were about 81.06% (APHRODITE_V1101+CFSR), 63.12% (APHRODITE_V1101+CRU TS3.1), 82.79% (CFSR), 81.66% (CRU TS3.1), and 67.67% (observational datasets), and the contributions of rain to the annual flow were about 18.94%, 36.88%, 17.21%, 18.34%, and 32.33%, respectively, for the overall scale. We found that gridded climate datasets can be used as an alternative source for hydrological modeling in the Upper Vakhsh River Basin in Central Asia, especially in scarce-observation regions. Water balance components, simulated by the SWAT model, provided a baseline understanding of the hydrological processes through which water management issues can be dealt with in the basin.
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Lee, Hyun-Mu, Du-Jin Park, and Seong-Yeol Kim. "Immediate Effects of Dynamic Neck Training Combined with the Hold-Relax Technique for Young College Students with Video Display Terminal Syndrome." International Journal of Athletic Therapy and Training 21, no. 1 (January 2016): 50–55. http://dx.doi.org/10.1123/ijatt.2015-0006.
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The purpose of this study was to identify the changes in the cervical range of motion (CROM), the cervical flexion-relaxation ratio (CFRR), and neck pain after dynamic neck training (DNT) combined with hold-relax technique (HRT) for young college students with video display terminal (VDT) syndrome. For this study, 15 young college students with VDT syndrome were recruited. DNT combined with HRT was applied to all participants in a sitting position for 15 min. Postintervention, the CROM and the CFRR were significantly higher than preintervention, and neck pain had significantly decreased. DNT combined with HRT showed immediate effects on the CROM, the CFRR, and neck pain in young college students with VDT syndrome.
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Setti, Sridhara, Rathinasamy Maheswaran, Venkataramana Sridhar, Kamal Kumar Barik, Bruno Merz, and Ankit Agarwal. "Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling." Atmosphere 11, no. 11 (November 20, 2020): 1252. http://dx.doi.org/10.3390/atmos11111252.
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Precipitation is essential for modeling the hydrologic behavior of watersheds. There exist multiple precipitation products of different sources and precision. We evaluate the influence of different precipitation product on model parameters and streamflow predictive uncertainty using a soil water assessment tool (SWAT) model for a forest dominated catchment in India. We used IMD (gridded rainfall dataset), TRMM (satellite product), bias-corrected TRMM (corrected satellite product) and NCEP-CFSR (reanalysis dataset) over a period from 1998–2012 for simulating streamflow. The precipitation analysis using statistical measures revealed that the TRMM and CFSR data slightly overestimate rainfall compared to the ground-based IMD data. However, the TRMM estimates improved, applying a bias correction. The Nash–Sutcliffe (and R2) values for TRMM, TRMMbias and CFSR, are 0.58 (0.62), 0.62 (0.63) and 0.52 (0.54), respectively at model calibrated with IMD data (Scenario A). The models of each precipitation product (Scenario B) yielded Nash–Sutcliffe (and R2) values 0.71 (0.76), 0.74 (0.78) and 0.76 (0.77) for TRMM, TRMMbias and CFSR datasets, respectively. Thus, the hydrological model-based evaluation revealed that the model calibration with individual rainfall data as input showed increased accuracy in the streamflow simulation. IMD and TRMM forced models to perform better in capturing the streamflow simulations than the CFSR reanalysis-driven model. Overall, our results showed that TRMM data after proper correction could be a good alternative for ground observations for driving hydrological models.
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Serrano, J., J. M. Jamilla, B. C. Hernandez, and E. Herrera. "EVALUATING HYDROLOGIC MODEL PERFORMANCE OF GLOBAL AND LOCAL WEATHER DATA INPUTS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W6-2021 (November 18, 2021): 265–71. http://dx.doi.org/10.5194/isprs-archives-xlvi-4-w6-2021-265-2021.
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Abstract. Runoffs from hydrologic models are often used in flood models, among other applications. These runoffs are converted from rainfall, signifying the importance of weather data accuracy. A common challenge for modelers is local weather data sparsity in most watersheds. Global weather datasets are often used as alternative. This study investigates the statistical significance and accuracy between using local weather data for hydrologic models and using the Climate Forecast System Reanalysis (CFSR), a global weather dataset. The Soil and Water Assessment Tool (SWAT) was used to compare the two weather data inputs in terms of generated discharges. Both long-term and event-based results were investigated to compare the models against absolute discharge values. The basin’s average total annual rainfall from the CFSR-based model (4062 mm) was around 1.5 times the local weather-based model (2683 mm). These basin precipitations yielded annual average flows of 53.4 cms and 26.7 cms for CFSR-based and local weather-based models, respectively. For the event-based scenario, the dates Typhoon Ketsana passed through the Philippine Area of Responsibility were checked. CFSR only read a spatially averaged maximum daily rainfall of 18.8 mm while the local gauges recorded 157.2 mm. Calibration and validation of the models were done using the observed discharges in Sto. Niño Station. The calibration of local weather-based model yielded satisfactory results for the Nash-Sutcliffe Efficiency (NSE), percent of bias (PBIAS), and ratio of the RMSE to the standard deviation of measured data (RSR). Meanwhile, the calibration of CFSR model yielded unsatisfactory values for all three parameters.
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Irvem, Ahmet, and Mustafa Ozbuldu. "Evaluation of the performance of CFSR reanalysis data set for estimating reference evapotranspiration (ET0) in Turkey." Italian Journal of Agrometeorology, no. 2 (January 29, 2023): 49–61. http://dx.doi.org/10.36253/ijam-1325.
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Evapotranspiration is a key process and a necessary parameter for hydrological, meteorological, and agricultural studies. However, the calculation of actual evapotranspiration is very challenging and costly. Therefore, reference evapotranspiration (ET0) calculated using meteorological data is generally preferred over actual evapotranspiration. However, it is challenging to get complete and accurate data from meteorology stations in rural and mountainous regions. This study examined the suitability of the Climate Forecast System Reanalysis (CFSR) reanalysis data set as an alternative to meteorological observation stations to compute seasonal reference evapotranspiration for seven different climatic regions of Turkey. The ET0 calculations using the CFSR reanalysis dataset for 1987-2017 were compared to data at 259 weather stations observed in Turkey. As a result of statistical evaluations, it has been determined that the most successful predicted season is winter (C’ = 0.64-0.89, SPAEF= 0.63-0.81). The most successful estimations for this season were obtained from coastal areas with low elevations. The weakest estimations were obtained for the summer season (C’ = 0.52-0.85, SPAEF= 0.59-0.77). These results show that the ET0 estimation ability of the CFSR reanalysis dataset is satisfactory for the study area. In addition, it has been observed that CFSR tends to overestimate the observation data, especially in the southern and western regions. These findings indicate that the results of the ET0 calculation using the CFSR reanalysis data set are relatively successful for the study area. However, the data should be evaluated with observation data before being used, especially in the summer models.
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Cuceloglu, Gokhan, and Izzet Ozturk. "Assessing the Impact of CFSR and Local Climate Datasets on Hydrological Modeling Performance in the Mountainous Black Sea Catchment." Water 11, no. 11 (October 30, 2019): 2277. http://dx.doi.org/10.3390/w11112277.
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Precise representation of precipitation input is one of the predominant factors affecting the simulation of hydrological processes in catchments. Choosing the representative climate datasets is crucial to obtain accurate model results, especially in mountainous regions. Hence, this study assesses the suitability of the Climate Forecasting System Reanalysis (CFSR) and local climate data to simulate the streamflow at multiple gauges in the data-scarce mountainous Black Sea catchment. Moreover, the applicability of using the elevations band in the model is also tested. The Soil and Water Assessment Tool (SWAT) is used as a hydrological simulator. Calibration and uncertainty analysis are performed by using SWAT-CUP with the Sequential Uncertainty Fitting (SUFI-2) algorithm based on monthly streamflow data at six different hydrometric stations located at different altitudes. The results reveal that the CFSR dataset provides quite reasonable agreements between the simulated and the observed streamflow at the gauge stations compared to the local dataset. However, SWAT simulations with both datasets result in poor performance for the upstream catchments of the study area. Considering orographic precipitation by applying elevation bands to the local climate dataset using CFSR data leads also to significant improvements to the model’s performance. Model results obtained with both climate datasets result in similar objective metrics, and larger uncertainty with a coefficient variation (CV) ranging from 73% to 107%. This paper mainly highlights that (i) global climate datasets (i.e., CFSR) can be a good alternative especially for data-scarce regions, (ii) elevation band application can improve the model performance for the catchments with high elevation gradients, and iii) CFSR data can be used to determine precipitation lapse rate in data scarce-regions.
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Zhang, Dandan, Mou Leong Tan, Sharifah Rohayah Sheikh Dawood, Narimah Samat, Chun Kiat Chang, Ranjan Roy, Yi Lin Tew, and Mohd Amirul Mahamud. "Comparison of NCEP-CFSR and CMADS for Hydrological Modelling Using SWAT in the Muda River Basin, Malaysia." Water 12, no. 11 (November 23, 2020): 3288. http://dx.doi.org/10.3390/w12113288.
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Identification of reliable alternative climate input data for hydrological modelling is important to manage water resources and reduce water-related hazards in ungauged or poorly gauged basins. This study aims to evaluate the capability of the National Centers for Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR) and China Meteorological Assimilation Driving Dataset for the Soil and Water Assessment Tool (SWAT) model (CMADS) for simulating streamflow in the Muda River Basin (MRB), Malaysia. The capability was evaluated in two perspectives: (1) the climate aspect—validation of precipitation, maximum and minimum temperatures from 2008 to 2014; and (2) the hydrology aspect—comparison of the accuracy of SWAT modelling by the gauge station, NCEP-CFSR and CMADS products. The results show that CMADS had a better performance than NCEP-CFSR in the climate aspect, especially for the temperature data and daily precipitation detection capability. For the hydrological aspect, the gauge station had a “very good” performance in a monthly streamflow simulation, followed by CMADS and NCEP-CFSR. In detail, CMADS showed an acceptable performance in SWAT modelling, but some improvements such as bias correction and further SWAT calibration are needed. In contrast, NCEP-CFRS had an unacceptable performance in validation as it dramatically overestimated the low flows of MRB and contains time lag in peak flows estimation.
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Irvem, Ahmet, and Mustafa Ozbuldu. "Evaluation of Satellite and Reanalysis Precipitation Products Using GIS for All Basins in Turkey." Advances in Meteorology 2019 (December 29, 2019): 1–11. http://dx.doi.org/10.1155/2019/4820136.
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Use of the satellite and reanalysis precipitation products, as supplementary data sources, are steadily rising for hydrometeorological applications, especially in data-sparse areas. However, the accuracy of these data sets is often lacking, especially in Turkey. This study evaluates the accuracy of satellite precipitation product (TRMM 3B42V7) and reanalysis precipitation product (NCEP-CFSR) against rain gauge observations for the 1998–2010 periods. Average annual precipitation for the 25 basins in Turkey was calculated using rain gauge precipitation data from 225 stations. The inverse distance weighting (IDW) method was used to calculate areal precipitation for each basin using GIS. According to the results of statistical analysis, the coefficient of determination for the TRMM product gave satisfactory results (R2 > 0.88). However, R2 for the CFSR data set ranges from 0.35 for the Eastern Black Sea basin to 0.93 for the West Mediterranean basin. RMSE was calculated to be 95.679 mm and 128.097 mm for the TRMM and CFSR data, respectively. The NSE results of TRMM data showed very good performance for 6 basins, while the PBias value showed very good performance for 7 basins. The NSE results of CFSR data showed very good performance for 3 basins, while the PBias value showed very good performance for 6 basins.
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Zhang, Shixiao, Yang Lang, Furong Yang, Xinran Qiao, Xiuni Li, Yuefei Gu, Qi Yi, Lifeng Luo, and Qingyun Duan. "Hydrological Modeling in the Upper Lancang-Mekong River Basin Using Global and Regional Gridded Meteorological Re-Analyses." Water 15, no. 12 (June 12, 2023): 2209. http://dx.doi.org/10.3390/w15122209.
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Multisource meteorological re-analyses provide the most reliable forcing data for driving hydrological models to simulate streamflow. We aimed to assess different hydrological responses through hydrological modeling in the upper Lancang-Mekong River Basin (LMRB) using two gridded meteorological datasets, Climate Forecast System Re-analysis (CFSR) and the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS). We selected the Pearson’s correlation coefficient (R), percent bias (PBIAS), and root mean square error (RMSE) indices to compare the six meteorological variables of the two datasets. The spatial distributions of the statistical indicators in CFSR and CMADS, namely, the R, PBIAS, and RMSE values, were different. Furthermore, the soil and water assessment tool plus (SWAT+) model was used to perform hydrological modeling based on CFSR and CMADS meteorological re-analyses in the upper LMRB. The different meteorological datasets resulted in significant differences in hydrological responses, reflected by variations in the sensitive parameters and their optimal values. The differences in the calibrated optimal values for the sensitive parameters led to differences in the simulated water balance components between the CFSR- and CMADS-based SWAT+ models. These findings could help improve the understanding of the strengths and weaknesses of different meteorological re-analysis datasets and their roles in hydrological modeling.
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Kim, Ji-Eun, and M. Joan Alexander. "Tropical Precipitation Variability and Convectively Coupled Equatorial Waves on Submonthly Time Scales in Reanalyses and TRMM." Journal of Climate 26, no. 10 (May 8, 2013): 3013–30. http://dx.doi.org/10.1175/jcli-d-12-00353.1.
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Abstract Tropical precipitation characteristics are investigated using the Tropical Rainfall Measuring Mission (TRMM) 3-hourly estimates, and the result is compared with five reanalyses including the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim), Modern Era Retrospective Analysis for Research and Applications (MERRA), National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) reanalysis (NCEP1), NCEP–U.S. Department of Energy (DOE) reanalysis (NCEP2), and NCEP–Climate Forecast System Reanalysis (CFSR). Precipitation characteristics are evaluated in terms of the mean, convectively coupled equatorial wave activity, frequency characteristics, diurnal cycle, and seasonality of regional precipitation variability associated with submonthly scale waves. Generally the latest reanalyses such as ERA-Interim, MERRA, and CFSR show better performances than NCEP1 and NCEP2. However, all the reanalyses are still different from observations. Besides the positive mean bias in the reanalyses, a spectral analysis revealed that the reanalyses have overreddened spectra with persistent rainfall. MERRA has the most persistent rainfall, and CFSR appears to have the most realistic variability. The diurnal cycle in NCEP1 is extremely exaggerated relative to TRMM. The low-frequency waves with the period longer than 3 days are relatively well represented in ERA-Interim, MERRA, and CFSR, but all the reanalyses have significant deficiencies in representing convectively coupled equatorial waves and variability in the high-frequency range.
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ISLEK, Fulya, Yalçın YÜKSEL, and Furkan YUKSEL. "Assessment of Spectral Wave Model Performance Using Three Wind Speeds in the Eastern Mediterranean Sea." International Journal of Environment and Geoinformatics 10, no. 2 (June 15, 2023): 82–100. http://dx.doi.org/10.30897/ijegeo.1159096.
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In the study, the performance of the MIKE 21 SW (Spectral Wave) model using the three different wind fields, namely ERA-Interim, ERA5, and CFSR was evaluated in the Eastern Mediterranean Sea. Model results were calibrated with four buoy measurements by tuning physical model parameters. Wave simulations showed a strong sensitivity to the whitecapping parameter (Cds). Calibrated MIKE 21 SW model run to validate at two buoy measurements. Considering the statistical error measures: (i) ERA-I predicted lower significant wave heights and wave periods than ERA5 and CFSR, (ii) statistical error measures (bias, RMSE, and SI) obtained with CFSR were calculated slightly higher than those obtained using ERA5 (iii) ERA5 performed slightly better in the hindcast of Eastern Mediterranean wave properties than ERA-I. As a result of all evaluations, the highest correlation coefficient (R), relatively low statistical error measures, and slightly better accuracy were provided by the model settings forced with ERA5 wind fields.
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Frumkin, Jeffrey A., and Michael F. Doherty. "Target bounds on reaction selectivity via Feinberg's CFSTR equivalence principle." AIChE Journal 64, no. 3 (September 28, 2017): 926–39. http://dx.doi.org/10.1002/aic.15968.
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Schoeberl, M. R., A. E. Dessler, and T. Wang. "Simulation of stratospheric water vapor and trends using three reanalyses." Atmospheric Chemistry and Physics Discussions 12, no. 3 (March 29, 2012): 8433–63. http://dx.doi.org/10.5194/acpd-12-8433-2012.
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Abstract. The domain-filling, forward trajectory calculation model developed by Schoeberl and Dessler (2011) is extended to the 1979–2010 period. We compare results from NASA's MERRA, NCEP's CFSR, and ECMWF's ERAi reanalyses with HALOE, MLS, and balloon observations. The CFSR based simulation produces a wetter stratosphere than MERRA, and ERAi produces a drier stratosphere than MERRA. We find that ERAi temperatures are cold biased compared to Singapore sondes and MERRA, which explains the ERAi result, and the CFSR grid does not resolve the cold point tropopause, which explains its relatively higher water vapor concentration. The pattern of dehydration locations is also different among the three reanalyses. ERAi dehydration pattern stretches across the Pacific while CFSR and MERRA are concentrate dehydration activity in the West Pacific. CSFR and ERAi also show less dehydration activity in the West Pacific Southern Hemisphere than MERRA. The models' lower stratospheres tend to be dry at high northern latitudes because of too little methane-derived water appears to be descending from the middle stratosphere. Using the tropical tape recorder signal, we find that MERRA vertical ascent is 15% too weak while ERAi is 30% too strong. The models tend to reproduce the observed weakening of the 100-hPa annual cycle in zonal mean water vapor as it propagates to middle latitudes. Finally, consistent with the observations, the models show less than 0.2 ppm decade−1 trends in water vapor both at mid-latitudes and in the tropics.
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Schoeberl, M. R., A. E. Dessler, and T. Wang. "Simulation of stratospheric water vapor and trends using three reanalyses." Atmospheric Chemistry and Physics 12, no. 14 (July 24, 2012): 6475–87. http://dx.doi.org/10.5194/acp-12-6475-2012.
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Abstract. The domain-filling, forward trajectory calculation model developed by Schoeberl and Dessler (2011) is extended to the 1979–2010 period. We compare results from NASA's MERRA, NCEP's CFSR, and ECMWF's ERAi reanalyses with HALOE, MLS, and balloon observations. The CFSR based simulation produces a wetter stratosphere than MERRA, and ERAi produces a drier stratosphere than MERRA. We find that ERAi 100 hPa temperatures are cold biased compared to Singapore sondes and MERRA, which explains the ERAi result, and the CFSR grid does not resolve the cold point tropopause, which explains its relatively higher water vapor concentration. The pattern of dehydration locations is also different among the three reanalyses. ERAi dehydration pattern stretches across the Pacific while CFSR and MERRA concentrate dehydration activity in the West Pacific. CSFR and ERAi also show less dehydration activity in the West Pacific Southern Hemisphere than MERRA. The trajectory models' lower northern high latitude stratosphere tends to be dry because too little methane-derived water descends from the middle stratosphere. Using the MLS tropical tape recorder signal, we find that MERRA vertical ascent is 15% too weak while ERAi is 30% too strong. The trajectory model reproduces the observed reduction in the amplitude of the 100-hPa annual cycle in zonal mean water vapor as it propagates to middle latitudes. Finally, consistent with the observations, the models show less than 0.2 ppm decade−1 trend in water vapor both at mid-latitudes and in the tropics.
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Heng, Zhiwei, Yunfei Fu, Guosheng Liu, Renjun Zhou, Yu Wang, Renmin Yuan, Jingchao Guo, and Xue Dong. "A Study of the Distribution and Variability of Cloud Water Using ISCCP, SSM/I Cloud Product, and Reanalysis Datasets." Journal of Climate 27, no. 9 (April 23, 2014): 3114–28. http://dx.doi.org/10.1175/jcli-d-13-00031.1.
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Abstract In this paper, the global distribution of cloud water based on International Satellite Cloud Climatology Project (ISCCP), Moderate Resolution Imaging Spectroradiometer (MODIS), CloudSat Cloud Profiling Radar (CPR), European Center for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim), and Climate Forecast System Reanalysis (CFSR) datasets is presented, and the variability of cloud water from ISCCP, the Special Sensor Microwave Imager (SSM/I), ERA-Interim, and CFSR data over the time period of 1995 through 2009 is discussed. The results show noticeable differences in cloud water over land and over ocean, as well as latitudinal variations. Large values of cloud water are mainly distributed over the North Pacific and Atlantic Oceans, eastern ITCZ, regions off the west coast of the continents as well as tropical rain forest. Cloud water path (CWP), liquid water path (LWP), and ice water path (IWP) from these datasets show a relatively good agreement in distributions and zonal means. The results of trend analyzing show an increasing trend in CWP, and also a significant increasing trend of LWP can be found in the dataset of ISCCP, ERA-Interim, and CFSR over the ocean. Besides the long-term variation trend, rises of cloud water are found when temperature and water vapor exhibit a positive anomaly. EOF analyses are also applied to the anomalies of cloud water, the first dominate mode of CWP and IWP are similar, and a phase change can be found in the LWP time coefficient around 1999 in ISCCP and CFSR and around 2002 in ERA-Interim.
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Yang, Rongqian, Michael Ek, and Jesse Meng. "Surface Water and Energy Budgets for the Mississippi River Basin in Three NCEP Reanalyses." Journal of Hydrometeorology 16, no. 2 (April 1, 2015): 857–73. http://dx.doi.org/10.1175/jhm-d-14-0056.1.
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Abstract Surface water and energy budgets from the National Centers for Environmental Prediction–U.S. Department of Energy (NCEP–DOE) Atmospheric Model Intercomparison Project (AMIP-II) Global Reanalysis 2 (GR2), the North American Regional Reanalysis (NARR), and the NCEP Climate Forecast System Reanalysis (CFSR) are compared here with each other and with available observations over the Mississippi River basin. The comparisons in seasonal cycle, interannual variation, and annual mean over a 31-yr period show that there are a number of noticeable differences and similarities in the large-scale basin averages. Warm season precipitation and runoff in the GR2 are too large compared to the observations, and seasonal surface water variation is small. By contrast, the precipitation in both NARR and CFSR is more reasonable and in better agreement with the observation, although the corresponding seasonal runoff is very small. The main causes of the differences in both surface parameterization and approach used in assimilating the observed precipitation datasets and snow analyses are then discussed. Despite the discrepancies in seasonal water budget components, seasonal energy budget terms in the three reanalyses are close to each other and to available observations. The interannual variations in both water and energy budgets are comparable. This study shows that the CFSR achieves a large improvement over the GR2, indicating that the CFSR dataset can be used in climate variability studies. Nonetheless, improved land surface parameterization schemes and data assimilation techniques are needed to depict the surface water and energy climates better, in particular, the variation in seasonal runoff.
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Boltz, Joshua P., Bruce R. Johnson, Imre Takács, Glen T. Daigger, Eberhard Morgenroth, Doris Brockmann, Róbert Kovács, Jason M. Calhoun, Jean-Marc Choubert, and Nicolas Derlon. "Biofilm carrier migration model describes reactor performance." Water Science and Technology 75, no. 12 (March 17, 2017): 2818–28. http://dx.doi.org/10.2166/wst.2017.160.
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The accuracy of a biofilm reactor model depends on the extent to which physical system conditions (particularly bulk-liquid hydrodynamics and their influence on biofilm dynamics) deviate from the ideal conditions upon which the model is based. It follows that an improved capacity to model a biofilm reactor does not necessarily rely on an improved biofilm model, but does rely on an improved mathematical description of the biofilm reactor and its components. Existing biofilm reactor models typically include a one-dimensional biofilm model, a process (biokinetic and stoichiometric) model, and a continuous flow stirred tank reactor (CFSTR) mass balance that [when organizing CFSTRs in series] creates a pseudo two-dimensional (2-D) model of bulk-liquid hydrodynamics approaching plug flow. In such a biofilm reactor model, the user-defined biofilm area is specified for each CFSTR; thereby, Xcarrier does not exit the boundaries of the CFSTR to which they are assigned or exchange boundaries with other CFSTRs in the series. The error introduced by this pseudo 2-D biofilm reactor modeling approach may adversely affect model results and limit model-user capacity to accurately calibrate a model. This paper presents a new sub-model that describes the migration of Xcarrier and associated biofilms, and evaluates the impact that Xcarrier migration and axial dispersion has on simulated system performance. Relevance of the new biofilm reactor model to engineering situations is discussed by applying it to known biofilm reactor types and operational conditions.
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Khedhaouiria, Dikra, Alain Mailhot, and Anne-Catherine Favre. "Stochastic Post-Processing of CFSR Daily Precipitation across Canada." Atmosphere-Ocean 56, no. 2 (March 12, 2018): 104–16. http://dx.doi.org/10.1080/07055900.2018.1434122.
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Wen, Caihong, Yan Xue, and Arun Kumar. "Ocean–Atmosphere Characteristics of Tropical Instability Waves Simulated in the NCEP Climate Forecast System Reanalysis." Journal of Climate 25, no. 18 (April 28, 2012): 6409–25. http://dx.doi.org/10.1175/jcli-d-11-00477.1.
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Abstract The NCEP Climate Forecast System Reanalysis (CFSR) represents a new effort with the first guess from a high-resolution coupled system and offers prospects for improved simulation of mesoscale air–sea coupled variability. This study aims to describe the characteristics of ocean–atmosphere covariability associated with tropical instability waves (TIWs) in the Pacific for the CFSR, and to assess how well they agree with in situ and satellite observations. Multiyear daily high-resolution CFSR data are used to describe variability associated with TIWs. Results show that TIW-induced SST variations exhibit pronounced seasonal and interannual variability that are tightly connected with cold tongue variations. The analysis illustrates coherent patterns associated with TIWs, both in the ocean and the atmosphere. Moisture and air temperature maximums are located west of SST maximums, leading to downstream displacement of surface pressure minimums relative to SST maximums. Surface winds accelerate (decelerate) over warm (cold) water, and a thermally direct circulation is created. Significant signals are observed in low-level cloud cover, which are closely in phase with surface wind convergences. The magnitudes of TIW-induced surface wind, surface pressure, and cloud cover perturbations agree well with in situ and satellite observations. Further analysis shows that surface net heat flux perturbations are dominated by latent heat fluxes and have a large negative feedback on TIW SST variability (~40 W m−2 °C−1). Water vapor perturbation is the primary factor contributing to changes in latent heat fluxes, while SST-induced wind perturbation plays a secondary role. The analysis presented here highlights that the CFSR provides an unprecedented opportunity to study the physical mechanisms for the TIWs, as well as their influences on climate variability.
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Santanello, Joseph A., Joshua Roundy, and Paul A. Dirmeyer. "Quantifying the Land–Atmosphere Coupling Behavior in Modern Reanalysis Products over the U.S. Southern Great Plains." Journal of Climate 28, no. 14 (July 13, 2015): 5813–29. http://dx.doi.org/10.1175/jcli-d-14-00680.1.
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Abstract The coupling of the land with the planetary boundary layer (PBL) on diurnal time scales is critical to regulating the strength of the connection between soil moisture and precipitation. To improve understanding of land–atmosphere (L–A) interactions, recent studies have focused on the development of diagnostics to quantify the strength and accuracy of the land–PBL coupling at the process level. In this paper, the authors apply a suite of local land–atmosphere coupling (LoCo) metrics to modern reanalysis (RA) products and observations during a 17-yr period over the U.S. southern Great Plains. Specifically, a range of diagnostics exploring the links between soil moisture, evaporation, PBL height, temperature, humidity, and precipitation is applied to the summertime monthly mean diurnal cycles of the North American Regional Reanalysis (NARR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR). Results show that CFSR is the driest and MERRA the wettest of the three RAs in terms of overall surface–PBL coupling. When compared against observations, CFSR has a significant dry bias that impacts all components of the land–PBL system. CFSR and NARR are more similar in terms of PBL dynamics and response to dry and wet extremes, while MERRA is more constrained in terms of evaporation and PBL variability. Each RA has a unique land–PBL coupling that has implications for downstream impacts on the diurnal cycle of PBL evolution, clouds, convection, and precipitation as well as representation of extremes and drought. As a result, caution should be used when treating RAs as truth in terms of their water and energy cycle processes.
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Berg, Larry K., Laura D. Riihimaki, Yun Qian, Huiping Yan, and Maoyi Huang. "The Low-Level Jet over the Southern Great Plains Determined from Observations and Reanalyses and Its Impact on Moisture Transport." Journal of Climate 28, no. 17 (September 1, 2015): 6682–706. http://dx.doi.org/10.1175/jcli-d-14-00719.1.
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Abstract This study utilizes six commonly used reanalysis products, including the NCEP–Department of Energy Reanalysis 2 (NCEP2), NCEP Climate Forecast System Reanalysis (CFSR), ECMWF interim reanalysis (ERA-Interim), Japanese 25-year Reanalysis Project (JRA-25), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and North American Regional Reanalysis (NARR), to evaluate features of the southern Great Plains low-level jet (LLJ) above the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF) Southern Great Plains site. Two sets of radiosonde data are utilized: the six-week Midlatitude Continental Convective Clouds Experiment (MC3E) and a 10-yr period spanning 2001 through 2010. All six reanalyses are compared to MC3E data, while only the NARR, MERRA, and CFSR are compared to the 10-yr data. The reanalyses are able to represent most aspects of the composite LLJ profile, although there is a tendency for each reanalysis to overestimate the wind speed between the nose of the LLJ (at approximately 900 mb) and a pressure level of 700 mb. There are large discrepancies in the number of LLJs observed and derived from the reanalysis, particularly for strong LLJs, leading to an underestimate of the moisture transport associated with LLJs. When the 10-yr period is considered, the NARR and CFSR overestimate and MERRA underestimates the total moisture transport, but all three underestimate the transport associated with strong LLJs by factors of 1.4, 2.0, and 2.7 for CFSR, NARR, and MERRA, respectively. During MC3E there were differences in the patterns of moisture convergence and divergence, but the patterns are more consistent during the 10-yr period.
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Kim, Chongyoup, and Hyun-Ku Rhee. "Analysis of a CFSTR with two consecutive reactions in transient states." Korean Journal of Chemical Engineering 5, no. 1 (March 1988): 53–59. http://dx.doi.org/10.1007/bf02697477.
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Yu, Jinna, Yiming Wei, Wei Fang, Zhen Liu, Yujie Zhang, and Jing Lan. "New Round of Collective Forest Rights Reform, Forestland Transfer and Household Production Efficiency." Land 10, no. 9 (September 18, 2021): 988. http://dx.doi.org/10.3390/land10090988.
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The purpose of this paper was to analyze the influence mechanism of the new round of Collective Forest Rights Reform (CFRR) on farmers’ production efficiency from the perspective of forestland transfer. Based on the panel data of field investigation in Jiangxi Province, a panel logit model was used to verify whether the new round of CFRR has affected farmers’ forestland circulation behavior. The results showed that the new round of CFRR has played a significant role in promoting forestland circulation. Secondly, the non-parametric DEA method was used to estimate the technical, scale, and comprehensive efficiency of households. DID and panel quantile models were constructed to analyze the impact of forestland inflow policy and forestland outflow policy effects on rural household productivity. The regression results showed that the effect of forestland inflow has had a significantly positive impact on scale and comprehensive efficiency, but it only had a significant effect on technical efficiency in the 0.1 quartile. The effect of forestland outflow was not found to be significant for technical, scale, and comprehensive efficiency, but it was found to be negative for technical efficiency in the 0.75 quartile and negative for scale efficiency in the 0.5 and 0.75 quantiles.
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Dhanesh, Yeganantham, V. M. Bindhu, Javier Senent-Aparicio, Tássia Mattos Brighenti, Essayas Ayana, P. S. Smitha, Chengcheng Fei, and Raghavan Srinivasan. "A Comparative Evaluation of the Performance of CHIRPS and CFSR Data for Different Climate Zones Using the SWAT Model." Remote Sensing 12, no. 18 (September 21, 2020): 3088. http://dx.doi.org/10.3390/rs12183088.
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The spatial and temporal scale of rainfall datasets is crucial in modeling hydrological processes. Recently, open-access satellite precipitation products with improved resolution have evolved as a potential alternative to sparsely distributed ground-based observations, which sometimes fail to capture the spatial variability of rainfall. However, the reliability and accuracy of the satellite precipitation products in simulating streamflow need to be verified. In this context, the objective of the current study is to assess the performance of three rainfall datasets in the prediction of daily and monthly streamflow using Soil and Water Assessment Tool (SWAT). We used rainfall data from three different sources: Climate Hazards Group InfraRed Rainfall with Station data (CHIRPS), Climate Forecast System Reanalysis (CFSR) and observed rain gauge data. Daily and monthly rainfall measurements from CHIRPS and CFSR were validated using widely accepted statistical measures, namely, correlation coefficient (CC), root mean squared error (RMSE), probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). The results showed that CHIRPS was in better agreement with ground-based rainfall at daily and monthly scale, with high rainfall detection ability, in comparison with the CFSR product. Streamflow prediction across multiple watersheds was also evaluated using Kling-Gupta Efficiency (KGE), Nash-Sutcliffe Efficiency (NSE) and Percent BIAS (PBIAS). Irrespective of the climatic characteristics, the hydrologic simulations of CHIRPS showed better agreement with the observed at the monthly scale with the majority of the NSE values ranging between 0.40 and 0.78, and KGE values ranging between 0.62 and 0.82. Overall, CHIRPS outperformed the CFSR rainfall product in driving SWAT for streamflow simulations across the multiple watersheds selected for the study. The results from the current study demonstrate the potential of CHIRPS as an alternate open access rainfall input to the hydrologic model.
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Bracegirdle, Thomas J., and Gareth J. Marshall. "The Reliability of Antarctic Tropospheric Pressure and Temperature in the Latest Global Reanalyses." Journal of Climate 25, no. 20 (May 1, 2012): 7138–46. http://dx.doi.org/10.1175/jcli-d-11-00685.1.
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Abstract In this study, surface and radiosonde data from staffed Antarctic observation stations are compared to output from five reanalyses [Climate Forecast System Reanalysis (CFSR), 40-yr ECMWF Re-Analysis (ERA-40), ECMWF Interim Re-Analysis (ERA-Interim), Japanese 25-year Reanalysis (JRA-25), and Modern Era Retrospective-Analysis for Research and Applications (MERRA)] over three decades spanning 1979–2008. Bias and year-to-year correlation between the reanalyses and observations are assessed for four variables: mean sea level pressure (MSLP), near-surface air temperature (Ts), 500-hPa geopotential height (H500), and 500-hPa temperature (T500). It was found that CFSR and MERRA are of a sufficiently high resolution for the height of the orography to be accurately reproduced at coastal observation stations. Progressively larger negative Ts biases at these coastal stations are apparent for reanalyses in order of decreasing resolution. However, orography height bias cannot explain large winter warm biases in CFSR, JRA-25, and MERRA (11.1°, 10.2°, and 7.9°C, respectively) at Amundsen–Scott and Vostok, which have been linked to problems with representing the surface energy balance. Linear trends in the annual-mean T500 and H500 averaged over Antarctica as a whole were found to be most reliable in CFSR, ERA-Interim, and MERRA, none of which show significant trends over the period 1979–2008. In contrast JRA-25 shows significant negative trends over 1979–2008 and ERA-40 gives significant positive trends during the 1980s (evident in both T500 and H500). Comparison to observations indicates that the positive trend in ERA-40 is spurious. At the smaller spatial scale of individual stations all five reanalyses have some spurious trends. However, ERA-Interim was found to be the most reliable for MSLP and H500 trends at station locations.
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Liu, Junli, Yun Zhang, Lei Yang, and Yuying Li. "Hydrological Modeling in the Chaohu Lake Basin of China—Driven by Open-Access Gridded Meteorological and Remote Sensing Precipitation Products." Water 14, no. 9 (April 28, 2022): 1406. http://dx.doi.org/10.3390/w14091406.
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This study assessed the performance of two well-known gridded meteorological datasets, CFSR (Climate Forecast System Reanalysis) and CMADS (China Meteorological Assimilation Driving Datasets), and three satellite-based precipitation datasets, TRMM (Tropical Rainfall Measuring Mission), CMORPH (Climate Prediction Center morphing technique), and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), in driving the SWAT (Soil and Water Assessment Tool) model for streamflow simulation in the Fengle watershed in the middle–lower Yangtze Plain, China. Eighteen model scenarios were generated by forcing the SWAT model with different combinations of three meteorological datasets and six precipitation datasets. Our results showed that (1) the three satellite-based precipitation datasets (i.e., TRMM, CMORPH, and CHIRPS) generally provided more accurate precipitation estimates than CFSR and CMADS. CFSR and CMADS agreed fairly well with the gauged measurements in maximum temperature, minimum temperature, and relative humidity, but large discrepancies existed for the solar radiation and wind speed. (2) The impact of precipitation data on simulated streamflow was much larger than that of other meteorological variables. Satisfactory simulations were achieved using the CMORPH precipitation data for daily streamflow simulation and the TRMM and CHIRPS precipitation data for monthly streamflow simulation. This suggests that different precipitation datasets can be used for optimal simulations at different temporal scales.
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Nakkazi, Maria Theresa, Jotham Ivan Sempewo, Martin Dahlin Tumutungire, and Jimmy Byakatonda. "Performance evaluation of CFSR, MERRA-2 and TRMM3B42 data sets in simulating river discharge of data-scarce tropical catchments: a case study of Manafwa, Uganda." Journal of Water and Climate Change 13, no. 2 (November 23, 2021): 522–41. http://dx.doi.org/10.2166/wcc.2021.174.
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Abstract Data scarcity has been a huge problem in modelling catchments especially in the tropical region. Satellite data and different statistical methods are being used to improve the quality of conventional meteorological data. However, their potential needs to be further investigated. This paper evaluates the performance of three datasets in simulating discharge of River Manafwa, Uganda. Two reanalysis datasets were selected for studying both rainfall and temperature, whereas a satellite algorithm was selected for studying rainfall alone. MERRA-2 data and CFSR were chosen as the reanalysis datasets whereas TRMM3B42 data were used as the satellite product in this study. The SWAT model was used to evaluate the performance of these datasets. The model performance indicators indicated that, at daily time steps, all the three datasets produced values of Nash -Sutcliffe Efficiency (NSE<0.4), coefficient of determination (R2<0.4) and Percent Bias +25%. Despite a general underperformance compared to MERRA-2, CFSR performed better than TRMM. On applying generated bias corrections for precipitation and temperature climate data, overall results showed that the bias-corrected data outperformed the original data. We conclude that, in the absence of gauged hydro-meteorological data, bias-corrected MERRA-2, CFSR and TRMM data could be used for simulating river discharge in data-scarce areas.