Medium Range Atmospheric Forecast System: Evaluation Plan.

1985 ◽  
Author(s):  
P. A. Petit ◽  
H. D. Hamilton ◽  
R. L. Elsberry
Keyword(s):  
System Evaluation ◽  
Forecast System ◽  
Evaluation Plan ◽  
Medium Range

Medium Range Atmospheric Forecast System: Evaluation Report.

1985 ◽  
Author(s):  
P. A. Petit ◽  
H. D. Hamilton ◽  
R. L. Elsberry
Keyword(s):  
System Evaluation ◽  
Forecast System ◽  
Evaluation Report ◽  
Medium Range

Evaluation of Global Forecast System (GFS) Medium-Range Precipitation Forecasts in the Nile River Basin

2021 ◽  
Author(s):  
Haowen Yue ◽  
Mekonnen Gebremichael ◽  
Vahid Nourani
Keyword(s):  
Temporal Dynamics ◽  
Disease Outbreaks ◽  
Rain Gauge ◽  
Global Forecast System ◽  
Forecast System ◽  
Forecast Performance ◽  
Weather Forecasts ◽  
Rain Gauges ◽  
Basin Scale ◽  
Medium Range

Abstract Reliable weather forecasts are valuable in a number of applications, such as, agriculture, hydropower, and weather-related disease outbreaks. Global weather forecasts are widely used, but detailed evaluation over specific regions is paramount for users and operational centers to enhance the usability of forecasts and improve their accuracy. This study presents evaluation of the Global Forecast System (GFS) medium-range (1 day – 15 day) precipitation forecasts in the nine sub-basins of the Nile basin using NASA’s Integrated Multi-satellitE Retrievals (IMERG) “Final Run” satellite-gauge merged rainfall observations. The GFS products are available at a temporal resolution of 3-6 hours, spatial resolution of 0.25°, and its version-15 products are available since 12 June 2019. GFS forecasts are evaluated at a temporal scale of 1-15 days, spatial scale of 0.25° to all the way to the sub-basin scale, and for a period of one year (15 June 2019 – 15 June 2020). The results show that performance of the 1-day lead daily basin-averaged GFS forecast performance, as measured through the modified Kling-Gupta Efficiency (KGE), is poor (0 < KGE < 0.5) for most of the sub-basins. The factors contributing to the low performance are: (1) large overestimation bias in watersheds located in wet climate regimes in the northern hemispheres (Millennium watershed, Upper Atbara & Setit watershed, and Khashm El Gibra watershed), and (2) lower ability in capturing the temporal dynamics of watershed-averaged rainfall that have smaller watershed areas (Roseires at 14,110 sq. km and Sennar at 13,895 sq. km). GFS has better bias for watersheds located in the dry parts of the northern hemisphere or wet parts of the southern hemisphere, and better ability in capturing the temporal dynamics of watershed-average rainfall for large watershed areas. IMERG Early has better bias than GFS forecast for the Millennium watershed but still comparable and worse bias for the Upper Atbara & Setit, and Khashm El Gibra watersheds. The variation in the performance of the IMERG Early could be partly explained by the number of rain gauges used in the reference IMERG Final product, as 16 rain gauges were used for the Millennium watershed but only one rain gauge over each Upper Atbara & Setit, and Khashm El Gibra watershed. A simple climatological bias-correction of IMERG Early reduces in the bias in IMERG Early over most watersheds, but not all watersheds. We recommend exploring methods to increase the performance of GFS forecasts, including post-processing techniques through the use of both near-real-time and research-version satellite rainfall products.

scholarly journals Medium-Range Convection-Allowing Ensemble Forecasts with a Variable-Resolution Global Model

2019 ◽  
Vol 147 (8) ◽  
pp. 2997-3023 ◽  
Author(s):  
Craig S. Schwartz
Keyword(s):  
High Resolution ◽  
Ensemble Forecast ◽  
The Other ◽  
Forecast System ◽  
Ensemble Forecasts ◽  
Variable Resolution ◽  
Cell Spacing ◽  
Medium Range ◽  
Potential Benefits ◽  
Convective Mode

Abstract Two sets of global, 132-h (5.5-day), 10-member ensemble forecasts were produced with the Model for Prediction Across Scales (MPAS) for 35 cases in April and May 2017. One MPAS ensemble had a quasi-uniform 15-km mesh while the other employed a variable-resolution mesh with 3-km cell spacing over the conterminous United States (CONUS) that smoothly relaxed to 15 km over the rest of the globe. Precipitation forecasts from both MPAS ensembles were objectively verified over the central and eastern CONUS to assess the potential benefits of configuring MPAS with a 3-km mesh refinement region for medium-range forecasts. In addition, forecasts from NCEP’s operational Global Ensemble Forecast System were evaluated and served as a baseline against which to compare the experimental MPAS ensembles. The 3-km MPAS ensemble most faithfully reproduced the observed diurnal cycle of precipitation throughout the 132-h forecasts and had superior precipitation skill and reliability over the first 48 h. However, after 48 h, the three ensembles had more similar spread, reliability, and skill, and differences between probabilistic precipitation forecasts derived from the 3- and 15-km MPAS ensembles were typically statistically insignificant. Nonetheless, despite fewer benefits of increased resolution for spatial placement after 48 h, 3-km ensemble members explicitly provided potentially valuable guidance regarding convective mode throughout the 132-h forecasts while the other ensembles did not. Collectively, these results suggest both strengths and limitations of medium-range high-resolution ensemble forecasts and reveal pathways for future investigations to improve understanding of high-resolution global ensembles with variable-resolution meshes.

scholarly journals Utility of Global Ensemble Forecast System (GEFS) Reforecast for Medium-Range Drought Prediction in India

2016 ◽  
Vol 17 (6) ◽  
pp. 1781-1800 ◽  
Author(s):  
Reepal D. Shah ◽  
Vimal Mishra
Keyword(s):  
Soil Moisture ◽  
Root Zone ◽  
Monsoon Season ◽  
Ensemble Forecast ◽  
Extreme Weather Events ◽  
Forecast System ◽  
Drought Prediction ◽  
Air Temperatures ◽  
Medium Range ◽  
Precipitation And Temperature

Abstract Medium-range (~7 days) forecasts of agricultural and hydrologic droughts can help in decision-making in agriculture and water resources management. India has witnessed severe losses due to extreme weather events during recent years and medium-range forecasts of precipitation, air temperatures (maximum and minimum), and hydrologic variables (root-zone soil moisture and runoff) can be valuable. Here, the skill of the Global Ensemble Forecast System (GEFS) reforecast of precipitation and air temperatures is evaluated using retrospective data for the period of 1985–2010. It is found that the GEFS forecast shows better skill in the nonmonsoon season than in the monsoon season in India. Moreover, skill in temperature forecast is higher than that of precipitation in both the monsoon and nonmonsoon seasons. The lower skill in forecasting precipitation during the monsoon season can be attributed to representation of intraseasonal variability in precipitation from the GEFS. Among the selected regions, the northern, northeastern, and core monsoon region showed relatively lower skill in the GEFS forecast. Temperature and precipitation forecasts were corrected from the GEFS using quantile–quantile (Q–Q) mapping and linear scaling, respectively. Bias-corrected forecasts for precipitation and air temperatures were improved over the raw forecasts. The influence of corrected and raw forcings on medium-range soil moisture, drought, and runoff forecasts was evaluated. The results showed that because of high persistence, medium-range soil moisture forecasts are largely determined by the initial hydrologic conditions. Bias correction of precipitation and temperature forecasts does not lead to significant improvement in the medium-range hydrologic forecasting of soil moisture and drought. However, bias correcting raw GEFS forecasts can provide better predictions of the forecasts of precipitation and temperature anomalies over India.

scholarly journals Evaluating Medium-Range Tropical Cyclone Forecasts in Uniform- and Variable-Resolution Global Models

2016 ◽  
Vol 144 (11) ◽  
pp. 4141-4160 ◽  
Author(s):  
Christopher A. Davis ◽  
David A. Ahijevych ◽  
Wei Wang ◽  
William C. Skamarock
Keyword(s):  
North Pacific ◽  
Forecast Skill ◽  
False Alarms ◽  
Shallow Convection ◽  
Forecast System ◽  
Variable Resolution ◽  
Verification Method ◽  
Operational Forecasts ◽  
Medium Range ◽  
Environmental Prediction

Abstract An evaluation of medium-range forecasts of tropical cyclones (TCs) is performed, covering the eastern North Pacific basin during the period 1 August–3 November 2014. Real-time forecasts from the Model for Prediction Across Scales (MPAS) and operational forecasts from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) are evaluated. A new TC-verification method is introduced that treats TC tracks as objects. The method identifies matching pairs of forecast and observed tracks, missed and false alarm tracks, and derives statistics using a multicategory contingency table methodology. The formalism includes track, intensity, and genesis. Two configurations of MPAS, a uniform 15-km mesh and a variable-resolution mesh transitioning from 60 km globally to 15 km over the eastern Pacific, are compared with each other and with the operational GFS. The two configurations of MPAS reveal highly similar forecast skill and biases through at least day 7. This result supports the effectiveness of TC prediction using variable resolution. Both MPAS and the GFS suffer from biases in predictions of genesis at longer time ranges; MPAS produces too many storms whereas the GFS produces too few. MPAS better discriminates hurricanes than does the GFS, but the false alarms in MPAS lower overall forecast skill in the medium range relative to GFS. The biases in MPAS forecasts are traced to errors in the parameterization of shallow convection south of the equator and the resulting erroneous invigoration of the ITCZ over the eastern North Pacific.

Impact of the Different Components of 4DVAR on the Global Forecast System of the Meteorological Service of Canada

2007 ◽  
Vol 135 (6) ◽  
pp. 2355-2364 ◽  
Author(s):  
Stéphane Laroche ◽  
Pierre Gauthier ◽  
Monique Tanguay ◽  
Simon Pellerin ◽  
Josée Morneau
Keyword(s):  
Data Assimilation ◽  
Positive Impact ◽  
Weather Forecast ◽  
Forecast Model ◽  
Variational Data Assimilation ◽  
Global Forecast System ◽  
Forecast System ◽  
Medium Range Weather Forecast ◽  
Medium Range ◽  
The Impact

Abstract A four-dimensional variational data assimilation (4DVAR) scheme has recently been implemented in the medium-range weather forecast system of the Meteorological Service of Canada (MSC). The new scheme is now composed of several additional and improved features as compared with the three-dimensional variational data assimilation (3DVAR): the first guess at the appropriate time from the full-resolution model trajectory is used to calculate the misfit to the observations; the tangent linear of the forecast model and its adjoint are employed to propagate the analysis increment and the gradient of the cost function over the 6-h assimilation window; a comprehensive set of simplified physical parameterizations is used during the final minimization process; and the number of frequently reported data, in particular satellite data, has substantially increased. The impact of these 4DVAR components on the forecast skill is reported in this article. This is achieved by comparing data assimilation configurations that range in complexity from the former 3DVAR with the implemented 4DVAR over a 1-month period. It is shown that the implementation of the tangent-linear model and its adjoint as well as the increased number of observations are the two features of the new 4DVAR that contribute the most to the forecast improvement. All the other components provide marginal though positive impact. 4DVAR does not improve the medium-range forecast of tropical storms in general and tends to amplify the existing, too early extratropical transition often observed in the MSC global forecast system with 3DVAR. It is shown that this recurrent problem is, however, more sensitive to the forecast model than the data assimilation scheme employed in this system. Finally, the impact of using a shorter cutoff time for the reception of observations, as the one used in the operational context for the 0000 and 1200 UTC forecasts, is more detrimental with 4DVAR. This result indicates that 4DVAR is more sensitive to observations at the end of the assimilation window than 3DVAR.

scholarly journals Estudo do ciclo de vida do ciclone subtropical Arani ocorrido no Atlântico Sul em março de 2011 através das reanálises ERA-Interim e CFSR

2020 ◽  
Vol 15 (3) ◽  
pp. 235-249
Author(s):  
Ana Cristina Pinto de Almeida Palmeira ◽  
Rodrigo De Souza Barreto Mathias
Keyword(s):  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range

O ciclone Arani ocorreu em março de 2011 no oceano Atlântico Sul e foi classificado inicialmente como depressão subtropical. Ao atingir ventos superiores a 34 nós, passou à categoria de tempestade subtropical, sendo nomeado pela Marinha do Brasil como Arani, que significa tempo furioso em Tupi Guarani. O objetivo deste trabalho foi analisar o ciclone Arani através do Espaço de Fase de Ciclones, construído com dados da reanálise ERA-Interim do European Centre for Medium-Range Weather Forecasts (ECMWF), com 0,7º de resolução espacial, e, também, utilizando campos sinóticos e cortes verticais com os dados da reanálise do Climate Forecast System Reanalisys (CFSR), com 0,5º de resolução. Através dos diagramas de fase foi possível identificar a estrutura subtropical do ciclone Arani e o indício de uma transição de fase extratropical no final de seu ciclo de vida. Os resultados indicaram, também, que a qualidade dos diagramas de fase para ciclones com fraco núcleo quente e pequenas dimensões depende de modelos atmosféricos adequados e, por isso, os valores obtidos devem ser analisados com cautela quando se trata do uso de modelos globais. Neste caso, o estudo qualitativo dos diagramas se mostrou mais útil do que a análise puramente quantitativa. Apesar de discordar da informação de uma transição de fase extratropical no final do ciclo de vida do ciclone Arani, contida nos diagramas de fase empregados no estudo, a análise dos campos e dos perfis sinóticos contribuiu para o entendimento do desenvolvimento do ciclone e para a interpretação dos próprios diagramas de fase.

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