scholarly journals EFECTO DE LA CORRIENTE EN CHORRO DE BAJOS NIVELES EN LA OCURRENCIA DE PRECIPITACIÓN EN LA SELVA DEL PERÚ

2021 ◽  
Vol 20 (2) ◽  
pp. 147-159
Author(s):  
Jose Carlos Coello Fababa ◽  
Victoria Calle Montes
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Global Forecast System ◽  
Forecast System ◽  
La Selva ◽  
Tropical Rainfall ◽  
América Del Sur

Se analizó la corriente en chorro de América del Sur (SALLJ, siglas en inglés) y la ocurrencia de precipitación sobre la selva del Perú, tomando en cuenta los datos del modelo atmosférico Global Forecast System (GFS) y datos de precipitación acumulada estimado por el satélite Tropical Rainfall Measuring Mission (TRMM) en los veranos australes comprendidos entre los años 2005 y 2014. Se utilizó la distribución de Weibull para el análisis estadístico del viento meridional del norte y el test estadístico no paramétrico de correlación de Kendall para asociar los eventos SALLJ definidos por los criterios de Whiteman et al. (1997) y Bonner (1968). Los resultados revelan que el comportamiento promedio de la componente meridional del viento fluctúa entre 1.2 y 11.7 m/s con variaciones de +/- 3.2 m/s, registrando un viento máximo de 21.4 m/s. De un total de 39 casos, el 53.8% se identificó con las condiciones propuestas por Whiteman y un 46.2% con las condiciones de Bonner. Se registró una precipitación máxima de 64.00 mm/día y mayor número de días con precipitaciones asociadas a eventos SALLJ para las 00 UTC.

scholarly journals PERBANDINGAN PREDIKSI CURAH HUJAN GFS METEOROGRAM DENGAN CURAH HUJAN TRMM DI DAS RIAM KANAN KALIMANTAN SELATAN

2015 ◽  
Vol 16 (2) ◽  
pp. 73 ◽  
Author(s):  
Samba Wirahma ◽  
Ibnu Athoillah ◽  
Sutrisno .
Keyword(s):  
Correlation Coefficient ◽  
Catchment Area ◽  
Water Discharge ◽  
Tropical Rainfall Measuring Mission ◽  
Precipitation Forecast ◽  
Global Forecast System ◽  
Weather Modification ◽  
Forecast System ◽  
Tropical Rainfall ◽  
Rainfall Prediction

Teknologi Modifikasi Cuaca (TMC) yang diterapkan oleh BPPT di Kalimantan Selatan dilakukan guna mengatasi kekurangan debit air yang terjadi pada DAS Riam Kanan. Untuk melaksanakan TMC yang efektif dan efisien dibutuhkan prediksi cuaca harian yang akurat dan mendetail pada catchment area (daerah tangkapan hujan) tersebut, khususnya prediksi curah hujan harian. TMC yang diterapkan oleh BPPT menggunakan prediksi yang salah satunya diambil dari Global Forecast System (GFS) Meteorogram. Prediksi tersebut bisa menjadi referensi untuk mengolah dan menganalisis parameter cuaca dengan baik, serta merencanakan dan memutuskan pelaksanaan penerbangan eksekusi selama kegiatan TMC. Untuk menguji ketepatan suatu prediksi, maka diperlukan validasi/perbandingan hasil prediksi dengan data real, yaitu data curah hujan yang dapat diambil dari data Tropical Rainfall Measuring Mission (TRMM).Prediksi curah hujan menggunakan GFS Meteorogram dibandingkan dengan data curah hujan dari TRMM di daerah DAS Riam Kanan menggunakan korelasi Pearson, pengambilan data prediksi GFS dilakukan mulai dari 16 Mei 2014 s/d 31 Mei 2014. Koefisien korelasi yang diambil hanya yang memiliki pola/bentuk hubungan korelasi linear positif (+1). Dari hasil analisis korelasi didapatkan bahwa dari 16 hari pengambilan data di semua lokasi, rata-rata terdapat 8 - 11 hari yang memiliki nilai koefisien korelasi (KK) positif untuk prediksi di hari yang sama dan 6 - 11 hari untuk prediksi Lag_1, dengan nilai KK yang paling banyak muncul yaitu : range 0.4 - 0.7 untuk prediksi 7 hari ke depan, range 0.7 - 0.9 untuk prediksi 5 hari ke depan, dan range 0.9 - 1 untuk prediksi 3 hari ke depan. Dari keenam lokasi titik prediksi dengan nilai koefisien korelasi linear positif yang paling banyak muncul dan memiliki hubungan yang paling kuat adalah di titik Banjarmasin dan DAS bagian Utara.Kata Kunci : prediksi curah hujan GFS, curah hujan TRMM DAS Riam Kanan, koefisien korelasiWeather Modification Technology applied by BPPT in South Kalimantan in order to overcome the shortage of water discharge that occurs in the Riam Kanan Watershed. To implement the weather modification technology an effective and efficient required daily weather predictions are accurate and detail in the catchment area, especially dailiy rainfall prediction. In this Technology, BPPT using prediction from the Global Forecast System (GFS) Meteorogram. This prediction could be a reference to analyze weather parameter, planning, and deciding to do flight execution for weather modification. To verifying accuracy of this prediction, it is necessary validation/ comparison with real data that can be retrieved from the data Tropical Rainfall Measuring Mission (TRMM).Rainfall prediction of GFS Meteorogram compared with data from TRMM rainfall on the Riam Kanan Watershed using Pearson Correlation, GFS forecast data collected from May 16 - May 3,1 2014. The correlation coefficient is taken only has a pattern a positive linear correlation. The result from correlation analysis showed that 16 days of data collection in all locations, on average there are 8 – 11 days have a correlation coefficient is positive for prediction in the same day, and 6 – 11 days for prediction in lag_1 with most value arise of correlation coefficient is 0.4 – 0.7 for prediction of next 7 days, range 0.7 – 0.9 for prediction of next 5 days, and range 0.9 – 1 for prediction of next 3 days. From the six location of prediction points with most value arise of correlation coefficient positive linier and have the strongest relation are in Banjarmasin and northern watershed.Keywords : GFS precipitation forecast, Riam Kanan TRMM rainfall, correlation coefficient

Evaluation of Precipitation Forecast from Global Forecast System Over Transboundary Rivers in Africa

2021 ◽  
Author(s):  
Haowen Yue ◽  
Mekonnen Gebremichael
Keyword(s):  
Correlation Coefficients ◽  
Precipitation Forecast ◽  
Nile River ◽  
Lead Times ◽  
General Tendency ◽  
Global Forecast System ◽  
Forecast System ◽  
Transboundary River Basins ◽  
Unbiased Estimates ◽  
Good Agreement

<p>This study evaluates the short-to-medium range precipitation forecasts from Global Forecast System for 14 major transboundary river basins in Africa against GPM IMERG “Early”, IMERG “Final”, and CHIRPSv2 products. Daily precipitation forecasts with lead times of 1-day, 5-day, 10-day, and 15-day and accumulated precipitation forecasts with periods of 1-day, 5-day, 10-day, and 15-day are investigated. The 14 selected basins are (1) Senegal; (2) Volta; (3) Niger; (4) Chad; (5) Nile; (6) Awash; (7) Congo; (8) Omo Gibe; (9) Tana; (10) Pangani; (11) Zambezi; (12) Okavango; (13) Limpopo and (14) Orange. For each basin, several sub-basins are defined by the major dams in the basin. Our preliminary results in the Nile river basin show that in terms of temporal variability, there was a good agreement between the forecasted and observed accumulated precipitation on a 15-day basis. When compared to IMERG “Final”, the correlation coefficients of accumulated GFS forecasts scored as high as 0.75. Thus, GFS products provide relatively reliable accumulated precipitation forecasts. However, the precipitation forecasts were mostly biased: they tend to overpredict rainfall for the eastern part of the Nile river, underestimate rainfall for the northern part of the Nile river and produce almost unbiased estimates for the southern part of the river. Additionally, GFS forecasts have a general tendency to underpredict the area of precipitation across the Nile basin. Although the performance of GFS varies at different locations, the GFS precipitation forecasts can be a good reference to dam operators in Africa. </p>

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.

Comparison Between Estimated Rainfall Estimated by the Tropical Rainfall Measuring Mission (TRMM) Satellite and Data Observed in the Lagoa Mirim/RS Basin, Brazil

INCREaSE 2019 ◽  
2019 ◽  
pp. 97-110
Author(s):  
Géri Eduardo Meneghello ◽  
Letícia Burkert Méllo ◽  
Ritâ De Cassia Fraga Damé ◽  
Francisco Amaral Villela ◽  
Maria Clotilde Carré Chagas Neta ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Tropical Rainfall
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