scholarly journals Evaluation of Gridded Multi-Satellite Precipitation Estimation (TRMM-3B42-V7) Performance in the Upper Indus Basin (UIB)

Climate ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 76 ◽  
Author(s):  
Asim Khan ◽  
Manfred Koch ◽  
Karen Chinchilla
Keyword(s):  
Time Scale ◽  
Winter Season ◽  
Indus Basin ◽  
Tropical Rainfall Measurement Mission ◽  
Satellite Precipitation ◽  
Tropical Rainfall ◽  
Upper Indus Basin ◽  
Gauge Data ◽  
Precipitation Analysis ◽  
Trmm 3B42

The present study aims to evaluate the capability of the Tropical Rainfall Measurement Mission (TRMM), Multi-satellite Precipitation Analysis (TMPA), version 7 (TRMM-3B42-V7) precipitation product to estimate appropriate precipitation rates in the Upper Indus Basin (UIB) by analyzing the dependency of the estimates’ accuracies on the time scale. To that avail, various statistical analyses and comparison of Multisatellite Precipitation Analysis (TMPA) products with gauge measurements in the UIB are carried out. The dependency of the TMPA estimates’ quality on the aggregation time scale is analyzed by comparisons of daily, monthly, seasonal and annual sums for the UIB. The results show considerable biases in the TMPA Tropical Rainfall Measurement Mission (TRMM) precipitation estimates for the UIB, as well as high numbers of false alarms and miss ratios. The correlation of the TMPA estimates with ground-based gauge data increases considerably and almost in a linear fashion with increasing temporal aggregation, i.e., time scale. There is a predominant trend of underestimation of the TRMM product across the UIB at most of the gauge stations, i.e., TRMM-estimated rainfall is generally lower than the gauge-measured rainfall. For the seasonal aggregates, the bias is mostly positive for the summer but predominantly negative for the winter season, thereby showing a slight overestimation of the precipitation in summer and underestimation in winter. The results of the study suggest that, in spite of these discrepancies between TMPA estimates and gauge data, the use of the former in hydrological watershed modeling undertaken by the authors may be a valuable alternative in data-scarce regions like the UIB, but still must be taken with a grain of salt.

scholarly journals Evaluation of Gridded Multi-Satellite Precipitation (TRMM-3B42-V7) Estimation Performance in the Upper Indus Basin (UIB)

2018 ◽  
Author(s):  
Asim Jahangir Khan ◽  
Manfred Koch ◽  
Karen Milena Chinchilla
Keyword(s):  
Time Scale ◽  
Winter Season ◽  
Indus Basin ◽  
False Alarms ◽  
Temporal Aggregation ◽  
Upper Indus Basin ◽  
Gauge Data ◽  
Precipitation Estimates ◽  
Trmm Precipitation ◽  
Trmm 3B42

The present study aims to evaluate the capability of the TRMM-3B42-(V7) precipitation product to estimate appropriate precipitation rates in the Upper Indus basin (UIB) and the analysis of the dependency of the estimates’ accuracies on the time scale. To that avail statistical analyses and comparison of the TMPA- products with gauge measurements in the UIB are carried out. The dependency of the TMPA estimates’ quality on the time scale is analysed by comparisons of daily, monthly, seasonal and annual sums for the UIB. The results show considerable biases in the TMPA- (TRMM) precipitation estimates for the UIB, as well as high false alarms and miss ratios. The correlation of the TMPA- estimates with ground-based gauge data increases considerably and almost in a linear fashion with increasing temporal aggregation, i.e. time scale. The BIAS is mostly positive for the summer season, while for the winter season it is predominantly negative, thereby showing a slight over-estimation of the precipitation in summer and under-estimation in winter. The results of the study suggest that, in spite of these discrepancies between TMPA- estimates and gauge data, the use of the former in hydrological watershed modelling, endeavoured presently by the authors, may be a valuable alternative in data- scarce regions, like the UIB, but still must be taken with a grain of salt.

Exploring Temporal Rainfall Variability and Trends Over a Tropical Region Using Tropical Rainfall Measurement Mission (TRMM) and Observatory Data

2021 ◽  
Vol 5 (2) ◽  
pp. 56-71
Author(s):  
Anu David Raj ◽  
K. R. Sooryamol ◽  
Aju David Raj
Keyword(s):  
Time Scales ◽  
Water Resource Management ◽  
Rainfall Variability ◽  
Winter Season ◽  
India Meteorological Department ◽  
Southwest Monsoon ◽  
Rainfall Data ◽  
Tropical Rainfall Measurement Mission ◽  
Tropical Rainfall ◽  
Observatory Data

Kerala is the gateway of the Indian southwest monsoon. The Tropical Rainfall Measurement Mission (TRMM) rainfall data is an efficient approach to rainfall measurement. This study explores the temporal variability in rainfall and trends over Kerala from 1998-2019 using TRMM data and observatory data procured from India Meteorological Department (IMD). Direct comparison with observatory data at various time scales proved the reliability of the TRMM data (monthly, seasonal and annual). The temporal rainfall converted by averaging the data on an annual, monthly and seasonal time scale, and the results have confirmed that the rainfall estimated based on satellite data is dependable. The station wise comparison of rainfall in monsoon season provides satisfactory results. However, estimation of rainfall in mountainous areas is challenging task using the TRMM. In the basins of humid tropical regions, TRMM data can be a valuable source of rainfall data for water resource management and monitoring with some vigilance. In Kerala, the study found an insignificant increase in the southwest monsoon and winter season rainfall during last two decades. The rainfall over Kerala showed uncertainty in the distribution of monthly, seasonal and yearly time scales. This study provides a preview of recent weather patterns that would enable us to make better decisions and improve public policy against climate change.

scholarly journals Prevailing climatic trends and runoff response from Hindukush–Karakoram–Himalaya, upper Indus basin

2015 ◽  
Vol 6 (1) ◽  
pp. 579-653 ◽  
Author(s):  
S. Hasson ◽  
J. Böhner ◽  
V. Lucarini
Keyword(s):  
High Altitude ◽  
Water Availability ◽  
Winter Season ◽  
Indus Basin ◽  
Climatic Trend ◽  
Upper Indus Basin ◽  
Climatic Trends ◽  
Mixed Response ◽  
Long Term Trends

Abstract. Largely depending on meltwater from the Hindukush–Karakoram–Himalaya, withdrawals from the upper Indus basin (UIB) contribute to half of the surface water availability in Pakistan, indispensable for agricultural production systems, industrial and domestic use and hydropower generation. Despite such importance, a comprehensive assessment of prevailing state of relevant climatic variables determining the water availability is largely missing. Against this background, we present a comprehensive hydro-climatic trend analysis over the UIB, including for the first time observations from high-altitude automated weather stations. We analyze trends in maximum, minimum and mean temperatures (Tx, Tn, and Tavg, respectively), diurnal temperature range (DTR) and precipitation from 18 stations (1250–4500 m a.s.l.) for their overlapping period of record (1995–2012), and separately, from six stations of their long term record (1961–2012). We apply Mann–Kendall test on serially independent time series to assess existence of a trend while true slope is estimated using Sen's slope method. Further, we statistically assess the spatial scale (field) significance of local climatic trends within ten identified sub-regions of UIB and analyze whether the spatially significant (field significant) climatic trends qualitatively agree with a trend in discharge out of corresponding sub-region. Over the recent period (1995–2012), we find a well agreed and mostly field significant cooling (warming) during monsoon season i.e. July–October (March–May and November), which is higher in magnitude relative to long term trends (1961–2012). We also find general cooling in Tx and a mixed response in Tavg during the winter season and a year round decrease in DTR, which are in direct contrast to their long term trends. The observed decrease in DTR is stronger and more significant at high altitude stations (above 2200 m a.s.l.), and mostly due to higher cooling in Tx than in Tn. Moreover, we find a field significant decrease (increase) in late-monsoonal precipitation for lower (higher) latitudinal regions of Himalayas (Karakoram and Hindukush), whereas an increase in winter precipitation for Hindukush, western- and whole Karakoram, UIB-Central, UIB-West, UIB-West-upper and whole UIB regions. We find a spring warming (field significant in March) and drying (except for Karakoram and its sub-regions), and subsequent rise in early-melt season flows. Such early melt response together with effective cooling during monsoon period subsequently resulted in a substantial drop (weaker increase) in discharge out of higher (lower) latitudinal regions (Himalaya and UIB-West-lower) during late-melt season, particularly during July. These discharge tendencies qualitatively differ to their long term trends for all regions, except for UIB-West-upper, western-Karakorum and Astore. The observed hydroclimatic trends, being driven by certain changes in the monsoonal system and westerly disturbances, indicate dominance (suppression) of nival (glacial) runoff regime, altering substantially the overall hydrology of UIB in future. These findings largely contribute to address the hydroclimatic explanation of the "Karakoram Anomaly".

scholarly journals Monitoramento de seca meteorológica com dados TRMM para uma região produtora de grãos do Brasil

2021 ◽  
Vol 12 (2) ◽  
pp. 249-264
Author(s):  
Marionei Fomaca de Sousa Junior ◽  
Eduardo Morgan Uliana ◽  
Mairon Anderson Cordeiro Correa de Carvalho ◽  
Múcio André dos Santos Alves Mendes ◽  
Luana Lisboa
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Mato Grosso ◽  
Satellite Precipitation ◽  
Tropical Rainfall ◽  
Precipitation Analysis

Dentre todos os desastres naturais, a seca caracteriza-se como um dos mais complexo e pouco entendido. Seus efeitos impactam várias áreas da sociedade, como agropecuária, indústria, saúde, distribuição de água e geração de energia. Os índices de seca utilizados para monitorar, identificar e quantificar a anomalia de precipitação tem como principal limitação a falta de dados representativos da área de ocorrência. As medições de variáveis hidro meteorológicas por satélites oferecem uma boa alternativa na falta de dados de superfície. O objetivo do trabalho foi avaliar se o uso do produto 3B43 V7 da missão Tropical Rainfall Measuring Mission (TRMM) multi-satellite Precipitation Analysis (TMPA) é eficaz na geração da precipitação mensal e de mapas de seca a partir do Índice de Precipitação Padronizado mensal na região médio norte de Mato Grosso. Os dados foram comparados a uma base dados de superfície no período de 1998 a 2017. A validação dos mapas de seca foi feita com base na seca que ocorreu durante a safra de 2015/16. Os resultados indicaram que o produto 3B43 V7superestima a precipitação, mas pode ser utilizado na ausência de dados de superfície, uma vez que o valor do coeficiente Nash-Sutcliffe (ENS) foi de 0,75 e do índice de concordância de Willmott (d) foi 0,93. O SPI estimado correspondeu ao observado, apresentando ENS e índice d iguais a 0,63 e 0,92, respectivamente. Os mapas de seca confirmaram a situação relatada nos boletins do Instituto Mato-grossense de Economia Agropecuária que indicaram diminuição da produtividade em decorrência da falta de chuva nos períodos críticos das culturas da soja e do milho.  

scholarly journals Characterization of Interannual and Seasonal Variability of Hydro-Climatic Trends in the Upper Indus Basin

2021 ◽  
Author(s):  
Muhammad Usman Liaqat ◽  
Giovanna Grossi ◽  
Shabeh ul Hasson ◽  
Roberto Ranzi
Keyword(s):  
Trend Analysis ◽  
Hydrological Cycle ◽  
Winter Season ◽  
Rain Gauge ◽  
Indus Basin ◽  
Annual Precipitation ◽  
Monthly Precipitation ◽  
Catchment Scale ◽  
Upper Indus Basin ◽  
Annual Scale

Abstract A high resolution seasonal and annual precipitation climatology of the Upper Indus Basin was developed, based on 1995-2017 precipitation normals obtained from four different gridded datasets (Aphrodite, CHIRPS, PERSIANN-CDR and ERA5) and quality-controlled high and mid elevation ground observations. Monthly precipitation values were estimated through the anomaly method at the catchment scale and compared with runoff data (1975-2017) for verification and detection of changes in the hydrological cycle. The gridded dataset is then analysed using running trends and spectral analysis and the Mann–Kendall test was employed to detect significant trends. The nonparametric Pettitt test was also used to identify the change point in precipitation and runoff time series. The results indicated that bias corrected CHIRPS precipitation dataset, followed by ERA5, performed better in terms of RMSE, MAE, MAPE and BIAS in simulating rain gauge-observed precipitation. The running trend analysis of annual precipitation exhibited a very slight increase whereas a more significant increase was found in the winter season (DJF). A runoff coefficient value greater than one, especially in glacierized catchments (Shigar, Shyok and Gilgit) indicate that precipitation was likely underestimated and glacial melt in a warming climate provides excess runoff volumes. As far as the streamflow is concerned, variabilities are more pronounced at the seasonal rather than at the annual scale. At the annual scale, trend analysis of discharge shows slightly significant increasing trend for the Indus River at the downstream Kachura, Shyok and Gilgit stations. Seasonal flow analysis reveals more complex regimes and its comparison with the variability of precipitation favours a deeper understanding of precipitation, snow- and ice-melt runoff dynamics, addressing the hydroclimatic behaviour of the Karakoram region.

scholarly journals Characterization of Interannual and Seasonal Variability of Hydro-Climatic Trends in the Upper Indus Basin

2020 ◽  
Author(s):  
Muhammad Usman Liaqat ◽  
Roberto Ranzi ◽  
Giovanna Grossi ◽  
Talha Mahmood
Keyword(s):  
Trend Analysis ◽  
Change Point ◽  
Winter Season ◽  
Kendall Test ◽  
Indus Basin ◽  
Percentage Error ◽  
Monsoon Period ◽  
Upper Indus Basin ◽  
Climatic Trends ◽  
Basin Scale

<p>A major part of Pakistan’s economy is dependent upon agriculture which is irrigated from the water resources of the Upper Indus Basin (UIB). Therefore the human impact of hydroclimatic variability in this area is of paramount importance. The Upper Indus Basin is characterized by uncertain hydro-climatic behaviour with changing patterns in different sub-basins. Many studies have worked on hydro-climatic trends at basin scale but only few studies focused on the hydroclimate, precipitation dynamics and their magnitude at sub-basin level. Based upon this scenario, high resolution seasonal and annual climatology of UIB was developed. It is based on precipitation normals 1995-2017 obtained from four different gridded satellite datasets (Aphrodite, Chirps, PERSIANN-CDR and GPCC) as well as quality- controlled high and mid elevation ground observations (1250–4500 m a.s.l.). The quality-control of the gridded dataset is computed by the anomaly method. In order to, evaluate the data quality of the gridded rainfall, four statistics i.e., BIAS, Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) are used in this study. Using running trends and spectral analysis with multi-gauge based anomaly, the study analyses the precipitation and runoff   seasonal and annual temporal variability at sub-basin scale. For this, Mann–Kendall test was employed to detect the presence of any trend while their slope is calculated by Theil Sen’s slope method. The nonparametric Pettitt Test was also used in this study to eventually identify the change point in hydro-climatic time series. The results indicated that bias corrected CHIRPS precipitation datasets performed better in simulating precipitation with RMSE, MAE, MAPE [%] and BIAS followed by APHRODITE. The annual and seasonal precipitation climatology exhibited higher precipitation in the lower side of the basin. The comparison between short and long duration climatologies is being investigated as well. The annual running trend analysis of precipitation exhibited a very slight change whereas a more significant increase was found in the winter season (DJF) and most of sub-basins feature a significant decreasing rate in precipitation and constant change point within the monsoon period (JJA). Similarly, trend analysis for runoff in main rivers of Upper Indus Basin at Gilgat, Indus (Besham Qila, Bunji) exhibit nonsignificant increase except Hunza and Indus at Kharmong which are showed decrease annual trends and will be further investigated for seasonal patterns. Overall, these findings would assist to better understand precipitation, snow- and ice-melt runoff dynamics, addressing the hydroclimatic behaviour of the Karakoram region.</p>

scholarly journals Evaluating the TRMM Multisatellite Precipitation Analysis for Extreme Precipitation and Streamflow in Ganjiang River Basin, China

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Shanshan Jiang ◽  
Zengxin Zhang ◽  
Yuhan Huang ◽  
Xi Chen ◽  
Sheng Chen
Keyword(s):  
River Basin ◽  
Extreme Precipitation ◽  
Hydrological Model ◽  
Tropical Rainfall Measuring Mission ◽  
Precipitation Data ◽  
Tropical Rainfall ◽  
Precipitation Estimation ◽  
Precipitation Analysis ◽  
Trmm 3B42 ◽  
Ganjiang River Basin

Based on the observed precipitation data and TRMM (Tropical Rainfall Measuring Mission) 3B42 RTV7 and 3B42 V7 precipitation products from 2003 to 2010, the extreme precipitation and streamflow in the Ganjiang River basin were analyzed. The VIC hydrological model was used to simulate the streamflow driven by RTV7/V7 precipitation products in the Ganjiang River basin. The results show that (1) both of the RTV7 and V7 precipitation products have good applicability in precipitation estimation in the Ganjiang River basin and the correlation between the observed precipitation and RTV7 (V7) was as higher as 0.85 (0.86); (2) the RTV7/V7 precipitation products can well be used to simulate the streamflow by using the VIC hydrological model and the correlation between the observed streamflow and simulated streamflow driven by RTV7 (V7) products was as high as 0.86 (0.89); (3) the extreme precipitation varied greatly in the Ganjiang River basin and both of the RTV7 and V7 can capture the pattern of extreme precipitation in the Ganjiang River basin; however, higher extreme precipitation can be found in the northern Ganjiang River basin; (4) the extreme streamflow simulated driven by RTV7/V7 products agreed well with the observed extreme streamflow in the Ganjiang River basin. This study indicated that the TRMM 3B42 RTV7 and V7 products can be well used in the estimation of extreme precipitation and extreme streamflow.

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