scholarly journals Comparisons of Spatially Downscaling TMPA and IMERG over the Tibetan Plateau

2018 ◽  
Vol 10 (12) ◽  
pp. 1883 ◽  
Author(s):  
Ziqiang Ma ◽  
Kang He ◽  
Xiao Tan ◽  
Jintao Xu ◽  
Weizhen Fang ◽  
...  
Keyword(s):  
Random Forest ◽  
Tibetan Plateau ◽  
Spatial Information ◽  
Rain Gauge ◽  
The Tibetan Plateau ◽  
Precipitation Data ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Improved Accuracy ◽  
Global Precipitation

Accurate precipitation data is crucial in many applications such as hydrology, meteorology, and ecology. Compared with ground observations, satellite-based precipitation estimates can provide much more spatial information to characterize precipitation. In this study, the satellite-based precipitation products of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) and Tropical Rainfall Measurement Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) were firstly evaluated over the Tibetan Plateau (TP) in 2015 against ground observations at both annual and monthly scales. Secondly, random forest algorithm was used to obtain the annual downscaled results (~1 km) based on IMERG and TMPA data and the downscaled results were examined against rain gauge data. Thirdly, a disaggregation algorithm was used to obtain the monthly downscaled results based on those at annual scale. The results indicated that (1) IMERG performed better than TMPA at both annual and monthly scales; (2) IMERG had few anomalies while TMPA displayed significant numbers of outliers in central and western parts of the TP; (3) random forest was a promising algorithm in acquiring high resolution precipitation data with improved accuracy; (4) the downscaled results based on IMERG had better performances than those based on TMPA.

scholarly journals Precipitation Retrieval over the Tibetan Plateau from the Geostationary Orbit—Part 2: Precipitation Rates with Elektro-L2 and Insat-3D

2020 ◽  
Vol 12 (13) ◽  
pp. 2114
Author(s):  
Christine Kolbe ◽  
Boris Thies ◽  
Nazli Turini ◽  
Zhiyu Liu ◽  
Jörg Bendix
Keyword(s):  
Tibetan Plateau ◽  
Rain Gauge ◽  
The Tibetan Plateau ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Geo Satellites ◽  
Spatio Temporal ◽  
Model Training ◽  
Global Precipitation Measurement ◽  
Global Precipitation

We present the new Precipitation REtrieval covering the TIbetan Plateau (PRETIP) as a feasibility study using the two geostationary (GEO) satellites Elektro-L2 and Insat-3D with reference to the GPM (Global Precipitation Measurement Mission) IMERG (Integrated Multi-satellitE Retrievals for GPM) product. The present study deals with the assignment of the rainfall rate. For precipitation rate assignment, the best-quality precipitation estimates from the gauge calibrated microwave (MW) within the IMERG product were combined with the GEO data by Random Forest (RF) regression. PRETIP was validated with independent MW precipitation information not considered for model training and revealed a good performance on 30 min and 11 km spatio-temporal resolution with a correlation coefficient of R = 0.59 and outperforms the validation of the independent MW precipitation with IMERG’s IR only product (R = 0.18). A comparison of PRETIP precipitation rates in 4 km resolution with daily rain gauge measurements from the Chinese Ministry of Water Resources revealed a correlation of R = 0.49. No differences in the performance of PRETIP for various elevation ranges or between the rainy (July, August) and the dry (May, September) season could be found.

Precipitation Retrieval over the Tibetan Plateau from the Geostationary Orbit

2020 ◽  
Author(s):  
Christine Kolbe ◽  
Boris Thies ◽  
Nazli Turini ◽  
Jörg Bendix
Keyword(s):  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Cloud Properties ◽  
Spectral Bands ◽  
Precipitation Measurement ◽  
High Asia ◽  
Precipitation Estimates ◽  
Optimization Schemes ◽  
Global Precipitation Measurement ◽  
Global Precipitation

<p>The distribution of precipitation on the Tibetan Plateau (TiP) is not yet understood due to various factors. Satellite-based precipitation retrieval can provide comprehensive information in a high spatial-temporal resolution. The aim of this feasibility study is to retrieve precipitation rates over High Asia using multi-spectral data from the two geostationary (GEO) satellites Elektro-L2 and Insat-3D in a 30 minutes and 4 km resolution. The variety of spectral bands from both satellites provides an insight into the cloud properties which are associated with precipitation. In the first step, the precipitation area is delineated, and in a second step, the rates are retrieved. To this end, we use a machine learning approach (Random Forest, RF) and a precipitation product of the Global Precipitation Measurement Mission (GPM IMERG) as a reference. From this product, we use the best quality gauge calibrated microwave (MW) precipitation estimates. We validate our results with independent gauge calibrated MW precipitation. To improve the RF models, we tested various optimization schemes. The results of this study will provide information about the precipitation processes in High Asia.</p>

scholarly journals The Contribution of Rain Gauges in the Calibration of the IMERG Product: Results from the First Validation over Spain

2020 ◽  
Vol 21 (2) ◽  
pp. 161-182 ◽  
Author(s):  
Francisco J. Tapiador ◽  
Andrés Navarro ◽  
Eduardo García-Ortega ◽  
Andrés Merino ◽  
José Luis Sánchez ◽  
...  
Keyword(s):  
Rain Gauge ◽  
Surface Precipitation ◽  
Rain Gauges ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Level 3 ◽  
Hydrologic Impacts ◽  
A Minor ◽  
Global Precipitation Measurement ◽  
Global Precipitation

AbstractAfter 5 years in orbit, the Global Precipitation Measurement (GPM) mission has produced enough quality-controlled data to allow the first validation of their precipitation estimates over Spain. High-quality gauge data from the meteorological network of the Spanish Meteorological Agency (AEMET) are used here to validate Integrated Multisatellite Retrievals for GPM (IMERG) level 3 estimates of surface precipitation. While aggregated values compare notably well, some differences are found in specific locations. The research investigates the sources of these discrepancies, which are found to be primarily related to the underestimation of orographic precipitation in the IMERG satellite products, as well as to the number of available gauges in the GPCC gauges used for calibrating IMERG. It is shown that IMERG provides suboptimal performance in poorly instrumented areas but that the estimate improves greatly when at least one rain gauge is available for the calibration process. A main, generally applicable conclusion from this research is that the IMERG satellite-derived estimates of precipitation are more useful (r2 > 0.80) for hydrology than interpolated fields of rain gauge measurements when at least one gauge is available for calibrating the satellite product. If no rain gauges were used, the results are still useful but with decreased mean performance (r2 ≈ 0.65). Such figures, however, are greatly improved if no coastal areas are included in the comparison. Removing them is a minor issue in terms of hydrologic impacts, as most rivers in Spain have their sources far from the coast.

scholarly journals Evaluation of GPM-Era Satellite Precipitation Products on the Southern Slopes of the Central Himalayas Against Rain Gauge Data

2020 ◽  
Vol 12 (11) ◽  
pp. 1836 ◽  
Author(s):  
Shankar Sharma ◽  
Yingying Chen ◽  
Xu Zhou ◽  
Kun Yang ◽  
Xin Li ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Dynamic Range ◽  
Precipitation Amount ◽  
Rain Gauge ◽  
Central Himalayas ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
New Generation ◽  
Global Precipitation Measurement ◽  
Global Precipitation

The Global Precipitation Measurement (GPM) mission provides high-resolution precipitation estimates globally. However, their accuracy needs to be accessed for algorithm enhancement and hydro-meteorological applications. This study applies data from 388 gauges in Nepal to evaluate the spatial-temporal patterns presented in recently-developed GPM-Era satellite-based precipitation (SBP) products, i.e., the Integrated Multi-satellite Retrievals for GPM (IMERG), satellite-only (IMERG-UC), the gauge-calibrated IMERG (IMERG-C), the Global Satellite Mapping of Precipitation (GSMaP), satellite-only (GSMaP-MVK), and the gauge-calibrated GSMaP (GSMaP-Gauge). The main results are as follows: (1) GSMaP-Gauge datasets is more reasonable to represent the observed spatial distribution of precipitation, followed by IMERG-UC, GSMaP-MVK, and IMERG-C. (2) The gauge-calibrated datasets are more consistent (in terms of relative root mean square error (RRMSE) and correlation coefficient (R)) than the satellite-only datasets in representing the seasonal dynamic range of precipitation. However, all four datasets can reproduce the seasonal cycle of precipitation, which is predominately governed by the monsoon system. (3) Although all four SBP products underestimate the monsoonal precipitation, the gauge-calibrated IMERG-C yields smaller mean bias than GSMaP-Gauge, while GSMaP-Gauge shows the smaller RRMSE and higher R-value; indicating IMERG-C is more reliable to estimate precipitation amount than GSMaP-Gauge, whereas GSMaP-Gauge presents more reasonable spatial distribution than IMERG-C. Only IMERG-C moderately reproduces the evident elevation-dependent pattern of precipitation revealed by gauge observations, i.e., gradually increasing with elevation up to 2000 m and then decreasing; while GSMaP-Gauge performs much better in representing the gauge observed spatial pattern than others. (4) The GSMaP-Gauge calibrated based on the daily gauge analysis is more consistent with detecting gauge observed precipitation events among the four datasets. The high-intensity related precipitation extremes (95th percentile) are more intense in regions with an elevation below 2500 m; all four SBP datasets have low accuracy (<30%) and mostly underestimated (by >40%) the frequency of extreme events at most of the stations across the country. This work represents the quantification of the new-generation SBP products on the southern slopes of the central Himalayas in Nepal.

scholarly journals Evaluation of Five Satellite-Based Precipitation Products in Two Gauge-Scarce Basins on the Tibetan Plateau

2018 ◽  
Vol 10 (8) ◽  
pp. 1316 ◽  
Author(s):  
Peng Bai ◽  
Xiaomang Liu
Keyword(s):  
Tibetan Plateau ◽  
Yellow River ◽  
Temporal Distribution ◽  
Rain Gauge ◽  
The Tibetan Plateau ◽  
Distributed Hydrological Model ◽  
Satellite Precipitation ◽  
Rain Gauges ◽  
Upper Yangtze River ◽  
Precipitation Estimates

The sparse rain gauge networks over the Tibetan Plateau (TP) cause challenges for hydrological studies and applications. Satellite-based precipitation datasets have the potential to overcome the issues of data scarcity caused by sparse rain gauges. However, large uncertainties usually exist in these precipitation datasets, particularly in complex orographic areas, such as the TP. The accuracy of these precipitation products needs to be evaluated before being practically applied. In this study, five (quasi-)global satellite precipitation products were evaluated in two gauge-sparse river basins on the TP during the period 1998–2012; the evaluated products are CHIRPS, CMORPH, PERSIANN-CDR, TMPA 3B42, and MSWEP. The five precipitation products were first intercompared with each other to identify their consistency in depicting the spatial–temporal distribution of precipitation. Then, the accuracy of these products was validated against precipitation observations from 21 rain gauges using a point-to-pixel method. We also investigated the streamflow simulation capacity of these products via a distributed hydrological model. The results indicated that these precipitation products have similar spatial patterns but significantly different precipitation estimates. A point-to-pixel validation indicated that all products cannot efficiently reproduce the daily precipitation observations, with the median Kling–Gupta efficiency (KGE) in the range of 0.10–0.26. Among the five products, MSWEP has the best consistency with the gauge observations (with a median KGE = 0.26), which is thus recommended as the preferred choice for applications among the five satellite precipitation products. However, as model forcing data, all the precipitation products showed a comparable capacity of streamflow simulations and were all able to accurately reproduce the observed streamflow records. The values of the KGE obtained from these precipitation products exceed 0.83 in the upper Yangtze River (UYA) basin and 0.84 in the upper Yellow River (UYE) basin. Thus, evaluation of precipitation products only focusing on the accuracy of streamflow simulations is less meaningful, which will mask the differences between these products. A further attribution analysis indicated that the influences of the different precipitation inputs on the streamflow simulations were largely offset by the parameter calibration, leading to significantly different evaporation and water storage estimates. Therefore, an efficient hydrological evaluation for precipitation products should focus on both streamflow simulations and the simulations of other hydrological variables, such as evaporation and soil moisture.

scholarly journals Comprehensive Characteristics of Summer Deep Convection over Tibetan Plateau and Its South Slope from the Global Precipitation Measurement Core Observatory

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 9 ◽  
Author(s):  
Guolu Gao ◽  
Quanliang Chen ◽  
Hongke Cai ◽  
Yang Li ◽  
Zhenglin Wang
Keyword(s):  
Tibetan Plateau ◽  
Diurnal Variation ◽  
Vertical Structure ◽  
Deep Convection ◽  
Low Frequency ◽  
The Tibetan Plateau ◽  
Precipitation Measurement ◽  
South Slope ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Observational data from the Global Precipitation Measurement (GPM) Core Observatory during four summers (2014–2017) has been used to investigate deep convection systems (DCSs) over the Tibetan Plateau (TP) and its south slope (SS). The frequency, geographical distribution diurnal variation, and vertical structure of DCSs over the TP and SS are compared among these two regions. The frequency of DCSs over the SS (0.98%) was far higher than over the TP (0.15%), suggesting that stronger DCSs occur to the east and south of the TP. The maximum number of DCS occurred in July and August. A clear diurnal variation in DCS was found over the whole region, DCSs over the TP and SS both have a greatest amplitude in the afternoon. The probability of DCSs from 1200 to 1800 local time (LT) was 76.3% and 44.1% over TP and SS respectively, whereas the probability of DCSs being generated from 2200 (LT) to 0600 on the next day LT was 0.03% and 33.1% over the TP and SS respectively. There was a very low frequency of DCSs over the TP during the night. Five special echo top heights were used to investigate the vertical structure of DCSs. DCSs over the TP were both weaker and smaller than those over the SS.

scholarly journals The Global Precipitation Measurement (GPM) Mission for Science and Society

2017 ◽  
Vol 98 (8) ◽  
pp. 1679-1695 ◽  
Author(s):  
Gail Skofronick-Jackson ◽  
Walter A. Petersen ◽  
Wesley Berg ◽  
Chris Kidd ◽  
Erich F. Stocker ◽  
...  
Keyword(s):  
Climate Models ◽  
Microwave Radiometer ◽  
Three Dimensional ◽  
Current Status ◽  
Precipitation Data ◽  
Dual Frequency ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract Precipitation is a key source of freshwater; therefore, observing global patterns of precipitation and its intensity is important for science, society, and understanding our planet in a changing climate. In 2014, the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA) launched the Global Precipitation Measurement (GPM) Core Observatory (CO) spacecraft. The GPM CO carries the most advanced precipitation sensors currently in space including a dual-frequency precipitation radar provided by JAXA for measuring the three-dimensional structures of precipitation and a well-calibrated, multifrequency passive microwave radiometer that provides wide-swath precipitation data. The GPM CO was designed to measure rain rates from 0.2 to 110.0 mm h−1 and to detect moderate to intense snow events. The GPM CO serves as a reference for unifying the data from a constellation of partner satellites to provide next-generation, merged precipitation estimates globally and with high spatial and temporal resolutions. Through improved measurements of rain and snow, precipitation data from GPM provides new information such as details on precipitation structure and intensity; observations of hurricanes and typhoons as they transition from the tropics to the midlatitudes; data to advance near-real-time hazard assessment for floods, landslides, and droughts; inputs to improve weather and climate models; and insights into agricultural productivity, famine, and public health. Since launch, GPM teams have calibrated satellite instruments, refined precipitation retrieval algorithms, expanded science investigations, and processed and disseminated precipitation data for a range of applications. The current status of GPM, its ongoing science, and its future plans are presented.

scholarly journals An Efficient Downscaling Scheme for High-Resolution Precipitation Estimates over a High Mountainous Watershed

2021 ◽  
Vol 13 (2) ◽  
pp. 234
Author(s):  
Na Zhao
Keyword(s):  
High Resolution ◽  
Model Performance ◽  
Absolute Error ◽  
Rain Gauge ◽  
Monthly Precipitation ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Residual Correction ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Satellites are capable of observing precipitation over large areas and are particularly suitable for estimating precipitation in high mountains and poorly gauged regions. However, the coarse resolution and relatively low accuracy of satellites limit their applications. In this study, a downscaling scheme was developed to obtain precipitation estimates with high resolution and high accuracy in the Heihe watershed. Shannon’s entropy, together with a semi-variogram, was applied to establish the optimal precipitation station network. A combination of the random forest (RF) method and the residual correction approach with the established rain gauge network was applied to downscale monthly precipitation products from Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG). The results indicated that the RF model showed little improvement in the accuracy of IMERG-based precipitation downscaling. Including residual modification could improve the results of the RF model. The mean absolute error (MAE) and root mean square error (RMSE) values decreased by 19% and 21%, respectively, after residual corrections were added to the RF approach. Moreover, we found that enough rain gauge records are necessary for and remain an important component of tuning model performance. The application of more rain gauges improves the performance of the combined RF and residual modification methods, with the MAE and RMSE values reduced by 8% and 9%, respectively. Residual correction, together with enough precipitation stations, can effectively enhance the quality of the precipitation patterns and magnitudes obtained in the RF downscaling process. The proposed downscaling scheme is an effective tool for increasing the accuracy and spatial resolution of precipitation fields in the Heihe watershed.

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