scholarly journals Precipitation Retrieval over the Tibetan Plateau from the Geostationary Orbit—Part 1: Precipitation Area Delineation with Elektro-L2 and Insat-3D

2019 ◽  
Vol 11 (19) ◽  
pp. 2302 ◽  
Author(s):  
Christine Kolbe ◽  
Boris Thies ◽  
Sebastian Egli ◽  
Lukas Lehnert ◽  
Hans Schulz ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Model Performance ◽  
Skill Score ◽  
Probability Of Detection ◽  
Geostationary Orbit ◽  
The Tibetan Plateau ◽  
Multispectral Data ◽  
Precipitation Estimates ◽  
Precipitation Area ◽  
Improved Performance

The lack of long term and well distributed precipitation observations on the Tibetan Plateau (TiP) with its complex terrain raises the need for other sources of precipitation data for this area. Satellite-based precipitation retrievals can fill those data gaps. Before precipitation rates can be retrieved from satellite imagery, the precipitating area needs to be classified properly. Here, we present a feasibility study of a precipitation area delineation scheme for the TiP based on multispectral data with data fusion from the geostationary orbit (GEO, Insat-3D and Elektro-L2) and a machine learning approach (Random Forest, RF). The GEO data are used as predictors for the RF model, extensively validated by independent GPM (Global Precipitation Measurement Mission) IMERG (Integrated Multi-satellitE Retrievals for GPM) gauge calibrated microwave (MW) best-quality precipitation estimates. To improve the RF model performance, we tested different optimization schemes. Here, we find that (1) using more precipitating pixels and reducing the amount of non-precipitating pixels during training greatly improved the classification results. The accuracy of the precipitation area delineation also benefits from (2) changing the temporal resolution into smaller segments. We particularly compared our results to the Infrared (IR) only precipitation product from GPM IMERG and found a markedly improved performance of the new multispectral product (Heidke Skill Score (HSS) of 0.19 (IR only) compared to 0.57 (new multispectral product)). Other studies with a precipitation area delineation obtained a probability of detection (POD) of 0.61, whereas our POD is comparable, with 0.56 on average. The new multispectral product performs best (worse) for precipitation rates above the 90th percentile (below the 10th percentile). Our results point to a clear strategy to improve the IMERG product in the absence of MW radiances.

scholarly journals Correction: Kolbe, C., et al. Precipitation Retrieval over the Tibetan Plateau from the Geostationary Orbit—Part 2: Precipitation Rates with Elektro-L2 and Insat-3D. Remote Sensing 2020, 12, 2114

2020 ◽  
Vol 12 (21) ◽  
pp. 3594
Author(s):  
Christine Kolbe ◽  
Boris Thies ◽  
Nazli Turini ◽  
Zhiyu Liu ◽  
Jörg Bendix
Keyword(s):  
Remote Sensing ◽  
Tibetan Plateau ◽  
Geostationary Orbit ◽  
The Tibetan Plateau

The authors wish to make the following corrections to this paper [...]

scholarly journals Statistical Characteristics of Mesoscale Convective Systems Initiated over the Tibetan Plateau in Summer by Fengyun Satellite and Precipitation Estimates

2021 ◽  
Vol 13 (9) ◽  
pp. 1652
Author(s):  
Xidi Zhang ◽  
Wenqiang Shen ◽  
Xiaoyong Zhuge ◽  
Shunan Yang ◽  
Yun Chen ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Rapid Development ◽  
Mesoscale Convective Systems ◽  
Statistical Characteristics ◽  
The Tibetan Plateau ◽  
Convective Systems ◽  
Lower Cloud ◽  
Mesoscale Convective ◽  
Precipitation Estimates ◽  
High Level

In order to investigate the key characteristics of mesoscale convective systems (MCSs) initiated over the Tibetan Plateau (TP) in recent years and the main differences in circulation and environmental factors between different types of MCSs, an automatic MCS identification and tracking method was applied based on the data from China’s Fengyun satellite and precipitation estimates. In total, 8820 MCSs were found to have been initiated over the TP during the summers from 2013 to 2019, and a total of 9.3% of them were able to move eastward out of the TP (EO). The number of MCSs showed a monthly variation, with a maximum in July and a minimum in June, while most EOs occurred in June. Compared with other types of MCSs, EOs usually had a lower cloud-top temperature, a greater rainfall intensity, a longer life duration, more rapid development, larger areas of rainfall and convective clouds, longer tracks and a wider influence range, indicating that EOs are more vigorous than the other types of MCSs. The movement of MCSs is mainly due to the mid- to high-level dynamic conditions, and moisture is an essential factor in their development and maintenance.

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 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.

scholarly journals A Methodological Framework to Retrospectively Obtain Downscaled Precipitation Estimates over the Tibetan Plateau

2018 ◽  
Vol 10 (12) ◽  
pp. 1974 ◽  
Author(s):  
Kang He ◽  
Ziqiang Ma ◽  
Ruiying Zhao ◽  
Asim Biswas ◽  
Hongfen Teng ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Tropical Rainfall Measuring Mission ◽  
Wavelet Coherence ◽  
The Tibetan Plateau ◽  
Methodological Framework ◽  
Precipitation Estimates ◽  
Precipitation Analysis ◽  
Better Than

Long-term precipitation estimates with both finer spatial resolution and better quality are vital and highly needed in various related fields. Numerous downscaling algorithms have been investigated based on the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), to obtain precipitation data with finer resolution (~1 km). However, this research was restricted by the time span of the TMPA dataset, as the starting time of TMPA was 1998. In this study, a new methodological framework incorporating wavelet coherence and Cubist was proposed to retrospectively obtain downscaled precipitation estimates (DS) over the Tibetan Plateau (TP), based on TMPA and ground observations, in 1990s. The correlations and similarities of precipitation patterns between the target years, from 1990 to 1999, and reference years, from 2000 to 2013, were firstly determined using wavelet coherence based on ground observations. Following this, the TMPA data in the reference years were regarded as the reference in the corresponding target years, which were adopted to be downscaled using Cubist models and land surface variables, to obtain the DS in the target years. We found that the DS showed continuous trends, which corresponded well with the ground observations. Additionally, the performances of the DS were better than those of the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over the TP. Therefore, this methodological framework has great potential for obtaining precipitation estimates for the period of the 1990s for which TMPA data is inaccessible.

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 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.

Sign in / Sign up

Export Citation Format

Share Document