scholarly journals Development of a new high spatial resolution (0.25° × 0.25°) long period (1901-2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region

MAUSAM ◽  
2021 ◽  
Vol 65 (1) ◽  
pp. 1-18 ◽  
Author(s):  
D.S Pai ◽  
M Rajeevan ◽  
O.P Sreejith ◽  
B. Mukhopadhyay ◽  
N.S Satbha
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Data Sets ◽  
Gridded Data ◽  
Rainfall Distribution ◽  
Data Set ◽  
The Western Ghats

ABSTRACT. The study discusses development of a new daily gridded rainfall data set (IMD4) at a high spatial resolution (0.25° × 0.25°, latitude × longitude) covering a longer period of 110 years (1901-2010) over the Indian main land.  A comparison of IMD4 with 4 other existing daily gridded rainfall data sets of different spatial resolutions and time periods has also been discussed. For preparing the new gridded data, daily rainfall records from 6955 rain gauge stations in India were used, highest  number of stations used by any studies so far for such a purpose. The gridded data set was developed after making quality control of basic rain-gauge stations. The comparison of IMD4 with other data sets suggested that the climatological and variability features of rainfall over India derived from IMD4 were comparable with the existing gridded daily rainfall data sets. In addition, the spatial rainfall distribution like heavy rainfall areas in the orographic regions of the west coast and over northeast, low rainfall in the lee ward side of the Western Ghats etc. were more realistic and better presented in IMD4 due to its higher spatial resolution and to the higher density of rainfall stations used for its development.

scholarly journals Performance of TRMM TMPA 3B42 V7 in Replicating Daily Rainfall and Regional Rainfall Regimes in the Amazon Basin (1998–2013)

2018 ◽  
Vol 10 (12) ◽  
pp. 1879 ◽  
Author(s):  
Véronique Michot ◽  
Daniel Vila ◽  
Damien Arvor ◽  
Thomas Corpetti ◽  
Josyane Ronchail ◽  
...  
Keyword(s):  
Amazon Basin ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Spatial Coverage ◽  
Rainfall Regimes ◽  
Trmm 3B42 ◽  
Good Agreement

Knowledge and studies on precipitation in the Amazon Basin (AB) are determinant for environmental aspects such as hydrology, ecology, as well as for social aspects like agriculture, food security, or health issues. Availability of rainfall data at high spatio-temporal resolution is thus crucial for these purposes. Remote sensing techniques provide extensive spatial coverage compared to ground-based rainfall data but it is imperative to assess the quality of the estimates. Previous studies underline at regional scale in the AB, and for some years, the efficiency of the Tropical Rainfall Measurement Mission (TRMM) 3B42 Version 7 (V7) (hereafter 3B42) daily product data, to provide a good view of the rainfall time variability which is important to understand the impacts of El Nino Southern Oscilation. Then our study aims to enhance the knowledge about the quality of this product on the entire AB and provide a useful understanding about his capacity to reproduce the annual rainfall regimes. For that purpose we compared 3B42 against 205 quality-controlled rain gauge measurements for the period from March 1998 to July 2013, with the aim to know whether 3B42 is reliable for climate studies. Analysis of quantitative (Bias, Relative RMSE) and categorical statistics (POD, FAR) for the whole period show a more accurate spatial distribution of mean daily rainfall estimations in the lowlands than in the Andean regions. In the latter, the location of a rain gauge and its exposure seem to be more relevant to explain mismatches with 3B42 rather than its elevation. In general, a good agreement is observed between rain gauge derived regimes and those from 3B42; however, performance is better in the rainy period. Finally, an original way to validate the estimations is by taking into account the interannual variability of rainfall regimes (i.e., the presence of sub-regimes): four sub-regimes in the northeast AB defined from rain gauges and 3B42 were found to be in good agreement. Furthermore, this work examined whether TRMM 3B42 V7 rainfall estimates for all the grid points in the AB, outgoing longwave radiation (OLR) and water vapor flux patterns are consistent in the northeast of AB.

scholarly journals High-resolution mapping of the NO<sub>2</sub> spatial distribution over Belgian urban areas based on airborne APEX remote sensing

2017 ◽  
Vol 10 (5) ◽  
pp. 1665-1688 ◽  
Author(s):  
Frederik Tack ◽  
Alexis Merlaud ◽  
Marian-Daniel Iordache ◽  
Thomas Danckaert ◽  
Huan Yu ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Urban Areas ◽  
High Spatial Resolution ◽  
European Space Agency ◽  
Correlation Coefficients ◽  
Time Frame ◽  
Quantitative Information ◽  
Data Sets ◽  
Vertical Column

Abstract. We present retrieval results of tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs), mapped at high spatial resolution over three Belgian cities, based on the DOAS analysis of Airborne Prism EXperiment (APEX) observations. APEX, developed by a Swiss-Belgian consortium on behalf of ESA (European Space Agency), is a pushbroom hyperspectral imager characterised by a high spatial resolution and high spectral performance. APEX data have been acquired under clear-sky conditions over the two largest and most heavily polluted Belgian cities, i.e. Antwerp and Brussels on 15 April and 30 June 2015. Additionally, a number of background sites have been covered for the reference spectra. The APEX instrument was mounted in a Dornier DO-228 aeroplane, operated by Deutsches Zentrum für Luft- und Raumfahrt (DLR). NO2 VCDs were retrieved from spatially aggregated radiance spectra allowing urban plumes to be resolved at the resolution of 60  ×  80 m2. The main sources in the Antwerp area appear to be related to the (petro)chemical industry while traffic-related emissions dominate in Brussels. The NO2 levels observed in Antwerp range between 3 and 35  ×  1015 molec cm−2, with a mean VCD of 17.4 ± 3.7  ×  1015 molec cm−2. In the Brussels area, smaller levels are found, ranging between 1 and 20  ×  1015 molec cm−2 and a mean VCD of 7.7 ± 2.1  ×  1015 molec cm−2. The overall errors on the retrieved NO2 VCDs are on average 21 and 28 % for the Antwerp and Brussels data sets. Low VCD retrievals are mainly limited by noise (1σ slant error), while high retrievals are mainly limited by systematic errors. Compared to coincident car mobile-DOAS measurements taken in Antwerp and Brussels, both data sets are in good agreement with correlation coefficients around 0.85 and slopes close to unity. APEX retrievals tend to be, on average, 12 and 6 % higher for Antwerp and Brussels, respectively. Results demonstrate that the NO2 distribution in an urban environment, and its fine-scale variability, can be mapped accurately with high spatial resolution and in a relatively short time frame, and the contributing emission sources can be resolved. High-resolution quantitative information about the atmospheric NO2 horizontal variability is currently rare, but can be very valuable for (air quality) studies at the urban scale.

scholarly journals Geo-Object-Based Land Cover Map Update for High-Spatial-Resolution Remote Sensing Images via Change Detection and Label Transfer

2020 ◽  
Vol 12 (1) ◽  
pp. 174
Author(s):  
Tianjun Wu ◽  
Jiancheng Luo ◽  
Ya’nan Zhou ◽  
Changpeng Wang ◽  
Jiangbo Xi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Change Detection ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Data Set ◽  
Label Transfer ◽  
Object Based ◽  
Training Samples ◽  
Map Updating

Land cover (LC) information plays an important role in different geoscience applications such as land resources and ecological environment monitoring. Enhancing the automation degree of LC classification and updating at a fine scale by remote sensing has become a key problem, as the capability of remote sensing data acquisition is constantly being improved in terms of spatial and temporal resolution. However, the present methods of generating LC information are relatively inefficient, in terms of manually selecting training samples among multitemporal observations, which is becoming the bottleneck of application-oriented LC mapping. Thus, the objectives of this study are to speed up the efficiency of LC information acquisition and update. This study proposes a rapid LC map updating approach at a geo-object scale for high-spatial-resolution (HSR) remote sensing. The challenge is to develop methodologies for quickly sampling. Hence, the core step of our proposed methodology is an automatic method of collecting samples from historical LC maps through combining change detection and label transfer. A data set with Chinese Gaofen-2 (GF-2) HSR satellite images is utilized to evaluate the effectiveness of our method for multitemporal updating of LC maps. Prior labels in a historical LC map are certified to be effective in a LC updating task, which contributes to improve the effectiveness of the LC map update by automatically generating a number of training samples for supervised classification. The experimental outcomes demonstrate that the proposed method enhances the automation degree of LC map updating and allows for geo-object-based up-to-date LC mapping with high accuracy. The results indicate that the proposed method boosts the ability of automatic update of LC map, and greatly reduces the complexity of visual sample acquisition. Furthermore, the accuracy of LC type and the fineness of polygon boundaries in the updated LC maps effectively reflect the characteristics of geo-object changes on the ground surface, which makes the proposed method suitable for many applications requiring refined LC maps.

scholarly journals Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia

2013 ◽  
Vol 17 (4) ◽  
pp. 1311-1318 ◽  
Author(s):  
F. Yusof ◽  
I. L. Kane ◽  
Z. Yusop
Keyword(s):  
Long Memory ◽  
Structural Breaks ◽  
Structural Break ◽  
Daily Rainfall ◽  
Least Square ◽  
Rainfall Data ◽  
Data Sets ◽  
Original Series ◽  
Empirical Survey ◽  
Daily Rainfall Data

Abstract. A short memory process that encounters occasional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I (d) processes. In this paper we employed a procedure for estimating the fractional differencing parameter in semiparametric contexts proposed by Geweke and Porter-Hudak (1983) to analyse nine daily rainfall data sets across Malaysia. The results indicate that all the data sets exhibit long memory. Furthermore, an empirical fluctuation process using the ordinary least square (OLS)-based cumulative sum (CUSUM) test for the break date was applied. Break dates were detected in all data sets. The data sets were partitioned according to their respective break date, and a further test for long memory was applied for all subseries. Results show that all subseries follows the same pattern as the original series. The estimate of the fractional parameters d1 and d2 on the subseries obtained by splitting the original series at the break date confirms that there is a long memory in the data generating process (DGP). Therefore this evidence shows a true long memory not due to structural break.

Estimation of Short-Duration Rainfall Distribution Using Data Measured at Longer Time Scales

1994 ◽  
Vol 29 (1-2) ◽  
pp. 39-45 ◽  
Author(s):  
Van-Thanh Van Nguyen ◽  
Ganesh Raj Pandey
Keyword(s):  
Mathematical Model ◽  
Probability Distribution ◽  
Time Scales ◽  
Short Duration ◽  
Daily Rainfall ◽  
Regional Model ◽  
Rainfall Data ◽  
Rainfall Distribution ◽  
Proposed Model ◽  
Using Data

An investigation on how to estimate the distribution of short-duration (hours or shorter) rainfalls based on available daily rainfall measurements was undertaken. On the basis of the theory of multifractal multiplicative cascades, a scale-independent mathematical model was proposed to represent the probability distribution of rainfalls at various time scales. Using rainfall records from a network of seven recording gauges in the Montreal region in Quebec (Canada), it was found that the proposed model could provide adequate estimates of the distribution of hourly rainfalls at locations where these short-duration rainfall data are not available. Further, it has been observed that one single regional model can be developed to describe the scaling nature of rainfall distributions within the whole study area.

scholarly journals Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations

2015 ◽  
Vol 19 (12) ◽  
pp. 4747-4764 ◽  
Author(s):  
F. Alshawaf ◽  
B. Fersch ◽  
S. Hinz ◽  
H. Kunstmann ◽  
M. Mayer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Data Fusion ◽  
Spatial Resolution ◽  
Heterogeneous Data ◽  
Spatial Density ◽  
Data Sets ◽  
Data Set ◽  
Fixed Rank Kriging ◽  
Fixed Rank

Abstract. Data fusion aims at integrating multiple data sources that can be redundant or complementary to produce complete, accurate information of the parameter of interest. In this work, data fusion of precipitable water vapor (PWV) estimated from remote sensing observations and data from the Weather Research and Forecasting (WRF) modeling system are applied to provide complete grids of PWV with high quality. Our goal is to correctly infer PWV at spatially continuous, highly resolved grids from heterogeneous data sets. This is done by a geostatistical data fusion approach based on the method of fixed-rank kriging. The first data set contains absolute maps of atmospheric PWV produced by combining observations from the Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). These PWV maps have a high spatial density and a millimeter accuracy; however, the data are missing in regions of low coherence (e.g., forests and vegetated areas). The PWV maps simulated by the WRF model represent the second data set. The model maps are available for wide areas, but they have a coarse spatial resolution and a still limited accuracy. The PWV maps inferred by the data fusion at any spatial resolution show better qualities than those inferred from single data sets. In addition, by using the fixed-rank kriging method, the computational burden is significantly lower than that for ordinary kriging.

scholarly journals Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation

2018 ◽  
Vol 20 (4) ◽  
pp. 784-797 ◽  
Author(s):  
Marija Ivković ◽  
Andrijana Todorović ◽  
Jasna Plavšić
Keyword(s):  
Daily Rainfall ◽  
Flood Forecasting ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Rainfall Data ◽  
Rain Gauges ◽  
Observation Network ◽  
Hourly Rainfall ◽  
Extreme Flood ◽  
Flood Simulations

Abstract Flood forecasting relies on good quality of observed and forecasted rainfall. In Serbia, the recording rain gauge network is sparse and rainfall data mainly come from dense non-recording rain gauges. This is not beneficial for flood forecasting in smaller catchments and short-duration events, when hydrologic models operating on subdaily scale are applied. Moreover, differences in rainfall amounts from two types of gauges can be considerable, which is common in operational hydrological practice. This paper examines the possibility of including daily rainfall data from dense observation networks in flood forecasting based on subdaily data, using the extreme flood event in the Kolubara catchment in May 2014 as a case study. Daily rainfall from a dense observation network is disaggregated to hourly scale using the MuDRain multivariate disaggregation software. The disaggregation procedure results in well-reproduced rainfall dynamics and adjusts rainfall volume to the values from the non-recording gauges. The fully distributed wflow_hbv model, which is under development as a forecasting tool for the Kolubara catchment, is used for flood simulations with two alternative hourly rainfall data. The results show an improvement when the disaggregated rainfall from denser network is used, thus indicating the significance of better representation of rainfall temporal and spatial variability for flood forecasting.

scholarly journals Spatial Downscaling of TRMM Precipitation Data Using an Optimal Subset Regression Model with NDVI and Terrain Factors in the Yarlung Zangbo River Basin, China

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Jinping Liu ◽  
Wanchang Zhang ◽  
Ning Nie
Keyword(s):  
River Basin ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Rain Gauge ◽  
Precipitation Data ◽  
Rain Gauge Data ◽  
Optimal Subset ◽  
Yarlung Zangbo River ◽  
Gauge Data ◽  
Subset Regression

High accuracy, high spatial resolution precipitation data is important for understanding basin-scale hydrology and the spatiotemporal distributions of regional precipitation. The objective of this study was to develop a reliable statistical downscaling algorithm to produce high quality, high spatial resolution precipitation products from Tropical Rainfall Monitoring Mission (TRMM) 3B43 data over the Yarlung Zangbo River Basin using an optimal subset regression (OSR) model combined with multiple topographical factors, the Normalized Difference Vegetation Index (NDVI), and observational data from rain gauge stations. After downscaling, the bias between TRMM 3B43 and rain gauge data decreased considerably from 0.397 to 0.109, the root-mean-square error decreased from 235.16 to 124.60 mm, and the r2 increased from 0.54 to 0.61, indicating significant improvement in the spatial resolution and accuracy of the TRMM 3B43 data. Moreover, the spatial patterns of both precipitation rates of change and their corresponding p value statistics were consistent between the downscaled results and the original TRMM 3B43 during the 2001–2014 period, which verifies that the downscaling method performed well in the Yarlung Zangbo River Basin. Its high performance in downscaling precipitation was also proven by comparing with other models. All of these findings indicate that the proposed approach greatly improved the quality and spatial resolution of TRMM 3B43 rainfall products in the Yarlung Zangbo River Basin, for which rain gauge data is limited. The potential of the post-real-time Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) downscaled precipitation product was also demonstrated in this study.

3D ray+Born migration/inversion—Part 2: Application to the SEG/EAGE overthrust experiment

Geophysics ◽  
2003 ◽  
Vol 68 (4) ◽  
pp. 1357-1370 ◽  
Author(s):  
Stéphane Operto ◽  
Gilles Lambaré ◽  
Pascal Podvin ◽  
Philippe Thierry
Keyword(s):  
Spatial Resolution ◽  
Seismic Data ◽  
Velocity Model ◽  
Nonuniform Distribution ◽  
Data Sets ◽  
Data Set ◽  
Quantitative Estimates ◽  
3D Processing ◽  
Type Data ◽  
New Formula

The SEG/EAGE overthrust model is a synthetic onshore velocity model that was used to generate several large synthetic seismic data sets using acoustic finite‐difference modeling. From this database, several realistic subdata sets were extracted and made available for testing 3D processing methods. For example, classic onshore‐type data‐acquisition geometries are available such as a swath acquisition, which is characterized by a nonuniform distribution of long offsets with azimuth and midpoints. In this paper, we present an application of 2.5D and 3D ray‐Born migration/inversion to several classical data sets from the SEG/EAGE overthrust experiment. The method is formulated as a linearized inversion of the scattered wavefield. The method allows quantitative estimates of short wavelength components of the velocity model. First, we apply a 3D migration/inversion formula formerly developed for marine acquisitions to the swath data set. The migrated sections exhibit significant amplitude artifacts and acquisition footprints, also revealed by the shape of the local spatial resolution filters. From the analysis of these spatial resolution filters, we propose a new formula significantly improving the migrated dip section. We also present 3D migrated results for the strike section and a small 3D target containing a channel. Finally, the applications demonstrate, that the ray+Born migration formula must be adapted to the acquisition geometry to obtain reliable estimates of the true amplitude of the model perturbations. This adaptation is relatively straightforward in the frame of the ray+Born formalism and can be guided by the analysis of the resolution operator.

scholarly journals Probability Distribution of Philippine Daily Rainfall Data

2017 ◽  
Author(s):  
Vanessa Althea B. Bermudez ◽  
Ariel Bettina B. Abilgos ◽  
Diane Carmeliza N. Cuaresma ◽  
Jomar F. Rabajante
Keyword(s):  
Probability Distribution ◽  
Probability Distributions ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Economic Systems ◽  
Tropical Country ◽  
Data Set ◽  
Cumulative Rainfall ◽  
The Pacific ◽  
The Pacific Ocean

Philippines as an archipelago and tropical country, which is situated near the Pacific ocean, faces uncertain rainfall intensities. This makes environmental, agricultural and economic systems affected by precipitation difficult to manage. Time series analysis of Philippine rainfall pattern has been previously done, but there is no study investigating its probability distribution. Modeling the Philippine rainfall using probability distributions is essential, especially in managing risks and designing insurance products. Here, daily and cumulative rainfall data (January 1961 - August 2016) from 28 PAGASA weather stations are fitted to probability distributions. Moreover, the fitted distributions are examined for invariance under subsets of the rainfall data set. We observe that the Gamma distribution is a suitable fit for the daily up to the ten-day cumulative rainfall data. Our results can be used in agriculture, especially in forecasting claims in weather index-based insurance.

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