Multi-source quantification of precipitation in the global water cycle

2020 ◽  
Author(s):  
Mijael Rodrigo Vargas Godoy ◽  
Rajani Kumar Pradhan ◽  
Shailendra Pratap ◽  
Akif Rahim ◽  
Yannis Markonis
Keyword(s):  
Remote Sensing ◽  
Water Cycle ◽  
Remote Sensing Data ◽  
Time Frame ◽  
Global Scale ◽  
Global Water Cycle ◽  
Data Products ◽  
Surrounding Areas ◽  
Global Precipitation ◽  
Global Water

<p>The knowledge of global precipitation is of crucial importance to the study of climate dynamics and the global water cycle in general. Although global precipitation climatologies have existed for some time, and their understanding has improved dramatically due to the vast amount of different data sources, their information has not been comprehensive enough due to precipitation spatial-temporal variability. Thus, ground station reports are, in some cases, not representative of the surrounding areas. Remote sensing data and model simulations complemented the traditional surface measurements and offered unprecedented coverage on a global scale. It is important to note that satellite data records are now of sufficient time frame lengths and with methods “mature” enough to develop meaningful precipitation climatologies that are able to provide information on precipitation patterns and intensities on a global scale. While data (and in some cases exploration/visualization tools as well) are widely available, each dataset comes with different spatial resolution, temporal resolution, and biases.</p><p>Consequently, this unique opportunity to obtain a robust quantification of global precipitation has been hindered by the uncertainty, already revealed in the first attempts of the unification of different data products. Herein, we present a multi-source quantification of global precipitation, focusing on the description of the underlying uncertainties. Our approach combines station (CRU, GHCN-M, PRECL, UDEL, and CPC Global), remote sensing (PERSIANN, PERSIANN-CCS, PERSIANN-CDR, GPCP, GPCP_PEN_v2.2, CMAP, and CPC-Global) and reanalysis (NCEP1, NCEP2, and 20CRv2) data products, providing an updated overview of the role of precipitation in global water cycle.</p>

scholarly journals Remote-sensing-based estimates of the fundamental global water cycle: Annual cycle

2005 ◽  
Vol 110 (D22) ◽  
Author(s):  
Vikram M. Mehta ◽  
Andrew J. DeCandis ◽  
Amita V. Mehta
Keyword(s):  
Remote Sensing ◽  
Annual Cycle ◽  
Water Cycle ◽  
Global Water Cycle ◽  
Global Water

scholarly journals Global water cycle and remote sensing big data: overview, challenge, and opportunities

2018 ◽  
Vol 2 (3) ◽  
pp. 282-297 ◽  
Author(s):  
Yaokui Cui ◽  
Xi Chen ◽  
Jinyu Gao ◽  
Binyan Yan ◽  
Guoqiang Tang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Big Data ◽  
Water Cycle ◽  
Global Water Cycle ◽  
Global Water

scholarly journals The MUSICA MetOp/IASI H<sub>2</sub>O and δD products: characterisation and long-term comparison to NDACC/FTIR data

2014 ◽  
Vol 7 (4) ◽  
pp. 3915-3952 ◽  
Author(s):  
A. Wiegele ◽  
M. Schneider ◽  
F. Hase ◽  
S. Barthlott ◽  
O. E. García ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapour ◽  
Water Cycle ◽  
Remote Sensing Data ◽  
Global Scale ◽  
Atmospheric Composition ◽  
Complex Nature ◽  
Quality Assessment Study ◽  
Complementary Value

Abstract. Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground- and space-based remote sensing as well as in-situ datasets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing dataset is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale. Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, mid-latitudes, and arctic) and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remote sensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier-Transform InfraRed) remote sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change). We confirm that IASI is able to measure tropospheric H2O profiles with a vertical resolution of about 4 km and a random error of about 10%. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H2O observations. Our study is both, a theoretical and an empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes.

scholarly journals Can we trust remote sensing ET products over Africa?

2019 ◽  
Author(s):  
Imeshi Weerasinghe ◽  
Ann van Griensven ◽  
Wim Bastiaanssen ◽  
Marloes Mul ◽  
Li Jia
Keyword(s):  
Remote Sensing ◽  
Water Cycle ◽  
Temporal Distribution ◽  
Remote Sensing Data ◽  
Global Scale ◽  
Data Availability ◽  
Systematic Evaluation ◽  
Basin Scale ◽  
Long Term Trends

Abstract. Evapotranspiration (ET) is one of the most important components in the water cycle. However, there are relatively few direct measurements of ET (using flux towers), whereas various disciplines ranging from hydrology to agricultural and climate sciences, require information on the spatial and temporal distribution of ET at regional and global scale. Due to limited data availability, attention has turned toward satellite based products to fill observational gaps. Various remote sensing data products have been developed, providing a large range of ET estimations. Across Africa only a limited number of flux towers are available which are insufficient for systematic evaluation of remotely sensed (RS) derived ET products. Thus we propose a methodology for evaluating RS derived ET data at the basin scale using a general water balance (WB) approach, where ET is equal to precipitation minus discharge for long-term annual averages. Firstly, RS ET products are compared with WB inferred ET for basins without long-term trends present. The RS products are then assessed according to spatial characteristics through analysing two land cover elements across Africa, irrigated areas and water bodies. A cluster analysis is also conducted to identify similarities between individual ET products. Finally, the RS products are evaluated against the Budyko equation. The results show that CMRSET, SSEBop and WaPOR rank highest in terms of estimation of long-term annual average mean ET across basins with low biases. Along with ETMonitor, the same three products rank highest in spatial distribution of ET patterns across Africa. GLEAM and MOD16 consistently rank the lowest in most criteria evaluation. Many of the products analysed in this study can be trusted depending on the study under question, keeping in mind some of these products have large biases in magnitude estimation. However our recommendation would be the three highest ranked products being CMRSET, SSEBop and WaPOR.

An Integrative Information Aqueduct to Close the Gaps between Global Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources (iAqueduct)

2020 ◽  
Author(s):  
yijian zeng ◽  
Keyword(s):  
Soil Moisture ◽  
Water Resources ◽  
Sustainable Management ◽  
Water Cycle ◽  
Satellite Observation ◽  
Global Scale ◽  
Multiple Sources ◽  
Management Level ◽  
Global Water Cycle ◽  
Global Water

&lt;p&gt;In the past decades, space-based Earth Observations (EO) have been rapidly advancing in monitoring the global water cycle, in particular for the variables related to precipitation, evapotranspiration and soil moisture, often at (tens of) kilometre scales. Whilst these data are highly effective to characterise water cycle variation at regional to global scale, they are less suitable for sustainable management of water resource, which needs more detailed information at local and field scale due to inhomogeneous characteristics of the soil and vegetation. To effectively exploit existing knowledge at different scales we thus need to answer the following questions: How to downscale the global water cycle products to local scale using multiple sources/scales of EO data? How to explore and apply the downscaled information at the management level for understanding soil-water-vegetation-energy processes? And how to use such fine-scale information to improve the management of soil and water resources? An integrative information aqueduct (iAqueduct) is proposed to close the gaps between global satellite observation of water cycle and local needs of information for sustainable management of water resources. iAqueduct aims to accomplish its goals by combining Copernicus satellite data (with intermediate resolutions) with high resolution Unmanned Aerial System (UAS) and in-situ observations to develop scaling functions for soil properties and soil moisture and evapotranspiration at high spatial resolution scales.&lt;/p&gt;

scholarly journals The MUSICA MetOp/IASI H<sub>2</sub>O and δD products: characterisation and long-term comparison to NDACC/FTIR data

2014 ◽  
Vol 7 (8) ◽  
pp. 2719-2732 ◽  
Author(s):  
A. Wiegele ◽  
M. Schneider ◽  
F. Hase ◽  
S. Barthlott ◽  
O. E. García ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapour ◽  
Water Cycle ◽  
Remote Sensing Data ◽  
Global Scale ◽  
Atmospheric Composition ◽  
Complex Nature ◽  
Data Set ◽  
Sensing Data ◽  
Complementary Value

Abstract. Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground- and space-based remote sensing as well as in situ data sets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing data set is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale. Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, midlatitudes, and Arctic), and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remote-sensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier Transform InfraRed) remote-sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change). We confirm that IASI is able to measure tropospheric H2O profiles with a vertical resolution of about 4 km and a random error of about 10%. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H2O observations. Our study presents theoretical and empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes.

scholarly journals Editorial for Special Issue “Remote Sensing Water Cycle: Theory, Sensors, Data, and Applications”

2019 ◽  
Vol 11 (10) ◽  
pp. 1210 ◽  
Author(s):  
Wei Wan ◽  
Hongjie Xie ◽  
Emad Hasan ◽  
Yang Hong
Keyword(s):  
Remote Sensing ◽  
Water Cycle ◽  
Special Issue ◽  
Global Water Cycle ◽  
Global Water

Global water cycle dynamics involve the exchange of water and energy matter among the atmosphere, hydrosphere, geosphere, cryosphere, and biosphere [...]

Assessing a Satellite-Era Perspective of the Global Water Cycle

2007 ◽  
Vol 20 (7) ◽  
pp. 1316-1338 ◽  
Author(s):  
C. Adam Schlosser ◽  
Paul R. Houser
Keyword(s):  
General Circulation ◽  
Water Cycle ◽  
Precipitable Water ◽  
Global Ocean ◽  
Mean Annual Precipitation ◽  
Near Surface ◽  
Global Water Cycle ◽  
Order Of Magnitude ◽  
Global Precipitation ◽  
Global Water

Abstract The capability of a global data compilation, largely satellite based, is assessed to depict the global atmospheric water cycle’s mean state and variability. Monthly global precipitation estimates from the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) span from 1979 to 1999. Monthly global Special Sensor Microwave Imager (SSM/I)-based bulk aerodynamic ocean evaporation estimates span from June 1987 to December 1999. Global terrestrial evapotranspiration rates are estimated over a multidecade period (1975–99) using a global land model simulation forced by bias-corrected reanalysis data. Monthly total precipitable water (TPW) from the NASA Global Water Vapor Project (NVAP) spans from 1988 to 1999. The averaged annual global precipitation (P) and evaporation (E) estimates are out of balance by 5% or 24 000 (metric) gigatons (Gton) of water, which exceeds the uncertainty of global mean annual precipitation (∼±1%). For any given year, the annual flux imbalance can be on the order of 10% (48 000 Gton of water). However, observed global TPW interannual variations suggest a water flux imbalance on the order of 0.01% (48 Gton of water)—a finding consistent with a general circulation model (GCM) simulation. Variations in observationally based global P and E rates show weak monthly and interannual consistency, and depending on the choice of ocean evaporation data, the mean annual cycle of global E − P can be up to 5 times larger to that of TPW. The global ocean annual evaporation rates have as much as a ∼1% yr−1 increase during the period analyzed (1988–99), which is consistent in sign with most transient CO2 GCM simulations, but at least an order of magnitude larger. The ocean evaporation trends are driven by trends in SSM/I-retrieved near-surface atmospheric humidity and wind speed, and the largest year-to-year changes are coincident with transitions in the SSM/I fleet. In light of (potential) global water cycle changes in GCM projections, the ability to consistently detect or verify these changes in nature rests upon one or more of the following: quantification of global evaporation uncertainty, at least a twofold improvement in consistency between the observationally based global precipitation and evaporation variations, a two order of magnitude rectification between annual variations of E − P and precipitable water as well as substantial improvements in the consistency of their seasonal cycles, a critical reevaluation of intersatellite calibration for the relevant geophysical quantities used for ocean evaporation estimates, and the continuation of a dedicated calibration in this regard for future satellite transitions.

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