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

Author(s):  
Imeshi Weerasinghe ◽  
Ann van Griensven ◽  
Wim Bastiaanssen ◽  
Marloes Mul ◽  
Li Jia

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.

2020 ◽  
Vol 24 (3) ◽  
pp. 1565-1586 ◽  
Author(s):  
Imeshi Weerasinghe ◽  
Wim Bastiaanssen ◽  
Marloes Mul ◽  
Li Jia ◽  
Ann van Griensven

Abstract. Evapotranspiration (ET) is one of the most important components in the water cycle. However, there are relatively few direct measurements of ET available (e.g. using flux towers). Nevertheless, various disciplines, ranging from hydrology to agricultural and climate sciences, require information on the spatial and temporal distribution of ET at regional and global scales. Due to the limited data availability, attention has turned toward satellite-based products to fill observational gaps. Various data products, including remote sensing (RS) products, have been developed and provide a large range of ET estimations. Across Africa, only a limited number of flux towers are available; hence, they are insufficient for the systematic evaluation of the available ET products. Thus, in this study, we conduct a methodological evaluation of nine existing RS-derived ET products as well as other available ET products in order to evaluate their reliability at the basin scale. A general water balance (WB) approach is used, where ET is equal to precipitation minus discharge for long-term averages. Firstly, ET products are compared with WB-inferred ET (ETWB) for basins that do not show long-term trends. The ET products and the calculated ETWB are then evaluated against the Budyko equation, which is used as a reference condition. The spatial characteristics of the ET products are finally assessed via the analysis of selected land cover elements across Africa: forests, irrigated areas and water bodies. Additionally, a cluster analysis is conducted to identify similarities between individual ET products. The results show that CMRSET, SSEBop and WaPOR rank highest in terms of the estimation of the long-term average mean ET across basins, with low biases and good spatial variability across Africa. GLEAM consistently ranks lowest in most evaluation criteria, although it has the longest available time period. Each product shows specific advantages and disadvantages. Depending on the study in question, at least one product should be suitable for a particular requirement. The reader should bear in mind that many products suffer from a large bias. Based on the evaluation criteria in this study, the three highest ranked products, CMRSET, SSEBop and WaPOR, would suit many users' needs due to the low biases and good spatial variability across Africa.


2014 ◽  
Vol 7 (4) ◽  
pp. 3915-3952 ◽  
Author(s):  
A. Wiegele ◽  
M. Schneider ◽  
F. Hase ◽  
S. Barthlott ◽  
O. E. García ◽  
...  

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.


2016 ◽  
Vol 9 (7) ◽  
pp. 2845-2875 ◽  
Author(s):  
Matthias Schneider ◽  
Andreas Wiegele ◽  
Sabine Barthlott ◽  
Yenny González ◽  
Emanuel Christner ◽  
...  

Abstract. In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.


2020 ◽  
Author(s):  
Nan Jiang ◽  
Yan Xu ◽  
Tianhe Xu

<p>Precipitable water vapor (PWV) is an important parameter reflecting the amount of solid water in the atmosphere, which is widely utilized in the studies of numerical weather prediction (NWP) and climate change. The microwave radiance measurements made by the space-based remote sensing satellites give us the opportunity to make the climate studies on a global scale. So far, PWV retrieval over the ocean has a long data record and the technology is very mature, but in the case of PWV retrieval over land, it is more challenging to isolate the atmospheric signals from the varied surface signals. In this study, we will apply a new retrieval method over land based on the dual-polarized difference (vertical and horizontal) at 19 GHz and 23 GHz using the brightness temperatures from the Global Change Observation Mission-Water (GCOM-W)/Advanced Microwave Scanning Radiometer 2 (AMSR2). We found polarization difference in brightness temperatures has an exponential relation on the amount of PWV. The validation results of the PWV retrieval from the ground-based GNSS stations show that the proposed method has a mean accuracy of 3.9 mm. Thus, the proposed method can give a possibility to improve the accuracy of data assimilation in the NWP applications and is useful for the studies of global climate change with the long-term data records.</p>


2016 ◽  
Vol 40 (2) ◽  
pp. 322-351 ◽  
Author(s):  
Jadunandan Dash ◽  
Booker O. Ogutu

Since the launch of the first Landsat satellite in the early 1970s, the field of space-borne optical remote sensing has made significant progress. Advances have been made in all aspects of optical remote sensing data, including improved spatial, temporal, spectral and radiometric resolutions, which have increased the uptake of these data by wider scientific communities. Flagship satellite missions such as NASA’s Terra and Aqua and ESA’s Envisat with their high temporal (<3days) and spectral (15–36 bands) resolutions opened new opportunities for routine monitoring of various aspects of terrestrial ecosystems at the global scale and have provided greater understanding of critical biophysical processes in the terrestrial ecosystem. The launch of new satellite sensors such as Landsat 8 and the European Space Agency’s Copernicus Sentinel missions (e.g. Sentinel 2 with improved spatial resolution (10–60 m) and potential revisit time of five days) is set to revolutionise the availability and use of remote sensing data in global terrestrial ecosystem monitoring. Furthermore, the recent move towards use of constellations of nanosatellites (e.g. the Flock missions by Planet Labs) to collect on-demand high spatial and temporal resolution optical remote sensing data would enable uptake of these data for operational monitoring. As a result of increase in data availability, optical remote sensing data are now increasingly used to support a number of operational services (e.g. land monitoring, atmosphere monitoring and climate change studies). However, many challenges still remain in exploiting the growing volume of optical remote sensing data to monitor global terrestrial ecosystems. These challenges include ensuring the highest data quality both in terms of the sensitivity of sensors and the derived biophysical products, affordability and availability of the data and continuity of data acquisition. This review provides an overview of the developments in space-borne optical remote sensing in the past decade and discusses a selection of aspects of global terrestrial ecosystems where the data are currently used. It concludes by highlighting some of the challenges and opportunities of using optical remote sensing data in monitoring global terrestrial ecosystems.


2014 ◽  
Vol 7 (8) ◽  
pp. 2719-2732 ◽  
Author(s):  
A. Wiegele ◽  
M. Schneider ◽  
F. Hase ◽  
S. Barthlott ◽  
O. E. García ◽  
...  

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.


2016 ◽  
Author(s):  
M. Schneider ◽  
A. Wiegele ◽  
S. Barthlott ◽  
Y. González ◽  
E. Christner ◽  
...  

Abstract. Abstract. In the lower/middle troposphere H2O-δD pairs are good proxies for moisture pathways, however their observation is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating remote sensing with in-situ measurement techniques. The aim is to retrieve accurate tropospheric H2O-δD pairs from the middle infrared spectra measured from ground by the FTIR (Fourier Transform InfraRed) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper we review the MUSICA framework, present the final MUSICA products, and outline the NDACC/FTIR’s and METOP/IASI’s potential for observing accurate and consistent H2O-δD data pairs. First, we briefly resume the particularities of an H2O-δD pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in-situ profile references measured in the subtropics, between 0 and 7 km. Third, we empirically demonstrate that the calibrated remote sensing H2O-δD pairs can identify different lower/middle tropospheric moisture pathways and advert to the risk of misinterpretations caused by an incorrect processing of such remote sensing data. Fourth, we reveal that the different sensors (NDACC/FTIR instruments, MetOp/IASI-A, and MetOp/IASI-B) provide consistent H2O-δD pairs for very distinct atmospheric clear sky conditions. Fifth, we document the unique possibilities of the NDACC/FTIR instruments for providing long-term records (important for climatological studies) and of the MetOp/IASI sensors for observing diurnal signals on quasi global scale and with high horizontal resolution.


2020 ◽  
Author(s):  
Mijael Rodrigo Vargas Godoy ◽  
Rajani Kumar Pradhan ◽  
Shailendra Pratap ◽  
Akif Rahim ◽  
Yannis Markonis

&lt;p&gt;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 &amp;#8220;mature&amp;#8221; 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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;


Climate ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 122
Author(s):  
Gerald Krebs ◽  
David Camhy ◽  
Dirk Muschalla

While ongoing climate change is well documented, the impacts exhibit a substantial variability, both in direction and magnitude, visible even at regional and local scales. However, the knowledge of regional impacts is crucial for the design of mitigation and adaptation measures, particularly when changes in the hydrological cycle are concerned. In this paper, we present hydro-meteorological trends based on observations from a hydrological research basin in Eastern Austria between 1979 and 2019. The analyzed variables include air temperature, precipitation, and catchment runoff. Additionally, the number of wet days, trends for catchment evapotranspiration, and computed potential evapotranspiration were derived. Long-term trends were computed using a non-parametric Mann–Kendall test. The analysis shows that while mean annual temperatures were decreasing and annual temperature minima remained constant, annual maxima were rising. Long-term trends indicate a shift of precipitation to the summer, with minor variations observed for the remaining seasons and at an annual scale. Observed precipitation intensities mainly increased in spring and summer between 1979 and 2019. Catchment actual evapotranspiration, computed based on catchment precipitation and outflow, showed no significant trend for the observed time period, while potential evapotranspiration rates based on remote sensing data increased between 1981 and 2019.


2019 ◽  
Vol 76 (5) ◽  
pp. 831-846 ◽  
Author(s):  
C.J. Watras ◽  
D. Grande ◽  
A.W. Latzka ◽  
L.S. Tate

Atmospheric deposition is the principal source of mercury (Hg) to remote northern landscapes, but its fate depends on multiple factors and internal feedbacks. Here we document long-term trends and cycles of Hg in the air, precipitation, surface water, and fish of northern Wisconsin that span the past three decades, and we investigate relationships to atmospheric processes and other variables, especially the regional water cycle. Consistent with declining emission inventories, there was evidence of declining trends in these time series, but the time series for Hg in some lakes and most fish were dominated by a near-decadal oscillation that tracked the regional oscillation of water levels. Concentrations of important solutes (SO4, dissolved organic carbon) and the acid–base status of lake water also tracked water levels in ways that cannot be attributed to simple dilution or concentration. The explanatory mechanism is analogous to the “reservoir effect” wherein littoral sediments are periodically exposed and reflooded, altering the internal cycles of sulfur, carbon, and mercury. These climatically driven, near-decadal oscillations confound short or sparse time series and complicate relationships among Hg emissions, deposition, and bioaccumulation.


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