scholarly journals Amazonian terrestrial water balance inferred from satellite-derived water vapor isotopes

2021 ◽  
Author(s):  
Mingjie Shi ◽  
John Worden ◽  
Adriana Bailey ◽  
David Noone ◽  
Camille Risi ◽  
...  
Keyword(s):  
Water Vapor ◽  
Water Balance ◽  
Temporal Distribution ◽  
Satellite Observations ◽  
Amazon Forest ◽  
Tightly Coupled ◽  
Terrestrial Water ◽  
Spatio Temporal ◽  
The Difference ◽  
Variable Bias

Abstract The evolution of the Amazon forest is tightly coupled to its terrestrial water balance (evapotranspiration minus precipitation, or ET-P), as an increase in ET-P reduces soil moisture, increasing water stress. However, large differences of ~ 50% between current monthly estimates of ET-P make it challenging to confidently quantify its spatio-temporal distribution and evolution. Here, we show that new satellite observations of the HDO/H2O ratio of water vapor, spanning 2003 to 2020, constrain estimates of the Amazon water balance with monthly precision of ~ 20%. The HDO/H2O ratio of water vapor is sensitive to the difference between ET and P, rather than to either flux alone, because lighter isotopes preferentially evaporate and heavier isotopes preferentially condense. Consequently, variable bias and sensitivity errors that result from combining different ET and precipitation products are minimized with this proxy. Our analysis demonstrates these data can quantify the spatial patterns of Amazon water balance from monthly to interannual time scales.

scholarly journals Spatio-Temporal Validation of AIRS CO2 Observations Using GAW, HIPPO and TCCON

2020 ◽  
Vol 12 (21) ◽  
pp. 3583
Author(s):  
Hui Yang ◽  
Gefei Feng ◽  
Ru Xiang ◽  
Yunjing Xu ◽  
Yong Qin ◽  
...  
Keyword(s):  
Co2 Concentration ◽  
Satellite Observations ◽  
Total Carbon ◽  
Near Surface ◽  
Temporal Validation ◽  
Satellite Sensors ◽  
Spatio Temporal ◽  
The Difference ◽  
Carbon Dioxide Co2

Carbon dioxide (CO2) is a significant atmospheric greenhouse gas and its concentrations can be observed by in situ surface stations, aircraft flights and satellite sensors. This paper investigated the ability of the CO2 satellite observations to monitor, analyze and predict the horizontal and vertical distribution of atmospheric CO2 concentration at global scales. CO2 observations retrieved by an Atmospheric Infrared Sounder (AIRS) were inter-compared with the Global Atmosphere Watch Program (GAW) and HIAPER Pole-to-Pole Observations (HIPPOs), with reference to the measurements obtained using high-resolution ground-based Fourier Transform Spectrometers (FTS) in the Total Carbon Column Observing Network (TCCON) from near-surface level to the mid-to-high troposphere. After vertically integrating the AIRS-retrieved values with the column averaging kernels of TCCON measurements, the AIRS observations are spatio-temporally compared with HIPPO-integrated profiles in the mid-to-high troposphere. Five selected GAW stations are used for comparisons with TCCON sites near the surface of the Earth. The results of AIRS, TCCON (5–6 km), GAW and TCCON (1 km) CO2 measurements from 2007 to 2013 are compared, analyzed and discussed at their respective altitudes. The outcomes indicate that the difference of about 3.0 ppmv between AIRS and GAW or other highly accurate in situ surface measurements is mainly due to the different vertical altitudes, rather than the errors in the AIRS. The study reported here also explores the potential of AIRS satellite observations for analyzing the spatial distribution and seasonal variation of CO2 concentration at global scales.

A scanning Raman lidar for observing the spatio-temporal distribution of water vapor

2016 ◽  
Vol 150-151 ◽  
pp. 21-30 ◽  
Author(s):  
Masanori Yabuki ◽  
Makoto Matsuda ◽  
Takuji Nakamura ◽  
Taiichi Hayashi ◽  
Toshitaka Tsuda
Keyword(s):  
Water Vapor ◽  
Temporal Distribution ◽  
Raman Lidar ◽  
Spatio Temporal

Quantitative study of atmospheric rivers in the Indian subcontinent

2021 ◽  
Author(s):  
Rosa V. Lyngwa ◽  
Munir Ahmad Nayak
Keyword(s):  
Water Vapor ◽  
Indian Subcontinent ◽  
Temporal Distribution ◽  
Large Degree ◽  
Water Vapor Transport ◽  
Boreal Summer ◽  
Atmospheric Rivers ◽  
Wind Speeds ◽  
Minimum Requirements ◽  
Spatio Temporal

<p>The principal sources of freshwater in India include precipitation, glaciers, and snowmelt. The former dominates the country’s annual river water contribution, which is important for agriculture and livelihood of the residents, and the latter two sources contribute at a much lower fraction in comparison to precipitation to even meet the minimum requirements. However, there is a large degree of variations in their spatio-temporal distribution throughout the country. India receives a major portion of its annual precipitation during the boreal summer (June – September). The well-known but relatively unexplored contributors to precipitation in India are atmospheric rivers (ARs). This study aims to understand the main climatological and dynamical differences between the Indian summer monsoon (ISM) and ARs in boreal summer. Zonal (‘u’) and meridional (‘v’) wind speeds, integrated water vapor transport (IVT), and integrated water vapor (IWV) are used to identify distinct features in ARs in the Indian sub-continent that can be used to distinguish them from ISM. The major differences between the two synoptic features were found in the increased zonal wind speed and moisture inputs during AR events, which often result in extreme precipitation and floods. Besides understanding them, the identification of ARs in this region and accounting for their existential contribution to moisture during peak rainfall seasons is critical for further hydrological impacts studies.</p>

scholarly journals Activity time series of old stars from late F to early K

2019 ◽  
Vol 632 ◽  
pp. A81 ◽  
Author(s):  
N. Meunier ◽  
A.-M. Lagrange ◽  
S. Cuzacq
Keyword(s):  
Time Series ◽  
Temporal Distribution ◽  
Active Regions ◽  
Activity Level ◽  
Large Set ◽  
Detection Rates ◽  
Chromospheric Emission ◽  
Spatio Temporal ◽  
The Difference ◽  
Geometrical Effects

Context. Inhibition of the convective blueshift in active regions is a major contribution to the radial velocity (RV) variations, at least for solar-like stars. A common technique to correct for this component is to model the RV as a linear function of chromospheric emission, because both are strongly correlated with the coverage by plages. Aims. This correction, although efficient, is not perfect: the aim of the present study is to understand the limits of this correction and to improve it. Methods. We investigate these questions by analysing a large set of synthetic time series corresponding to old main sequence F6-K4 stars modelled using a consistent set of parameters. We focus here on the analysis of the correlation between time series, in particular between RV (variability due to different processes) and chromospheric emission on different timescales. We also study the temporal variation for each time series. Results. We find that inclination strongly impacts these correlations, as well as the presence of additional signals (in particular granulation and supergranulation). Although RV and log R′HK are often well correlated, a combination of geometrical effects (butterfly diagrams related to dynamo processes and inclination) and activity level variations over time create an hysteresis pattern during the cycle, which produces a departure from an excellent correlation: for a given activity level, the RV is higher or lower during the ascending phase compared to the descending phase of the cycle depending on inclination, with a reversal for inclinations about 60° from pole-on. We find that this hysteresis is also observed for the Sun, as well as for other stars. This property is due to the spatio-temporal distribution of the activity pattern (and therefore to the dynamo processes) and to the difference in projection effects of the RV and chromospheric emission. Conclusions. These results allow us to propose a new method which significantly improves the correction for long timescales (fraction of the cycle), and could be crucial to improving detection rates of planets in the habitable zone around F6-K4 stars.

scholarly journals Three approaches to the assessment of spatio-temporal distribution of the water balance: the case of the Cuitzeo basin, Michoacán, Mexico

2012 ◽  
pp. 34
Author(s):  
Alfredo Amador García ◽  
Erna Granados López ◽  
Manuel E. Mendoza
Keyword(s):  
Water Balance ◽  
Temporal Distribution ◽  
El Sistema ◽  
Spatio Temporal

La distribución espacial de la energía y los flujos de ciclo hidrológico en forma de vapor (evapotranspiración), escurrimiento e infiltración en una región, son una función de las características climáticas (precipitación, temperatura y evaporación) y del paisaje (relieve, suelo y cobertura) de un área y constituyen el llamado ciclo hidrológico. El modelo general de evaluación de cada uno de los compartimentos y flujos es el balance hídrico. Los métodos desarrollados para calcular el balance hídrico de una región toman como base el enfoque de transferencia de masa o el de transferencia de energía. Este trabajo se planteó como objetivo calcular, comparar y evaluar tres aproximaciones en la estimación del balance hídrico regional espacialmente distribuido en cuencas sin datos de aforos. El modelamiento espacial de las variables hidrometeorológicas se efectuó en el sistema de información geográfica ArcView 3.2, y el modelamiento de los del escurrimiento se realizó con el sistema HEC versión 3.1.0. La primera aproximación está basada en el análisis de la información registrada en las estaciones meteorológicas disponibles, estimación puntual del balance hídrico mensual conforme al método de Thornthwaite y Mather y de polígonos de Thiessen; la segunda, en el cálculo y distribución de los parámetros para la aplicación del Método de Thornthwaite y Mather; finalmente la tercera aproximación se basó en el uso de la ecuación de FAO – Penman. Se escogió a la cuenca del lago de Cuitzeo como área de aplicación de los modelos. Destaca que mediante el resultado de la 3ª aproximación el volumen anual promedio de escurrimientos corresponde a 229.05 hm3. Dicho volumen es apenas 8.5 hm3 inferior al estimado como necesario para mantener 1 m de profundidad en la extensión del cuerpo de agua del lago de Cuitzeo. Esta diferencia representa en esa misma extensión una eventual fluctuación de 3 cm en el nivel medio del espejo del lago. El modelo HEC representa una alternativa para el modelamiento de la cuenca ya que demanda relativamente de pocos insumos, los principales (T, PP, PET, ET) obtenibles o espacializables mediante alguna de las aproximaciones presentadas aquí.

scholarly journals Spatio-temporal approach to moving window block kriging of satellite data v1.0

2017 ◽  
Vol 10 (2) ◽  
pp. 709-720 ◽  
Author(s):  
Jovan M. Tadić ◽  
Xuemei Qiu ◽  
Scot Miller ◽  
Anna M. Michalak
Keyword(s):  
Global Scale ◽  
Variable Density ◽  
Satellite Observations ◽  
Moving Window ◽  
Block Kriging ◽  
Temporal Correlations ◽  
Environmental Properties ◽  
Level 3 ◽  
Spatio Temporal ◽  
The Difference

Abstract. Numerous existing satellites observe physical or environmental properties of the Earth system. Many of these satellites provide global-scale observations, but these observations are often sparse and noisy. By contrast, contiguous, global maps are often most useful to the scientific community (i.e., Level 3 products). We develop a spatio-temporal moving window block kriging method to create contiguous maps from sparse and/or noisy satellite observations. This approach exhibits several advantages over existing methods: (1) it allows for flexibility in setting the spatial resolution of the Level 3 map, (2) it is applicable to observations with variable density, (3) it produces a rigorous uncertainty estimate, (4) it exploits both spatial and temporal correlations in the data, and (5) it facilitates estimation in real time. Moreover, this approach only requires the assumption that the observable quantity exhibits spatial and temporal correlations that are inferable from the data. We test this method by creating Level 3 products from satellite observations of CO2 (XCO2) from the Greenhouse Gases Observing Satellite (GOSAT), CH4 (XCH4) from the Infrared Atmospheric Sounding Interferometer (IASI) and solar-induced chlorophyll fluorescence (SIF) from the Global Ozone Monitoring Experiment-2 (GOME-2). We evaluate and analyze the difference in performance of spatio-temporal vs. recently developed spatial kriging methods.

scholarly journals Spatio-temporal approach to moving window block kriging of satellite data

2016 ◽  
Author(s):  
Jovan M. Tadić ◽  
Xuemei Qiu ◽  
Scot Miller ◽  
Anna M. Michalak
Keyword(s):  
Global Scale ◽  
Variable Density ◽  
Satellite Observations ◽  
Moving Window ◽  
Block Kriging ◽  
Temporal Correlations ◽  
Environmental Properties ◽  
Level 3 ◽  
Spatio Temporal ◽  
The Difference

Abstract. Numerous existing satellites observe physical or environmental properties of the Earth system. Many of these satellites provide global-scale observations, but these observations are often sparse and noisy. By contrast, contiguous, global maps are often most useful to the scientific community (i.e., level 3 products). We develop a spatiotemporal moving window block kriging method to create contiguous maps from sparse and/or noisy satellite observations. This approach exhibits several advantages over existing methods: 1) it allows for flexibility in setting the spatial resolution of the level 3 map, 2) it is applicable to observations with variable density, 3) it produces a rigorous uncertainty estimate, 4) it exploits both spatial and temporal correlations in the data, and 5) it facilitates estimation in real time. Moreover, this approach only requires a limited number of assumptions – that the observable quantity exhibits spatial and temporal correlations that are inferable from the data. We test this method by creating Level 3 products from satellite observations of CO2 (XCO2) from GOSAT, CH4 (XCH4) from IASI and solar-induced chlorophyll fluorescence (SIF) from GOME-2. We evaluate and analyze the difference in performance of spatio-temporal vs. recently developed spatial kriging methods.

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