Clouds and the Earth's Radiant Energy System (CERES): An Earth Observing System Experiment

Wielicki, Bruce A.; Barkstrom, Bruce R.; Harrison, Edwin F.; Lee, Robert B.; Smith, G. Louis; Cooper, John E.

doi:10.1175/1520-0477(1996)077<0853:catere>2.0.co;2

Cited by 1,668 publications

(1,287 citation statements)

References 27 publications

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“…Over the study period, our method estimates the global land surface mean total solar radiation to be 182.5 W·m −2 , which is 33 W·m −2 lower than the NCEP data, but close to other satellite-based estimates such as the International Satellite Cloud Climatology Project (ISCCP) data [9] and the CERES data [51,54] which are 188.8 and 180.1 W·m −2 , respectively. For E b and E d , comparison shows that our estimated E b and E d are 39.2 W·m −2 lower and 6.6 W·m −2 higher than NCEP data respectively, which is consistent with site-level conclusions.…”

Section: Global-scale Comparisonsupporting

confidence: 62%

“…It is part of NASA's Earth Observation System (EOS) and provides long-term, accurate estimation of the radiative fluxes within the Earth atmosphere. The algorithms of CERES mainly follow the previous project ERBE and uses the instrument-derived multiple satellite-based parameters, but combine more-frequent satellite data and more-detailed cloud information from other EOS instruments such as MODIS [51]. Specifically, we collect the recently released the global daily downward solar radiation at 1-degree resolution (SYN1deg) from CERES to compare with our estimates.…”

Section: Evaluating the Modis Estimatesmentioning

confidence: 99%

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An Efficient Method of Estimating Downward Solar Radiation Based on the MODIS Observations for the Use of Land Surface Modeling

Chen

Zhuang

2014

Remote Sensing

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Solar radiation is a critical variable in global change sciences. While most of the current global datasets provide only the total downward solar radiation, we aim to develop a method to estimate the downward global land surface solar radiation and its partitioned direct and diffuse components, which provide the necessary key meteorological inputs for most land surface models. We developed a simple satellite-based computing scheme to enable fast and reliable estimation of these variables. The global Moderate Resolution Imaging Spectroradiometer (MODIS) products at 1° spatial resolution for the period 2003-2011 were used as the forcing data. Evaluations at Baseline Surface Radiation Network (BSRN) sites show good agreement between the estimated radiation and ground-based observations. At all the 48 BSRN sites, the RMSE between the observations and estimations are 34.59, 41.98 and 28.06 W·m −2 for total, direct and diffuse solar radiation, respectively. Our estimations tend to slightly overestimate the total and diffuse but underestimate the direct solar radiation. The errors may be related to the simple model structure and error of the input data. Our estimation is also comparable to the Clouds and Earth's Radiant Energy System (CERES) data while shows notable improvement over the widely used National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data. Using our MODIS-based datasets of total solar radiation OPEN ACCESS Remote Sens. 2014, 6 7137 and its partitioned components to drive land surface models should improve simulations of global dynamics of water, carbon and climate.

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Section: Global-scale Comparisonsupporting

confidence: 62%

Section: Evaluating the Modis Estimatesmentioning

confidence: 99%

An Efficient Method of Estimating Downward Solar Radiation Based on the MODIS Observations for the Use of Land Surface Modeling

Chen

Zhuang

2014

Remote Sensing

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“…For both approaches, environmental variables obtained for multi-year time series were collapsed to monthly means of daily values before calculation of PET, PET was scaled from daily to monthly values, then summed to obtain annual PET. To test the sensitivity of our results to driving data, we used two radiation data sets: mean monthly values from the NASA/CERES energy-balanced and filled surface radiation budget, version 2.8, over the years 2001-2014 38 , and mean monthly values from the NASA/GEWEX surface radiation budget version 3.0 over the years 1984-2007 39 . We obtained mean monthly values of air temperature and vapour pressure from the CRU TS3.13 data set, a gridded climatology at 0.5° resolution interpolated from weather station measurements, which we averaged over the period 1961-2001, the period of maximum weather station coverage 40 .…”

Section: Methodsmentioning

confidence: 99%

Water balance creates a threshold in soil pH at the global scale

Slessarev

Lin

Bingham

et al. 2016

Nature

437

255

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Soil pH regulates the capacity of soils to store and supply nutrients, and thus contributes substantially to controlling productivity in terrestrial ecosystems 1 . However, soil pH is not an independent regulator of soil fertility-rather, it is ultimately controlled by environmental forcing. In particular, small changes in water balance cause a steep transition from alkaline to acid soils across natural climate gradients 2,3 . Although the processes governing this threshold in soil pH are well understood, the threshold has not been quantified at the global scale, where the influence of climate may be confounded by the effects of topography and mineralogy. Here we evaluate the global relationship between water balance and soil pH by extracting a spatially random sample (n = 20,000) from an extensive compilation of 60,291 soil pH measurements. We show that there is an abrupt transition from alkaline to acid soil pH that occurs at the point where mean annual precipitation begins to exceed mean annual potential evapotranspiration. We evaluate deviations from this global pattern, showing that they may result from seasonality, climate history, erosion and mineralogy. These results demonstrate that climate creates a nonlinear pattern in soil solution chemistry at the global scale; they also reveal conditions under which soils maintain pH out of equilibrium with modern climate.Climate controls many aspects of soil chemistry, affecting soil pH (ref. 4). Alkaline soils are known to be common in arid climates, while acid soils are known to be common in humid climates 1 . Surprisingly, however, the global-scale mechanisms governing this pattern remain broadly defined, and untested by direct observation. What are the dominant chemical equilibria that constrain soil pH? What aspect of climate defines the transition between alkaline and acid soils, and is the transition linear? The answers to these questions are fundamental to understanding soil development and surface geochemistry at the global scale. Furthermore, achieving this understanding may prove essential for representing soils in models of the terrestrial biosphere, given that soil pH controls many aspects of soil fertility 5,6 . Here we illustrate that simple geochemical and hydrological concepts can be used to build a mechanistic understanding of soil pH at the global scale.Interpretations of acid-titration experiments indicate that the soil pH is typically most strongly buffered by equilibrium with two secondary minerals: calcite (CaCO 3 ), or gibbsite (Al(OH) 3 ) 7,8 Fig. 1).Local studies of climate gradients have shown that the relative importance of these two buffers is determined by leaching, which removes Ca 2+ from the soil 2,3,8,9 . In climates where evaporative demand exceeds precipitation, leaching rates are low, and dissolved Ca 2+ accumulates as CaCO 3 -buffering soil pH near 8.2 (ref. 4). Conversely, in climates where precipitation exceeds evaporative demand, water leaches through the soil, removing Ca 2+ and allowing accumulation of relatively immobile...

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“…Temperature was obtained from the CRUNCEP version 6.1 dataset (Viovy, 2015), which is a merged product of Climate Research Unit (CRU) TS.3.23 observation-based monthly climatology (New et al, 2000) and the National Center for Environmental Prediction (NCEP) 6-hourly reanalysis data (Kalnay et al, 1996). Net radiation is based on radiation fluxes of the SYN1deg Ed3A data product of the Clouds and the Earth's Radiant Energy Systems (CERES) program of the US National Aeronautics and Space Administration (NASA) (Wielicki et al, 1996).…”

Section: Input Datamentioning

confidence: 99%

Understanding terrestrial water storage variations in northern latitudes across scales

Trautmann

Koirala

Eicker

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual timescales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snowpacks, soil moisture, and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid-to high latitudes.To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological spatio-temporal patterns and was used to assess the relative contributions of solid (snowpack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales.Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across all spatial scales in the northern mid-to high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages at all spatial scales. The relative contribution of snow to inter-annual TWS variations, though, increases when the spatial domain over which the storages are averaged becomes larger. This is due to a stronger spatial coherence of snow dynamics that are mainly driven by temperature, as opposed to spatially more heterogeneous liquid water anomalies, that cancel out when averaged over a larger spatial domain. The findings first highlight the effectiveness of our model-data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale-dependent. In particular, they seem to be not merely driven by snow variability, but rather are determined by liquid water storages on interannual timescales. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short-and long-term variability of water resources.

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Clouds and the Earth's Radiant Energy System (CERES): An Earth Observing System Experiment

Cited by 1,668 publications

References 27 publications

An Efficient Method of Estimating Downward Solar Radiation Based on the MODIS Observations for the Use of Land Surface Modeling

An Efficient Method of Estimating Downward Solar Radiation Based on the MODIS Observations for the Use of Land Surface Modeling

Water balance creates a threshold in soil pH at the global scale

Understanding terrestrial water storage variations in northern latitudes across scales

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