ESMDIS: Earth System Model Data Information System

2002 ◽  
Author(s):  
Yuechen Chi ◽  
C.R. Mechoso ◽  
M. Stonebraker ◽  
K. Sklower ◽  
R. Troy ◽  
...  
Keyword(s):  
Information System ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Model Data

scholarly journals Lossy compression of Earth system model data based on a hierarchical tensor with Adaptive-HGFDR (v1.0)

2021 ◽  
Vol 14 (2) ◽  
pp. 875-887
Author(s):  
Zhaoyuan Yu ◽  
Dongshuang Li ◽  
Zhengfang Zhang ◽  
Wen Luo ◽  
Yuan Liu ◽  
...  
Keyword(s):  
Field Data ◽  
Large Scale ◽  
Data Representation ◽  
Lossy Compression ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Model Data ◽  
Compression Method ◽  
Compression Parameter

Abstract. Lossy compression has been applied to the data compression of large-scale Earth system model data (ESMD) due to its advantages of a high compression ratio. However, few lossy compression methods consider both global and local multidimensional coupling correlations, which could lead to information loss in data approximation of lossy compression. Here, an adaptive lossy compression method, adaptive hierarchical geospatial field data representation (Adaptive-HGFDR), is developed based on the foundation of a stream compression method for geospatial data called blocked hierarchical geospatial field data representation (Blocked-HGFDR). In addition, the original Blocked-HGFDR method is also improved from the following perspectives. Firstly, the original data are divided into a series of data blocks of a more balanced size to reduce the effect of the dimensional unbalance of ESMD. Following this, based on the mathematical relationship between the compression parameter and compression error in Blocked-HGFDR, the control mechanism is developed to determine the optimal compression parameter for the given compression error. By assigning each data block an independent compression parameter, Adaptive-HGFDR can capture the local variation of multidimensional coupling correlations to improve the approximation accuracy. Experiments are carried out based on the Community Earth System Model (CESM) data. The results show that our method has higher compression ratio and more uniform error distributions compared with ZFP and Blocked-HGFDR. For the compression results among 22 climate variables, Adaptive-HGFDR can achieve good compression performances for most flux variables with significant spatiotemporal heterogeneity and fast changing rate. This study provides a new potential method for the lossy compression of the large-scale Earth system model data.

scholarly journals Adaptive lossy compression of climate model data based on hierarchical tensor with Adaptive-HGFDR (v1.0)

2020 ◽  
Author(s):  
Zhaoyuan Yu ◽  
Zhengfang Zhang ◽  
Dongshuang Li ◽  
Wen Luo ◽  
Yuan Liu ◽  
...  
Keyword(s):  
Data Compression ◽  
Compression Ratio ◽  
Large Scale ◽  
Data Representation ◽  
Lossy Compression ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Model Data ◽  
Compression Parameter

Abstract. Lossy compression has been applied to large-scale experimental model data compression due to its advantages of a high compression ratio. However, few methods consider the uneven distribution of compression errors affecting compression quality. Here we develop an adaptive lossy compression method with the stable compression error for earth system model data based on Hierarchical Geospatial Field Data Representation (HGFDR). We extended the original HGFDR by firstly dividing the original data into a series of the local block according to the exploratory experiment to maximize the local correlations of the data. After that, from the mathematical model of the HGFDR, the relationship between the compression parameter and compression error in HGFDR for each block is analyzed and calculated. Using optimal compression parameter selection rule and an adaptive compression algorithm, our method, the Adaptive-HGFDR, achieved the data compression under the constraints that the compression error is as stable as possible through each dimension. Experiments concerning model data compression are carried out based on the Community Earth System Model (CESM) data. The results show that our method has higher compression ratio and more uniform error distributions, compared with other commonly used lossy compression methods, such as the Fixed-Rate Compressed Floating-Point Arrays method.

scholarly journals Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM)

2013 ◽  
Vol 6 (2) ◽  
pp. 301-325 ◽  
Author(s):  
J. F. Tjiputra ◽  
C. Roelandt ◽  
M. Bentsen ◽  
D. M. Lawrence ◽  
T. Lorentzen ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Deep Water ◽  
Earth System Model ◽  
Carbon Pool ◽  
System Model ◽  
Carbon Uptake ◽  
Generation Model ◽  
Earth System ◽  
Model Data ◽  
Overturning Circulation

Abstract. The recently developed Norwegian Earth System Model (NorESM) is employed for simulations contributing to the CMIP5 (Coupled Model Intercomparison Project phase 5) experiments and the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC-AR5). In this manuscript, we focus on evaluating the ocean and land carbon cycle components of the NorESM, based on the preindustrial control and historical simulations. Many of the observed large scale ocean biogeochemical features are reproduced satisfactorily by the NorESM. When compared to the climatological estimates from the World Ocean Atlas (WOA), the model simulated temperature, salinity, oxygen, and phosphate distributions agree reasonably well in both the surface layer and deep water structure. However, the model simulates a relatively strong overturning circulation strength that leads to noticeable model-data bias, especially within the North Atlantic Deep Water (NADW). This strong overturning circulation slightly distorts the structure of the biogeochemical tracers at depth. Advancements in simulating the oceanic mixed layer depth with respect to the previous generation model particularly improve the surface tracer distribution as well as the upper ocean biogeochemical processes, particularly in the Southern Ocean. Consequently, near-surface ocean processes such as biological production and air–sea gas exchange, are in good agreement with climatological observations. The NorESM adopts the same terrestrial model as the Community Earth System Model (CESM1). It reproduces the general pattern of land-vegetation gross primary productivity (GPP) when compared to the observationally based values derived from the FLUXNET network of eddy covariance towers. While the model simulates well the vegetation carbon pool, the soil carbon pool is smaller by a factor of three relative to the observational based estimates. The simulated annual mean terrestrial GPP and total respiration are slightly larger than observed, but the difference between the global GPP and respiration is comparable. Model-data bias in GPP is mainly simulated in the tropics (overestimation) and in high latitudes (underestimation). Within the NorESM framework, both the ocean and terrestrial carbon cycle models simulate a steady increase in carbon uptake from the preindustrial period to the present-day. The land carbon uptake is noticeably smaller than the observations, which is attributed to the strong nitrogen limitation formulated by the land model.

Earth System Music: music generated from the first United Kingdom Earth System model

2020 ◽  
Author(s):  
Lee de Mora ◽  
Alistair Sellar ◽  
Andrew Yool ◽  
Julien Palmieri ◽  
Robin S. Smith ◽  
...  
Keyword(s):  
United Kingdom ◽  
Time Series Data ◽  
Scientific Data ◽  
Earth System Model ◽  
System Model ◽  
Series Data ◽  
Historical Period ◽  
System Modelling ◽  
Earth System ◽  
Model Data

<p>With the ever-growing interest from the general public towards understanding climate science, it is becoming increasingly important that we present this information in ways accessible to non-experts. In this pilot study, we use time series data from the first United Kingdom Earth System model (UKESM1) to create six procedurally generated musical pieces and use them to explain the process of modelling the earth system and to engage with the wider community. </p><p>Scientific data is almost always represented graphically either in figures or in videos. By adding audio to the visualisation of model data, the combination of music and imagery provides additional contextual clues to aid in the interpretation. Furthermore, the audiolisation of model data can be employed to generate interesting and captivating music, which can not  only reach a wider audience, but also hold the attention of the listeners for extended periods of time.</p><p>Each of the six pieces presented in this work was themed around either a scientific principle or a practical aspect of earth system modelling. These pieces demonstrate the concepts of a spin up, a pre-industrial control run, multiple historical experiments, and the use of several future climate scenarios to a wider audience. They also show the ocean acidification over the historical period, the changes in circulation, the natural variability of the pre-industrial simulations, and the expected rise in sea surface temperature over the 20th century. </p><p>Each of these pieces were arranged using different musical progression, style and tempo. All six pieces were performed by the digital piano synthesizer, TiMidity++, and were published on the lead author's YouTube channel. The videos all show the progression of the data in time with the music and a brief description of the methodology is posted alongside the video. </p><p>To disseminate these works, links to each piece were published on the lead author's personal and professional social media accounts. The reach of these works was also analysed using YouTube's channel monitoring toolkit for content creators, YouTube studio.</p>

Korea Institute of Ocean Science and Technology Earth System Model and Its Simulation Characteristics

2021 ◽  
Author(s):  
Gyundo Pak ◽  
Yign Noh ◽  
Myong-In Lee ◽  
Sang-Wook Yeh ◽  
Daehyun Kim ◽  
...  
Keyword(s):  
Science And Technology ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Ocean Science

scholarly journals Climate Change Projection in the Twenty-First Century Simulated by NIMS-KMA CMIP6 Model Based on New GHGs Concentration Pathways

2021 ◽  
Author(s):  
Hyun Min Sung ◽  
Jisun Kim ◽  
Sungbo Shim ◽  
Jeong-byn Seo ◽  
Sang-Hoon Kwon ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Changes ◽  
Scientific Information ◽  
Earth System Model ◽  
First Century ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Future Projections ◽  
Twenty First Century

AbstractThe National Institute of Meteorological Sciences-Korea Meteorological Administration (NIMS-KMA) has participated in the Coupled Model Inter-comparison Project (CMIP) and provided long-term simulations using the coupled climate model. The NIMS-KMA produces new future projections using the ensemble mean of KMA Advanced Community Earth system model (K-ACE) and UK Earth System Model version1 (UKESM1) simulations to provide scientific information of future climate changes. In this study, we analyze four experiments those conducted following the new shared socioeconomic pathway (SSP) based scenarios to examine projected climate change in the twenty-first century. Present day (PD) simulations show high performance skill in both climate mean and variability, which provide a reliability of the climate models and reduces the uncertainty in response to future forcing. In future projections, global temperature increases from 1.92 °C to 5.20 °C relative to the PD level (1995–2014). Global mean precipitation increases from 5.1% to 10.1% and sea ice extent decreases from 19% to 62% in the Arctic and from 18% to 54% in the Antarctic. In addition, climate changes are accelerating toward the late twenty-first century. Our CMIP6 simulations are released to the public through the Earth System Grid Federation (ESGF) international data sharing portal and are used to support the establishment of the national adaptation plan for climate change in South Korea.

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