Climate research, monitoring, prediction, and related services rely on accurate observations of the atmosphere, land, and ocean, adequately sampled globally and over sufficiently long time periods. The Global Climate Observing System, set up under the auspices of United Nations organizations and the International Council for Science to help ensure the availability of systematic observations of climate, developed the concept of essential climate variables (ECVs). ECV data records are intended to provide reliable, traceable, observation-based evidence for a range of applications, including monitoring, mitigating, adapting to, and attributing climate changes, as well as the empirical basis required to understand past, current, and possible future climate variability. The ECV concept has been broadly adopted worldwide as the guiding basis for observing climate, including by the United Nations Framework Convention on Climate Change (UNFCCC), WMO, and space agencies operating Earth observation satellites. This ...

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The Concept of Essential Climate Variables in Support of Climate Research, Applications, and Policy

. This paper presents an update and extension of HYDE, the History Database of the Global Environment (HYDE version 3.2). HYDE is an internally consistent combination of historical population estimates and allocation algorithms with time-dependent weighting maps for land use. Categories include cropland, with new distinctions for irrigated and rain-fed crops (other than rice) and irrigated and rain-fed rice. Grazing lands are also provided, divided into more intensively used pasture and less intensively used rangeland, and further specified with respect to conversion of natural vegetation to facilitate global change modellers. Population is represented by maps of total, urban, rural population, population density and built-up area. The period covered is 10 000 before Common Era (BCE) to 2015 Common Era (CE). All data can be downloaded from https://doi.org/10.17026/dans-25g-gez3 . We estimate that global population increased from 4.4 million people (we also estimate a lower range Cropland occupied approximately less than 1 % of the global land area (13 037 Mha, excluding Antarctica) for a long time period until 1 CE, quite similar to the grazing land area. In the following centuries the share of global cropland slowly grew to 2.2 % in 1700 CE (ca. 293 Mha, uncertainty range 220–367 Mha), 4.4 % in 1850 CE (578 Mha, range 522–637 Mha) and 12.2 % in 2015 CE (ca. 1591 Mha, range 1572–1604 Mha). Cropland can be further divided into rain-fed and irrigated land, and these categories can be further separated into rice and non-rice. Rain-fed croplands were much more common, with 2.2 % in 1700 CE (289 Mha, range 217–361 Mha), 4.2 % (549 Mha, range 496–606 Mha) in 1850 CE and 10.1 % (1316 Mha, range 1298–1325 Mha) in 2015 CE, while irrigated croplands used less than 0.05 % (4.3 Mha, range 3.1–5.5 Mha), 0.2 % (28 Mha, range 25–31 Mha) and 2.1 % (277 Mha, range 273–278 Mha) in 1700, 1850 and 2015 CE, respectively. We estimate the irrigated rice area (paddy) to be 0.1 % (13 Mha, range 9–16 Mha) in 1700 CE, 0.2 % (28 Mha, range 26–31 Mha) in 1850 CE and 0.9 % (118 Mha, range 117–120 Mha) in 2015 CE. The estimates for land used for grazing are much more uncertain. We estimate that the share of grazing land grew from 5.1 % in 1700 CE (667 Mha, range 507–820 Mha) to 9.6 % in 1850 CE (1192 Mha, range 1068–1304 Mha) and 24.9 % in 2015 CE (3241 Mha, range 3211–3270 Mha). To aid the modelling community we have divided land used for grazing into more intensively used pasture, less intensively used converted rangeland and less or unmanaged natural unconverted rangeland. Pasture occupied 1.1 % in 1700 CE (145 Mha, range 79–175 Mha), 1.9 % in 1850 CE (253 Mha, range 218–287 Mha) and 6.0 % (787 Mha, range 779–795 Mha) in 2015 CE, while rangelands usually occupied more space due to their occurrence in more arid regions and thus lower yields to sustain livestock. We estimate converted rangeland at 0.6 % in 1700 CE (82 Mha range 66–93 Mha), 1 % in 1850 CE (129 Mha range 118–136 Mha) and 2.4 % in 2015 CE (310 Mha range 306–312 Mha), while the unconverted natural rangelands occupied approximately 3.4 % in 1700 CE (437 Mha, range 334–533 Mha), 6.2 % in 1850 CE (810 Mha, range 733–881 Mha) and 16.5 % in 2015 CE (2145 Mha, range 2126–2164 Mha).

https://essd.copernicus.org/articles/9/927/2017/essd-9-927-2017.pdf

Anthropogenic land use estimates for the Holocene – HYDE 3.2

Key issues in rigorous accuracy assessment of land cover products

Soil moisture (SM) is a key hydrologic state variable that is of significant importance for numerous Earth and environmental science applications that directly impact the global environment and human society. Potential applications include, but are not limited to, forecasting of weather and climate variability; prediction and monitoring of drought conditions; management and allocation of water resources; agricultural plant production and alleviation of famine; prevention of natural disasters such as wild fires, landslides, floods, and dust storms; or monitoring of ecosystem response to climate change. Because of the importance and wide‐ranging applicability of highly variable spatial and temporal SM information that links the water, energy, and carbon cycles, significant efforts and resources have been devoted in recent years to advance SMmeasurement andmonitoring capabilities from the point to the global scales. This review encompasses recent advances and the state‐of‐the‐art of ground, proximal, and novel SM remote sensing techniques at various spatial and temporal scales and identifies critical future research needs and directions to further advance and optimize technology, analysis and retrieval methods, and the application of SM information to improve the understanding of critical zone moisture dynamics. Despite the impressive progress over the last decade, there are still many opportunities and needs to, for example, improve SM retrieval from remotely sensed optical, thermal, and microwave data and opportunities for novel applications of SM information for water resources management, sustainable environmental development, and food security.

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Ground, Proximal, and Satellite Remote Sensing of Soil Moisture

Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980–1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate–soil interactions. Using moderate climate-change scenarios for 2080–2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate–soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.

https://www.pnas.org/content/pnas/114/11/2848.full.pdf

Selenium deficiency risk predicted to increase under future climate change

Observations of Earth from space have been made for over 40 years and have contributed to advances in many aspects of climate science. However, attempts to exploit this wealth of data are often hampered by a lack of homogeneity and continuity and by insufficient understanding of the products and their uncertainties. There is, therefore, a need to reassess and reprocess satellite datasets to maximize their usefulness for climate science. The European Space Agency has responded to this need by establishing the Climate Change Initiative (CCI). The CCI will create new climate data records for (currently) 13 essential climate variables (ECVs) and make these open and easily accessible to all. Each ECV project works closely with users to produce time series from the available satellite observations relevant to users' needs. A climate modeling users' group provides a climate system perspective and a forum to bring the data and modeling communities together. This paper presents the CCI program. It outlines its benefit and presents approaches and challenges for each ECV project, covering clouds, aerosols, ozone, greenhouse gases, sea surface temperature, ocean color, sea level, sea ice, land cover, fire, glaciers, soil moisture, and ice sheets. It also discusses how the CCI approach may contribute to defining and shaping future developments in Earth observation for climate science.

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The ESA Climate Change Initiative: Satellite Data Records for Essential Climate Variables

The ESA's Climate Change Initiative is reprocessing and reassessing over 40 years of multi-sensor satellite records to generate consistent, traceable, long-term datasets of "essential climate variables" for the climate modeling and research communities. THE ESA CLIMATE CHANGE INITIATIVE Satellite Data Records for Essential Climate Variables

RA Saunders

Papers

The ESA Climate Change Initiative: Satellite Data Records for Essential Climate Variables