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At least 1,117 records · Page 62Linked to original sources

MIS 5e sea-level history along the Pacific coast of North America

The primary last interglacial, marine isotope substage (MIS) 5e records on the Pacific coast of North America, from Washington (USA) to Baja California Sur (Mexico), are found in the deposits of erosional marine terraces. Warmer coasts along the southern Golfo de California host both erosional marine terraces and constructional coral reef terraces. Because the northern part of the region is tectonically active, MIS 5e terrace elevations vary considerably, from a few meters above sea level to as much as 70 m above sea level. The primary paleo-sea-level indicator is the shoreline angle, the junction of the wave-cut platform with the former sea cliff, which forms very close to mean sea level. Most areas on the Pacific coast of North America have experienced uplift since MIS 5e time, but the rate of uplift varies substantially as a function of tectonic setting. Chronology in most places is based on uranium-series ages of the solitary coral Balanophyllia elegans (erosional terraces) or the colonial corals Porites and Pocillopora (constructional reefs). In areas lacking corals, correlation to MIS 5e often can be accomplished using amino acid ratios of fossil mollusks, compared to similar ratios in mollusks that also host dated corals. Uranium-series (U-series) analyses of corals that have experienced largely closed-system histories range from ∼124 to ∼118 ka, in good agreement with ages from MIS 5e reef terraces elsewhere in the world. There is no geomorphic, stratigraphic, or geochronological evidence for more than one high-sea stand during MIS 5e on the Pacific coast of North America. However, in areas of low uplift rate, the outer parts of MIS 5e terraces apparently were re-occupied by the high-sea stand at ∼100 ka (MIS 5c), evident from mixes of coral ages and mixes of molluscan faunas with differing thermal aspects. This sequence of events took place because glacial isostatic adjustment processes acting on North America resulted in regional high-sea stands at ∼100 and ∼80 ka that were higher than is the case in far-field regions, distant from large continental ice sheets. During MIS 5e time, sea surface temperatures (SSTs) off the Pacific coast of North America were higher than is the case at present, evident from extralimital southern species of mollusks found in dated deposits. Apparently, no wholesale shifts in faunal provinces took place, but in MIS 5e time, some species of bivalves and gastropods lived hundreds of kilometers north of their present northern limits, in good agreement with SST estimates derived from foraminiferal records and alkenone-based reconstructions in deep-sea cores. Because many areas of the Pacific coast of North America have been active tectonically for much or all of the Quaternary, many earlier interglacial periods are recorded as uplifted, higher-elevation terraces. In addition, from southern Oregon to northern Baja California, there are U-series-dated corals from marine terraces that formed at ∼80 ka, during MIS 5a. In contrast to MIS 5e, these terrace deposits host molluscan faunas that contain extralimital northern species, indicating cooler SST at the end of MIS 5. Here I present a review and standardized database of MIS 5e sea-level indicators along the Pacific coast of North America and the corresponding dated samples. The database is available in Muhs et al. (2021b; https://doi.org/10.5281/zenodo.5903285 ).

Earth System Science Data↗

Implementation of the CCDC algorithm to produce the LCMAP Collection 1.0 annual land surface change product

The increasing availability of high-quality remote sensing data and advanced technologies have spurred land cover mapping to characterize land change from local to global scales. However, most land change datasets either span multiple decades at a local scale or cover limited time over a larger geographic extent. Here, we present a new land cover and land surface change dataset created by the Land Change Monitoring, Assessment, and Projection (LCMAP) program over the conterminous United States (CONUS). The LCMAP land cover change dataset consists of annual land cover and land cover change products over the period 1985-2017 at 30-meter resolution using Landsat and other ancillary data via the Continuous Change Detection and Classification (CCDC) algorithm. In this paper, we describe our novel approach to implement the CCDC algorithm to produce the LCMAP product suite composed of five land cover and five land surface change related products. The LCMAP land cover products were validated using a collection of ~ 25,000 reference samples collected independently across CONUS. The overall agreement for all years of the LCMAP primary land cover product reached 82.5%. The LCMAP products are produced through the LCMAP Information Warehouse and Data Store (IW+DS) and Shared Mesos Cluster systems that can process, store, and deliver all datasets for public access. To our knowledge, this is the first set of published 30m annual land cover and land cover change datasets that span from the 1980s to the present for the United States. The LCMAP product suite provides useful information for land resource management and facilitates studies to improve the understanding of terrestrial ecosystems and the complex dynamics of the Earth system. The LCMAP system could be implemented to produce global land change products in the future.

Earth System Science Data↗

A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan

From the Hindu Kush mountains to the Registan Desert, Afghanistan is a diverse landscape where droughts, floods, conflict, and economic market accessibility pose challenges for agricultural livelihoods and food security. The ability to remotely monitor environmental conditions is critical to support decision making for humanitarian assistance. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams provide information on hydrologic states for routine integrated food security analysis. While developed for a specific project, these data are publicly available and useful for other applications that require hydrologic estimates of the water and energy balance. These two data streams are unique because of their suitability for routine monitoring, as well as for being a historical record for computing relative indicators of water availability. The global stream is available at ∼ 1-month latency, and monthly average outputs are on a 10 km grid from 1982–present. The second data stream, Central Asia (21–56 ∘ N, 30–100 ∘ E), at ∼ 1 d latency, provides daily average outputs on a 1 km grid from 2000–present. This paper describes the configuration of the two FLDAS data streams, background on the software modeling framework, selected meteorological inputs and parameters, and results from previous evaluation studies. We also provide additional analysis of precipitation and snow cover over Afghanistan. We conclude with an example of how these data are used in integrated food security analysis. For use in new and innovative studies that will improve understanding of this region, these data are hosted by U.S. Geological Survey data portals and the National Aeronautics and Space Administration (NASA). The Central Asia data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/VQ4CD3Y9YC0R (Jacob and Slinski, 2021), and the global data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/5NHC22T9375G (McNally, 2018).

Earth System Science Data↗

The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil

Fungi and bacteria are the two dominant groups of soil microbial communities worldwide. By controlling the turnover of soil organic matter, these organisms directly regulate the exchange of carbon between the soil and the atmosphere. Fundamental differences in the physiology and life history of bacteria and fungi suggest that variation in the biogeography of soil fungal and bacterial relative abundance could drive striking differences in carbon decomposition and soil organic matter formation across different biomes. However, a lack of global and predictive information on the distribution of these organisms in terrestrial 45 ecosystems has prevented the inclusion of soil fungal and bacterial relative abundance and the associated processes into global biogeochemical models. Here, we used a global scale dataset in the top soil surface (>3000 distinct observations of soil fungal and bacterial abundance) to generate the first quantitative and spatially high resolution (1km) explicit map of soil fungal proportion, defined as fungi/fungi + bacteria, across terrestrial ecosystems. We reveal striking latitudinal trends where fungal dominance increases in cold and high latitude environments with large soil carbon stocks. There was strong non-linear response of fungal 50 dominance to environmental gradient, i.e., mean annual temperature (MAT) and net primary productivity (NPP). Fungi and bacteria dominated in regions with low and high MAT and NPP, respectively, thus representing slow vs. fast soil energy channels, a concept with a long history in soil ecology. These high-resolution models provide the first steps towards representing the major soil microbial groups and their functional differences in global biogeochemical models to improve predictions of soil organic matter turnover under current and future climate scenarios

Earth System Science Data↗

Multi-year, spatially extensive, watershed-scale synoptic stream chemistry and water quality conditions for six permafrost-underlain Arctic watersheds

Repeated sampling of spatially distributed river chemistry can be used to assess the location, scale, and persistence of carbon and nutrient contributions to watershed exports. Here, we provide a comprehensive set of water chemistry measurements and ecohydrological metrics describing the biogeochemical conditions of permafrost-affected Arctic watersheds. These data were collected in watershed-wide synoptic campaigns in six stream networks across northern Alaska. Three watersheds are associated with the Arctic Long-Term Ecological Research site at Toolik Field Station (TFS), which were sampled seasonally each June and August from 2016 to 2018. Three watersheds were associated with the National Park Service (NPS) of Alaska and the U.S. Geological Survey (USGS) and were sampled annually from 2015 to 2019. Extensive water chemistry characterization included carbon species, dissolved nutrients, and major ions. The objective of the sampling designs and data acquisition was to characterize terrestrial–aquatic linkages and processing of material in stream networks. The data allow estimation of novel ecohydrological metrics that describe the dominant location, scale, and overall persistence of ecosystem processes in continuous permafrost. These metrics are (1) subcatchment leverage, (2) variance collapse, and (3) spatial persistence. Raw data are available at the National Park Service Integrated Resource Management Applications portal (O'Donnell et al., 2021, https://doi.org/10.5066/P9SBK2DZ ) and within the Environmental Data Initiative (Abbott, 2021, https://doi.org/10.6073/pasta/258a44fb9055163dd4dd4371b9dce945 ).

Alaska↗

GRiMeDB: The Global River Database Methane Database of concentrations and fluxes

Despite their small spatial extent, fluvial ecosystems play a significant role in processing and transporting carbon in aquatic networks, which results in substantial emission of methane ( CH 4 ) into the atmosphere. For this reason, considerable effort has been put into identifying patterns and drivers of CH 4 concentrations in streams and rivers and estimating fluxes to the atmosphere across broad spatial scales. However, progress toward these ends has been slow because of pronounced spatial and temporal variability of lotic CH 4 concentrations and fluxes and by limited data availability across diverse habitats and physicochemical conditions. To address these challenges, we present a comprehensive database of CH 4 concentrations and fluxes for fluvial ecosystems along with broadly relevant and concurrent physical and chemical data. The Global River Methane Database (GriMeDB; https://doi.org/10.6073/pasta/f48cdb77282598052349e969920356ef , Stanley et al., 2023) includes 24 024 records of CH 4 concentration and 8205 flux measurements from 5029 unique sites derived from publications, reports, data repositories, unpublished data sets, and other outlets that became available between 1973 and 2021. Flux observations are reported as diffusive, ebullitive, and total CH 4 fluxes, and GriMeDB also includes 17 655 and 8409 concurrent measurements of concentrations and 4444 and 1521 fluxes for carbon dioxide ( CO 2 ) and nitrous oxide ( N 2 O ), respectively. Most observations are date-specific (i.e., not site averages), and many are supported by data for 1 or more of 12 physicochemical variables and 6 site variables. Site variables include codes to characterize marginal channel types (e.g., springs, ditches) and/or the presence of human disturbance (e.g., point source inputs, upstream dams). Overall, observations in GRiMeDB encompass the broad range of the climatic, biological, and physical conditions that occur among world river basins, although some geographic gaps remain (arid regions, tropical regions, high-latitude and high-altitude systems). The global median CH 4 concentration (0.20 µmol L −1 ) and diffusive flux (0.44 mmol m -2 d -1 ) in GRiMeDB are lower than estimates from prior site-averaged compilations, although ranges (0 to 456 µmol L −1 and − 136 to 4057 mmol m -2 d -1 ) and standard deviations (10.69 and 86.4) are greater for this larger and more temporally resolved database. Available flux data are dominated by diffusive measurements despite the recognized importance of ebullitive and plant-mediated CH 4 fluxes. Nonetheless, GriMeDB provides a comprehensive and cohesive resource for examining relationships between CH 4 and environmental drivers, estimating the contribution of fluvial ecosystems to CH 4 emissions, and contextualizing site-based investigations.

Earth System Science Data↗

Inventory of glaciers and perennial snowfields of the conterminous USA

This report summarizes an updated inventory of glaciers and perennial snowfields of the conterminous United States. The inventory is based on interpretation of mostly aerial imagery provided by the National Agricultural I magery Program, US Department of Agriculture, with some satellite imagery in places where aerial imagery was not suitable. The inventory includes all perennial snow and ice features ≥ 0.01 km 2 . Due to aerial survey schedules and seasonal snow cover, imageries acquired over a number of years were required. The earliest date is 2013 and the latest is 2020, but more than 73 % of the outlines were acquired from 2015 imagery. The inventory is compiled as shapefiles within a geographic information system that includes feature classification, area, and location. The inventory identified 1331 (366.52 ± 14.34 km 2 ) glaciers, 1176 (31.01 ± 9.30 km 2 ) perennial snowfields, and 35 (3.57 km 2 ± no uncertainty) buried-ice features. The data including both the shapefiles and tabulated results are publicly available at https://doi.org/10.15760/geology-data.03 (Fountain and Glenn, 2022).

Earth System Science Data↗

Global methane budget 2000-2020

Understanding and quantifying the global methane (CH 4 ) budget is important for assessing realistic pathways to mitigate climate change. CH 4 is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO 2 ), and both emissions and atmospheric concentrations of CH 4 have continued to increase since 2007 after a temporary pause. The relative importance of CH 4 emissions compared to those of CO 2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH 4 sources and from the uncertain magnitude and temporal change in the destruction of CH 4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH 4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH 4 budget, integrating results of top-down CH 4 emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH 4 yr −1 ). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH 4 yr −1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH 4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH 4 yr −1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH 4 yr −1 or ∼ 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH 4 yr −1 or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH 4 yr −1 (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH 4 yr −1 (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH 4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH 4 yr −1 ) larger global emissions (669 Tg CH 4 yr −1 , range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH 4 yr −1 in Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH 4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH 4 yr −1 based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty ( ∼ 25 %). The total sink of CH 4 is estimated at 633 [507–796] Tg CH 4 yr −1 by the bottom-up approaches and at 554 [550–567] Tg CH 4 yr −1 by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified. For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH 4 yr −1 in the top-down budget and 211 [195–231] Tg CH 4 yr −1 in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH 4 yr −1 in the top-down budget and 120 [117–125] Tg CH 4 yr −1 in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH 4 yr −1 in the top-down budget and 28 [21–39] Tg CH 4 yr −1 in the bottom-up budget. We identify five major priorities for improving the CH 4 budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH 4 based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH 4 observations at local (e.g. FLUXNET-CH 4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning.

Earth System Science Data↗

Permafrost–wildfire interactions: active layer thickness estimates for paired burned and unburned sites in northern high latitudes

As the northern high-latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impacts permafrost stability through the combustion of insulating organic matter, vegetation, and post-fire changes in albedo. Efforts to synthesis the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52 466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end-of-season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality-checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 48 669 ALT estimates with 32 attributes across 9446 plots and 157 burned–unburned pairs spanning Canada, Russia, and the United States. The data span fire events from 1900 to 2022 with measurements collected from 2001 to 2023. The time since fire ranges from 0 to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end-of-season maximum. This dataset can be used to address understudied research areas, particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost–wildfire interactions under accelerated warming across the high-northern-latitude permafrost zone. The FireALT dataset is available through the Arctic Data Center ( https://doi.org/10.18739/A2RN3092P , Talucci et al., 2024).

Arctic↗

A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region

High-latitude terrestrial ecosystems are key components in the global carbon cycle. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify stocks of soil organic carbon (SOC) in the northern circumpolar permafrost region (a total area of 18.7 × 10 6 km 2 ). The NCSCD is a geographical information system (GIS) data set that has been constructed using harmonized regional soil classification maps together with pedon data from the northern permafrost region. Previously, the NCSCD has been used to calculate SOC storage to the reference depths 0–30 cm and 0–100 cm (based on 1778 pedons). It has been shown that soils of the northern circumpolar permafrost region also contain significant quantities of SOC in the 100–300 cm depth range, but there has been no circumpolar compilation of pedon data to quantify this deeper SOC pool and there are no spatially distributed estimates of SOC storage below 100 cm depth in this region. Here we describe the synthesis of an updated pedon data set for SOC storage (kg C m -2 ) in deep soils of the northern circumpolar permafrost regions, with separate data sets for the 100–200 cm (524 pedons) and 200–300 cm (356 pedons) depth ranges. These pedons have been grouped into the North American and Eurasian sectors and the mean SOC storage for different soil taxa (subdivided into Gelisols including the sub-orders Histels, Turbels, Orthels, permafrost-free Histosols, and permafrost-free mineral soil orders) has been added to the updated NCSCDv2. The updated version of the data set is freely available online in different file formats and spatial resolutions that enable spatially explicit applications in GIS mapping and terrestrial ecosystem models. While this newly compiled data set adds to our knowledge of SOC in the 100–300 cm depth range, it also reveals that large uncertainties remain. Identified data gaps include spatial coverage of deep (> 100 cm) pedons in many regions as well as the spatial extent of areas with thin soils overlying bedrock and the quantity and distribution of massive ground ice. An open access data-portal for the pedon data set and the GIS-data sets is available online at http://bolin.su.se/data/ncscd/ .

Earth System Science Data↗

Temperature data acquired from the DOI/GTN-P Deep Borehole Array on the Arctic Slope of Alaska, 1973-2013

A homogeneous set of temperature measurements obtained from the DOI/GTN-P Deep Borehole Array between 1973 and 2013 is presented; DOI/GTN-P is the US Department of the Interior contribution to the Global Terrestrial Network for Permafrost (GTN-P). The 23-element array is located on the Arctic Slope of Alaska, a region of cold continuous permafrost. Most of the monitoring wells are situated on the Arctic coastal plain between the Brooks Range and the Arctic Ocean, while others are in the foothills to the south. The data represent the true temperatures in the wellbores and surrounding rocks at the time of the measurements; they have not been corrected to remove the thermal disturbance caused by drilling the wells. With a few exceptions, the drilling disturbance is estimated to have been on the order of 0.1 K or less by 1989. Thus, most of the temperature measurements acquired during the last 25 yr are little affected by the drilling disturbance. The data contribute to ongoing efforts to monitor changes in the thermal state of permafrost in both hemispheres by the Global Terrestrial Network for Permafrost, one of the primary subnetworks of the Global Terrestrial Observing System (GTOS). The data will also be useful for refining our basic understanding of the physical conditions in permafrost in Arctic Alaska, as well as providing important information for validating predictive models used for climate impact assessments. The processed data are available from the Advanced Cooperative Arctic Data and Information Service (ACADIS) repository at doi:10.5065/D6N014HK.

Alaska↗

PeRL: A circum-Arctic Permafrost Region Pond and Lake database

Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1. 0 × 10 4 m 2 , have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002–2013) high-resolution aerial and satellite imagery with a resolution of 5 m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6 m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1. 4 × 10 6 km 2 across the Arctic, about 17 % of the Arctic lowland ( < 300 m a.s.l.) land surface area. PeRL waterbodies with sizes of 1. 0 × 10 6 m 2 down to 1. 0 × 10 2 m 2 contributed up to 21 % to the total water fraction. Waterbody density ranged from 1. 0 × 10 to 9. 4 × 10 1 km −2 . Ponds are the dominant waterbody type by number in all landscapes representing 45–99 % of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349 .

Earth System Science Data↗

Glaciological measurements and mass balances from Sperry Glacier, Montana, USA, years 2005–2015

Glacier mass balance measurements help to provide an understanding of the behavior of glaciers and their response to local and regional climate. In 2005 the United States Geological Survey established a surface mass balance monitoring program on Sperry Glacier, Montana, USA. This project is the first quantitative study of mass changes of a glacier in the US northern Rocky Mountains and continues to the present. The following paper describes the methods used during the first 11 years of measurements and reports the associated results. From 2005 to 2015, Sperry Glacier had a cumulative mean mass balance loss of 4.37 m w.e. (water equivalent). The mean winter, summer, and annual glacier-wide mass balances were 2.92, −3.41, and −0.40 m w.e. yr −1 respectively. We derive these cumulative and mean results from an expansive data set of snow depth, snow density, and ablation measurements taken at selected points on the glacier. These data allow for the determination of mass balance point values and a time series of seasonal and annual glacier-wide mass balances for all 11 measurement years. We also provide measurements of glacier extent and accumulation areas for select years. All data have been submitted to the World Glacier Monitoring Service and are available at doi:10.5904/wgms-fog-2016-08 . This foundational work provides valuable insight about Sperry Glacier and supplies additional data to the worldwide record of glaciers measured using the glaciological method. Future research will focus on the processes that control accumulation and ablation patterns across the glacier. Also we plan to examine the uncertainties related to our methods and eventually quantify a more robust estimate of error associated with our results.

Montana↗

The ACER pollen and charcoal database: A global resource to document vegetation and fire response to abrupt climate changes during the last glacial period

Quaternary records provide an opportunity to examine the nature of the vegetation and fire responses to rapid past climate changes comparable in velocity and magnitude to those expected in the 21st century. The best documented examples of rapid climate change in the past are the warming events associated with the Dansgaard-Oeschger (D-O) cycles during the last glacial period, which were sufficiently large to have had a potential feedback through changes in albedo and greenhouse gas emissions on climate. Previous reconstructions of vegetation and fire changes during the D-O cycles used independently constructed age models, making it difficult to compare the changes between different sites and regions. Here we present the ACER (Abrupt Climate Changes and Environmental Responses) global database which includes 93 pollen records from the last glacial period (73–15 ka) with a temporal resolution better than 1,000 years, 32 of which also provide charcoal records. A harmonized and consistent chronology based on radiometric dating (¹⁴C, ²³⁴U/²³⁰Th, OSL, ⁴⁰Ar/³⁹Ar dated tephra layers) has been constructed for 86 of these records, although in some cases additional information was derived using common control points based on event stratigraphy. The ACER database compiles metadata including geospatial and dating information, pollen and charcoal counts and pollen percentages of the characteristic biomes, and is archived in Microsoft AccessTM at doi:10.1594/PANGAEA.870867.

Earth System Science Data↗

A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data

Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004–2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance model for (i) quantitative assessment of the impact of basin developmental activities on lake levels and for (ii) forecasting lake level changes and their impact on fisheries. From this study, we suggest that globally available satellite altimetry data provide a unique opportunity for calibration and validation of hydrologic models in ungauged basins.

Lake Turkana↗

Soil-water dynamics and unsaturated storage during snowmelt following wildfire

Many forested watersheds with a substantial fraction of precipitation delivered as snow have the potential for landscape disturbance by wildfire. Little is known about the immediate effects of wildfire on snowmelt and near-surface hydrologic responses, including soil-water storage. Montane systems at the rain-snow transition have soil-water dynamics that are further complicated during the snowmelt period by strong aspect controls on snowmelt and soil thawing. Here we present data from field measurements of snow hydrology and subsurface hydrologic and temperature responses during the first winter and spring after the September 2010 Fourmile Canyon Fire in Colorado, USA. Our observations of soil-water content and soil temperature show sharp contrasts in hydrologic and thermal conditions between north- and south-facing slopes. South-facing burned soils were ∼1–2 °C warmer on average than north-facing burned soils and ∼1.5 °C warmer than south-facing unburned soils, which affected soil thawing during the snowmelt period. Soil-water dynamics also differed by aspect: in response to soil thawing, soil-water content increased approximately one month earlier on south-facing burned slopes than on north-facing burned slopes. While aspect and wildfire affect soil-water dynamics during snowmelt, soil-water storage at the end of the snowmelt period reached the value at field capacity for each plot, suggesting that post-snowmelt unsaturated storage was not substantially influenced by aspect in wildfire-affected areas. Our data and analysis indicate that the amount of snowmelt-driven groundwater recharge may be larger in wildfire-impacted areas, especially on south-facing slopes, because of earlier soil thaw and longer durations of soil-water contents above field capacity in those areas.

Hydrology and Earth System Sciences↗

A basin-scale approach for assessing water resources in a semiarid environment: San Diego region, California and Mexico

Many basins throughout the world have sparse hydrologic and geologic data, but have increasing demands for water and a commensurate need for integrated understanding of surface and groundwater resources. This paper demonstrates a methodology for using a distributed parameter water-balance model, gaged surface-water flow, and a reconnaissance-level groundwater flow model to develop a first-order water balance. Flow amounts are rounded to the nearest 5 million cubic meters per year. The San Diego River basin is 1 of 5 major drainage basins that drain to the San Diego coastal plain, the source of public water supply for the San Diego area. The distributed parameter water-balance model (Basin Characterization Model) was run at a monthly timestep for 1940–2009 to determine a median annual total water inflow of 120 million cubic meters per year for the San Diego region. The model was also run specifically for the San Diego River basin for 1982–2009 to provide constraints to model calibration and to evaluate the proportion of inflow that becomes groundwater discharge, resulting in a median annual total water inflow of 50 million cubic meters per year. On the basis of flow records for the San Diego River at Fashion Valley (US Geological Survey gaging station 11023000), when corrected for upper basin reservoir storage and imported water, the total is 30 million cubic meters per year. The difference between these two flow quantities defines the annual groundwater outflow from the San Diego River basin at 20 million cubic meters per year. These three flow components constitute a first-order water budget estimate for the San Diego River basin. The ratio of surface-water outflow and groundwater outflow to total water inflow are 0.6 and 0.4, respectively. Using total water inflow determined using the Basin Characterization Model for the entire San Diego region and the 0.4 partitioning factor, groundwater outflow from the San Diego region, through the coastal plain aquifer to the Pacific Ocean, is calculated to be approximately 50 million cubic meters per year. The area-scale assessment of water resources highlights several hydrologic features of the San Diego region. Groundwater recharge is episodic; the Basin Characterization Model output shows that 90 percent of simulated recharge occurred during 3 percent of the 1982–2009 period. The groundwater aquifer may also be quite permeable. A reconnaissance-level groundwater flow model for the San Diego River basin was used to check the water budget estimates, and the basic interaction of the surface-water and groundwater system, and the flow values, were found to be reasonable. Horizontal hydraulic conductivity values of the volcanic and metavolcanic bedrock in San Diego region range from 1 to 10 m per day. Overall, results establish an initial hydrologic assessment formulated on the basis of sparse hydrologic data. The described flow variability, extrapolation, and unique characteristics represent a realistic view of current (2012) hydrologic understanding for the San Diego region.

California↗

Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?

In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.

Hydrology and Earth System Sciences↗