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17 results for “hydrological cycle”

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edi48/100

Consequences of non-random tree species loss on litter mass loss, nutrient dynamics, carbon cycling, and decomposer communities across a terrestrial-aquatic interface at Coweeta Hydrologic Lab, Otto, NC

Although litter decomposition is a fundamental ecological process, most of our understanding comes from studies of single-species decay. Recently, litter-mixing studies have tested whether monoculture data can be applied to mixed-litter systems. These studies have mainly attempted to detect non-additive effects of litter mixing, which address potential consequences of random species loss. The focus is not on which species are lost, but the decline in diversity per se. Under global change, species loss is likely to be non-random, with some species more vulnerable to extinction than others. Under such scenarios, the effects of individual species (additivity) as well as of species interactions (non-additivity) on decomposition rates are of interest. To examine potential impacts of non-random species loss on ecosystems, we studied additive and non-additive effects of litter mixing on decomposition. A full-factorial litterbag experiment was conducted using four deciduous leaf species, from which mass loss and nitrogen content were measured. Data were analysed using a statistical approach that first looks for additive identity effects based on the presence or absence of species and then significant species interactions occurring beyond those. It partitions non-additive effects into those caused by richness and or composition.

openCustomJan 2020View details →
zenodo44/100

Intensified atmospheric branch of the hydrological cycle over the Tibetan Plateau during the Last Interglacial from a dynamical downscaling perspective

<p>We provide the datasets run for&nbsp;investigating&nbsp;the atmospheric branch of the hydrological cycle over the Tibetan Plateau during the Last Interglacial (127 ka), based on the &nbsp;mesoscale Weather Research and Forecasting (WRF) model driven by the Community Earth System Model (CESM). We upload summer mean of the model outputs&nbsp;from the WRF over the Tibetan Plateau used in estimating the atmospheric branch of the hydrological cycle.</p>

opencc-by-4.0Jul 2022View details →
edi44/100

Soil carbon cycling response to hemlock mortality at the Coweeta Hydrologic Laboratory

We studied the impacts of hemlock mortality from infestation by the hemlock woolly adlegid (HWA) on soil carbon cycling at the Coweeta Hydrologic Laboratory. The HWA was first found at Coweeta in 2003. In 2013 and 2014, we re-sampled plots established in an earlier study by Elliott and others. There were 12 20 x 20 m plots: 4 were control hardwood stands, 4 were untreated hemlock communities, and 4 were hemlock that were girdled. We measured soil C and N concentration, soil delta 13 C, exoemzyme activities, root biomass, soil respiration, forest floor mass, and fungal hyphal biomass.

openCustomJan 2020View details →
zenodo40/100

Рис. 2. Размерная структура G. lacustris в ΛитораΛьной зоне озера АрахΛей: 1 — июнь; 2 — август; 3 — октябрь Fig. 2. G. lacustris population size structure in the Lake Arakhley littoral zone: 1 — June, 2 — August, 3 — October in The life cycle of Gmelinoides fasciatus (Stebbing, 1899) and Gammarus lacustris (Sars, 1863) amphipods in the lake Arakhley littoral during the extreme low-water phase of the hydrological cycle

Рис. 2. Размерная структура G. lacustris в ΛитораΛьной зоне озера АрахΛей: 1 — июнь; 2 — август; 3 — октябрь Fig. 2. G. lacustris population size structure in the Lake Arakhley littoral zone: 1 — June, 2 — August, 3 — October

opencc-by-4.0Dec 2020View details →
zenodo40/100

Рис. 1. Размерная структура Gm. fasciatus в ΛитораΛьной зоне озера АрахΛей: 1 — в июне; 2 — в августе; 3 — в октябре; 4 — в Αекабре 2017 г. и июне 2018 г. Fig. 1. Gm. fasciatus population size structure in the Lake Arakhley littoral zone: 1 — June; 2 — August; 3 — October; 4 — December, 2017 and June, 2018 in The life cycle of Gmelinoides fasciatus (Stebbing, 1899) and Gammarus lacustris (Sars, 1863) amphipods in the lake Arakhley littoral during the extreme low-water phase of the hydrological cycle

Рис. 1. Размерная структура Gm. fasciatus в ΛитораΛьной зоне озера АрахΛей: 1 — в июне; 2 — в августе; 3 — в октябре; 4 — в Αекабре 2017 г. и июне 2018 г. Fig. 1. Gm. fasciatus population size structure in the Lake Arakhley littoral zone: 1 — June; 2 — August; 3 — October; 4 — December, 2017 and June, 2018

opencc-by-4.0Dec 2020View details →
zenodo40/100

Cycles in hydrologic intensification and de-intensification create instabilities in spring nitrate-N export C-Q behavior in northern temperate forests

<p>Data supporting analysis in "Cycles in hydrologic intensification and de-intensification create instabilities in spring nitrate-N export C-Q behavior in northern temperate forests".</p> <p>The worksheet "daily SWE" contains modeled daily snow water equivalent (SWE; mm) at Turkey Lakes Watershed. &nbsp;Daily values were modeled using a snow accumulation and melt routine within a hydrologic model that used measured precipitation and snow survey data as input and was calibrated to daily discharge measurements at a reference catchment.&nbsp;</p> <p>For use of SWE data, please cite:<br>Leach, J. A., Buttle, J. M., Webster, K. L., Hazlett, P. W., &amp; Jeffries, D. S. (2020). Travel times for snowmelt-dominated headwater catchments: influences of wetlands and forest harvesting, and linkages to stream water quality. Hydrological Processes, 34(10), 2154-2175. https://doi.org/10.1002/hyp.13746</p> <p>The worksheet "monthly T, P, PET" contains monthly mean temperature (&deg;C), monthly total precipitation (mm), and monthly Hamon potential evapotranspiration (PET; mm) from measurements made at the Algoma CAPMoN (Canadian Air and Precipitation Monitoring Network) meteorological station (47&deg;02&prime;N, 84&deg;22&prime;W, 411 m.a.s.l.).</p> <p>For use of these climate data, please cite:<br>Semkin, R. G., Jeffries, D. S., Neureuther, R., Lahaie, G., McAulay, M., Norouzian, F., &amp; Franklyn, J. (2012). Summary of hydrological and meteorological measurements in the Turkey Lakes Watershed, Algoma, Ontario, 1980-2010. Water Science and Technology Directorate Contribution No. 11-145. Environment Canada, National Water Research Institute, Burlington, ON, 85 p.</p>

opencc-by-4.0Jul 2024View details →
zenodo40/100

TERENO-preAlpine observatory and ScaleX 2016 campaign data set associated with HESS paper "High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation"

<p>netCDF Dataset, that holds processed hourly station observations for the period 2016-06-01 to 2016-10-31.</p> <p>dimensions:<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; time = 3672 ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; stations = 6 ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; name_strlen = 6 ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; depth = 3 ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; height = 201 ;<br> variables:<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double time(time) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; time:standard_name = &quot;time&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; time:long_name = &quot;time of measurement&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; time:units = &quot;hours since 2016-06-01 00:00:00&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; time:timezone = &quot;UTC&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; time:calendar = &quot;proleptic_gregorian&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double lat(stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lat:standard_name = &quot;latitude&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lat:long_name = &quot;station_latitude&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lat:units = &quot;degrees_north&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double lon(stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lon:standard_name = &quot;longitude&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lon:long_name = &quot;station_longitude&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; lon:units = &quot;degrees_east&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double elev(stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; elev:standard_name = &quot;altitude&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; elev:long_name = &quot;station_altitude&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; elev:units = &quot;m ASL&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double height(height) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; height:standard_name = &quot;altitude&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; height:long_name = &quot;station_altitude&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; height:units = &quot;m ASL&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double depth(depth) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; depth:standard_name = &quot;soil_depth&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; depth:long_name = &quot;soil sensor depth&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; depth:units = &quot;cm&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; char station_name(name_strlen, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; station_name:long_name = &quot;station_name&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; station_name:cf_role = &quot;timeseries_id&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double T(time, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T:standard_name = &quot;temperature&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T:long_name = &quot;2m air temperature&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T:units = &quot;degree_Celsius&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double Q(time, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Q:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Q:standard_name = &quot;mixing_ratio&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Q:long_name = &quot;2m mixing ratio&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Q:units = &quot;g kg-1&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Q:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double ET_i(time, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_i:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_i:standard_name = &quot;evapotranspiration_intensive&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_i:long_name = &quot;lysimeter evapotranspiration intensive management&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_i:units = &quot;g kg-1 h-1&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_i:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double ET_e(time, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_e:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_e:standard_name = &quot;evapotranspiration_extensive&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_e:long_name = &quot;lysimeter evapotranspiration extensive management&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_e:units = &quot;g kg-1 h-1&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ET_e:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double LvE_cor(time, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LvE_cor:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LvE_cor:standard_name = &quot;latent_heat_flux&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LvE_cor:long_name = &quot;energy balance corrected flux tower latent heat flux&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LvE_cor:units = &quot;W m-2&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LvE_cor:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double HTs_cor(time, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HTs_cor:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HTs_cor:standard_name = &quot;sensible_heat_flux&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HTs_cor:long_name = &quot;energy balance corrected flux tower sensible heat flux&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HTs_cor:units = &quot;W m-2&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HTs_cor:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double GHF(time, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GHF:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GHF:standard_name = &quot;ground_heat_flux&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GHF:long_name = &quot;flux tower ground heat flux&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GHF:units = &quot;W m-2&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GHF:positive = &quot;up&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GHF:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double SW(time, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; SW:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; SW:standard_name = &quot;short_wave_radiation&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; SW:long_name = &quot;downward short wave radiation&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; SW:units = &quot;W m-2&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; SW:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double LW(time, stations) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LW:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LW:standard_name = &quot;long_wave_radiation&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LW:long_name = &quot;downward long wave radiation&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LW:units = &quot;W m-2&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; LW:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double VWC_25(time, depth) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_25:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_25:standard_name = &quot;volumetric_water_content&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_25:long_name = &quot;DE-Fen SoilNet volumetric water content first quartile&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_25:units = &quot;vol. %&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_25:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double VWC_50(time, depth) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_50:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_50:standard_name = &quot;volumetric_water_content&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_50:long_name = &quot;DE-Fen SoilNet volumetric water content second quartile&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_50:units = &quot;vol. %&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_50:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double VWC_75(time, depth) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_75:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_75:standard_name = &quot;volumetric_water_content&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_75:long_name = &quot;DE-Fen SoilNet volumetric water content third quartile&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_75:units = &quot;vol. %&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; VWC_75:source = &quot;TERENO-preAlpine&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double T_prof(time, height) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T_prof:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T_prof:standard_name = &quot;temperature_profile&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T_prof:long_name = &quot;DE-Fen HATPRO spline interpolated temperature profile&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T_prof:units = &quot;K&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; T_prof:source = &quot;scaleX campaign 2016&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double A_prof(time, height) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; A_prof:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; A_prof:standard_name = &quot;humidity_profile&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; A_prof:long_name = &quot;DE-Fen HATPRO spline interpolated absolute humidity profile&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; A_prof:units = &quot;kg m-3&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; A_prof:source = &quot;scaleX campaign 2016&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; double PRW(time) ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PRW:_FillValue = -9999. ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PRW:standard_name = &quot;precipitable_water&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PRW:long_name = &quot;DE-Fen HATPRO column precipitable water&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PRW:units = &quot;kg m-2&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PRW:source = &quot;scaleX campaign 2016&quot; ;</p> <p>// global attributes:<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; :history = &quot;2019-09-12: File created.&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; :institution = &quot;Karlsruhe Institute of Technology (KIT) - Campus Alpin, Institute for Meteorology and Climate Research&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; :Contact_person = &quot;Benjamin Fersch (benjamin.fersch@kit.edu)&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; :Author = &quot;Benjamin Fersch (benjamin.fersch@kit.edu)&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; :source = &quot;https://www.tereno.net, https://scalex.imk-ifu.kit.edu&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; :Conventions = &quot;CF-1.6&quot; ;<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; :License = &quot;Creative Commons Attribution Non Commercial Share Alike 4.0 International&quot; ;</p> <p>&nbsp;</p>

opencc-by-nc-sa-4.0Sep 2019View details →
edi40/100

Examining the potential effects of phytophagous insect frass on forest nitrogen cycling at the Coweeta Hydrologic Laboratory from 1999 to 2001

Human alteration of the global nitrogen cycle has increased the importance of understanding the major sources, sinks, and fluxes of the cycle within natural ecosystems. One poorly understood component of the nitrogen cycle in forest ecosystems is the contribution of phytophagous insect frass on soil N-cycling dynamics. This study proposes to investigate the influence of frass on (1) the dynamics of soil N-cycling; (2) the loss of N from the ecosystem via leaching; (3) the slow cycle decomposition of post-herbivore leaf litter; and (4) the overall potential of soil near the Coweeta Hydrologic Laboratory to retain nitrogen. Red Oak (Quercus rubra [Fagaceae]) saplings will be subjected to defoliation by the seasonal phytophagous insect larvae of the White-Marked Tussock Moth (Orgyia leucostigma [Lepidoptera: Lymantriidae]) and the frass added to the soil in a factorial, controlled experimental design. Soil nutrient concentrations, leachate nutrient concentrations, "soil" respiration, and leaf quality will be measured. The project is expected to increase our understanding of the complex relationship between above-ground and below-ground nitrogen cycling dynamics as well as inform the current debate concerning the relative impacts and importance of human versus natural alterations to the nitrogen cycle.

openCustomJan 2020View details →
dryad36/100

Enhancing understanding of the hydrological cycle via pairing of process‐oriented and isotope ratio tracers

<p>This dataset contains monthly average output files from the iCAM6 simulations used in the manuscript "Enhancing understanding of the hydrological cycle via pairing of process-oriented and isotope ratio tracers," in review at the Journal of Advances in Modeling Earth Systems. A file corresponding to each of the tagged and isotopic variables used in this manuscript is included. Files are at 0.9° latitude x 1.25° longitude, and are in NetCDF format. Data from two simulations are included: 1) a simulation where the atmospheric model was "nudged" to ERA5 wind and surface pressure fields, by adding an additional tendency (see section 3.1 of associated manuscript), and 2) a simulation where the atmospheric state was allowed to freely evolve, using only boundary conditions imposed at the surface and top of atmosphere.</p> <p>Specific information about each of the variables provided is located in the "usage notes" section below.</p> <p>Associated article abstract:</p> <p>The hydrologic cycle couples the Earth's energy and carbon budgets through evaporation, moisture transport, and precipitation. Despite a wealth of observations and models, fundamental limitations remain in our capacity to deduce even the most basic properties of the hydrological cycle, including the spatial pattern of the residence time (RT) of water in the atmosphere and the mean distance traveled from evaporation sources to precipitation sinks. Meanwhile, geochemical tracers such as stable water isotope ratios provide a tool to probe hydrological processes, yet their interpretation remains equivocal despite several decades of use. As a result, there is a need for new mechanistic tools that link variations in water isotope ratios to underlying hydrological processes. Here we present a new suite of "process-oriented tags," which we use to explicitly trace hydrological processes within the isotopically enabled Community Atmosphere Model, version 6 (iCAM6). Using these tags, we test the hypotheses that precipitation isotope ratios respond to parcel rainout, variations in atmospheric RT, and preserve information regarding meteorological conditions during evaporation. We present results for a historical simulation from 1980 to 2004, forced with winds from the ERA5 reanalysis. We find strong evidence that precipitation isotope ratios record information about atmospheric rainout and meteorological conditions during evaporation, but little evidence that precipitation isotope ratios vary with water vapor RT. These new tracer methods will enable more robust linkages between observations of isotope ratios in the modern hydrologic cycle or proxies of past terrestrial environments and the environmental processes underlying these observations.<br> </p>

opencc-zeroNov 2021View details →
zenodo36/100

Modeling the hydrological cycle in the atmosphere of Mars: Influence of a bimodal size distribution of aerosol nucleation particles

<p>Data from figures.</p>

opencc-by-4.0Nov 2017View details →
zenodo36/100

Data for "Multiple Equilibria and Soil Moisture-Precipitation Feedbacks in Idealized Convection-Permitting Simulations with an Open Hydrological Cycle"

<p>Code, simulation input files, and simulation&nbsp;output data supporting&nbsp;&ldquo;Multiple Equilibria and Soil Moisture-Precipitation Feedbacks in Idealized Convection-Permitting Simulations with an Open Hydrological Cycle&rdquo;, under review at JAMES. Enclosed README files provide detailed descriptions of the archive contents.</p>

opencc-by-4.0Jul 2023View details →
dryad36/100

Enhancing understanding of the hydrological cycle via pairing of process‐oriented and isotope ratio tracers

Open the record for dataset details and reuse information.

publicDec 2022View details →
edi36/100

Riparian Carbon and Nitrogen Cycling: Influences of Spatial Heterogeneity and Hydrologic Vectors

Terrestrial and aquatic ecosystem ecologists study the same phenomena (e.g., nutrient cycling, energy flow, succession) but they do so within separate conceptual frameworks. Terrestrial frameworks address state factors of climate, organisms, parent material, topography, and time to understand ecosystem processes within a location, but less often consider how ecosystems are connected. Aquatic ecologists, especially those studying flowing waters, emphasize the role of water as a means of propagating processes and materials through space and time. Both terrestrial and aquatic ecosystems contain hydrologic vectors as well as soils or sediments that record the influences of state factors. This dissertation is an investigation of carbon and nitrogen cycling in the stream-riparian corridor of the San Pedro River, a large desert river, and tests the relative effects of soil characteristics and hydrologic vectors. Riparian zones are well suited to such investigations because they are spatially heterogeneous and subject to material and water inputs from multiple hydrologic vectors. Spatially explicit methods showed that flood vectors homogenized soil characteristics and denitrification along a stream reach with frequent overbank floods, whereas soils of a riparian site that was infrequently inundated by floods were heterogeneous. Legacies of previous floods appeared to determine the spatial locations of denitrification at the latter site. At a plot scale, manipulation of precipitation and flood vectors across a gradient of soil types showed that water functioned as an essential resource during the dry season, resulting in increased emissions of trace gases following simulation of floods. Following inundation of riparian soils by several monsoon floods, however, further addition of water appeared to suppress biogeochemical activity by decreasing oxygen availability. Thus desert riparian ecosystems appear to shift seasonally along a terrestrial-aquatic continuum, functioning si

openOpenJan 2020View details →
zenodo32/100

Decoding the Interactions Between Hydrological Processes and Nitrogen Cycling in Bohemian Mountainous Watersheds (Slavkov Forest)

<h1><strong>DATASET&nbsp;<br>Decoding the Interactions Between Hydrological Processes and Nitrogen Cycling in Bohemian Mountainous Watersheds (Slavkov Forest)&nbsp;</strong></h1> <p>F. Buzek<sup>1</sup>, B. Cejkova<sup>1</sup>, I. Jackova<sup>1</sup>, P. Kram<sup>1</sup>, F. Oulehle<sup>1</sup>, O. Myska<sup>1</sup>, F. Veselovsky<sup>1</sup>, J. Curik<sup>1</sup>&nbsp; and D.A. Petrash<sup>1</sup></p> <p>This dataset contains modeling parameters and model results on the influences of hydrological factors on nitrogen (N) mineralization and denitrification processes in three adjacent mountain catchments located in the Slavkov Forest, western Czech Republic, from 2016 to 2020</p>

opencc-by-4.0Dec 2023View details →
zenodo32/100

Data for "Impacts of an active Pacific Meridional Overturning Circulation on the Pliocene climate and hydrological cycle"

<p>Post-Processing Scripts and Data for the Paper<br>Title: Impacts of an Active Pacific Meridional Overturning Circulation on the Pliocene Climate and Hydrological Cycle<br>Authors: Minmin Fu, Alexey Fedorov<br>Publication Year: 2024<br>Contact: minmin.fu@yale.edu</p> <p>Overview<br>This repository contains the post-processing scripts and data used in the paper. It includes Jupyter notebooks for data analysis and plot generation, as well as the GCM output and utilities for adding land-sea masks and proxy sites.</p> <p>Repository Structure<br>notebooks/: Jupyter notebooks for analyzing data and creating plots.<br>data/: GCM output files for reproducing all figures in the paper.<br>utilities/: Functions for adding the land-sea mask and proxy sites.<br>PlioMIP2/: PlioMIP2 boundary conditions.</p> <p>Data<br>The data directory contains the GCM output files necessary for reproducing all figures. Ensure you have the necessary storage space as these files may be large.</p> <p>Utilities<br>The utilities directory contains utility functions, including:</p> <p>Land-Sea Mask Functions: Scripts to apply land-sea masks to the data.<br>Proxy Site Functions: Scripts to integrate proxy site data into the analysis.<br>The PlioMIP2 directory contains the boundary condition files used for the PlioMIP2 experiments.</p>

opencc-by-4.0May 2024View details →
zenodo32/100

Data and figure production code for 'Hydrological cycle amplification imposes spatial pattern on climate change response of ocean pH and carbonate chemistry'

<p>Time mean data, and python code, used to create figures in 'Hydrological cycle amplification imposes spatial pattern on climate change response of ocean pH and carbonate chemistry', Biogeosciences, Hogikyan and Resplandy 2024</p>

opencc-by-4.0Jul 2024View details →
zenodo32/100

A complete view of the atmospheric hydrologic cycle

<p>fig01.zip: Inside this zip there are 4 files which were used to make Figure 1. The 3 csv files are used to plot the trajectory pathways from their starting positions to the ending locations. The variable &#39;ntopo&#39; in the single netcdf file represents the ocean basin and global landmass mask.</p> <p>fig02_03_04.zip: In this zip there are 192 netcdf files and were used to produce Figure 2, 3 and 4. Each file is for a month and consists of evaporation, precipitation, meridional and zonal overturning stream function within and between the three major ocean basins and the global landmass. Here atl = Atlantic Ocean, pac=Pacific Ocean,ind = Indian Ocean, and lnd = global landmass.</p> <p>fig05.zip: In this zip there are also 192 netcdf files that were used to produce Figure 5.</p> <p>fig06.zip: Consists of 16 nectdf files that represent average residence time (days) of the atmospheric waters travelling from the surface evaporative regions to the precipitation areas. This residence time was calculated from the points where net evaporation exceeds a monthly mean value of 0.2 mm/day.</p> <p>table1.zip: This zip file was used to calculate the atmospheric freshwater transport within and between the ocean basins and land.</p>

opencc-by-4.0Oct 2021View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record