ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Data  (14)
Collection
Keywords
Publisher
Years
  • 1
    Publication Date: 2023-04-11
    Keywords: CloudCA_Italy_Grid_1x1; Cloud cover anomaly; DATE/TIME; LATITUDE; LONGITUDE; Visual observation
    Type: Dataset
    Format: text/tab-separated-values, 3808 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2023-04-11
    Keywords: CloudCA_Italy_Grid_1x1; Cloud cover anomaly; DATE/TIME; LATITUDE; LONGITUDE; Visual observation
    Type: Dataset
    Format: text/tab-separated-values, 3808 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2023-04-11
    Keywords: CloudCA_Italy_Grid_1x1; Cloud cover anomaly; DATE/TIME; LATITUDE; LONGITUDE; Visual observation
    Type: Dataset
    Format: text/tab-separated-values, 3808 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2023-04-11
    Keywords: CloudCA_Italy_Grid_1x1; Cloud cover anomaly; DATE/TIME; LATITUDE; LONGITUDE; Visual observation
    Type: Dataset
    Format: text/tab-separated-values, 3808 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 5
    Publication Date: 2023-04-11
    Keywords: CloudCA_Italy_Grid_1x1; Cloud cover anomaly; DATE/TIME; LATITUDE; LONGITUDE; Visual observation
    Type: Dataset
    Format: text/tab-separated-values, 3808 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 6
    facet.materialart.
    Unknown
    PANGAEA
    In:  Supplement to: Wild, Martin; Ohmura, Atsumu; Schär, Christoph; Müller, Guido; Folini, Doris; Schwarz, Matthias; Hakuba, Maria Z; Sanchez-Lorenzo, Arturo (2017): The Global Energy Balance Archive (GEBA) version 2017: a database for worldwide measured surface energy fluxes. Earth System Science Data, 9(2), 601-613, https://doi.org/10.5194/essd-9-601-2017
    Publication Date: 2024-02-16
    Description: The Global Energy Balance Archive (GEBA) is a database for the central storage of the worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 dataset, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and contains in its 2017 version around 500.000 monthly mean entries of various surface energy balance components measured at 2500 locations. The database contains observations from 15 surface energy flux components, with the most widely measured quantity available in GEBA being the shortwave radiation incident at the Earth's surface (global radiation). Many of the historic records extend over several decades. GEBA contains monthly data from a variety of sources, namely from the World Radiation Data Centre (WRDC) in St. Petersburg, from national weather services, from different research networks (BSRN, ARM, SURFRAD), from peer-reviewed publications, project and data reports, and from personal communications. Quality checks are applied to test for gross errors in the dataset. GEBA has played a key role in various research applications, such as in the quantification of the global energy balance, in the discussion of the anomalous atmospheric shortwave absorption, and in the detection of multi-decadal variations in global radiation, known as "global dimming" and "brightening". GEBA is further extensively used for the evaluation of climate models and satellite-derived surface flux products. On a more applied level, GEBA provides the basis for engineering applications in the context of solar power generation, water management, agricultural production and tourism. GEBA is publicly accessible through the internet via http://www.geba.ethz.ch.
    Type: Dataset
    Format: application/zip, 1.4 MBytes
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 7
    Publication Date: 2024-04-12
    Description: Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In-situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. Therefore, we here provide four datasets comprising: 1. Harmonized, standardized and aggregated in situ observations of SEB components at 64 vegetated and glaciated sites north of 60° latitude, in the time period 1994-2021 2. A description of all study sites and associated environmental conditions, including the vegetation types, which correspond to the classification of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019). 3. Data generated in a literature synthesis from 358 study sites on vegetation or glacier (〉=60°N latitude) covered by 148 publications. 4. Metadata, including data contributor information and measurement heights of variables associated with Oehri et al. 2022.
    Keywords: Arctic; ArcticTundraSEB; Arctic Tundra Surface Energy Budget; dry tundra; Eddy covariance; eddy heat flux; glacier; graminoids; ground heat flux and net radiation; harmonized data; high latitude; Land-Atmosphere; Land-cover; latent and sensible heat; latent heat flux; longwave radiation; meteorological data; observatory data; Peat bog; Radiation fluxes; Radiative energy budget; sensible heat flux; shortwave radiation; shrub tundra; surface energy balance; synthetic data; tundra vegetation; wetland
    Type: Dataset
    Format: application/zip, 4 datasets
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 8
    Publication Date: 2024-04-20
    Keywords: ASCII file; ASCII file (MD5 Hash); CloudCA_Italy_Grid_1x1; File content; Visual observation
    Type: Dataset
    Format: text/tab-separated-values, 10 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 9
    Publication Date: 2024-04-02
    Description: In the framework of the global energy balance, the radiative energy exchanges between Sun, Earth and space are now accurately quantified from new satellite missions. Much less is known about the magnitude of the energy flows within the climate system and at the Earth surface, which cannot be directly measured by satellites. In addition to satellite observations, here we make extensive use of the growing number of surface observations to constrain the global energy balance not only from space, but also from the surface. We combine these observations with the latest modeling efforts performed for the 5th IPCC assessment report to infer best estimates for the global mean surface radiative components. Our analyses favor global mean downward surface solar and thermal radiation values near 185 and 342 Wm**-2, respectively, which are most compatible with surface observations. Combined with an estimated surface absorbed solar radiation and thermal emission of 161 Wm**-2 and 397 Wm**-2, respectively, this leaves 106 Wm**-2 of surface net radiation available for distribution amongst the non-radiative surface energy balance components. The climate models overestimate the downward solar and underestimate the downward thermal radiation, thereby simulating nevertheless an adequate global mean surface net radiation by error compensation. This also suggests that, globally, the simulated surface sensible and latent heat fluxes, around 20 and 85 Wm**-2 on average, state realistic values. The findings of this study are compiled into a new global energy balance diagram, which may be able to reconcile currently disputed inconsistencies between energy and water cycle estimates.
    Keywords: Alaska, USA; Algeria; Alice Springs; Antarctica; ASP; Australia; AWIPEV; AWIPEV_based; BAR; Barrow; Baseline Surface Radiation Network; BER; Bermuda; BIL; Billings; BON; Bondville; BOS; BOU; Boulder; Brazil; BSRN; CAB; Cabauw; CAM; Camborne; Canada; CAR; Carpentras; Cener; Chesapeake Light; China; CLH; CNR; COC; Cocos (Keeling) Islands; Cocos Island; Colorado, United States of America; Cosmonauts Sea; DAA; DAR; Darwin; Darwin Met Office; De Aar; Desert Rock; DRA; Dronning Maud Land, Antarctica; DWN; E13; Estonia; FLO; Florianopolis; Fort Peck; FPE; France; GCR; Georg von Neumayer; Germany; Goodwin Creek; GVN; Illinois, United States of America; ILO; Ilorin; ISH; Ishigakijima; Israel; IZA; Izaña; Japan; KWA; Kwajalein; LER; Lerwick; LIN; Lindenberg; Macdonnell Ranges, Northern Territory, Australia; MAN; Mississippi, United States of America; Momote; Monitoring station; MONS; Montana, United States of America; NAU; Nauru; Nauru Island; Neumayer_based; NEUMAYER III; Nevada, United States of America; Nigeria; North Pacific Ocean; NYA; Ny-Ålesund; Ny-Ålesund, Spitsbergen; Oklahoma, United States of America; PAL; Palaiseau, SIRTA Observatory; Papua New Guinea; PAY; Payerne; Pennsylvania, United States of America; PSU; REG; Regina; Rock Springs; São Martinho da Serra; Saudi Arabia; SBO; Sede Boqer; Shetland Island, United Kingdom; Sioux Falls; SMS; Solar Village; South Africa; South Atlantic Ocean; South Dakota, United States of America; Southern Great Plains; South Pole; SOV; Spain, Sarriguren, Navarra; SPO; Switzerland; SXF; SYO; Syowa; TAM; Tamanrasset; TAT; Tateno; Tenerife, Spain; The Netherlands; TOR; Toravere; United Kingdom; XIA; Xianghe
    Type: Dataset
    Format: 6378 datasets
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 10
    Publication Date: 2024-04-22
    Description: Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset describes the environmental conditions for 64 tundra and glacier sites (〉=60°N latitude) across the Arctic, for which in situ measurements of surface energy budget components were harmonized (see Oehri et al. 2022). These environmental conditions are (proxies of) potential drivers of SEB-components and could therefore be called SEB-drivers. The associated environmental conditions, include the vegetation types graminoid tundra, prostrate dwarf-shrub tundra, erect-shrub tundra, wetland complexes, barren complexes (≤ 40% horizontal plant cover), boreal peat bogs and glacier. These land surface types (apart from boreal peat bogs) correspond to the main classification units of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019). For each site, additional climatic and biophysical variables are available, including cloud cover, snow cover duration, permafrost characteristics, climatic conditions and topographic conditions.
    Keywords: Arctic; Arctic_SEB_CA-SCB; Arctic_SEB_CP1; Arctic_SEB_Dye-2; Arctic_SEB_EGP; Arctic_SEB_FI-Lom; Arctic_SEB_GL-NuF; Arctic_SEB_GL-ZaF; Arctic_SEB_GL-ZaH; Arctic_SEB_KAN_B; Arctic_SEB_KAN_L; Arctic_SEB_KAN_M; Arctic_SEB_KAN_U; Arctic_SEB_KPC_L; Arctic_SEB_KPC_U; Arctic_SEB_MIT; Arctic_SEB_NASA-E; Arctic_SEB_NASA-SE; Arctic_SEB_NASA-U; Arctic_SEB_NUK_K; Arctic_SEB_NUK_L; Arctic_SEB_NUK_N; Arctic_SEB_NUK_U; Arctic_SEB_QAS_A; Arctic_SEB_QAS_L; Arctic_SEB_QAS_M; Arctic_SEB_QAS_U; Arctic_SEB_RU-Che; Arctic_SEB_RU-Cok; Arctic_SEB_RU-Sam; Arctic_SEB_RU-Tks; Arctic_SEB_RU-Vrk; Arctic_SEB_Saddle; Arctic_SEB_SCO_L; Arctic_SEB_SCO_U; Arctic_SEB_SE-St1; Arctic_SEB_SJ-Adv; Arctic_SEB_SJ-Blv; Arctic_SEB_SouthDome; Arctic_SEB_Summit; Arctic_SEB_TAS_A; Arctic_SEB_TAS_L; Arctic_SEB_TAS_U; Arctic_SEB_THU_L; Arctic_SEB_THU_U; Arctic_SEB_Tunu-N; Arctic_SEB_UPE_L; Arctic_SEB_UPE_U; Arctic_SEB_US-A03; Arctic_SEB_US-A10; Arctic_SEB_US-An1; Arctic_SEB_US-An2; Arctic_SEB_US-An3; Arctic_SEB_US-Atq; Arctic_SEB_US-Brw; Arctic_SEB_US-EML; Arctic_SEB_US-HVa; Arctic_SEB_US-ICh; Arctic_SEB_US-ICs; Arctic_SEB_US-ICt; Arctic_SEB_US-Ivo; Arctic_SEB_US-NGB; Arctic_SEB_US-Upa; Arctic_SEB_US-xHE; Arctic_SEB_US-xTL; ArcticTundraSEB; Arctic Tundra Surface Energy Budget; Aspect; Aspect, coefficient of variation; Calculated average/mean values; Cloud cover; Cloud cover, standard deviation; Cloud top pressure; Cloud top pressure, standard deviation; Cloud top temperature; Cloud top temperature, standard deviation; Conrad's continentality index; Daily maximum; Daily mean; Data source; Date/Time of event; dry tundra; Eddy covariance; eddy heat flux; ELEVATION; Elevation, standard deviation; Event label; Field observation; glacier; graminoids; ground heat flux and net radiation; harmonized data; high latitude; Humidity, relative; Land-Atmosphere; Land-cover; Land cover classes; Land cover type; latent and sensible heat; latent heat flux; LATITUDE; Location ID; LONGITUDE; longwave radiation; Mean values; Median values; meteorological data; Number of vegetation types; observatory data; Peat bog; Permafrost, type; Permafrost extent; Permafrost ice content, description; Precipitation; Precipitation, coefficient of variation; Precipitation, daily, maximum; Precipitation, snow; Precipitation, sum; Pressure, atmospheric; p-value; Radiation fluxes; Radiative energy budget; Reference/source; sensible heat flux; Shannon Diversity Index; Shannon Diversity Index, maximum; shortwave radiation; shrub tundra; Site; Slope; Slope, coefficient of variation; Slope, mathematical; Snow, onset, day of the year; Snow cover, number of days; Snowfall, coefficient of variation; Snow-free days; Snow type; Soil water content, volumetric; Species present; Summer warmth index; surface energy balance; synthetic data; Temperature, air, annual mean; Temperature, air, coefficient of variation; Temperature, annual mean range; tundra vegetation; Type of study; Uniform resource locator/link to reference; Vapour pressure deficit; Vegetation type; wetland; Wind speed; Zone
    Type: Dataset
    Format: text/tab-separated-values, 4705 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...