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304 results for “monsoons”
Figure 9 in Taxonomic revision of dragon lizards in the genus Diporiphora (Reptilia: Agamidae) from the Australian monsoonal tropics
Figure 9. Diporiphora albilabris: a, adult male in breeding colouration (registered specimen NMV D73860) from King Edward River crossing, Western Australia (photo: J. Melville); b, dorsal view of holotype WAM R43517, Mitchell Plateau, Western Australia.
Figure 7 in Taxonomic revision of dragon lizards in the genus Diporiphora (Reptilia: Agamidae) from the Australian monsoonal tropics
Figure 7. Diporiphora jugularis: a, adult male with breeding colouration, Iron Range, Queensland (photo: S. Wilson); b, syntype(s) AMS R40672– 4, juveniles, Cape Grenville, Cape York Peninsula, Queensland.
Figure 6 in Taxonomic revision of dragon lizards in the genus Diporiphora (Reptilia: Agamidae) from the Australian monsoonal tropics
Figure 6. Lateral images of the Diporiphora australis syntype NHMW 19821:1: a, Naturhistorisches Museum, Vienna (photo: J. Melville); b, taken from the original species description (Steindachner, 1867).
Figure 5 in Taxonomic revision of dragon lizards in the genus Diporiphora (Reptilia: Agamidae) from the Australian monsoonal tropics
Figure 5. Examples of the range of habitats in which the Diporiphora species of the Australian monsoon tropics occur: a, sandstone escarpment, Mitchell Plateau, Kimberley region, Western Australia; b, rocky outcrops in savannah woodlands, western Arnhem Land, Northern Territory; c, savannah woodlands, Kimberley region, Western Australia; d, savannah grasslands on cracking clay soils, floodplain of the Lennard River, Kimberley Region, Western Australia; e, savannah woodlands, western Arnhem Land, Northern Territory; f, arid spinifex grasses with scattered trees on stony ground, Tennant Creek, Northern Territory (photos: J. Melville).
Figure 4 in Taxonomic revision of dragon lizards in the genus Diporiphora (Reptilia: Agamidae) from the Australian monsoonal tropics
Figure 4. Diporiphora australis: a, adult, Karawatha, south-eastern Queensland (photo: S. Wilson); b, lectotype NHMW 19821.1, Australia ("Cape York, QLD" on type label); c, ventral view of head showing gular fold.
Figure 1. Bayesian 50 in Taxonomic revision of dragon lizards in the genus Diporiphora (Reptilia: Agamidae) from the Australian monsoonal tropics
Figure 1. Bayesian 50% majority-rules phylogenetic tree for Diporiphora based on mtDNA on ~1200 bp mitochondrial DNA (ND2). Asterisks on branches represent>99% posterior probability support. Clades highlighted in green are expanded, with phylogenetic relationships within each of the species groups reviewed in the current paper: a, D. australis; b, D. bennettii; c, D. bilineata. Species reviewed in the current paper are coloured to represent the taxonomic revision that is undertaken.
Figure 3 in Taxonomic revision of dragon lizards in the genus Diporiphora (Reptilia: Agamidae) from the Australian monsoonal tropics
Figure 3. Distributions of D. australis and D. jugularis based on specimens examined and collection records.
Figure 2. Images from micro X in Taxonomic revision of dragon lizards in the genus Diporiphora (Reptilia: Agamidae) from the Australian monsoonal tropics
Figure 2. Images from micro X-ray computed tomography scans showing the differences in pleurodont (canine) tooth number in the upper jaw: a, arrangement in D. bennettii species group; b, other species groups included in the current study.
Data for "Opposing changes in Indian Summer Monsoon Rainfall variability produced by orbital and anthropogenic forcing"
<p>The dataset for the CAM5 and LBM experiments is presented in the manuscript titled "Opposing changes in Indian summer monsoon rainfall variability produced by orbital and anthropogenic forcing. And the proxy data for the paper.</p>
Рис. 6. МоΔеΛирование экоΛогических ниш коΛораΔского жука ΔΛя ΔаΛьневосточного, европейского и североамериканского ареаΛов метоΔом метрического Δвухмерного шкаΛирования с применением коэффициента Жаккара Fig. 6. Models of ecological niches of the Colorado potato beetle for the Far Eastern, European, and North-American habitats (metric multidimensional scaling, Jaccard index) in Comparative characterization of the ecology of native (Henosepilachna vigintioctomaculata) and invasive (Leptinoatrsa decemlineata) species under the conditions of the monsoon climate in the southern part of the Russian Far East
Рис. 6. МоΔеΛирование экоΛогических ниш коΛораΔского жука ΔΛя ΔаΛьневосточного, европейского и североамериканского ареаΛов метоΔом метрического Δвухмерного шкаΛирования с применением коэффициента Жаккара Fig. 6. Models of ecological niches of the Colorado potato beetle for the Far Eastern, European, and North-American habitats (metric multidimensional scaling, Jaccard index)
Рис. 1. ЗасеΛенность посаΔок картофеΛя коΛораΔским жуком в Приморском крае (2008-2011 гг.) (по: Мацишина, Рогатных 2013) Примечание. БаΛΛ поврежΔения привеΔен по 6-баΛΛьной шкаΛе ВИЗР (Шапиро и Δр., 1980; 1993) in Comparative characterization of the ecology of native (Henosepilachna vigintioctomaculata) and invasive (Leptinoatrsa decemlineata) species under the conditions of the monsoon climate in the southern part of the Russian Far East
Рис. 1. ЗасеΛенность посаΔок картофеΛя коΛораΔским жуком в Приморском крае (2008-2011 гг.) (по: Мацишина, Рогатных 2013) Примечание. БаΛΛ поврежΔения привеΔен по 6-баΛΛьной шкаΛе ВИЗР (Шапиро и Δр., 1980; 1993)
The North American Monsoon GPS Hydrometeorological Network 2017: Flux and Precipitation Data
<p>Water, energy and carbon fluxes and ancillary meteorological measurements and precipitation data taken during The North American Monsoon GPS-Hydrometeorological Network 2017. The experiment was carried out during the summer of 2017 in the state of Sonora in northwestern Mexico.</p>
Linked collectors and determiners for: Species delimitation in the Gehyra nana (Squamata: Gekkonidae) complex: cryptic and divergent morphological evolution in the Australian Monsoonal Tropics, with the description of four new species.
Natural history specimen data linked to collectors and determiners held within, "Species delimitation in the Gehyra nana (Squamata: Gekkonidae) complex: cryptic and divergent morphological evolution in the Australian Monsoonal Tropics, with the description of four new species". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/5f73d28a-b9b5-4297-91c5-e14ce6f4db0b">https://bionomia.net/dataset/5f73d28a-b9b5-4297-91c5-e14ce6f4db0b</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/5f73d28a-b9b5-4297-91c5-e14ce6f4db0b">https://gbif.org/dataset/5f73d28a-b9b5-4297-91c5-e14ce6f4db0b</a>. Formatted as a Frictionless Data package.
Dataset from: Mechanical forcing of the North American monsoon by orography
<p>The core of the North American monsoon consists of a band of intense rainfall along the west coast of Mexico, commonly thought to be caused by thermal forcing from both land and the elevated terrain of that region. Here we use observations, a global climate model, and stationary wave solutions to show that this rainfall maximum is instead generated when Mexico's Sierra Madre mountains mechanically force an adiabatic stationary wave by diverting extratropical eastward winds toward the equator; eastward, upslope flow in that wave lifts warm and moist air to produce convective rainfall. Land surface heat fluxes do precondition the atmosphere for convection, particularly in summer afternoons, but these heat fluxes alone are insufficient for producing the observed rainfall maximum. These results, together with dynamical structures in observations and models, indicate that the core monsoon should be understood as convectively enhanced orographic rainfall in a mechanically forced stationary wave, not as a classic, thermally forced tropical monsoon. This has implications for the response of the North American monsoon to past and future global climate change, making trends in jet stream interactions with orography of central importance.</p>
Data used in "Climatology and variability of air mass transport from the boundary layer to the Asian monsoon anticyclone"
<p>The data presented here are needed to reproduce the analyses of the publication: Nützel, M., Brinkop, S., Dameris, M., Garny, H., Jöckel, P., Pan, L. L., and Park, M.: Climatology and variability of air mass transport from the boundary layer to the Asian monsoon anticyclone, Atmos. Chem. Phys., 22, 15659–15683, https://doi.org/10.5194/acp-22-15659-2022, 2022. A short explanation of the archived data is presented in the accompanying README.</p> <p>Note: In the previous data set version (<a href="https://doi.org/10.5281/zenodo.7275804">10.5281/zenodo.7275804</a>) one file was missing and is added here.</p> <p> </p> <p> </p>
Monsoon low-pressure system (LPS) tracks in ERA5 over India (1979-2019) with added environmental variables
<p>Derived from the LPS v3.0 dataset (https://doi.org/10.5281/zenodo.7568990). Filtered to monsoon LPSs (majority of track lifetime between June and September), with genesis over the Bay of Bengal and making landfall over India. Temporal resolution also reduced from hourly to six-hourly. This dataset accompanies the paper "Using interpretable gradient-boosted decision-tree ensembles to uncover novel dynamical relationships governing monsoon low-pressure systems" (DOI to follow).</p> <p>Aside from the core variables described in the main LPS dataset (linked above), this version includes a large number of environmental variables, listed below. All are computed from ERA5 unless otherwise stated, "<em>mean</em>" means that the variable is computed as an average within 400 km of the LPS centre, "<em>mcz</em>" means that the variable is computed as an average in the box [75-85°E, 18.5-27°N].<br> <em>mean_u200</em>: 200 hPa zonal wind (m s<sup>-1</sup>)<br> <em>mean_u850</em>: 850 hPa zonal wind (m s<sup>-1</sup>)<br> <em>mean_skt</em>: surface temperature (K)<br> <em>mean_land_frac</em>: fraction of area within 400 km that is over land<br> <em>mcz_tcwv</em>: mean total column water vapour over monsoon trough (kg m<sup>-2</sup>)<br> <em>vortex_depth</em>: mean_vort_500 x mean_vort_700/mean_vort_850<sup>2</sup><br> <em>over_land</em>: flag for LPS centre (Boolean)<br> <em>dvo850_dt</em>: rate of change of mean_vort_850 (10<sup>-5</sup> s<sup>-1</sup> day<sup>-1</sup>) <br> <em>acc_land_time</em>: accumulated time where over_land = True (hours)<br> <em>total_land_time</em>: final value of acc_land_time} for a given LPS (hours)<br> <em>qshear_850</em>: meridional shear of 850 hPa specific humidity over India (m<sup>3</sup> m<sup>-3</sup> (°)<sup>-1</sup>)<br> <em>ushear_850</em>: meridional shear of 850 hPa zonal wind over India (m s<sup>-1</sup> (°)<sup>-1</sup>)<br> <em>mean_cape</em>: CAPE (J kg<sup>-1</sup>)<br> <em>mcz_cape</em>: mean CAPE over the monsoon trough (J kg<sup>-1</sup>)<br> <em>mean_dthetae_dp_900_750</em>: d(theta_e)/dp between 900 and 750 hPa, a measurement of atmospheric stability (K hPa<sup>-1</sup>)<br> <em>mean_dthetae_dp_750_500</em>: d(theta_e)/dp between 750 and 500 hPa, a measurement of atmospheric stability (K hPa<sup>-1</sup>)<br> <em>mean_land_skt</em>: land surface temperature (K; NaN over ocean)<br> <em>mean_sst</em>: sea surface temperature (K; NaN over land)<br> <em>mean_swvl1</em>: soil moisture in the top layer (m<sup>3</sup> m<sup>-3</sup>; <7 cm; NaN over ocean)<br> <em>mean_swvl2</em>: soil moisture in the second layer (m<sup>3</sup> m<sup>-3</sup>; 7-28 cm; NaN over ocean)<br> <em>mean_swvl1_grad</em>: mean absolute horizontal gradient of mean_swvl1 (m<sup>3</sup> m<sup>-4</sup>)<br> <em>mean_swvl2_grad</em>: mean absolute horizontal gradient of mean_swvl2 (m<sup>3</sup> m<sup>-4</sup>)<br> <em>olr_90</em>: 90th percentile of negative OLR (i.e. ~90th percentile of cloud top height) (W m<sup>-2</sup>)<br> <em>olr_75</em>: 75th percentile of negative OLR (W m<sup>-2</sup>)<br> <em>olr_50</em>: 50th percentile of negative OLR (W m<sup>-2</sup>)<br> <em>qshear_850_background</em>: qshear\_850 averaged over the previous ten days (m<sup>3</sup> m<sup>-3</sup> (°)<sup>-1</sup>)<br> <em>ushear_850_background</em>: ushear\_850 averaged over the previous ten days (m<sup>3</sup> s<sup>-1</sup> (°)<sup>-1</sup>)<br> <em>mean_q_850</em>: 850 hPa specific humidity (m<sup>3</sup> m<sup>-3</sup>)<br> <em>orography_height</em>: elevation of land surface under LPS centre (m)<br> <em>peak_vorticity</em>: largest value of mean_vort_850} attained by a given LPS (10<sup>-5</sup> s<sup>-1</sup>)<br> <em>reached_peak</em>: False if peak\_vorticity has not been reached yet, else True<br> <em>mean_prcp_400</em>: mean precipitation rate within 400 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>mean_prcp_800</em>: mean precipitation rate within 800 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>max_prcp_400</em>: maximum precipitation rate within 400 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>max_prcp_800</em>: maximum precipitation rate within 800 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>mean_vimfd_400</em>: vertically integrated moisture flux convergence (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>mean_v200</em>: 200 hPa meridional wind speed (m s<sup>-1</sup>)<br> <em>mean_v500</em>: 500 hPa meridional wind speed (m s<sup>-1</sup>)<br> <em>mean_v850</em>: 850 hPa meridional wind speed (m s<sup>-1</sup>)<br> <em>mean_u500</em>: 500 hPa zonal wind speed (m s<sup>-1</sup>)<br> <em>zonal_speed</em>: zonal (x) component of LPS propagation velocity (m s<sup>-1</sup>)<br> <em>merid_speed</em>: meridional (y) component of LPS propagation velocity (m s<sup>-1</sup>)<br> <em>mean_prcp_imerg</em>: as mean_prcp_400 but computed using IMERG data, rather than ERA5 (kg m<sup>-2</sup> hr<sup>-1</sup>)</p> <p> </p> <p>qshear_850, ushear_850 and their backgrounds are averaged over 5° longitude either side of the LPS centre, with the gradient computed between 10°N and 27°N, reflecting the moisture and zonal wind gradients across the monsoon region.</p>
500-year periodic vegetation and monsoonal climate oscillations during the last deglaciation in East Asia
<p>1 Core Xiaolongwan description</p> <p>2 Age-depth models</p> <p>3 Pollen counts</p> <p>4 Pollen concentration</p> <p>5 Pollen percentage</p> <p>6 HHT Betula</p> <p>7 HHT Boreal Conifer with Herb</p> <p>8 HHT Artemisia</p> <p>9 HHT Broadleaved Tree</p> <p>10 Long chain <em>n</em>-alkanes δ<sup>13</sup>C</p>
Data from: River interlinking alters land-atmosphere feedback and changes the Indian summer monsoon.
<p>The dataset contains post-processed output from two experiments performed for Indian Summer Monsoon (June-September) from 1991-2012 using WRF-CLM4: CTL and IRR. Here, CTL represents WRF-CLM4 simulation with irrigation currently practiced in India. We use a modified irrigation module in CLM4 that better represents the Indian practices of irrigation by incorporating groundwater withdrawal and flood irrigation practiced over paddy fields. The module can be found at <a href="https://github.com/IMMM-SFA/WRF_CLM4_Irrigation">https://github.com/IMMM-SFA/WRF_CLM4_Irrigation</a> and <a href="https://doi.org/10.1029/2019GL083875">https://doi.org/10.1029/2019GL083875</a>. IRR simulation adds additional irrigation to CTL by increasing the percentage of irrigated area to 80% in regions where India's river-interlinking projects target an increase in the culturable command area.</p> <p>The post-processed output contains the following variables:</p> <ol> <li>Mean Daily Temperature</li> <li>Daily Maximum Temperature</li> <li>Latent Heat Flux</li> <li>Sensible Heat Flux</li> <li>Relative Humidity</li> <li>U-Wind at Pressure levels</li> <li>V-Wind at Pressure levels</li> <li>Net-Solar Radiation on Land</li> <li>Soil Moisture</li> </ol> <p>Irrigation input files for CTL and IRR simulations of WRF-CLM4 are also included.</p>
Inorganic nitrogen, microbial ecoenzymatic activities, and organic matter in soils collected from the Monsoon Rainfall Manipulation Experiment (MRME), Sevilleta National Wildlife Refuge, New Mexico during the 2014 growing season
Drylands are characterized by a pulse dynamics framework in which episodic rain events trigger brief pulses of biological activity and resource availability that regulate primary production in these ecosystems. Relatively small rain events can stimulate microbial processes like decomposition that release inorganic nitrogen needed by plant processes, which typically also depend on soil moisture received from larger rain events. Little is known how changes in rainfall patterns may affect plant available nitrogen in dryland soils, particularly across temporal scales. Therefore, we conducted a study to examine the daily and seasonal responses of plant available nitrogen to rain events that differed in size and frequency throughout a summer monsoon in a northern Chihuahuan Desert grassland located in the Sevilleta National Wildlife Refuge, New Mexico, USA. This data package, which accompanies an associated manuscript (Brown et al. 2022), contains measurements of inorganic nitrogen, nitrogen-acquiring microbial ecoenzymatic activities, and organic matter in soils collected from the Monsoon Rainfall Manipulation Experiment (MRME) during the 2014 summer growing season.
Monsoon Rainfall Manipulation Experiment (MRME) Soil Moisture Data from the Sevilleta National Wildlife Refuge, New Mexico (7/2007 - 8/2009)
The Monsoon Rainfall Manipulation Experiment (MRME) is to understand changes in ecosystem structure and function of a semiarid grassland caused by increased precipitation variability, which alters the pulses of soil moisture that drive primary productivity, community composition, and ecosystem functioning. The overarching hypothesis being tested is that changes in event size and variability will alter grassland productivity, ecosystem processes, and plant community dynamics. In particular, we predict that many small events will increase soil CO2 effluxes by stimulating microbial processes but not plant growth, whereas a small number of large events will increase aboveground NPP and soil respiration by providing sufficient deep soil moisture to sustain plant growth for longer periods of time during the summer monsoon.
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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.
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.
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.
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.
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.