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opencc-by-4.0Jan 2023View details →

MetUM Simulations of 2nd February Case Study

This repository contains data to support the publication "Kilometre-scale simulations of trade-wind cumulus capture processes of mesoscale organization" submitted to JAMES. The data is from Met Office Unified Model simulations of the 2nd February 2020 EUREC4A case study. There are 3 kilometre-scale resolutions (1.1km, 2.2km, 4.4km) nested in ERA5 boundary conditions, and two 100m-scale resolutions (300m, 500m) nested in the 1.1km simulation. The simulations are initialised at 1st February 00:00. Also included are two sensitivity tests with the kilometre-scale simulations run with 1) evaporation of rain switched off and 2) a later start time (2nd February 00:00). The code used to analyse this data is at <a href="https://github.com/leosaffin/moisture_tracers">https://github.com/leosaffin/moisture_tracers</a>. The data is across four folders (full directory structure at the bottom) regridded - Contains model data regridded to the lowest resolution (4.4km) either fixed on the 100m-scale domain (coarse_grid) or following a Lagrangian trajectory for the kilometre-scale resolutions and sensitivity tests (lagrangian_grid). There are also files with model data following a different trajectory and smaller domain, to be consistent with <a href="https://doi.org/10.1029/2021MS002619">Narenpitak et al. (2021)</a>, for the default kilometre-scale simulations (lagrangian_grid_Ron_Brown). trajectories - Contains all the trajectories used to extract the domains in "regridded" simulated_satellite - Contains model simulated brightness temperatures from 11Z-21Z for each resolution simulation. These simulations were run with the same setup but on a different machine and also include a 150m-resolution simulation. full_grid - Contains 2d model output a T+36 from the 500m and 1.1km simulations which were used to make figure 1 in the paper. Full directory structure: <ul> <li>full_grid <ul> <li>D100m_500m <ul> <li>model-diagnostics_20200201T0000_T+35.nc</li> </ul> </li> <li>km1p1 <ul> <li>model-diagnostics_20200201T0000_T+35.nc</li> </ul> </li> </ul> </li> <li>regridded <ul> <li>D100m_300m <ul> <li>coarse_grid <ul> <li>20200201T0000_D100m_300m_T+{24..48}_coarse_grid.nc</li> </ul> </li> </ul> </li> <li>D100m_500m <ul> <li>coarse_grid <ul> <li>20200201T0000_D100m_500m_T+{24..48}_coarse_grid.nc</li> </ul> </li> </ul> </li> <li>km1p1 <ul> <li>coarse_grid <ul> <li>20200201T0000_km1p1_T+{24..48}_coarse_grid.nc</li> </ul> </li> <li>lagrangian_grid <ul> <li>20200201T0000_km1p1_T+{01..48}_lagrangian_grid.nc</li> <li>20200202T0000_km1p1_T+{01..24}_lagrangian_grid.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_no_evap.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_Ron_Brown.nc</li> </ul> </li> </ul> </li> <li>km2p2 <ul> <li>coarse_grid <ul> <li>20200201T0000_km2p2_T+{24..48}_coarse_grid.nc</li> </ul> </li> <li>lagrangian_grid <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid.nc</li> <li>20200202T0000_km2p2_T+{01..24}_lagrangian_grid.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_no_evap.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_Ron_Brown.nc</li> </ul> </li> </ul> </li> <li>km4p4 <ul> <li>coarse_grid <ul> <li>20200201T0000_km4p4_T+{24..48}_coarse_grid.nc</li> </ul> </li> <li>lagrangian_grid <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid.nc</li> <li>20200202T0000_km4p4_T+{01..24}_lagrangian_grid.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_no_evap.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_Ron_Brown.nc</li> </ul> </li> </ul> </li> </ul> </li> <li>regridded_large_scale <ul> <li>km1p1 <ul> <li>lagrangian_grid <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_large_scale.nc</li> <li>20200202T0000_km1p1_T+{01..24}_lagrangian_grid_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_no_evap_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km1p1_T+{24..48}_lagrangian_grid_Ron_Brown_large_scale.nc</li> </ul> </li> </ul> </li> <li>km2p2 <ul> <li>lagrangian_grid <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_large_scale.nc</li> <li>20200202T0000_km2p2_T+{01..24}_lagrangian_grid_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_no_evap_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km2p2_T+{24..48}_lagrangian_grid_Ron_Brown_large_scale.nc</li> </ul> </li> </ul> </li> <li>km4p4 <ul> <li>lagrangian_grid <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_large_scale.nc</li> <li>20200202T0000_km4p4_T+{01..24}_lagrangian_grid_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_no_evap <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_no_evap_large_scale.nc</li> </ul> </li> <li>lagrangian_grid_Ron_Brown <ul> <li>20200201T0000_km4p4_T+{24..48}_lagrangian_grid_Ron_Brown_large_scale.nc</li> </ul> </li> </ul> </li> </ul> </li> <li>simulated_satellite <ul> <li>UMRA3p3_MOapp_20200201T0000Z_HMscale_2D_Hourly_150m_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_HMscale_2D_Hourly_300m_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_HMscale_2D_Hourly_500m_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_KMscale_2D_Hourly_1p1km_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_KMscale_2D_Hourly_2p2km_Baseline_goes16_brt.nc</li> <li>UMRA3p3_MOapp_20200201T0000Z_KMscale_2D_Hourly_4p4km_Baseline_goes16_brt.nc</li> </ul> </li> <li>trajectories <ul> <li>trajectories_20200201_km1p1_500m.pkl</li> <li>trajectories_20200201_km2p2_500m.pkl</li> <li>trajectories_20200201_km4p4_500m.pkl</li> <li>trajectories_20200201_km1p1_500m_no_evap.pkl</li> <li>trajectories_20200201_km2p2_500m_no_evap.pkl</li> <li>trajectories_20200201_km4p4_500m_no_evap.pkl</li> <li>trajectories_20200201_km1p1_500m_Ron_Brown.pkl</li> <li>trajectories_20200201_km2p2_500m_Ron_Brown.pkl</li> <li>trajectories_20200201_km4p4_500m_Ron_Brown.pkl</li> <li>trajectories_20200202_km1p1_500m.pkl</li> <li>trajectories_20200202_km2p2_500m.pkl</li> <li>trajectories_20200202_km4p4_500m.pkl</li> </ul> </li> </ul>

PERTEMUAN 6_02 FEBRUARY 2023_PPh WAJIB PAJAK_UNIVERSITAS WIJAYA PUTRA _PRIGEN_JAM 18-00-20.30

Capaian Pembelajaran Mata Kuliah (CPMK) Mahasiswa Mampu mengetahui PPh WP Badan dan Bentuk Usaha Tetap (BUT).   Indikator Pembelajaran Konsep PPh Wajib Pajak Badan : Mampu menguasai dan menjelaskan mengenai PPh WP Badan 1.Subjek PPh Wp Badan 2.Obyek PPh Badan dan BUT

PERTEMUAN PERTAMA_6 FEBRUARY 2023_ Penjelasan Rencana Pembelajaran Semester (RPS) Kontrak Kuliah Statistik_JAM 20.00-21.30

Capaian Pembelajaran Mata Kuliah ICPMK) Setelah mengikuti perkuliahan ini mahasiswa mampu mengaplikasikan statistika dalam memecahkan masalah, dan  menggunakan serta menerapkannya dalam pengolahan dan analisa data dalam penelitian kuantitatif dengan tepat.

PERTEMUAN 1_ 7 FEBRUARY 2023_PENJELASAN RPS, RPP, DAN KONTRAK KULIAH AKUNTANSI KEUANGAN LANJUTAN 2_UNIVERSITAS GRESIK JAM 18.00-20.00

Capaian Pembelajaran Mata Kuliah (CPMK) Setelah mengikuti perkuliahan ini mahasiswa mampu mengaplikasikan penyusunan laporan keuangan untuk Akuntansi Penggabungan Usaha baik secara marger maupun konsolidasi, akuisisi langsung / tidak langusung, menctat laba transaksi antar perusahan serta laporan keuangan perubahan kepemilikan dari berbagai macam organisasi bisnis

PERTEMUAN 1_07 FEBRUARY 2023_PENJELASAN RPS, RPP, KONTRAK KULIAH AKUNTANSI KEUANGAN MENENGAH 2_UNIVERSITAS GRESIK JAM 20.00-21.30

Capaian Pembelajarn Mata Kuliah (CPMK) Setelah mengikuti perkuliahan ini mahasiswa Mampu menyusun laporan keuangan sesuai kaidah pengakuan, pengukuran, penyajian dan pengungkapan dalam PSAK dan SAK ETAP terkini. Pendukung Mata Ajar Mampu menggunakan dengan konsep professional judgement dalam tatanan lokal maupun global dalam menyusun dan memeriksa laporan keuangan

LPL14 - February 2023

Measurements of LPL14 (Ilha das Flores) in February 2023 Flores Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL14">info</a>

LPL4 - February 2023

Measurements of LPL4 (Ilha do Corvo) in February 2023 Corvo Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL4">info</a>

LPL3 - February 2023

Measurements of LPL3 (Madeira East Coast) in February 2023 Madeira Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL3">info</a>

LPL5 - February 2023

Measurements of LPL5 (Tejeda) in February 2023 Gran Canaria Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL5">info</a>

LPL1 - February 2023

Measurements of LPL1 (Teide NP) in February 2023 Tenerife Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL1">info</a>

SG - February 2023

Measurements of SG (Global) in February 2023 Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/SG">info</a>

LPL17 - February 2023

Measurements of LPL17 (Isla de Tabarca) in February 2023 Alicante Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL17">info</a>

LPL8 - February 2023

Measurements of LPL8 (Timanfaya NP) in February 2023 Lanzarote Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL8">info</a>

opencc-by-4.0Mar 2023View details →

Resolutions of Local Maidans, November 2013 - February 2014

This is a collection of local Maidans' resolutions – primary documents composed and voted by local Maidan assemblies from November 2013 through February 2014. Local Maidan resolutions are an important source of information about the dynamics of local protests and the contents of the protesters' claims during Ukraine’s 2013-14 Euromaidan social movement. The data are presented as an MS Excel document detailing the date, location (locality and oblast), actual text and source of a local Maidan resolution. Background In 2013-14, residents in all regions of Ukraine gathered for local protest rallies, called Maidans, people’s “viches” and meetings (jointly referred to as “local Maidans”), and issued demands towards local and national authorities. To add credibility to local Maidans' decisions, to disseminate information on protest and foster mobilization, these local assemblies had often put their claims in writing by issuing an assembly resolution and voting for its text. Resolutions were picked up and published by individual users of social media, local offices of public organizations and political parties, and local media. Using this and other outreach strategies, local Maidan communities around the country attempted to pressure local authorities, weaken the regime’s control and push the government into concessions over national and local issues. Data Collection Methodology I collected data on local Maidans' resolutions during 2014-15 by addressing the members of protest assemblies and organizations, contacting Ukrainian archives and museums, and by a complex Internet search algorithm that I designed. In particular, during 2013-14 local Maidans held All-Ukrainian Forums of Euromaidans to share experiences and coordinate efforts. I contacted the organizing committee and asked them to distribute my call for the collection of the original documents produced by local Maidans among Forums’ participants. I also contacted institutions in Ukraine that work on preserving Maidan history. Among these are the Lviv Oblast Archive, which presented an exhibit of documents on the Euromaidan movement in Lviv oblast, and the Ukrainian Institute of National Memory, which launched the Maidan archive in cooperation with the CSO “Maidan Museum.” I performed an Internet search using the following advanced Google search algorithms in Ukrainian and Russian: <ul> <li>(viche OR meeting) AND (resolution OR demand OR statement) AND (city OR rayon OR oblast);</li> <li>Regional Maidan AND resolution AND (viche OR meeting);</li> <li>(Maidan or Euromaidan) AND resolution AND (viche OR meeting).</li> </ul> In some cases, the text I found was titled e.g. “the resolution of the second city viche” (italics added), which suggested there might be several texts produced in the same locality. In such cases, I browsed the websites which published the initial text for the keywords of the algorithm. Additionally, I devised a location-focused search algorithm (in either Ukrainian or Russian, depending on the language of the initially-found text). For example, [(viche OR protest) AND (resolution OR demands OR address) AND Chernivtsy] or [Chernivtsy AND resolution AND (second OR third) AND city viche]. I also searched for videos of adopting Maidans' resolutions on YouTube – the biggest global source of video content, using the following algorithms, in Ukrainian and Russian: <ul> <li>Maidan resolution;</li> <li>Euromaidan resolution;</li> <li>Resolution of people’s viche.</li> </ul> Data Cleaning I applied the following filters to the documents I collected: <ol> <li>the text had to reflect the meeting of a local community, and thus decisions of local and regional authorities who claimed to speak “on behalf of local people” were separated from this collection;</li> <li>the text of a resolution had to be presented in full -- I disregarded newspaper interpretations and excerpts; and</li> <li>a source had to have a clear indication of both the date and the place of the event where a resolution was adopted.</li> </ol> Data Characteristics For November 2013 to February 2014, I found 94 resolutions that were adopted by 57 localities in 20 Ukraine's oblasts. Among these 57 localities, 31 are cities; of these 15 are oblast centers. The remaining 26 resolutions were adopted by the communities representing rayons, which are composed of towns and villages. Localities are quite diverse in size, ranging from 1.4 million residents (Kharkiv, Kharkiv oblast) to only 20,000 residents (Truskavets, Lviv oblast). On average, localities that adopted a Maidan resolution had below 200,000 residents; the median locality had 70,000 residents. The earliest resolutions date back to November 24, 2013. The most recent one was voted on February 27, 2014. The minimum number of resolutions adopted by a locality in this collection is one and the maximum is five. The collection is composed of 94 resolutions, declarations, addresses and decisions of local Maidans, which are jointly referred to as resolutions. A typical resolution is a one-page document, containing statements of protesters’ self-identification, the reasons for the protest, the demands to national and local authorities, calls for mobilization, and declarations of support or condemnation. Most of the local Maidan resolutions are in Ukrainian, and six texts are in Russian. It is important to note that by texts I refer mostly to the content of text documents. There were, however, few exceptions when I found the links to video or graphic evidence of the resolution proclamation. About half of the resolutions (55 texts out of 94) come from local media and include those published on local media outlets’ web pages and YouTube channels. These include 34 newspaper articles - usually short informative pieces, providing an introduction, some background information on the protests, a resolution text in full, and sometimes brief interviews with the speakers and the participants. In 18 cases, only a resolution text was published. In three cases I only have the videos of resolution adoption, usually accompanied by background information. Out of 55 cases, 25 news posts had no reference to the author at all, 18 were marked as “editorial”, and the remaining 12 news posts indicated the name of the journalist. The sources of the texts varied. Twelve texts were found on the web pages of local authorities (rayon and city councils, rayon state administrations). The other sources include CSOs' web pages, social media channels and blogs (12 texts), and local branches of political parties (five texts). Ten texts were posted by individual protesters on their private social media profiles (Facebook, personal YouTube channels, and blogs). Potential Data Limitations The local Maidan data is not a sample, but rather an attempt to collect the whole of the phenomenon, albeit within specific parameters. I attempted a comprehensive collection of local Maidan resolutions within a particular definition of local Maidan. I also limited the collection to a particular time. During Euromaidan not every locality had a protest and not every protest group chose to adopt a resolution. In some instances, the information about both the protest and the resolution can be found, but the text of the actual document remains out of reach.  Yet, there may be some localities, which had both the protest and the resolution, that are not in my collection. These considerations illustrate the complexity of Ukrainian Euromaidan – a spontaneous, grassroots movement without open central coordination and record-keeping, and highlight that the exact universe of local Maidans cannot be fully assessed. Acknowledging this complexity, this collection is likely the largest and most complete of its kind.

opencc-by-4.0Mar 2023View details →

CA Jobs Dataset: Comprehensive Job Count Information by Company - February, 2023

<a href="https://tarta.ai/open-data/datasets/number-of-jobs-by-company-in-CA-0223">This dataset</a> provides a comprehensive view of the job market, highlighting the companies and cities that have the highest number of job opportunities. The <a href="https://tarta.ai/open-data/datasets">Tarta.ai dataset</a> is a valuable resource for anyone interested in the job market and provides a comprehensive view of the employment landscape across different industries and regions. This dataset was created by Tarta.ai and contains information on the number of jobs by company and city in California, with features such as: • Company name • City • State • Number of active jobs

dryad36/100

Vessel traffic observations and associated waterbird surveys, March 2020 – February 2021, Roberts Point and Ogden Point, Victoria, BC, Canada

The coastal waters of southern British Columbia, Canada, encompass habitat of international conservation significance to coastal and marine birds, including sizeable areas designated in the early 1900s as Migratory Bird Sanctuaries (MBS) to protect overwintering waterfowl from hunting near urban centres. Two of these, Shoal Harbour (SHMBS) and Victoria Harbour (VHMBS), have seen significant marine infrastructure development in recent decades and experience considerable vessel traffic. We conducted a pilot study using shore-based observers to develop small-vessel baselines for the winter months when regional waterbird numbers are highest. During our surveys, we recorded considerable inter-site variability in vessel traffic characteristics, with one site (SHMBS) a source of nearly twice as many vessels in total as the other (VHMBS). For waterbirds, hourly 3-minute 'snapshot' surveys, combined with daily tallies of incidental observations, showed that community composition also varied by locality, with one site dominated by gulls (Laridae), cormorants (Phalacrocoracidae), and seaducks (Tribe Mergini), and the other by gulls, cormorants, and alcids (Alcidae). Our results demonstrate that fine-scale local variability must be taken into account when managing for vessel traffic disturbance of waterbirds, particularly at sites of high human population density and increasing coastal development. Results are in press in PLoS ONE (doi:10.1371/journal.pone.0283791).

opencc-by-4.0May 2023View details →

6th February 2023 Turkish Earthquake 1-30s RINEX database

Database used to study the ionospheric response to the 6th of February Turkish earthquake. The database contains both 1s and 30s time resolution RINEX

opencc-by-4.0May 2023View details →

Brightness Temperature Spectra 400-1200 cm**-1 from satellite METEOR-29 instrument SI-1 in February 1979 along with radiative transfer simulations from 4 different reanalyses, clear scenes only over ocean

This dataset is published in support of a tentative journal publication in a peer-reviewed journal. The full data record is scheduled for release under DOI:10.15770/EUM_SEC_CLM_0086

dryad36/100

Mojave Bell's Sparrow (Artemisiospiza bellii canescens) and Sagebrush Sparrow (Artemisiospiza nevadensis) captures at western Arizona sites, February 2014

Bell's Sparrows (Artemisiospiza belli)) have only recently been recognized as distinct from Sagebrush Sparrows (A. nevadensis), and the "Mojave" subspecies (A. b. canescens) shares an overlapping wintering distribution with Sagebrush Sparrow in the Mojave and Sonoran deserts of southeastern California and western Arizona. We lack understanding of the 2 species' respective wintering habitat preferences and the degree to which they interact or segregate on their wintering grounds due to the difficulty in separating them in the field and to their previous classification as one species. We captured and sampled 74 Artemisiospiza sparrows from 5 sites across western Arizona, supporting field identifications with genetic analyses of mitochondrial DNA to confirm species and molecular sexing of sampled individuals. Bell's Sparrows and Sagebrush Sparrows segregated into different habitat types across our study area, with only one species detected at 4 of 5 study sites. Bell's Sparrows comprised 82 percent (n = 33) of Artemisiospiza sparrows captured at the 5th site at Robbins Butte. Broadly, Sagebrush Sparrows were found in more upland, well-drained locations that were sparsely vegetated with xerophytic scrub. Bell's Sparrows were found in more vegetated locations with halophytic Mojave seablite (Suaeda nigra) and saltbush (Atriplex) adjacent to mesquite and tamarisk woodlands. Bell's Sparrow sex ratios were significantly female-biased (binomial test: n = 56, observed k = 48 females, expected k = 28 females for assumed p = 0.5, Pr (k ≤ 8 or k ≥ 48) < 0.0001; 95% CI = 0.369 – 0.631 for assumed p = 0.5) at Fort Mohave and Robbins Butte, the 2 sites where Bell's Sparrows were found. Our observed sex-ratios and well-documented year-round presence of Bell's Sparrows on and near the breeding grounds suggest that Bell's Sparrow males and females employ different migration strategies, a phenomenon not previously documented for this taxon.

opencc-zeroAug 2023View details →