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These services provide fire risk analyses for the current season per day and hour in real time. The daily API represents the fire risk in the afternoon when the fire risk is usually at its highest. The API per hour describes the fire risk hour by hour and thus shows the variation of fire risk during the day. In the APIs for fire risk forecasts, there are corresponding calculations in the future, when the fire risk on the day also depends on how the weather was before, especially with regard to the precipitation. SMHI’s work on fire risk calculations (forecasts and analyses) is carried out on behalf of MSB. Calculations of fire risk (forecast and analysis) are made only over land and lakes in Sweden. In both the daily and hour API, the Canadian Fire Weather Index (FWI) model* is a well-used model both inside and outside Europe. The FWI model is also part of a larger model system for assessing fire risk and behaviour called Canadian Forest Fire Danger Rating System (CFFDRS)**. At SMHI, the daily variant of the FWI model was introduced in 1999. The FWI model describes, among other things, fire behaviour, spreading speed and the amount of fuel available for the fire in various variables. The daily input data of the FWI model are the weather parameters temperature, relative humidity and wind 12 UTC and precipitation 18-18 UTC, from MESAN. The input data for the hourly variant of the FWI model is instead temperature, relative humidity and precipitation for every hour from MESAN. The differences between the daily and hour variations of the FWI model: — The hourly variant uses inputs from the daily variant for (DMC, DC, BUI) as these variables do not vary significantly during the day. — In the hourly variant, moisturisation/drying speeds are faster than in the daily variant. The first 0.5 mm is ignored in the daily variance, but the hourly variation includes all precipitation. — Since the model set and input data for the daily and hour variants are not the same, the different FWI models will get different values even for the time 12 UTC. In addition to the FWI model variables, the hourly API also contains: — grass fire risk in the old last year’s grass — potential rate of spread of a fully developed grass fire in uncut and unmoved last year grass (m/min) (Rn) global radiation in W/m² (GLirr) In addition to the FWI model variables, the daily API also contains: —fuel dehydration indicating how dehydrated it has become both in the fuel and in the soil layers most important in forest fires. —grass fire risk in the old last year’s grass fire model on a daily basis — the potential rate of spread of a fully developed grass fire in uncut and unmoved last year grass (m/min) (Rn) according to the grass fire model on a daily basis. The daily model*** for grass is based on the hourly model**** and uses temperature, precipitation, relative humidity, wind and global radiation (solar radiation) as input. The daily model represents the highest grass fire risk during the day, unlike the hourly model, which instead describes the grass fire risk for each hour. * Development and structure of the Canadian Forest Fire Weather Index System. 1987. Van Wagner, C.E. Canadian Forestry Service, Headquarters, Ottawa. Forestry Technical Report 35. 35 p. https://cfs.nrcan.gc.ca/publications?id=19927 ** https://cwfis.cfs.nrcan.gc.ca/background/summary/fdr *** will come later **** A new model for grass fire hazard (2021) Sjöström, J., Granström, A, Jansson, A and Böhlin, J https://rib.msb.se/filer/pdf/29530.pdf

Idealized Short/Long Fire Ignition on a Homogeneous Grassland Simulation QUIC-Fire - Version: Jan2022 Working alongside Los Alamos National Lab (LANL), Tall Timbers Research Station (TTRS) produced a parameter sweep to compare QUIC-Fire to FIRETEC. The canonical example of an idealized rectangular ignition over a homogeneous grassland was used and developed. The QUIC-Fire simulations were made to match the FIRETEC simulations as closely as possible, with a notable exception made for the vertical grid resolution. Provided in this folder are Zarr arrays containing the bulk density over time for 10 different runs: 5 wind speeds for a short and a long fire ignitions. The first time step then is the initial condition of the fuel. The arrays are structured as [ntimes,ny,nx,nz]. The 'ntimes' is not the total simulation time but the amount of time-steps that were output. For these simulations, that would be every 10 seconds (simulation time step is 1 s but the outputs are printed every 10 s). Provided is a txt file containing the number of timesteps for each simulation (Table 2). Ny and Nx will be set for 200, 200 for all these runs, and Nz is set to 5 (vertical cells in the fuel grid). Provided is also the generating text files for the run. Please contact Daniel Rosales (dgiron@talltimbers.org) for any questions, comments or concerns about the simulations. See Jupyter Notebook demonstrating how to access the data (https://github.com/BurnPro3D/data-api-notebooks/blob/main/access-QuicFire-QF-Idealized-Grass-Plots-data.ipynb)

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Data provided here are from the DC's 311 service request center. They represent all service requests such as abandoned automobiles, parking meter repair and bulk trash pickup. Requests are received by the Office of Unified Communications (OUC) through the Mayor's Call Center (311), citizens web intake at https://311.dc.gov, electronic and US mail service or via other methods of communication. The Office of Unified Communications (OUC)oversees the designated call center for all 311 calls and for all District 911 calls. Please also visit the DC 311 Service Request Mapwhich allows the public to see service requests in the last 30 days. Users can view requests by Ward within charts. Just set the area filter to select service requests. Click on a service request to view details.

Geospatial data about US Turf Cover. Export to CAD, GIS, PDF, CSV and access via API.

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This is a development key figure, see questions and answers on kolada.se for more information. Number of 11-playing pitches artificial grass divided by number of inhabitants total on 31/12 multiplied by 10000. The construction survey is conducted every 4-5 years, the last time it was carried out in 2019. The key figure is updated with the latest survey value each year until a new survey has been completed.

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