# ENVI-met Output Files

## Overview

Each ENVI-met simulation creates a huge amount of data which is organized in different files and folders. In general, there are two different types of output files regardless their content:

• Simple Text Files: Files which contain data in pure ASCII text format seperated with “comma” aka CSV Data. The content of the file (variable names) are described in the first row of the file. These file can be read and visiualized with any software that can read text files. From Version 5 on, ENVI-met provides different options to analyse data using Python e.g. the DataStudio inside LEONARDO. With respect to Python, the format of the text output files have been changed from V5 on to allow a seamless integration with Python and Pandas.
• Binary Files (EDX/EDT): The main ENVI-met output files are stored in a binary format and require special software to be read. The LEONARDO software included in the ENVI-met system offers a comfortable and visual access to all data and give various options for 2D and 3D visualisation. In addition, with the help of the reference for the EDX/EDT file format, own reader routines can easily be developed. Moreover, ENVI-met provides the option to write simulation data in addition using the NetCDF format.

In order to use advanced analysis functions like Time Series in LEONARDO, it is strongly recommended to store only one simulation run in the same folder and not to mix different model runs. While the files remain usable itself, the logic of the different applications might not be able to sort out the structure of your simulation data.

## Name and storage logic

The huge amount of data generated by each simulation requires a strict concept of storage and labelling in order not to loose overview or to overwrite files. ENVI-met uses a three-level concept to organize the output data:

• Level 1: Storage by folder name
• Level 2: Classification by filename or file extension
• Level 3: Metadata information in the . EDX File

For simple Text files, Level 3 data are not available, so that the filename and filename extension provide information about the content of the files.

### Level 1: Storage by folder name

The uppermost level of file organisation starts by sorting the output files into subfolders of the selected output folders. Some folders are only existing in the full version of ENVI-met, others may be added in the course of time. All files in one folder are of the same structure and contain the same set of information, some of the output folders are further organized in sub folders. The following list summarizes the basic content of the folders. For more information on the file types, see sections below.

1. InputData: This folder contains a copy of all relevant simulation files (.INX, .SIMX,…), database files and forcing data used in the simulation. Using this folder, you can reconstruct your model settings as they have been at the time of simulation even if they have been changed afterwards. This folder is required by several tools such as BIO-met. (Added with V5.0.3)
2. Atmosphere: All information about the state of the atmosphere at different times of model simulation. Definitely the largest set of data and mostly considered as “the” model result (which is not true as the other data are very important, too).
3. Buildings: Detailed data for the facades and roofs of the buildings. Folder includes static data such as material, albedo (folder STATIC) as well as dynamic data of meteorology along the building and building physics data like temperatures and fluxes (folder DYNAMIC, not in ENVI-met LITE). In addition, summary files about the different buildings are included.
4. → Inflow: Data about the inflow model of ENVI-met used to represent the surroundings of the model domain that cannot be modelled in the given scale.
5. Log: A copy of the ENVI-met outputs generated during the model run.
6. Pollutants: Data about pollutant concentration in the model atmosphere (only present if pollutants are used in the model).
8. → Receptors: Time series and profile data at defined receptor points in the model (if defined)
9. Soil: State of the ENVI-met soil model
10. Solar Access: Detailed analysis on solar access data such as solargrams, sun hours, etc (Full versions of ENVI-met only)
11. Surface: State of the soil surface as an interface between the atmosphere and the soil model
12. Vegetation: State of the vegetation including detailed log of observed 3D plants. Contains 3D data and text data for observed plants which are organized in a STATIC folder for constant properties and a DYNAMIC folder with time-dependent properties of the plants.

In addition, the BIOMet tool will create further folders, by default labled “Biomet”, but with a free choice of names. Future versions or additional modules of ENVI-met will create further folders and file, but the general concept of storage will be the same.

### Level 2: Classification by file name or extension

Sorting the output files into folders provides a first system of order in the output data. However, once a file has been moved out of its folder or if several simulations come together, this system is not unique and not persistent. As a solution, the ENVI-met file name generation scheme allows a direct identification of the simulation files and their content.

Each ENVI-met output filename consists of 3 parts:

1. Simulation Base Name: This is the given working name for the simulation. You define this name in the .SIMX simulation configuration file. It should be not too log (as more data are added) and unique. In the example above, urbanLayout has been selected as basename.
2. Type identifier: The type identifier describes the content of the file following the categories listed above. For example _AT_ defines that this file holds atmospheric data. The different content ids are listed in the description of the output files categories and at the end of this page.
3. Time of data: The last part of the filename represents the model time the data were taken. This part of the filename is generated base on the “YYYY-MM-DD+'_'+hh.mm.ss” scheme. In the example shown above, the file represents the state of the atmosphere (_AT_) at 08:00:01 model time on the 15th July (07) 2018. If the data in the file are not time sensitive, this part of the filename is empty.

#### Classification by file extension

For pure text files, which might be processed in other programs or using the Python-based DataStudio, it is not possible to include metadata or other addtional data in the files except a header line defining the variables stored in the different colums of the file.

From ENVI-met Version 5 on, all text files are comma-seperated (CSV) files that can be processed directly in Python/Pandas or other software. In order to identify the contents of the file and suggest the correct scripts in DataStudio, the file extension is requried for these file types.

### Level 3: Metatadata information in EDX file

Level 1 and 2 provide a good information basis about the content of a simulations file and they where the only sources of information in ENVI-met versions prior to V4. However, files get moved and files get renamed. For that reason, starting from ENVI-met Version 4, each data file again holds detailed information about its data type in the metadata stored in the EDX information file, in the <data_content> section. For all ENVI-met tools, this is the evaluated information when working with data files. All ENVI-met tools try to interpret data files coming from older ENVI-met versions, but this import process might not work in all cases.

## Binary Files: Overview and description

The list below lists and links to the basic main files in binary format generated by the ENVI-met simulations.

ID Content Remark Details
AT Atmospheric data 3D Data Main state of the atmosphere with most of the variables in it
FX Surface data and surface fluxes 2D Data describing state and fluxes at the ground surface
SO Soil data 3D Data about the state of the soil model, mainly temperature and soil water
VEG Vegetation data Plant data like Leaf Temperature in the context of the 3D Model, Detailed data for observed plants are additional text files of .VEG_status type (see below)
BLDG_static Building data static Static building data like material properties (Subfolder STATIC)
BLDG Building data dynamic Dynamic building data like wall temperatures or state of facade greeings (Subfolder DYNAMIC)
POLU Pollutants 3D Data containing air pollutants including chemical conversion rates if used
BIO BIO-met Data Data generated by BIO-met
SA Solar Access Solar Access Data for the ground and Biomet level
SAFAC Solar Access on Facades and Roofs Solar Access for Facade/ Roofs and Single Walls

## Text Files: Overview and description

This list gives an overview over the different text output files generated by ENVI-met. All files are CSV text files that can be loaded directly in to Python (Pandas). Not all files may be generated in each simulation. This list refers to ENVI-met V5 and newer.

ID Content Remark
.AT_1DR Receptor Atmospheric data (Profile) Vertical profile atmosphere at receptor at a given model time
.AT_1DT Receptor Atmospheric data (Time Series) Vertical profile atmosphere at receptor for all model times of simulation in one file
.FX_1DT Receptor Surface data (Time Series) Time series of ground surface state at receptor for all model times
.SO_1DR Receptor Soil data (Profile) Vertical profile soil at receptor at a given model time
.SO_1DT Receptor Soil data (Time Series) Vertical profile soil at receptor for all model times of simulation in one file
.BLDG_status Single Building Status (Time Series) Actual status of individual buildings for all model times of simulation in one file (one for each building)
.BLDG_statistics Building Statistics Summary of static parameters for the buildings (one for each building)
.BLDG_list Buildings Inventory List of all buildings in model (all buildings in one file)
.VEG_status Vegetation Status (Time Series) Actual status of 3D vegetation for all model times of simulation (only for observed plants)
.VEG_list Vegetation Inventory List of all 3D plants and their key properties in the model
.Inflow1D Profile Atmosphere Model at inflow boundary State of the 1D inflow boundary layer model at a given time up to 2500 m

Please note, for all receptor files, you can produce output files with a higher resolution than the main output file intervall. All other files will be generated when the main model files are saved.

#### Import text file into Python Pandas

To import ENVI-met output text files with time series into Python Pandas, use:

import pandas as pd

# this imports the (ENVI-met) text file "mysourcefile" into a Panda dataframe object.
# Comma "," is selected as seperator sign,
# the "DateTime" column is flaged to be handeld as date information
# and also is set as the default index column for data processing

df = pd.read_csv("mysourcefile", sep=",", parse_dates=['DateTime'], index_col=['DateTime'])

Each Time Series files now contains a Python-compatible DataTime column to allow a direct use of the different Date and Time functions supplied by Python.

The LEONARDO DataStudio automatically recognizes the content of the ENVI-met output text files and offers specific scripts matching the file types.