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I have created some epw files from real weather data. (1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical dimensions and what conversion factors to apply on the input (cf. EP input-output documentation manual)

If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the cvs table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

I have created some epw files from real weather data. (1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical dimensions and what conversion factors to apply on the input (cf. EP input-output documentation manual)

If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the cvs csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

I have created some epw files from real weather data. (1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical dimensions (units) and what conversion factors to apply on the input (cf. EP input-output documentation manual)

If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

I have created some epw files from real weather data. (1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical dimensions (units) and what conversion factors to apply on the input (cf. EP input-output documentation manual)

If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

Another complication may arise, if the your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

I have created some epw files from real weather data. (1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical dimensions (units) and what conversion factors to apply on the input (cf. EP input-output documentation manual)

It may be necessary to convert the original time data into the required time format for the epw converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

I have created some epw files from real weather data. (1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical dimensions (units) and what conversion factors to apply on the input (cf. EP input-output documentation manual)

It may be necessary to convert the original time data into the required time format for the epw converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., you will need to create a numerical estimate for sky cover.

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

I have created some epw files from real weather data. (1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical dimensions (units) and what conversion factors to apply on the input (cf. EP input-output documentation manual)

It may be necessary to convert the original time data into the required time format for the epw converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., and if solar radiation data are missing, you will need to create a numerical estimate for sky cover.

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

I have created some epw files from real weather data. PREPARING AN INPUT FILE FOR THE EPW WEATHER CONVERTER: (1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical dimensions (units) units and what conversion factors to apply on the input (cf. EP input-output documentation manual)

It may be necessary to convert the original time data into the required time format for the epw weather converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., and if solar radiation data are missing, you will need to create a numerical estimate for sky cover. if you have METAR data, - although not very accurate - a reasonable method seems to set sky cover values according to CLR=0, FEW=1.5/8, SCT=3.5/8, BKN=6/8, OVC=1.0 in each sky layer and to assign overall sky cover fraction to the maximum from all reported layers. (cf. a paper by James Tobin, J.W. Nielsen-Gammon, Texas A&M University, 2010)

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

PREPARING AN INPUT FILE FOR THE EPW WEATHER CONVERTER: (1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical units and what conversion factors to apply on the input (cf. EP input-output documentation manual)

It may be necessary to convert the original time data into the required time format for the epw weather converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., and if solar radiation data are missing, you will need to create a numerical estimate for sky cover. if you have In the case of METAR data, - although not very accurate - a reasonable method seems to set sky cover values according to CLR=0, FEW=1.5/8, SCT=3.5/8, BKN=6/8, OVC=1.0 in each sky layer and to assign overall sky cover fraction to the maximum from all reported layers. (cf. a paper by James Tobin, J.W. Nielsen-Gammon, Texas A&M University, 2010)

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

PREPARING AN INPUT FILE FOR THE EPW WEATHER CONVERTER: CONVERTER:

(1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical units and what conversion factors to apply on the input (cf. EP input-output documentation manual)Auxiliary Programs documentation)

It may be necessary to convert the original time data into the required time format for the epw weather converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., and if solar radiation data are missing, you will need to create a numerical estimate for sky cover. In the case of METAR data, - although not very accurate - a reasonable method seems to set sky cover values according to CLR=0, FEW=1.5/8, SCT=3.5/8, BKN=6/8, OVC=1.0 in each sky layer and to assign overall sky cover fraction to the maximum from all reported layers. (cf. a paper by James Tobin, J.W. Nielsen-Gammon, Texas A&M University, 2010)

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

QUICK CHECK for "error occurred in processing csv file": * maybe input data format deviates from expected format by weather converter * if the csv data file contains column names you need to specify number of records to skip=1 in the DEF file, if there is more information in lines preceding the data increase skip number accordingly.

GENERAL HOW-TO for PREPARING AN INPUT FILE FOR THE EPW WEATHER CONVERTER:

(1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical units and what conversion factors to apply on the input (cf. EP Auxiliary Programs documentation)

It may be necessary to convert the original time data into the required time format for the epw weather converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., and if solar radiation data are missing, you will need to create a numerical estimate for sky cover. In the case of METAR data, - although not very accurate - a reasonable method seems to set sky cover values according to CAVOK=0, SKC=0, CLR=0, FEW=1.5/8, SCT=3.5/8, BKN=6/8, OVC=1.0 in each sky layer and to assign overall sky cover fraction to the maximum from all reported layers. (cf. a paper by James Tobin, J.W. Nielsen-Gammon, Texas A&M University, 2010)

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

QUICK CHECK for "error occurred in processing csv file": * maybe input data format deviates from expected format by weather converter * if the csv data file contains column names you need to specify number of records to skip=1NumRecordsToSkip=1 in the DEF file, file, if there is more information in lines preceding the data increase skip NumRecordsToSkip number accordingly.

GENERAL HOW-TO for PREPARING AN A CUSTOM INPUT FILE FOR THE EPW WEATHER CONVERTER:

(1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical units and what conversion factors to apply on the input (cf. EP Auxiliary Programs documentation)

It may be necessary to convert the original time data into the required time format for the epw weather converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., and if solar radiation data are missing, you will need to create a numerical estimate for sky cover. In the case of METAR data, - although not very accurate - a reasonable method seems to set sky cover values according to CAVOK=0, SKC=0, CLR=0, FEW=1.5/8, SCT=3.5/8, BKN=6/8, OVC=1.0 in each sky layer and to assign overall sky cover fraction to the maximum from all reported layers. (cf. a paper by James Tobin, J.W. Nielsen-Gammon, Texas A&M University, 2010)

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

QUICK CHECK for "error occurred in processing csv file": * maybe input data format deviates from DEF file specification, as expected format by weather converter * if the csv data file contains column names you need to specify number of records to NumRecordsToSkip=1 in the DEF file, if there is more information in lines preceding the data increase NumRecordsToSkip number accordingly.

GENERAL HOW-TO for PREPARING A CUSTOM INPUT FILE FOR THE EPW WEATHER CONVERTER:

(1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical units and what conversion factors to apply on the input (cf. EP Auxiliary Programs documentation)

It may be necessary to convert the original time data into the required time format for the epw weather converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., and if solar radiation data are missing, you will need to create a numerical estimate for sky cover. In the case of METAR data, - although not very accurate - a reasonable method seems to set sky cover values according to CAVOK=0, SKC=0, CLR=0, FEW=1.5/8, SCT=3.5/8, BKN=6/8, OVC=1.0 in each sky layer and to assign overall sky cover fraction to the maximum from all reported layers. (cf. a paper by James Tobin, J.W. Nielsen-Gammon, Texas A&M University, 2010)

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

QUICK CHECK for "error occurred in processing csv file": * maybe input data format data format deviates from your DEF file specification, as expected format by weather converter or your DEF file specifications are illegal. (cf. DEF file examples in documentation), e.g. DataElements=... and and corresponding DataUnits=... need to be specified. * if the csv data file contains column names you need to specify number of records to NumRecordsToSkip=1 in the DEF file, if there is more information in lines preceding the data increase NumRecordsToSkip number accordingly.

GENERAL HOW-TO for PREPARING A CUSTOM INPUT FILE FOR THE EPW WEATHER CONVERTER:

(1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical units and what conversion factors to apply on the input (cf. EP Auxiliary Programs documentation)

It may be necessary to convert the original time data into the required time format for the epw weather converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., and if solar radiation data are missing, you will need to create a numerical estimate for sky cover. In the case of METAR data, - although not very accurate - a reasonable method seems to set sky cover values according to CAVOK=0, SKC=0, CLR=0, FEW=1.5/8, SCT=3.5/8, BKN=6/8, OVC=1.0 in each sky layer and to assign overall sky cover fraction to the maximum from all reported layers. (cf. a paper by James Tobin, J.W. Nielsen-Gammon, Texas A&M University, 2010)

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.

QUICK CHECK for "error occurred in processing csv file": * maybe input data format deviates from your DEF file specification, or your DEF file specifications are illegal. (cf. DEF file examples in documentation), e.g. DataElements=... and and corresponding DataUnits=... need to be specified. * if the csv data file contains column names you need to specify number of records to NumRecordsToSkip=1 in the DEF file, if there is more information in lines preceding the data increase NumRecordsToSkip number accordingly.

GENERAL HOW-TO for PREPARING A CUSTOM INPUT FILE FOR THE EPW WEATHER CONVERTER:

(1) make sure that in your csv file you really have a table of weather data only (e.g. dry bulb temperature, wet bulb temperature, humidity,....) (2) your def file looks as if incomplete: you also need to specify here what data the weather converter will find in every column, in which physical units and what conversion factors to apply on the input (cf. EP Auxiliary Programs documentation)

It may be necessary to convert the original time data into the required time format for the epw weather converter (yyy,mm,dd,hh, min). If the data are incomplete regarding certain time steps you will probably need to fill in some interpolated or default values in the csv table (preferably done with an appropriately coded script). If certain physical data (e.g. solar radiation) are missing, the weather converter may be able to create them estimates automatically for a complete epw file.

If the available data do not comprise numerical values for sky cover but only verbal descriptions of sky condition, clouds etc., and if solar radiation data are missing, you will need to create a numerical estimate for sky cover. In the case of METAR data, - although not very accurate - a reasonable method seems to set sky cover values according to CAVOK=0, SKC=0, CLR=0, FEW=1.5/8, SCT=3.5/8, BKN=6/8, OVC=1.0 in each sky layer and to assign overall sky cover fraction to the maximum from all reported layers. (cf. a paper by James Tobin, J.W. Nielsen-Gammon, Texas A&M University, 2010)

Another complication may arise, if your weather data refer to e.g. 3 time steps per hour, but not regularly. (some hours with two measurements, some with three). In this case I have observed that the weather converter crashes, if you have specified 2 time steps per hour (without having checked that the weather data really conform to this). For preparation of data for the weather converter in this case you will need to extract a selection of the data that strictly conforms to the 2-time-step/hour rhythm. This also is best done by writing a script which automates the task.