Glossary

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Glossary of aWhere variables and terminology

Overview of aWhere data

Aside from the web-based platform and API (Application Programming Interface), aWhere provides daily .csv files through our online adaptER Platform ready to be imported into QGIS or the software/platform of your choosing. These are produced in time-period aggregates of the past 30 days, past 7 days, next 7 days (forecast), next 8-15 days (forecast), and next 1-15 days (forecast), which is indicated in the file name – “YearMonthDay_past7” or “YearMonthDay_next7” etc..
For example, if file is named: “181006_past30”, the file contains data for your country from the previous day and back 30 days. Here from the previous day – October 5th back to September 6th.
Similarly, “181006_past7” will refer to the time from September 29 – October 5. The file 181006_next7 contains the 7 day aggregate forecast from October 6 through October 12.

Data Structure

The aWhere data files contain:
● unique identification of each “virtual weather station” (5 arc-min grid cell);
● latitude and longitude of each “virtual weather station” centroid;
● 15 ag-meteorological variables;
● Well-known text (WKT) markup language for representing data geospatially and includes the polygon for each location ID.

Variables and Terminology

Short nameDescriptionUse / Interpretation / Example
Agronomic terminology
PETPotential EvaportranspirationPET is the Potential Evapotranspiration or the evaporative demand of the environment. aWhere leverages the Penman-Monteith equation to calculate PET. Required inputs are daily minimum and maximum temperature, minimum and maximum relative humidity, solar radiation, and average wind speed. Essentially this is a measure of how much water the plants need to drink each day for optimal growth.
P/PETRatio of Precipitation (P) to Potential Evapotranspiration (PET)P/PET is the ratio of Precipitation (P) to PET. This ratio translates directly into a moisture stress index. Ratios of lower than 0.80, for example, indicate a threshold where maize may struggle to produce grain (depends on genetic and agronomics i.e., number of plant / hectare). P/PET below 1.0 indicates less precipitation than evaporative demand – dry conditions. Conversely, consistent values over 1.1-1.2 may indicate growing issues related to waterlogging and fungal diseases.
GDDGrowing Degree Days (in Celsius)In agronomy the standard metric for heat measurement is the growing degree-day. GDD is a simple starting point that is used by many farmers for tracking their crop growth. It’s a standard metric that provides a common language for discussing when to perform certain actions on the farm. For example, certain pests will only attack a plant at a certain stage. If the plant hasn’t received enough heat to reach that stage, then there isn’t a need to worry about the bug.
Note: “growing degree-day” is a somewhat misleading name, because it has nothing to do with calendar days. GDD equations are based on daily temperatures, and a single calendar day can accumulate several of GDDs.
Commonly used variables: Each “virtual weather station” or grid cell reports values for a variety of weather variables described below.
CSUMPRECurrent Accumulated Precipitation (mm)Total rainfall, measured in millimeters. Useful metric for understanding the pattern of rainfall from the perspective of the amount of moisture being held in the soil
CSUMPETCurrent Accumulated Potential Evapotranspiration (PET, mm)Measured in millimeters. Useful metric for understanding the pattern of water being drawn from the soil over time
CPOVRPRCurrent Precipitation to Potential Evapotranspiration Ratio (P/PET)Index. Useful metric for understanding the pattern of plant available water in the soil over time
CSUMGDD1Current Growing Degree Days (GDD, in Celsius)Base 10 capped at 35
CAvgMinTCurrent Average Minimum Temperature (in Celsius)For many plants their growth effectively slows and even stops below certain temperatures. A colder than typical year is likely to impact yields
CAvgMaxTCurrent Average Minimum Temperature (in Celsius)For many plants their growth effectively increases as temperatures increase until a point where further increases do damage to the plant. An excessively hot year, especially one that is also a dry year, will negatively impact yields.
LTNLong-Term Normal 2006-2018Arithmetic mean of the data across 2006-2018 by the day of the year
LTNSUMPLong-Term Norma; (LTN) of Accumulated Precipitation (mm)LTN or ‘Long Term Normal’ is the long-term average for the variable. For aWhere, our daily global weather surfaces go back to 2006. LTN is thus the average conditions from 2006 to the year prior the year under examination
LTNSPETLong-Term Normal Sum of PET (mm)The typical amount of accumulated PET to be expected at a location
LTNASPOLong-Term Normal Average of P/PETThe typical amount of P/PET to be expected at a location.
LTAvgMnTLong-Term Normal of Average Minimum Temperature (in Celsius)The typical minimum temperature to be expected at a location
LTAvgMxT Long-Term Normal of Average Maximum Temperature (in Celsius)The typical maximum temperature to be expected at a location
DFLTSUMDifference between Current Precipitation and the Long-Term Normal (in Celsius)Difference between the current year and the LTN precipitation. Positive differences indicate wetter conditions than normal, negative differences indicate drier conditions than normal
DFLTMinT Difference between Current Average Minimum Temperature and the Long-Term Normal (in Celsius) Difference between the current year and the LTN minimum temperature. Positive differences indicate warmer conditions than normal, negative differences indicate colder conditions than normal
DFLTMaxT Difference between Current Precipitation and the Long-Term Normal (in Celsius)Difference between the current year and the LTN maximum temperature. Positive differences indicate warmer than normal, negative differences indicate colder conditions than normal
DFLTPVPDifference between Current P/PET and the Long-Term NormalDifference between the current year and the LTN P/PET. Positive differences indicate wetter conditions than normal, negative differences indicated drier conditions than normal.

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