Continuity of daily temperature time series in the transition from conventional to automated stations for the Colombian coffee network

Meteorological applications

article

Carolina Ramírez Carabalí¹  Ninibeth Gibelli Sarmiento Herrera¹  Luis Carlos Imbachi Quinchua³  Juan Carlos García López¹ 

[1] Program of Agroclimatology, National Center for Coffee Research;Contribution: Data curation;Program of Biometrics, National Center for Coffee Research;Contribution: Formal analysis;Contribution: Conceptualization

关键词: additive constant;    automatic weather stations;    conventional weather station;    daily temperature;    meteorological observation;    parallel observations;    quantile mapping;    temperature bias;   

DOI  :  10.1002/met.2054

学科分类：社会科学、人文和艺术（综合）

来源: Wiley

【 摘 要 】

The transition from conventional weather stations (CWSs) to automated weather stations (AWSs) of the Colombian coffee network has required testing their performance and adjusting the temperature measurements to ensure the continuity of the historical CWS series. In this study, the mean ( T mean ), minimum ( T min ), and maximum temperature ( T max ) measurements of CWS and AWS operating in parallel at 36 locations between 2014 and 2019 were compared, and the biases of the daily temperature differences (CWS − AWS), the agreement index ( d ), and the percentage of data within the allowed range (PR05) were calculated. The most consistent method for calculating T mean and T max for CWS was selected for use on the AWS data. With the standard normal homogeneity test and with the metadata, we found that the series of temperature differences between CWS and AWS was not homogeneous, instrument failures and sensor changes being the main causes of the lack of homogeneity. The statistical analyses indicated that the AWS data need to be adjusted to be continuous with the CWS series. To correct the temperature bias, two approaches were applied: quantile mapping and the additive constant. The results suggest that the quantile mapping adjustments improve the average bias at all stations but do not necessarily bring the percentage to within ±0.5°C. In T min and T mean , 12 AWSs can give continuity with the historical series of the CWS, and for the rest of the stations and variables, the series of the AWSs are independent of the CWSs.

【 授权许可】

CC BY|CC BY-NC|CC BY-NC-ND