Reconstructing synthetic hourly time series of near-surface air temperatures in a mountainous region of the tropical Andes
Abstract
There is a need to quantify near-surface air temperatures in areas of ongoing and projected faster upper-tropospheric warming. Twenty-two high-resolution data loggers were deployed along a steep altitudinal gradient in the Colombian Central Cordillera. Digital sensors were distributed in the range [4,891-1,611 m] and are collecting hourly near-surface temperature, relative humidity and dew point data. To date, records of the oldest data loggers span back to mid Dec 2008. A reconstruction methodology was used to generate long term temperature series at an hourly resolution. The approach included spatio-temporal interpolations where there was sufficient information from data-loggers, but relied on the typical behavior of the diurnal cycle when there was not hourly information to interpolate from. The typical diurnal cycle for each month was described using a "characteristic curve," created from hourly data-logger records. This characteristic curves allow to generate hourly data using daily temperatures. It is worth noticing that the ENSO signal is included in the synthetic series as it is already captured by daily temperature records. Comparisons with actual temperature records yield monthly mean errors of -0.38°C, and Pearson and Spearman correlations reaching values above 0.910. Synthetic hourly time series are also reconstructed through the analysis of the vertical profiles of reanalysis and ground-truth data. In this case, mean errors increase to -0.98°C and the lowest correlations decrease to 0.784. The tropical altitudinal transect is already providing numerous insights to understand convective processes in a site where large vertical temperature gradients exist, and that is projected to warm up faster that the surrounding lowlands.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMGC51D1205A
- Keywords:
-
- 1616 Climate variability;
- GLOBAL CHANGEDE: 1621 Cryospheric change;
- GLOBAL CHANGEDE: 1631 Land/atmosphere interactions;
- GLOBAL CHANGEDE: 1632 Land cover change;
- GLOBAL CHANGE