AgriMetSoft publications

This study evaluated the drought state of Fars Province, Iran using PDSI and meteorological data from six stations. SDSM was used to downscale general circulation model outputs for climate prediction. The results suggested increasing dry periods under future scenarios and supported SDSM as a useful approach for drought prediction in arid and semi-arid regions.

This research used pooled panel data, economic variables, meteorological variables, SPI, SPEI, and downscaled climate projections to estimate future rainfed wheat yield. The results identified key variables such as guaranteed wheat price, precipitation, sunshine hours, cultivated area, and SPI of October.

The study compared ant colony optimization, genetic algorithm, and K-means clustering for identifying climate patterns related to rainfed wheat yield. The genetic algorithm was selected as the best method based on the evaluated clustering criteria.

This paper compared dynamical and statistical downscaling methods for historical precipitation over a semi-arid region. The analysis showed that dynamical downscaling performed better during the evaluation period according to several efficiency criteria.

This study compared k-nearest-neighbor weather generation with MIROC5 outputs for daily precipitation, Tmax, and Tmin in an arid environment. MIROC5 performed better for temperature and precipitation projections in the study region.

The study evaluated APHRODITE, PERSIANN, TRMM, and AgMERRA precipitation products against station observations and crop-model simulations. AgMERRA and APHRODITE showed strong potential for filling gaps in ground-observed precipitation data.

This paper evaluated climate-change indicators and their relationship to pearl millet yield in Punjab, Pakistan using statistical downscaling and a genetic algorithm. The projections suggested negative yield impacts due to future warming.

This paper investigated the usefulness of the Keetch-Byram Drought Index for vegetation monitoring and cereal-yield prediction in a semi-arid environment, including comparisons with MODIS-derived NDVI.

This research compared several rain-based drought indices calculated from AgMERRA gridded precipitation and station-observed precipitation data. The study supported AgMERRA as a useful source for filling gaps in station precipitation data.