Fire activity in the Peruvian Andes has increased significantly in recent decades, but climatic parameters associated with drought, which may indirectly contribute to the occurrence of severe forest fires, have not yet been investigated. Because fire prevention tools are scarce, strategies for deterring burning are necessary in order to reduce impacts in regions where forest fires usually result from human activity. This study explores the conditions conducive to forest fire in the Andes of Peru. Daily precipitation and temperature observed data from the PISCO gridded dataset for the 2002–2016 period were used. In addition, MODIS satellite images (MOD09A1 product) were collected to characterise Andean vegetation using spectral indices. Analysis of daily temperature and rainfall indicates that climatic parameters such as cumulative precipitation, dry-day frequency and hot-day frequency are statistically associated with conditions that could contribute to increased forest fire occurrence. Our findings suggest that a decrease in the water content of vegetation, estimated by the Global Vegetation Moisture Index during the dry period and wet period onset, can be used to identify potential conditions for forest fire occurrence. This study suggests that forest managers should consider implementing prevention strategies that include continuous monitoring of climate and vegetation parameters.

Daily precipitation concentration in the Amazon basin (AB) is characterized using concentration index (CI), which is computed from HYBAM Observed Precipitation (HOP) dataset, for 1980‐2009 period. The ability of four satellite precipitation datasets (TMPA V7, TMPA RT, CMORPH and PERSIANN) to estimate CI is evaluated for 2001‐2009 period. Our findings provide new information about the spatial irregularity of daily rainfall distribution over the AB. In addition, the spatial distribution of CI values is not completely explained by rainfall seasonality, which highlights the influence of different weather systems over the AB. The results of rainfall concentration indicate that the distribution of daily rainfall is more regular over northwest (northern Peru) and central Andes. Conversely, Roraima region and a large area of Bolivian Amazon register the highest irregularity in the daily rainfall. Bolivian Amazon also represents regions where the large percentage of total rainfall arises from extreme events (> 90^th percentile). Heavy rainfall episodes over Roraima region are induced by humidity influx come from Caribbean region, while heavy rainfall events over Bolivian Amazon and Andes region are induced by the northward propagation of cold and dry air along both sides of Andes Mountains, but only propagates in all tropospheric levels for the Andes. The results also show that PERSIANN and TMPA7 datasets better estimates the daily precipitation concentration for whole AB, but with a relative error 8%. CI estimated from satellites does not agree well with HOP over the Andes and northern Peruvian Amazon. On the other hand, the temporal variability of CI can partly be detected using CMORPH and TMPAV7 datasets over the Peruvian Andes, and central and southern Brazil. Errors in CI estimating might be related to inaccurate estimation of daily rainfall. Finally, we conclude that satellite‐based precipitation datasets are useful for analyzing rainfall concentration in some regions of AB.

Wildfire occurrence has increased sharply in the last two decades in the Peruvian Andes. There is, however, little research on wildfires and their impacts. This study explores the conditions conducive to wildfire during 2020. MODIS images were collected to estimate the development of vegetation. In addition, ground-based monthly and satellite-based daily precipitation data were collected. Daily precipitation regularity was evaluated using a concentration index (CI), while monthly precipitation was used to estimate the Standard Precipitation Index (SPI). We used also the Global Vegetation Moisture Index (GVMI), which is a useful indicator of vegetation dynamics based on vegetation moisture. Our results do not indicate a direct link between rainfall regularity (lowest CI values) and development of vegetation. Although the SPI drought analysis using seasonal rainfall indicated nearly normal conditions during 2019–2020, analysis of dry-day frequency (DDF) suggests that the dry period played an important role between September and November 2020, producing conditions similar to the droughts of 2005, 2010 and 2016. GVMI also showed below-average values from April to November. We corroborate the usefulness of DDF for monitoring the potential increase in wildfire conditions. A controlled burn policy could offer a more useful way to reduce the impacts of wildfire.