¿Puede la disponibilidad temporal de datos determinar el calentamiento percibido por las tribus nómadas de mongoles cerca de las montañas Khangai?

Temperatures changes can be difficult to infer from changes in vegetation patterns or other ecological changes, yet warming can be inferred through changes in the habits of people who live in close connection with their natural environment. Herders near the Khangai Mountains of central Mongolia have perceived a warming trend in recent years. Since it is difficult to determine the exact time period over which perceived warming has occurred, we examined the statistical difference in changes based on the length of data and the specific period of record used in the analysis. We used temperature data from five meteorological stations for up to 50 years (1961-2010). We examined varying lengths of record from 15 to 50 years with varying start periods (1961 through 1986), based on the length of record. We found that the most statistically significant changes occurred for the longest time periods and for the annual average minimum temperatures. We also found that one very cold winter, in particular 2009-2010 decreased the warming trend and for shorter periods of record reduced the statistical significance.Los cambios de temperatura pueden ser difíciles de inferir a partir de los cambios en los patrones de vegetación u otros cambios ecológicos. Sin embargo, el calentamiento se puede inferir a través de cambios en los hábitos de las personas que viven en estrecha relación con su entorno natural. Los pastores de las montañas de Mongolia central, cerca deKhangai, perciben una tendencia hacia el calentamiento en los últimos años. Ya que resulta difícil determinar el período de tiempo exacto durante el que se ha producido el calentamiento, se analizó la diferencia estadística de los cambios en función de la longitud de los datos y el período de registros utilizado en el análisis. Hemos utilizado los datos de temperatura de cinco estaciones meteorológicas con 50 años de registros (1961-2010). Se examinaron diferentes longitudes de registro (de 15 a 50 años) con períodos de inicio diferentes (1961 a 1986). Se comprobó que los cambios estadísticamente más significativos se registran en los períodos más largos y considerando las temperaturas mínimas medias anuales. También se encontró que un invierno muy frío, en particular (2009-2010) disminuyó la tendencia al calentamiento

Does the length of station record influence the warming trend that is perceived by mongolian herders near the Khangai Mountains?

Temperatures changes can be difficult to infer from changes in vegetation patterns or other ecological changes, yet warming can be inferred through changes in the habits of people who live in close connection with their natural environment. Herders near the Khangai Mountains of central Mongolia have perceived a warming trend in recent years. Since it is difficult to determine the exact time period over which perceived warming has occurred, we examined the statistical difference in changes based on the length of data and the specific period of record used in the analysis. We used temperature data from five meteorological stations for up to 50 years (1961-2010). We examined varying lengths of record from 15 to 50 years with varying start periods (1961 through 1986), based on the length of record. We found that the most statistically significant changes occurred for the longest time periods and for the annual average minimum temperatures. We also found that one very cold winter, in particular 2009-2010 decreased the warming trend and for shorter periods of record reduced the statistical significance.Los cambios de temperatura pueden ser difíciles de inferir a partir de los cambios en los patrones de vegetación u otros cambios ecológicos. Sin embargo, el calentamiento se puede inferir a través de cambios en los hábitos de las personas que viven en estrecha relación con su entorno natural. Los pastores de las montañas de Mongolia central, cerca deKhangai, perciben una tendencia hacia el calentamiento en los últimos años. Ya que resulta difícil determinar el período de tiempo exacto durante el que se ha producido el calentamiento, se analizó la diferencia estadística de los cambios en función de la longitud de los datos y el período de registros utilizado en el análisis. Hemos utilizado los datos de temperatura de cinco estaciones meteorológicas con 50 años de registros (1961-2010). Se examinaron diferentes longitudes de registro (de 15 a 50 años) con períodos de inicio diferentes (1961 a 1986). Se comprobó que los cambios estadísticamente más significativos se registran en los períodos más largos y considerando las temperaturas mínimas medias anuales. También se encontró que un invierno muy frío, en particular (2009-2010) disminuyó la tendencia al calentamiento

Merging Indigenous Knowledge Systems and Station Observations to Estimate the Uncertainty of Precipitation Change in Central Mongolia

Across the globe, station-based meteorological data are analyzed to estimate the rate of change in precipitation. However, in sparsely populated regions, like Mongolia, stations are few and far between, leaving significant gaps in station-derived precipitation patterns across space and over time. We combined station data with the observations of herders, who live on the land and observe nature and its changes across the landscape. Station-based trends were computed with the Mann–Kendall significance and Theil–Sen rate of change tests. We surveyed herders about their observations of changes in rain and snowfall amounts, rain intensity, and days with snow, using a closed-ended questionnaire and also recorded their qualitative observations. Herder responses were summarized using the Potential for Conflict Index (PCI2), which computes the mean herder responses and their consensus. For one set of stations in the same forest steppe ecosystem, precipitation trends were similar and decreasing, and the herder-based PCI2 consensus score matched differences between stations. For the other station set, trends were less consistent and the PCI2 consensus did not match well, since the stations had different climates and ecologies. Herder and station-based uncertainties were more consistent for the snow variables than the rain variables. The combination of both data sources produced a robust estimate of climate change uncertainty