Quantitative estimates of glacial and Holocene temperature and precipitation change in lowland Amazonian Bolivia

Quantitative estimates of temperature and precipitation change during the late Pleistocene and Holocene have been difficult to obtain for much of the lowland Neotropics. Using two published lacustrine pollen records and a climate-vegetation model based on the modern abundance distributions of 154 Neotropical plant families, we demonstrate how family-level counts of fossil pollen can be used to quantitatively reconstruct tropical paleoclimate and provide needed information on historic patterns of climatic change. With this family-level analysis, we show that one area of the lowland tropics, northeastern Bolivia, experienced cooling (1–3 °C) and drying (400 mm/yr), relative to present, during the late Pleistocene (50,000–12,000 calendar years before present [cal. yr B.P.]). Immediately prior to the Last Glacial Maximum (LGM, ca. 21,000 cal. yr B.P.), we observe a distinct transition from cooler temperatures and variable precipitation to a period of warmer temperatures and relative dryness that extends to the middle Holocene (5000–3000 cal. yr B.P.). This prolonged reduction in precipitation occurs against the backdrop of increasing atmospheric CO2 concentrations, indicating that the presence of mixed savanna and dry-forest communities in northeastern Bolivia durng the LGM was not solely the result of low CO2 levels, as suggested previously, but also lower precipitation. The results of our analysis demonstrate the potential for using the distribution and abundance structure of modern Neotropical plant families to infer paleoclimate from the fossil pollen record.

Recent trends in Inner Asian forest dynamics to temperature and precipitation indicate high sensitivity to climate change

Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO2. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area ‘browning’ during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prior-year lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO2 causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO2 fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO2 fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.

Global observed changes in daily climate extremes of temperature and precipitation

A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed. By setting an exact formula for each index and using specially designed software, analyses done in different countries have been combined seamlessly. This has enabled the presentation of the most up-to-date and comprehensive global picture of trends in extreme temperature and precipitation indices using results from a number of workshops held in data-sparse regions and high-quality station data supplied by numerous scientists world wide. Seasonal and annual indices for the period 1951-2003 were gridded. Trends in the gridded fields were computed and tested for statistical significance. Results showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature. Over 70% of the global land area sampled showed a significant decrease in the annual occurrence of cold nights and a significant increase in the annual occurrence of warm nights. Some regions experienced a more than doubling of these indices. This implies a positive shift in the distribution of daily minimum temperature throughout the globe. Daily maximum temperature indices showed similar changes but with smaller magnitudes. Precipitation changes showed a widespread and significant increase, but the changes are much less spatially coherent compared with temperature change. Probability distributions of indices derived from approximately 200 temperature and 600 precipitation stations, with near-complete data for 1901-2003 and covering a very large region of the Northern Hemisphere midlatitudes (and parts of Australia for precipitation) were analyzed for the periods 1901-1950, 1951-1978 and 1979-2003. Results indicate a significant warming throughout the 20th century. Differences in temperature indices distributions are particularly pronounced between the most recent two periods and for those indices related to minimum temperature. An analysis of those indices for which seasonal time series are available shows that these changes occur for all seasons although they are generally least pronounced for September to November. Precipitation indices show a tendency toward wetter conditions throughout the 20th century.

Co-variation of temperature and precipitation in CMIP5 models and satellite observations

Current variability of precipitation (P) and its response to surface temperature (T) are analysed using coupled(CMIP5) and atmosphere-only (AMIP5) climate model simulations and compared with observational estimates. There is striking agreement between Global Precipitation Climatology Project (GPCP) observed and AMIP5 simulated P anomalies over land both globally and in the tropics suggesting that prescribed sea surface temperature and realistic radiative forcings are sufficient for simulating the interannual variability in continental P. Differences between the observed and simulated P variability over the ocean, originate primarily from the wet tropical regions, in particular the western Pacific, but are reduced slightly after 1995. All datasets show positive responses of P to T globally of around 2 %/K for simulations and 3-4 %/K in GPCP observations but model responses over the tropical oceans are around 3 times smaller than GPCP over the period 1988-2005. The observed anticorrelation between land and ocean P, linked with El Niño Southern Oscillation, is captured by the simulations. All data sets over the tropical ocean show a tendency for wet regions to become wetter and dry regions drier with warming. Over the wet region (75% precipitation percentile), the precipitation response is ~13-15%/K for GPCP and ~5%/K for models while trends in P are 2.4%/decade for GPCP, 0.6% /decade for CMIP5 and 0.9%/decade for AMIP5 suggesting that models are underestimating the precipitation responses or a deficiency exists in the satellite datasets.

RegCM3 nested in HadAM3 scenarios A2 and B2: projected changes in extratropical cyclogenesis, temperature and precipitation over the South Atlantic Ocean

The RegCM3 (Regional Climate Model-version 3) was nested in HadAM3 model to simulate present (1975-1989, referred hereafter as RegHad) and two future climate scenarios (A2 and B2 from 2071 to 2085, referred as RegA2 and RegB2) over the South America (SA) and South Atlantic Ocean (SAO). Projected changes in the air temperature, precipitation, low level circulation and cyclogenesis climatology were investigated. The cyclogenesis were identified using an automatic scheme for tracking based on the minimum of relative vorticity (zeta) from 10-m height wind. During summer, a general decrease (increase) in the precipitation is projected by RegA2 and RegB2 over the northeastern SA (center-west and south Brazil, north Argentina and Uruguay). For winter, an anomalous low level anticyclonic circulation is associated with the reduction in the rainfall over the central part of southern Brazil in RegA2 and RegB2 scenarios. Similar to HadAM3, RegCM3 projects larger warming in A2 scenario. For the present climate, when compared to HadAM3, RegHad defines better both the location of the main cyclogenetic areas and its annual cycle near southwestern SAO. The projections indicate a reduction in the total number of cyclones of -7.2% and -4.7% for RegA2 and RegB2, respectively, while HadAM3 reduction is -4.5% for both scenarios. The decrease is larger for initially intense cyclones (zeta <=-<= 2.5 x 10(-5) s-(1)): -20.9% (RegA2) and -11.3% (RegB2). For the lifetime, distance traveled and mean velocity of the cyclones, the A2 and B2 scenarios present mean values close to the present climate ( 3 days, 1900 km, and 9 m s(-1), respectively). Regarding the initial mean vorticity of the systems, RegB2 simulates values similar to the present climate, but they are initially weaker in RegA2. In general, RegA2 and RegB2 show a large decrease in the number of cyclones over the southern SAO due to an anticyclonic anomaly covering SAO between 30-55A degrees S. The reduction is larger in the scenario with higher concentrations of greenhouse gases (RegA2).

Temperature and precipitation effects on δ13C depth profiles in SOM under temperate beech forests

Enrichment of 13C in SOM with soil depth is related to interacting processes influenced by temperature and precipitation. Our objectives were to derive climate effects on patterns of vertical δ13C values of soil organic matter (SOM) while minimizing the effect of confounding variables. We investigated vertical changes in δ13C values of SOM in 1-cm depth intervals in silvicultural mature beech (Fagus sylvatica L.) forest ecosystems in northern Rhineland-Palatinate across gradients of MAT (7.9 to 9.7 °C mean annual temperature) and MAP (607 to 1085 mm mean annual precipitation) in winter 2011. Forest stands (n = 10) were chosen based on data sets provided by the Rhineland-Palatinate Forest Administration so that variations in these gradients occurred while other environmental factors like physico-chemical soil properties, tree species, stand age, exposition and precipitation (for the temperature gradient) or temperature (for the precipitation gradient) did not differ among study sites. From litter down to the mineral soil at 10 cm depth, soil organic carbon (SOC) content decreased (47.5 ± SE 0.1% to 2.5 ± 0.1%) while the δ13C values increased (− 29.4 ± 0.1‰ to − 26.1 ± 0.1‰). Litter of sites under higher MAP/lower MAT had lower δ13C values which was in line with literature data on climate driven plant physiological process. To compare the dimension of the vertical 13C enrichment, δ13C values were regressed linearly against log-transformed carbon contents yielding absolute values of these slopes (beta). Beta values ranged between 0.6 and 4.5 (range of r from − 0.7 to − 1.0; p < 0.01). Due to an assumed decay continuum and similar variations of δ13C values in litter and in 10 cm depth, we conclude that effects on isotope composition in the Oi layer continue vertically and therefore, δ13C values in litter do not solely control beta values. Beta values decreased with increasing MAT (r = − 0.83; p < 0.05). Reduced soil moisture and therefore both, reduced microbial activity and reduced downward transport of microbial cycled DOM (=13C enriched) might be responsible for less pronounced δ13C depth profiles in case of high temperatures. Greater C:N ratios (lower degradability) of the litter under higher temperatures likely contributed to these depth trends. Beta values increased with increasing MAP (r = 0.73; p < 0.05). We found decreasing C:N ratios in the mineral soil that possibly indicates higher decomposition under higher precipitation. Exclusion of the organic layers from linear regressions indicated a stronger impact of MAP on the development of δ13C depth profiles. Our results confirm temperature and precipitation effects on δ13C depth profiles and indicate stronger 13C enrichment under lower MAT/higher MAP. Therefore, time series of vertical δ13C depth profiles might provide insights into climate change effects.

Examining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibration data, with calibrations applied independently to the same models in three cases. The sensitivity of modelled yield to changes in temperature and precipitation was tested by systematically modifying values of 1981-2010 baseline weather data to span the range of 19 changes projected for the late 21st century at three locations in Europe.

Effect of temperature and precipitation on salmonellosis cases in South-East Queensland, Australia: An observational study

Objective Foodborne illnesses in Australia, including salmonellosis, are estimated to cost over $A1.25 billion annually. The weather has been identified as being influential on salmonellosis incidence, as cases increase during summer, however time series modelling of salmonellosis is challenging because outbreaks cause strong autocorrelation. This study assesses whether switching models is an improved method of estimating weather–salmonellosis associations. Design We analysed weather and salmonellosis in South-East Queensland between 2004 and 2013 using 2 common regression models and a switching model, each with 21-day lags for temperature and precipitation. Results The switching model best fit the data, as judged by its substantial improvement in deviance information criterion over the regression models, less autocorrelated residuals and control of seasonality. The switching model estimated a 5°C increase in mean temperature and 10 mm precipitation were associated with increases in salmonellosis cases of 45.4% (95% CrI 40.4%, 50.5%) and 24.1% (95% CrI 17.0%, 31.6%), respectively. Conclusions Switching models improve on traditional time series models in quantifying weather–salmonellosis associations. A better understanding of how temperature and precipitation influence salmonellosis may identify where interventions can be made to lower the health and economic costs of salmonellosis.

Surface temperature and precipitation variations in the western U.S. and their relation to large scale circulation indices [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): An analysis of the principal components of surface temperature and precipitation in the western U.S. is presented. Data consist of monthly mean temperature and total precipitation for 66 climate divisions west of the Continental Divide, for the years 1931-1984. The analysis is repeated for three separate combinations of months - the water year (Oct - Sept), the cool season (Oct - Mar) and the warm season (Apr - Sept). Inspection of monthly precipitation climatology indicates that selection of these combinations of months results in very few awkward splittings of the natural precipitation seasons found in the West.

Uncovering North American temperature and precipitation patterns associated with the Southern Oscillation

The extreme phases of the Southern Oscillation (SO) have been linked to fairly persistent classes of circulation anomalies over the North Pacific and parts of North America. It has been more difficult to uncover correspondingly consistent patterns of surface temperature and precipitation over much of the continent. The few regions that appear to have consistent SO-related patterns of temperature and precipitation anomalies are identified and discussed. Also discussed are regions that appear to have strong SO-related surface anomalies whose sign varies from episode to episode.

Exploratory temperature and precipitation reconstructions from the Qinling Mountains, north-central China

IEECAS SKLLQG

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation.

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.