Interannual Variability Trends Research Articles

Estimation of Satellite-Based SO42− and NH4+ Composition of Ambient Fine Particulate Matter over China Using Chemical Transport Model

Epidemiologic and health impact studies have examined the chemical composition of ambient PM2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM2.5 data with a spatial resolution of 0.1 × 0.1°, we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of −35.9%, NME of 48.2%, ARB_50% of 53.68% for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO42− and NH4+ concentrations and time series of monthly average concentrations were also investigated. On a national scale, both exhibited a downward trend each year between 2004 and 2014 (SO42−: −0.61%; NH4+: −0.21%), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004–2007 and 2008–2011, followed by a negative trend over the period 2012–2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as follows: winter > summer > autumn > spring. High concentrations of these species were concentrated in the NCP and SCB, originating from coal-fired power plants and agricultural activities, respectively. Efforts to reduce sulfur dioxide (SO2) emissions have yielded remarkable results since the government has adopted stricter control measures in recent years. Moreover, ammonia emissions should be controlled while reducing the concentration of sulfur, nitrogen and particulate matter. This study provides an assessment of the population’s exposure to certain chemical components.

昆明大气降水稳定同位素与西南(印度)季风强度

根据全球降水同位素观测网(GNIP)提供的昆明站大气降水氢氧稳定同位素数据及其气象资料，对昆明站1986~1992、1996~2003年共计15年的月均和年均大气降水氢氧同位素组成及其影响因素进行分析和研究。结果表明：昆明月均及年均同位素组成均落在中国和全球降水同位素的变化范围之内，并呈现明显的季节及年际变化。昆明大气降水中δD和δ18O主要受到水汽来源影响，而且在季节和年际尺度上存在较大差异。经计算得出：昆明雨季(5~10月)降水中氧同位素值81.7%受当地降水量控制，18.3%受气温影响，这说明昆明大气降水中δ18O受降水量和气温的协同影响，但以降水量对其影响为主；通过年降水量与西南季风指数对比证实，昆明年降水量与西南季风指数呈正相关性，但与δ18O呈显著的负相性，由此说明在季风影响显著的单一态地区，可以用降水δ18O值指示降水强度或季风强度，这种季风强度-大气降水量-δ18O三者之间的关系可为研究石笋中所蕴含的环境信息提供依据。另外，通过与香港降水同位素对比研究，发现二者的d值虽然均呈现旱季高于雨季的季节性变化趋势，但它们的平均d值几乎相同，由于昆明与香港所处地理位置和距离海洋远近的差异明显，说明二者的水汽来源不同，昆明降水主要受印度洋的西南季风控制，香港降水则主要来源于太平洋控制的东南季风。昆明大气降水线斜率和截距的季节及年际变化趋势可用云下二次蒸发和动力分馏效应来解释。 Using isotope and meteorology data at Kunming station from the GNIP, the average monthly and annual hydrogen and oxygen stable isotopic compositions and the main factors of 15 years (1986-1992 and 1996-2003) at Kunming station were analyzed. The average monthly and annual hydrogen and oxygen stable isotopic compositions fall within the scope of changes in China and the global isotopes of precipitation, and the seasonal and interannual variations are significant. Hydrogen and oxygen stable isotopic compositions of precipitation at Kunming are mainly influenced by vapor source. There exist obvious differences in the seasonal and interannual scales. The local precipitation amount and air temperature determine 81.7% and 18.3% oxygen isotope values in the rainy season, respectively. Even the δ18O in precipitation affected by the precipitation amount and air temperature, the precipitation amount has a stronger affect on the δ18O in precipitation than the air temperature. In addition, the relationship between annual precipitation and Indian monsoon indexes show a positive correlation, but a significant negative correlation with δ18O in precipitation, illustrating that δ18O in precipitation indicates monsoon or rainfall intensity. The relationship between monsoon intensity and precipitation amount and the δ18O in precipitation can provide a scientific support on the meaning of the isotope of the stalagmites. Comparing the isotopes of precipitation in Kunming with that from Hong Kong station, their d values have distinct seasonality with lower values in the rainy season and higher values in the dry season, but they have almost similar values. Nevertheless, geographical location and distance from sea are different, illustrating that the vapor sources are different. Precipitation in Kunming is affected mostly by southwest monsoon from Indian Ocean, but the rainfall in Hong Kong is mainly controlled by southeast monsoon from Pacific Ocean. The seasonal and interannual variation trends of slope and intercept of Kunming precipitation can be explained by below-cloud secondary evaporation and dynamic fractionation effect.

The regional features of precipitation variation trends over Sichuan in China by the ESMD method

Based on a precipitation time series from 49 meteorological stations in Sichuan Province during the period from 1961 to 2011, the multi-scale characteristics of precipitation variability are analyzed using the extreme-point symmetric mode decomposition method (ESMD). Regional differences in variation trends and change-points were also preliminarily discussed. The results indicated that in the last 50+ years, the overall precipitation in Sichuan Province has exhibited a significant non-linear downward trend, and its changes have clearly exhibited an inter-annual scale (quasi-3 and quasi-8-year) and interdecadal scale (quasi-13-year). The variance contribution rates of each component demonstrated that the inter-annual change had a strong influence on the overall precipitation change in Sichuan Province, and the reconstructed inter-annual variation trend could describe the fluctuation state of the original precipitation during the study period. The reconstructed interdecadal variability revealed that the climate mode in Sichuan Province had divided into three distinct variation periods with 1973 and 1998 as the boundaries. Furthermore, there were regional differences in the non-linear changes and change-points of precipitation. In addition, in order to study the relations between the changing more or less of rising or decrease and meteorological station’s geographical position (latitude, longitude and elevation) i.e., the Cokriging interpolation technique is applied directly to precipitation variation trend components through ESMD decomposition. At the same time, the results also suggested that the ESMD method can effectively reveal variations in long-term precipitation sequences at different time scales and can be used for the complex diagnosis of non-linear and non-stationary signal changes.

Spatial and temporal characteristics of rainfall across Ganjiang River Basin in China

The hydrological variations of Ganjiang River Basin have significant influence on the ecological environment of Poyang Lake, which is one of the largest freshwater lake and wetland in the world. This study analyzed the spatial and temporal characteristics of rainfall across Ganjiang River Basin. The analyses include annual total rainfall amount (ATRA), annual total rainy day (ATRD) and annual mean daily rainfall intensity (AMDRI). To detect changes in the hydrological trends, data from 19 rainfall stations from 1953 to 2013 were used in the analyses. First, quality control and homogeneity detection was carried out to examine the annual rainfall series. Second, the spatial correlation analysis was used to identify the spatial relationship among the measurements from different stations. Finally, the statistics of coefficient of variation (CV) and average were used to analyze the interannual variation trend. The modified Mann–Kendall (MMK) trend test method was used to detect the temporal characteristics of rainfall. The results include: (1) Some outliers were detected and corrected. (2) The correlation of ATRA and ATRD series of all the stations had lower spatial variability while the AMDRI series of all the stations had higher spatial variability. On the other hand, the ATRA, ATRD and AMDRI series of single stations show similar spatial variability and the influencing radius of the rainfall events was less than 50 km. (3) the rainfall at the northern and southern parts of the basin had smaller CV. Further, by applying the MMK test method to the ATRA, ATRD, and AMDRI series, the ATRA series has an increasing trend which is opposite to that of the ATRD series. The increasing trend in the ATRA series also led to the increasing trend in the AMDRI series. These stations are mainly in central and northern parts of the basin which are more likely to experience droughts and floods. Thus, for the central and northern parts of the basin, they should receive particular attention on the prevention and treatment of droughts and floods.

Multi-scale response of runoff to climate fluctuation in the headwater region of Kaidu River in Xinjiang of China

Based on the hydrological and meteorological data in the headwater region of the Kaidu River during 1960–2009, the multi-scale characteristics of runoff variability were analyzed using the ensemble empirical mode decomposition method (EEMD), and the aim is to investigate the oscillation mode structure characteristics of runoff change and its response to climate fluctuation at different time scales. Results indicated that in the past 50 years, the overall runoff of Kaidu River in Xinjiang has showed a significant nonlinear upward trend, and its changes have obviously exhibited an inter-annual scale (quasi-3 and quasi-6-year) and inter-decadal scale (quasi-10 and quasi-25-year). Variance contribution rates of each component manifested that the inter-decadal change had been playing a more important role in the overall runoff change for Kaidu River, and the reconstructed inter-annual variation trend could describe the fluctuation state of the original runoff anomaly during the study period. The reconstructed inter-decadal variability effectively revealed that the runoff for Kaidu River changed over the years, namely the states of abundance and low water period appear alternately. In addition, we found that runoff has a positive correlation to precipitation and temperature at different time scales, but they are most significant and relevant at inter-decadal scale, indicating the inter-decadal scale is most suitable for investigating the responses of runoff dynamics to climate fluctuation. At the same time, the results also suggested that EEMD is an effective method to analyze the multi-scale characteristics of nonlinear and non-stationary signal.

An analysis of recent rainfall conditions in eastern Africa

This article examines recent rainfall conditions in two sectors of eastern Africa, the summer rainfall region and the equatorial rainfall region with rainy seasons in the boreal spring and boreal autumn. The analysis covers the years 1998–2014 and is carried out using TRMM 3B43 Version 7 rainfall estimates. In both regions, extensive periods of anomalously low rainfall and prolonged drought have prevailed since roughly 2008. Prior to that time, only three periods of drought are noteworthy 1998/1999, 2000, and 2005. The post-2008 drought conditions were interrupted by floods in both regions in February 2010 and in several years in the equatorial region. This rapid alternation between extremes creates additional hardships on the population. Two notable results emerge from this analysis. One is the tendency for similar trends in interannual variability in both regions, despite vastly different rainfall regimes. The other is the persistence of recent droughts through several rainy seasons. The implication of these results is that one or more factors in interannual variability is operative in all seasons. This could account for the common trends in the equatorial and summer rainfall regions.

Wetland Changes and Their Responses to Climate Change in the “Three-River Headwaters” Region of China since the 1990s

The wetland ecosystem in the “Three-River Headwaters” (TRH) region plays an irreplaceable role in water source conservation, run-off adjustment and biodiversity maintenance. In recent years, assessment of wetland resources affected by climate changes has aroused enormous attention, since it can further protect wetland resources and provide a scientific basis for decision makers. In this study, wetland changes and its response to climate changes in the TRH region from the early 1990s to 2012 were analyzed by remote sensing (RS) image interpretation and climate change trend analysis. The results showed that wetlands occupied 6.3% of the total land area in 2012, and swamps, streams & rivers and lakes were the dominant wetland types in the TRH region. Since the early 1990s, wetlands have undergone great changes, and total wetland area increased by 260.57 km2 (1.17%). Lakes, reservoir & ponds took on continuous increasing trend, but swamps, streams & rivers had a continuous decreasing trend. On the other hand, the wetland area in the Yangtze River basin showed an overall increasing trend, while in the Yellow River and Langcang River basins, it decreased in general. The climate turned from Warm-Dry to Warm-Wet. The average temperature and precipitation increased by 0.91 °C and 101.99 mm, respectively, from 1990 to 2012, and the average humidity index (HI) increased by 0.06 and showing an upward trend and a shifting of the dividing line towards the northwest in both the areas of semi-humid and semi-arid zone. The correlation analysis of wetland changes with meteorological factors from 1990 to 2012 indicated that the regional humidity differences and the interannual variation trend, caused by the change of precipitation and evaporation, was the main driving factor for the dynamic variation of wetland change in the TRH region. In the general, the increase of HI in the THR region since the 1990s, especially in the western TRH region, contributed to wetland increase continuously. The conclusions of this study will provide some scientific references for the management and protection of wetlands in the TRH region, especially for restoration, reconstruction and conservation of degradation wetland.

The effects of nutrient addition on plant species diversity in desert grassland, Xinjiang, northwest China

Fertilization (CK, N, P, K, NP, NK, PK, NPK) and watering (CK, rain, snow) were applied to a desert grassland of northwest Xinjiang, China. Results showed that: (1) After nutrient and water additions for one year, the plant community structure changed, the individual number of Graminoids increased significantly, while the individual number of Cruciferaes decreased sharply. The total species number was 16 before the treatment and 10 after the treatment, reduced by 37.5%. (2) The vegetation coverage above ground and the plant density increased significantly under the additions of NP and NPK (p < 0.05), while the other nutrient additions had no significant effects on the vegetation coverage and density. Neither additional snow addition nor rain had significant effects. (3) Compared with the control (CK), the additions of N, P and PK increased the diversity indexes (D &H′) and Evenness (J); the additions of K, NP, NK and NPK decreased the diversity indexes (D &H′) and evenness (J). However, neither of the treatments has significant effect on the diversity indexes and Evenness based on the ANOVA (p < 0.05). (4) Snow significantly decreased the plant species richness (p < 0.05). However, neither the rain nor the nutrient addition has significant effect on the species richness. (5) The inter-annual variation trend of the diversity indexes (D &H′) and Evenness (J) showed an increasing trend during 2009–2012.

A statistical spatial downscaling algorithm of TRMM precipitation based on NDVI and DEM in the Qaidam Basin of China

The availability of precipitation data with high spatial resolution is of fundamental importance in several applications such as hydrology, meteorology and ecology. At present, there are mainly two sources of precipitation estimates: raingauge stations and remote sensing technology. However, a large number of studies demonstrated that traditional point measurements based on raingauge stations cannot reflect the spatial variation of precipitation effectively, especially in ungauged basins. The technology of remote sensing has greatly improved the quality of precipitation observations and produced reasonably high resolution gridded precipitation fields. These products, derived from satellites, have been widely used in various parts of the world. However, when applied to local basins and regions, the spatial resolution of these products is too coarse. In this paper, we present a statistical downscaling algorithm based on the relationships between precipitation and other environmental factors in the Qaidam Basin such as topography and vegetation, which was developed for downscaling the spatial precipitation fields of these remote sensing products. This algorithm is demonstrated with the Tropical Rainfall Measuring Mission (TRMM) 3B43 dataset, the Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM) and SPOT VEGETATION. The statistical relationship among precipitation, DEM and Normalized Difference Vegetation Index (NDVI), which is a proxy for vegetation, is variable at different scales: therefore, a multiple linear regression model was established under four different scales (0.25 degrees, 0.50 degrees, 0.75 degrees and 1.00 degrees, respectively). By applying a downscaling methodology, TRMM 3B43 0.25 degrees x 0.25 degrees precipitation fields were downscaled to 1 x 1 km pixel precipitation for each year from 1999 to 2009. On the basis of three criteria, these four downscaled results were compared with each other and the regression model established at the resolution of 0.50 degrees was selected as the final downscaling algorithm in this study. The final downscaled results were validated by applying the observations for a duration of 11 years obtained from six raingauge stations in the Qaidam Basin. These results indicated that the downscaled result effectively captured the trends in inter-annual variability and the magnitude of annual precipitation with the coefficient of determination r(2) ranging from 0.72 to 0.96 at six different raingauge stations.

Reservoirs Effects on the Interannual Variability of Winter and Spring Streamflow in the St-Maurice River Watershed (Quebec, Canada)

The aim of this study was to test three main hypotheses about the interannual variability of streamflow downstream from dams: (1) an almost similar long-term trend in interannual variability, (2) low variability of flow, and (3) its independence (no link) from climate variability. To test these hypotheses, the interannual variability of winter and spring streamflow downstream from three reservoirs (Gouin, Manouane, and Matawin) which induce an inversion of the natural cycle of streamflow (maximum flows in winter and minimum flows in spring) was compared to the interannual variability of streamflow in natural rivers (measured at the Matawin and Vermillon stations) over the period from 1932 to 2008 in the St-Maurice River watershed. As far as the interannual variability of flow is concerned, its long-term trend is not homogeneous downstream from the three reservoirs in both seasons. However, downstream from two reservoirs, changes in streamflow were observed to be different from those in natural rivers (no significant trend downstream from the Taureau reservoir, on the Matawin River, and significant decrease in spring flow downstream from the Manouane reservoir). Finally, coefficient of variation values for minimum flows are higher downstream from reservoirs than in natural rivers, despite the fact that watershed surface area is larger for regulated rivers than for natural ones. As for the link with climate variability, analysis of the correlation between climate variables (temperature and precipitation) and mean winter and spring daily streamflow reveals that winter streamflow downstream from the Taureau reservoir is not correlated with any climate variable, whereas spring streamflow is positively correlated with rainfall and negatively correlated with maximum temperature. Thus, downstream from reservoirs, the interannual variability of streamflow depends on climate during the spring, but not during winter.

Reproductive potential of the eastern baltic cod Gadus morhua callarias L. population

Trends in interannual variation in maturation and spawning terms of various age cohorts in the Eastern Baltic cod population in 1997-2009 were studied. Specific features in the age structure of the mature population part that were established by the end of the first decade of the 21st century were clarified. The role of cod age cohorts in the current population reproduction was considered taking into account the data on cod recruitment and fecundity.

The effects of drought and timing of precipitation on the inter-annual variation in ecosystem-atmosphere exchange in a Mediterranean grassland

We studied the seasonal and inter-annual variation in carbon, water and energy fluxes over a Mediterranean grassland ecosystem in Portugal, dominated by annual species, using the eddy-covariance technique. The study period, from 2004 to 2008, was characterised by high intra- and inter-annual precipitation variation: the hydrological years 2004–2005 and 2007–2008 had precipitation below average (‘dry’ years) whereas the other two hydrological years had precipitation above average (‘wet’ years). The variation in energy partitioning into sensible heat ( H) and latent heat ( λE) fluxes was associated with changes in soil water content, coinciding with plant emergence and senescence. The ecosystem was λE-dominated in those periods with soil water content above 15%, and became H-dominated when soil water content fell below 15%. Annually integrated net ecosystem carbon exchange (NEE) was highly sensitive to drought, varying from a carbon sink in ‘wet’ years (e.g., 2005–2006, −190 g C m −2 y −1), to a carbon source in ‘dry’ years (e.g., 2004–2005, +49 g C m −2 y −1). There was a negative correlation between annually integrated NEE and annual precipitation ( r 2 = 0.78). However, timing of precipitation influenced NEE, with individual rain events in the dry season resulting in large pulses of ecosystem respiration ( R eco). Low precipitation at the peak of the growing season, as in the spring of 2007, decreased carbon sequestration. The best descriptor for inter-annual variation in NEE was leaf area duration (LAD), which explained 96% of the variance. Average radiation-use efficiency (RUE) was 1.59 g MJ −1 and inherent water-use efficiency (IWUE) was 24.6 g C hPa kg −1 H 2O. RUE and IWUE had similar trends in inter-annual variation, reflecting differences in productivity and timing of precipitation. Our study showed that carbon and energy fluxes in this Mediterranean environment depended strongly upon water availability.

Copepod biomass, size composition and production in the Southern Benguela: Spatio–temporal patterns of variation, and comparison with other eastern boundary upwelling systems

Zooplankton sampling has been conducted biannually off the west and south-west coasts of South Africa since 1988, as part of the pelagic fish stock assessment cruises covering the continental shelf (0–200 m). Previously established relationships between body mass and growth rate were used to derive copepod production. Mean copepod biomass and annual production in the Southern Benguela between 1988 and 2003 were 2.1 g C m −2 and 134.4 g C m −2 yr −1, respectively. Biomass and production were higher during summer in four latitudinal areas, but seasonal variability was only significant for the central West Coast. This area, lying downstream from the Cape Columbine upwelling cell, supported the highest levels of copepod biomass (3.1 g C m −2) and production (545 g C m −2 d −1). Production during winter, when upwelling is minimal, contributed over one third of annual production in all four areas. Copepod biomass, daily production and size composition varied with latitude, season and year, and there were no consistent trends in interannual variability over the study period. Although biomass in the four major EBUS was of the same magnitude (usually <5 g C m −2), annual production estimates are an order of magnitude greater than those made four decades ago, with highest values for the Southern Benguela.

Rainfall trends in the KwaZulu‐Natal Drakensberg region of South Africa during the twentieth century

AbstractThis study assesses long‐term rainfall records in the KwaZulu‐Natal Drakensberg, South Africa's most valuable source of surface runoff. Records from 11 stations covering the Drakensberg region in South Africa indicate that no statistically significant trend in interannual variability existed during the last half of the twentieth century. Annual rainfall in the Drakensberg is highly seasonal, and analysis of monthly rainfall indicates an increase in the variability of the distribution of monthly rainfall and the strengthening of rainfall seasonality in the Drakensberg through a significant decrease in autumn rainfall. The El Niño/Southern Oscillation (ENSO) influences summer rainfall variability of the KwaZulu‐Natal Drakensberg, and a strong correlation also exists between summer rainfall and the Southern Oscillation Index (SOI) for preceding periods. This correlation between summer rainfall and ENSO events suggests that changes in the frequency and intensity of the ENSO should affect the rainfall in the Drakensberg. The lagged correlation between summer rainfall in the Drakensberg and the SOI could be used as an indicator for seasonal forecasting. Copyright © 2008 Royal Meteorological Society

Aerosol influence domain of Beijing and peripheral city agglomeration and its climatic effect

The aerosol distribution in Beijing and peripheral cities agglomeration (BPCA) and its regional climatic effect are investigated on the basis of the statistical analyses of satellite Total Ozone Mapping Spectrometer (TOMS) retrieval aerosol optical depth (AOD) and the meteorological data of sunshine duration, fog days, and low cloud cover, observed at Beijing and its peripheral meteorological stations. The analysis on multi-samples variational correction of the satellite remote sensing Moderate Resolution Imaging Spectroradiometer (MODIS) AOD under the clear sky and stable weather condition in conjunction with surface observations reveal that there was a “triangle-like” distribution pattern of the high values of aerosols in the southern “valley” of the “U-shape” megarelief of Beijing and its peripheral areas. The distribution pattern suggests that the large-scale transfer and diffusion of city agglomeration pollutants might form a relatively persistent characteristic spatial distribution of city agglomeration pollutants much larger than city-scale. Under the background of the particular megarelief effect of Beijing and peripheral areas, the high value area of TOMS AOD, as well as regional correlation distribution between clear sky sunshine duration and TOMS AOD are also similar to the composite image of MODIS AOD variational fields, that is to say, the effect of atmospheric aerosols was very distinctive in Beijing and peripheral areas. The high value area of the negative correlation between clear sky sunshine duration and TOMS AOD approximately accorded with the significant negative value area of the sunshine duration deviations of the 1980s to the 1990s, and the daily variations of the AOD also showed an anti-phase relation with those of clear sky sunshine duration. The above high correlation area of the urban aerosol impact of Beijing-Tianjin region leant towards south peripheral area, with its “center of gravity” in the south of Beijing-Tianjin agglomeration, and the main body of the high correlation area prolongating southwards, forming an aerosol influence domain of “eccentric ellipse” shape, that is to say, there was an aerosol influence domain of some “radius” in Beijing City and its peripheral areas, within and outside which sunshine duration, low cloud cover, and fog days showed a remarkable difference in interannual variation trend. At the downstream of the city agglomeration there was a significant interdecadal increment area of fog or low cloud cover, which might be associated with the local climatic feature of the regional flow convergent field in the diffusion process of city agglomeration pollutants in the aerosol influence domain, and such a local dynamical convergence feature might lead to the regional exacerbation of aerosol impact downstream of the city agglomeration. The research result reveals that the significant area of interdecadal change rate of low cloud cover within the aerosol influence domain is correlated with the regional strengthening effect of aerosol impact of the local wind structure in the “downstream plume area” of the city.

Spatiotemporal distribution characteristics of the fog regions in China

The spatial distribution and monthly/annual variation of foggy days in China are analyzed based on the monthly mean fog data collected from 604 observational stations for the period 1961–2000. Results show that there are six fog regions in China: the middle reaches of the Yangtze River, coastal areas, Yunnan-Guizhou Plateau, eastern Gansu-Shaanxi region, Huaihe River valley, Tianshan mountainous area and northern Xinjiang. On the whole the interannual variation trend of foggy days is descending, especially an obvious decline after the 1980s. The areas where the foggy days have obvious tendency present a southwest-northeast direction. The rising trend regions alternate with descending trend regions, forming a SE-NW directional wave structure. In general, the number of foggy days in autumn and winter is larger than in spring and summer over most fog regions. The monthly variation curves of foggy days are bimodal in the coastal area of the Yellow Sea and northern Xinjiang, and unimodal in other regions.

A New View on Lyme Disease: Rodents Hold the Key to Annual Risk

Any kid who spent summers playing in the woods knew Mom wouldn't let you back in the house without a head-to-toe search for ticks—vectors for a wide range of pathogens throughout the world's temperate regions. In the United States, Rocky Mountain spotted fever was the main concern until 1975, when Lyme disease was found in Connecticut. Since then, incidence has skyrocketed from 497 cases reported in 1982 (the first year national statistics were collected) to a record 23,763 in 2002. Lyme disease, like other zoonoses, is transmitted by a vector that picks up the pathogen during a blood meal from a vertebrate host. In the eastern and central United States, the spirochete bacterium Borrelia burgdorferi infects blacklegged ticks, Ixodes scapularis, which feed on a wide variety of birds, lizards, and mammals, including mice, deer, and humans. Since human risk is a function of the prevalence of infection among vectors, outbreak prevention depends in part on understanding what controls infection rates among the agents of transmission. In a new study, Richard Ostfeld, Felicia Keesing, and colleagues examined the ecological determinants of Lyme disease over a 13-year period in southeastern New York, a hot zone for the disease. Combining field data with computer simulations, they analyzed trends in interannual variation and found two powerful predictors of entomological risk of Lyme disease in a given year: abundance of tick hosts—white-footed mice and chipmunks—in the previous year and abundance of acorns—which sustain the rodents—two years out. Their findings upset the long-held view that deer and climate are the best indicators of disease risk. I. scapularis larvae hatch in midsummer, and acquire infection after feeding on an infected mouse or other small animal. Larvae detach after several days of feeding, then molt into nymphs and enter a nearly year-long dormant stage. After another round of feeding, nymphs fall off and molt into adults, which prefer the blood of larger mammals. Larvae and nymphs can acquire and transmit infection, but people are most likely to contract Lyme disease from nymphs. A person's risk of exposure to Lyme disease depends on the population density of infected nymphal ticks, which is a product of the total density of nymphs and the nymphal infection prevalence. (Humans can reduce their personal risk by using repellents and routinely checking for ticks when visiting high-risk areas.) Many studies have examined variations in climate and white-tailed deer population dynamics as determinants of tick abundance and disease risk. But few have investigated the impacts of fluctuations in the abundance of hosts for larval ticks, and none have examined all of these variables—temperature, precipitation, deer, mice, chipmunks, and acorns—simultaneously over such a long period. From 1991 to 2004, the researchers collected temperature and precipitation data, and estimated the abundance of acorns and animals on six plots of land. From this 13-year dataset, they developed computer models to estimate how each of the 11 variables (including multiple climate and deer indexes) contributed to yearly variations in the density of infected ticks and thus risk of human exposure. While none of the climate variables influenced nymphal infection prevalence, higher temperatures in the previous year and precipitation patterns in the current year had weak, though unexpected, effects on total density and density of infected nymphs. It's thought that higher temperatures keep tick populations down, but the models showed them increasing both total density and density of infected nymphs. And though tick survival is expected to rise with precipitation, the models found the highest tick numbers at intermediate precipitation levels. These inconsistencies can be explored by incorporating other variables with documented effects into the approach outlined here. Also surprising, the researchers found that even a 3-fold variation in deer numbers had no impact on subsequent nymph abundance. Density of infected nymphs—the principal determinant of Lyme disease risk—varied significantly from year to year, fueled mostly by large fluctuations in total nymph density, which in turn depended mostly on fluctuations in abundance of acorns, mice, and chipmunks. Interestingly, though chipmunk densities are generally lower than mice, their numbers were the best predictor of total nymph density in the subsequent year, likely reflecting their inferior grooming skills. Overall, the results found that acorns were the best predictor of Lyme disease risk—stemming from their crucial role in supporting white-footed mice, chipmunks, and likely other small animals, which in turn provide large reservoirs for B. burgdorferi. Acorns will not be a universal predictor of risk, the researchers acknowledge, since the disease occurs in areas without oaks. But the strength of these findings suggests that the observed link between increased Lyme disease risk and high rodent densities indicates that important food sources—or predators—of the rodent hosts of nymphs will be valuable predictors of disease risk.

Arctic sea ice trends and narwhal vulnerability

Conservation measures related to global climate change require that species vulnerability be incorporated into population risk models, especially for those that are highly susceptible to rapid or extreme changes due to specialized adaptation. In the case of Arctic cetaceans, effects of climate change on habitat and prey availability have been subject to intense speculation. Climate perturbations may have significant impacts on the fitness and success of this group, yet measuring these parameters for conservation purposes is complicated by remote and offshore preferences. The narwhal ( Monodon monoceros) in Baffin Bay occupies a habitat where reversed (increasing) regional sea ice trends have been detected over 50 years. We used a combination of long-term narwhal satellite tracking data and remotely sensed sea ice concentrations to detect localized habitat trends and examine potential vulnerability. Spatial and temporal variability in the fraction of open water were examined on two narwhal wintering grounds between November and April, 1978–2001 using approximate sea ice concentrations derived from microwave SSMR/SSMI passive brightness temperatures. Less than 3% open water was available to narwhals between 15 January and 15 April, and reached minima of 0.5% open water at the end of March (125 km 2 out of a 25,000 km 2 area). Decreasing trends in the fraction of open water, together with increasing trends in interannual variability, were detected on both wintering grounds, significantly in northern Baffin Bay (−0.04% per year, SE 0.02). The limited number of leads and cracks available to narwhals during the winter, in combination with localized decreasing trends in open water and high site fidelity, suggests vulnerability to changes in Arctic sea ice conditions. Increasing risk of ice entrapments, many of which may go undetected in remote offshore areas, should be incorporated into population risk assessments as this may exceed the natural response capacity of the species.

Continental-scale comparisons of terrestrial carbon sinks estimated from satellite data and ecosystem modeling 1982–1998

A simulation model based on satellite observations of monthly vegetation cover was used to estimate monthly carbon fluxes in terrestrial ecosystems from 1982 to 1998. The NASA–CASA model was driven by vegetation properties derived from the Advanced Very High Resolution Radiometer (AVHRR) and radiative transfer algorithms that were developed for Moderate Resolution Imaging Spectroradiometer (MODIS). For the terrestrial biosphere, predicted net ecosystem production (NEP) flux for atmospheric CO 2 has varied widely between an annual source of −0.9 Pg C per year and a sink of +2.1 Pg C per year. The southern hemisphere tropical zones (SHT, between 0° and 30°S) have a major influence over the predicted global trends in interannual variability of NEP. In contrast, the terrestrial NEP sink for atmospheric CO 2 on the North American (NA) continent has been fairly consistent between +0.2 and +0.3 Pg C per year, except during relatively cool annual periods when continental NEP fluxes are predicted to total to nearly zero. The predicted NEP sink for atmospheric CO 2 over Eurasia (EA) increased notably in the late 1980s and has been fairly consistent between +0.3 and +0.55 Pg C per year since 1988. High correlations can be detected between the El Niño Southern Oscillation (ENSO) and predicted NEP fluxes on the EA continent and for the SHT latitude zones, whereas NEP fluxes for the North American continent as a whole do not correlate strongly with ENSO events over the same time series since 1982. These observations support the hypothesis that regional climate warming has had notable but relatively small-scale impacts on high latitude ecosystem (tundra and boreal) sinks for atmospheric CO 2.

Extraseasonal ensemble numerical predictions of winter climate over China

Using the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM) under the Chinese Academy of Sciences, 30-year extraseasonal short-term ensemble hincast of winter climate is performed, with integrations starting from annual autumn during 1969–1998. Winter climate predictability over China is then evaluated for the first time. It follows that the predictability is higher in tropics than in extratropics. Also, it is higher over ocean compared with land, especially for surface air temperature. With height increasing in troposphere, the predictability of geopotential height slightly changes zonally, but for weakening of band-ship distribution and dropping near the date line. Of all analyzed variables, the prediction skill of air temperature and geopotential height (precipitation) is the highest (smallest). In addition, the predictability of winter climate over China and even East Asia enhances obviously during ENSO cycle, especially during La Nina phase. Simulation comparison against verifying analysis for surface temperature anomaly exhibits the model’s skill in predicting surface temperature’s interannual variation trend in winter.