Seasonal Means Research Articles

Land Use Regression Modelling of Outdoor NO₂ and PM2.5 Concentrations in Three Low Income Areas in the Western Cape Province, South Africa.

Air pollution can cause many adverse health outcomes, including cardiovascular and respiratory disorders. Land use regression (LUR) models are frequently used to describe small-scale spatial variation in air pollution levels based on measurements and geographical predictors. They are particularly suitable in resource limited settings and can help to inform communities, industries, and policy makers. Weekly measurements of NO2 and PM2.5 were performed in three informal areas of the Western Cape in the warm and cold seasons 2015–2016. Seasonal means were calculated using routinely monitored pollution data. Six LUR models were developed (four seasonal and two annual) using a supervised stepwise land-use-regression method. The models were validated using leave-one-out-cross-validation and tested for spatial autocorrelation. Annual measured mean NO2 and PM2.5 were 22.1 μg/m3 and 10.2 μg/m3, respectively. The NO2 models for the warm season, cold season, and overall year explained 62%, 77%, and 76% of the variance (R2). The PM2.5 annual models had lower explanatory power (R2 = 0.36, 0.29, and 0.29). The best predictors for NO2 were traffic related variables (major roads, bus routes). Local sources such as grills and waste burning sites appeared to be good predictors for PM2.5, together with population density. This study demonstrates that land-use-regression modelling for NO2 can be successfully applied to informal peri-urban settlements in South Africa using similar predictor variables to those performed in Europe and North America. Explanatory power for PM2.5 models is lower due to lower spatial variability and the possible impact of local transient sources. The study was able to provide NO2 and PM2.5 seasonal exposure estimates and maps for further health studies.

Aerosol columnar characteristics and their heterogeneous nature over Varanasi, in the central Ganges valley.

The Indo-Gangetic Basin (IGB) experiences one of the highest aerosol loading over the globe with pronounced inter-/intra-seasonal variability. Four-year (January 2011-December 2014) continuous MICROTOPS-II sun-photometer measurements at Varanasi, central Ganges valley, provide an opportunity to investigate the aerosol physical and optical properties and their variability. A large variation in aerosol optical depth (AOD: from 0.23 to 1.89, mean of 0.82 ± 0.31) and Ångström exponent (AE: from 0.19 to 1.44, mean of 0.96 ± 0.27) is observed, indicating a highly turbid atmospheric environment with significant heterogeneity in aerosol sources, types and optical properties. The highest seasonal means of both AOD and AE are observed in the post-monsoon (October-November) season (0.95 ± 0.31 for AOD and 1.16 ± 0.14 for AE) followed by winter (December, January, February; 0.97 ± 0.34 for AOD and 1.09 ± 0.20 for AE) and are mainly attributed to the accumulation of aerosols from urban and biomass/crop residue burning emissions within a shallow boundary layer. In contrast, during the pre-monsoon and monsoon seasons, the aerosols are mostly coming from natural origin (desert and mineral dust) mixed with pollution in several cases. The spectral dependence of AE, the aerosol "curvature" effect and other graphical techniques are used for the identification of the aerosol types and their mixing processes in the atmosphere. Furthermore, the aerosol source-apportionment assessment using the weighted potential source contribution function (WPSCF) analysis reveals the different aerosol types, emission sources and transport pathways.

TRMM PR Observed Spatial Patterns of The Convective-Stratiform Rainfall Over Indonesia and Their Response to ENSO

This study investigates the variability of convective and stratiform rainfall over Indonesia from 5 years (2004–2008) data of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The remote sensing data was employed to analyze the seasonal means and seasonal differences between convective and stratiform rainfall values. In addition, the El Niño Southern Oscillation (ENSO) analysis impact on two rainfall types was also done with exemplification in 2006 and 2007 event. Two datasets were used namely the probability and the rainfall accumulation from both rainfall types. The results showed that the probability of Indonesian stratiform rainfall type was higher than convective rainfall type. In contrast, convective rainfall type more contributed to rainfall values. Spatial patterns of convective-stratiform rainfall types have different spreads. Generally, convective rainfall supplied more rainfall over the land, whereas stratiform rainfall supplied more rainfall over the sea, except in December-January-February (DJF) season. The ENSO impact was clearly seen during September-October-November (SON) season from both rainfall types over the south. Moreover, the stratiform rainfall type was more affected by ENSO during June-July-August (JJA) season.

Characteristics of aerosol vertical profiles in Tsukuba, Japan, and their impacts on the evolution of the atmospheric boundary layer

Abstract. Vertical profiles of the aerosol physical and optical properties, with a focus on seasonal means and on transport events, were investigated in Tsukuba, Japan, by a synergistic remote sensing method that uses lidar and sky radiometer data. The retrieved aerosol vertical profiles of the springtime mean and five transport events were input to our developed one-dimensional atmospheric model, and the impacts of the aerosol vertical profiles on the evolution of the atmospheric boundary layer (ABL) were studied by numerical sensitivity experiments. The characteristics of the aerosol vertical profiles in Tsukuba are as follows: (1) the retrieval results in the spring showed that aerosol optical thickness at 532 nm in the free atmosphere (FA) was 0.13, greater than 0.08 in the ABL owing to the frequent occurrence of transported aerosols in the FA. In other seasons, optical thickness in the FA was almost the same as that in the ABL. (2) The aerosol optical and physical properties in the ABL showed a dependency on the extinction coefficient. With an increase in the extinction coefficient from 0.00 to 0.24 km−1, the Ångström exponent increased from 0.0 to 2.0, the single-scattering albedo increased from 0.87 to 0.99, and the asymmetry factor decreased from 0.75 to 0.50. (3) The large variability in the physical and optical properties of aerosols in the FA were attributed to transport events, during which the transported aerosols consisted of varying amounts of dust and smoke particles depending on where they originated (China, Mongolia, or Russia). The results of the numerical sensitivity experiments using the aerosol vertical profiles of the springtime mean and five transport events in the FA are as follows: (1) numerical sensitivity experiments based on simulations conducted with and without aerosols showed that aerosols caused the net downward radiation and the sensible and latent heat fluxes at the surface to decrease. The decrease in temperature in the ABL (−0.2 to −0.6 K) and the direct heating of aerosols in the FA (0.0 to 0.4 K) strengthened the capping inversion around the top of the ABL. Consequently, the ABL height was decreased by 133 to 208 m in simulations with aerosols compared to simulations without aerosols. (2) We also conducted simulations in which all aerosols were compressed into the ABL but in which the columnar properties were the same and compared with the simulation results for uncompressed aerosol profiles. The results showed that the reductions in net downward radiation and in sensible and latent heat fluxes were the same in both types of simulations. However, the capping inversion in the simulations with compression was weakened owing to aerosol direct heating in the ABL and the lack of direct heating in the FA. This resulted in an increase in the ABL height, compared with that in the simulations without compression. (3) The dependencies of the 2 m temperature and ABL height on the optical thickness and Ångström exponent in the FA were investigated using the results of the numerical sensitivity tests. The 2 m temperature and ABL height was decreased with an increase in the optical thickness, and their reduction rates increase with a decrease in the Ångström exponent because the optical thickness in the near-infrared wavelength region was large when the Ångström exponent was small. However, there was a case in which the Ångström exponent was large but the decrease in the ABL height was the largest of all the simulation results. In this case, the strong capping inversion due to the large extinction coefficient around the top of the ABL was an import factor. These results suggest that the vertical profiles of the aerosol physical and optical properties, and the resulting direct heating has important effects on the ABL evolution.

What’s that stuff? Hair removers

It’s almost summer in the Northern Hemisphere. Temperatures are rising, swimming pools are opening, and bare arms and legs are emerging from winter clothing. For some people, the start of shorts-and-swimsuit season means it’s time to get rid of body hair. These sunseekers have an array of techniques to turn to: hair removal creams, waxing and sugaring, lasers, and even a good ol’ pair of tweezers. Knowing how the various options work might help you decide which one to use. Getting rid of body hair is a billion-dollar industry and growing worldwide. But depilatories are nothing new. Evidence indicates that prehistoric cultures used stones and shark teeth as crude razors. Some ancient Egyptians removed hair with tweezers, razors, and pumice stones and ripped it out with wax or sugar pastes, leaving behind only their eyebrows. Chemical removers have ancient roots too. People living 6,000 to 7,000 years ago in what

Climate Change of 4\xb0C Global Warming above Pre-industrial Levels

Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4◦C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4◦C global warming will occur is 2084. Based on the median results of models that project a 4◦C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-tonoise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5◦C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the intermodel consistency is better for temperature than for precipitation.

ESTIMATION OF CURRENT DYNAMICS AND FORECAST OF GLACIOLOGICAL CHARACTERISTICS OF THE MALYI AKTRU GLACIER (CENTRAL ALTAI)

In the context of global and regional climatic changes in the Altai mountain region, observations performed in 1949–2014 demonstrated evident rises of air temperatures, both annual and seasonal means. Relative to the climatic norm (1949–1985), mean annual temperature (averaged for the period 1986–2014) had risen by 0.8– 1.9 °С. The most significant warming took place in winter and spring. In winter, the positive difference with the mean value is approximately equal to 0.9–3.8 °C, while in spring 0.9 and 1.7 °C. Air temperatures in summer and autumn periods were rising as well. Changes in annual and seasonal precipitations were more variable. The autumn and winter periods are characterized by a decrease in precipitation. On average, it is respectively 17% and 6%. In the spring and summer seasons, the tendency is opposite since these periods are characterized by a weak increase in precipitation. On average for the whole territory, the increase in the mean climatic amount of seasonal precipitation was equal to 2% and 4% relative the climatic norm for 1966–1985, for spring and summer respectively. The amount of annual precipitation on theterritoryofGorny Altairemained unchanged. Under current climate conditions which are characterized by decreasing in winter precipitation, the air temperature rise during all seasons, and longer warm period the mass balance of the Malyi Aktru Glacier becomes drastically negative. Total accumulation decreases, the ablation increases, and as a result, the negative mass balance grows. Using the methods of exponential smoothing, given the type of the trend component in series of meteorological quantities, a forecast of a 10‑year mean air temperature and the amount of atmospheric precipitation was made for the period 2021–2030. Using the appropriate regression equations, this allowed calculating predictive mean values of accumulation, ablation, and mass balance of the Malyi Aktru Glacier for the third decade of the XXI century

Variation in MERRA-2 aerosol optical depth over the Yangtze River Delta from 1980 to 2016

In this study, 765 instantaneous MERRA-2 (second Modern-Era Retrospective analysis for Research and Applications) aerosol optical depth (AOD) values at 550 nm were compared with those of a sky radiometer in Hefei (31.90° N, 117.17° E) for the different seasons from March 2007 to February 2010. The correlation coefficients (R) were 0.88, 0.83, 0.88, and 0.80 in spring, summer, autumn, and winter, respectively. The MERRA-2 AOD is also compared with MODIS Aqua AOD in the entire Yangtze River Delta, and good agreement has been obtained. The MERRA-2 AOD product was used to analyze the spatial distribution and temporal variation of the annual, seasonal and monthly means of the AOD over the Yangtze River Delta region from 1980 to 2016 (37 years). The mean values of the MERRA-2 AOD during the study period show that the AOD (between 0.45 and 0.55) in the northern area of the Yangtze River Delta was higher than that (between 0.30 and 0.45) of the southern area. The northwest part of the Yangtze River Delta had the highest mean AOD values (between 0.50 and 0.55). The AOD increased slowly in the 1980s and 1990s, followed by a rapid increase between 2001 and 2010. An AOD decrease can be seen from 2011 to 2016. The mean AOD in each month is discussed. High AOD was observed in March, April, and June, while low AOD could be seen in September, October, November, and December. Three different area types (large cities, medium-sized cities, and remote areas) had nearly the same annual AOD variation. Large cities had the highest AOD (about 0.48), while remote areas had the lowest (about 0.42). In summer, the AOD in remote areas was much lower than that in cities. The AOD variational trend over the Yangtze River Delta was studied during two periods. The increasing trend could be seen over the entire Yangtze River Delta in each month from 1980 to 2009. A decreasing trend was found all over the Yangtze River Delta in January, February, March, July, October, and November, whereas in other months, some parts witnessed increasing AOD while others saw a decreasing trend between 2010 and 2016.

Impacts and Limits of Irrigation Water Management on Wheat Yield and Quality

Crop Sci. 57(6):3239-3251, doi: 10.2135/cropsci2016.12.1032 In the original article, incorrect values for mean maximum and minimum temperature were published. in Table 3. The corrected table is included. In addition, the first paragraph of the Results section was corrected to reflect the changes in Table 3. Monthly and seasonal means for ambient mean, maximum, and minimum air temperatures were near normal (i.e., 26-yr average from 1989–2015) in 2014 (Table 3). However, in 2015, the seasonal maximum temperature was 2.4°C greater than normal and 5.9°C greater than the normal June temperature. The highest maximum temperature in June 2015 was 38°C (data not shown).

Estimation of Systematic Errors in the GFS Using Analysis Increments

AbstractWe estimate the effect of model deficiencies in the Global Forecast System that lead to systematic forecast errors, as a first step toward correcting them online (i.e., within the model) as in Danforth & Kalnay (2008a, 2008b). Since the analysis increments represent the corrections that new observations make on the 6 h forecast in the analysis cycle, we estimate the model bias corrections from the time average of the analysis increments divided by 6 h, assuming that initial model errors grow linearly and first ignoring the impact of observation bias. During 2012–2016, seasonal means of the 6 h model bias are generally robust despite changes in model resolution and data assimilation systems, and their broad continental scales explain their insensitivity to model resolution. The daily bias dominates the submonthly analysis increments and consists primarily of diurnal and semidiurnal components, also requiring a low dimensional correction. Analysis increments in 2015 and 2016 are reduced over oceans, which we attribute to improvements in the specification of the sea surface temperatures. These results provide support for future efforts to make online correction of the mean, seasonal, and diurnal and semidiurnal model biases of Global Forecast System to reduce both systematic and random errors, as suggested by Danforth & Kalnay (2008a, 2008b). It also raises the possibility that analysis increments could be used to provide guidance in testing new physical parameterizations.

Evaluation of Precipitation From EURO‐CORDEX Regional Climate Simulations in a Small‐Scale Mediterranean Site

AbstractThe evaluation of regional climate models' (RCMs') ability to reproduce the present‐day climate is critical to support their utility in impact studies under future climatic scenarios. This study evaluates the skill of an ensemble of state‐of‐the‐art regional climate simulations from the European Coordinated Regional Downscaling Experiment initiative in reproducing the precipitation (P) properties in Sardinia, a Mediterranean island of ~24,000 km2. The ensemble includes simulations at 0.44° and 0.11° grid spacing of the “Historical” experiment from 1950 to 2005. Precipitation records from a high‐density network of gauges are used as reference data set. The interannual and seasonal climatology of P, presence of trend, and orographic effect are assessed at the original RCM grid spacings and different spatial scales of aggregation. Most models capture the observed positive relation between annual P and elevation, with better performance at 0.11° spacing. The simulated spatial patterns of the climatological annual and seasonal means are well correlated with the observation at both spacings, but their spatial variability is overestimated. Positive and negative bias of up to ±60% are found in the simulation of annual mean and interannual variability. While the majority of the models reproduce the phase of the seasonal cycle, they underestimate (overestimate) winter (summer) P. The RCMs exhibit different deficiencies in capturing the negative annual and seasonal observed trends. In general, models' skill degrades when analyses are conducted at smaller aggregation scales. Results of this study reveal insight on RCM performances in small‐scale regions, which are often targeted by impact studies and have so far received less attention.

Modeling East Asian Dust and Its Radiative Feedbacks in CAM4‐BAM

AbstractEast Asian dust and its radiative feedbacks are analyzed by the use of the fourth version of the Community Atmosphere Model (CAM4) with a bulk aerosol model parameterization (BAM) for the dust size distribution (CAM4‐BAM). Two numerical experiments are conducted and intercompared: one with (Active) and one without (Passive) the radiative effects of dust aerosols. This CAM4‐BAM captures the main spatial distribution of the dust aerosol optical depth (AOD) and the dust surface concentrations over East Asia, with positive correlations with the local observational data on annual and seasonal means. A comparative analysis of the Active and Passive experiments reveals that consideration of the dust‐radiation interaction can significantly reduce dust emissions, loading, transport, and dry and wet depositions over East Asia, which is opposite to the enhanced dust cycle over North Africa. Further analysis of the contrasting dust‐radiation feedbacks between North Africa and East Asia shows that over North Africa, the dust radiative forcing significantly increases the surface temperature and 10 m wind speed, whereas it decreases the surface temperature and the surface wind speeds over East Asia. These contrasting radiative effects, in turn, result in distinct dust cycle changes over these two regions. Mechanistic analysis reveals that the radiative contrasts between East Asia and North Africa are mainly due to the differences in their regional surface albedo, dust vertical distribution, and size distribution.

A Poisson-Gamma Model for Zero Inflated Rainfall Data

Rainfall modeling is significant for prediction and forecasting purposes in agriculture, weather derivatives, hydrology, and risk and disaster preparedness. Normally two models are used to model the rainfall process as a chain dependent process representing the occurrence and intensity of rainfall. Such two models help in understanding the physical features and dynamics of rainfall process. However rainfall data is zero inflated and exhibits overdispersion which is always underestimated by such models. In this study we have modeled the two processes simultaneously as a compound Poisson process. The rainfall events are modeled as a Poisson process while the intensity of each rainfall event is Gamma distributed. We minimize overdispersion by introducing the dispersion parameter in the model implemented through Tweedie distributions. Simulated rainfall data from the model shows a resemblance of the actual rainfall data in terms of seasonal variation, means, variance, and magnitude. The model also provides mechanisms for small but important properties of the rainfall process. The model developed can be used in forecasting and predicting rainfall amounts and occurrences which is important in weather derivatives, agriculture, hydrology, and prediction of drought and flood occurrences.

A Poisson Gamma Model for Zero Inflated Rainfall Data

Rainfall modeling is significant for prediction and forecasting purposes in agriculture, weather derivatives, hydrology, risk and disaster preparedness. Normally two models are used to model the rainfall process as a chain dependent representing the occurrence and intensity of rainfall. Such two models helps to understand the physical features and dynamics of rainfall process. However rainfall data is zero inflated and exhibit overdispersion which is always underestimated by such models. In this study we have modeled the two processes simultaneously as a compound Poisson process. The rainfall events are modeled as a Poisson process while the intensity of each rainfall event is Gamma distributed. We minimize overdispersion by introducing the dispersion parameter in the model implemented through Tweedie distributions. Simulated rainfall data from the model shows a resemblance of the actual rainfall data in terms of seasonal variation, means, variance and magnitude. The model also provides mechanisms for small but important properties of the rainfall process. The model developed can be used in forecasting and predicting rainfall amounts and occurrences which is important in weather derivatives, agriculture, hydrology, and predicting of drought and flood occurrences.

Climate impacts on crop yields in Central Argentina. Adaptation strategies

The Pampas is among the major agricultural regions in the world; a large proportion of Argentina crop production is originated in this region. The exportation of grain and oil crop represents more than 40% of the total national exportations.Impact of future climate on wheat, maize and soybean yield and crop adaptation in the Pampas region (60 million hectares) are assessed using climatic inputs generated by CCSM4 climate model (National Center for Atmospheric Research, US). Projections show an increase in the seasonal means maximum and minimum temperature for both the near (2015–2039) and the far (2075–2099) future, as well as a seasonal annual precipitation increase in the near future and a significant increase in the far future with extreme emissions scenarios.In the near future the crop model projects a reduction in wheat yield, an increase in maize yield and a significant increment in soybean yield compared to the regional baseline for moderate (RCP4.5) and extreme (RCP8.5) emissions. In the far future the projection shows a decrease in wheat yield in the RCP4.5 scenario and an increase in the RCP8.5 scenario, maize and soybean shown a yield increase in both scenarios. Adaptation strategies for the near and far future are proposed for wheat and maize that result in up to 45% yield increases. Adaptation strategies are not proposed for soybean because yield increases were predicted in all scenarios and horizons.

CHASE-PL Climate Projection dataset over Poland – bias adjustment of EURO-CORDEX simulations

Abstract. The CHASE-PL (Climate change impact assessment for selected sectors in Poland) Climate Projections – Gridded Daily Precipitation and Temperature dataset 5 km (CPLCP-GDPT5) consists of projected daily minimum and maximum air temperatures and precipitation totals of nine EURO-CORDEX regional climate model outputs bias corrected and downscaled to a 5 km × 5 km grid. Simulations of one historical period (1971–2000) and two future horizons (2021–2050 and 2071–2100) assuming two representative concentration pathways (RCP4.5 and RCP8.5) were produced. We used the quantile mapping method and corrected any systematic seasonal bias in these simulations before assessing the changes in annual and seasonal means of precipitation and temperature over Poland. Projected changes estimated from the multi-model ensemble mean showed that annual means of temperature are expected to increase steadily by 1 °C until 2021–2050 and by 2 °C until 2071–2100 assuming the RCP4.5 emission scenario. Assuming the RCP8.5 emission scenario, this can reach up to almost 4 °C by 2071–2100. Similarly to temperature, projected changes in regional annual means of precipitation are expected to increase by 6 to 10 % and by 8 to 16 % for the two future horizons and RCPs, respectively. Similarly, individual model simulations also exhibited warmer and wetter conditions on an annual scale, showing an intensification of the magnitude of the change at the end of the 21st century. The same applied for projected changes in seasonal means of temperature showing a higher winter warming rate by up to 0.5 °C compared to the other seasons. However, projected changes in seasonal means of precipitation by the individual models largely differ and are sometimes inconsistent, exhibiting spatial variations which depend on the selected season, location, future horizon, and RCP. The overall range of the 90 % confidence interval predicted by the ensemble of multi-model simulations was found to likely vary between −7 % (projected for summer assuming the RCP4.5 emission scenario) and +40 % (projected for winter assuming the RCP8.5 emission scenario) by the end of the 21st century. Finally, this high-resolution bias-corrected product can serve as a basis for climate change impact and adaptation studies for many sectors over Poland. The CPLCP-GDPT5 dataset is publicly available at http://dx.doi.org/10.4121/uuid:e940ec1a-71a0-449e-bbe3-29217f2ba31d.

Block bootstrap for periodic characteristics of periodically correlated time series

ABSTRACTThis research is dedicated to the study of periodic characteristics of periodically correlated time series such as seasonal means, seasonal variances and autocovariance functions. Two bootstrap methods are used: the extension of the usual Moving Block Bootstrap (EMBB) and the Generalised Seasonal Block Bootstrap (GSBB). The first approach is proposed, because the usual Moving Block Bootstrap does not preserve the periodic structure contained in the data and cannot be applied for the considered problems. For the aforementioned periodic characteristics the bootstrap estimators are introduced and consistency of the EMBB in all cases is obtained. Moreover, the GSBB consistency results for seasonal variances and autocovariance function are presented. Additionally, the bootstrap consistency of both considered techniques for smooth functions of the parameters of interest is obtained. Finally, the simultaneous bootstrap confidence intervals are constructed. A simulation study to compare their actual coverage probabilities is provided. A real data example is presented.

A seasonal climatology of UV reflectivity for southern South America

ABSTRACTA seasonal climatology for the Lambertian equivalent reflectivity (LER) in ultraviolet (UV) for southern South America is introduced. The study region was limited by 10° and 60°S and by 100° and 30°W; the data set spanned the period 1978–2015. Features of the seasonal means and of the quarterly (Q) and the interannual (IA) variabilities for each season were ascribed to atmospheric and oceanic processes of local, regional, or global origin which lead to the formation or maintenance of clouds. Shifts in the Q and IA time series were detected, most notably in the early 1990s. Linear trends were also estimated. The largest positive and negative trends in the Q time series were found along the Peruvian Andes (PA) (3.20 reflectivity units [RU] decade−1) and east of the Chapada Diamantina (CD) and the Serra do Espinhaço (SE) in Brazil (−1.40 RU decade−1), respectively. The largest positive and negative trends in the IA time series were found in PA (6 RU decade−1, summer) and east of CD and SE (−2.50 RU decade−1, spring), respectively. The linkages between UV LER and regional or global circulation indices were also studied. The largest relationships were found with the Dipole Mode Index on a Q basis and with the Southern Oscillation Index on an IA basis in winter.

Spatiotemporal variations of differences between surface air and ground temperatures in China

AbstractThis study analyzed the temporal evolution and spatial distribution of the difference between ground surface temperature (GST) and surface air temperature (SAT) in China based on monthly station data (1970–2015). Overall, the spatial patterns and temporal evolutions of the annual and seasonal means of GST are similar to those of SAT. However, a dramatic increase in the difference between GST and SAT in northern China in winter is observed since 2005, which is due to a pronounced increase of GST and a slight decrease of SAT. The interdecadal variations of the tendencies of GST and SAT appear associated with the increase of snow depth in northern China (north of 40°N) in winter in recent decades, especially in northern Xinjiang, northern Inner Mongolia, and most parts of Northeast China. The connection of snow depth with the variation of GST‐SAT obtained from the station observations was consistent with that based on reanalysis data.

Spatial variability in factors that control the sinking flux of organic and inorganic particles in the Cariaco Basin: a vision from space

ABSTRACTThe Cariaco Basin, located on the continental margin of the south-eastern Caribbean Sea, has been a site of extensive oceanographic research since the early 1950s. Here we examined the seasonal and spatial variability in satellite wind, sea surface temperature (SST), surface chlorophyll (CHL), and primary production (PP) within the Cariaco Basin (1994–2009). This variability has implications in modulating the vertical flux of particulate material to the bottom of the basin. While cross-shore Ekman Transport was positive (upwelling inducing) year-round, it showed 20–60% higher values (stronger upwelling) in the eastern sub-basin, compared to the western sub-basin 1.35–2.77 m2 s−1 and 1.06–1.73 m2 s−1, respectively; p < 0.01). This translated into differences in CHL concentration and PP rates between the eastern and western Cariaco sub-basins. Long-term seasonal means of SST, CHL, and PP showed significant inter-basin differences (p < 0.01) between December and July; during that period the eastern basin was cooler (24.86 ± 1.03°C vs. 25.56 ± 0.80°C, p < 0.01), with higher CHL (0.50 mg m−3 vs. 0.35 mg m−3; p < 0.01) and PP (1763 ± 994 vs. 782 ± 129 mg C m−2 day−1, p < 0.01) than the western sub-basin. The eastern Cariaco sub-basin had larger seasonal amplitude and variability in oceanographic characteristics than the western sub-basin, while the western sub-basin had slightly higher and more variable seasonal riverine run-off inputs. These differences have implications for the interpretation of the paleoclimate sediment record stored in different sectors of the Cariaco Basin.