Small Interannual Variations Research Articles

Deciphering the spatiotemporal trade-offs and synergies between ecosystem services and their socio-ecological drivers in the plain river network area

Understanding changes in ecosystem services (ESs) and quantitatively identifying the drivers that influence these changes are essential for achieving sustainable ecosystem development. In this study, multiple data sources and techniques, including meteorological data, land use/cover data, soil data, the InVEST model, and ArcGIS, were used to analyze the spatiotemporal variation characteristics of carbon storage, habitat quality, soil retention, water yield, and crop product supply in Xinghua City from 2000 to 2015. Additionally, we explored the causes of these changes and the interrelationships among these ESs. The results showed that: (1) During the study period, carbon storage and habitat quality declined, water yield fluctuated and increased, and soil retention had small interannual variations. The supply capacity of crop products first increased rapidly and then stabilized. (2) ESs were influenced by multiple drivers, with altitude having the strongest explanatory power for habitat quality and soil retention, and food production having the strongest explanatory power for crop product supply. (3) Relationships between different ESs were variable and changed over time. This study could enrich the understanding of spatial and temporal changes and drivers of ESs in the plain river network area, which has important implications for future land use planning and sustainable development of ESs.

Formation and variations of dew and hoarfrost in the Hulu Catchment on Northeast Qinghai-Tibet Plateau, China

Study regionThe Hulu Catchment on Northeast Qinghai-Tibet Plateau, China Study focusDew and hoarfrost (DH) are prominent components of the Non-Precipitation Water Inputs in arid and semi-arid regions, but research into them is mostly neglected in alpine regions. To understand the formation and variations of DH, as well as whether DH has a significant impact on the water balance and ecosystem, a field measurement experiment of dew was conducted in the Hulu Catchment. Meanwhile, the amount, duration, and frequency of DH at different elevations in the Hulu Catchment from 2016 to 2020 were estimated using the Penman equation. New hydrological insights for the regionDH was common weather phenomenon in the Hulu Catchment, with small interannual and large monthly variations in amount, duration, and frequency. DH showed significant seasonal pattern and elevation dependence, which depending on the seasonal pattern and elevation dependence of meteorological factors. The mean annual amount of DH ranged from 3 mm to 33 mm, contributing 0.3–7.3% of precipitation, indicating that DH was not a critical component of water balance. Nevertheless, DH was ecologically important in replenishing surface soil water deficits and mitigating diurnal fluctuations in surface temperature, protecting vegetation and microorganisms from water and temperature stress in alpine regions. This study has important implications for understanding the energy transfer, water cycle and ecosystem operation in alpine regions.

Limitations of the radon tracer method (RTM) to estimate regional greenhouse gas (GHG) emissions – a case study for methane in Heidelberg

Abstract. Correlations of nighttime atmospheric methane (CH4) and 222radon (222Rn) observations in Heidelberg, Germany, were evaluated with the radon tracer method (RTM) to estimate the trend of annual nocturnal CH4 emissions from 1996–2020 in the footprint of the station. After an initial 30 % decrease in emissions from 1996 to 2004, there was no further systematic trend but small inter-annual variations were observed thereafter. This is in accordance with the trend of total emissions until 2010 reported by the EDGARv6.0 inventory for the surroundings of Heidelberg and provides a fully independent top-down verification of the bottom-up inventory changes. We show that the reliability of total nocturnal CH4 emission estimates with the RTM critically depends on the accuracy and representativeness of the 222Rn exhalation rates estimated from soils in the footprint of the site. Simply using 222Rn fluxes as estimated by Karstens et al. (2015) could lead to biases in the estimated greenhouse gas (GHG) fluxes as large as a factor of 2. RTM-based GHG flux estimates also depend on the parameters chosen for the nighttime correlations of CH4 and 222Rn, such as the nighttime period for regressions and the R2 cut-off value for the goodness of the fit. Quantitative comparison of total RTM-based top-down flux estimates with bottom-up emission inventories requires representative high-resolution footprint modelling, particularly in polluted areas where CH4 emissions show large heterogeneity. Even then, RTM-based estimates are likely biased low if point sources play a significant role in the station footprint as their emissions may not be fully captured by the RTM method, for example, if stack emissions are injected above the top of the nocturnal inversion layer or if point-source emissions from the surface are not well mixed into the footprint of the measurement site. Long-term representative 222Rn flux observations in the footprint of a station are indispensable in order to apply the RTM method for reliable quantitative flux estimations of GHG emissions from atmospheric observations.

Performance stability of the MODIS and VIIRS LAI algorithms inferred from analysis of long time series of products

The science teams of Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imager Radiometer Suite (VIIRS) have been supporting various global climate, biogeochemistry, and energy flux research efforts by producing valuable long-term Leaf Area Index (LAI) products. Although intensive LAI validation studies have been carried out globally, retrieval accuracy has been assessed only over short time spans and product quality is reported as a constant based on the assumption that it is stationary. However, a preliminary evaluation found a time-dependent signal degradation of the MODIS sensors which may cause the uncertainty of the Bidirectional Reflectance Factor (BRF) product to exceed the preset uncertainty buffer in the retrieval algorithm and result in MODIS LAI quality variation and time-series inconsistency with VIIRS LAI. Therefore, to ensure the reliability of trend-detection studies and to answer the critical question of whether the algorithm configuration is still suitable for the uncertainty level of present BRF product, there is a need for a more comprehensive investigation regarding the performance stability of LAI retrieval algorithm due to model uncertainty and input uncertainties. This paper reports analyses of inter-annual stability and trends of LAI uncertainties (inferred from product quality flag rather than ground-based validation) as well as LAI magnitudes using multi-year (MODIS: 2001–2019, VIIRS: 2013–2019) and multi-site (445 sites) datasets. We found that the quality metrics of the two products are consistent across different biome types and LAI values (R2 ranged from 0.88 to 0.99). In the 19-year MODIS period, we found a significant increasing trend in LAI magnitudes (4.5%/decade) which agrees with previous reports, while there was no significant trend in product quality. Moreover, quality metrics showed much smaller inter-annual variations than LAI values, which confirms the performance stability of retrieval algorithms and suggests that the configuration of MODIS algorithm is still compatible with the uncertainty of algorithm inputs. Additionally, this study provides support to the “Greening Asia” studies by eliminating the possibility that the “greening” could be attributed to artificial trends caused by sensor degradation. We also found very small inter-annual variations in atmospheric conditions (e.g., cloud and aerosols), which further assures that the performance stability of retrieval algorithm. Overall, our results demonstrate the robustness of the retrieval algorithm in the presence of changes in input uncertainties. The temporal stability of the algorithm performance indirectly strengthen the confidence in the continuous use of MODIS LAI products either independently or in combination with its successor - VIIRS LAI - to study global and regional vegetation dynamics

Projected distribution of the warm season droughts over the territory of Ukraine in 2021-2050

Introduction. Drought is a natural phenomenon that occurs in all climates, and is one of the most relevant natural hazards, which propagates through the full hydrological cycle and affects large areas, often with long-term economic and environmental impacts. A prolonged deficit in precipitation over a defined region cause a meteorological drought, while the other types of drought describe secondary effects on specific ecological and economic compartments. Recent trends in the drought distribution and intensity shows that Europe splits into two big areas, in which the southern and western regions have positive trends of drought frequency, duration, and severity, and the northern and eastern regions show a decrease in this parameters. Regarding the long events, territory of Ukraine belongs to the areas in which a prominent decrease in drought frequency, duration and severity are fixed. But positive trends in the drought characteristics are observed on the Black Sea coast, also in the Carpathian region, many droughts occurred in the past three decades. The purpose of this study to examine the results of analysis of the spatiotemporal distribution of warm season droughts (April-October) across the administrative areas of Ukraine in 2021-2050 under the climate scenarios RCP4.5 and RCP6.0 with them comparing. Data and methods. Drought estimation was performed using the SPEI index (the Standardized Precipitation Evapotranspiration index). The inclusion of temperature through the potential evapotranspiration (PET) along with precipitation data allows SPEI to account for the impact of temperature regime on a drought situation. A drought episode for given time scale is defined as a period, in which SPEI is continuously negative and reaches a value of –1.0 or less. In this study, the gridded fields of monthly air temperature and precipitation intensity from multimodel sets of global CMP5 models are taken for calculations of SPEI. Data access was made through the Climate Explorer. All data were averaged over the area of each of 25 administrative regions of Ukraine. Research results. Analysis of the time series of the calculated SPEI index for both scenarios showed that in all regions of Ukraine there will be a tendency to transition from moderately wet conditions in 2021-2035 to droughty conditions in 2037-2050. In the first half of the study period drought is expected near 2024, as well as in 2030-2033 almost in all provinces except southern areas. In the second half of the period prolonged seasonal drought is projected in 2044-2047 over all Ukraine and in some areas drought may reach an extreme intensity. Decade analysis of the SPEI7 time series showed that in both scenarios in all regions of Ukraine, the least number of dry seasons is expected from 2021 to 2030. The highest number of dry seasons in this period may reach up to 4-5 cases per 10 years in the western regions under RCP6.0 scenario. In other regions the number of dry warm seasons will be 2-3 cases per 10 years. In the period from 2031 to 2040, the number of dry seasons will increase substantially in all regions of Ukraine under RCP4.5 scenario, in which their number will be 5-6 cases per 10 years. Under RCP6.0 scenario, an increase in the number of droughts will be observed in all areas except the western regions, where will be from 2 to 4 dry seasons per 10 years. In the last decade from 2041 to 2050, in both scenarios, the number of dry seasons will increase throughout Ukraine compared to the previous decade. Under RCP6.0 scenario, the greatest increase is projected in the north of the country and in some other regions throughout Ukraine, where the maximum number of seasons with droughts will reached up 8-10 cases per 10 years. Conclusions. Comparison of the SPEI7 time series for both scenarios showed that under RCP6.0 scenario the transition from wet conditions to dry conditions is projected during long period from 2030 to the early 2040s. In this time, small interannual variations of the SPEI index across all regions are expected, and only in the last decade the dry seasons will prevail. In addition, in the RCP6.0 scenario, maxima of drought frequency are expected in few different regions of the country, compared with the RCP4.5 scenario, which indicates significant scenarios' differences in the predicted state of the regional atmospheric circulation determined the temperature and precipitation regimes in the future.

Phenology of the tree community in a seasonal forest in southern Brazil

Seasonal variations in environmental factors, such as precipitation, influence plant phenology and the relative importance of each factor, differ according to the ecosystem in question. In this study, we evaluated the phenology of 60 tree species in a seasonal semi-deciduous forest located at the southern border of the tropical zone (23°26′35ʺS and 51°15′30ʺW) during 3 years. We aimed to investigate the relationship of leaf fall, leaf flushing, budding, flowering, immature and mature fruit phenophases with precipitation, temperature and photoperiod. We also analyzed whether the phenological patterns of tree community were seasonal and similar between consecutive years. Although the climate of the region is classified as Cfa, there are two distinct season: a hot humid summer and a cold drier winter. Leaf fall occurred predominantly in the dry season, with leaf flushing and flowering at the end of the dry and early wet season. The mature fruits were observed throughout the year. For the six phenophases analyzed, the percentage of species did not differ among the three study years. The tree community presented, in general, weakly seasonal phenological patterns, mainly in response to variations in temperature and photoperiod. The mature fruits showed seasonal patterns when the species were grouped by dispersal syndrome. This predictability suggests that small inter-annual variations in precipitation and temperature are not relevant for the studied tree species’ phenology.

Observed spatial-temporal changes in the autumn navigability of the Arctic Northeast Route from 2010 to 2017

Recently, the Arctic Northeast Route (ANR), an important shipping route connecting Asia and Europe, has become more and more navigable because of the accelerating melt of sea ice in the Arctic. The exploitation of the ANR could shorten the navigational distances from North Asia to Northwestern Europe by 40% (about 2500 nautical miles) and reduce one-third (about 10 days) of the time required for maritime transport by the Royal Road, which can help to save lots of transport costs and bring large environmental benefits. It’s very important and urgent to accurately understand the changes in the navigability of the ANR for the development of the route. However, due to the lack of high-quality observed dataset, there are very few observation-based studies. Some model-based studies cannot effectively reflect the real changes in the navigability of the ANR, due to the varying degrees of the data quality issues. In this study, we applied the daily sea ice concentration product provided by the NSIDC and the reconstructed daily SMOS sea ice thickness product into the Arctic Transportation Accessibility Model (ATAM) from the Arctic Ice Regime Shipping System (AIRSS) to assess and map the daily navigation risks for open water vessels in the ANR from 2010–2017 and further analyze the spatial and temporal changes of the Autumn navigability of the route during the eight years. Assuming the navigability of a specific ice regime is affected by the sea ice conditions and the ice-breaking ability of the vessels, the ATAM model can quantify the navigability of a specific ice regime for seven different vessel types. Since the SMOS ice thickness product is more reliable in thin ice area (lower than 0.5 m), we only focus on the navigability changes of the ANR for open water vessels in this study. We found that, although the end of shipping season for open water vessels across the ANR has extended to the day of 297±4 (October 24th) since 2010 (excluding 2013), there is no significant trend in the navigability of the ANR for open water vessels in the last 8 years. Further analysis of the spatial distribution map of the navigation risk for open water vessels at the end of shipping season in different years shows that the navigability of the ANR mainly affected by the ice regime around the Eastern Siberian Sea, the Novosibirsk Islands and the Severnaya Zemlya Islands. In most years, it’s the earlier frozen ice over the three regions leading to the end of the entire ANR, in the case that most other areas are still safely navigable. We also performed detailed analysis and found that there are significant differences in the navigability changes in the three key straits for open water vessels over the ANR. The Long strait shows great inter-annual variations in the navigability, but has limit impact on the navigability of the entire route because of its late ending of the shipping season. The Sannikov Strait shows the fastest decline, but small inter-annual variations in the navigability. It is also the earliest one that ending the shipping season, and therefore has a great impact on the long-term trend of the navigability of the ANR. The intra- and inter-annual changes in the navigability of the Vlikitsky Strait are very complex. It always fluctuates dramatically, and thus has great impact on the short-term navigability of the entire ANR. In view of the complexity of the change in the ANR navigability, observed high-quality, near real-time sea ice datasets are very important for the quantification of navigation risk in the ASR.

Underlying causes of PM2.5-induced premature mortality and potential health benefits of air pollution control in South and Southeast Asia from 1999 to 2014

Quantification of spatial and temporal variations in premature mortality attributable to PM2.5 has important implications for air quality control in South and Southeast Asia (SSEA). The number of PM2.5-induced premature deaths during 1999–2014 in SSEA was estimated using an integrated exposure-response model based on 0.01° × 0.01° satellite-retrieved PM2.5 data, population density, and spatially and temporally variable baseline mortality data. The results showed extremely high premature death rates in North India and Bangladesh. PM2.5-induced premature deaths in SSEA increased with small interannual variations from 1999 to 2014 owing to the interannual variations in PM2.5 concentrations. Moreover, four scenarios on the effects of premature deaths by PM2.5 mitigation efforts based on World Health Organization (WHO) air quality guidelines (AQG) and interim targets (ITs) were investigated for each disease and each country during 1999–2014. Four scenarios based on WHO AQG (10 μg/m3), IT-3 (15 μg/m3), IT-2 (25 μg/m3), and IT-1 (35 μg/m3) resulted in 69.3%, 49.1%, 25.4%, and 12.8% reductions compared to the total reference premature deaths (1256,300), which was calculated using the original PM2.5 datasets. Overall, stroke was the most serious disease associated with air pollution, causing 40% of total premature deaths. Ischemic heart disease was the largest contributor (58%) to the deaths in relatively cleaner air (Scenario 1). The annual rate of change in premature deaths in South Asian countries (India, Bangladesh, and Pakistan) was higher than that in Southeast Asian countries under all scenarios. The results for different scenarios provide insight into the largest health benefits of PM2.5 reduction efforts.

Multiple timescale variations and controls of soil respiration in a tropical dry dipterocarp forest, western Thailand

This study aims to improve our understanding of temporal variations and controlling factors of soil respiration (Rs) and its components (microbial respiration or Rm and root respiration or Rb) in an Asian tropical seasonal forest at diurnal, seasonal and annual timescales in relation to biotic and abiotic controls. Rs was studied by the trenching method in a seasonal dry diptercarp forest, western Thailand. An automated soil chamber system was used to produce hourly data of Rs during 2008–2011. Analysis of Rs in relation to both biotic and abiotic factors was carried out to understand its temporal variations at different timescales. Rm was the main contributor to overall magnitude and variability of Rs. Soil temperature alone was the main driver of diurnal variation, while the combination of soil moisture and soil temperature determined the seasonal variations. The amount of Rs was also related to the fine root (<2 mm) and microbial biomass at seasonal timescales. Due to the small inter-annual variations in soil temperature and moisture, total soil respiration among the 4 years was not significantly different (p < 0.05). The annual totals for Rs during 2008–2011 were 3.20, 3.89, 3.52, 4.14 kgCO2 m−2 years−1, respectively. The 4-year average ratio of Rm (trenched) to Rs (untrenched) was 66 ± 4 %. Rm plays a crucial role in determining the magnitude (large ratio between Rm and Rs) and temporal variations of Rs. In this forest ecosystem, high seasonal variations in Rs were observed and were mainly attributed to the response of Rm to moisture.

Considerations for Ku-Band Scatterometer Calibration Using the Dry-Snow Zone of the Greenland Ice Sheet

Postlaunch calibration of satellite-borne scatterometers using backscatter data from natural land targets helps to maintain scatterometer accuracy. Due to its temporal stability, the dry-snow zone of the Greenland ice sheet has been proposed in previous studies as a calibration target. Using QuikSCAT data, this letter examines the backscatter properties of the dry-snow zone that are relevant to Ku-band scatterometer calibration including temporal and spatial variabilities, and azimuth-angle and polarization and incidence-angle dependences. The backscatter is found to seasonally vary throughout the dry-snow zone by 0.4 dB on average. Small interannual variations (less than 1.5 dB over a nine year period) in the backscatter are also present in some regions. Azimuth modulation is generally less than 0.4 dB in magnitude and is not significant in some regions of the dry-snow zone. Melting and refreezing appear to cause the quasi-polarization ratio to temporarily decrease. Spatially consistent and relatively temporally stable regions that are well within the interior of the dry-snow zone are best suited as calibration sites.

Climatic, Biological, and Land Cover Controls on the Exchange of Gas-Phase Semivolatile Chemical Pollutants between Forest Canopies and the Atmosphere

An ecophysiological model of a structured broadleaved forest canopy was coupled to a chemical fate model of the air-canopy exchange of gaseous semivolatile chemicals to dynamically assess the short-term (hours) and medium term (days to season) air-canopy exchange and the influence of biological, climatic, and land cover drivers on the dynamics of the air-canopy exchange and on the canopy storage for airborne semivolatile pollutants. The chemical fate model accounts for effects of short-term variations in air temperature, wind speed, stomatal opening, and leaf energy balance, all as a function of layer in the canopy. Simulations showed the potential occurrence of intense short/medium term re-emission of pollutants having log K(OA) up to 10.7 from the canopy as a result of environmental forcing. In addition, relatively small interannual variations in seasonally averaged air temperature, canopy biomass, and precipitation can produce relevant changes in the canopy storage capacity for the chemicals. It was estimated that possible climate change related variability in environmental parameters (e.g., an increase of 2 °C in seasonally averaged air temperature in combination with a 10% reduction in canopy biomass due to, e.g., disturbance or acclimatization) may cause a reduction in canopy storage capacity of up to 15-25%, favoring re-emission and potential for long-range atmospheric transport. On the other hand, an increase of 300% in yearly precipitation can increase canopy sequestration by 2-7% for the less hydrophobic compounds.

Ten-year evapotranspiration estimates in a Bornean tropical rainforest

This study was undertaken to quantify interannual variations of total evaporation ( ET) in a tropical rainforest in Sarawak, Malaysia. To this end, we conducted 10-year meteorological measurements and formulated a simplified big-leaf model that reproduces transpiration ( Et), rainfall interception ( Ei), and ET as the sum of these. The model was validated independently using eddy covariance fluxes, rainfall interception based on throughfall and stemflow measurements, and sap flow measurements conducted for more than 2 years. Using the model, Et, Ei, and ET were estimated for the period 2000–2009. Annual Et, Ei, and ET averaged over 10 years were estimated as 1114, 209, and 1323 mm, respectively, with small seasonal fluctuations. The derived estimates showed conservative year-to-year variations in annual Et, Ei, and ET (CV = 5–7%) in contrast to considerable year-to-year variations in annual rainfall (CV = 11%). Specific rainfall characteristics (e.g. intense short duration storms) at this site can explain the conservative year-to-year Ei variations. Small interannual variations in meteorological conditions and absence of severe drought during the study period can explain the small year-to-year Et variations. To characterize ET at our site, we also compared Ei and ET at our site with those of other tropical forests. Based on the derived ET characteristics, we discuss possible ET changes in response to changes in rainfall regime at this site.

Atmospheric three-dimensional inverse modeling of regional industrial emissions and global oceanic uptake of carbon tetrachloride

Abstract. Carbon tetrachloride (CCl4) has substantial stratospheric ozone depletion potential and its consumption is controlled under the Montreal Protocol and its amendments. We implement a Kalman filter using atmospheric CCl4 measurements and a 3-dimensional chemical transport model to estimate the interannual regional industrial emissions and seasonal global oceanic uptake of CCl4 for the period of 1996–2004. The Model of Atmospheric Transport and Chemistry (MATCH), driven by offline National Center for Environmental Prediction (NCEP) reanalysis meteorological fields, is used to simulate CCl4 mole fractions and calculate their sensitivities to regional sources and sinks using a finite difference approach. High frequency observations from the Advanced Global Atmospheric Gases Experiment (AGAGE) and the Earth System Research Laboratory (ESRL) of the National Oceanic and Atmospheric Administration (NOAA) and low frequency flask observations are together used to constrain the source and sink magnitudes, estimated as factors that multiply the a priori fluxes. Although industry data imply that the global industrial emissions were substantially declining with large interannual variations, the optimized results show only small interannual variations and a small decreasing trend. The global surface CCl4 mole fractions were declining in this period because the CCl4 oceanic and stratospheric sinks exceeded the industrial emissions. Compared to the a priori values, the inversion results indicate substantial increases in industrial emissions originating from the South Asian/Indian and Southeast Asian regions, and significant decreases in emissions from the European and North American regions.

Seasonal and interannual variability of particulate organic carbon within the Southern Ocean from satellite ocean color observations

We use field data of particulate organic carbon (POC) concentration and spectral remote‐sensing reflectance, Rrs(λ), to develop an empirical algorithm for estimating POC from ocean color in the Southern Ocean. The algorithm based on the band ratio Rrs(443)/Rrs(555) is used in conjunction with Sea‐viewing Wide Field‐of‐View Sensor satellite data to demonstrate seasonal and interannual variability in POC from 1997 to 2007. The surface POC concentrations generally range from 30 to 120 mg m−3. On a whole basin scale (south of 35°S), the monthly means are mostly 70–80 mg m−3. The seasonal signal is weakest at lower latitudes within the Sub‐Antarctic Zone and most pronounced at higher latitudes (&gt;55°S). The area‐integrated stock of water column POC in the upper 100 m shows small interannual variations and no clear evidence for long‐term trend during the examined 10 year period. The seasonal maximum of the POC stock occurs in December and reaches a value of about 0.6 Pg of carbon for the entire basin south of 35°S. The seasonal range of area‐normalized POC is between about 5.5 and 6.6 g m−2. The region south of 55°S provides a dominant contribution to the accumulation of POC within the Southern Ocean during the productive period of the season. During the austral spring, the area‐normalized POC accumulates in these high‐latitude waters at rates from about 0.2 to 0.7 g m−2 month−1. The comparison of these rates with large‐scale satellite‐based estimates of net primary production indicates that only a small fraction (&lt;10%) of production accumulates as POC.

A novel approach for estimating the pan coefficient of irrigation water reservoirs: Application to South Eastern Spain

The evaporation rate ( E) and pan coefficient ( K p) of agricultural water reservoirs for irrigation (AWRIs) were determined using a novel approach based on a reservoir energy balance model and measurements of pan evaporation. The model, previously developed and validated for an insulated Class-A pan, was upscaled to the case of AWRIs by introducing a new formulation of the wind function combining the Brutsaert and Harbeck formulae. The model was run for different combinations of area ( S) and depth ( D) at several locations of the Segura River Basin (South Eastern Spain) where routine pan evaporation measurements ( E p) were available. The monthly and annual K p values were derived from the simulation runs as the ratio of the simulated AWRI evaporation to the measured pan evaporation, E/ E p. Results at a monthly scale indicated that D was the main factor affecting the evolution and the value of the surface temperature and evaporation rate, while S, for a given value of D, had only a small influence. Monthly K p varied significantly through the year, the variation range being larger for deep AWRIs (0.5 < K p < 1.5) than for shallow ones (0.8 < K p < 1.2). At a yearly scale, K p was found nearly constant for a given AWRI, with small inter-annual variations. Annual K p varied in the range 0.76 ( S = 50,000 m 2) to 0.86 ( S = 500 m 2), depending primarily on S, and to a lesser extent, on the vapour pressure deficit measured at the location. Empirical formulae allowing to predict annual K p as a function of S and vapour pressure deficit were proposed. It was concluded that the proposed modelling approach can be applied to accurately estimate values of K p in AWRIs at regional scale, taking into account the influence of reservoir dimensions and local climate conditions. Its application under South Eastern Spain conditions supplied the monthly and annual values of K p to be used under similar Mediterranean semi-arid climates.

Simulation of Water Sources and Precipitation Recycling for the MacKenzie, Mississippi, and Amazon River Basins

Abstract An atmospheric general circulation model simulation for 1948–97 of the water budgets for the MacKenzie, Mississippi, and Amazon River basins is presented. In addition to the water budget, passive tracers are included to identify the geographic sources of water for the basins, and the analysis focuses on the mechanisms contributing to precipitation recycling in each basin. While each basin’s precipitation recycling has a strong dependency on evaporation during the mean annual cycle, the interannual variability of the recycling shows important relationships with the atmospheric circulation. The MacKenzie River basin recycling has only a weak interannual correspondence with evaporation, where the variations in zonal moisture transport from the Pacific Ocean can affect the basin water cycle. On the other hand, the Mississippi River basin precipitation and recycling have strong interannual correlation on evaporation. The evaporation is related to the moist and shallow planetary boundary layer that provides moisture for convection at the cloud base. At global scales, high precipitation recycling is also found to be partly correlated to warm SSTs in the tropical Pacific Ocean. The Amazon River basin evaporation exhibits small interannual variations, so the interannual variations of precipitation recycling are related to atmospheric moisture transport from the tropical South Atlantic Ocean. Increasing SSTs over the 50-yr period are causing increased easterly transport across the basin. As moisture transport increases, the Amazon precipitation recycling decreases (without real-time varying vegetation changes). In addition, precipitation recycling from a bulk diagnostic method is compared to the passive tracer method used in the analysis. While the mean values of the different recycling methods are different, the interannual variations are comparable between each method. The methods also exhibit similar relationships to the terms of the basin-scale water budgets.

Estimating annual N2O emissions from agricultural soils in temperate climates

AbstractThe Kyoto protocol requires countries to provide national inventories for a list of greenhouse gases including N2O. A standard methodology proposed by the Intergovernmental Panel on Climate Change (IPCC) estimates direct N2O emissions from soils as a constant fraction (1.25%) of the nitrogen input. This approach is insensitive to environmental variability. A more dynamic approach is needed to establish reliable N2O emission inventories and to propose efficient mitigation strategies. The objective of this paper is to develop a model that allows the spatial and temporal variation in environmental conditions to be taken into account in national inventories of direct N2O emissions. Observed annual N2O emission rates are used to establish statistical relationships between N2O emissions, seasonal climate and nitrogen‐fertilization rate. Two empirical models, MCROPS and MGRASS, were developed for croplands and grasslands. Validated with an independent data set, MCROPS shows that spring temperature and summer precipitation explain 35% of the variance in annual N2O emissions from croplands. In MGRASS, nitrogen‐fertilization rate and winter temperature explain 48% of the variance in annual N2O emissions from grasslands. Using long‐term climate observations (1900–2000), the sensitivity of the models with climate variability is estimated by comparing the year‐to‐year prediction of the model to the precision obtained during the validation process. MCROPS is able to capture interannual variability of N2O emissions from croplands. However, grassland emissions show very small interannual variations, which are too small to be detectable by MGRASS. MCROPS and MGRASS improve the statistical reliability of direct N2O emissions compared with the IPCC default methodology. Furthermore, the models can be used to estimate the effects of interannual variation in climate, climate change on direct N2O emissions from soils at the regional scale.

Effect on nitrate concentration in stream water of agricultural practices in small catchments in Brittany: II. Temporal variations and mixing processes

Abstract. In catchments with impervious bedrock, the nitrate concentrations in streamwater often show marked seasonal and small inter-annual variations. The inter-annual trends are usually attributed to changes in nitrogen inputs, due to changes in land use or in nitrogen deposition whereas seasonal patterns are explained in terms of availability of soil nitrate for leaching and of seasonality of nitrogen biotransformations. The companion paper showed that inter-annual variations of nitrogen in streamwater are not directly related to the variations of land use. The aim of this study is to describe nitrate concentration variations in a set of very small adjacent catchments, and to discuss the origin of the inter-annual and seasonal trends. Data from four catchments at the Kerbernez site (South Western Brittany, France) were used in this study. Nitrate concentrations in streamwater were monitored for eight years (1992 to 1999) at the outlet of the catchments. They exhibit contrasting inter-annual and seasonal patterns. An extensive survey of agricultural practices during this period allowed assessment of the amount of nitrogen available for leaching. The discharges measured since 1997 show similar specific fluxes but very different seasonal dynamics between the catchments. A simple, lumped linear store model is proposed as an initial explanation of the differences in discharge and nitrate concentration patterns between the catchments. The base flow at the outlet of each catchment is considered as a mixture of water from two linear reservoirs with different time constants. Each reservoir comprises two water stores, one mobile contributing to discharge, the other, immobile, where nitrate moves only by diffusion. The storm flow, which accounts for less than 10% of the annual flux, is not considered here. Six parameters were adjusted for each catchment to fit the observed data: the proportion of deep losses of water, the proportion of the two reservoirs and the size and initial concentration of the two immobile stores. The model simulates the discharge and nitrate concentration dynamics well. It suggests that the groundwater store plays a very important role in the control of nitrate concentration in streamwater, and that the pattern of the seasonal variation of nitrate concentration may result from the long term evolution of nitrogen losses by leaching. Keywords: nitrate, diffuse pollution, groundwater, seasonal variations, agricultural catchment, simulation model

Implications of interannual variability in atmospheric circulation on modeled CO2 concentrations and source estimates

The impact of the interannual variability (IAV) of atmospheric transport on atmospheric CO2 observations is often ignored in carbon cycle studies. We use 8 years of analyzed European Centre for Medium‐Range Weather Forecasts (ECMWF) wind fields from 1985–1992 to demonstrate the effect of IAV of the circulation on modeled CO2 concentrations for fossil and biosphere CO2 sources. The wind fields are used to drive the Melbourne University Tracer Model. The modeled annual mean CO2 values at observing locations show little IAV in the fossil case. In the biosphere case the IAV of the annual mean is considerably larger, especially in the high northern latitudes. Simulated baseline selection using modeled radon concentrations does not reduce the IAV. In both cases, surface layer interhemispheric differences show small interannual variations indicating small changes in interhemispheric transport. Source fields from a mass balance inversion using 1985–1992 ECMWF winds are compared with those from inversions using a single year of winds repeated for each year of observations. We find differences in semi‐hemispheric sources of up to 0.6 Gt C yr−1 at some times. However, 8 year mean sources show smaller differences, mostly less than 0.2 Gt C yr−1 at regional scales. This indicates that the variability in the circulation is a second order factor in determining the sources from inversion calculations.

The use of eddy covariance to infer the net carbon dioxide uptake of Brazilian rain forest

Abstract Eddy covariance measurements of CO2 flux, based on four and six week campaigns in Rondôdnia, Brazil, have been used in conjunction with a model to scale up data to a whole year, and thus estimate the carbon balance of the tropical forest ecosystem, and the changes in carbon balance expected from small interannual variations in climatological conditions. One possible source of error in this estimation arises from the difficulty in measuring fluxes under stably stratified meteorological conditions, such as occur frequently at night. Flux may be ‘lost’ because of low velocity advection, caused by nocturnal radiative cooling at sites on raised ground. Such effects may be detected by plotting the net ecosystem flux of CO2, Feco is a function of wind speed. If flux is ‘lost’ then Feco is expected to decline with wind speed. In the present data set, this did not occur, and Feco was similar to the nocturnal flux estimated independently from chamber measurements. The model suggests that in 1992/3, the Gross Primary Productivity (GPP) was 203.3 mol C m−2 y−1 and ecosystem respiration was 194.8 mol C m−2 y−1, giving an ecosystem carbon balance of 8.5 mol C m−2 y−1, equivalent to a sink of 1.0 ton C ha−1 y−1. However, the sign and magnitude of this figure is very sensitive to temperature, because of the strong influence of temperature on respiration. The model also suggests that the effect of temperature on the net carbon balance is strongly dependent on the partial pressure of CO2.