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Here, we provided a comprehensive analysis of long-term drought and climate extreme patterns in the agro ecological zones (AEZs) of Pakistan during 1980–2019. Drought trends were investigated using the standardized precipitation evapotranspiration index (SPEI) at various timescales (SPEI-1, SPEI-3, SPEI-6, and SPEI-12). The results showed that droughts (seasonal and annual) were more persistent and severe in the southern, southwestern, southeastern, and central parts of the region. Drought exacerbated with slopes of −0.02, −0.07, −0.08, −0.01, and −0.02 per year. Drought prevailed in all AEZs in the spring season. The majority of AEZs in Pakistan’s southern, middle, and southwestern regions had experienced substantial warming. The mean annual temperature minimum (Tmin) increased faster than the mean annual temperature maximum (Tmax) in all zones. Precipitation decreased in the southern, northern, central, and southwestern parts of the region. Principal component analysis (PCA) revealed a robust increase in temperature extremes with a variance of 76% and a decrease in precipitation extremes with a variance of 91% in the region. Temperature and precipitation extremes indices had a strong Pearson correlation with drought events. Higher temperatures resulted in extreme drought (dry conditions), while higher precipitation levels resulted in wetting conditions (no drought) in different AEZs. In most AEZs, drought occurrences were more responsive to precipitation. The current findings are helpful for climate mitigation strategies and specific zonal efforts are needed to alleviate the environmental and societal impacts of drought.

Climate variability and drought are increasing in the Horn of Africa. Evaluating land use/land cover (LULC) changes and their impacts on water availability and variation are vital for regional land use planning and water resources management. LULC changes during 2000-2015 were estimated using high-resolution Landsat images and the Google Earth Engine cloud platform, and land use dynamic index (K). The impact of LULC change on water yield was evaluated using the Integrated Valuation of Ecosystem Services and Tradeoff (InVEST) model. The results at a regional scale show that there were rapid decreases in the area of forests and barren lands (-K) while there was a drastic increase in the built-up area (+Kvalues). The transition was found to occur from forested land to low and very low biomass areas with 51.13% and 16.7%, respectively. There were similar LULC changes in the Mereb-Gash River Basin. The mean annual water yield increased for all the catchments during 2000-2015 and with the peak in 2005. The highest annual sum water yield decreased in the forested lands from 43.18 million m(3)in 2000 to 4.1 million m(3)in 2015. There was a strong positive correlation between areal changes (%) and the annual water yield variations (%) for all the LULC types except for water body, and the correlation was significantly positive for forest (p

Ecosystem water use efficiency (WUE) reflects the intimately coupled relationship between the carbon and water cycles in terrestrial ecosystems. However, the inter-annual variation and its drivers of WUE are poorly understood at regional/global scale, due to either limited data availability or uncertainties in current data streams. In this study, we used process-based models simulated gross primary productivity (GPP) and evapotranspiration (ET) data to estimate the ecosystem WUE (eWUE, GPP/ET) in China for 1979–2012. The eWUE estimates were validated against eddy covariance-based values from 35 flux towers. The inter-annual variation of the eWUE was quantified and its responses to annual precipitation (AP), annual mean temperature (AMT), and annual mean leaf area index (AMLAI) were analyzed. The key findings were as follows. (i) The mean annual eWUE over China was 1.48 ± 1.04 g C kg−1 H2O and had a slightly increasing but not significant trend (7.32 × 10−4 g C kg−1 H2O yr−1, p

In this study, the performance of solar-induced chlorophyll fluorescence (SIF) in detecting the end date of the vegetation growing season (EGS) is evaluated at the canopy level. The experiment was conducted at two ecological stations in the Olympic Park mixed forest and Yucheng cropland in China. Validated against the gross primary productivity (GPP) measured by the eddy covariance technique (GPPEC), the SIF was first compared with the normalized difference vegetation index (NDVI). The results showed that at the Olympic Park station (mixed forest), the EGS of SIF was 4 days earlier than that of the GPPEC, and the EGS of the NDVI showed 2 days of hysteresis. However, in the Yucheng cropland, the EGS of the NDVI was 26 days later than that of the GPPEC, while SIF lagged by 18 days. Considering the total biases against the EGS of GPPEC, the SIF was comprehensively superior to the NDVI for determining the end date of the vegetation growing season in these two ecosystems. SIF was further incorporated into a light use efficiency model to estimate the GPP, which was also used to extract the EGS. Two sets of inputs were employed, including the photochemical reflectance index and SIF, apparent fluorescence yield and SIF. The results showed that this SIF-based light use efficiency model can yield good estimations of GPPs, with correlation coefficients of all GPP values being above 0.8 for both ecosystems. Additionally, the estimated end dates of the vegetation growing season were better than those from the single SIF proxy. In particular, the combination of the two fluorescence variables used in the light use efficiency model contributed the best performance in that the EGS was 2 days earlier than that of the GPPEC at Olympic Park station and 13 days later than that of the GPPEC at Yucheng station. The EGS was improved by 2 days and 5 days for the mixed forest site and cropland site, respectively, compared to the EGSs determined by SIF. The influences of air temperature and sunlight availability on the temporal patterns of the GPP, SIF and NDVI was investigated. Light was the main factor controlling the GPP and SIF, while the NDVI was primarily controlled by the air temperature in both ecosystems. These results explained the different mechanisms of the three surrogates, and therefore, the distinct performances in detecting the EGSs of plants was explained. Our findings suggest that SIF is suitable for determining the end date of the vegetation growing season, regardless of whether it is used alone or in combination with other photosynthetic indices in mixed forest and cropland ecosystems. The errors in the estimated EGS can be limited to twenty days. Based on the results of this study, SIF can be more widely employed either in the ecological field to investigate vegetation dynamics and carbon cycling or in the agronomic field to predict the harvest period and adjust agricultural management strategies.

Forested ecosystems represent an important part of the global carbon cycle, with accurate estimates of gross primary productivity (GPP) crucial for understanding ecosystem response to environmental controls and improving global carbon models. This research investigated the relationships between leaf area index (LAI) and leaf chlorophyll content (ChlLeaf) with forest carbon uptake. Ground measurements of LAI and ChlLeaf were taken approximately every 9 days across the 2013 growing season from day of year (DOY) 130 to 290 at Borden Forest, Ontario. These biophysical measurements were supported by on-site eddy covariance flux measurements. Differences in the temporal development of LAI and ChlLeaf were considerable, with LAI reaching maximum values within approximately 10 days of bud burst at DOY 141. In contrast, ChlLeaf accumulation only reached maximum values at DOY 182. This divergence has important implications for GPP models which use LAI to represent the fraction of light absorbed by a canopy (fraction of absorbed photosynthetic active radiation (fAPAR)). Daily GPP values showed the strongest relationship with canopy chlorophyll content (ChlCanopy; R2 = 0.69, p

In this study, the net primary productivity (NPP) in China from 2001 to 2012 was estimated based on the Carnegie-Ames-Stanford Approach (CASA) model using Moderate Resolution Imaging Spectroradiometer (MODIS) and meteorological datasets, and the accuracy was verified by a ChinaFLUX dataset. It was found that the spatiotemporal variations in NPP present a downward trend with the increase of latitude and longitude. Moreover, the influence of climate change on the evolution of NPP shows that NPP has had different impact factors in different regions and periods over the 12 years. The eastern region has shown the largest increase in gross regional product (GRP) and a significant fluctuation in NPP over the 12 years. Meanwhile, NPP in the eastern and central regions is significantly positively correlated with annual solar radiation, while NPP in these two regions is significantly negatively correlated with the growth rate of GRP. It is concluded that both the development of the economy and climate change have influenced NPP evolution in China. In addition, NPP has shown a steadily rising trend over the 12 years as a result of the great importance attributed to ecological issues when developing the economy.

The mass transfer (MT) equation and the Penman-Monteith (PM) equation are two common approaches used in various land surface models for simulating evapotranspiration (ET). Yet assessments are rarely conducted to determine how well these structurally differing equations simulate ET across various biomes and climatic environments with different canopy upscaling strategies. We evaluated the capacity of models to estimate ET using the MT equation with the one-leaf strategy in the Community Land Model version 4 and the PM equation in the Dynamic Land Model using the one-leaf and two-leaf upscaling approaches for 22 selected eddy covariance flux towers representing 10 typical plant functional types. Overall, across half-hourly, daily, monthly, and seasonal scales, the MT equation performed less robust than the PM equation in forests. The former had 8-15% higher root-mean-square error and 1-4% lower index of agreement and a large uncertainty in warm and wet seasons for several sites. It leaves a doubt about its application of estimating ET across regional to global scales. Considering the net radiation available on the surface of leaf/soil and adopting the two-leaf approach made the PM equation closer to the EC measurements on average but still could not capture the variation during the cold season. We suggest that further improvements in simulation of ET require seasonal variation of some key parameters and quantification of spatial heterogeneity.

Atmospheric inversions use measurements of atmospheric CO2 gradients to constrain regional surface fluxes. Current inversions indicate a net terrestrial CO2 sink in China between 0.16 and 0.35 PgC/yr. The uncertainty of these estimates is as large as the mean because the atmospheric network historically contained only one high altitude station in China. Here, we revisit the calculation of the terrestrial CO2 flux in China, excluding emissions from fossil fuel burning and cement production, by using two inversions with three new CO2 monitoring stations in China as well as aircraft observations over Asia. We estimate a net terrestrial CO2 uptake of 0.39–0.51 PgC/yr with a mean of 0.45 PgC/yr in 2006–2009. After considering the lateral transport of carbon in air and water and international trade, the annual mean carbon sink is adjusted to 0.35 PgC/yr. To evaluate this top-down estimate, we constructed an independent bottom-up estimate based on ecosystem data, and giving a net land sink of 0.33 PgC/yr. This demonstrates closure between the top-down and bottom-up estimates. Both top-down and bottom-up estimates give a higher carbon sink than previous estimates made for the 1980s and 1990s, suggesting a trend towards increased uptake by land ecosystems in China.

This study investigated how nitrogen (N) fertilization with 200 kg N ha � 1 of urea affected ecosystem carbon (C) sequestration in the first-postfertilization year in a Pacific Northwest Douglas-fir (Pseudotsuga menziesii) stand on the basis of multiyear eddy-covariance (EC) and soil-chamber measurements before and after fertilization in combination with ecosystem modeling. The approach uses a data-model fusion technique which encompasses both model parameter optimization and data assimilation and minimizes the effects of interannual climatic perturbations and focuses on the biotic and abiotic factors controlling seasonal C fluxes using a prefertilization 9-year-long time series of EC data (1998–2006). A process-based ecosystem model was optimized using the half-hourly data measured during 1998–2005, and the optimized model was validated using measurements made in 2006 and further applied to predict C fluxes for 2007 assuming the stand was not fertilized. The N fertilization effects on C sequestration were then obtained as differences between modeled (unfertilized stand) and EC or soil-chamber measured (fertilized stand) C component fluxes. Results indicate that annual net ecosystem productivity in the first-post-N fertilization year increased by � 83%, from 302 � 19 to 552 � 36 g m � 2 yr � 1 , which resulted primarily from an increase in annual gross primary productivity of � 8%, from 1938 � 22 to 2095 � 29 g m � 2 yr � 1 concurrent with a decrease in annual ecosystem respiration (Re )o f� 5.7%, from 1636 � 17 to 1543 � 31 g m � 2 yr � 1 . Moreover, with respect to respiration, model results showed that the fertilizer-induced reduction in Re (� 93 g m � 2 yr � 1 ) principally resulted from the decrease in soil respiration Rs (� 62 g m � 2 yr � 1 ).

Coupled terrestrial carbon (C), nitrogen (N) and hydrological processes play a crucial role in the climate system, providing both positive and negative feedbacks to climate change. In this review we summarize published research results to gain an increased understanding of the dynamics between vegetation and atmosphere processes. A variety of methods, including monitoring (e.g., eddy covariance flux tower, remote sensing, etc.) and modeling (i.e., ecosystem, hydrology and atmospheric inversion modeling) the terrestrial carbon and water budgeting, are evaluated and compared. We highlight two major research areas where additional research could be focused: (i) Conceptually, the hydrological and biogeochemical processes are closely linked, however, the coupling processes between terrestrial C, N and hydrological processes are far from well understood; and (ii) there are significant uncertainties in estimates of the components of the C balance, especially at landscape and regional scales. To address these two questions, a synthetic research framework is needed which includes both bottom-up and top-down approaches integrating scalable (footprint and ecosystem) models and a spatially nested hierarchy of observations which include multispectral remote sensing, inventories, existing regional clusters of eddy-covariance flux towers and CO(2) mixing ratio towers and chambers.

This study analyzes 9 years of eddy-covariance (EC) data carried out in a Pacific Northwest Douglas-fir (Pseudotsuga menzesii) forest (58-year old in 2007) on the east coast of Vancouver Island, Canada, and characterizes the seasonal and interannual variability in net ecosystem productivity (NEP), gross primary productivity (GPP), and ecosystem respiration (Re) and primary climatic controls on these fluxes. The annual values (± SD) of NEP, GPP and Re were 357 ± 51, 2124 ± 125, and 1767 ± 146 g C m−2 yr−1, respectively, with ranges of 267–410, 1592–2338, and 1642–2071 g C m−2 yr−1, respectively. Spring to early summer (March–June) accounted for more than 80% of annual NEP while late spring to early autumn (May–August) was mainly responsible for its interannual variability (∼80%). The major drivers of interannual variability in annual carbon (C) fluxes were annual and spring mean air temperatures (Ta) and water deficiency during late summer and autumn (July–October) when this Douglas-fir forest growth was often water-limited. Photosynthetically active radiation (Q), and the combination of Q and soil water content (θ) explained 85% and 91% of the variance of monthly GPP, respectively; and 91% and 96% of the variance of monthly Re was explained by Ta and the combination of Ta and θ, respectively. Annual net C sequestration was high during optimally warm and normal precipitation years, but low in unusually warm or severely dry years. Excluding 1998 and 1999, the 2 years strongly affected by an El Nino/La Nina cycle, annual NEP significantly decreased with increasing annual mean Ta. Annual NEP will likely decrease whereas both annual GPP and Re will likely increase if the future climate at the site follows a trend similar to that of the past 40 years.

A new remote-sensing-based land surface model, named ecosystem–atmosphere simulation scheme (EASS), is introduced in this paper. The principle motivation for formulating EASS is to provide realistic partition of energy fluxes at regional scales as well as consistent estimates of carbon assimilation rates. EASS has the following characteristics: (i) satellite data are used to describe the spatial and temporal information on vegetation, and in particular, we use a foliage clumping index (˝) in addition to leaf area index to characterize the effects of three-dimensional canopy structure on radiation, energy and carbon fluxes; (ii) energy and water exchanges and carbon assimilation in the soil–vegetation–atmosphere system are fully coupled and are simulated simultaneously; (iii) the energy and carbon assimilation fluxes are calculated with stratification of sunlit and shaded leaves to avoid shortcomings of the “big-leaf” assumption. Model experiments shows that the simulation realism and accuracy by the new strategy are enhanced about 9–14% compared with the “big-leaf model”. Moreover, ˝ is useful for accurate separation of sunlit and shaded leaves in the canopy. The accuracy in simulation of energy and carbon fluxes increase about 5–8% by considering the effects of ˝ on the radiation interception and the separation of sunlit and shaded leaves; (iv) snow and soil simulations are emphasized by including a flexible and multiple layer scheme. EASS has been tested and validated against multiple-year observed data at several sites. EASS is proved to be overall successful in capturing variations in energy fluxes, canopy and soil temperatures, and soil moisture over diurnal, synoptic, seasonal and inter-annual temporal scales.

Accurate estimation of temporal and spatial variations in photosynthetic discrimination of 13C is critical to carbon cycle research. In this study, a combined ecosystem-boundary layer isotope model, which was satisfactorily validated against intensive campaign data, was used to explore the temporal variability of carbon discrimination in response to environmental driving factors in a boreal ecosystem in the vicinity of Fraserdale Tower, Ontario, Canada (49 degrees 52'30''N, 81 degrees 34'12''W). A 14 year (1990-1996 and 1998-2004) hourly CO2 concentration and meteorological record measured on this tower was used for this purpose. The 14 year mean yearly diurnal amplitude of canopy-level discrimination Delta(canopy) was computed to be 2.8 +/- 0.5 per thousand, and the overall diurnal cycle showed that the greatest Delta(canopy) values occurred at dawn and dusk, while the minima generally appeared in mid-afternoon. The average annual Delta(canopy) varied from 18.3 to 19.7 per thousand with the 14 year average of 19 +/- 0.4 per thousand. The overall seasonality of Delta(canopy) showed a gradually increasing trend from leaf emergence in May-September and with a slight decrease at the end of the growing season in October. Delta(canopy) was negatively correlated to vapour pressure deficit and air temperature across hourly to decadal timescales. A strong climatic control on stomatal regulation of ecosystem isotope discrimination was found in this study.

Stable isotopes of CO2 contain unique information on the biological and physical processes that exchange CO2 between terrestrial ecosystems and the atmosphere. In this study, we developed an integrated modeling system to simulate dynamics of stable carbon isotope of CO2, as well as moisture, energy, and momentum, between a boreal forest ecosystem and the atmosphere, as well as their transport/mixing processes through the convective boundary layer (CBL), using remotely sensed surface parameters to characterize the surface heterogeneity. It has the following characteristics: (i) it accounts for the influences of the CBL turbulent mixing and entrainment of the air aloft; (ii) it scales individual leaf-level photosynthetic discrimination up to the whole canopy (Δcanopy) through the separation of sunlit and shaded leaf groups; (iii) it has the capacity to examine the detailed interrelationships among plant water-use efficiency, isotope discrimination, and vapor pressure deficit; and (iv) it has the potential to investigate how an ecosystem discriminates against 13C at various time and spatial scales. The monthly mean isotopic signatures of ecosystem respiration (i.e. δ13CR) used for isotope flux calculation are retrieved from the nighttime flask data from the intensive campaigns (1998–2000) at 20 m level on Fraserdale tower, and the data from the growing season in 1999 are used for model validation. Both the simulated CO2 mixing ratio and δ13C of CO2 at the 20 m level agreed with the measurements well in different phases of the growing season. On a diurnal basis, the greatest photosynthetic discrimination at canopy level (i.e. Δcanopy) occurred early morning and late afternoon with a varying range of 10–26‰. The diurnal variability of Δcanopy was also associated with the phases of growing season and meteorological variables. The annual mean Δcanopy in 1999 was computed to be 19.58‰. The monthly averages of Δcanopy varied between 18.55‰ and 20.84‰ with a seasonal peak during the middle growing season. Because of the strong opposing influences of respired and photosynthetic fluxes on forest air (both CO2 and 13CO2) on both the diurnal and seasonal time scales, CO2 was consistently enriched with the heavier 13C isotope (less negative δ13C) from July to October and depleted during the remaining months, whereas on a diurnal basis, CO2 was enriched with the heavier 13C in the late afternoon and depleted in early morning. For the year 1999, the model results reveal that the boreal ecosystem in the vicinity of Fraserdale tower was a small sink with net uptake of 29.07 g 12C m−2 yr−1 and 0.34 g 13C m−2 yr−1.

Until now, most of the early rice remains in China were found in the middle to lower reaches of the Yangtze River drainage. Recently, rice remains earlier than 8000 B.P. were found from Jiahu site (8942-7801 B.P.) in Wuyang County of Henan Province, central China. This is the earliest cultivated rice found at this latitude (33°37’N), which is far outside the current distribution of wild rice species. The discovery is of great implications. It suggests that central China may be one of the centers of early rice domestication.

[1] The seasonal and interannual variability of gross ecosystem photosynthesis (Pg) and ecosystem respiration (Re), and their relationships to environmental variables and stand characteristics were used to explain the variation of eddy-covariance-measured net ecosystem productivity (FNEP) of three different-aged Douglas-fir stands located on the east coast of Vancouver Island in British Columbia, Canada. During the 9-year period, 1998–2006, which included a strong El Nino/La Nina event, the near-end-of-rotation stand (DF49, 57 years old in 2006) was a moderate carbon (C) sink for CO2 with annual FNEP ranging from 267 to 410 g C m−2 yr−1 (mean ± SD, 357 ± 51 g C m−2 yr−1). The pole/sapling stand (HDF88, 18 years old in 2006) was a weak C source (FNEP = −64 ± 75 g C m−2 yr−1), and the recently harvested stand (HDF00, 6 years old in 2006) was a large C source (FNEP = −515 ± 88 g C m−2 yr−1) during 2002–2006. Irrespective of stand age, all sites responded quite similarly to changes in environmental variables during each year. Daily total values of Pg and Re were highest in July–August in all three stands, while daily FNEP peaked during April–June at DF49, May–June at HDF88, and June–July at HDF00. Reductions in root-zone soil water content decreased both Pg and Re especially during the dry period from May to September, and this effect was more pronounced in the younger stands. Evapotranspiration and dry-foliage surface conductance also decreased with decreasing root-zone soil water content whereas water use efficiency appeared to be conservative, especially at DF49. Increasing spring temperature had a positive effect on annual Pg and Re but caused a slight decrease in annual FNEP. During the summer to autumn transition period, increases in soil water content resulted in a greater increase in Re than Pg causing a reduction in FNEP. The interannual variation in the C balance was determined mainly by the interannual variation in Re for the near-end-of-rotation stand and Pg for the two younger stands. The results indicate that regardless of the stand age, interannual variability in the C balance was mainly determined by year-to-year variability in spring temperature and water availability in late summer.

[1] This study investigated how nitrogen (N) fertilization with 200 kg N ha−1 of a 58-year-old West Coast Douglas fir stand influenced its net greenhouse gas (GHG) global warming potential (GWP) in the first year after fertilization. Effects of fertilization on GHG GWP were calculated considering changes in soil N2O emissions, measured using the static chamber technique and the soil N2O gradient technique; eddy covariance (EC) measured net ecosystem productivity (NEP); and energy requirements of fertilizer production, transport, and its aerial spreading. We found significant N2O losses in fertilized plots compared to a small uptake in nonfertilized plots. Chamber-measured N loss in the fertilized plots was about 16 kg N2O ha−1 in the first year, which is equivalent to 10 kg N ha−1 or 5% of the applied fertilizer N. Soil N2O emissions measured using the gradient technique, however, exceeded the chamber measurements by about 50%. We also compared a polymer-coated slow-release urea with regular urea and found that the former delayed N2O emissions but the year-end total loss was about the same as that from regular urea. Change in NEP due to fertilization was determined by relating annual NEP for the nonfertilized stand to environmental controls using an empirical and a process-based model. Annual NEP increased by 64%, from 326 g C m−2, calculated assuming that the stand was not fertilized, to the measured value of 535 g C m−2 with fertilization. At the end of the year, net change in GHG GWP was −2.28 t CO2 ha−1 compared to what it would have been without fertilization, thereby indicating favorable effect of fertilization even in the first year after fertilization with significant emissions of N2O.

[1] Gross ecosystem production (GEP) can be estimated at the global scale and in a spatially continuous mode using models driven by remote sensing. Multiple studies have demonstrated the capability of high resolution optical remote sensing to accurately measure GEP at the leaf and stand level, but upscaling this relationship using satellite data remains challenging. Canopy structure is one of the complicating factors as it not only alters the strength of a measured signal depending on integrated leaf-angle-distribution and sun-observer geometry, but also drives the photosynthetic output and light-use-efficiency (ɛ) of individual leaves. This study introduces a new approach for upscaling multiangular canopy level reflectance measurements to satellite scales which takes account of canopy structure effects by using Light Detection and Ranging (LiDAR). A tower-based spectro-radiometer was used to observe canopy reflectances over an annual period under different look and solar angles. This information was then used to extract sunlit and shaded spectral end-members corresponding to minimum and maximum values of canopy-ɛ over 8-d intervals using a bidirectional reflectance distribution model. Using three-dimensional information of the canopy structure obtained from LiDAR, the canopy light regime and leaf area was modeled over a 12 km2 area and was combined with spectral end-members to derive high resolution maps of GEP. Comparison with eddy covariance data collected at the site shows that the spectrally driven model is able to accurately predict GEP (r2 between 0.75 and 0.91, p < 0.05).

[1] The temporal variation of the CO 2 mixing ratio in the atmosphere at a given height results from several processes, including photosynthesis and respiration of the underlying ecosystems, the vertical mixing of the atmosphere near the surface and in the planetary boundary layer (PBL), and entrainment of the air above the PBL. Theoretically, if all atmospheric processes are modeled accurately, we can estimate the magnitude of ecosystem photosynthesis and respiration from the variations in the measured CO 2 mixing ratio. Through analyzing the CO 2 concentration measured at several heights (30 m, 122 m, and 396 m) on the Wisconsin tall tower, we demonstrate that it is possible to derive the daily carbon flux resulting from CO 2 uptake from hourly CO 2 mixing ratio data. At 30 m, the concentration-derived daily gross primary productivity (GPP) is well correlated with measured daily GPP derived from flux measurements (r 2 = 0.70), but the former was 20% larger than the latter. The correlation increased considerably for 10-day averages (r2 = 0.87). As the variations at lower heights have larger diurnal CO 2 amplitudes, the concentration-derived GPP is more accurate at lower heights. The footprint distance of CO 2 concentration during the daytime under the influence of the mixed layer is estimated to be of the order of 10 km, or a footprint area of 10 3 -10 4 km 2 , which is much larger than that of CO 2 fluxes measured using eddy covariance methods (typically 1 km 2 ). The difference in these footprint areas may partly explain the differences between these two flux estimates at the Wisconsin tower. These differences also signify the importance of retrieving flux information from the mixing ratio as it provides a means to upscale from local sites to a region.

[1] Ecosystem CO2 exchange with the atmosphere and the planetary boundary layer (PBL) dynamics are correlated diurnally and seasonally. The strength of this kind of covariation is quantified as the rectifier effect, and it affects the vertical gradient of CO2 and thus the global CO2 distribution pattern. An 11-year (1990–1996, 1999–2002), continuous CO2 record from Fraserdale, Ontario (49°52′29.9″N, 81°34′12.3″W), along with a coupled vertical diffusion scheme (VDS) and ecosystem model named Boreal Ecosystem Productivity Simulator (BEPS), are used to investigate the interannual variability of the rectifier effect over a boreal forest region. The coupled model performed well (r2 = 0.70 and 0.87, at 40 m at hourly and daily time steps, respectively) in simulating CO2 vertical diffusion processes. The simulated annual atmospheric rectifier effect varies from 3.99 to 5.52 ppm, while the diurnal rectifying effect accounted for about a quarter of the annual total (22.8∼28.9%).The atmospheric rectification of CO2 is not simply influenced by terrestrial source and sink strengths, but by seasonal and diurnal variations in the land CO2 flux and their interaction with PBL dynamics. Air temperature and moisture are found to be the dominant climatic factors controlling the rectifier effect. The annual rectifier effect is highly correlated with annual mean temperature (r2 = 0.84), while annual mean air relative humidity can explain 51% of the interannual variation in rectification. Seasonal rectifier effect is also found to be more sensitive to climate variability than diurnal rectifier effect.

[1] The magnitude and spatial distribution of the carbon sink in the extratropical Northern Hemisphere remain uncertain in spite of much progress made in recent decades. Vertical CO2 diffusion in the planetary boundary layer (PBL) is an integral part of atmospheric CO2 transport and is important in understanding the global CO2 distribution pattern, in particular, the rectifier effect on the distribution [Keeling et al., 1989; Denning et al., 1995]. Attempts to constrain carbon fluxes using surface measurements and inversion models are limited by large uncertainties in this effect governed by different processes. In this study, we developed a Vertical Diffusion Scheme (VDS) to investigate the vertical CO2 transport in the PBL and to evaluate CO2 vertical rectification. The VDS was driven by the net ecosystem carbon flux and the surface sensible heat flux, simulated using the Boreal Ecosystem Productivity Simulator (BEPS) and a land surface scheme. The VDS model was validated against half-hourly CO2 concentration measurements at 20 m and 40 m heights above a boreal forest, at Fraserdale (49°52′29.9″N, 81°34′12.3″W), Ontario, Canada. The amplitude and phase of the diurnal/seasonal cycles of simulated CO2 concentration during the growing season agreed closely with the measurements (linear correlation coefficient (R) equals 0.81). Simulated vertical and temporal distribution patterns of CO2 concentration were comparable to those measured at the North Carolina tower. The rectifier effect, in terms of an annual-mean vertical gradient of CO2 concentration in the atmosphere that decreases from the surface to the top of PBL, was found at Fraserdale to be about 3.56 ppmv. Positive covariance between the seasonal cycles of plant growth and PBL vertical diffusion was responsible for about 75% of the effect, and the rest was caused by covariance between their diurnal cycles. The rectifier effect exhibited strong seasonal variations, and the contribution from the diurnal cycle was mostly confined to the surface layer (less than 300 m).