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Satellite-derived observations of land surface temperature (LST) are being utilized in a growing number of land surface studies; however, these observations are generally obtained from optical sensors that exclude cloudy observations of the land surface. The impact of using only clear-sky observations of land surfaces on monthly and annual estimates of daytime LST over two U.S. Climate Reference Network (USCRN) sites was evaluated over five years with daily in situ LST observations available for all-sky (clear and cloudy) conditions. The in situ LST observations were obtained for the nominal daytime observations associated with the MODIS sensors on board the Terra and Aqua satellites and were identified as all-sky or clear-sky conditions by utilizing cloud information provided with the MODIS LST product. Both monthly/annual mean and monthly/annual maximum values of daytime LST were significantly different when only clear-sky values were utilized, in comparison with all-sky values. Monthly averaged differences between the mean clear- and all-sky daytime LST (dLST) values ranged from −0.1° ± 1.5°C for January to 5.6° ± 1.8°C for May. Annually averaged dLST values, over the five years of the study, were 2.58°C, and differences between the maximum values of clear- and all-sky daytime LST values were −1.03°C. Although significant differences between mean annual clear-sky and all-sky daytime LST values were more frequent than differences observed for the annual maximum daytime LST values, the results suggest that the exclusive use of either mean or maximum clear-sky daytime LST values is not advisable for applications in which the use of daytime all-sky LST values would be more applicable.

The terrestrial biosphere interacts with the free atmosphere through the exchange of momentum, energy and mass [...]

Despite their sparse vegetation, dryland regions exert a huge influence over global biogeochemical cycles because they cover more than 40% of the world surface (Schimel 2010 Science 327 418–9). It is thought that drylands dominate the inter-annual variability (IAV) and long-term trend in the global carbon (C) cycle (Poulter et al 2014 Nature 509 600–3, Ahlstrom et al 2015 Science 348 895–9, Zhang et al 2018 Glob. Change Biol. 24 3954–68). Projections of the global land C sink therefore rely on accurate representation of dryland C cycle processes; however, the dynamic global vegetation models (DGVMs) used in future projections have rarely been evaluated against dryland C flux data. Here, we carried out an evaluation of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 dryland flux sites in the southwestern US encompassing a range of ecosystem types (forests, shrub- and grasslands). We find that all the models underestimate both mean annual C uptake/release as well as the magnitude of NEE IAV, suggesting that improvements in representing dryland regions may improve global C cycle projections. Across all models, the sensitivity and timing of ecosystem C uptake to plant available moisture was at fault. Spring biases in gross primary production (GPP) dominate the underestimate of mean annual NEE, whereas models’ lack of GPP response to water availability in both spring and summer monsoon are responsible for inability to capture NEE IAV. Errors in GPP moisture sensitivity at high elevation forested sites were more prominent during the spring, while errors at the low elevation shrub and grass-dominated sites were more important during the monsoon. We propose a range of hypotheses for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future dryland DGVM developments. Our analysis suggests that improvements in modeling C cycle processes across more than a quarter of the Earth’s land surface could be achieved by addressing the moisture sensitivity of dryland C uptake.

Dryland ecosystems occupy ~40% of the land surface and are thought to dominate the inter-annual variability (IAV) and long-term trend of the global carbon (C) cycle. Therefore, it is imperative tha...

Land surface temperature (LST) is a key variable in the determination of land surface energy exchange processes from local to global scales. Accurate ground measurements of LST are necessary for a number of applications including validation of satellite LST products or improvement of both climate and numerical weather prediction models. With the objective of assessing the quality of in situ measurements of LST and to evaluate the quantitative uncertainties in the ground-based LST measurements, intensive field experiments were conducted at NOAA&rsquo, s Air Resources Laboratory (ARL)&rsquo, s Atmospheric Turbulence and Diffusion Division (ATDD) in Oak Ridge, Tennessee, USA, from October 2015 to January 2016. The results of the comparison of LSTs retrieved by three narrow angle broadband infrared temperature sensors (IRT), hemispherical longwave radiation (LWR) measurements by pyrgeometers, forward looking infrared camera with direct LSTs by multiple thermocouples (TC), and near surface air temperature (AT) are presented here. The brightness temperature (BT) measurements by the IRTs agreed well with a bias of &lt, 0.23 &deg, C, and root mean square error (RMSE) of &lt, 0.36 &deg, C. The daytime LST(TC) and LST(IRT) showed better agreement (bias = 0.26 &deg, C and RMSE = 0.67 &deg, C) than with LST(LWR) (bias &gt, 1.1 and RMSE &gt, 1.46 &deg, C). In contrast, the difference between nighttime LSTs by IRTs, TCs, and LWR were &lt, 0.47 &deg, C, whereas nighttime AT explained &gt, 81% of the variance in LST(IRT) with a bias of 2.64 &deg, C and RMSE of 3.6 &deg, C. To evaluate the annual and seasonal differences in LST(IRT), LST(LWR) and AT, the analysis was extended to four grassland sites in the USA. For the annual dataset of LST, the bias between LST (IRT) and LST (LWR) was &lt, 0.7 &deg, C, except at the semiarid grassland (1.5 &deg, C), whereas the absolute bias between AT and LST at the four sites were &lt, 2 &deg, C. The monthly difference between LST (IRT) and LST (LWR) (or AT) reached up to 2 &deg, C (5 &deg, C), whereas half-hourly differences between LSTs and AT were several degrees in magnitude depending on the site characteristics, time of the day and the season.

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO2 sink. However, such analyses are poorly constrained by measured CO2 exchange in drylands. Here we address this observation gap with eddy covariance data from 25 sites in the water-limited Southwest region of North America with observed ranges in annual precipitation of 100-1000 mm, annual temperatures of 2-25°C, and records of 3-10 years (150 site-years in total). Annual fluxes were integrated using site-specific ecohydrologic years to group precipitation with resulting ecosystem exchanges. We found a wide range of carbon sink/source function, with mean annual net ecosystem production (NEP) varying from -350 to +330 gCm-2 across sites with diverse vegetation types, contrasting with the more constant sink typically measured in mesic ecosystems. In this region, only forest-dominated sites were consistent carbon sinks. Interannual variability of NEP, gross ecosystem production (GEP), and ecosystem respiration (Reco ) was larger than for mesic regions, and half the sites switched between functioning as C sinks/C sources in wet/dry years. The sites demonstrated coherent responses of GEP and NEP to anomalies in annual evapotranspiration (ET), used here as a proxy for annually available water after hydrologic losses. Notably, GEP and Reco were negatively related to temperature, both interannually within site and spatially across sites, in contrast to positive temperature effects commonly reported for mesic ecosystems. Models based on MODIS satellite observations matched the cross-site spatial pattern in mean annual GEP but consistently underestimated mean annual ET by ~50%. Importantly, the MODIS-based models captured only 20-30% of interannual variation magnitude. These results suggest the contribution of this dryland region to variability of regional to global CO2 exchange may be up to 3-5 times larger than current estimates.

Spatial and temporal variability of the Marine Atmospheric Boundary Layer (MABL) height for the Indian Ocean Experiment (INDOEX) study period are examined using the data collected through Cross-chained LORAN (Long-Range Aid to Navigation) Atmospheric Sounding System (CLASS) launchings during the Northern Hemispheric winter monsoon period. This paper reports the results of the analyses of the data collected during the pre-INDOEX (1997) and the INDOEX-First Field Phase (FFP; 1998) in the latitude range 14°N to 20°S over the Arabian Sea and the Indian Ocean. Mixed layer heights are derived from thermodynamic profiles and they indicated the variability of heights ranging from 400m to 1100m during daytime depending upon the location. Mixed layer heights over the Indian Ocean are slightly higher during the INDOEX-FFP than the pre-INDOEX due to anomalous conditions prevailing during the INDOEX-FFP. The trade wind inversion height varied from 2.3km to 4.5km during the pre-INDOEX and from 0.4km to 2.5km during the INDOEX-FFP. Elevated plumes of polluted air (lofted aerosol plumes) above the marine boundary layer are observed from thermodynamic profiles of the lower troposphere during the INDOEX-FFP. These elevated plumes are examined using 5-day back trajectory analysis and show that one group of air mass travelled a long way from Saudi Arabia and Iran/Iraq through India before reaching the location of measurement, while the other air mass originates from India and the Bay of Bengal.

Land surface temperature (LST) is a key variable for studying the energy and water vapor exchange at the biosphere–atmosphere interface. In an effort to better quantify the spatial variability and overall representativeness of single-point LST measurements being recorded at NOAA's Climate Reference Network (CRN) sites and to improve the accuracy of satellite LST measurements, airborne flight campaigns were conducted over a CRN site in Crossville, Tennessee, USA during 2010 to 2011. Multiple measurements of LST were made using infrared temperature sensors at micrometeorological tower sites and onboard an instrumented Piper Navajo airborne research aircraft. In addition to this, coincident LST products from the moderate resolution imaging spectroradiometer (MODIS) instruments (Collection 5), onboard NASA Terra and Aqua Earth Observing System satellites were used. In this paper the comparison of LST measurements made from multiple platforms are presented. Our study showed that the temporal and spatial variability of surface temperature as indicated by the standard deviation of the brightness temperature (Tb) during the flight periods were

This study compares six evapotranspiration ET products for Canada’s landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of data quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November–February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.

Automated measurements of the net forest-floor CO 2 exchange (NFFE) were made in a mature (130-year-old) boreal black spruce forest over an 8-year period (2002–2009) with the objectives of (1) quantifying the spatial and temporal (seasonal and interannual) patterns in NFFE, soil respiration (SR) and gross forest-floor photosynthesis (GFFP), and (2) better understanding the key climatic controls on each component at both time scales. Scaling-up of the component fluxes to the stand level showed that the feather moss community accounted for more than 85% of NFFE and SR, and more than 70% of GFFP. The remainder was partitioned almost equally between the sphagnum and lichen communities for all components fluxes, while the exposed mineral soil in hollows accounted for less than 1% of NFFE and SR. Soil temperature ( T s ) was the dominant climate variable determining seasonal trends in NFFE and SR. The shape of the exponential response was, however, strongly modulated by soil water content (SWC) in the surface organic horizon, with reduced apparent temperature sensitivity at low SWC. A lowering of the water table depth also had an effect on NFFE and SR, although very weak, with increased CO 2 loss from the hollows likely due to improved soil aeration. Air temperature ( T a ) was the dominant climate variable determining seasonal trends in GFFP, while plant water status seemed to have played a minor role. Although not statistically significant ( p = 0.9907), annual totals of scaled-up NFFE varied from 505 ± 121 to 601 ± 144 g C m −2 y −1 over the 8-year period. The lowest NFFE was observed in 2004, the coldest and wettest year on record, while the highest was observed in 2005, a warmer year with slightly above-average precipitation. SR, by far the dominant component of the forest-floor CO 2 exchange, closely followed the inter-annual trends in NFFE, while GFFP was lowest in 2004 and highest in 2003, also a cold year but with very low precipitation. Over the 8-year period, winter NFFE contributed 7% to annual NFFE while GFFP during the growing season reduced losses due to SR by 18%. While strong correlations were observed between the component fluxes and temperature ( T s or T a ) and SWC at the seasonal time scale, the mean annual values of these climate variables were poor predictors of the inter-annual trends when considered individually. Combining multiplicatively T s and SWC for NFFE and SR, and T a and SWC for GFFP, significantly increased the predictive ability of the models. The difference in predictability of the two time scales poses some interesting challenges for interpreting and modeling the long-term temporal trends in NFEE and its components. The results obtained in this relatively long-term study suggest that the inter-annual variability in the component fluxes was not driven by the mean annual climate conditions, but rather the shorter time scale changes in climate conditions, i.e. changes that occurred within days, weeks and/or seasons. Moreover, it appeared that the timing of the climatic changes within each year was also critical, spring and summer conditions having a far greater impact than fall and winter conditions in this stand.

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO

The seasonal and interannual variability in surface energy exchange and evapotranspiration ( E ) of two temperate semi-arid grasslands in southeastern Arizona, USA, were investigated using multi-year (2004–2007) eddy covariance measurements. The study sites, a post-fire site (AG) and an unburned site (KG), received 43–87% of the annual precipitation ( P ) during the North American Monsoon season (July–September), with the lowest values in the drought years of 2004 and 2005. Irrespective of the differences in temperature, surface albedo, vegetation cover and soil characteristics both sites responded similarly to changes in environmental conditions. The seasonal and interannual variations in the partitioning of net radiation to turbulent fluxes were mainly controlled by P through the changes in soil water content ( θ ) and vegetation growth. Drastic changes in albedo, vegetation growth and energy fluxes occurred following the onset of the monsoon season in July. During the dry or cool periods of autumn, winter and spring, the sensible heat flux was the largest component of the energy balance, whereas latent heat flux dominated during the warm and wet periods of summer. The dry-foliage Priestley–Taylor coefficient ( α ) declined when θ in the 0–15 cm soil layer dropped below 0.08 m 3 m −3 at AG, and 0.09 m 3 m −3 at KG, respectively. The July–September average of dry-foliage surface conductance, α and E , reached their lowest values in 2004 at AG and in 2005 at KG. During July–September, monthly E was linearly correlated to the monthly mean θ and the broadband normalized difference vegetation index (NDVI), whereas during May–June the relationship between NDVI and E was not significant. Annual E varied from 264 to 322 mm at AG and from 196 to 284 mm at KG with the lowest value during the severe drought year at the site. July–September E had positive correlation with total P , the mean NDVI and the number of growing season days during that period. Annual P explained more than 80% of the variance in annual E .

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 large area of boreal jack pine (Pinus banksiana Lamb.) forest in Canada is recovering from clear-cut harvesting, and the carbon (C) balance of these regenerating forests remains uncertain. Net ecosystem CO 2 exchange was measured using the eddy-covariance technique at four jack pine sites representing different stages of stand development: three postharvest sites (HJP02, HJP94, and HJP75) and one preharvest site (OJP). The four sites, located in the southern Canadian boreal forest, Saskatchewan, Canada, are typical of low productivity jack pine stands and were 2, 10, 29, and 90 years old in 2004, respectively. Mean annual net ecosystem production (NEP) for 2004 and 2005 was -137 ± 11, 19 ± 16, 73 ± 28, and 22 ± 30 g C m -2 yr -1 at HJP02, HJP94, HJP75 and OJP, respectively, showing the postharvest jack pine stands to be moderate C sources immediately after harvesting, weak sinks at 10 years, moderate C sinks at 30 years, then weak C sinks at 90 years. Mean annual gross ecosystem photosynthesis (GEP) for the 2 years was 96 ± 10, 347 ± 20, 576 ± 34, and 583 ± 35 g Cm -2 yr -1 at HJP02, HJP94, HJP75, and OJP, respectively. The ratio of annual ecosystem respiration (R) to annual GEP was 2.51 ± 0.15, 0.95 ± 0.04, 0.87 ± 0.03, and 0.96 ± 0.03. Seasonally, NEP peaked in May or June at all four sites but GEP and R were highest in July. R at a reference soil temperature of 10 °C, ecosystem quantum yield and photosynthetic capacity were lowest for the 2-year-old stand. R was most sensitive to soil temperature for the 90-year-old stand. The primary source of variability in NEP over the course of succession of the jack pine ecosystem following harvesting was stand age due to the changes in leaf area index. Intersite variability in GEP and R was an order of magnitude greater than interannual variability at OJP. For both young and old stands, GEP had greater interannual variability than R and played a more important role than R in interannual variation in NEP. Based on year-round flux measurements from 2000 to 2005, the 10-year stand had larger interannual variability in GEP and R than the 90-year stand. Interannual variability in NEP was driven primarily by early-growing-season temperature and growing-season length. Photosynthesis played a dominant role in the rapid rise in NEP early in stand development. Late in stand development, however, the subtle decrease in NEP resulted primarily from increasing respiration.

Similar nonsteady-state automated chamber systems were used to measure and partition soil CO 2 efflux in contrasting deciduous (trembling aspen) and coniferous (black spruce and jack pine) stands located within 100km of each other near the southern edge of the Boreal forest in Canada. The stands were exposed to similar climate forcing in 2003, including marked seasonal variations in soil water availability, which provided a unique opportunity to investigate the influence of climate and stand characteristics on soil CO 2 efflux and to quantify its contribution to the net ecosystem CO 2 exchange (NEE) as measured with the eddy-covariance technique. Partitioning of soil CO 2 efflux between soil respiration (including forest-floor vegetation) and forest-floor photosynthesis showed that short- and long-term temporal variations of soil CO 2 efflux were related to the influence of (1) soil temperature and water content on soil respiration and (2) below-canopy light availability, plant water status and forest-floor plant species composition on forest-floor photosynthesis. Overall, the three stands were weak to moderate sinks for CO 2 in 2003 (NEE of -103, -80 and -28 g C m -2 yr -1 for aspen, black spruce and jack pine, respectively). Forest-floor respiration accounted for 86%, 73% and 75% of annual ecosystem respiration, in the three respective stands, while forest-floor photosynthesis contributed to 11% and 14% of annual gross ecosystem photosynthesis in the black spruce and jack pine stands, respectively. The results emphasize the need to perform concomitant measurements of NEE and soil CO 2 efflux at longer time scales in different ecosystems in order to better understand the impacts of future interannual climate variability and vegetation dynamics associated with climate change on each component of the carbon balance.

The light-use efficiency (LUE) of a mature Canadian Douglas-fir forest (DF49) was studied using high-resolution in situ temporal, spatial, and spectral measurements in conjunction with fluxes acquired from an instrumented tower. We examined the photochemical reflectance index (PRI), a spectral index responsive to high light conditions that alters reflectance at 531 nm, in combination with several alternative reference bands at 551, 570, and 488 nm. These indices were derived from directional reflectance spectra acquired by a hyperspectral radiometer system mounted on the DF49 tower, viewing the canopy through almost 360° rotations multiple times an hour daily throughout the 2006 growing season. From canopy structure information, three foliage sectors within the canopy were delineated according to instantaneous illumination conditions (sunlit, shaded, and mixed shaded–sunlit). On sunny days, the PRI indices for the sunlit foliage sector captured high light-induced stress responses, expressed as significant...

Monitoring of photosynthetic efficiency ( e ) over space and time is a critical component of climate change research as it is a major determinant of the amount of carbon accumulated by terrestrial ecosystems. While the past decade has seen progress in the remote estimation of e at the leaf, canopy and stand level using the photochemical reflectance index PRI (based on the normalized difference of reflectance at 531 and 570 nm), little is known about the temporal and spatial requirements for up-scaling PRI to landscape and global levels using satellite observations. One potential way to investigate these requirements is using automated tower-based remote sensing platforms, which observe stand level reflectance with high spatial, temporal, and spectral resolution. Prediction of e from PRI diurnally or over a full year requires observations of canopy reflectance over multiple view and sun-angles. As a result, these observations are subject to directional reflectance effects which can be interpreted in terms of the bidirectional reflectance distribution function (BRDF) using semi-empirical kernel driven models. These semi-empirical models use a combination of physically based BRDF shapes and empirical observations to standardize multi-angular observations to a common viewing and illumination geometry. Directional reflectance effects are thereby modeled as a linear superposition of mathematical kernels, representing the bi-direction variation in reflectance from isotropic, geometric, and volumetric scattering components of the vegetation canopy. However, because variations in plant physiological conditions can also introduce bidirectional reflectance variations, we introduce an approach to separate bidirectional effects arising purely from plant physiological status from other effects by stratifying PRI observations into categories based on environmental conditions for which the expected physiological variability is low. Within each of these PRI strata, the derived physically based BRDF shapes were used to standardize multi-angular PRI measurements to a common viewing and illumination geometry. The method significantly enhanced the relationship found between PRI and e (from r 2 = 0.38 for the directionally uncorrected case to r 2 = 0.82 for the directionally corrected case) from data measured continuously over the course of 1 year over an evergreen conifer forest using an automated platform. Results show that isotropic PRI scattering is highly correlated to changes in e , while geometric scattering can be related to canopy level shading. Instrumentation and approaches such as the one demonstrated in this study may be integrated into current efforts aiming at predicting e at global scales using satellite observations.

The interannual and seasonal variability of gross ecosystem photosynthesis (P), ecosystem respiration (R) and evapotranspiration (E), and their relationships to environmental factors were used to explain changes in net ecosystem productivity (F NEP) at the onset of, during, and following a 3-year-long (2001–2003) drought in a mature boreal aspen stand in central Saskatchewan, Canada. The forest was a moderate carbon (C) sink over its entire 11-year data record (F NEP = 153 � 99 g C m � 2 year � 1 ), including the peak drought years of 2002 and 2003. In 2001, the depletion of water near the soil surface likely reduced heterotrophic soil respiration while water remaining deep in the root zone maintained P above the pre-drought mean, resulting in above-average F NEP. In 2002 and 2003, the forest remained a C sink even though P was below average because R was also below average—a likely consequence of the influence of low soil water content in deep and shallow soil layers on both autotrophic and heterotrophic respiration. In 2004, the recharge of soil water in shallow soil layers allowed R to recover to its pre-drought values, whereas low spring temperatures, the slow recharge of soil water in deep soil layers in spring, late leaf emergence and diminished leaf area index combined to suppress P and produce the lowest annual F NEP of the 11-year record (4 g C m � 2 year � 1 ). The low F NEP and P were mirrored in the lowest stem growth and LAI values of the 11-year record. In 2005, a warm wet year, both the annual values and seasonal variations of F NEP, P and R returned to those of pre-drought years; the partial recovery of LAI to pre-drought values suggests that aspen P was able to adjust to this restriction on C assimilation. Growing season average dry surface conductance (gsv), the Priestley–Taylor coefficient (a) and light use efficiency (LUE) reached their lowest values in 2003 and became similar to predrought years in 2004–2005. Water use efficiency (WUE) was highest in 2003 and remained above average in 2004 and 2005. At the ecosystem scale, the above-average gains made in C sequestration in the first year of the drought were significantly offset by belowaverage stand F NEP in the final 2 years of the drought, and in the year following the drought. # 2006 Elsevier B.V. All rights reserved.

This paper discusses the observations of the Atmospheric Surface Layer (ASL) parameters during the solar eclipse of August 11th, 1999. Intensive surface layer experiments were conducted at Ahmedabad (23‡21′N, 72‡36′E), the western part of India, which was close to the totality path. This rare event provided by nature is utilised to document the surface layer effects during the eclipse period using measurements of high frequency fluctuations of temperature, tri-axial wind components as well as mean parameters such as temperature, humidity, wind speed and subsoil temperature. Analysis showed that during the eclipse period, the turbulence parameters were affected leading to the suppression of the turbulence process, the main dynamic process in the atmospheric boundary layer, while the mean parameters showed variations within the natural variability of the observational period. The spectra of the wind components and temperature indicated decrease in spectral power by one order in magnitude during the eclipse period. The rate of dissipation of turbulent kinetic energy is found to decrease by more than one order during the eclipse period. The stability parameter showed a change from unstable to stable condition during the period of eclipse and back to unstable condition by the end of eclipse

Some characteristic features of the atmospheric surfacelayer over an inland tropical station, Lucknow (27°N, 81°E)in India, are investigated for different seasons using micrometeorological data collected at the 10-m levelof an instrumented tower. Seasonal monsoonal variations in wind circulation (north-easterliesand south-westerlies) dominate the flow over this part of the region. This study utilizesthe wind, temperature and humidity data obtained for a period of one year from February 1996 to January 1997. The diurnal variation of mean parameterssuch as temperature, relative humidity, and wind speed are studied for different seasonsnamely pre-, south-west, post- and north-east monsoon periods. Turbulent statistics are computedusing the eddy correlation technique, and are studied under the framework of Monin–Obukhov similarity theory with results compared with otherexperimental studies reported in the literature. It is found that the turbulence statistics arenearly independent of season and the near-neutral values of the normalized standard deviations ofthe three wind components, temperature and specific humidityare found to be 1.00 ± 0.04 (vertical), 2.63 ± 0.36(longitudinal), 2.19 ± 0.06 (lateral), 6.56 ± 0.33and 6.45 ± 0.33 respectively.

This paper describes the variation of air–sea parameters and fluxes during winter months of 1997 (pre-INDOEX) and 1998 (INDOEX-FFP) using ship-based in situ measurements in the latitude range 15°N to 20°S over the Indian Ocean and Arabian Sea. The 1998 cruise period coincided with one of the strongest El Nino events in the decade over the Pacific Ocean. The tropical Indian Ocean underwent a highly anomalous series of events during 1998 with warm sea surface temperature (SST) anomaly over 2 °C during February 1998 and easterly winds associated with the reversed Walker circulation. In situ observations during 1998 cruise period show that the winds in the Indian Ocean region had basically resumed their climatological state as of March 15, 1998 with lesser wind speeds as El Nino waned. However, the sea surface temperatures in Indian Ocean were found to be high even though climatological state had resumed. The present results are the observational evidence to show that the reduced latent heat flux due to low wind speeds could have contributed to the surface warming in the Indian Ocean. The sensible heat and latent heat fluxes are found to be high during anomalous period due to higher sea surface temperature and wind speeds in comparison to the normal period.

A surface layer experiment conducted at a site in the northwest part of India is described. Micrometeorological data collected from the intense field experiment conducted at a tropical inland station, Ahmedabad (23°N, 72.5°E), India during southwest monsoon period by deploying tower-based instruments were analyzed using eddy correlation method to study the characteristics of atmospheric surface layer (ASL). The normalized standard deviation of vertical wind, temperature and specific humidity were studied using Monin Obukhov (MO) similarity relations. The normalized standard deviation of vertical wind velocity ( φ w ) is found to be around 1.37 for near neutral condition and it is found to be proportional to ( z / L ) 1/3 for unstable condition and ( z / L ) 1 for stable conditions. The normalized standard deviation of temperature ( φ T ) and humidity ( φ q ) are studied as a function of z / L and it showed ( z / L ) −1/3 dependence for unstable condition and ( z / L ) −1 dependence for stable condition. The value of φ T for near neutral condition is found to be around 6.5, which is high compared with the values reported from other field experiments. The drag coefficient showed a strong dependence on wind velocity at low wind conditions and it is found to obey a power law of wind speed irrespective of the various stability conditions.

[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] 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] Factors controlling the seasonal and interannual variability of net ecosystem productivity (FNEP), gross ecosystem photosynthesis (Pg), ecosystem respiration (Re) and evapotranspiration (E) of a mature boreal black spruce forest in central Saskatchewan, Canada were investigated using eight years (1999–2006) of continuous eddy covariance measurements. During 2000–2006, which included a three-year drought, the forest was a weak sink for CO2 with annual FNEP ranging from 27 to 80 g C m-2 (56 ± 21 g C m−2 a−1). The beginning of the growing season occurred when daily mean air temperature exceeded 4°C and the near surface soil temperature equaled or exceeded 0°C. The length of the growing season varied from 186 to 232 days. During the extreme drought year (2003), the smaller reduction in annual Pg than in Re resulted in highest FNEP of the record. Annual FNEP decreased slightly with increasing soil water content; however, there was evidence of increased FNEP due to high water table conditions in 2004 because of the slightly higher decrease in Re than Pg. Although bulk surface conductance (gs) decreased significantly during the dry conditions in 2003, the associated increase in D prevented a significant drop in E, which resulted in only a slight decline in evaporative fraction and almost no change in water use efficiency. Interannual variation inPg, Re and FNEP in the early growing season (April–June) and late growing season (July–September) was controlled by air temperature and soil water content, respectively. However, spring (April–May) mean air temperature was the main factor determining the interannual variation in annual FNEP. The effect of late growing season soil water content on annual Pg and Re was greater than its effect on annual FNEP. The results emphasize the need to consider soil moisture conditions as well as temperature when simulating the response of the carbon balance components of this ecosystems to climate change.

[1] Signatures of the low frequency intraseasonal oscillations (ISO) and their time-height evolution in the lower atmosphere are studied using multilevel wind observations made at a tropical Indian site, Gadanki using UHF radar during the period from March 1999 to September 2000. Spectral analysis using Fast Fourier transform (FFT) and wavelet transform showed the presence of oscillations in zonal wind and revealed their evolution in height and time during the observational period. 10–25 day and 30–60 day oscillations are predominantly observed during pre-monsoon and southwest (SW) monsoon respectively. The amplitude of these oscillations are found to be weak in the lower altitudes and strengthened across the lower Atmospheric Boundary Layer (ABL) and this is quite prominent in the case of 30–60 day oscillations. All these oscillations strengthened at higher altitudes especially above mean ABL height >1 km. It is observed that intense 10–25 day oscillations present during pre monsoon become 30–60 day oscillations as monsoon intensifies. Spectral analysis carried out using NCEP wind for the same period also showed the existence of increasing time scale along SW monsoon season even though 10–25 day and 80–90 day oscillations are found to be relatively weak. Further use of NCEP zonal wind in 2001 and 2002 showed a remarkably different behaviour during the dry year of 2002 with an early development of low-frequency oscillations prior to the monsoon season.

The carbon science community must rely on satellite remote sensing to obtain global estimates of photosynthetic activity, typically expressed as net primary production (NPP), gross primary production (GPP) or light use efficiency (LUE). The photochemical reflectance index (PRI), calculated as a normalized difference reflectance index using a physiologically active green band (~531 nm) and another physiologically insensitive green reference band (~570 nm), denoted as PRI(570), has been confirmed in many studies as being strongly related to LUE. Here, we examined the potential of utilizing PRI(570) observations under different illumination conditions for canopy LUE estimation of a forest. In order to evaluate this, directional hyperspectral reflectance measurements were collected continuously throughout the daytime periods using an automated spectroradiometer in conjunction with tower-based eddy covariance fluxes and environmental measurements at a coastal conifer forest in British Columbia, Canada throughout the 2006 growing season. A parameter calculated as the PRI(570) difference (dPRI(570)) between shaded versus sunlit canopy foliage sectors showed a strong correlation to tower-based LUE. The seasonal pattern for this correlation produced a dramatic change from high negative (r ~ ?0.80) values in the springtime and early fall to high positive values (r ~ 0.80) during the summer months, which could represent the seasonality of physiological characteristics and environmental factors. Although the PRI(570) successfully tracked canopy LUE, one or both of its green bands (~531 and 570 nm) used to calculate the PRI are unavailable on most existing and planned near-term satellites. Therefore, we examined the potential to use 24 other spectral indexes for LUE monitoring that might be correlated to PRI, and thereby a substitute for it. We also continued our previous investigations into the influence of illumination conditions on the observed PRI(570) and other indexes. Among the 24 indexes examined, three PRI indexes using different reference bands (488, 551 and 705 nm) showed high correlations to the traditional PRI(570), especially PRI(551) and PRI(705). This indicates three additional PRI variations for LUE monitoring if the traditional reference band at 570 nm is not available but the 531 nm band is available. Five other indexes also yielded high correlations to PRI(570): Dmax and DM705, two indexes calculated from derivative reflectance spectra; a simple ratio of reflectance values at 685 nm and 655 nm (SR685_655); and a double-peak optical index (DPI). The diurnal and seasonal dynamics of these eight indexes and PRI(570) were explored. All of these indexes except DPI expressed linear dependence on available sunlight and more strongly expressed diurnal dynamics in April than in August during summer drought. The differences for shaded versus sunlit canopy foliage sectors were also calculated for the eight indexes, and their correlations to canopy LUE across the season were examined. The performances were similar for the most successful and seasonally stable indexes: dPRI(551), dPRI(705) and dPRI(570). The other five indexes showed good correlation to LUE in some but not all the months, and the months with high correlations varied among them.

Gross primary production (GPP) is often expressed as the product of absorbed photosynthetically active radiation and the efficiency (epsilon) with which a plant community uses absorbed radiation in biomass production. Light-use efficiency is affected by environmental stresses, and varies diurnally and seasonally. Uncertainty about epsilon can be a serious limitation when modeling GPP. An important determinant of epsilon is the amount and type of solar radiation incident on a canopy, because an abundance of light can trigger a photo-protective reaction, diminishing GPP. The radiation regime in a forest canopy is determined by the predominant sky conditions and by mutual shading of tree crowns. Shading effects, producing shifts in the amount of incident direct and diffuse solar radiation, have been largely ignored, however, because they depend on forest structure and are difficult to measure. We describe a new approach for estimating changes in mutual canopy shading throughout the day and year based on a canopy structure model derived from light detection and ranging (LiDAR). Proportions of canopy shading were then combined with eddy covariance data to assess the explanatory power for variance in epsilon by regression tree analysis over half-hourly, daily and weekly time scales. The approach explained between 75 and 97% of variance in epsilon, representing an increase of between 5 and 16% compared with models driven solely by meteorological variables.