Satellite-derived Observations Research Articles

Wind-driven variability in sea surface temperature front distribution in the California Current System

Simultaneous satellite-derived observations from 2002 to 2009 are used to quantify the relation between sea surface temperature (SST) fronts and ocean winds in the California Current System (CCS). An edge-detection algorithm is applied to SST observations to generate monthly maps of frontal probabilities. Empirical orthogonal decompositions reveal that the seasonal evolution of fronts in the CCS is strongly related to the seasonal evolution of coastal alongshore wind stress. The seasonal development of SST fronts is remarkably different to the north and to the south of Cape Mendocino, however. While fronts to the north of the cape extend for hundreds of kilometers from the coast peaking during summer and fall, when upwelling winds are stronger off northern California and Oregon, the region to the south of Cape Mendocino is characterized by high frontal activity during spring in a much narrower band close to the coast. Throughout the region, anomalies in the intensity of upwelling-favorable wind stress are followed by anomalies in frontal activity. The width and speed of the widening of the region of high frontal activity are also related to coastal alongshore wind stress. Interannual variability in the timing of the widening of the region of high frontal activity in the lee of Cape Blanco compared to the timing of the spring transition to upwelling-favorable winds may be related to the wind stress curl distribution in the lee of the cape. Stronger upwelling-favorable wind stress curl anomalies lead to early widening of the region of high frontal activity.

Estimating extremes from global ocean and climate models: A Bayesian hierarchical model approach

Estimating oceanic and atmospheric extremes from global climate models is not trivial as these models often poorly represent extreme events. However, these models do tend to capture the central climate statistics well (e.g., the mean temperature, variances, etc.). Here, we develop a Bayesian hierarchical model (BHM) to improve estimates of extremes from ocean and climate models. This is performed by first modeling observed extremes using an extreme value distribution (EVD). Then, the parameters of the EVD are modeled as a function of climate variables simulated by the ocean or atmosphere model over the same time period as the observations. By assuming stationarity of the model parameters, we can estimate extreme values in a projected future climate given the climate statistics of the projected climate (e.g., a climate model projection under a specified carbon emissions scenario). The model is demonstrated for extreme sea surface temperatures off southeastern Australia using satellite-derived observations and downscaled global climate model output for the 1990s and the 2060s under an A1B emissions scenario. Using this case study we present a suite of statistics that can be used to summarize the probabilistic results of the BHM including posterior means, 95% credible intervals, and probabilities of exceedance. We also present a method for determining the statistical significance of the modeled changes in extreme value statistics. Finally, we demonstrate the utility of the BHM to test the response of extreme values to prescribed changes in climate.

Evaluation of Forecasts of the Water Vapor Signature of Atmospheric Rivers in Operational Numerical Weather Prediction Models

Abstract The ability of five operational ensemble forecast systems to accurately represent and predict atmospheric rivers (ARs) is evaluated as a function of lead time out to 10 days over the northeastern Pacific Ocean and west coast of North America. The study employs the recently developed Atmospheric River Detection Tool to compare the distinctive signature of ARs in integrated water vapor (IWV) fields from model forecasts and corresponding satellite-derived observations. The model forecast characteristics evaluated include the prediction of occurrence of ARs, the width of the IWV signature of ARs, their core strength as represented by the IWV content along the AR axis, and the occurrence and location of AR landfall. Analysis of three cool seasons shows that while the overall occurrence of ARs is well forecast out to a 10-day lead, forecasts of landfall occurrence are poorer, and skill degrades with increasing lead time. Average errors in the position of landfall are significant, increasing to over 800 km at 10-day lead time. Also, there is a 1°–2° southward position bias at 7-day lead time. The forecast IWV content along the AR axis possesses a slight moist bias averaged over the entire AR but little bias near landfall. The IWV biases are nearly independent of forecast lead time. Model spatial resolution is a factor in forecast skill and model differences are greatest for forecasts of AR width. This width error is greatest for coarser-resolution models that have positive width biases that increase with forecast lead time.

Geospatial interpolation of MODIS-derived salinity and temperature in the Chesapeake Bay

In dynamic coastal systems such as the Chesapeake Bay, limited coverage and frequency of in situ measurements often makes generalizability of regional forecasting systems difficult. Satellite-derived environmental variables have the potential to address this problem, but satellite datasets suffer from incomplete coverage as well: atmospheric conditions—most notably cloud cover—lead to data gaps that significantly hinder the broad application of satellite-informed predictions. In this study, the Chesapeake Bay estuary was used as a model “test bed” to which we applied the power of near real-time satellite-derived observations to the issue of water quality monitoring. To use remote sensing in support of spatially complete estimates of salinity and temperature in the Bay, we tested geospatial interpolation techniques as a method for filling gaps and minimizing errors in the satellite record. These interpolated values were then compared to the output of a regional hydrodynamic model in order to assess the relative value of each method for generating inputs into various modeling applications. Results show that MODIS-derived salinity and temperature can be interpolated with acceptable accuracy in the Bay, with a mean absolute error of 1.88psu and 0.60°C. These errors differed systematically from ChesROMS errors both spatially and seasonally, with higher errors for salinity and lower errors for temperature at most sampling stations throughout the year. This suggests that the two techniques offer complementary information that can be applied to ecological monitoring systems in complex estuaries like Chesapeake Bay.

A Comparison of Atmospheric Reanalysis Surface Products over the Ocean and Implications for Uncertainties in Air–Sea Boundary Forcing

Abstract This paper investigates the uncertainties related to atmospheric fields from reanalysis products used in forcing ocean models. Four reanalysis products, namely from 1) the interim ECMWF Re-Analysis (ERA-Interim), 2) version 2 of the Common Reference Ocean–Ice Experiments (CORE2), 3) the 25-Year Japanese Reanalysis Project (JRA-25), and 4) NCEP–NCAR, are evaluated against satellite-derived observations for eight different fields (zonal and meridional winds, precipitation, specific humidity, continental discharge, surface air temperature, and downwelling longwave and shortwave radiation fluxes). No single product is found to agree better in all fields with satellite-derived observations. Reanalysis products are mostly comparable to each other because of their similar physical assumptions and assimilation of common observations. Adjusted atmospheric fields from the Estimating the Circulation and Climate of the Ocean (ECCO) optimizations are also in agreement with other reanalysis products. Time-mean and time-variable errors are estimated separately and mapped globally in space, based on 14-day average fields to focus on monthly to interannual periods. Time-variable errors are larger in comparison to the signal than time-mean errors for most fields, thus justifying the need to separate them for studying uncertainties as well as formulating optimization procedures. Precipitation and wind stress fields show significant time-mean and time-variable errors whereas downwelling radiation, air temperature, and humidity fields show small time-mean errors but large time-variable errors, particularly in the tropics. Uncertainties based on evaluating multiple products presented here are considerably larger than uncertainties based on single product pairs.

A modeling study of ice–water processes for Lake Erie applying coupled ice-circulation models

A hydrodynamic model that includes ice processes and is optimized for parallel processing was configured for Lake Erie in order to study the ice–water coupling processes in the lake. A hindcast from April 2003 to December 2004 with hourly atmospheric forcing was conducted. The model reproduced the seasonal variation of ice cover, but the development of ice extent in January and its decay in March somewhat preceded the observations. Modeled lake circulation in ice-free seasons is consistent with previous studies for Lake Erie. Thermal structure of the lake was reasonably comparable to both satellite-derived observations and in-situ measurements, with mean differences ranging from −2°C to 4°C, depending on the season. The impacts of ice–water stress coupling and basal melting of ice were examined based on numerical experiments. The results show that: 1) ice–water stress coupling significantly dampens the subjacent lake circulation in winter due to packed ice cover that slows down the surface water, and 2) basal melting of ice contributes to widespread ice cover in the lake. The demonstrated model validity could lead to further studies of ice–water processes in the lake, including interannual variation and impacts on ecosystems.

CMIP5 simulated climate conditions of the Greater Horn of Africa (GHA). Part 1: contemporary climate

The present study is a preliminary interrogation of the ability of ten Earth System Models (ESMs) from the fifth phase of coupled model intercomparison project to characterize seasonal and annual mean precipitation cycle over the Greater Horn of Africa region. Each ESM had at least 2 ensemble members. In spite of distributional anomalies of observations, ESM ensemble means were examined on the basis of gridded precipitation data. Majority of the ten ESMs analyzed correctly reproduce the mean seasonal and annual cycle of precipitation for the period 1979-2008 as compared to gridded satellite-derived observations. At the same time our analysis shows signif- icant biases in individual models depending on region and season. Specifically, a modest number of models were able to capture correctly the peaks of bimodal (MAM and OND) and JJAS rainfall while a few either dragged the onset to subsequent months or displaced the locations of seasonal rainfall further north. Nearly all models were in agreement with their representation of the zonal orientation of spatial pattern of the leading EOF rainfall modes; more so, enhanced precipitation over the Indian Ocean and a dipole mode of precipitation pattern are captured in the first and second mode respectively. Further, the corresponding EOF time series of the ESMs rainfall modes were all in phase with observations. However, all models output were posi- tively biased against observations, with large medians and varied range of anomalies. Therefore, caution needs to be taken when choosing models for applications over the region, especially when ensemble means have to be considered.

Assessment of urban heat island effect for different land use–land cover from micrometeorological measurements and remote sensing data for megacity Delhi

Urban heat island intensities (UHI) have been assessed based on in situ measurements and satellite-derived observations for the megacity Delhi during a selected period in March 2010. A network of micrometeorological observational stations was set up across the city. Site selection for stations was based on dominant land use–land cover (LULC) classification. Observed UHI intensities could be classified into high, medium and low categories which overall correlated well with the LULC categories viz. dense built-up, medium dense built-up and green/open areas, respectively. Dense urban areas and highly commercial areas were observed to have highest UHI with maximum hourly magnitude peaking up to 10.7 °C and average daily maximum UHI reaching 8.3 °C. UHI obtained in the study was also compared with satellite-derived land surface temperatures (LST). UHI based on in situ ambient temperatures and satellite-derived land surface temperatures show reasonable comparison during nighttime in terms of UHI magnitude and hotspots. However, the relation was found to be poor during daytime. Further, MODIS-derived LSTs showed overestimation during daytime and underestimation during nighttime when compared with in situ skin temperature measurements. Impact of LULC was also reflected in the difference between ambient temperature and skin temperature at the observation stations as built-up canopies reported largest gradient between air and skin temperature. Also, a comparison of intra-city spatial temperature variations based UHI vis-a-vis a reference rural site temperature-based UHI indicated that UHI can be computed with respect to the station measuring lowest temperature within the urban area in the absence of a reference station in the rural area close to the study area. Comparison with maximum and average UHI of other cities of the world revealed that UHI in Delhi is comparable to other major cities of the world such as London, Tokyo and Beijing and calls for mitigation action plans.

Using Satellite-Derived Snow Cover Data to Implement a Snow Analysis in the Met Office Global NWP Model

AbstractSnow cover and amount are important components in the interaction between the land surface and atmosphere, but until recently there has been no observational snow information incorporated into the Met Office global numerical weather prediction (NWP) model. This paper presents a Northern Hemisphere (NH) snow analysis, based on satellite-derived observations of snow cover, that has recently been implemented in the operational global Unified Model (UM). The analysis uses daily snow maps from the NOAA National Environmental Satellite Data and Information Service Interactive Multisensor Snow and Ice Mapping System (IMS) to modify the UM background snow amount. Assimilation experiments carried out during the NH snow accumulation and ablation periods show improvements in analyzed snow cover, both qualitatively and quantitatively, when compared with unmodified control runs. Although the effect on forecast accuracy of introducing the snow analysis is largely neutral, there is some evidence of small improvements in screen-level temperature and humidity forecasts. Retention of information introduced by the snow analysis is hard, and so the limited impact on forecast accuracy is not unexpected. Several methods of validation and verification are presented, and their results and implications are discussed. The NH snow analysis delivers a basic snow assimilation system that can be expanded and developed further in future iterations to improve the representation of snow cover and amount in global and regional forecasting models.

A gridded sea surface salinity data set for the tropical Pacific with sample applications (1950–2008)

We present a gridded data set of Sea Surface Salinity (SSS) for the tropical Pacific (120°E–70°W; 30°N–30°S), with a grid resolution of 1° longitude, 1° latitude and 1 month, from 1950 to 2008. The product, together with its associated error field, is derived from an objective analysis of about 10 million validated SSS records, with most of the data originating from Voluntary Observing Ships, TAO/TRITON moorings and Argo profilers (during the most recent period). We expect this product to benefit studies in oceanography, meteorology and paleoceanography. As examples of applications, we analyse: (a) the seasonal and ENSO (El Niño Southern Oscillation) modes of observed SSS variability, (b) the ability of 23 coupled models used in the Intergovernmental Panel for Climate Change 4th Assessment Report (IPCC AR4) to simulate the mean SSS and these two time varying modes, and (c) the usefulness of the SSS product and of its associated error field in calibrating and validating the paleo-salinity time series. We anticipate improvements and regular updates to our product, as more SSS data become available from in situ networks and from the ongoing and near-future satellite-derived observations by SMOS (Soil Moisture and Ocean Salinity) and Aquarius.

Marine boundary layer over the subtropical southeast Pacific during VOCALS-REx – Part 2: Synoptic variability

Abstract. In the second part of this work we study the day-to-day variability of the marine atmospheric boundary layer (MBL) over the subtropical southeast Pacific using primarily results from a numerical simulation that covered the whole VOCALS-REx period (October–November 2008). In situ and satellite-derived observations of the MBL height in the offshore region indicate rapid, significant variations (from 500 m to 1700 m a.s.l. over a few days) during October. These MBL changes are connected with the passage of midlatitude troughs that altered the large-scale environment over the VOCALS-REx region. In contrast, the synoptic forcing and MBL changes were less prominent during November. Modelled and observed MBL depth at Point Omega (20° S, 85° W) compare quite well during October (but the simulation is on average 200 m lower) while in November the simulation does not perform as well. In the prognostic local MBL height equation the height change, the horizontal MBL height advection, and the large scale vertical velocity at MBL top are calculated explicitly from the simulation. The entrainment velocity is calculated as the residual of the other terms in the equation. While the vertical velocity and residual terms are opposing and generally have the largest magnitude on average, it is the variability in the advection that explains most of the large changes in the MBL depth. Examination of several cases during VOCALS-REx suggests that the advective term is in turn largely controlled by changes in wind direction, driven by midlatitude activity, acting on a MBL that generally slopes down toward the coast. In one phase, the subtropical anticyclone is reinforced and extends toward the Chilean coast, leading to easterly wind that advects low MBL heights from the coast as far as Point Omega. The opposite phase occurs after the passage of an extratropical cyclone over southern Chile, leading to southwesterly wind that advects a deeper MBL towards subtropical latitudes.

Land-atmosphere interactions in an high resolution atmospheric simulation coupled with a surface data assimilation scheme

Abstract. A valid tool for the retrieving of the turbulent fluxes that characterize the surface energy budget is constituted by the remote sensing of land surface states. In this study sequences of satellite-derived observations (from SEVIRI sensors aboard the Meteosat Second Generation) of Land Surface Temperature have been used as input in a data assimilation scheme in order to retrieve parameters that describe energy balance at the ground surface in the Tuscany region, in central Italy, during summer 2005. A parsimonious 1-D multiscale variational assimilation procedure has been followed, that requires also near surface meteorological observations. A simplified model of the surface energy balance that includes such assimilation scheme has been coupled with the limited area atmospheric model RAMS, in order to improve in the latter the accuracy of the energy budget at the surface. The coupling has been realized replacing the assimilation scheme products, in terms of surface turbulent fluxes and temperature and humidity states during the meteorological simulation. Comparisons between meteorological model results with and without coupling with the assimilation scheme are discussed, both in terms of reconstruction of surface variables and of vertical characterization of the lower atmosphere. In particular, the effects of the coupling on the moisture feedback between surface and atmosphere are considered and estimates of the precipitation recycling ratio are provided. The results of the coupling experiment showed improvements in the reconstruction of the surface states by the atmospheric model and considerable influence on the atmospheric dynamics.

A new present-day temperature parameterization for Greenland

AbstractNear-surface air temperature (2 m) over the Greenland ice sheet (GrIS) is parameterized using data from automatic weather stations located on land and on the ice sheet. The parameterization is expressed in terms of mean annual temperatures and mean July temperatures, both depending linearly on altitude, latitude and longitude. The temperature parameterization is compared to a previous study and is shown to be in better agreement with observations. The temperature parameterization is tested in a positive degree-day model to simulate the present (1996–2006) mean melt area extent of the GrIS. The model accounts for firn warming, rainfall and refreezing of meltwater, with different degree-day factors for ice and snow under warm and cold climate conditions. The simulated melt area extent is found to have reasonable agreement with satellite-derived observations.

Midlatitude Cyclone Compositing to Constrain Climate Model Behavior Using Satellite Observations

Abstract Identical composite analysis of midlatitude cyclones over oceanic regions has been carried out on both output from the NCAR Community Atmosphere Model, version 3 (CAM3) and multisensor satellite data. By focusing on mean fields associated with a single phenomenon, the ability of the CAM3 to reproduce realistic midlatitude cyclones is critically appraised. A number of perturbations to the control model were tested against observations, including a candidate new microphysics package for the CAM. The new microphysics removes the temperature-dependent phase determination of the old scheme and introduces representations of microphysical processes to convert from one phase to another and from cloud to precipitation species. By subsampling composite cyclones based on systemwide mean strength (mean wind speed) and systemwide mean moisture the authors believe they are able to make meaningful like-with-like comparisons between observations and model output. All variations of the CAM tested overestimate the optical thickness of high-topped clouds in regions of precipitation. Over a system as a whole, the model can both over- and underestimate total high-topped cloud amounts. However, systemwide mean rainfall rates and composite structure appear to be in broad agreement with satellite estimates. When cyclone strength is taken into account, changes in moisture and rainfall rates from both satellite-derived observations and model output as a function of changes in sea surface temperature are in accordance with the Clausius–Clapeyron equation. The authors find that the proposed new microphysics package shows improvement to composite liquid water path fields and cloud amounts.

Diatoms and their influence on the biologically mediated uptake of atmospheric CO<sub>2</sub> in the Arabian Sea upwelling system

Abstract. Sediment trap experiments have been carried out in order to study processes controlling shifts from diatom to non-diatom dominated systems in the western Arabian Sea. One of our major problems was to link sediment trap records to surface ocean processes. Satellite-derived observations on upper ocean parameters were helpful to reduce this problem in the past and gain a new quality by combining it with results obtained during the Joint Global Ocean Flux Study (JGOFS) in the Arabian Sea. The new results imply that intense grazing can decline or impede the development of large diatom blooms in a silicon-enriched near shore upwelling system off Oman. In the open western Arabian Sea diatom blooms recover within the offshore advecting upwelled water and lead to peak organic fluxes into the deep sea but only during the later phase of the upwelling season. During onset of the upwelling season grazing favoured by eolian iron inputs causing the formation of thinner diatom shells seems to prevent the development of a large diatom bloom within the silicon-enriched offshore advecting upwelled water. An increased relevance of diatoms and diatom-grazing copepods in the planktonic community as well as oligotrophic conditions seem to raise the ratio between organic carbon formation and calcium carbonate carbon precipitation (rain ratio) in the surface water. The decomposition of organic matter in the water column reduces the rain ratio within in the sinking matter especially in the oligotrophic region dominated by cyanobacteria and reduces also the variation of the carbon to nutrient uptake ratios seen in the surface water.

Simulating the Transition from Drizzling Marine Stratocumulus to Boundary Layer Cumulus with a Mesoscale Model

A case of coastal California summer season boundary layer cloud has been simulated with the U.S. Navy Coupled Ocean‐Atmosphere Mesoscale Prediction System and the results analyzed in the context of consistency with conclusions derived from large eddy simulation‐based (LES) studies. Results show a pronounced diurnal cycle and fair agreement with satellite-derived observations of liquid water path. When drizzle processes are included, a significant degree of mesoscale organization emerges in the form of cloud bands, accompanied by a transition from a well-mixed boundary layer topped by unbroken stratocumulus cloud into a more potentially unstable, convective boundary layer regime. The transition and the subsequent development of mesoscale variability is analogous to the drizzle-induced cloud breakup produced in large eddy simulation studies. The dynamics of the pure stratocumulus cloud are dictated by the model’s subgrid parameterization, while the more convective regime exhibits appreciable vertical velocities characteristic of an ensemble of cumulus updrafts. The existence of convective updrafts is tied to a weak drizzle-induced decoupling of the cloud and subcloud layer, after which air of higher equivalent potential temperature (ue) can pool at the surface. Some similarities to the propagation of deep convection are also noted.

The geomorphology of planetary calderas

Satellite-derived observations of the geomorphology of calderas on Earth, Mars and Venus can be used to learn more about shield volcanoes. Examples of terrestrial basaltic volcanoes from the Galapagos Islands, Hawaii, and the Comoro Islands show how these volcanoes contrast with examples found on Mars and Venus. Caldera structure, degree of infilling, and the location of vents on the flanks are used to interpret each volcano's recent history. The geometry of the caldera floor can be used to infer some of the characteristics of the magma storage system, and the orientation of the deep magma conduits. The formation of benches within the caldera and the effects of the caldera on the distribution of flank eruptions are considered, and it is evident that most calderas on the planets are/were dynamic features. Presently, deep calderas, with evidence of overflowing lavas and ponded lavas high in the caldera wall, show that these calderas were once shallow. Similarly, shallow calderas filled with ponded lavas are evidence that they were once deeper. It is probably a mistake, therefore, to place great significance on caldera depth with regard to the position, shape, or size of subsurface plumbing.

The Atmospheric Water Vapor Cycle in South America and theTropospheric Circulation

The main characteristics of the atmospheric water vapor cycle over the South American continent and the adjacent oceans are investigated using the 22-yr period, from 1976 to 1997, of the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) 40-Year Reanalysis Project database. Precipitation rate and water vapor content fields obtained from this dataset are compared over the region with newly available observed datasets, which combine ground-based and satellite-derived observations. The temporal variation and spatial distribution of the atmospheric water vapor balance equation terms (precipitation rate, evaporation rate, and water vapor flux convergence) are examined with regard to their consistency and relative importance. The net effect of the atmospheric water vapor transport, represented in the last term of the balance equation, is decomposed into the horizontal and vertical convergence terms. The analysis of the latter highlights those regions where the topographic uplift makes a substantial contribution to the total precipitation rate. The former term is further decomposed into the stationary and transient water vapor flux contributions. The comparison of these terms with relevant characteristics of the large-scale tropospheric circulation provides a better understanding of the different precipitation regimes in South America. The mean annual balance satisfactorily closes over most of the oceanic regions. However, important imbalances found in the vicinity of high topographic features, such as in the central Andes, are attributed to large errors in the local computation of the atmospheric water vapor flux. The current results corroborate previous findings on the role of the stationary water vapor flux convergence in the spatial distribution and seasonal variation of the rainfall rate in tropical and subtropical latitudes and extend over the less-investigated continental midlatitudes. The magnitude of the transient water vapor flux convergence is, in general, lower than that of the stationary flux. Nonetheless, in some oceanic and continental regions, they are comparable and seem to be dynamically linked. This interaction, which can be explained by means of a simple transport-gradient model of the transient water vapor flux, could help to clarify the observed seasonal and interannual variability of the rainfall rate in the humid-to-dry transition zone in the southern part of the continent.

Sea surface temperature signals from satellites—An update

Polar satellite‐derived observations of sea surface temperatures (SSTs) have been used routinely since 1982 to provide a complete monitoring of our planet, covering all comers of the oceans (unless covered by clouds) twice each day. In 1992, an initial glimpse was published (Strong, 1992) of some tendencies that had been observed during the 1980s. Now that seven additional years of NOAA satellite SST data have become available, the earlier time‐series (Strong, 1992) has been up‐dated, hi this analysis of the global nighttime SSTs, care was taken to avoid the anomalous conditions found during the 1982–83 El Chichón aerosols, 1991–92 Mt. Pinatubo aerosols, and the strong El Niño of 1997‐98. Evidence of warming is found to be present throughout much of the Tropics and in the mid‐latitude Northern Hemisphere. Estimates from the Southern Hemisphere, while strongly indicative of compensatory cooling in the region, are found to be not as reliable.

A regional estimate of convective transport of CO from biomass burning

We present a regional‐scale estimate of the fraction of biomass burning emissions that are transported to the free troposphere by deep convection. The focus is on CO and the study region is a part of Brazil that underwent intensive deforestation in the 1980's. The method of calculation is stepwise, scaling up from a prototype convective event, the dynamics of which are well‐characterized, to the vertical mass flux of carbon monoxide over the region. Satellite‐derived observations of the area extent of pollution from biomass burning and convective cloud cover are used in the scaling.Given uncertainties in CO emissions from biomass burning and the representativeness of the protoype event, it is estimated that 10–40 percent of CO emissions from the burning region may be rapidly transported to the free troposphere over the burning region. These relatively fresh emissions will produce O3 efficiently in the free troposphere where O3 has a longer lifetime than in the boundary layer.