To accurately assess the impacts of human land use on the Earth system, information is needed on the current and historical patterns of land-use activities. Previous global studies have focused on developing reconstructions of the spatial patterns of agriculture. Here, we provide the first global gridded estimates of the underlying land conversions (land-use transitions), wood harvesting, and resulting secondary lands annually, for the period 1700-2000. Using data-based historical cases, our results suggest that 42-68% of the land surface was impacted by land-use activities (crop, pasture, wood harvest) during this period, some multiple times. Secondary land area increased 10-44 Â 10 6 km 2 ; about half of this was forested. Wood harvest and shifting cultivation generated 70-90% of the secondary land by 2000; permanent abandonment and relocation of agricultural land accounted for the rest. This study provides important new estimates of globally gridded land-use activities for studies attempting to assess the consequences of anthropogenic changes to the Earth's surface over time.
Carbon estimates from terrestrial ecosystem models are limited by large uncertainties in the current state of the land surface. Natural and anthropogenic disturbances have important and lasting influences on ecosystem structure and fluxes that can be difficult to detect or assess with conventional methods. In this study, we combined two recent advances in remote sensing and ecosystem modeling to improve model carbon stock and flux estimates at a tropical forest study site at La Selva, Costa Rica (10Њ25Ј N, 84Њ00Ј W). Airborne lidar remote sensing was used to measure spatial heterogeneity in the vertical structure of vegetation. The ecosystem demography model (ED) was used to estimate the consequences of this heterogeneity for regional estimates of carbon stocks and fluxes. Lidar data provided substantial constraints on model estimates of both carbon stocks and net carbon fluxes. Lidar-initialized ED estimates of aboveground biomass were within 1.2% of regression-based approaches, and corresponding model estimates of net carbon fluxes differed substantially from bracketing alternatives. The results of this study provide a promising illustration of the power of combining lidar data on vegetation height with a heightstructured ecosystem model. Extending these analyses to larger scales will require the development of regional and global lidar data sets, and the continued development and application of height structured ecosystem models.
SUMMARYA case of orographic precipitation in the Alps on 20 September 1999 was studied using several models, along with rain-gauge and radar data. The objective of the study is to describe the orographic transformation of an air mass, including multi-scale aspects. Several new and some conventional diagnostic quantities are estimated, including drying ratio, precipitation ef ciency, buoyancy work, condensed-water residence time, parcel changes in heat, moisture and altitude, and dominant space-and time-scales.For the case considered, the drying ratio was about 35%. Precipitation ef ciency values are ambiguous due to repeated ascent and descent over small-scale terrain. The sign of buoyancy work changed during the event, indicating a shift from stratiform orographic to weak convective clouds. Cloud-water residence times are different for the two mesoscale models (400 compared to 1000 s) due to different cloud-physical formulations. The two mesoscale models agree that the dominant spatial-scale of lifting and precipitation is about 10 km; smaller than the scale of the main Alpine massif. Trajectory analysis of air crossing the Alps casts doubt on the classic model of föhn. Few parcels exhibit classic pattern of moist ascent followed by dry descent. Parcels that gain latent heat descend only brie y, before rising into the middle troposphere. Parcels that descend along the lee slope, originate in the middle troposphere and gain little, or even lose, latent heat during the transit. As parcels seek their proper buoyancy level downstream, a surprising scrambling of the air mass occurs.Radar data con rm the model prediction that the rainfall eld is tightly controlled by local terrain on scales as small as 10 km, rather than the full 100 km cross-Alpine scale. A curious pulsing of the precipitation is seen, indicating either drifting moisture anomalies or weak convection.
During the summer of 2015, a number of large wildfires burned across Northern California in areas of localized topographic relief. Persistent valley smoke hindered fire‐fighting efforts, delayed helicopter operations, and exposed communities to extreme concentrations of particulate matter. It was hypothesized that smoke from the wildfires reduced the amount of incoming solar radiation reaching the ground, which resulted in near‐surface cooling, while smoke aerosols resulted in warming aloft. As a result of increased inversion‐like conditions, smoke from wildfires was trapped within mountain valleys adjacent to active wildfires. In this study, wildfire smoke‐induced inversion episodes across Northern California were examined using a modeling framework that couples an atmospheric, chemical, and fire spread model. Modeling results examined in this study indicate that wildfire smoke reduced incoming solar radiation during the afternoon, which lead to local surface cooling by up to 3 °C, which agrees with cooling observed at nearby surface stations. Direct heating from the fire itself did not significantly enhance atmospheric stability. However, midlevel warming (+0.5 °C) and pronounced surface cooling was observed in the smoke layer, indicating that smoke aerosols significantly enhanced atmospheric stability. A positive feedback associated with the presence of smoke was observed, where local smoke‐enhanced inversions inhibited the growth of the planetary boundary layer, and reduced surface winds, which resulted in smoke accumulation that further reduced near‐surface temperatures. This work suggests that the inclusion of fire‐smoke‐atmosphere feedback in a coupled modeling framework such as WRF‐SFIRE‐CHEM can forecast the dispersion of wildfire smoke and its radiative feedback, and potentially provide decision‐support for wildfire operations.
Abstract. The effect of Land Use Change and Forestry (LUCF) on terrestrial carbon fluxes can be regarded as a carbon credit or debit under the UNFCCC, but scientific uncertainty in the estimates for LUCF remains large. Here, we assess the LUCF estimates by examining a variety of models of different types with different land cover change maps in the 1990s. Annual carbon pools and their changes are separated into different components for separate geographical regions, while annual land cover change areas and carbon fluxes are disaggregated into different LUCF activities and the biospheric response due to CO 2 fertilization and climate change. We developed a consolidated estimate of the terrestrial carbon fluxes that combines book-keeping models with process-based biogeochemical models and inventory estimates and yields an estimate of the global terrestrial carbon flux that is within the uncertainty range developed in the IPCC 4th Assessment Report. We examined the USA and Brazil as case studies in order to assess the cause of differences from the UNFCCC reported carbon fluxes. Major differences in the litter and soil organic matter components are found for the USA. Differences in Brazil result from assumptions about the LUC for agricultural purposes. The effects of CO 2 fertilization and climate change also vary significantly in Brazil. Our consolidated estimate shows that the small Correspondence to: A. Ito (akinorii@jamstec.go.jp) sink in Latin America is within the uncertainty range from inverse models, but that the sink in the USA is significantly smaller than the inverse models estimates. Because there are different sources of errors at the country level, there is no easy reconciliation of different estimates of carbon fluxes at the global level. Clearly, further work is required to develop data sets for historical land cover change areas and models of biogeochemical changes for an accurate representation of carbon uptake or emissions due to LUC.
The degree to which Arctic cyclones locally affect sea ice cover during the melt season is unclear. To address this, we use the ERA‐5 reanalysis to statistically analyze how surface energy fluxes and wind forcing from Arctic cyclones in the marginal ice zone between May and August (1999–2018) locally affect sea ice extent on 1–10 day time scales. In May and June, cyclones decelerate the local seasonal loss of sea ice extent compared to when no cyclone is present, which we hypothesize is due to cyclones reducing net shortwave radiative fluxes at the surface. By July and August, cyclones no longer decelerate the seasonal loss of sea ice extent, despite still reducing the net surface energy flux. Surface wind forcing across the ice edge only explains up to 13.5% of the variance in local sea ice extent in August, suggesting that processes other than wind‐induced drift and atmospheric energy fluxes drive late‐summer sea ice extent variability.
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