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Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns. Our results show that for the period 1979 to 2020, variation in the atmospheric circulation explains, on average, only 32% of the observed VPD trend of 0.48 ± 0.25 hPa/decade (95% CI) over the WUS during the warm season (May to September). The remaining 68% of the upward VPD trend is likely due to anthropogenic warming. The ensemble simulations of climate models participating in the sixth phase of the Coupled Model Intercomparison Project suggest that anthropogenic forcing explains an even larger fraction of the observed VPD trend (88%) for the same period and region. These models and observational estimates likely provide a lower and an upper bound on the true impact of anthropogenic warming on the VPD trend over the WUS. During August 2020, when the August Complex "Gigafire" occurred in the WUS, anthropogenic warming likely explains 50% of the unprecedented high VPD anomalies.

The recent severe and frequent [PM.sub.2.5] (i.e., fine particles smaller than 2.5[micro]m) pollution in China has aroused unprecedented public concern. The first two years of [PM.sub.2.5] measurements in China are [...]

Most evapotranspiration over land occurs through vegetation. The fraction of net radiation balanced by evapotranspiration depends on stomatal controls. Stomates transpire water for the leaf to assimilate carbon, depending on the canopy carbon demand, and on root uptake, if it is limiting. Canopy carbon demand in turn depends on the balancing between visible photon-driven and enzyme-driven steps in the leaf carbon physiology. The enzyme-driven component is here represented by a Rubisco-related nitrogen reservoir that interacts with plant–soil nitrogen cycling and other components of a climate model. Previous canopy carbon models included in GCMs have assumed either fixed leaf nitrogen, that is, prescribed photosynthetic capacities, or an optimization between leaf nitrogen and light levels so that in either case stomatal conductance varied only with light levels and temperature.A nitrogen model is coupled to a previously derived but here modified carbon model and includes, besides the enzyme reservoir, additional plant stores for leaf structure and roots. It also includes organic and mineral reservoirs in the soil; the latter are generated, exchanged, and lost by biological fixation, deposition and fertilization, mineralization, nitrification, root uptake, denitrification, and leaching. The root nutrient uptake model is a novel and simple, but rigorous, treatment of soil transport and root physiological uptake. The other soil components are largely derived from previously published parameterizations and global budget constraints.The feasibility of applying the derived biogeochemical cycling model to climate model calculations of evapotranspiration is demonstrated through its incorporation in the Biosphere–Atmosphere Transfer Scheme land model and a 17-yr Atmospheric Model Inter comparison Project II integration with the NCAR CCM3 GCM. The derived global budgets show land net primary production (NPP), fine root carbon, and various aspects of the nitrogen cycling are reasonably consistent with past studies. Time series for monthly statistics averaged over model grid points for the Amazon evergreen forest and lower Colorado basin demonstrate the coupled interannual variability of modeled precipitation, evapotranspiration, NPP, and canopy Rubisco enzymes.

Sixteen land-surface schemes participating in the project for the Intercomparison of Land-surface Schemes (PILPS) Phase 2(c) were run using 10 years (1979-1988) of forcing data for the Red-Arkansas River basins in the Southern Great Plains region of the United States. Forcing data (precipitation, incoming radiation and surface meteorology) and land-surface characteristics (soil and vegetation parameters) were provided to each of the participating schemes. Two groups of runs are presented. (1) Calibration-validation runs, using data from six small catchments distributed across the modeling domain. These runs were designed to test the ability of the schemes to transfer information about model parameters to other catchments and to the computational grid boxes. (2) Base-runs, using data for 1979-1988, designed to evaluate the ability of the schemes to reproduce measured energy and water fluxes over multiple seasonal cycles across a climatically diverse, continental-scale basin. All schemes completed the base-runs but five schemes chose not to calibrate. Observational data (from 1980-1986) including daily river flows and monthly basin total evaporation estimated through an atmospheric budget analysis, were used to evaluate model performance. In general, the results are consistent with earlier PILPS experiments in terms of differences among models in predicted water and energy fluxes. The mean annual net radiation varied between 80 and 105 W m-2 (excluding one model). The mean annual Bowen ratio varied from 0.52 to 1.73 (also excluding one model) as compared to the data-estimated value of 0.92. The run-off ratios varied from a low of 0.02 to a high of 0.41, as compared to an observed value of 0.15. In general, those schemes that did not calibrate performed worse, not only on the validation catchments, but also at the scale of the entire modeling domain. This suggests that further PILPS experiments on the value of calibration need to be carried out.

The energy components of sixteen Soil-Vegetation Atmospheric Transfer (SVAT) schemes were analyzed and intercompared using 10 years of surface meteorological and radiative forcing data from the Red-Arkansas River basin in the Southern Great Plains of the United States. Comparisons of simulated surface energy fluxes among models showed that the net radiation and surface temperature generally had the best agreement among the schemes. On an average (annual and monthly) basis, the estimated latent heat fluxes agreed (to within approximate estimation errors) with the latent heat fluxes derived from a radiosonde-based atmospheric budget method for slightly more than half of the schemes. The sensible heat fluxes had larger differences among the schemes than did the latent heat fluxes, and the model-simulated ground heat fluxes had large variations among the schemes. The spatial patterns of the model-computed net radiation and surface temperature were generally similar among the schemes, and appear reasonable and consistent with observations of related variables, such as surface air temperature. The spatial mean patterns of latent and sensible heat fluxes were less similar than for net radiation, and the spatial patterns of the ground heat flux vary greatly among the 16 schemes. Generally, there is less similarity among the models in the temporal (interannual) variability of surface fluxes and temperature than there is in the mean fields, even for schemes with similar mean fields.

The water-balance components of 16 Soil-Vegetation Atmospheric Transfer (SVAT) schemes were evaluated by comparing predicted and observed streamflow, predicted evapotranspiration and evapotranspiration inferred from an atmospheric moisture budget analysis, and soil moisture storage changes for a seven-year period (1980-1986) using data from the Red-Arkansas River basins of the Southern Great Plains of the USA. The evaluations support the following suggestions: (a) The mean annual runoff of all models follows, at least generally, the strong climatic East-West gradient of precipitation, although most models predict too much runoff in the dry part of the basin. (b) The mean monthly storage change tends to be underestimated, even though all models capture reasonably well the seasonality of the evapotranspiration. (c) The wide range of conceptualizations used for generation of surface and subsurface runoff strongly affect runoff generation on seasonal, and shorter, time scales. Model responses to summer precipitation ranged from almost no summer runoff (one model) to the (more common) situation of persistent overprediction of summer runoff, especially in the driest part of the basin. (d) All models tended to underpredict evapotranspiration in summer and overpredict in winter. (e) Model-derived mean seasonal cycles of changes in soil moisture storage are qualitatively similar to those inferred from observations, but most models do not predict the decrease in April soil moisture storage and the increase in October that is inferred from observations.