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Abstract In this study, we investigate the air temperature response to land-use and land-cover change (LULCC; cropland expansion and deforestation) using subgrid land model output generated by a set of CMIP6 model simulations. Our study is motivated by the fact that ongoing land-use activities are occurring at local scales, typically significantly smaller than the resolvable scale of a grid cell in Earth system models. It aims to explore the potential for a multimodel approach to better characterize LULCC local climatic effects. On an annual scale, the CMIP6 models are in general agreement that croplands are warmer than primary and secondary land (psl; mainly forests, grasslands, and bare ground) in the tropics and cooler in the mid–high latitudes, except for one model. The transition from warming to cooling occurs at approximately 40°N. Although the surface heating potential, which combines albedo and latent heat flux effects, can explain reasonably well the zonal mean latitudinal subgrid temperature variations between crop and psl tiles in the historical simulations, it does not provide a good prediction on subgrid temperature for other land tile configurations (crop vs forest; grass vs forest) under Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) forcing scenarios. A subset of simulations with the CESM2 model reveals that latitudinal subgrid temperature variation is positively related to variation in net surface shortwave radiation and negatively related to variation in the surface energy redistribution factor, with a dominant role from the latter south of 30°N. We suggest that this emergent relationship can be used to benchmark the performance of land surface parameterizations and for prediction of local temperature response to LULCC. 

The timeliness of monitoring is essential to algal bloom management. However, acquiring algal bio-indicators can be time-consuming and laborious, and bloom biomass data often contain a large proportion of extreme values limiting the predictive models. Therefore, to predict algal blooms from readily water quality parameters (i.e. dissolved oxygen, pH, etc), and to provide a novel solution to the modeling challenges raised by the extremely distributed biomass data, a Bayesian scale-mixture of skew-normal (SMSN) model was proposed. In this study, our SMSN model accurately predicted over-dispersed biomass variations with skewed distributions in both rivers and lakes (in-sample and out-of-sample predictionR²ranged from 0.533 to 0.706 and 0.412 to 0.742, respectively). Moreover, we successfully achieve a probabilistic assessment of algal blooms with the Bayesian framework (accuracy >0.77 and macro-F₁score >0.72), which robustly decreased the classic point-prediction-based inaccuracy by up to 34%. This work presented a promising Bayesian SMSN modeling technique, allowing for real-time prediction of algal biomass variations andin-situprobabilistic assessment of algal bloom.

 

Abstract. For the radiative impact of individual climate forcings,most previous studies focused on the global mean values at the top of theatmosphere (TOA), and less attention has been paid to surface processes,especially for black carbon (BC) aerosols. In this study, the surface radiativeresponses to five different forcing agents were analyzed by using idealizedmodel simulations. Our analyses reveal that for greenhouse gases, solarirradiance, and scattering aerosols, the surface temperature changes aremainly dictated by the changes of surface radiative heating, but for BC,surface energy redistribution between different components plays a morecrucial role. Globally, when a unit BC forcing is imposed at TOA, the netshortwave radiation at the surface decreases by -5.87±0.67 W m−2 (W m−2)−1 (averaged over global land without Antarctica), which ispartially offset by increased downward longwave radiation (2.32±0.38 W m−2 (W m−2)−1 from the warmer atmosphere, causing a netdecrease in the incoming downward surface radiation of -3.56±0.60 W m−2 (W m−2)−1. Despite a reduction in the downward radiationenergy, the surface air temperature still increases by 0.25±0.08 Kbecause of less efficient energy dissipation, manifested by reduced surfacesensible (-2.88±0.43 W m−2 (W m−2)−1) and latent heat flux(-1.54±0.27 W m−2 (W m−2)−1), as well as a decrease inBowen ratio (-0.20±0.07 (W m−2)−1). Such reductions of turbulentfluxes can be largely explained by enhanced air stability (0.07±0.02 K (W m−2)−1), measured as the difference of the potential temperaturebetween 925 hPa and surface, and reduced surface wind speed (-0.05±0.01 m s−1 (W m−2)−1). The enhanced stability is due to the fasteratmospheric warming relative to the surface, whereas the reduced wind speedcan be partially explained by enhanced stability and reduced Equator-to-poleatmospheric temperature gradient. These rapid adjustments under BC forcingoccur in the lower atmosphere and propagate downward to influence thesurface energy redistribution and thus surface temperature response, whichis not observed under greenhouse gases or scattering aerosols. Our studyprovides new insights into the impact of absorbing aerosols on surfaceenergy balance and surface temperature response.