Search

The downwelling longwave radiation at the surface (DLR) is a key component of the Earth's surface energy budget. We present a novel set of equations that explicitly account for both clouds and the CO2 $\mathrm{C}{\mathrm{O}}_{\mathrm{2}}$ effect to calculate the all‐sky DLR. This paper first extends the clear‐sky DLR model of Shakespeare and Roderick (2021, https://doi.org/10.1002/qj.4176) to include temperature inversions and clouds. We parameterize relevant cloud properties through theoretical and empirical considerations to formulate an all‐sky model. Our model is more accurate than existing methods (reduces Root Mean Squared Error by 2.1–8.7 W/m2 $\mathrm{W}/{\mathrm{m}}^{\mathrm{2}}$ and 1.2–10.1 W/m2 $\mathrm{W}/{\mathrm{m}}^{\mathrm{2}}$ compared to ERA5 reanalysis and in‐situ data respectively), and provides a strong physical basis for the estimation of the downwelling longwave from near‐surface information. We highlight the important role of CO2 $\mathrm{C}{\mathrm{O}}_{\mathrm{2}}$ dependence by showing our model largely captures the change in atmospheric emissivity purely due to CO2 $\mathrm{C}{\mathrm{O}}_{\mathrm{2}}$ (i.e., the instantaneous radiative forcing) in CMIP6 models. Plain Language Summary: The downwelling longwave radiation (DLR) at the surface is a key component of the energy balance at the Earth's surface. Understanding how the DLR will change under future climate conditions is vital. For the first time, we explicitly write a set of equations to calculate the DLR that sufficiently account for the impact of CO2 $\mathrm{C}{\mathrm{O}}_{\mathrm{2}}$ and clouds simultaneously. Our model is more accurate than existing methods, and provides a much stronger physical basis for the estimation of the downwelling longwave from near‐surface information. In this paper, we extend an existing method for estimating the DLR under clear‐sky conditions (i.e., no clouds) to operate under all sky conditions. This method can be used to inform models where the DLR is needed, but only basic observations are available. Key Points: Downwelling longwave radiation (DLR) is a poorly estimated element of the surface energy budget by existing analytical modelsExplicitly accounting for temperature inversions and cloud emissivities improves the accuracy of DLR estimationConsidering the radiative forcing from increasing CO2 $\mathrm{C}{\mathrm{O}}_{\mathrm{2}}$ is necessary to produce unbiased future estimates of DLR [ABSTRACT FROM AUTHOR]

Observations and models show that near‐surface relative humidity is nearly constant at ∼80% over the ocean in the current climate, and almost invariant in the global mean in projected future climates. Here, this behavior is investigated through the development of a simple theoretical model for near‐surface relative humidity by considering the moisture balance above a uniform ocean surface. The relative humidity is predicted to depend on only the near‐surface wind speed, air‐surface temperature difference, surface wetness and large‐scale moisture convergence. Although developed in the context of moist over‐ocean convection, the theory is able to determine the relative humidity in a suite of idealized simulations over both wet and dry surfaces with a root‐mean‐square error of less than 3%. The theory also predicts the climatology of relative humidity over the ocean with a root‐mean‐square error of less than 3%. The theory thus provides a theoretical basis for investigating changes in relative humidity over the ocean, water vapor feedbacks and the water cycle in current and future climates. Plain Language Summary: Relative humidity is the water content of air relative to its saturation value. Observations and climate models show that global mean near‐surface relative humidity is almost invariant in a changing climate, an observation which underpins the enhancement of the water cycle with increasing global mean temperatures and surface radiative feedbacks. Furthermore, relative humidity over the ocean, whether in the tropics or polar regions, takes a near uniform value of ∼80%. However, a theoretical basis for this remarkable invariance of relative humidity has not been previously established. Here we show that near‐surface relative humidity is controlled by the geometry of moist convection over the ocean surface. Its value is set by a non‐dimensional geometric constant and is independent of the absolute air temperature, with weak dependence on near‐surface wind speeds, air‐surface temperature difference and large‐scale moisture convergence. Hence, the over ocean relative humidity is largely climate and latitude invariant. Key Points: Convection above the ocean surface exhibits a characteristic geometry that controls the value of near‐surface relative humidityA quadratic equation is derived to predict near‐surface relative humidity in terms of known surface properties and a geometric constantThe equation predicts the relative humidity in idealized simulations and ocean observations with less than 3% error [ABSTRACT FROM AUTHOR]

Drought is a major natural hazard that can have devastating impacts on regional agriculture, water resources and the environment, with far-reaching impacts in an increasingly globalized world (11). The perceived [...], Drought is expected to increase in frequency and severity in the future as a result of climate change, mainly as a consequence of decreases in regional precipitation but also because of increasing evaporation driven by global warming (1-3). Previous assessments of historic changes in drought over the late twentieth and early twenty-first centuries indicate that this may already be happening globally. In particular, calculations of the Palmer Drought Severity Index (PDSI) show a decrease in moisture globally since the 1970s with a commensurate increase in the area in drought that is attributed, in part, to global warming (4,5). The simplicity of the PDSI, which is calculated from a simple water-balance model forced by monthly precipitation and temperature data, makes it an attractive tool in large-scale drought assessments, but may give biased results in the context of climate change (6). Here we show that the previously reported increase in global drought is overestimated because the PDSI uses a simplified model of potential evaporation (7) that responds only to changes in temperature and thus responds incorrectly to global warming in recent decades. More realistic calculations, based on the underlying physical principles (8) that take into account changes in available energy, humidity and wind speed, suggest that there has been little change in drought over the past 60 years. The results have implications for how we interpret the impact of global warming on the hydrological cycle and its extremes, and may help to explain why palaeoclimate drought reconstructions based on tree-ring data diverge from the PDSI-based drought record in recent years (9,10).