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In this paper we coupled a crop growth model to the Weather Research and Forecasting model with its land surface model Noah‐MP and demonstrated the influence of the weather driven crop growth on land‐atmosphere (L‐A) feedback. An impact study was performed at the convection permitting scale of 3 km over Germany. While the leaf area index (LAI) in the control simulation was the same for all cropland grid cells, the inclusion of the crop growth model resulted in heterogeneous crop development with higher LAI and stronger seasonality. For the analyses of L‐A coupling, a two‐legged metric was applied based on soil moisture, latent heat flux and convective available potential energy. Weak atmospheric coupling is enhanced by the crop model, the terrestrial coupling determines the regions with the L‐A feedback. The inclusion of the crop model turns regions with no L‐A feedback on this path into regions with strong positive coupling. The number of non‐atmospherically controlled days between April and August is increased by 10–15 days in more than 50% of Germany. Our work shows that this impact results in a reduction of both cold bias and warm biases and thus improves the metrics of distributed added value of the monthly mean temperatures. The study confirms that the simulation of the weather driven annual phenological development of croplands for the regional climate simulations in mid‐latitudes is crucial due to the L‐A feedback processes and the currently observed and expected future change in phenological phases. Key Points: Coupling a crop growth model with the Weather and Research Forecasting model significantly improves the simulation of the leaf area indexLand‐atmosphere coupling strength is enhanced by weather dependent crop growth simulationThe distributed added value metric shows a reduction in temperature biases of up to 80% in croplands throughout the season in Germany [ABSTRACT FROM AUTHOR]

We present the new Atmospheric Raman Temperature and Humidity Sounder (ARTHUS). We demonstrate that ARTHUS measurements resolve (1) the strength of the inversion layer at the planetary boundary layer top, (2) elevated lids in the free troposphere during daytime and nighttime, and (3) turbulent fluctuations in water vapor and temperature, simultaneously, also during daytime. Very stable and reliable performance was demonstrably achieved during more than 2,500 hr of operations time experiencing a huge variety of weather conditions. ARTHUS provides temperature profiles with resolutions of 10–60 s and 7.5–100 m vertically in the lower free troposphere. During daytime, the statistical uncertainty of the water vapor mixing ratio is <2 % in the lower troposphere for resolutions of 5 min and 100 m. Temperature statistical uncertainty is <0.5 K even up to the middle troposphere. ARTHUS fulfills the stringent WMO breakthrough requirements on nowcasting and very short range forecasting. Plain Language Summary: The observation of atmospheric moisture and temperature profiles is essential for the understanding and prediction of earth system processes. These are fundamental components of the global and regional energy and water cycles; they determine the radiative transfer through the atmosphere and are critical for the cloud formation and precipitation. Also, it is expected that the assimilation of high‐quality, lower tropospheric WV and T profiles will result in a considerable improvement of the skill of weather forecast models particularly with respect to extreme events. Here we present the Atmospheric Raman Temperature and Humidity Sounder, an exceptional tool for observations in the atmospheric boundary layer during daytime and nighttime with a very short latency. This performance serves very well the next generation of very fast rapid‐update‐cycle data assimilation systems for nowcasting and short‐range weather forecasting. Ground‐based stations and networks can be set up or extended for climate monitoring, verification of weather, climate and earth system models, and data assimilation for improving weather forecasts. Key Points: Fulfills World Meteorological Organization breakthrough requirements for nowcasting/very short range forecasting in the lower troposphereResolves strength of the inversion layer at the planetary boundary layer top and elevated lids above during daytime and nighttimeProvides statistics on turbulent fluctuations in water vapor and temperature simultaneously in the lower troposphere [ABSTRACT FROM AUTHOR]

In previous work, the similarity relationship for the water vapor variance in the interfacial layer (IL) at the top of the convective boundary layer (CBL) was proposed to be proportional to the convective velocity scale and the gradients of the water vapor mixing ratio and the Brunt‐Vaisala frequency in the entrainment zone. In the presence of wind shear in the IL, the similarity relationship was hypothesized to also include a dependence on the gradient Richardson number. Simultaneous measurements of the surface buoyancy flux, wind‐shear profiles from a radar wind profiler, water vapor mixing ratio and temperature measurements and their gradients from a Raman lidar provide a unique opportunity to thoroughly examine the function used in defining the variance and validate it. These observations were made over the Atmospheric Radiation Measurement Southern Great Plains site. We identified 19 cases from 2016 during which the CBL was quasi‐stationary and well mixed for at least 2 hr in the afternoon. Furthermore, we simulated the CBL using a large‐eddy simulation (LES) model for these cases and derived the water vapor variance and other profiles to test the similarity function. Utilizing this unique combination of observations and LES, we demonstrate that the water vapor variance in the IL has little‐to‐no dependence on wind shear. Furthermore, we demonstrate that the predicted variance using the original similarity function matches the observed and LES‐modeled variance very well, with linear correlations between the two variances of 0.82 and 0.95, respectively. Plain Language Summary: Numerical weather prediction and global circulation models need to be able to predict the variance in water vapor in the atmosphere, as this is an important signature of turbulent mixing. However, the variance is something that is not directly resolved by the model and must be approximated using variables that the models actually resolve such as gradients in water vapor, temperature, and wind. This study evaluates a commonly used approximation approach, illustrates its shortcomings, and suggests how the approximation can be improved. Key Points: A similarity relationship is used to predict water vapor variance in the interfacial layer from other variablesWind shear is shown to be unimportant for the prediction of water vapor variance in the interfacial layerThere is very high correlation between the true and predicted variance in both the observations and LES data [ABSTRACT FROM AUTHOR]

Abstract: On 21 August 2017, a solar eclipse occurred over the continental United States resulting in a rapid reduction and subsequent increase of solar radiation over a large region of the country. The eclipse's effect on the land‐atmosphere system is documented in unprecedented detail using a unique array of sensors deployed at three sites in north‐central Oklahoma. The observations showed that turbulent fluxes of heat and momentum at the surface responded quickly to the change in solar radiation. The decrease in the sensible heat flux resulted in a decrease in the air temperature below 200 m, and a large decrease in turbulent motions throughout the boundary layer. Furthermore, the turbulent mixing in the boundary layer lagged behind the change in the surface fluxes, and this lag depended on the height above the surface. The turbulent motions increased and the convective boundary layer was reestablished as the sensible heat flux recovered. [ABSTRACT FROM AUTHOR]