Reply on RC2

Two physically-models of solar radiation transmission and of a steady-state slope energy budget have been coupled. Using climatic observational inputs, averaged in 10-deg latitude bands, a systematic examination was made of changing surface temperatures and differences between surface and air temperatures as functions of varying slope angles (0 to 90 deg) and orientations (south-, west-, and north-facing). Along a latitudinal transect of the east coast of the Americas (northern hemisphere), two contrasting landscapes were examined: barren and grassy. No simple relationship was discovered among the factors regarding shortwave and longwave radiative absorption, components of the energy budget, and surface temperature trends, yet the response of temperatures on a latitudinal basis was systematic and orderly. Characteristically, a great diversity existed among surface temperatures of different slopes and orientations at any particular latitude. Such diversity was accentuated in the higher latitudes. The findings were assumed general enough to encompass most of the possible contrasts encountered in a real-world north-south transect.

Convection and subsequent precipitation induced by the sea breeze circulations are often observed in the Florida peninsula during summer. In this study, the mechanisms of initiation and maintenance of the convective clouds and precipitation are investigated. A fully-compressible fine resolution non-hydrostatic mesoscale numerical model is used in this study. Surface energy and moisture budget were included in this model to simulate the diurnal cycle of ground surface temperature and wetness. The model also has a sophisticated boundary layer and explicit cloud physics. A sounding obtained from Orlando, Florida at 1110 UTC 17 July 1991 as part of the Convection and Precipitation Electrification (CaPE) experiment is used for initialization. The initial data for the model is kept in geostrophic and thermal wind balance. Several sensitivity tests were conducted to investigate the effects of different treatments of ground surface moisture and temperature on the model forecast of the convection and precipitation induced by the sea breeze circulations. The simulations agree reasonably well with the observations when both surface energy and moisture budget were included in the model to predict ground surface temperature and wetness. The surface moisture has a significant impact on the formation, strength, sustenance, and the location of convection and precipitation induced by the sea breezes.

Aerosols are known to exert a powerful influence on the Indian summer monsoon, reducing precipitation from onset through demise. We analyze model simulations aimed at detection and attribution to compare and contrast the processes that affect the energy budget and water cycle in the presence of aerosols to those associated with land-use/land-cover change (LULCC) over the Indian subcontinent. We find that the response of the water cycle to these external forcings is remarkably similar: precipitation decreases in the presence of either aerosols or LULCC. We also find that this occurs despite opposite responses in the surface energy budget, manifest in surface temperature: aerosols cool the continent, while LULCC warms it. Consequently, the temperature contrast set up by the difference in thermal inertia between land and ocean at peak insolation is weakened in the aerosol case, but it is strengthened in the LULCC case. These results therefore support the perspective that has forcefully emerged in tropical climate dynamics in the past couple decades that the temperature contrast between land and ocean alone is not sufficient to explain variation in monsoon rains. In line with this perspective, we find that viewing humidity as an expression of energy on par with temperature, that is, considering the moist static energy contrast, is critical to explaining outcome. In the simulations analyzed here, the presence of either aerosols or LULCC coherently reduces moist static energy over land, weakening the contrast between land and ocean, and results in reduced precipitation, confirming the monsoon’s sensitivity to external forcing.

HighlightsEvaporation from clear water, manure, and separated liquid manure was 4.6 mm d-1 on average.Straw, foam, geotextile, and roof covers decreased evaporation by 54%, 53%, 31%, and 21%, respectively.Albedo was highest for floating foam covers and lowest for metal roof covers.Straw, foam, and geotextile increased manure temperature compared to uncovered manure. ABSTRACT. Evaporation is a key component of the surface energy budget of liquid manure. Models rely on accurate energy budgets to predict manure temperature, which in turn is used to model temperature-dependent greenhouse gas emissions from liquid manure storages. Due to lack of data, it has been assumed that liquid manure has similar evaporative properties to water; however, this assumption may be inaccurate. Many factors, including manure crusting, covers, and turbidity, are all likely to affect the surface energy budget and the evaporation rate. This experiment investigated the differences in evaporation between eight treatments, including water, dyed water, raw and separated liquid manure, and four commonly used covers (straw, geotextile, foam, and roof), by measuring weekly evaporation. Albedo, surface temperatures, and internal temperatures were also measured to determine treatment effects. Over the 10-week study, no significant difference was found between the evaporation rates of water, raw manure, and separated liquid manure, with an average rate of 4.6 mm d-1. Notably, the raw manure did not form a consistent surface crust, which may explain the similarities in evaporation rates in this study and is unlikely to represent manure with a crust. Overall, covers significantly decreased evaporative losses by between 21% and 54% compared to uncovered raw manure. Average evaporation rates of the covered treatments were 1.9 mm d-1 for straw cover, 2.0 mm d-1 for foam cover, 2.9 mm d-1 for geotextile cover, and 3.4 mm d-1 under a roof cover. Similarities between each treatment and water as well as between the four covered treatments and the uncovered raw manure were found using linear regression on weekly evaporation. Generally, the uncovered treatments were more similar and could be predicted (high R2) by multiple linear regression with environmental variables, while the covered treatments differed more and were not as well predicted (lower R2). Results from this study can help adjust evaporation rates in biophysical models to improve estimates of manure temperature, tank holding capacity, and emission predictions. Keywords: Evaporation, Dairy manure, Liquid manure, Manure covers, Manure management.

In mountainous surfaces, land surface temperature (LST) plays a vital role in surface energy budget and vegetation–soil ecosystems. Despite advancements in retrieving LST from thermal infrared measurements at various spatial and temporal scales, accurately estimating LST for complex terrain remains challenging. This challenge arises from the conflict between the topographic effect and the assumption of flatten surface in many existing studies. In the absence of a simple and practical model for the topographic effect on the directional anisotropies of LST (LSTDA) over mountainous areas, the equivalent slope method is introduced to bridge the gap between studies conducted on flat surfaces and complex terrain. The proposed thermal equivalent slope kernel-driven (TESKD) model is validated using measurements and simulations from an unmanned aerial vehicle (UAV) system and a 3-dimensional raytracing model, respectively. Results indicate the following: (a) Under varying topographic conditions, vegetation cover, and solar zenith angles, there is a significant impact of topography on LSTDA. The average effect is greater than 0.5 K and can reach up to 1.5 K at the higher solar zenith angle (50°). (b) Based on UAV data, TESKD provides a better explanation and fitting effect for LSTDA in 3 typical mountainous surfaces including valley, peak, and solo-slope, with an average root mean square error (RMSE) of 0.27 K and an average coefficient of determinations of 0.628 of the 3 conditions, compared to a flat model (0.35 K and 0.335). (c) Based on simulations, TESKD exhibits more than a 30% improvement in accuracy, and for sparsely vegetated surfaces, the difference in RMSE can be up to 0.8 K when considering the topographic effect compared to not considering it. The new model can help to understand the radiative transfer process in heterogeneous mountainous surfaces and serves as a valuable tool for studies associated with water and carbon cycles.

Earth's Energy budget is a major force that drives global climate. The long-term pattern of land surface energy budget with pronounced biophysical effects on climate was normally ignored at a regional scale, particularly in Pakistan. In this paper, the land surface energy budget from 2001 to 2018 was estimated and analyzed from Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud and the Earth's Radiant Energy System (CERES) observations over three geographical regions (Northern highlands, Indus plains and Baluchistan plateau) in Pakistan. Biophysical and energy budget parameters such as Land Surface Temperature (LST), albedo, emissivity, and Normalized Difference Vegetation Index (NDVI) were obtained from MODIS, while the downward shortwave solar and longwave thermal radiation were obtained from CERES satellite data. Spatiotemporal trends of three energy budget parameters: net radiation, latent heat flux and sensible heat flux, and three biophysical parameters, albedo, NDVI and LST, were investigated from 2001 to 2018. The latent heat flux showed a significant increase with a trend of 0.24, while a decrease in sensible heat flux with a trend of−0.21 was observed over Pakistan. Net radiation showed an ignorable increase with a trend of 0.054 over whole Pakistan. A significant negative relation was found between net radiation and sensible heat flux with albedo while a significant positive relation was found between latent heat flux and NDVI. Biophysical parameters such as NDVI, albedo and LST successively explain the trends of radiative and non-radiative fluxes. This study comprehensively explains the mechanism and patterns of the regional energy budget.

Intense moist intrusions originating from the lower latitudes of the Pacific Ocean have been found to have a significant impact on the Antarctic Peninsula (AP), including enhancement of surface melt events, increased runoff, reduction in sea-ice cover and ice shelves destabilization. Clouds play an important role in the surface energy budget during these events and in precipitation formation. Precipitation phase and amounts determine local and regional surface mass and energy budget. Our  research focuses on cloud and precipitation microphysical and dynamic characteristics over the AP region, using  ground based remote sensing at the Ukrainian Antarctic Station Akademic Vernadsky Moreover, an enhanced radiosonde program was launched during the austral winter at the Vernadsky station as part of the Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) international initiative (May-August 2022). Here we present detailed analysis of one of the Targeted Observing Periods (TOPs) during an intense moisture and heat intrusion affecting the AP.Although there is a lot of research on the atmospheric processes over the AP region, the local dynamic and microphysical characteristics of clouds and precipitation are still poorly understood and misrepresented in the models due to the lack of direct measurements, particularly in winter.Further we performed  Polar-WRF model simulations, forced by ERA5 reanalysis and configured with Morrison double moment cloud microphysical scheme. The simulations were run at 1-km spatial resolution with 10-minute temporal output centered over the Vernadsky region. Simulation results were verified with precipitation properties derived from Micro Rain Radar-Pro measurements and radiosonde profiles. We found that there is  more snow in PolarWRF outputs in comparison to MRR-Pro measurements. Thus it does not represent mixed phased precipitation properly. At the same time Polar WRF shows warm temperature bias compared to radiosounding. Measurements and model output are used to analyze cloud ice and water particle distribution, thickness and precipitation particle spectra over the Vernadsky station and the AP mountains during the extreme precipitation events in the Antarctic Winter. In overall there were five TOPs over the AP region. However, not all of them were associated with extreme precipitation on Vernadsky station.Our preliminary results show the importance of the transition between dry and wet snowfall during intense moisture transport events at the AP (particularly remarkable during winter at the location of Vernadsky station). Polar-WRF shows differences in simulating the timing and intensity of such transitions probably related to the biases in temperature profiles influencing the melting layer height.

The Norwegian young sea ice campaign obtained the first measurements of the surface energy budget over young, thin Arctic sea ice through the seasonal transition from winter to summer. This campaign was the first of its kind in the North Atlantic sector of the Arctic. This study describes the atmospheric and surface conditions and the radiative and turbulent heat fluxes over young, thin sea ice. The shortwave albedo of the snow surface ranged from about 0.85 in winter to 0.72–0.80 in early summer. The near‐surface atmosphere was typically stable in winter, unstable in spring, and near neutral in summer once the surface skin temperature reached 0°C. The daily average radiative and turbulent heat fluxes typically sum to negative values (−40 to 0 W m−2) in winter but then transition toward positive values of up to nearly +60 W m−2 as solar radiation contributes significantly to the surface energy budget. The sensible heat flux typically ranges from +20–30 W m−2 in winter (into the surface) to negative values between 0 and −20 W m−2 in spring and summer. A winter case study highlights the significant effect of synoptic storms and demonstrates the complex interplay of wind, clouds, and heat and moisture advection on the surface energy components over sea ice in winter. A spring case study contrasts a rare period of 24 h of clear‐sky conditions with typical overcast conditions and highlights the impact of clouds on the surface radiation and energy budgets over young, thin sea ice.

Severe cloud contamination of MODIS Land Surface Temperatures over an Arctic ice cap, Svalbard

Spatial distribution and pattern persistence of surface soil moisture and temperature over prairie from remote sensing

Land surface temperature (LST) is a key parameter in the physics of land surface processes on regional and global scales. Although there are MODIS and Landsat land surface reflectance products, there is no LST product for Landsat data due in part to many challenges in the development of an operational Landsat LST product generating system because Landsat possesses only one thermal infrared channel. The aim of this article is to describe the Landsat LST product generation project launched by the Centre for Earth Observation and Digital Earth (CEODE), Chinese Academy of Sciences. The generalized single-channel (SC) algorithm proposed by Jiménez-Muñoz et al. is used for LST retrieval. It is fully operational, requires minimal input data requirements, and has acceptable precision. Total atmospheric water vapour content is the key input parameter required by the SC algorithm. In this project, the MODIS water vapour product is employed to derive total atmospheric water vapour content. In this way, an operational Landsat LST product generation program was constructed by integration of MODIS and Landsat satellite imagery.

Estimates of melt from debris-covered glaciers require distributed estimates of meteorological variables and air temperature in particular. Meteorological data are scarce for this environment, and spatial variability of temperature over debris is poorly understood. Based on multiple measurements of air and surface temperature from three ablation seasons (2012–14) we investigate the variability of temperature over Lirung Glacier, Nepal, in order to reveal how air temperature is affected by the debris cover and improve ways to extrapolate it. We investigate how much on-glacier temperature deviates from that predicted from a valley lapse rate (LR), analyse on-glacier LRs and test regression models of air temperature and surface temperature. Air temperature over the debris-covered glacier tongue is much higher than what a valley LR would prescribe, so an extrapolation from off-glacier stations is not applicable. An on-glacier LR is clearly defined at night, with strong correlation, but not during the day, when the warming debris disrupts the elevation control. An alternative to derive daytime air temperature is to use a relationship between air and surface temperature, as previously suggested. We find strong variability during daytime that should be accounted for if these regressions are used for temperature extrapolation.

Continuous monitoring of the surface temperature is critical to understanding and forecasting Arctic climate change; as surface temperature integrates changes in the surface energy budget. The sea-ice surface temperature (IST) has been measured with optical and thermal infrared sensors for many years. With the IST Environmental Data Record (EDR) available from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) and future Joint Polar Satellite System (JPSS) satellites; we can continue to monitor and investigate Arctic climate change. This work examines the quality of the VIIRS IST EDR. Validation is performed through comparisons with multiple datasets; including NASA IceBridge measurements; air temperature from Arctic drifting ice buoys; Moderate Resolution Imaging Spectroradiometer (MODIS) IST; MODIS IST simultaneous nadir overpass (SNO); and surface air temperature from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. Results show biases of −0.34; −0.12; 0.16; −3.20; and −3.41 K compared to an aircraft-mounted downward-looking pyrometer; MODIS; MODIS SNO; drifting buoy; and NCEP/NCAR reanalysis; respectively; root-mean-square errors of 0.98; 1.02; 0.95; 4.89; and 6.94 K; and root-mean-square errors with the bias removed of 0.92; 1.01; 0.94; 3.70; and 6.04 K. Based on the IceBridge and MODIS results; the VIIRS IST uncertainty (RMSE) meets or exceeds the JPSS system requirement of 1.0 K. The product can therefore be considered useful for meteorological and climatological applications.

In this study, the influence of subsurface water on the energy budget components of three locations with heterogeneous land surfaces in the Nebraska Sand Hills are examined through observations and use of the Noah land surface model (LSM). Observations of the four primary components of the surface energy budget are compared for a wet interdunal meadow valley, a dry interdunal valley, and a dunal upland location. With similar atmospheric forcing at each site, it was determined that differences in the partitioning of the mean diurnal net radiation (Rnet) existed among the three locations due to the influence of varied soil moisture and vegetation through the year. At the wet valley, observations indicated that almost 65% of the mean daily peak Rnet was used for latent heating, due to the relatively higher soil moisture content resulting from an annual upward gradient of subsurface water and denser vegetation. In sharp contrast, the dunal upland site yielded only 21% of the mean daily peak Rnet going to latent heating, and a greater mean diurnal soil heat flux with typically drier soils and sparser vegetation than at the wet valley. The dry valley partition of the peak Rnet fell between the wet valley and dunal upland site, with approximately 50% going to sensible heating and 50% toward latent heating. In addition to the observational analysis, an uncoupled land surface model was forced with the observations from each site to simulate the energy budgets, with no tuning of the model’s fundamental equations and with little adjustment of the model parameters to improve results. While the model was able to reasonably simulate the mean diurnal and annual energy budget components at all locations, in most instances with root-mean-square errors within 20%–25% of the observed values, the lack of explicit treatment of subsurface water within the model limited predictability, particularly at the wet valley site. For instance, only 25% of the peak mean diurnal Rnet went toward latent heating in the model simulation of the wet valley, compared to 65% as estimated by observations. Model evaluation statistics are presented to document the land surface model’s ability to capture the annual and mean diurnal variations in the surface energy budget terms at the dry valley and dunal upland sites, but the absence of subsurface water results in large errors in the wet valley simulation. From these results, a case is made for the future inclusion of the explicit treatment of subsurface water within the Noah LSM to better approximate the prediction of the surface energy budget in such environments.

Evapotranspiration is a key parameter in agricultural water planning and management strategies because it determines the crop and irrigation water requirements. With the recent advance in satellite-based field observations and meteorological modeling, several techniques have been developed and applied to estimate actual evapotranspiration. This paper presents the first results of the application to field evapotranspiration monitoring of land surface temperatures observed by Japan’s new Global Change Observation Mission-Climate (GCOM-C) satellite. Through a test application conducted in an irrigation region in the western USA, specifications of the GCOM-C surface temperature observation and the derived field evapotranspiration were evaluated. The specifications of the surface temperature observation were that the satellite observed the study fields with a spatial resolution of about 300 m at a frequency of 4–5 days per week. Clouds further degraded observation frequency. However, at least one constant successful observation of land surface temperature was available each week during the study period from June 17 to July 21, 2018. With the unique spatial and temporal resolution of GCOM-C, the surface temperature data allowed weekly monitoring of individual field evapotranspiration for large-size fields. Estimation results of field evapotranspiration by the GCOM-C ETindex estimation algorithm were evaluated for fields of wheat, pea, alfalfa, bean, and corn/potato/beet, as well as for rangeland. The result reasonably explained the relative differences of evapotranspiration among the different crop types and among individual fields having the same crop type. Quantitatively, some indications of underestimation of evapotranspiration were found during the application.