Humidity is a basic and crucial meteorological indicator commonly measured in several forms, including specific humidity, relative humidity, and absolute humidity. These different forms can be inter-derived based on the saturation vapor pressure (SVP). In past decades, dozens of formulae have been developed to calculate the SVP with respect to, and in equilibrium with, liquid water and solid ice surfaces, but many prior studies use a single function for all temperature ranges, without considering the distinction between over the liquid water and ice surfaces. These different approaches can result in humidity estimates that may impact our understanding of surface-subsurface thermal-hydrological dynamics in cold regions. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. These RHs, along with other meteorological indicators, were then used to drive physics-rich land surface models at a permafrost-affected site. We found that higher values of RH (up to 40 %) were obtained if the SVP was calculated with the over-ice formulation when air temperatures were below freezing, which could lead to a 30 % maximum difference in snow depths. The choice of whether to separately calculate the SVP over an ice surface in winter also produced a significant range (up to 0.2 m) in simulated annual maximum thaw depths. The sensitivity of seasonal thaw depth to the formulation of SVP increases with the rainfall rate and the height of above-ground ponded water, while it diminishes with warmer air temperatures. These results show that RH variations based on the calculation of SVP with or without over-ice calculation meaningfully impact physicallybased predictions of snow depth, sublimation, soil temperature, and active layer thickness. Under particular conditions, when severe flooding (inundation) and cool air temperatures are present, care should be taken to evaluate how humidity data is estimated for land surface and earth system modeling

Climate changes significantly impact the hydrological cycle. Precipitation is one of the most important atmospheric inputs to the terrestrial hydrologic system, and its variability considerably influences environmental and socioeconomic development. Atmospheric warming intensifies the hydrological cycle, increasing both atmospheric water vapor concentration and global precipitation. The relationship between heavy precipitation and temperature has been extensively investigated in literature. However, the relationship in different percentile ranges has not been thoroughly analyzed. Moreover, a percentilebased regression provides a simple but effective framework for investigation into other factors (precipitation type) affecting this relationship. Herein, a comprehensive investigation is presented on the temperature dependence of daily precipitation in various percentile ranges over the Qinghai-Tibet Plateau. The results show that 1) most stations exhibit a peaklike scaling structure, while the northeast part and south margin of the plateau exhibit monotonic positive and negative scaling structures, respectively. The scaling structure is associated with the precipitation type, and 2) the positive and negative scaling rates exhibit similar spatial patterns, with stronger (weaker) sensitivity in the south (north) part of the plateau. The overall increase rate of daily precipitation with temperature is scaled by Clausius-Clapeyron relationship. 3) The higher percentile of daily precipitation shows a larger positive scaling rate than the lower percentile. 4) The peak-point temperature is closely related to the local temperature, and the regional peak-point temperature is roughly around 10 degrees C.

Precipitation variability in tropical high mountains is a fundamental yet poorly understood factor influencing local climatic expression and a variety of environmental processes, including glacier behavior and water resources. Precipitation type, diurnality, frequency, and amount influence hydrological runoff, surface albedo, and soil moisture, whereas cloud cover associated with precipitation events reduces solar irradiance at the surface. Considerable uncertainty remains in the multiscale atmospheric processes influencing precipitation patterns and their associated regional variability in the tropical Andesparticularly related to precipitation phase, timing, and vertical structure. Using data from a variety of sourcesincluding new citizen science precipitation stations; new high-elevation comprehensive precipitation monitoring stations at Chacaltaya, Bolivia, and the Quelccaya Ice Cap, Peru; and a vertically pointing Micro Rain Radarthis article synthesizes findings from interdisciplinary research activities in the Cordillera Real of Bolivia and the Cordillera Vilcanota of Peru related to the following two research questions: (1) How do the temporal patterns, moisture source regions, and El Nino-Southern Oscillation relationships with precipitation occurrence vary? (2) What is the vertical structure (e.g., reflectivity, Doppler velocity, melting layer heights) of tropical Andean precipitation and how does it evolve temporally? Results indicate that much of the heavy precipitation occurs at night, is stratiform rather than convective in structure, and is associated with Amazonian moisture influx from the north and northwest. Improving scientific understanding of tropical Andean precipitation is of considerable importance to assessing climate variability and change, glacier behavior, hydrology, agriculture, ecosystems, and paleoclimatic reconstructions.