Precipitation Phase Changes Research Articles

Projection of snowfall and precipitation phase changes over the Northwest China based on CMIP6 multimodels

The change of precipitation phase could have profound influence on water cycle and ecological environment in Northwest China (NWC). It has been observed that snowfall is inclined to transition into rainfall under climate warming. However, the evolution process of precipitation phase in the future over the NWC remains poorly understanding. In this study, the performance of snowfall simulated by Coupled Model Intercomparison Project Phase 6 (CMIP6) is evaluated by results of observation-based rain/snow separation, subsequently analyzing the changes in snowfall and precipitation phase under different climate scenarios over the NWC. The results indicated that most of CMIP6 models overestimate snowfall while underestimate the Snowfall to Precipitation Ratio (SPR) over the NWC. The performance of CMIP6 models is poorer in high-altitude mountainous region but relatively more robust in low-altitude areas. Superior performance of five models are selected for analysing changes of snowfall and precipitation phase in the future. Under the SSP1-2.6 scenario, the trend of changes in snowfall is not obviously in the future. Conversely, snowfall is projected to decline at rates of −1.04 mm·10a-1 and −2.94 mm·10a-1 under the SSP2-4.5 and SSP5-8.5 scenarios, respectively, with significant declines in high-altitude zones. The SPR will decrease at rates of −0.19 %·10a-1, −0.64 %·10a-1, and −1.50 %·10a-1 under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenario, respectively. The magnitudes in changes of snowfall and SPR show significant differences across sub-regions in the future, with low-altitude areas exhibiting upward trends in snowfall and SPR under certain conditions. Winter snowfall in the future shows an increased trend, while declines are observed in spring and autumn snowfall overall, with notable disparities between scenarios. The correlation between snowfall biases and biases of temperature and precipitation indicate that temperature is a pivotal factor contributing to precipitation phase bias. The findings are helpful for enhancing the simulation precision of hydrological processes and providing scientific strategies for future water resource management over the NWC.

Analysis of Dual-Polarimetric Radar Observations of Precipitation Phase during Snowstorm Events in Jiangsu Province, China

Based on ground observed data, S-band dual-polarization radar data, and ERA-5 reanalysis data, the statistical characteristics of polarimetric parameters and the application of melting layer (ML) and hydrometeor classification (HCL) products during eight snowstorm events in Jiangsu Province from 2020 to 2022 were investigated. A heavy snowstorm that went through different phases of rain, sleet, and pure snow and that occurred on 29 December 2020 was also analyzed as a typical example. The results showed the following: During the phase transition between rain and snow in the Jiangsu region, the basic reflectivity factor ZH ≥ 27 dBZ, the zero-order lag correlation coefficient CC ≤ 0.93, and the differential reflectivity ZDR ≥ 1.0 dB were important indicators for judging the melting layer while the specific differential phase KDP changed slightly. The snowstorm event was well observed and recorded by the Yancheng dual-polarimetric radar, whose low value area of CC coincided mostly with the melting layer. The ML products and HCL products based on fuzzy-logic hydrometeor classification algorithms can help identify the melting layer and the properties of precipitation particles. ML products are more reliable when the melting layer is high and can better show the trends of melting layer decline. They can certainly serve as a reference for detecting and judging precipitation phase changes in winter in Jiangsu Province.

Microstructure evolution and mechanical properties of wire-arc-additively manufactured Al–Cu–Mg–Ag alloy

In this article, Al–Cu–Mg–Ag specimens were successfully wire-arc-additive-manufactured based on by gas metal arc process to investigate the evolution of microstructure and mechanical properties. The results showed that the grain morphology and pore size in the printed specimens varied in height direction. Under the influence of repeated thermal cycling, which affected the solid-state diffusion of the deviated elements at the grain boundaries, the distribution of the nanoscale second phase appeared significantly different in the height direction. The precipitation phase changes caused the microhardness of the printed specimens to decrease gradually from a peak of 125 HV and stabilise at around 100 HV. The changes in the printed specimens’ horizontal mechanical properties were insignificant mainly due to interlayer porosity.

Diverging Trends in Rain‐On‐Snow Over High Mountain Asia

AbstractRain‐on‐snow (ROS) over snow‐dominated regions such as High Mountain Asia (HMA) modulates snowmelt and runoff and is key contributor in influencing water availability and hazards (e.g., floods and landslides). We studied the trends in ROS in HMA over the past two decades from 2001 to 2018 using the land surface model Noah‐MP driven by an ensemble precipitation data set. Our results show that changes in precipitation phase and rainfall are altering ROS. Because of the strong physical heterogeneity and atmospheric dynamics of HMA, ROS characteristics and trends are region‐dependent and ROS occurs predominantly over the Indus, Ganges‐Brahmaputra, and northwestern basins. In the Indus, ROS representing ∼5% of the annual precipitation and ∼20% of the annual snowmelt, has an increasing trend. This is contrary to the Ganges‐Brahmaputra characterized by decreasing ROS trends, where it represents ∼11% of the annual precipitation and ∼60% of the annual snowmelt. In the northwestern basins, ROS has bidirectional trends due to elevation patterns and trends in rainfall, and it constitutes ∼5 to ∼10% of the annual precipitation. Increasing trends in ROS over Indus contribute to reducing the snowpack in late summer, with concerns of reduced water availability and increased groundwater exploitation. Similarly, because of its high amount and contribution to snowmelt, the decreasing ROS trends in the Ganges‐Brahmaputra will have consequences of decreased recharge from the headwaters and exacerbated use of groundwater unless increasing trends in rainfall compensate for the decreasing snowmelt. These results provide new insights on ROS‐driven changes in the hydrological cycle over HMA.

Historical evaluation and projection of precipitation phase changes in the cold season over the Tibetan Plateau based on CMIP6 multimodels

The solid precipitation in the cold season over the TP is important for the recharge of snow cover, glaciers, rivers, etc. During the past decades, the TP has experienced enhanced warming in the cold season, which could transfer more snowfall to rainfall and influence the land-atmosphere hydrological cycle of the Asian water tower. However, most CMIP6 models underestimate the cold season temperature and overestimate the total precipitation, and the performance of the precipitation phase in the CMIP6 simulations remains unclear. This study investigates the precipitation phase bias in the cold season by comparing simulations from CMIP6 to observations. The results suggest that the snowfall-to-precipitation ratio (SPR) from CMIP6 was significantly underestimated, and the SPR at the southern edge of the TP was underestimated by approximately 30%. However, the decreasing trend of SPR is significantly overestimated. Comparing the influence of the surface temperature and total precipitation, the correlation coefficient between the mean SPR bias and the simulated temperature bias is −0.701 with a 99% confidence level, which is much greater than that with total precipitation bias. The mean SPR in the seven best models is much greater than the ensemble mean of the original 23 CMIP6 models over the TP. Moreover, the SPR varies significantly under different future scenarios. Under the most severe scenario, the decrease in SPR exceeds −21.45%, substantially influencing the water balance over the TP, while the decline is only −9.79% under the weak scenario. Therefore, the warming caused by high emissions should not be ignored when projecting the precipitation phase, and the significant effect of surface temperature on the precipitation phase requires additional consideration when investigating the hydrological cycle imbalance over the TP.

Tracking the impacts of precipitation phase changes through the hydrologic cycle in snowy regions: From precipitation to reservoir storage

Cool season precipitation plays a critical role in regional water resource management in the western United States. Throughout the twenty-first century, regional precipitation will be impacted by rising temperatures and changing circulation patterns. Changes to precipitation magnitude remain challenging to project; however, precipitation phase is largely dependent on temperature, and temperature predictions from global climate models are generally in agreement. To understand the implications of this dependence, we investigate projected patterns in changing precipitation phase for mountain areas of the western United States over the twenty-first century and how shifts from snow to rain may impact runoff. We downscale two bias-corrected global climate models for historical and end-century decades with the Weather Research and Forecasting (WRF) regional climate model to estimate precipitation phase and spatial patterns at high spatial resolution (9 km). For future decades, we use the RCP 8.5 scenario, which may be considered a very high baseline emissions scenario to quantify snow season differences over major mountain chains in the western U.S. Under this scenario, the average annual snowfall fraction over the Sierra Nevada decreases by >45% by the end of the century. In contrast, for the colder Rocky Mountains, the snowfall fraction decreases by 29%. Streamflow peaks in basins draining the Sierra Nevada are projected to arrive nearly a month earlier by the end of the century. By coupling WRF with a water resources model, we estimate that California reservoirs will shift towards earlier maximum storage by 1–2 months, suggesting that water management strategies will need to adapt to changes in streamflow magnitude and timing.

The Influence of Precipitation Phase Changes on the Recharge Process of Terrestrial Water Storage in the Cold Season Over the Tibetan Plateau

AbstractClimate warming has affected the land surface and atmospheric temperature over the Tibetan Plateau (TP), resulting in a series of hydrological changes, such as atmospheric wetting and decreasing terrestrial water storage (TWS). According to Gravity Recovery and Climate Experiment data, TWS higher than 2,500 m over the TP significantly decreased during the 1979–2019 period, with a more enhanced trend in the cold season. Previous studies have mainly focused on the influence of global warming on the discharge process in the warm season, such as glacier melting, increasing runoff and decreasing snow cover. The changes in atmospheric moisture recharge in the cold season and its contribution to decreasing TWS remain unclear. Based on the time scale, the hydrological process can be divided into slow (snowfall and evaporation) and fast (rainfall and runoff) processes. Our results suggest that the TWS changes in the cold season are dominated by slow processes. Cold‐season warming over the TP can increase the atmospheric melting level height (MLH), leading to a transition from snowfall to rainfall. Consequently, the decreasing snowfall and increasing evaporation induced by warming result in a net decrease in atmospheric recharge to the TWS. A quantified contribution of the fast and slow processes to the TWS changes in the cold season indicates that the slow processes play a dominant role over most of the TP, except for the Hexi, Inner, Qaidam, Yangtze, and Yellow Basins. Decreasing atmospheric recharge could accelerate the decrease in TWS, which motivates further investigation to better predict the hydrological response.

Tracking the impacts of precipitation phase changes through the hydrologic cycle in snowy regions: From precipitation to reservoir storage

Tracking the impacts of precipitation phase changes through the hydrologic cycle in snowy regions: From precipitation to reservoir storage

Modeling streamflow sensitivity to climate warming and surface water inputs in a montane catchment

Study regionGordon Gulch, an upper-montane forest watershed in the Colorado Front Range. Study focusAs the climate warms, the fraction of precipitation falling as snow is expected to decrease and the timing of snowmelt is expected to shift earlier in spring. In snow-dominated regions, these changes in snow accumulation and melt prompt us to examine downstream changes in streamflow. The objective of this study is to understand how changes in precipitation phase and snowmelt timing alter the timing of surface water inputs (i.e. rainfall and snowmelt) and the partitioning of these inputs between evapotranspiration and streamflow. We used the Distributed Hydrology Soil Vegetation Model and Weather Research and Forecasting Model-based projections of future climatic conditions to simulate streamflow. New hydrological insights for the regionModeled annual streamflow decreased by 22% for the period 2071–2100. Surface water inputs increased during winter when atmospheric water demand was relatively low. Subsequently, the winter-period partitioning of water (as rain or snowmelt) to streamflow (as opposed to evapotranspiration) increased, by 15%, while partitioning to evapotranspiration decreased, effectively buffering what would have otherwise been a larger net streamflow decline associated with warming. Seasonal streamflow buffering is unique to snow-influenced systems, as the magnitude and timing of water released from snowpacks is sensitive to warming. This effect may diminish as warming drives snow-influenced systems toward rain-dominance, with implications for hydrological and ecological processes and water-resource management.

Reducing misclassified precipitation phase in conceptual models using cloud base heights and relative humidity to adjust air temperature thresholds

Abstract In cold region, conceptual models assigned precipitation phase, liquid (rain) or solid (snow), cause vastly different atmospheric, hydrological, and ecological responses, along with significant differences in evaporation, runoff, and infiltration fates for measured precipitation mass. A set air temperature threshold (ATT) applied to the over 30% annual precipitation events occurring with surface air temperatures between −3 and 5 °C resulted in 11.0 and 9.8% misclassified precipitation in Norway and Sweden, respectively. Surface air temperatures do not account for atmospheric properties causing precipitation phase changes as snow falls toward the ground. However, cloud base height and relative humidity (RH) measured from the surface can adjust ATT for expected hydrometeor-atmosphere interactions. Applying calibrated cloud base height ATTs or a linear RH function for Norway (Sweden) reduced misclassified precipitation by 4.3% (2.8%) and 14.6% (8.9%) misclassified precipitation, respectively. Cloud base height ATTs had lower miss-rates with low cloud bases, 100 m in Norway and 300 m in Sweden. Combining the RH method with cloud base ATT in low cloud conditions resulted in 16.1 and 10.8% reduction in misclassified precipitation in Norway and Sweden, respectively. Therefore, the conceptual model output should improve through the addition of available surface data without coupling to an atmospheric model.

Extremes become routine in an emerging new Arctic

The Arctic is rapidly warming and experiencing tremendous changes in sea ice, ocean and terrestrial regions. Lack of long-term scientific observations makes it difficult to assess whether Arctic changes statistically represent a ‘new Arctic’ climate. Here we use five Coupled Model Intercomparison Project 5 class Earth system model large ensembles to show how the Arctic is transitioning from a dominantly frozen state and to quantify the nature and timing of an emerging new Arctic climate in sea ice, air temperatures and precipitation phase (rain versus snow). Our results suggest that Arctic climate has already emerged in sea ice. Air temperatures will emerge under the representative concentration pathway 8.5 scenario in the early- to mid-twenty-first century, followed by precipitation-phase changes. Despite differences in mean state and forced response, these models show striking similarities in their anthropogenically forced emergence from internal variability in Arctic sea ice, surface temperatures and precipitation-phase changes. The short observational record makes it difficult to gauge how unprecedented recent Arctic warming is. A multi-model large ensemble estimates a new Arctic climate has emerged for sea-ice extent. As the Arctic shifts from a primarily frozen state, temperature and precipitation follow within decades.

Radar Remote Sensing of Precipitation in High Mountains: Detection and Characterization of Melting Layer in the Grenoble Valley, French Alps

The RadAlp experiment aims at developing advanced methods for rain and snow estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed in the French Alps, Grenoble region. It is composed of a Météo-France operated X-band MOUC radar (volumetric, Doppler and polarimetric) on top of the Mt Moucherotte (1920 m ASL), the X-band XPORT research radar (volumetric, Doppler, polarimetric), a K-band micro rain radar (MRR, Doppler, vertically pointing) and in situ sensors (rain gauges, disdrometers), latter three operated on the Grenoble campus (220 m ASL). Based on the observation that the precipitation phase changes at/below the elevation of mountain-top MOUC radar for more than 60% of the significant events, an algorithm for ML identification has been developed using valley-based radar systems: it uses the quasi vertical profiles of XPORT polarimetric measurements (horizontal and vertical reflectivity, differential reflectivity, cross-polar correlation coefficient) and the MRR vertical profiles of apparent falling velocity spectra. The algorithm produces time series of the altitudes and values of peaks and inflection points of the different radar observables. A literature review allows us to link the micro-physical processes at play during the melting process with the available polarimetric and Doppler signatures, e.g., (i) regarding the altitude differences between the peaks of reflectivity, cross-polar correlation coefficient and differential reflectivity, as well as (ii) regarding the co-variation of the profiles of Doppler velocity spectra and cross-polar correlation coefficient. A statistical analysis of the ML based on 42 rain events (98 h of XPORT data) is then proposed. Among other results, this study indicates that (i) the mean value of the ML width in Grenoble is 610 m with a standard deviation of 160 m; (ii) the mean altitude difference between the horizontal reflectivity and the ρ H V peaks is 90 m and the mean altitude difference between the ρ H V and Zdr peaks is 30 m; (iii) even for the limited rainrate range in the dataset (0–8.5 mm h − 1 ), the “intensity effect” is clear on the reflectivity profile and the ML width, as well as on polarimetric variables such as ρ H V peak value and the Zdr enhancement in the upper part of the profile. On the contrary, the study of both the “density effect” and the influence of the 0 ° C isotherm altitude did not yield significant results with the considered dataset; (iv) a principal component analysis on one hand shows the richness of the dataset since the first 2 PCs explain only 50% of the total variance and on the other hand the added-value of the polarimetric variables since they rank high in a ranking of the total variance explained by individual variables.

Reconciling High Glacier Surface Melting in Summer with Air Temperature in the Semi-Arid Zone of Western Himalaya

In Himalaya, the temperature plays a key role in the process of snow and ice melting and, importantly, the precipitation phase changes (i.e., snow or rain). Consequently, in longer period, the melting and temperature gradient determine the state of the Himalayan glaciers. This necessitates the continuous monitoring of glacier surface melting and a well-established meteorological network in the Himalaya. An attempt has been made to study the seasonal and annual (October 2015 to September 2017) characteristics of air temperature, near-surface temperature lapse rate (tlr), in-situ glacier surface melting, and surface melt simulation by temperature-index (T-index) models for Sutri Dhaka Glacier catchment, Lahaul-Spiti region in Western Himalaya. The tlr of the catchment ranges from 0.3 to 6.5 °C km−1, varying on a monthly and seasonal timescale, which suggests the need for avoiding the use of standard environmental lapse rate (SELR ~6.5 °C km−1). The measured and extrapolated average air temperature (tavg) was found to be positive on glacier surface (4500 to 5500 m asl) between June and September (summer). Ablation data calculated for the balance years 2015–16 and 2016–17 shows an average melting of −4.20 ± 0.84 and −3.09 ± 0.62 m w.e., respectively. In compliance with positive air temperature in summer, ablation was also found to be maximum ~88% of total yearly ice melt. When comparing the observed and modelled ablation data with air temperature, we show that the high summer glacier melt was caused by warmer summer air temperature and minimum spells of summer precipitation in the catchment.

Long-term changes in precipitation phase in Europe in cold half year

The change in precipitation phase is an important manifestation of climate change, especially in the moderate climate zone and mountain regions. We analyse changes in precipitation at 107 European stations in cold months (November–April). Stations in Czechia where both surface synoptic observations (SYNOP) reporting the precipitation phase, and temperature and precipitation data are available in sufficient quality, are used to determine the regional threshold temperature. The threshold temperature is then applied to separate solid and liquid precipitation phase in cold months at European stations in 1961–2010. If daily mean temperature is higher than the regional threshold temperature, daily precipitation amount is considered to be liquid and vice versa. The value of the regional threshold temperature is 1.1 °C. The ratio of solid to total precipitation (S/P) significantly declines over large parts of Europe. The strongest negative trend is detected in the belt stretching from the coast of northern Scandinavia through central and eastern Europe towards southern and southeastern Europe. The trend of S/P ranges from −0.2 to −0.9%·year−1 there. The average annual trend of the ratio of solid precipitation for all Europe is −0.12%·year−1. The magnitude of the trend of the ratio of solid precipitation exhibits only a minor sensitivity to the choice of the threshold temperature. A comparison with real trends, calculated for stations in Czechia, indicates that trends determined from the threshold temperature tend to be overestimated, that is, the decline of solid precipitation in Europe is even faster that what results of this study indicate.

Long-term changes in precipitation phase in Czechia

Long-term changes in precipitation phase are investigated at ten stations in Czechia. Trends are calculated from 1983 to 2018 for the period between November and April. Daily SYNOP reports and daily precipitation totals are used at every station, where number and occurrence of specific codes in SYNOP report determine daily precipitation totals as solid, combined (which represents, to a large extent, category of mixed precipitation), or liquid. Thereafter, it is possible to calculate trends of all precipitation phases as well as the proportion of solid to total precipitation (S/P; in %). The average S/P trend over all Czech stations is significantly negative (−0.60%·year-1) and accompanied by a sharp decrease in solid precipitation (−1.66 mm·year-1) and an increase in combined precipitation (1.50 mm·year-1). Thus, our results show a ship of precipitation phase from solid to combined. Because of the dependence of S/P on air temperature, we suppose that the current S/P decline is a manifestation of rising air temperatures in the past decades.

Regional climate forcing and topographic influence on glacier shrinkage: eastern cordilleras of Peru

ABSTRACTThis study assessed the influence of regional climate variability and topography on surface area changes at glacierized mountain peaks of four eastern tropical Andes cordilleras between 10.5° and 13.5°S, namely, Huaguruncho, Huaytapallana, Urubamba and Vilcabamba, during the period 1985–2015 using satellite data. Time series analysis of three key climate variables (temperature, precipitation and relative humidity) at 500 hPa level was also included. Decreasing trends in precipitation and increasing relative humidity trends were observed at the northern region. Further analysis on mean distribution of wind at 500 hPa level showed significant rising trend southwards during the austral winter. Glacierized surfaces at lower altitudes were shrinking faster than those at high altitudes as expected. However, spatial orientation of glacier retreat was not similar to nearby cordilleras such as Vilcanota and Carabaya excepting for Cordillera Urubamba. Despite the high rate of precipitation due to the humidity transport from the Amazon Basin on the eastern slopes, glaciers on the eastern and north‐eastern slopes in the Cordillera Urubamba retreated at a higher rate compared with those glaciers on western and south‐western sides. Whether higher retreat on the eastern sides towards the south is controlled by precipitation phase changes (rain or snow) or by increased humidity levels was discussed. Furthermore, there was a predominant snowline altitude (SLA) rising trend varying between 56 and 129 m for the studied glaciers. A sharp rise in SLAs for periods 1995–2000 and 2010–2015 was attested, coinciding with warming trends in the Pacific. The relative stability in observed SLAs between 2000 and 2010 also coincided with cooling trends in the Pacific.

Variation in Biological Soil Crust Bacterial Abundance and Diversity as a Function of Climate in Cold Steppe Ecosystems in the Intermountain West, USA.

Biological soil crust (biocrust) is a composite of mosses, lichens, and bacteria that performs many important soil system functions, including increasing soil stability, protecting against wind erosion, reducing nutrient loss, and mediating carbon and nitrogen fixation cycles. These cold desert and steppe ecosystems are expected to experience directional changes in both climate and disturbance. These include increased temperatures, precipitation phase changes, and increased disturbance from anthropogenic land use. In this study, we assessed how climate and grazing disturbance may affect the abundance and diversity of bacteria in biocrusts in cold steppe ecosystems located in southwestern Idaho, USA. To our knowledge, our study is the first to document how biocrust bacterial composition and diversity change along a cold steppe climatic gradient. Analyses based on 16S small subunit ribosomal RNA gene sequences identified the phylum Actinobacteria as the major bacterial component within study site biocrusts (relative abundance=36-51%). The abundance of the phyla Actinobacteria and Firmicutes was higher at elevations experiencing cooler, wetter climates, while the abundance of Cyanobacteria, Proteobacteria, and Chloroflexi decreased. The abundance of the phyla Cyanobacteria and Proteobacteria showed no significant evidence of decline in grazed areas. Taken together, results from this study indicate that bacterial communities from rolling biocrusts found in cold steppe ecosystems are affected by climate regime and differ substantially from other cold desert ecosystems, resulting in potential differences in nutrient cycling and ecosystem dynamics.

Rain or snow: hydrologic processes, observations, prediction, and research needs

Abstract. The phase of precipitation when it reaches the ground is a first-order driver of hydrologic processes in a watershed. The presence of snow, rain, or mixed-phase precipitation affects the initial and boundary conditions that drive hydrological models. Despite their foundational importance to terrestrial hydrology, typical phase partitioning methods (PPMs) specify the phase based on near-surface air temperature only. Our review conveys the diversity of tools available for PPMs in hydrological modeling and the advancements needed to improve predictions in complex terrain with large spatiotemporal variations in precipitation phase. Initially, we review the processes and physics that control precipitation phase as relevant to hydrologists, focusing on the importance of processes occurring aloft. There is a wide range of options for field observations of precipitation phase, but there is a lack of a robust observation networks in complex terrain. New remote sensing observations have the potential to increase PPM fidelity, but generally require assumptions typical of other PPMs and field validation before they are operational. We review common PPMs and find that accuracy is generally increased at finer measurement intervals and by including humidity information. One important tool for PPM development is atmospheric modeling, which includes microphysical schemes that have not been effectively linked to hydrological models or validated against near-surface precipitation-phase observations. The review concludes by describing key research gaps and recommendations to improve PPMs, including better incorporation of atmospheric information, improved validation datasets, and regional-scale gridded data products. Two key points emerge from this synthesis for the hydrologic community: (1) current PPMs are too simple to capture important processes and are not well validated for most locations, (2) lack of sophisticated PPMs increases the uncertainty in estimation of hydrological sensitivity to changes in precipitation phase at local to regional scales. The advancement of PPMs is a critical research frontier in hydrology that requires scientific cooperation between hydrological and atmospheric modelers and field scientists.

Cloud effects on surface energy and mass balance in the ablation area of Brewster Glacier, New Zealand

Abstract. The effect of clouds on glacier surface energy balance (SEB) has received increased attention in the last decade, but how clouds interact with other meteorological forcing to influence surface mass balance (SMB) is not as well understood. This paper resolves the SEB and SMB at a site in the ablation zone of Brewster Glacier over a 22-month period, using high-quality radiation data to carefully evaluate SEB terms and define clear-sky and overcast conditions. A fundamental change in glacier SEB in cloudy conditions was driven by increased effective sky emissivity and surface vapour pressure, rather than a minimal change in air temperature and wind speed. During overcast conditions, positive net long-wave radiation and latent heat fluxes allowed melt to be maintained through a much greater length of time compared to clear-sky conditions, and led to similar melt in each sky condition. The sensitivity of SMB to changes in air temperature was greatly enhanced in overcast compared to clear-sky conditions due to more frequent melt and changes in precipitation phase that created a strong albedo feedback. During the spring and autumn seasons, the sensitivity during overcast conditions was strongest. To capture these processes, future attempts to explore glacier–climate interactions should aim to resolve the effects of atmospheric moisture (vapour, cloud, and precipitation) on melt as well as accumulation, through enhanced statistical or physically based methods.

Seasonal snow cover in the Qilian Mountains of Northwest China: Its dependence on oasis seasonal evolution and lowland production of water vapour

Back and forth exchange of water vapour and liquid water from oases at the base of the Qilian Mountains (NW China) and from the Qilian Mountains to oases as surface and shallow subsurface flow has been previously shown by model simulation to be a potentially important mechanism in the long-term stabilisation of oases in westcentral Gansu (Bourque and Hassan, 2009). In a subsequent re-examination of oasis self-support, we use monthly snow-cover patterns in the Qilian Mountains to determine the extent oasis vegetation and evapotranspiration in the low-lying portions of the upper and middle Shiyang and Hei River watersheds control snowfall dynamics in the Qilian Mountains. Monthly snow-cover area (SCA) in the watersheds is simulated with a spatially-distributed model designed to address differences in (i) topography along the prevailing wind direction, (ii) water-vapour production and transport, (iii) in-mountain production of precipitation, and (iv) precipitation phase changes. Seasonal variations in oasis vegetation, surface temperature (for model input), and SCA (for model validation) are described as separate timeseries of monthly composites of enhanced vegetation index, land surface temperature, and normalised difference snow index generated from MODIS optical reflectance and thermal emission data. Comparisons of modelled and snow-index-based estimates of SCA in the Shiyang and Hei River watersheds for the hydrological year, from August 2004 to July 2005, provide nearly similar spatiotemporal patterns; overlap between SCA’s exceeds 60% for most months. An exception to this is in mid-summer of 2004, where overlap between SCA’s is <30%. Agreement between monthly SCA’s reinforces the importance of oasis-vegetation dynamics and mass transfer of water vapour to the atmosphere in guiding seasonal formation of precipitation and snow-cover dynamics in the Qilian Mountains.