Relationship of extreme precipitation, surface air temperature, and dew point temperature across the Tibetan Plateau

Yong, Zhiwei; Xiong, Junnan; Wang, Zegen; Cheng, Weiming; Yang, Jiawei; Quan, Pang

doi:10.1007/s10584-021-03076-2

Cited by 20 publications

(6 citation statements)

References 60 publications

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“…1), for all three seasons, which explains why we see consistently positive SAT scaling rates over this region, which are comparable to the DPT scaling rates. A previous study by Yong et al (2021) also highlighted that the DPT scaling rates in the Tibetan plateau are similar to the SAT scaling rates, and that the scaling rates are higher during the winter months compared to summer months, and similar results are found in our analysis. This is largely due to the occurrence of these extremes at SAT values higher than that normally found on wet days, which also highlights that higher temperatures do drive precipitation extremes, especially in climates that are generally colder, while humidity variations play a more important role in tropical and warmer climates.…”

Section: Thermodynamic and Dynamical Features Associated With Precipi...supporting

confidence: 90%

Seasonal variations in the dynamic and thermodynamic response of precipitation extremes in the Indian subcontinent

2022

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Precipitation extremes are a major impact-relevant implication of climate change. Rising temperatures increase the moisture holding capacity at a rate of ≈ 7%K −1 , called the Clausius-Claypeyron (CC) scaling, which can lead to intense precipitation which last for short duration. At a regional level, the scaling of extremes deviates from this expected scaling rate. Large scale circulation dynamics and local variability in thermodynamic influences are suspected to cause these deviation, but these drivers differ across seasons. In the present study, we use ERA5 reanalysis to evaluate the seasonal changes in precipitation-temperature scaling rates over the Indian subcontinent. We further determine the deviations from the expected CC scaling rate, and the precipitation extremes are decomposed to their dynamic and thermodynamic contribution across different seasons. It is found that significant seasonal contrast exists in the dynamic and thermodynamic contributions, with the latter dominating during the Indian summer monsoon season, while the former being higher during the pre-monsoon and post-monsoon season. Further analysis highlights that the lower dynamic contribution is attributed to drop in dew . point temperatures and Convective Available Potential Energy during extremes. The primary drivers causing the extremes in different seasons are also pointed out, further improving the understanding of how the intensity and frequency of precipitation extremes changes spatially across different seasons, and what are the physical drivers causing these changes.

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Section: Thermodynamic and Dynamical Features Associated With Precipi...supporting

confidence: 90%

Seasonal variations in the dynamic and thermodynamic response of precipitation extremes in the Indian subcontinent

2022

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“…On a large scale, this determines the relation between daily rainfall extremes and surface air temperature. For hourly or sub‐hourly extremes, water vapour increases even faster with air temperature (Lenderink & Van Meijgaard, 2008; Moustakis et al, 2020; Yong et al, 2021). It would be of interest to study the influence of orography on these scaling relations in depth (Kendon et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Topoclimate and diurnal cycle of summer rain over the Ethiopian highlands in a convection‐permitting simulation

Negash,

Van Schaeybroeck,

Termonia

et al. 2023

Intl Journal of Climatology

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Topoclimate, orographically enhanced rain on windward slopes and leeward rain shadows, control rainfall variability in tropical mountains. Such variability may cause a substantial societal impact in populated highlands such as in Ethiopia. This study aims at understanding the rainfall diurnal cycle and the orographic driving factors over the Ethiopian highlands using the ALARO‐0 regional climate model at convection‐permitting resolution, over a period of 21 years. While the evaluation against satellite‐based observations shows a too early onset of the model diurnal cycle and a too low nocturnal rainfall, several conclusions can be drawn from the model simulations presented here. Elevation is the most important determining factor for modelled rainfall with increased average rainfall and rainfall per rainfall event towards higher elevations. Ethiopia's simulated summer rain exhibits a pronounced diurnal cycle with the highest rainfall occurring during the early afternoon hours and the minimum values occurring in the late night. Average rainfall and rainfall per rainfall event are substantially larger on the windward sides than on the leeward sides of the mountains, except during the peak hours. The diurnal cycles of temperature and humidity start earlier in the morning and recede later than the cycles of wind speed and rainfall. Moreover, rainfall peaks occur earlier in the day at higher elevations, and at night in valleys and in Afar Triangle. Rain intensities around noon on the leeward side are slightly higher than those on the windward side of the highest mountains (>3000 m). This could be due to delayed onset of cloudiness and larger morning insolation on the leeward side of the mountain, but this needs further study. The prevalence of windward over leeward rainfall, the stark contrast in wind‐speed diurnal cycle between windward and leeward slopes, and the early peak hour of surface air and dew point temperature all point towards temperature‐induced rather than wind‐induced convection. These differences are likely to determine hydrology and vegetation distribution, and farmers economy at large. Hence, the need for a way out from the ‘one‐size‐fits‐all’ agro‐ecosystem management approach towards a site‐specific policy that takes into account climatic differences.

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“…ETP, which is similar to the spatial changes in temperature reforecasts. With the higher temperature, the evaporation intensity becomes higher, and more moisture is carried to the atmosphere (Zhang et al, 2019;Yong et al, 2021), providing conditions for the more precipitation. Moreover, it can be noticed that the largest differences in snowfall between the two reforecasts (the DA reforecasts minus the control reforecasts) reach 0.8 mm w.e., while those in precipitation reach 1.8 mm, meaning that most of the increased precipitation is in the form of rainfall.…”

Section: Discussionmentioning

confidence: 99%

Impacts of snow assimilation on seasonal snow and meteorological forecasts for the Tibetan Plateau

Chen

et al. 2022

The Cryosphere

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Abstract. The Tibetan Plateau (TP) contains the largest amount of snow outside the polar regions and is the source of many major rivers in Asia. An accurate long-range (i.e. seasonal) meteorological forecast is of great importance for this region. The fifth-generation seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (SEAS5) provides global long-range meteorological forecasts including over the TP. However, SEAS5 uses land initial conditions produced by assimilating Interactive Multisensor Snow and Ice Mapping System (IMS) snow data only below 1500 m altitude, which may affect the forecast skill of SEAS5 over mountainous regions like the TP. To investigate the impacts of snow assimilation on the forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer 2018. Significant changes occur in the springtime. Without snow assimilation, the reforecasts overestimate snow cover and snow depth while underestimating daily temperature over the TP. Compared to satellite-based estimates, precipitation reforecasts perform better in the west TP (WTP) than in the east TP (ETP). With snow assimilation, the reforecasts of snow cover, snow depth and temperature are consistently improved in the TP in the spring. However, the positive bias between the precipitation reforecasts and satellite observations worsens in the ETP. Compared to the experiment with no snow assimilation, the snow assimilation experiment significantly increases temperature and precipitation for the ETP and around the longitude 95∘ E. The higher temperature after snow assimilation, in particular the cold bias reduction after initialization, can be attributed to the effects of a more realistic, decreased snowpack, providing favourable conditions for generating more precipitation. Overall, snow assimilation can improve seasonal forecasts through the interaction between land and atmosphere.

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Relationship of extreme precipitation, surface air temperature, and dew point temperature across the Tibetan Plateau

Cited by 20 publications

References 60 publications

Seasonal variations in the dynamic and thermodynamic response of precipitation extremes in the Indian subcontinent

Seasonal variations in the dynamic and thermodynamic response of precipitation extremes in the Indian subcontinent

Topoclimate and diurnal cycle of summer rain over the Ethiopian highlands in a convection‐permitting simulation

Impacts of snow assimilation on seasonal snow and meteorological forecasts for the Tibetan Plateau

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