scholarly journals Suitability of a constant air temperature lapse rate over an Alpine glacier: testing the Greuell and Böhm model as an alternative

2013 ◽  
Vol 54 (63) ◽  
pp. 120-130 ◽  
Author(s):  
Lene Petersen ◽  
Francesca Pellicciotti ◽  
Inge Juszak ◽  
Marco Carenzo ◽  
Ben Brock
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Ambient Air ◽  
Lapse Rate ◽  
Spatial And Temporal Variability ◽  
Near Surface ◽  
Alpine Glacier ◽  
Temperature Lapse Rate ◽  
Boundary Layer Height ◽  
Air Temperatures

AbstractNear-surface air temperature, typically measured at a height of 2 m, is the most important control on the energy exchange and the melt rate at a snow or ice surface. It is distributed in a simplistic manner in most glacier melt models by using constant linear lapse rates, which poorly represent the actual spatial and temporal variability of air temperature. In this paper, we test a simple thermodynamic model proposed by Greuell and Böhm in 1998 as an alternative, using a new dataset of air temperature measurements from along the flowline of Haut Glacier d’Arolla, Switzerland. The unmodified model performs little better than assuming a constant linear lapse rate. When modified to allow the ratio of the boundary layer height to the bulk heat transfer coefficient to vary along the flowline, the model matches measured air temperatures better, and a further reduction of the root-mean-square error is obtained, although there is still considerable scope for improvement. The modified model is shown to perform best under conditions favourable to the development of katabatic winds – few clouds, positive ambient air temperature, limited influence of synoptic or valley winds and a long fetch – but its performance is poor under cloudy conditions.

Spatial and temporal variation of surface air temperature at different altitude zone in recent 30 years over Nepal

MAUSAM ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 417-428
Author(s):  
JANAK LAL NAYAVA ◽  
SUNIL ADHIKARY ◽  
OM RATNA BAJRACHARYA
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Temperature Data ◽  
Lapse Rate ◽  
Spatial And Temporal Variation ◽  
Mountain Regions ◽  
Temperature Lapse Rate ◽  
Air Temperatures ◽  
Long Term Trend

This paper investigates long term (30 yrs) altitudinal variations of surface air temperatures based on air temperature data of countrywide scattered 22 stations (15 synoptic and 7 climate stations) in Nepal. Several researchers have reported that rate of air temperature rise (long term trend of atmospheric warming) in Nepal is highest in the Himalayan region (~ 3500 m asl or higher) compared to the Hills and Terai regions. Contrary to the results of previous researchers, however this study found that the increment of annual mean temperature is much higher in the Hills (1000 to 2000 m asl) than in the Terai and Mountain Regions. The temperature lapse rate in a wide altitudinal range of Nepal (70 to 5050 m asl) is -5.65 °C km-1. Warming rates in Terai and Trans-Himalayas (Jomsom) are 0.024 and 0.029 °C/year respectively.  

scholarly journals Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate

2016 ◽  
Vol 121 (20) ◽  
pp. 12,005-12,030 ◽  
Author(s):  
Lei Wang ◽  
Litao Sun ◽  
Maheswor Shrestha ◽  
Xiuping Li ◽  
Wenbin Liu ◽  
...  
Keyword(s):  
Air Temperature ◽  
Process Modeling ◽  
Surface Air Temperature ◽  
Lapse Rate ◽  
Near Surface ◽  
Temperature Lapse Rate

scholarly journals Near-Surface Air Temperature Lapse Rate Over Complex Terrain in the Southern Ecuadorian Andes: Implications for Temperature Mapping

2016 ◽  
Vol 48 (4) ◽  
pp. 673-684 ◽  
Author(s):  
Mario Córdova ◽  
Rolando Célleri ◽  
Cindy J. Shellito ◽  
Johanna Orellana-Alvear ◽  
Andrés Abril ◽  
...  
Keyword(s):  
Air Temperature ◽  
Complex Terrain ◽  
Surface Air Temperature ◽  
Lapse Rate ◽  
Near Surface ◽  
Temperature Lapse Rate ◽  
Temperature Mapping

scholarly journals Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC<sup>4</sup>RS and DISCOVER-AQ airborne campaigns

2017 ◽  
Vol 10 (8) ◽  
pp. 3085-3104 ◽  
Author(s):  
Min Huang ◽  
Gregory R. Carmichael ◽  
James H. Crawford ◽  
Armin Wisthaler ◽  
Xiwu Zhan ◽  
...  
Keyword(s):  
Case Studies ◽  
Air Temperature ◽  
Initial Conditions ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Heat Fluxes ◽  
Aircraft Observation ◽  
Near Surface ◽  
Boundary Layer Height ◽  
Small Scales

Abstract. Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ∼ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

scholarly journals An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern United States: observational-based analysis of surface temperature

2016 ◽  
Vol 16 (10) ◽  
pp. 6475-6494 ◽  
Author(s):  
Jianglong Zhang ◽  
Jeffrey S. Reid ◽  
Matthew Christensen ◽  
Angela Benedetti
Keyword(s):  
United States ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Cooling Efficiency ◽  
Surface Cooling ◽  
Near Surface ◽  
Smoke Aerosol ◽  
Weather Forecasts ◽  
Air Temperatures ◽  
Daily Changes

Abstract. A major continental-scale biomass burning smoke event from 28–30 June 2015, spanning central Canada through the eastern seaboard of the United States, resulted in unforecasted drops in daytime high surface temperatures on the order of 2–5  °C in the upper Midwest. This event, with strong smoke gradients and largely cloud-free conditions, provides a natural laboratory to study how aerosol radiative effects may influence numerical weather prediction (NWP) forecast outcomes. Here, we describe the nature of this smoke event and evaluate the differences in observed near-surface air temperatures between Bismarck (clear) and Grand Forks (overcast smoke), to evaluate to what degree solar radiation forcing from a smoke plume introduces daytime surface cooling, and how this affects model bias in forecasts and analyses. For this event, mid-visible (550 nm) smoke aerosol optical thickness (AOT, τ) reached values above 5. A direct surface cooling efficiency of −1.5 °C per unit AOT (at 550 nm, τ550) was found. A further analysis of European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), United Kingdom Meteorological Office (UKMO) near-surface air temperature forecasts for up to 54 h as a function of Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target AOT data across more than 400 surface stations, also indicated the presence of the daytime aerosol direct cooling effect, but suggested a smaller aerosol direct surface cooling efficiency with magnitude on the order of −0.25 to −1.0 °C per unit τ550. In addition, using observations from the surface stations, uncertainties in near-surface air temperatures from ECMWF, NCEP, and UKMO model runs are estimated. This study further suggests that significant daily changes in τ550 above 1, at which the smoke-aerosol-induced direct surface cooling effect could be comparable in magnitude with model uncertainties, are rare events on a global scale. Thus, incorporating a more realistic smoke aerosol field into numerical models is currently less likely to significantly improve the accuracy of near-surface air temperature forecasts. However, regions such as eastern China, eastern Russia, India, and portions of the Saharan and Taklamakan deserts, where significant daily changes in AOTs are more frequent, are likely to benefit from including an accurate aerosol analysis into numerical weather forecasts.

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

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1561 ◽  
Author(s):  
Bhanu Pratap ◽  
Parmanand Sharma ◽  
Lavkush Patel ◽  
Ajit T. Singh ◽  
Vinay Kumar Gaddam ◽  
...  
Keyword(s):  
Air Temperature ◽  
Arid Zone ◽  
Summer Precipitation ◽  
Western Himalaya ◽  
Surface Melting ◽  
Phase Changes ◽  
Lapse Rate ◽  
Glacier Surface ◽  
Near Surface ◽  
Temperature Lapse Rate

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.

scholarly journals A Comparison of Methods for Filling Gaps in Hourly Near-Surface Air Temperature Data

2013 ◽  
Vol 14 (3) ◽  
pp. 929-945 ◽  
Author(s):  
Brian Henn ◽  
Mark S. Raleigh ◽  
Alex Fisher ◽  
Jessica D. Lundquist
Keyword(s):  
Missing Data ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Accurate Method ◽  
Temperature Data ◽  
Lapse Rate ◽  
Horizontal Distance ◽  
Method Performance ◽  
Near Surface ◽  
Temperature Observations

Abstract Near-surface air temperature observations often have periods of missing data, and many applications using these datasets require filling in all missing periods. Multiple methods are available to fill missing data, but the comparative accuracy of these approaches has not been assessed. In this comparative study, five techniques were used to fill in missing temperature data: spatiotemporal correlations in the form of empirical orthogonal functions (EOFs), time series diurnal interpolation, and three variations of lapse rate–based filling. The method validation used sets of hourly surface temperature observations in complex terrain from five regions. The most accurate method for filling missing data depended on the number of available stations and the number of hours of missing data. Spatiotemporal correlations using EOF reconstruction were most accurate provided that at least 16 stations were available. Temporal interpolation was the most accurate method when only one or two stations were available or for 1-h gaps. Lapse rate–based filling was most accurate for intermediate numbers of stations. The accuracy of the lapse rate and EOF methods was found to be sensitive to the vertical separation of stations and the degree of correlation between them, which also explained some of the regional differences in performance. Horizontal distance was less significantly correlated with method performance. From these findings, guidelines are presented for choosing a filling method based on the duration of the missing data and the number of stations.

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