Constant Lapse Research Articles

Growth and Breakdown of Kelvin–Helmholtz Billows in the Stable Atmospheric Boundary Layer

The development and breakdown of Kelvin–Helmholtz (KH) waves (billows) in the stable atmospheric boundary layer (SABL) and their impact on vertical transport of momentum and scalars have been examined utilizing large eddy simulations. These simulations are initialized with a vertically uniform geostrophic wind and a constant potential temperature lapse rate. An Ekman type of boundary layer develops, and an inflection point forms in the SABL, which triggers the KH instability (KHI). KHI develops with the kinetic energy (KE) in the KH billows growing exponentially with time. The subsequent onset of secondary shear instability along S-shaped braids leads to the turbulent breakdown of the KH billow cores and braids. The frictional ground surface tends to slow down the growth of KE near the surface, reduce the KH billow core depth, and likely suppress other types of secondary instability. KH billows induce substantial down-gradient transport of momentum and sensible heat, which can be further enhanced by the onset of secondary shear instability. Although the KHI-induced strong transport only lasts for around 10–20 min, it reduces vertical shear and stratification in the SABL, enhances surface winds, and results in a 2–3-fold increase in the SABL depth.

Generalized continuum methodologies in acoustics: Selected case studies

Three problems from acoustics theory are considered using both analytical and numerical methods. Each problem involves the use of a particular generalized continuum (GC) formulation. In the first, mechanical and thermal plane waves in gases wherein the specific internal energy is described by the modified internal energy model are analyzed; in the second, vertically-propagating acceleration waves in a dusty, constant lapse rate, atmosphere are investigated using the Laplace transform; and, in the third, dispersed shocks in gases wherein viscous stresses are described by the Stokesian fluid relation are examined under the traveling wave assumption. The presentation concludes with a listing of possible follow-on studies involving GC-based model systems.

The Snowline and 0°C Isotherm Altitudes During Precipitation Events in the Dry Subtropical Chilean Andes as Seen by Citizen Science, Surface Stations, and ERA5 Reanalysis Data

Understanding the variability of the snowline and the closely related 0°C isotherm during infrequent precipitation events in the dry Andes in Chile is fundamental for precipitation, snow cover, and discharge predictions. For instance, it is known that on the windward side of mountains, the 0°C isotherm can be several hundreds of meters lower than on the free air upwind counterpart, but little is understood about such effects in the Andes due to missing in situ evidence on the precipitation phase. To bridge this gap, 111 photographs of the snowline after precipitation events between 2011 and 2021 were gathered in the frame of a citizen science programme to estimate the snowline altitude. Since photographs of the mountain snowline are in good agreement with Sentinel-2 imagery, they have great potential to validate empirical snowline estimations. Using the snowline altitude from the photos, we evaluated different methods to estimate the snowline and 0°C isotherm altitude during precipitation events based on surface meteorological observations and ERA5 reanalysis data. We found a high correlation between the observed snowline altitude and the extrapolated 0°C isotherm based on constant lapse rates (−5.5 to −6.5°C km−1) applied to air temperature from single, near stations. However, uncertainty increases for distances >10 km. The results also indicate that the linear regression method is a good option to estimate ZSL, but the results strongly depend on the availability of high-elevation station datasets. During half of the precipitation events, the 0°C isotherm lies between ∼1,800 and ∼2,400–2,500 m asl. in winter, and the snowline is on average ∼280 m below this altitude. Our results indicate the presence of a mesoscale lowering of the 0°C isotherm over the windward slopes compared to the free-air upwind value during precipitation events and a possible isothermal layer of near-freezing air temperatures comparable to other mountain ranges. Due to this mesoscale and local behavior, ERA5 data generally overestimate the snow–rain transition in high-elevation areas, especially for relatively intense events. On the other hand, the 0°C isotherm altitude is underestimated if only low-elevation valley stations are considered, highlighting the importance of high-altitude meteorological stations in the network.

The Friedmann–Lemaître–Robertson–Walker metric

The Friedmann–Lemaître–Robertson–Walker (FLRW) metric used to describe the cosmic spacetime is based on the cosmological principle, which assumes homogeneity and isotropy throughout the Universe. It also adopts free-fall conditions via the selection of a constant lapse function, [Formula: see text], regardless of whether or not the chosen energy–momentum tensor [Formula: see text] produces an accelerated expansion. This is sometimes justified by arguing that one may shift the gauge, if necessary, transforming the time [Formula: see text] to a new coordinate [Formula: see text], thereby re-establishing a unitary value for [Formula: see text]. Previously, we have demonstrated that this approach is inconsistent with the Friedmann equations derived using comoving coordinates. In this paper, we advance this discussion significantly by using the Local Flatness Theorem in general relativity to prove that [Formula: see text] in FLRW is inextricably dependent on the expansion dynamics via the expansion factor [Formula: see text], which itself depends on the equation-of-state in [Formula: see text]. One is therefore not free to choose [Formula: see text] arbitrarily without ensuring its consistency with the energy–momentum tensor. We prove that the use of FLRW in cosmology is valid only for zero active mass, i.e. [Formula: see text], where [Formula: see text] and [Formula: see text] are, respectively, the total energy density and pressure in the cosmic fluid.

Correctly applying lapse rates in ecological studies: comparing temperature observations and gridded data in Yellowstone

AbstractResearchers often use gridded datasets to develop statistical relationships between climate and natural resources at locations that are distant from weather stations. These gridded datasets may provide inaccurate estimates of temperature at sites with elevations that differ significantly from the elevation assigned to the corresponding grid cell. We assess the accuracy of three gridded climate datasets commonly used in ecological studies (800‐m resolution PRISM, 4‐km GRIDMET, and 1‐km Daymet) compared with a network of 153 temperature dataloggers arranged along elevation transects in Yellowstone National Park (Wyoming, Montana, Idaho). Measured lapse rates for monthly average daytime high temperatures were generally steeper (more cooling per unit of elevation increase) than lapse rates in gridded datasets and steeper than those in similar mountainous regions. Measured lapse rates for monthly average nighttime lows were similar to gridded data lapse rates. Our measured lapse rates are most useful for the adjustment of daytime highs from weather stations or gridded data during warmer months. Temperatures during cooler months sometimes are strongly affected by other factors. Ecologically relevant metrics calculated from temperatures adjusted with constant lapse rates can increase multiplicatively and by varying amounts from year to year. For example, high‐elevation estimates of climatic water deficit (CWD) calculated from gridded data that were not adjusted with our measured lapse rates were 2.5–4 times greater (depending on the year) than calculations from temperatures that were adjusted. Our results emphasize the importance of correcting grid‐based climate estimates for elevation in complex terrain when accurate, site‐specific data are required. When the elevation assigned to grid cells differs significantly from the elevation of points within the cell, the lapse rate obtained for data extracted from grids can be shallower than the true rate. We illustrate the implications of these findings with case studies in Yellowstone.

A Mountain‐Front Recharge Component Characterization Approach Combining Groundwater Age Distributions, Noble Gas Thermometry, and Fluid and Energy Transport Modeling

AbstractMountain‐front recharge (MFR), or all inflow to a basin‐fill aquifer with its source in the mountain block, is an important component of recharge to basin‐fill aquifer systems. Distinguishing and quantifying the surface from subsurface components of MFR is necessary for water resource planning and management, particularly as climate change may impact these components in distinct ways. This study tests the hypothesis that MFR components can be distinguished in long‐screened, basin‐fill production wells by (1) groundwater age and (2) the median elevation of recharge. We developed an MFR characterization approach by combining age distributions in six wells using tritium, krypton‐85, argon‐39, and radiocarbon, and median recharge elevations from noble gas thermometry combined with numerical experiments to determine recharge temperature lapse rates using flow and energy transport modeling. We found that groundwater age distributions provided valuable information for characterizing the dominant flow system behavior captured by the basin‐fill production wells. Tracers indicated the presence of old (i.e., no detectable tritium) water in a well completed in weathered bedrock located close to the mountain front. Two production wells exhibited age distributions of binary mixing between modern and a small fraction of old water, whereas the remaining wells captured predominantly modern flow paths. Noble gas thermometry provided important complementary information to the age distributions; however, assuming constant recharge temperature lapse rates produced improbable recharge elevations. Numerical experiments suggest that surface MFR, if derived from snowmelt, can locally suppress water table temperatures in the basin‐fill aquifer, with implications for recharge elevations estimated from noble gas thermometry.

Evaluation of corrected APHRODITE estimates for hydrological simulation in the Yarlung Tsangpo–Brahmaputra River Basin

AbstractPrecipitation is one of the most important inputs for hydrological simulation because it controls water balance, and accurate representation of rainfall distribution is essential for hydrological simulation. In the Yarlung Tsangpo–Brahmaputra River Basin (YBRB), gauge‐based gridded datasets have difficulties in representing complex orographic precipitation as the rainfall stations are too sparse to capture accurate precipitation patterns. This study used Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) estimates to drive the Soil and Water Assessment Tool (SWAT) model in the YBRB. Bias correction on APHRODITE estimates was achieved through linear scaling based on a denser network of gauges. In addition, the elevation bands method was implemented in SWAT to reproduce spatial precipitation by considering orographic effects. The results showed that original APHRODITE data tended to systematically underestimate rainy season precipitation with considerable underestimation on windward slopes of the Himalayas. Corrected APHRODITE data increased precipitation estimates and were able to better represent the spatial patterns of precipitation. During the calibration and validation periods, the mean monthly Nash–Sutcliffe efficiency (NSE) of the corrected APHRODITE‐simulation were 0.86 and 0.82, respectively, which were much higher than those of the original APHRODITE‐simulation (0.79 and 0.72), indicating the reliability of corrected APHRODITE estimates in driving hydrological model. In addition, although the elevation bands method has some limitations induced by the constant precipitation lapse rate, it was also found that this method could improve the accuracy of hydrological simulation. In large transboundary sparsely gauged river basins, implementation of bias correction and elevation bands can improve the representation of spatial precipitation of gridded gauge‐based rainfall products, which may be beneficial for hydrological simulation and water resources management.

Quantifying the Congruence between Air and Land Surface Temperatures for Various Climatic and Elevation Zones of Western Himalaya

The surface and near-surface air temperature observations are primary data for glacio-hydro-climatological studies. The in situ air temperature (Ta) observations require intense logistic and financial investments, making it sparse and fragmented particularly in remote and extreme environments. The temperatures in Himalaya are controlled by a complex system driven by topography, seasons, and cryosphere which further makes it difficult to record or predict its spatial heterogeneity. In this regard, finding a way to fill the observational spatiotemporal gaps in data becomes more crucial. Here, we show the comparison of Ta recorded at 11 high altitude stations in Western Himalaya with their respective land surface temperatures (Ts) recorded by Moderate Resolution Imagining Spectroradiometer (MODIS) Aqua and Terra satellites in cloud-free conditions. We found remarkable seasonal and spatial trends in the Ta vs. Ts relationship: (i) Ts are strongly correlated with Ta (R2 = 0.77, root mean square difference (RMSD) = 5.9 °C, n = 11,101 at daily scale and R2 = 0.80, RMSD = 5.7 °C, n = 3552 at 8-day scale); (ii) in general, the RMSD is lower for the winter months in comparison to summer months for all the stations, (iii) the RMSD is directly proportional to the elevations; (iv) the RMSD is inversely proportional to the annual precipitation. Our results demonstrate the statistically strong and previously unreported Ta vs. Ts relationship and spatial and seasonal variations in its intensity at daily resolution for the Western Himalaya. We anticipate that our results will provide the scientists in Himalaya or similar data-deficient extreme environments with an option to use freely available remotely observed Ts products in their models to fill-up the spatiotemporal data gaps related to in situ monitoring at daily resolution. Substituting Ta by Ts as input in various geophysical models can even improve the model accuracy as using spatially continuous satellite derived Ts in place of discrete in situ Ta extrapolated to different elevations using a constant lapse rate can provide more realistic estimates.

Near surface air temperature lapse rates over complex terrain: a WRF based analysis of controlling factors and processes for the central Himalayas

Various environmental processes are strongly controlled by spatio-temporal variations of surface air temperature (hereafter temperature) in complex terrain. However, the usually scarce network of observations in high mountain regions does not allow for an investigation of the relevant micro-meteorological processes that result in complex temperature fields. Climate impact studies often utilize a constant lapse rate of temperature (LRT hereafter) in order to generate spatially distributed temperature data, although it is well acknowledged that LRTs feature a pronounced variability at spatial, seasonal, and diurnal scales. In this study, the Weather Research and Forecasting (WRF) model is used to understand the factors and processes influencing temperature and LRT in the Khumbu and Rolwaling regions of the central Himalayas. A high resolution simulation is performed for one complete year (June 2014–May 2015) in order to capture the entire seasonal cycle. To test the model response to land cover and terrain characteristics, additional simulations with adjusted surface conditions are conducted. Our results demonstrate the capability of WRF to reproduce the processes controlling LRT, although an LRT bias is detected during non-monsoon seasons. The simulated temperature fields feature two LRT minima (i.e. low temperature decrease with elevation) during Nov–Dec and monsoon season, and two LRT maxima (strong temperature decrease with elevation) during the early post-monsoon and pre-monsoon seasons. A steeper LRT (i.e. a rapid decrease of temperature with elevation) is found at high elevations (> 4500 m) while shallower LRT values (i.e. a slower decrease or even increase of temperature with elevation) are apparent at lower elevations. During the pre-monsoon season, high net insolation rates and a reduced latent heat loss from snow free surfaces cause strong sensible heating at low elevations, while the presence of snow at high elevations leads to reduced sensible heating. This strong contrast results in steeper LRT values. Early post-monsoon shows similar characteristics but with a reduced magnitude. The shallow LRT during monsoon season is shown to be caused by the large-scale moisture supply and the associated latent heat release at the Himalayan slopes. This effect is further intensified due to strong up-valley winds which contribute to a well-mixed troposphere. Temperature inversions associated with cold air pooling cause shallow LRT values in lower river valleys during Nov–Dec. The results suggest that the identified processes should be considered for downscaling applications, particularly if distributed temperature fields are required for climate impact investigations.

Air Temperature Characteristics, Distribution, and Impact on Modeled Ablation for the South Patagonia Icefield

AbstractThe glaciers of Patagonia are the largest in South America and are shrinking rapidly, raising concerns about their contribution to sea level rise in the face of ongoing climatic change. However, modeling studies forecasting future glacier recession are limited by the scarcity of measured on‐glacier air temperatures and thus tend to use spatially and temporally constant lapse rates. This study presents 9 months of air temperature observations. The network consists of five automatic weather stations and three on‐glacier air temperature sensors installed on the South Patagonia Icefield along a transect at 48°45′S. Observed lapse rates are, overall, steeper on the east (−0.0072 °C/m) compared to the west (−0.0055 °C/m) and vary between the lower section (tongue, ablation zone) and the upper section (plateau, accumulation zone) of the glaciers. Warmer off‐glacier temperatures are found in the east compared to the west for similar elevations. However, on‐glacier observations suggest that the glacier cooling effect is higher in the east compared to the west. Through application of distributed temperature‐index and point‐scale energy balance models we show that modeled ablation rates vary by up to 60%, depending on the air temperature extrapolation method applied, and that melt is overestimated and sublimation is underestimated if the glacier cooling effect is not included in the distributed air temperature data. These results can improve current and future modeling efforts of the energy and mass balance of the whole South Patagonia Icefield.

Impact of summer monsoon on the elevation‐dependence of meteorological variables in the south of central Himalaya

ABSTRACTThe South Asian summer monsoon brings abundant precipitation and associated latent heat release to the south of central Himalaya, and alters hydrothermal conditions of this region. This study explored the impact of South Asian summer monsoon on the elevation‐dependence of meteorological variables along the south slope of Mt. Everest in the central Himalaya, which is crucial to modelling the glacio‐hydrological processes in this elevated region. The data were collected at five stations deployed at 2660–5600 m above sea level (asl) along the slope during 2007–2011. Major findings are the following: (1) The amount of precipitation during the monsoon season usually decreases with elevation but it is relatively uniform between 3600 and 5000 m asl. This uniform profile may be attributed to the monsoon–terrain–land interactions, particularly to the retard effect of glacier cooling on daytime upvalley wind; (2) Cloud shielding effects cause lower solar radiation and higher downward longwave radiation in the monsoon than in the other seasons. In particular, higher elevations have more clouds in the afternoon, resulting in an abnormal elevation‐dependence of solar radiation (i.e. higher elevations receive less solar radiation); (3) Strong daytime upvalley wind and moist convection homogenizes the vertical distributions of air mass along the slope, causing a constant lapse rate of both surface air temperature and dew‐point temperature (representing humidity) during typical monsoon months, but this phenomenon is not found in the other seasons. These findings provide critical guidance for extrapolating the meteorological variables from lower to higher elevations in this region.

Comparison of spatial interpolation methods for gridded bias removal in surface temperature forecasts

All numerical weather prediction (NWP) models inherently have substantial biases, especially in the forecast of near-surface weather variables. Statistical methods can be used to remove the systematic error based on historical bias data at observation stations. However, many end users of weather forecasts need bias corrected forecasts at locations that scarcely have any historical bias data. To circumvent this limitation, the bias of surface temperature forecasts on a regular grid covering Iran is removed, by using the information available at observation stations in the vicinity of any given grid point. To this end, the running mean error method is first used to correct the forecasts at observation stations, then four interpolation methods including inverse distance squared weighting with constant lapse rate (IDSW-CLR), Kriging with constant lapse rate (Kriging-CLR), gradient inverse distance squared with linear lapse rate (GIDS-LR), and gradient inverse distance squared with lapse rate determined by classification and regression tree (GIDS-CART), are employed to interpolate the bias corrected forecasts at neighboring observation stations to any given location. The results show that all four interpolation methods used do reduce the model error significantly, but Kriging-CLR has better performance than the other methods. For Kriging-CLR, root mean square error (RMSE) and mean absolute error (MAE) were decreased by 26% and 29%, respectively, as compared to the raw forecasts. It is found also, that after applying any of the proposed methods, unlike the raw forecasts, the bias corrected forecasts do not show spatial or temporal dependency.

Atmospheric Refraction Predictions Based on Actual Atmospheric Pressure and Temperature Data

Calculations of atmospheric refraction are generally based on a simplified model of atmospheric density in the troposphere that assumes the temperature decreases at a constant lapse rate L from sea level up to a height , and that afterward it remains constant. In this model, the ratio To/L, where To is the temperature at the observer’s location, determines the length scale in the calculations for altitudes . But daily balloon measurements across the USA show that in some cases there is an inversion so that the air temperature actually increases from sea level up to a height , and only after reaching a plateau with temperature at this height, it decreases at an approximately constant lapse rate. Hence, in such cases the relevant length scale for atmospheric refraction calculations in the range is , and the contribution for has to be calculated from actual measurements of air density in this range. Moreover, in three examples considered here, the temperature does not remain constant for , but continues to decreases to a minimum at , and then increases at higher altitudes at a lower rate. Calculations of atmospheric refraction based on this actual atmospheric data are compared with the results of current simplified models.

On static solutions of the Einstein-Scalar Field equations

In this article we study self-gravitating static solutions of the Einstein-Scalar Field system in arbitrary dimensions. We discuss the existence of geodesically complete solutions depending on the form of the scalar field potential \(V(\phi )\), and provide full global geometric estimates when the solutions exist. The most complete results are obtained for the physically important Klein–Gordon field and are summarised as follows. When \(V(\phi )=m^{2}|\phi |^{2}\), it is proved that geodesically complete solutions have Ricci-flat spatial metric, have constant lapse and are vacuum, (that is \(\phi \) is constant and equal to zero if \(m\ne 0\)). In particular, when the spatial dimension is three, the only such solutions are either Minkowski or a quotient thereof (no nontrivial solutions exist). When \(V(\phi )=m^{2}|\phi |^{2}+2\Lambda \), that is, when a vacuum energy or a cosmological constant is included, it is proved that no geodesically complete solution exists when \(\Lambda >0\), whereas when \(\Lambda <0\) it is proved that no non-vacuum geodesically complete solution exists unless \(m^{2}<-2\Lambda /(n-1)\), (n is the spatial dimension) and the spatial manifold is non-compact. The proofs are based on novel techniques in comparison geometry a la Bakry-Emery that have their own interest.

Combining thin-plate spline interpolation with a lapse rate model to produce daily air temperature estimates in a data-sparse alpine catchment

Insufficient availability of weather stations recording air temperature is a common problem in many alpine regions. The low station density combined with the high variability of air temperature means that interpolated fields based on simple or more complex interpolation techniques are unlikely to be representative of the real patterns of air temperature. In this study, a novel method was developed to tackle this problem, following initial investigation of lapse rate variability in the study domain: the alpine Clutha catchment, New Zealand. Owing to a series of complexities in lapse rate variability, a multi-layer approach was adopted to produce 1 km2 daily fields of maximum (Tmax) and minimum air temperature (Tmin). The first layer of the Tmax and Tmin models was calculated using a trivariate thin-plate spline, which was constrained to the elevations of the continuous network to avoid unrealistic extrapolation. To compensate for missing continuous high elevation records, two lapse rate models were implemented to scale air temperature above the first layer. The two lapse rate models were based on the dominant processes driving lapse rate variation, which were found to be cold air ponding (Tmin) and spatial differences in relative humidity (Tmax). Independent station records were used to assess accuracy and compare the resultant fields to an existing product (the Virtual Climate Station Network) and a more conventional method based on a bivariate spline and a constant lapse rate. The validation revealed that the new methods developed here have led to a substantial improvement in producing spatial estimates of Tmax, with a mean root mean square error (RMSE) of 2.38 °C, while progress in regard to Tmin was more limited (mean RMSE of 2.93 °C). As such, this work demonstrates that inclusion of the driving processes controlling lapse rates in interpolation routines can lead to improvements in accuracy.

Simple equations for temperature simulations on mid-latitude volcanic islands: a case study from Jeju (Republic of Korea)

Volcanic islands can be characterized by remarkable surface air temperature variability. The distribution of weather stations in these settings, however, is typically too sparse to reliably describe temperature patterns which can complicate regional-scale hydrologic analyses. Here, a simple method is presented to estimate near surface air temperatures for such a setting (Jeju Island, Republic of Korea). The method utilizes temperature lapse rates (TLR; the change in temperature with elevation) which are computed for Tmin, Tave, and Tmax for two distinct hemispheres: the more arid northern flanks and the more humid southern flanks of the central orographic divide. Computed TLRs vary greatly with season and location relative to the orographic divide and, unlike in continental mountainous settings, are generally highest for Tmin in winter. Cross-validation results indicate a good match between modeled and measured values particularly for high altitude stations that are characterized by highest precipitation rates. Because temporally changing TLRs perform better than the often applied theoretical constant environmental lapse rate of 6.5 °C/km, monthly mean TLRs compiled from temperature data from Jeju Island are presented here as proxies for surface air temperature simulation efforts in similar settings for which only limited climatic data are available.

Effects of Temperature Forcing Provenance and Extrapolation on the Performance of an Empirical Glacier-Melt Model

Temperature-index models are popular tools for glacier melt-modeling due to their minimal data requirements and generally favorable performance. We examine the effects of temperature forcing provenance and extrapolation on the performance of one such model applied to a small glacier in the Saint Elias Mountains of northwestern Canada. The model is forced with air temperatures recorded (a) on two glaciers, (b) at two nearby ice-free locations, and (c) by two low-elevation valley stations. We extrapolate these temperatures using constant lapse rates and assess model performance by comparing measured and modeled cumulative summer ablation at a network of stakes over five melt seasons. When the model is calibrated individually for each temperature forcing and lapse rate, the variation in model performance is modest relative to inter-annual variations associated with melt-season conditions and calibration data quality. Despite <30% variation in estimated summer ablation arising from the combined influences of temperature forcing and lapse rate, the resulting variations in estimated annual mass balance can be significant (>100% in some cases). While model parameters calibrated in this way suffer from error compensation and exhibit equifinality, the lapse rates associated with minimum model error exhibit inter-annual variation that can be related to prevailing meteorological conditions. When the model is instead calibrated at the point scale without employing a lapse rate, and the resulting parameters are paired with an arbitrary temperature forcing, lapse rates associated with minimum model error vary widely between forcing types and years. Low-elevation stations distal from the study site sometimes outperform the calibration station, but the prescribed lapse rate becomes critical in this case. With either calibration method, lapse rates that minimize model error for the valley stations are generally steeper than the measured environmental lapse rates.

Comparison of surface air temperature derived from NCEP/DOE R2, ERA-Interim, and observations in the arid northwestern China: a consideration of altitude errors

The surface air temperatures measured at 68 meteorological stations in the arid northwestern China during 1979–2012 are compared with temperatures interpolated from the National Centers for Environmental Prediction/Department of Energy (NCEP/DOE) Reanalysis 2 (NCEP R2) and the European Center for Medium-Range Weather Forecasts ERA-Interim. The altitude effects on reanalysis temperature errors are discussed, and the interpolated reanalysis data are calibrated by altitude errors between reanalysis and observation. Using a simple correction method with a constant lapse rate, the elevation-related errors can be greatly removed and an improvement is achieved for the interpolated temperature from both NCEP R2 and ERA-Interim. The cold bias of reanalysis data becomes weak after calibration. On an annual basis, root mean square error of temperature derived from NCEP R2 for each stations has decreased from 6.0 (raw data) to 2.6 °C (calibrated data) and that from ERA-Interim has decreased from 3.2 to 1.4 °C. Similarly, correlation coefficients between raw reanalysis-based and observed temperature are 0.191 and 0.709 for NCEP R2 and ERA-Interim, respectively, whereas the correlation coefficients using the calibrated annual data are 0.819 and 0.932 for NCEP R2 and ERA-Interim, respectively. Generally, ERA-Interim is closer to the ground-based observations than NCEP R2. The topographic correction is more effective in summer than in winter, which may be related to the temperature inversion in winter. Evaluation and correction of reanalysis datasets is a crucial work before the gridded data are applied in climate research, and the altitude-related errors should be calibrated especially in the regions with complex topography.

Evaluation of LPM permafrost distribution in NE Asia reconstructed and downscaled from GCM simulations

A high‐resolution map of potential frozen ground distribution in NE Asia (90–150°E, 25–60°N) at the period of the Last Permafrost Maximum (LPM, c. 21 000 years ago) was dually reconstructed by means of a statistical classification using air freezing and thawing indices and a topographical downscaling using a digital relief model (ETOPO1). Background LPM climate data were derived from global climate model simulations of the Paleoclimate Model Intercomparison Project, Phase II (PMIP2). The reconstructed LPM map shows the southward shift of the southern limit of climate‐driven permafrost by 400–1500 km, with the greatest advance in the western sector (90–110°E), encompassing an area from central Siberia to most of the Altai area. The advance of environmentally conditional permafrost and seasonally frozen ground was greatest in the eastern sector (110–150°E), with an average shift of about 450 km. The descent of the lower limit of LPM alpine permafrost was in the range of 400–800 m. A comparison of the reconstructed map with published literature shows that this method, simplistically constructed yet effectively recognizing seasonality, continentality and topography, captures local features better than more elaborate methods. The sensitivity examination of a constant atmospheric lapse rate shows that altitudes of 2000–5000 m a.s.l. were most sensitive, though with only a limited effect on overall LPM distribution.

A new approach to retrieve cloud base height of marine boundary layer clouds

AbstractA novel approach for estimating marine boundary layer cloud base height (CBH) is proposed based on calculated boundary layer lapse rates, collocated cloud top height (CTH), cloud top, and ocean surface temperatures from the A‐Train satellite constellation. The method takes advantage of the assumption that decreases of temperature within and below water clouds may follow the different constant apparent lapse rates in the same region, respectively. The CBHs derived from the new method compare well with the coincident CBH product from the active sensors of Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat. The correlation coefficient, the mean difference, and the standard deviation are 0.79 (0.54), 0.02 km (0.03 km), and ±0.35 km (±0.54 km), respectively, when CTH is derived from CALIPSO data (or Moderate Resolution Imaging Spectroradiometer retrieval). Besides the relatively small bias, the most important advantage of this method compared to previous CBH retrieval techniques is that it is independent of boundary layer cloud types, optical thickness, and illumination.