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NASA NTRS2019

Investigating Sources of Variability and Error in Simulations of Carbon Dioxide in an Urban Region

Greenhouse gas (GHG) emissions estimation methods that use atmospheric trace gas observations, including inverse modeling techniques, perform better when carbon dioxide (CO2) fluxes are more accurately transported and dispersed in the atmosphere by a numerical model. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric CO2 from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations).

CO2↗

NASA NTRS2023

Sustainable Development in Algeria’s Urban Areas: Population Growth and Land Consumption

We analyzed the urban development sustainability in five major urban areas of Algeria by the standard of the UN Sustainability Development Goal indicator SDG 11.3.1, which focuses on the ratio of land consumption rate to population growth rate. We utilized the annual global artificial impervious area (GAIA) dataset to characterize land-use and population data from the two censuses carried out by the National Office of Statistics (ONS) for 2008 and 2018. We discuss the prevailing relationship between urban land consumption rate and population growth rate at the smallest territorial and population census unit scale. We confirm that the indicator SDG 11.3.1 is nonlinear and that while, for example, the wilaya of Tlemcen as a whole appears to be on a sustainable path, twenty-one of its communes are not. We found that overall, and for most of its communes, the wilaya of Oran seems to have an urban land use commensurable to its population growth, but in the wilaya of Algiers, out of fifty-seven communes, only fourteen have a tendency towards sustain-able development. However, the latter wilaya hosts the country’s capital and includes government buildings that are uninhabited but are accounted for as land consumed, and as such, the relationship between urban land consumption and population growth is biased. The wilaya of Annaba showed large discrepancies in terms of land use and population growth rates, and the evolution of these quantities is not homogenous across communes and not sustainable. In the Saharan wilaya of Ghardaia, the development is not homogeneous in all communes, with smaller communes undergoing buildup increases of more than 150% over the decade. Finally, in all communes where population growth exceeded urban land growth, there will be overcrowding, an aspect neither the SDG 11.3.1 nor the impervious surface per capita indicator captures. This result, in addition to other limitations, makes SDG 11.3.1 incomplete for the determination of the sustainable development in urban areas.

Algeria↗

DOE OSTI2022

Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions

Abstract Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Understanding the Influence of Urban Form on the Spatial Pattern of Precipitation

Urban areas are known to modify the spatial pattern of precipitation climatology. Existing observational evidence suggests that precipitation can be enhanced downwind of a city. Among the proposed mechanisms, the thermodynamic and aerodynamic processes in the urban lower atmosphere interact with the meteorological conditions and can play a key role in determining the resulting precipitation patterns. In addition, these processes are influenced by urban form, such as the impervious surface extent. This study aims to unravel how different urban forms impact the spatial patterns of precipitation climatology under different meteorological conditions. We use the Multi-Radar Multi-Sensor quantitative precipitation estimation data products and analyze the hourly precipitation maps for 27 selected cities across the continental United States from the years 2015–2021 summer months. Results show that about 80% of the studied cities exhibit a statistically significant downwind enhancement of precipitation. Additionally, we find that the precipitation pattern tends to be more spatially clustered in intensity under higher wind speed; the location of radial precipitation maxima is located closer to the city center under low background winds but shifts downwind under high wind conditions. The magnitude of downwind precipitation enhancement is highly dependent on wind directions and is positively correlated with the city size for the south, southwest, and west directions. This study presents observational evidence through a cross-city analysis that the urban precipitation pattern can be influenced by the urban modification of atmospheric processes, providing insight into the mechanistic link between future urban land-use change and hydroclimates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Going mobile to address emerging climate equity needs in the heterogeneous urban environment

We report the Brookhaven National Laboratory Center for Multiscale Applied Sensing (CMAS) aims to address environmental equity needs in the context of a changing climate. As a first step towards this goal, the center developed a one-of-a-kind observatory tailored to the study of highly heterogeneous urban environments. This article describes the features of the mobile observatory that enable its rapid deployment either on or off the power grid, as well as its instrument payload. Beyond its unique design, the observatory optimizes data collection within the obstacle-laden urban environment using a new smart sampling paradigm. This setup facilitated the collection of previously poorly documented environmental properties including wind profiles throughout the atmospheric column. The mobile observatory captured unique observations during its first few intensive observation periods (IOPs).. Vertical air motion and infrared temperature measurements collected along the faces of the supertall One Vanderbilt skyscraper in Manhattan, NY reveal how solar and anthropogenic heating affect wind flow and thus the venting of heat, pollution, and contaminants in urban street canyons. Also, air temperature measurements collected during travel along a 150-km transect between Upton and Manhattan, NY offer a high-resolution view of the urban heat island and reveal that temperature disparities also exist within the city across different neighborhoods. Ultimately, the datasets collected by CMAS are poised to help guide equitable urban planning by highlighting existing disparities and characterizing the impact of urban features on the urban microclimate with the goal of improving human comfort.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Determinants of rural-urban differences in health care provider visits among women of reproductive age in the United States

Background Rural health disparities and access gaps may contribute to higher maternal and infant morbidity and mortality. Understanding and addressing access barriers for specialty women’s health services is important in mitigating risks for adverse childbirth events. The objective of this study was to investigate rural-urban differences in health care access for women of reproductive age by examining differences in past-year provider visit rates by provider type, and quantifying the contributing factors to these findings. Methods and findings Using a nationally-representative sample of reproductive age women (n = 37,026) from the Medical Expenditure Panel Survey (2010–2015) linked to the Area Health Resource File, rural-urban differences in past-year office visit rates with health care providers were examined. Blinder-Oaxaca decomposition analysis quantified the portion of disparities explained by individual- and county-level sociodemographic and provider supply characteristics. Overall, there were no rural-urban differences in past-year visits with women’s health providers collectively (65.0% vs 62.4%), however differences were observed by provider type. Rural women had lower past-year obstetrician-gynecologist (OB-GYN) visit rates than urban women (23.3% vs. 26.6%), and higher visit rates with family medicine physicians (24.3% vs. 20.9%) and nurse practitioners/physician assistants (NPs/PAs) (24.6% vs. 16.1%). Lower OB-GYN availability in rural versus urban counties (6.1 vs. 13.7 providers/100,000 population) explained most of the rural disadvantage in OB-GYN visit rates (83.8%), and much of the higher family physician (80.9%) and NP/PA (50.1%) visit rates. Other individual- and county-level characteristics had smaller effects on rural-urban differences. Conclusion Although there were no overall rural-urban differences in past-year visit rates, the lower OB-GYN availability in rural areas appears to affect the types of health care providers seen by women. Whether rural women are receiving adequate specialized women’s health care services, while seeing a different cadre of providers, warrants further investigation and has particular relevance for women experiencing high-risk pregnancies and deliveries.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1984

Methane concentrations and source strengths in urban locations

The results of a six year measurement of trace gases in 18 different urban and remote areas throughout the Northern and Southern Hemispheres are reported. It is found that the measurements are consistent with a yearly atmospheric release of 30 to 60 megatons of CH4 in urban environments. Concentrations of CCl3F, CCl2F2, and CH3CCl3 were also found to be higher in the same urban samples than in corresponding samples from remote areas. The 'urban excess' (urban concentration minus remote concentration) was generally 1000 to 2000 times larger on a molar basis for CH4 than for CCl3F. The fraction of world-wide methane release occurring in the urban environment is estimated from the concentration ratios for CH4 vs CCl3F. It is shown that about 8 to 15 percent of atmospheric methane release occurs in urban areas.

Blake, D. R.↗

NASA NTRS1992

AVIRIS data and neural networks applied to an urban ecosystem

Urbanization is expanding on every continent. Although urban/industrial areas occupy a small percentage of the total landscape of the earth, their influence extends far beyond their borders, affecting terrestrial, aquatic, and atmospheric systems globally. Yet little has been done to characterize urban ecosystems of their linkages to other systems horizontally or vertically. With remote sensing we now have the tools to characterize, monitor, and model urban landscapes world-wide. However, the remote sensing performed on cities so far has concentrated on land-use patterns as distinct from land-cover or composition. The popular Anderson system is entirely land-use oriented in urban areas. This paper begins with the premise that characterizing the biophysical composition of urban environments is fundamental to understanding urban/industrial ecosystems, and, in turn, supports the modeling of other systems interfacing with urban systems. Further, it is contended that remote sensing is a tool poised to provide the biophysical composition data to characterize urban landscapes.

Ridd, Merrill K.↗

NASA NTRS1998

Urban Environment Initiative

The Urban Environment Initiative (UEI), has been established as part of a Cooperative Agreement with the National Aeronautics and Space Administration (NASA). The UEI is part of NASA's overall High Performance Computing and Communications (HPCC) and the Information Infrastructure Technology Applications (IITA) programs. The goal of the UEI is to provide public access to Earth Science information and promote its use with a focus on the environment of urban areas. This goal will be accomplished through collaborative efforts of the UEI team with both community-based and local/regional governmental organizations. The UEI team is comprised of four organizations representing private industry, NASA, and universities: Prime Technologies Service Corporation, NASA's Minority University Space Interdisciplinary Network (MU-SPIN) California State University, at Los Angeles, and Central State University (Wilberforce, OH). "Urban Environment" refers to the web of environmental, economic, and social factors that combine to create the urban world in which we live. Examples of these factors are population distribution, neighborhood demographic profiles, economic resources, business activities, location and concentration of environmental hazards and various pollutants, proximity and level of urban services, which form the basis of the urban environment and ultimately affect our lives and experiences. The use of Geographic Information Systems (GIS) and remote sensing allows data to be visualized in the forms of maps and spatial images. The use of these tools allow analysis of information about urban environments. Also included are descriptions of the four query types which will assist in understanding the maps.

Source record↗

NASA NTRS2001

Remote Sensing of the Urban Heat Island Effect: Assessment of Risks to Human Health and Development of Mitigation Strategies for Sustainable Cities

The growth of cities, both in population and in areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80% of the world's population will live in cities. One of the more egregious side effects of urbanization is the deterioration in air quality as a result of increased vehicular traffic, industrialization and related activities. In the United States alone, under the more stringent air quality guidelines established by the U.S. Environmental Protection Agency (EPA) in 1997, nearly 300 counties in 34 states will not meet the new air quality standards for ground level ozone. The mitigation of one the physical/environmental characteristics of urbanization known as the urban heat island (UHI) effect, is now being looked at more closely as a possible way to bring down ground level ozone levels in cities and assist states in improving air quality. The UHI results from the replacement of "natural" land covers (e.g., trees, grass) with urban land surface types, such as pavement and buildings. Heat stored in these surfaces is released into the air and results in a "dome" of elevated air temperatures that presides over cities. The effect of this dome of elevated air temperatures is known as the UHI, which is most prevalent about 2-3 hours after sunset on days with intense solar radiation and calm winds. Given the local and regional impacts of the UHI, there are significant potential affects on human health, particularly as related to heat stress and ozone on body temperature regulation and on the cardiovascular and respiratory systems. In this study we are using airborne and satellite remote sensing data to analyze how differences in the urban landscape influence or drive the development of the UHI over four U.S. cities. Additionally, we are assessing what the potential impact is on risks to human health, and developing mitigation strategies to make urban areas more environmentally sustainable.

Quattrochi, Dale A.↗

NASA NTRS2001

An Investigation of the Influence of Urban Areas on Rainfall Using a Cloud-Mesoscale Model and the TRMM Satellite

A recent paper by Shepherd and Pierce (conditionally accepted to Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. A convective-mesoscale model with extensive land-surface processes is employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. Early analysis suggests that urban surface roughness (through turbulence and low-level convergence) may control timing and initial location of UHI-induced convection. The magnitude of the heat island appears to be closely linked to the total rainfall amount with minor impact on timing and location. The physical size of the city may predominantly impact on the location of UHI-induced rainfall anomaly. The UHI factor parameter space will be thoroughly investigated with respect to their effects on rainfall amount, location, and timing. This study extends prior numerical investigations of the impact of urban surfaces on meteorological processes, particularly rainfall development. The work also contains several novel aspects, including the application of a high-resolution (less than I km) cloud-mesoscale model to investigate urban-induce rainfall process; investigation of thermal magnitude of the UHI on rainfall process; and investigation of UHI physical size on rainfall processes.

Shepherd, J. Marshall↗

NASA NTRS2001

Spectral Dimensionality and Scale of Urban Radiance

Characterization of urban radiance and reflectance is important for understanding the effects of solar energy flux on the urban environment as well as for satellite mapping of urban settlement patterns. Spectral mixture analyses of Landsat and Ikonos imagery suggest that the urban radiance field can very often be described with combinations of three or four spectral endmembers. Dimensionality estimates of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) radiance measurements of urban areas reveal the existence of 30 to 60 spectral dimensions. The extent to which broadband imagery collected by operational satellites can represent the higher dimensional mixing space is a function of both the spatial and spectral resolution of the sensor. AVIRIS imagery offers the spatial and spectral resolution necessary to investigate the scale dependence of the spectral dimensionality. Dimensionality estimates derived from Minimum Noise Fraction (MNF) eigenvalue distributions show a distinct scale dependence for AVIRIS radiance measurements of Milpitas, California. Apparent dimensionality diminishes from almost 40 to less than 10 spectral dimensions between scales of 8000 m and 300 m. The 10 to 30 m scale of most features in urban mosaics results in substantial spectral mixing at the 20 m scale of high altitude AVIRIS pixels. Much of the variance at pixel scales is therefore likely to result from actual differences in surface reflectance at pixel scales. Spatial smoothing and spectral subsampling of AVIRIS spectra both result in substantial loss of information and reduction of apparent dimensionality, but the primary spectral endmembers in all cases are analogous to those found in global analyses of Landsat and Ikonos imagery of other urban areas.

Small, Christopher↗

NASA NTRS2002

High Spatial Resolution Thermal Remote Sensing of the Urban Heat Island Effect: Assessment of Risks to Human Health and Development of Mitigation Strategies for Sustainable Cities

Quattrochi, Dale A.↗

NASA NTRS2002

An Investigation of the Influence of Urban Areas on Rainfall Using the TRMM Satellite and a Cloud-Mesoscale Model

A recent paper by Shepherd and Pierce (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of approx. 28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Shepherd, J. Marshall↗

NASA NTRS2004

Status of NASA Satellite, Field Observations, and Numerical Modeling Addressing the Impact of Urbanization on Short and Long Term Precipitation Variability

Howard (1833a) made the first documented observation of a temperature difference between an urban area and its rural environment. Manley (1958) termed this contrast the "urban heat island (UHI)". The UHI has now become a widely acknowledged, observed, and researched phenomenon because of its broad implications. It is estimated that by the year 2025, 60% of the world's population will live in cities (UNFP, 1999). In the United States, the current urban growth rate is approximately 12.5%, with 80% currently living in urban areas. As cities continue to grow, urban sprawl creates unique problems related to land use, transportation, agriculture, housing, pollution, and development for policymakers. Urban expansion and its associated urban heat islands also have measurable impacts on weather and climate processes.

Shepherd, J. Marshall↗

NASA NTRS2005

A Multi-scale Approach to Urban Thermal Analysis

An environmental consequence of urbanization is the urban heat island effect, a situation where urban areas are warmer than surrounding rural areas. The urban heat island phenomenon results from the replacement of natural landscapes with impervious surfaces such as concrete and asphalt and is linked to adverse economic and environmental impacts. In order to better understand the urban microclimate, a greater understanding of the urban thermal pattern (UTP), including an analysis of the thermal properties of individual land covers, is needed. This study examines the UTP by means of thermal land cover response for the Salt Lake City, Utah, study area at two scales: 1) the community level, and 2) the regional or valleywide level. Airborne ATLAS (Advanced Thermal Land Applications Sensor) data, a high spatial resolution (10-meter) dataset appropriate for an environment containing a concentration of diverse land covers, are used for both land cover and thermal analysis at the community level. The ATLAS data consist of 15 channels covering the visible, near-IR, mid-IR and thermal-IR wavelengths. At the regional level Landsat TM data are used for land cover analysis while the ATLAS channel 13 data are used for the thermal analysis. Results show that a heat island is evident at both the community and the valleywide level where there is an abundance of impervious surfaces. ATLAS data perform well in community level studies in terms of land cover and thermal exchanges, but other, more coarse-resolution data sets are more appropriate for large-area thermal studies. Thermal response per land cover is consistent at both levels, which suggests potential for urban climate modeling at multiple scales.

Gluch, Renne↗

NASA NTRS2006

The Use of ATLAS Data to Quantify Surface Radiative Budget Alteration Through Urbanization for San Juan, Puerto Rico.

The additional heating of the air over the city is the result of the replacement of naturally vegetated surfaces with those composed of asphalt, concrete, rooftops and other manmade materials. The temperatures of these artificial surfaces can be 20 to 40 0 C higher than vegetated surfaces. Materials such as asphalt store much of the sun s energy and remains hot long after sunset. This produces a dome of elevated air temperatures 5 to 8 C greater over the city, compared to the air temperatures over adjacent rural areas. This effect is called the "urban heat island". Urban landscapes are a complex mixture of vegetated and nonvegetated surfaces. It is difficult to take enough temperature measurements over a large city area to characterize the complexity of urban radiant surface temperature variability. However, the use of remotely sensed thermal data from airborne scanners are ideal for the task. The NASA Airborne Thermal and Land Applications Sensor (ATLAS) operates in the visual and IR bands was used in February 2004 to collect data from San Juan, Puerto Rico with the main objective of investigating the Urban Heat Island (UHI) in tropical cities. In this presentation we will examine the techniques of analyzing remotely sensed data for measuring the effect of various urban surfaces on their contribution to the urban heat island effect. Results from data collected from other US cities of Sacramento, Salt Lake City and Baton Rouge will be used to compare the "urban fabric" among the cities.

Luvall, Jeffrey C.↗

NASA NTRS2006

Simulation of Urban Heat Island Mitigation Strategies in Atlanta, GA Using High-Resolution Land Use/Land Cover Data Set to Enhance Meteorological Modeling

The specification of land use/land cover (LULC) and associated land surface parameters in meteorological models at all scales has a major influence on modeled surface energy fluxes and boundary layer states. In urban areas, accurate representation of the land surface may be even more important than in undeveloped regions due to the large heterogeneity within the urban area. Deficiencies in the characterization of the land surface related to the spatial or temporal resolution of the data, the number of LULC classes defined, the accuracy with which they are defined, or the degree of heterogeneity of the land surface properties within each class may degrade the performance of the models. In this study, an experiment was conducted to test a new high-resolution LULC data set for meteorological simulations for the Atlanta, Georgia metropolitan area using a mesoscale meteorological model and to evaluate the effects of urban heat island (UHI) mitigation strategies on modeled meteorology for 2030. Simulation results showed that use of the new LULC data set reduced a major deficiency of the land use data used previously, specifically the poor representation of urban and suburban land use. Performance of the meteorological model improved substantially, with the overall daytime cold bias reduced by over 30%. UHI mitigation strategies were projected to offset much of a predicted urban warming between 2000 and 2030. In fact, for the urban core, the cooling due to UHI mitigation strategies was slightly greater than the warming associated with urbanization over this period. For the larger metropolitan area, cooling only partially offset the projected warming trend.

Crosson, William L.↗