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At least 109 records · Page 6

Regime shifts in Arctic terrestrial hydrology manifested from impacts of climate warming

Abstract. Anthropogenic warming in the Arctic is causing hydrological cycle intensification and permafrost thaw, with implications for flows of water, carbon, and energy from terrestrial biomes to coastal zones. To better understand the likely impacts of these changes, we used a hydrology model driven by meteorological data from atmospheric reanalysis and two global climate models for the period 1980–2100. The hydrology model accounts for soil freeze–thaw processes and was applied across the pan-Arctic drainage basin. The simulations point to greater changes over northernmost areas of the basin underlain by permafrost and to the western Arctic. An acceleration of simulated river discharge over the recent past is commensurate with trends drawn from observations and reported in other studies. Between early-century (2000–2019) and late-century (2080–2099) periods, the model simulations indicate an increase in annual total runoff of 17 %–25 %, while the proportion of runoff emanating from subsurface pathways is projected to increase by 13 %–30 %, with the largest changes noted in summer and autumn and across areas with permafrost. Most notably, runoff contributions to river discharge shift to northern parts of the Arctic Basin that contain greater amounts of soil carbon. Each season sees an increase in subsurface runoff; spring is the only season where surface runoff dominates the rise in total runoff, and summer experiences a decline in total runoff despite an increase in the subsurface component. The greater changes that are seen in areas where permafrost exists support the notion that increased soil thaw is shifting hydrological contributions to more subsurface flow. The manifestations of warming, hydrological cycle intensification, and permafrost thaw will impact Arctic terrestrial and coastal environments through altered river flows and the materials they transport.

54 ENVIRONMENTAL SCIENCES↗

Models of atmosphere-ecosystem-hydrology interactions: Approaches and testing

Interactions among the atmosphere, terrestrial ecosystems, and the hydrological cycle have been the subject of investigation for many years, although most of the research has had a regional focus. The topic is broad, including the effects of climate and hydrology on vegetation, the effects of vegetation on hydrology, the effects of the hydrological cycle on the atmosphere, and interactions of the cycles via material flux such as solutes and trace gases. The intent of this paper is to identify areas of critical uncertainty, discuss modeling approaches to resolving those problems, and then propose techniques for testing. I consider several interactions specifically to illustrate the range of problems. These areas are as follows: (1) cloud parameterizations and the land surface, (2) soil moisture, and (3) the terrestrial carbon cycle.

Schimel, David S.↗

Future precipitation increase constrained by climatological pattern of cloud effect

The fractional increase in global mean precipitation (?P ¯/P ¯) is a first-order measure of the hydrological cycle intensification under anthropogenic warming. However, ?P ¯/P ¯ varies by a factor of more than three among model projections, hindering credible assessments of the associated climate impacts. The uncertainty in ?P ¯/P ¯ stems from uncertainty in both hydrological sensitivity (global mean precipitation increase per unit warming) and climate sensitivity (global mean temperature increase per forcing). Here, by investigating hydrological and climate sensitivities in a unified surface-energy-balance perspective, we find that both sensitivities are significantly correlated with surface shortwave cloud feedback, which is further linked to the climatological pattern of cloud shortwave effect. The observed pattern of cloud effect thus constrains both sensitivities and consequently constrains ?P ¯/P ¯. The 5%-95% uncertainty range of ?P ¯/P ¯ from 1979-2005 to 2080-2100 under the high-emission (moderate-emission) scenario is constrained from 6.34±3.53% (4.19±2.28%) in the raw ensemble-model projection to 7.03±2.59% (4.63±1.71%). The constraint thus suggests a higher most-likely ?P ¯/P ¯ and reduces the uncertainty by ~25%, providing valuable information for impact assessments.

Zhou, Wenyu↗

A wet-geology and cold-climate Mars model: Punctuation of a slow dynamic approach to equilibrium

It was suggested that Mars may have possessed a relatively warm humid climate and a vigorous hydrological cycle involving meteoric precipitation, oceans, and continental ice sheets. Baker hypothesized that these geologically active conditions may have been repeated several times; each of these dynamic epochs was followed by a collapse of the climate and hydrologic cycle of Mars into essentially current conditions, completing what is termed a 'Baker cycle'. The purpose is to present an endmember possibility that Martian glacial landscapes, including some that were previously considered to have formed under warm climatic conditions, might be explained by processes compatible with an extremely cold surface. Two aspects of hypothesized Martian glacial terrains were cited as favoring a warm climate during Baker cycles: (1) the formation of some landscapes, including possible eskers, tunnel channels, drumlins, and outwash plains, appears to have required liquid water, and (2) a liquid-surfaced ocean was probably necessary to feed the glaciers. The requirement for liquid water, if these features were correctly interpreted, is difficult to avoid; it is entirely possible that a comparatively warm climate was involved, but it is not clear that formation of landforms by wet-based glaciers actually requires a warm climate. Even less certain is the supposed requirement for liquid oceans. Formation of glaciers only requires a source of water or ice to supply an amount of precipitation that exceeds losses due to melting and sublimation. At Martian temperatures precipitation is very low, but so are melting and sublimation, so a large body of ice that is unstable with respect to sublimation may take the role of Earth's oceans in feeding the glaciers. Recent models suggest that even current Martian polar caps, long thought to be static bodies of ice and dust, might actually be slow-moving, cryogenic continental glaciers. Is it possible that subglacial processes beneath cryogenic (but wetbased) ice sheets formed the hypothesized Martian glacial landscapes?

Kargel, J. S.↗

Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System

Seasonal variability of the global hydrologic cycle directly impacts human activities, including hazard assessment and mitigation, agricultural decisions, and water resources management. This is particularly true across the High Mountain Asia (HMA) region, where availability of water resources can change depending on local seasonality of the hydrologic cycle. Forecasting the atmospheric states and surface conditions, including hydrometeorologically relevant variables, at subseasonal-to-seasonal (S2S) lead times of weeks to months is an area of active research and development. NASA's Goddard Earth Observing System (GEOS) S2S prediction system has been developed with this research goal in mind. Here, we benchmark the forecast skill of GEOS-S2S (version 2) hydrometeorological forecasts at 1–3-month lead times in the HMA region, including a portion of the Indian subcontinent, during the retrospective forecast period, 1981–2016. To assess forecast skill, we evaluate 2 m air temperature, total precipitation, fractional snow cover, snow water equivalent, surface soil moisture, and terrestrial water storage forecasts against the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and independent reanalysis data, satellite observations, and data fusion products. Anomaly correlation is highest when the forecasts are evaluated against MERRA-2 and particularly in variables with long memory in the climate system, likely due to the similar initial conditions and model architecture used in GEOS-S2S and MERRA-2. When compared to MERRA-2, results for the 1-month forecast skill range from an anomaly correlation of R anom =0.18 for precipitation to R anom =0.62 for soil moisture. Anomaly correlations are consistently lower when forecasts are evaluated against independent observations; results for the 1-month forecast skill range from R anom =0.13 for snow water equivalent to R anom =0.24 for fractional snow cover. We find that, generally, hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system's ability to forecast HMA hydrometeorology.

54 ENVIRONMENTAL SCIENCES↗

Seasonal Forecasting Skill for the High Mountain Asia Region in the Goddard Earth Observing System

Seasonal variability of the global hydrologic cycle directly impacts human activities, including hazard assessment and mitigation, agricultural decisions, and water resources management. This is particularly true across the High Mountain Asia (HMA) region, where availability of water resources can change depending on local seasonality of the hydrologic cycle. Forecasting the atmospheric states and surface conditions, including hydrometeorological relevant variables, at subseasonal-to-seasonal (S2S) lead times of weeks-to-months is an area of active research and development. NASA’s 15 Goddard Earth Observing System (GEOS) S2S prediction system has been developed with this research goal in mind. Here, we benchmark the forecast skill of GEOS-S2S (version 2) hydrometeorological forecasts at 1-3 month lead times in the HMA region, including a portion of the Indian Subcontinent, during the retrospective forecast period, 1981-2016. To assess forecast skill, we evaluate 2-m air temperature, total precipitation, fractional snow cover, snow water equivalent, surface soil moisture, and terrestrial water storage forecasts against the Modern-Era Retrospective analysis for Research and 20 Applications, Version 2 (MERRA-2) and independent reanalysis data, satellite observations, and data fusion products. Anomaly correlation is highest when the forecasts are evaluated against MERRA-2 and particularly in variables with long memory in the climate system, likely due to similar initial conditions and model architecture used in GEOS-S2S and MERRA-2. When compared to MERRA-2, results for the 1-month forecast skill range from anomaly correlation of R anom =0.18 for precipitation to R anom =0.62 for soil moisture. Anomaly correlations are consistently lower when forecasts are 25 evaluated against independent observations; results for the 1-month forecast skill range from R anom =0.13 for snow water equivalent to R anom =0.24 for fractional snow cover. We find that, generally, hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system’s ability to forecast HMA hydrometeorology.

GEOS↗

Intercomparison and interpretation of surface energy fluxes in atmospheric general circulation models

Responses of the surface energy budgets and hydrologic cycles of 19 atmospheric general circulation models to an imposed, globally uniform sea surface temperature perturbation of 4 K were analyzed. The responses of the simulated surface energy budgets are extremely diverse and are closely linked to the responses of the simulated hydrologic cycles. The response of the net surface energy flux is not controlled by cloud effects; instead, it is determined primarily by the response of the latent heat flux. The prescribed warming of the oceans leads to major increases in the atmospheric water vapor content and the rates of evaporation and precipitation. The increased water vapor amount drastically increases the downwelling IR radiation at the earth's surface, but the amount of the change varies dramatically from one model to another.

Randall, D. A.↗

NGEE Arctic Integrated Modeling (IM2): Improved subgrid hillslope hydrologic connectivity

This data product represents the integration of new code capability for arctic tundra hillslope hydrologic processes into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The current ELM represents water movement primarily through vertical processes, such as precipitation, canopy interception, evaporation, infiltration, and soil water movement. Lateral water movement—such as surface runoff, subsurface flow, and river transport—plays a significant role in the hydrological cycle, especially in regions with varied topography. While E3SM includes a runoff routing component representing water transport in the river network, the lateral transport of water at the subgrid scale within the land model has previously not been taken into account. With the recent development of topographic units within the ELM subgrid data structure, there is an opportunity to simulate hillslope hydrologic connectivity by introducing water transport along topographic gradients. We expect that more realistic representation of hillslope hydrologic processes will lead to improved predictions of both soil water content and river network flows. Lateral transport of water at and near the surface is represented as a sub-grid process in this new code development. Water is tracked as it moves from higher to lower elevations within a gridcell. This capability uses the nested hierarchical sub-grid scheme within ELM to connect water fluxes from sub-grid elements with higher elevation to those with lower elevation. This data record consists of a single document (pdf format) that describes the theoretical basis for the hillslope hydrology processes added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗

Role of a cumulus parameterization scheme in simulating atmospheric circulation and rainfall in the nine-layer Goddard Laboratory for Atmospheres General Circulation Model

The influence of a cumulus convection scheme on the simulated atmospheric circulation and hydrologic cycle is investigated by means of a coarse version of the GCM. Two sets of integrations, each containing an ensemble of three summer simulations, were produced. The ensemble sets of control and experiment simulations are compared and differentially analyzed to determine the influence of a cumulus convection scheme on the simulated circulation and hydrologic cycle. The results show that cumulus parameterization has a very significant influence on the simulation circulation and precipitation. The upper-level condensation heating over the ITCZ is much smaller for the experiment simulations as compared to the control simulations; correspondingly, the Hadley and Walker cells for the control simulations are also weaker and are accompanied by a weaker Ferrel cell in the Southern Hemisphere. Overall, the difference fields show that experiment simulations (without cumulus convection) produce a cooler and less energetic atmosphere.

Sud, Y. C.↗

A satellite view of aerosols in the climate system

Anthropogenic aerosols are intricately linked to the climate system and to the hydrologic cycle. The net effect of aerosols is to cool the climate system by reflecting sunlight. Depending on their composition, aerosols can also absorb sunlight in the atmosphere, further cooling the surface but warming the atmosphere in the process. These effects of aerosols on the temperature profile, along with the role of aerosols as cloud condensation nuclei, impact the hydrologic cycle, through changes in cloud cover, cloud properties and precipitation. Unravelling these feedbacks is particularly difficult because aerosols take a multitude of shapes and forms, ranging from desert dust to urban pollution, and because aerosol concentrations vary strongly over time and space. To accurately study aerosol distribution and composition therefore requires continuous observations from satellites, networks of ground-based instruments and dedicated field experiments. Increases in aerosol concentration and changes in their composition, driven by industrialization and an expanding population, may adversely affect the Earth's climate and water supply.

Review, Tutorial↗

Salinity Remote Sensing and the Study of the Global Water Cycle

The SMOS and AquariusISAC-D satellite missions will begin a new era to map the global sea surface salinity (SSS) field and its variability from space within the next twothree years. They will provide critical data needed to study the interactions between the ocean circulation, global water cycle and climate. Key scientific issues to address are (1) mapping large expanses of the ocean where conventional SSS data do not yet exist, (2) understanding the seasonal and interannual SSS variations and the link to precipitation, evaporation and sea-ice patterns, (3) links between SSS and variations in the oceanic overturning circulation, (4) air-sea coupling processes in the tropics that influence El Nino, and (4) closing the marine freshwater budget. There is a growing body of oceanographic evidence in the form of salinity trends that portend significant changes in the hydrologic cycle. Over the past several decades, highlatitude oceans have become fresher while the subtropical oceans have become saltier. This change is slowly spreading into the subsurface ocean layers and may be affecting the strength of the ocean's therrnohaline overturning circulation. Salinity is directly linked to the ocean dynamics through the density distribution, and provides an important signature of the global water cycle. The distribution and variation of oceanic salinity is therefore attracting increasing scientific attention due to the relationship to the global water cycle and its influence on circulation, mixing, and climate processes. The oceans dominate the water cycle by providing 86% of global surface evaporation (E) and receiving 78% of global precipitation (P). Regional differences in E-P, land runoff, and the melting or freezing of ice affect the salinity of surface water. Direct observations of E-P over the ocean have large uncertainty, with discrepancies between the various state-of-the-art precipitation analyses of a factor of two or more in many regions. Quantifying the climatic influence of the oceanic water cycle requires more accurately resolving the net air-sea water flux. Measuring global SSS trends on seasonal to interannual timescales by satellite is fundamental to this problem because the SSS trends represent detectable time-integrated signals of the variable marine hydrological cycle. Satellite measurements, coupled with an array of in situ observations, will provide global synoptic SSS fields for the first time history. These data will provide a strong constraint on climate models and data assimilation efforts, which must properly represent the freshwater budget in terms of E-P, ocean advection and surface layer mixing in order to accurately simulate the true ocean state. The SSS fields will allow us to quantify the covariability between the SSS and the strong seasonal E-P cycle in the tropics and high latitudes. Field measurement campaigns to exploit satellite and in situ measurements to close the seasonal E-P cycle over an ocean region are being considered. Lastly the satellite systems will monitor and trace the large long-lived SSS anomalies from year to year that have the potential to influence El Nino and the large scale ocean circulation.

Lagerloef, G. S. E.↗

Toward Urban Water Security: Broadening the Use of Machine Learning Methods for Mitigating Urban Water Hazards

Due to the complex interactions of human activity and the hydrological cycle, achieving urban water security requires comprehensive planning processes that address urban water hazards using a holistic approach. However, the effective implementation of such an approach requires the collection and curation of large amounts of disparate data, and reliable methods for modeling processes that may be co-evolutionary yet traditionally represented in non-integrable ways. In recent decades, many hydrological studies have utilized advanced machine learning and information technologies to approximate and predict physical processes, yet none have synthesized these methods into a comprehensive urban water security plan. In this paper, we review ways in which advanced machine learning techniques have been applied to specific aspects of the hydrological cycle and discuss their potential applications for addressing challenges in mitigating multiple water hazards over urban areas. We also describe a vision that integrates these machine learning applications into a comprehensive watershed-to-community planning workflow for smart-cities management of urban water resources.

54 ENVIRONMENTAL SCIENCES↗

TRMM Data Assimilation at NASA

We give an overview of the research at NASA in assimilating tropical rainfall and total precipitable water (TPW) retrievals derived from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments. Global analyses currently contain order-one errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. We show that an effective strategy to assimilate tropical rainfall data is to use observations to compensate for errors in moisture tendencies produced by the assimilation model. Results show that assimilating TMI and SSM/I surface rainrates and TPW estimates improves shortrange forecasts and reduces state-dependent systematic errors in the hydrological cycle and related climate parameters such as cloud, radiation, and the large-scale circulation in the tropics. The study provides a demonstration of the potential of using rainfall and moisture observations derived from passive microwave instruments to improve the quality of 4-dimensional global datasets for climate analysis and weather forecasting applications.

Hou, Arthur Y.↗

Climatic consequences of anthropogenic vegetation changes from 1880-1980

The changes in the surface albedo associated with land-use alterations from 1880-1980 and the climatic implications of these changes are discussed. Changes in atmospheric CO2, the hydrologic cycle, atmospheric particulates and aerosols are reviewed. A global survey of the growth of agriculture and forestry data is presented. The anthopogenic vegetation changes in western Africa are examined in detail. Maps and tables of anthopogenic vegetation and albedo changes are presented for western Africa, South America, and worldwide. It is found that the mean regional albedo increased from 17.4 in 1880 to 17.8 in 1980. No apparent secular decrease in precipitation linked to vegetation clearing is observed. It is suggested that disruption of the hydrologic cycle as a result of devegetation may have led to reductions in soil moisture.

Gornitz, Vivien↗

Importance of Rain Evaporation and Continental Convection in the Tropical Water Cycle

Atmospheric moisture cycling is an important aspect of the Earth's climate system, yet the processes determining atmospheric humidity are poorly understood. For example, direct evaporation of rain contributes significantly to the heat and moisture budgets of clouds, but few observations of these processes are available. Similarly, the relative contributions to atmospheric moisture over land from local evaporation and humidity from oceanic sources are uncertain. Lighter isotopes of water vapour preferentially evaporate whereas heavier isotopes preferentially condense and the isotopic composition of ocean water is known. Here we use this information combined with global measurements of the isotopic composition of tropospheric water vapour from the Tropospheric Emission Spectrometer (TES) aboard the Aura spacecraft, to investigate aspects of the atmospheric hydrological cycle that are not well constrained by observations of precipitation or atmospheric vapour content. Our measurements of the isotopic composition of water vapour near tropical clouds suggest that rainfall evaporation contributes significantly to lower troposphere humidity, with typically 20% and up to 50% of rainfall evaporating near convective clouds. Over the tropical continents the isotopic signature of tropospheric water vapour differs significantly from that of precipitation, suggesting that convection of vapour from both oceanic sources and evapotranspiration are the dominant moisture sources. Our measurements allow an assessment of the intensity of the present hydrological cycle and will help identify any future changes as they occur.

Worden, John↗

An Improved Zhang's Dynamic Water Balance Model Using Budyko-Based Snow Representation for Better Streamflow Predictions

Understanding the water balance of a catchment in relation to its regional climate forcings and catchment characteristics is critical for predicting current and future water resources amid changing climate and land cover. This study intends to improve Zhang's monthly water balance model (a physics-based conceptual hydrologic model) that reflects the physical partitioning process of the hydrological cycle at the basin level based on regional climate and catchment characteristics. The existing model does not include snow process and has confronted evident limitations in snow-affected areas, which is a critical aspect since snowmelt water has been a significant source of water resources for many regions, especially in the temperate and frigid zones. We introduce a snow module based on surface energy balance and Budyko-limits on melting and combine it with the existing water balance equations. Moreover, monthly parameterization is applied to the model to better explain the time-varying hydrological characteristics of a catchment. The proposed model involves five different monthly parameters, which determine the physical partitioning process of the hydrological cycle, and they are regionally calibrated and validated under Budyko-type constraints. The model is applied to 1,210 basins across the continental United States (CONUS), and the simulated streamflow is compared to the observed data. The proposed model significantly outperformed the original model, improving the median NSE by 31% (from 0.51 to 0.67) and increasing the number of catchments with an acceptable NSE by 58%. The spatial variability of the basin characteristics across the CONUS is also investigated based on the calibrated parameters.

54 ENVIRONMENTAL SCIENCES↗

An Overview of Mesoscale Convective Systems: Global Climatology, Satellite Observations, and Modeling Strategies

Deep convection is responsible for redistributing water as well as energy and providing vital water resources for many regions of the world. Cumulonimbus clouds aggregation into a single storm system develop mesoscale convective systems (MCS). MCSs have precipitation covering a horizontal region on the scale of 100?km or more. After more than the last seven decades, MCS has been gradually received wide attention in the scientific community as an important component of the Earth's hydrologic cycle and energy balance. MCSs differ from ordinary deep convection because of the mesoscale circulations consisting of a layer of air overturning on a scale much larger than those created by individual convective updrafts or downdrafts. Moreover, a key feature that separates MCS from ordinary deep convection is the significant portion of stratiform precipitation that results in the production and detrainment of a large number of ice particles from their organized convective cores and continues the mesoscale ascent that supports ice growth and aggregation as the crystals fall. This significant stratiform precipitation gives rise to top-heavy latent heating profiles that have substantial impacts on the upper-level global circulations, especially for those MCS that have a larger portion of stratiform rainfall. Top-heavy latent heating profiles are more frequent over the ocean than over the land. These unique features of MCS suggest that they are important for the hydrologic cycle, general circulation, and radiative balance of the climate system. In this chapter, we focus on the recent advances in the climatological perspective of MCS as well as the research tools used to better understand MCS after the advent of the satellite era. We will discuss both tropical and midlatitude MCS, the influence of modes of tropical climate variability on MCS, and the new insight from satellite observations on MCS interaction with the land surface.

Chakraborty, Sudip↗

Precipitable Water Variability Using SSM/I and GOES VAS Pathfinder Data Sets

Determining moisture variability for all weather scenes is critical to understanding the earth's hydrologic cycle and global climate changes. Remote sensing from geostationary satellites provides the necessary temporal and spatial resolutions necessary for global change studies. Due to antenna size constraints imposed with the use of microwave radiometers, geostationary satellites have carried instruments passively measuring radiation at infrared wavelengths or shorter. The shortfall of using infrared instruments in moisture studies lies in its inability to sense terrestrial radiation through clouds. Microwave emissions, on the other hand, are mostly unaffected by cloudy atmospheres. Land surface emissivity at microwave frequencies exhibit both high temporal and spatial variability thus confining moisture retrievals at microwave frequencies to over marine atmospheres (a near uniform cold background). This study intercompares the total column integrated water content Precipitable Water, (PW) as derived from both the Special Sensor Microwave Imager (SSM/I) and the Geostationary Operational Environmental Satellite (GOES) VISSR Atmospheric Sounder (VAS) pathfinder data sets. PW is a bulk parameter often used to quantify moisture variability and is important to understanding the earth's hydrologic cycle and climate system. This research has been spawned in an effort to combine two different algorithms which together can lead to a more comprehensive quantification of global water vapor. The approach taken here is to intercompare two independent PW retrieval algorithms and to validate the resultant retrievals against an existing data set, namely the European Center for Medium range Weather Forecasts (ECMWF) model analysis data.

Lerner, Jeffrey A.↗