Results for “hydrological cycle global” — Page 13

NASA NTRS2012

A Cloud Greenhouse Effect on Mars: Significant Climate Change in the Recent Past

The large variations in Mars orbit parameters are known to be significant drivers of climate change on the Red planet. The recent discovery of buried CO2 ice at the South Pole adds another dimension to climate change studies. In this paper we present results from the Ames GCM that show within the past million years it is possible that clouds from a greatly intensified Martian hydrological cycle may have produced a greenhouse effect strong enough to raise global mean surface temperatures by several tens of degrees Kelvin. It is made possible by the ability of the Martian atmosphere to transport water to high altitudes where cold clouds form, reduce the outgoing longwave radiation, and drive up surface temperatures to maintain global energy balance.

Haberle, Robert M.↗

NASA NTRS2021

NASA’s MODIS/VIIRS Global Water Reservoir Product Suite from Moderate Resolution Remote Sensing Data

Global reservoir information can not only benefit local water management but can also improve our understanding of the hydrological cycle. This information includes water area, elevation, and storage; evaporation rate and volume values; and other characteristics. However, operational wall-to-wall reservoir storage and evaporation monitoring information is lacking on a global scale. Here we introduce NASA’s new MODIS/VIIRS Global Water Reservoir product suite based on moderate resolution remote sensing data—the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Visible Infrared Imaging Radiometer Suite (VIIRS). This product consists of 8-day (MxD28C2 and VNP28C2) and monthly (MxD28C3 and VNP28C3) measurements for 164 large reservoirs (MxD stands for the product from both Terra (MOD) or Aqua (MYD) satellites). The 8-day product provides area, elevation, and storage values, which were generated by first extracting water areas from surface reflectance data and then applying the area estimations to the pre-established Area–Elevation (A–E) relationships. These values were then further aggregated to monthly, with the evaporation rate and volume information added. The evaporation rate and volume values were calculated after the Lake Temperature and Evaporation Model (LTEM) using MODIS/VIIRS land surface temperature product and meteorological data from the Global Land Data Assimilation System (GLDAS). Validation results show that the 250 m area classifications from MODIS agree well with the high-resolution classifications from Landsat (R^(2) = 0.99). Validation of elevation and storage products for twelve Indian reservoirs show good agreement in terms of R^(2) values (0.71–0.96 for elevation, and 0.79–0.96 for storage) and normalized root-mean-square error (NRMSE) values (5.08–19.34% for elevation, and 6.39–18.77% for storage). The evaporation rate results for two reservoirs (Lake Nasser and Lake Mead) agree well with in situ measurements (R^(2) values of 0.61 and 0.66, and NRMSE values of 16.25% and 21.76%). Furthermore, preliminary results from the VIIRS reservoir product have shown good consistency with the MODIS based product, confirming the continuity of this 20-year product suite. This new global water reservoir product suite can provide valuable information with regard to water-sources-related studies, applications, management, and hydrological modeling and change analysis such as drought monitoring.

Yao Li↗

NASA NTRS1999

Soil Surface Runoff Scheme for Improving Land-Hydrology and Surface Fluxes in Simple SiB (SSiB)

Evapotranspiration on land is hard to measure and difficult to simulate. On the scale of a GCM grid, there is large subgrid-scale variability of orography, soil moisture, and vegetation. Our hope is to be able to tune the biophysical constants of vegetation and soil parameters to get the most realistic space-averaged diurnal cycle of evaporation and its climatology. Field experiments such as First ISLSCP Field Experiment (FIFE), Boreal Ecosystem-Atmosphere Study (BOREAS), and LBA help a great deal in improving our evapotranspiration schemes. However, these improvements have to be matched with, and coupled to, consistent improvement in land-hydrology; otherwise, the runoff problems will intrinsically reflect on the soil moisture and evapotranspiration errors. Indeed, a realistic runoff simulation also ensures a reasonable evapotranspiration simulation provided the precipitation forcing is reliable. We have been working on all of the above problems to improve the simulated hydrologic cycle. Through our participation in the evaluation and intercomparison of land-models under the behest of Global Soil Wetness Project (GSWP), we identified a few problems with Simple SiB (SSIB; Xue et al., 1991) hydrology in regions of significant snowmelt. Sud and Mocko (1999) show that inclusion of a separate snowpack model, with its own energy budget and fluxes with the atmosphere aloft and soil beneath, helps to ameliorate some of the deficiencies of delayed snowmelt and excessive spring season runoff. Thus, much more realistic timing of melt water generation was simulated with the new snowpack model in the subsequent GSWP re-evaluations using 2 years of ISLSCP Initiative I forcing data for 1987 and 1988. However, we noted an overcorrection of the low meltwater infiltration of SSiB. While the improvement in snowmelt timing was found everywhere, the snowmelt infiltration has became excessive in some regions, e.g., Lena river basin. This leads to much reduced runoff in many basins as compared to observations. We believe this is a consequence of neglect of the influence of subgrid-scale variations in orography that affects the production of surface runoff.

Sud, Y. C.↗

NASA NTRS2023

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier2 High-Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common dataset consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

Atmospheric Rivers↗

DOE OSTI2023

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High–Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

3D Simulations of the Early Martian Hydrological Cycle Mediated by a H2-CO2 Greenhouse

For decades, the scientific community has been trying to reconcile abundant evidence for fluvialactivity on Noachian and early Hesperian Mars with the faint young Sun and reasonableconstraints on ancient atmospheric pressure and composition. Recently, the investigation of H2-CO2 collision-induced absorption has opened up a new avenue to warm Noachian Mars. We usethe ROCKE-3D global climate model to simulate plausible states of the ancient Martian climatewith this absorptive warming and reasonable constraints on surface paleopressure. We find that1.5-2 bar CO2-dominated atmospheres with ≥3% H2 can produce global mean surfacetemperatures above freezing, while also providing sufficient warming to avoid surfaceatmospheric CO2 condensation at 0°-45° obliquity. Simulations conducted with both moderntopography and a paleotopography, before Tharsis formed, highlight the importance of Tharsis asa cold trap for water on the planet. Additionally, we find that low obliquity (modern and 0°) ismore conducive to rainfall over valley network locations than high (45°) obliquity. PLAIN LANGUAGE SUMMARY Much evidence tells us that ancient Mars had liquid water on its surface. But reconciling thatwith the fainter young Sun and reasonable constraints on Mars' early atmosphere is challenging.We use a 3D global climate model with an atmosphere containing some amount of hydrogen (apossible greenhouse gas) to study Mars' early hydrological cycle and compare it to the geologicalevidence of surface liquid water billions of years ago. We find that hydrogen and carbon dioxidetogether in an atmosphere twice as thick as modern Earth can warm early Mars above thefreezing point of water and that a low axial tilt produces rainfall patterns that best match thegeologic evidence

Scott D Guzewich↗

NASA NTRS2011

Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (approx.10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 10(exp 9) unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a grand challenge to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

Wood, Eric F.↗

NASA NTRS2005

Land surface water cycles observed with satellite sensors

Acceleration of the global water cycle may lead to increased global precipitation, faster evaporation and a consequent exacerbation of hydrologic extreme. In the U.S. national assessment of the potential consequences of climate variability and change, two GCMs (CGCM1 and HadCM2) show a large increase in precipitation in the future over the southwestern U.S. particularly during winter (Felzer and Heard, 1999). Increased precipitation potentially has important impacts on agricultural and water use in the southeast U.S. (Hatch et al., 1999) and in the central Great Plains (Nielsen, 1997). A hurricane model predicts a 40% precipitation increase for severe hurricanes affecting southeastern Florida, which provokes substantially greater flooding that could negate most of the benefits of present water-management practices in this basin (Gutowski et al., 1994). Thus, it is important to observe the hydroclimate on a continuous longterm basis to address the question of increased precipitation in the enhanced water cycle.

droughts↗

NASA NTRS1999

Improving Reanalyses Using TRMM and SSM/I-Derived Precipitation and Total Precipitable Water Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of rainfall and total precipitable water (TPW) observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve these fields in reanalyses. The DAO has developed a "1+1"D procedure to assimilate 6-hr averaged rainfall and TPW into the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS. The "1+1" designation refers to one spatial dimension plus one temporal dimension. The scheme minimizes the least-square differences between the satellite-retrieved rain rates and those produced by the column model over the 6-hr analysis window. The control variables are analysis increments of moisture within the Incremental Analysis Update (IAU) framework of the GEOS DAS. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but differs in its choice of the control variable. Instead of estimating the initial condition at the beginning of the assimilation cycle, it estimates the constant IAU forcing applied over a 6-hr assimilation cycle. In doing so, it imposes the forecast model as a weak constraint in a manner similar to the variational continuous assimilation techniques. We present results from an experiment in which the observed rain rate and TPW are assumed to be "perfect". They show that assimilating the TMI and SSM/I-derived surface precipitation and TPW observations improves not only the precipitation and moisture fields but also key climate parameters directly linked to convective activities such as clouds, the outgoing longwave radiation, and the large-scale circulation in the tropics. In particular, assimilating these data types reduce the state-dependent systematic errors in the assimilated products. The improved analysis also leads to a better short-range forecast, but the impact is modest compared with improvements in the time-averaged fields. These results suggest that, in the presence of biases and other errors of the forecast model, it is possible to improve the time-averaged "climate content" in the assimilated data without comparable improvements in the short-range forecast skill. Results of this experiment provide a useful benchmark for evaluating error covariance models for optimal use of these data types.

Hou, Arthur Y.↗

NASA NTRS1999

Improving Global Reanalyses and Short-Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a 1+1D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the 1+1D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSW rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Hou, Arthur Y.↗

NASA NTRS2000

Improving Global Reanalyses and Short Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a "1+1"D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the "1+1"D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+lD scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSM/I rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Hou, Arthur Y.↗

NASA NTRS2002

Version 2 Goddard Satellite-Based Surface Turbulent Fluxes (GSSTF2)

The global air-sea fluxes of momentum, latent and sensible heat, radiation, and freshwater (precipitation-evaporation) are required for driving Ocean models and validating coupled ocean- atmosphere global models. Wind stress is the major forcing for driving the oceanic circulation, while evaporation is a key component of hydrological cycle and surface heat budget. We have produced a 13.5-year (July 1987-December 2000) dataset containing daily, monthly, and climatological surface fluxes of momentum, latent and sensible heat over the global Oceans from the Special Sensor Microwave/Imager (SSM/I) radiance easurements. This dataset is called version 2 Goddard Satellite-based Surface Turbulent Fluxes (GSSTF-2). The GSSW-2 has a spatial resolution of 1.0deg x 1.0deg lat-long. In addition, evaporation has been combined with the satellite-retrieved precipitation to produce monthly freshwater fluxes over the global Ocean for the same period. Daily turbulent fluxes are derived from the S S M surface winds and surface air humidity, and 2-m air and sea surface temperatures (SST) of the NCEP/NCAR reanalysis, using an improved stability-dependent bulk flux algorithm based on the surface layer similarity theory. Hourly fluxes computed from the GSSTF-2 bulk flux algorithm using the observed hourly input variables validate well against those of ten experiments observed by the research ships over the tropical and midlatitude oceans. In addition, daily wind stresses, latent heat fluxes, wind speeds, surface air humidity and SSTs of the GSSTF-2 compare reasonably well with those of the collocated in situ measurements of the ten experiments. The global distributions of 1988-2000 annual- and seasonal-mean turbulent fluxes show reasonable patterns related to the atmospheric general circulation and its seasonal variations. The comparison of zonally-averaged wind stress and latent heat fluxes of the GSSTF-2 with those of other satellite products as well as the NCEPNCAR and ECMWF reanalyses for the annual mean and seasonal variations during 1992-93 will be discussed. .

Chou, Shu-Hsien↗

NASA NTRS2003

Earth System Dynamics: The Determination and Interpretation of the Global Angular Momentum Budget using the Earth Observing System

The objective of this investigation has been to examine the mass and momentum exchange between the atmosphere, oceans, solid Earth, hydrosphere, and cryosphere. The investigation has focused on changes in the Earth's gravity field, its rotation rate, atmospheric and oceanic circulation, global sea level change, ice sheet change, and global ground water circulation observed by contemporary sensors and models. The primary component of the mass exchange is water. The geodetic observables provided by these satellite sensors are used to study the transport of water mass in the hydrological cycle from one component of the Earth to another, and they are also used to evaluate the accuracy of models. As such, the investigation is concerned with the overall global water cycle. This report provides a description of scientific, educational and programmatic activities conducted during the period July 1, 1999 through June 30,2000. Research has continued into measurements of time-varying gravity and its relationship to Earth rotation. Variability of angular momentum and the related excitation of polar motion and Earth rotation have been examined for the atmosphere and oceans at time-scales of weeks to several years. To assess the performance of hydrologic models, we have compared geodetic signals derived from them with those observed by satellites. One key component is the interannual mass variability of the oceans obtained by direct observations from altimetry after removing steric signals. Further studies have been conducted on the steric model to quantify its accuracy at global and basin-scales. The results suggest a significant loss of water mass from the Oceans to the land on time-scales longer than 1-year. These signals are not reproduced in any of the models, which have poorly determined interannual fresh water fluxes. Output from a coupled atmosphere-ocean model testing long-term climate change hypotheses has been compared to simulated errors from the Gravity Recovery and Climate Experiment (GRACE) mission. Results indicate that GRACE will be able to observe seasonal signals at half-wavelengths ranging from 1000 to 10000 km, and may be able to observe secular trends at half- wavelengths of greater than 2000-3000 km for soil moisture and snow depth if they are as large as some of the climate experiments predict.

Source record↗

NASA NTRS2016

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

biogeochemistry↗

NASA NTRS1997

The Global Enery and Water Cycle Experiment Science Strategy

The distribution of water in the atmosphere and at the surface of the Earth is the most influential factor regulating our environment, not only because water is essential for life but also because through phase transitions it is the main energy source that control clouds and radiation and drives the global circulation of the atmosphere.

GEWEX hydrological cycle energy fluxes seasonal-to↗

NASA NTRS2002

The Global Geophysical Fluids Center of IERS (and its Special Bureau for Mantle)

The Global Geophysical Fluids Center (GGFC) was established by the International Earth Rotation Service (IERS) on IERS's 10th anniversary day January 1, 1998, in an effort to expand IERS's services to the scientific community. Under the GGFC, eight Special Bureaus (SB) have been selected, each to be responsible for research and data service activities pertaining to mass transports and related geophysical processes in specific components of the Earth system, or "global geophysical fluids," including the atmosphere, oceans, solid Earth, core, and geophysical processes of gravity, loading, tides and hydrological cycles. GGFC and the SBs have the responsibility of supporting, facilitating, and providing services to the worldwide research community, in areas related to the variations in Earth rotation, gravity field and geocenter that are caused by mass transport in the global geophysical fluids. These minute variations have been observed by various space geodetic techniques, as effective remote sensing tools, with ever increasing precision/accuracy and temporal/spatial resolution. The GGFC and SBs have organized dedicated workshops and special sessions at international conferences, published articles, and held regular business meetings. The SBs also maintain individual website for data services and information exchanges. See URL . In particular, the SB for Mantle focuses on large-scale mass redistributions that occur in the mantle in association with various dynamic processes, including seismic activities, the post-glacial rebound, and mantle convections.

Chao, Benjamin F.↗

NASA NTRS2015

Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow

As a component of the Earth's hydrologic cycle, and especially at higher latitudes,falling snow creates snow pack accumulation that in turn provides a large proportion of the fresh water resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) mission Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011-2012 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite,and radiometers on constellation member satellites. Multi-parameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precipitation detection and estimation can be based. The data collection strategy was coordinated, stacked, high-altitude and in-situ cloud aircraft missions with three research aircraft sampling within a broader surface network of five ground sites taking in-situ and volumetric observations. During the field campaign 25 events were identified and classified according to their varied precipitation type, synoptic context, and precipitation amount. Herein, the GCPEx fieldcampaign is described and three illustrative cases detailed.

GCPEx↗

NASA NTRS2000

A Brief Summary of the Geomorphic Evidence for an Active Surface Hydrologic Cycle in Mars' Past

Because Mars is just over half the Earth's diameter (about 6800 km), it does not exhibit global tectonism on a scale comparable to Earth and Venus. But because it is still a large body compared to Mercury and the moon, it has had an atmosphere and climate over the history of the solar system. This is why Mars has been able to retain surfaces produced both through volcanic and climatic processes that are intermediate in age between volcanic surfaces on the moon and Mercury and both types of surfaces on Venus and Earth. For the purposes of this discussion, this has important implications about the origins and evolution of topographic depressions that potentially may have contained lakes. Tectonism is probably the most important process on Earth for producing closed depressions on the continents, and is clearly responsible for maintenance of the ocean basins through geologic time. This is probably also true for depressions in the highland terrains and lowland plains of Venus. On Mars, however, tectonism appears limited to relatively small amounts of regional extension, compression, and vertical motion largely due to crustal loading of the two major volcanic provinces - Tharsis and Elysium Impact craters and large impact basins (including all or parts of the northern plains) are clearly more important sites for potential lake basins on Mars, though they were likely more important on Earth, and Venus as well, during the period of heavy meteorite bombardment throughout the solar system prior to 3.5 Ga. Comparisons of the relative importance of other formative processes on Mars with those on Earth are less obvious, and some may be quite speculative, since our understanding of the early Martian environment is still rather limited. Additional information is contained in the original extended abstract.

Parker, T. J.↗