M M Holland
Biographic Data
| ID | 33334 |
|---|---|
| NAME | M M Holland |
| GIVEN NAMES | M M |
| FAMILY NAME | Holland |
| SIGNATURE | HOLLAND M M |
| AFFILIATIONS | NSF National Center for Atmospheric Research |
| ORCID | 0000-0001-5621-8939 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2007 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Theoretical estimates of light transmittance at the MosaiC Central Observatory
Light transmission through a sea ice cover has strong implications for the heat content of the upper ocean, the magnitude of bottom and lateral ice melt, and primary productivity in the ocean. Light transmittance in the vicinity of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) Central Observatory was estimated by driving a two-stream radiative transfer model with physical property observations. Data include p…
Snow redistribution onto young sea ice
Vertical heat conduction through young ice is a major source of wintertime sea ice growth in the Arctic. However, field observations indicate that young ice preferentially accumulates wind-blown snow, resulting in greater snow thickness on young ice than would be expected from precipitation alone, and hence greater snow thickness on young ice than climate models represent. As snow has a low thermal conductivity, this additional snow thickness due…
Spatiotemporal evolution of melt ponds on Arctic sea ice
Melt ponds on sea ice play an important role in the Arctic climate system. Their presence alters the partitioning of solar radiation: decreasing reflection, increasing absorption and transmission to the ice and ocean, and enhancing melt. The spatiotemporal properties of melt ponds thus modify ice albedo feedbacks and the mass balance of Arctic sea ice. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition …
Arctic sea ice albedo
The magnitude, spectral composition, and variability of the Arctic sea ice surface albedo are key to understanding and numerically simulating Earth’s shortwave energy budget. Spectral and broadband albedos of Arctic sea ice were spatially and temporally sampled by on-ice observers along individual survey lines throughout the sunlit season (April–September, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MO…
Partitioning uncertainty in projections of Arctic sea ice
Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model …
The Community Earth System Model Version 2 (Cesm2)
An overview of the Community Earth System Model Version 2 (CESM2) is provided, including a discussion of the challenges encountered during its development and how they were addressed. In addition, an evaluation of a pair of CESM2 long preindustrial control and historical ensemble simulations is presented. These simulations were performed using the nominal 1° horizontal resolution configuration of the coupled model with both the “low‐top” (40 km, …
Essential gaps and uncertainties in the understanding of the roles and functions of Arctic sea ice
While Arctic sea ice is changing, new observation methods are developed and process understanding improves, whereas gaps in observations and understanding evolve. Some previous gaps are filled, while others remain, or come up new. Knowing about the status of observation and knowledge gaps is important for interpreting observation and research results, interpretation and use of key climate indicators, and for research and observation planning. Thi…
The Community Earth System Model (Cesm) Large Ensemble Project
While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. I…
The Community Earth System Model
By simulating biogeochemical cycles, the Greenland ice sheet, and more-with reach to the lower thermosphere-this system gives the research community a flexible, state-of-thescience tool for understanding climate variability and change.
The Arctic’s rapidly shrinking sea ice cover
The sequence of extreme September sea ice extent minima over the past decade suggests acceleration in the response of the Arctic sea ice cover to external forcing, hastening the ongoing transition towards a seasonally open Arctic Ocean. This reflects several mutually supporting processes. Because of the extensive open water in recent Septembers, ice cover in the following spring is increasingly dominated by thin, first-year ice (ice formed during…
Abrupt onset of the Little Ice Age triggered by volcanism and sustained by sea‐ice/ocean feedbacks
Northern Hemisphere summer temperatures over the past 8000 years have been paced by the slow decrease in summer insolation resulting from the precession of the equinoxes. However, the causes of superposed century‐scale cold summer anomalies, of which the Little Ice Age (LIA) is the most extreme, remain debated, largely because the natural forcings are either weak or, in the case of volcanism, short lived. Here we present precisely dated records o…
Arctic sea ice decline
From 1953 to 2006, Arctic sea ice extent at the end of the melt season in September has declined sharply. All models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) show declining Arctic ice cover over this period. However, depending on the time window for analysis, none or very few individual model simulations show trends comparable to observations. If the multi‐model ensemble mean time series p…
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Arctic sea ice decline
From 1953 to 2006, Arctic sea ice extent at the end of the melt season in September has declined sharply. All models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) show declining Arctic ice cover over this period. However, depending on the time window for analysis, none or very few individual model simulations show trends comparable to observations. If the multi‐model ensemble mean time series p…
The Arctic’s rapidly shrinking sea ice cover
The sequence of extreme September sea ice extent minima over the past decade suggests acceleration in the response of the Arctic sea ice cover to external forcing, hastening the ongoing transition towards a seasonally open Arctic Ocean. This reflects several mutually supporting processes. Because of the extensive open water in recent Septembers, ice cover in the following spring is increasingly dominated by thin, first-year ice (ice formed during…
Abrupt onset of the Little Ice Age triggered by volcanism and sustained by sea‐ice/ocean feedbacks
Northern Hemisphere summer temperatures over the past 8000 years have been paced by the slow decrease in summer insolation resulting from the precession of the equinoxes. However, the causes of superposed century‐scale cold summer anomalies, of which the Little Ice Age (LIA) is the most extreme, remain debated, largely because the natural forcings are either weak or, in the case of volcanism, short lived. Here we present precisely dated records o…
The Community Earth System Model
By simulating biogeochemical cycles, the Greenland ice sheet, and more-with reach to the lower thermosphere-this system gives the research community a flexible, state-of-thescience tool for understanding climate variability and change.
The Community Earth System Model (Cesm) Large Ensemble Project
While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. I…
Essential gaps and uncertainties in the understanding of the roles and functions of Arctic sea ice
While Arctic sea ice is changing, new observation methods are developed and process understanding improves, whereas gaps in observations and understanding evolve. Some previous gaps are filled, while others remain, or come up new. Knowing about the status of observation and knowledge gaps is important for interpreting observation and research results, interpretation and use of key climate indicators, and for research and observation planning. Thi…
The Community Earth System Model Version 2 (Cesm2)
An overview of the Community Earth System Model Version 2 (CESM2) is provided, including a discussion of the challenges encountered during its development and how they were addressed. In addition, an evaluation of a pair of CESM2 long preindustrial control and historical ensemble simulations is presented. These simulations were performed using the nominal 1° horizontal resolution configuration of the coupled model with both the “low‐top” (40 km, …
Partitioning uncertainty in projections of Arctic sea ice
Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model …
Snow redistribution onto young sea ice
Vertical heat conduction through young ice is a major source of wintertime sea ice growth in the Arctic. However, field observations indicate that young ice preferentially accumulates wind-blown snow, resulting in greater snow thickness on young ice than would be expected from precipitation alone, and hence greater snow thickness on young ice than climate models represent. As snow has a low thermal conductivity, this additional snow thickness due…
Spatiotemporal evolution of melt ponds on Arctic sea ice
Melt ponds on sea ice play an important role in the Arctic climate system. Their presence alters the partitioning of solar radiation: decreasing reflection, increasing absorption and transmission to the ice and ocean, and enhancing melt. The spatiotemporal properties of melt ponds thus modify ice albedo feedbacks and the mass balance of Arctic sea ice. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition …
Arctic sea ice albedo
The magnitude, spectral composition, and variability of the Arctic sea ice surface albedo are key to understanding and numerically simulating Earth’s shortwave energy budget. Spectral and broadband albedos of Arctic sea ice were spatially and temporally sampled by on-ice observers along individual survey lines throughout the sunlit season (April–September, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MO…
Theoretical estimates of light transmittance at the MosaiC Central Observatory
Light transmission through a sea ice cover has strong implications for the heat content of the upper ocean, the magnitude of bottom and lateral ice melt, and primary productivity in the ocean. Light transmittance in the vicinity of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) Central Observatory was estimated by driving a two-stream radiative transfer model with physical property observations. Data include p…
Environmental Science (11 works) · Climatology (9 works) · Arctic (8 works) · Arctic ice pack (8 works) · Sea ice (8 works) · Arctic and Antarctic ice dynamics (7 works) · Climate change and permafrost (7 works) · Geology (6 works) · Atmospheric sciences (5 works) · Climate change (5 works)