Pith. sign in

REVIEW 3 major objections 6 minor 42 references

CloudSat-inferred vertical structure of precipitation over the Antarctic continent

T0 review · 3 major / 6 minor · reviewed 2026-08-14 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read Antarctic precipitation is largely orographic: the new 3D CloudSat climatology shows air lifted up the ice-sheet slopes at about 0.02 m/s.

desk verdict A genuinely useful 3D Antarctic precipitation climatology whose headline 0.02 m/s vertical wind claim is a visually fitted parameter, not an independently estimated physical quantity. read the letter →

arxiv 1908.00457 v2 pith:VXB7PRIS submitted 2019-08-01 physics.ao-ph

Florentin Lemonnier , Jean-Baptiste Madeleine , Chantal Claud , Cyril Palerme , Christophe Genthon , Tristan L'Ecuyer , Norman B. Wood This is my paper · ORCID
classification physics.ao-ph
keywords CloudSatAntarcticprecipitationsnowfallverticalstructureorographicprecipitation-temperaturerelationshipicesheetmassbalancesatelliteradarpolarmeteorology
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

CloudSat's cloud-profiling radar lets scientists see, for the first time, where Antarctic snowfall forms and how it changes with height, not just how much reaches the surface. This paper builds the first continent-scale three-dimensional precipitation climatology from those measurements and uses it to argue that most Antarctic precipitation is orographic: moist air from the Southern Ocean is pushed up the ice-sheet slopes, cools, and condenses along the moist adiabat. The observations show a sharp split between the periphery, which receives about 275 mm/yr at 1200 m above ground with a ±11% seasonal swing, and the high plateau, which receives about 34 mm/yr with a ±143% swing. At every altitude, the spread of precipitation with temperature follows a simple analytical lifting curve with a vertical wind near 0.02 m/s. If this explanation is right, a climate model's three-dimensional snowfall field can be checked against one compact diagnostic rather than against scattered surface measurements.

What carries the argument

The load-bearing object is Equation 1, the saturation-forced-lifting relation $$ \mathrm{Pr}=-\frac{w}{\rho_{\mathrm{water}}}\int_z \rho_{\mathrm{atm}}\frac{L\,q_{\mathrm{sat}}(T,p)}{R_{\mathrm{vap}}$T^{2}$}\Gamma_{\mathrm{sat}}\,dz, $$ derived in Appendix B from a moisture budget by assuming steady, saturated air, zero evaporation, and purely vertical motion, so that precipitation equals the column-integrated condensation produced by lifting at vertical speed $w$. The paper overlays curves for $w=0.0001$ to $1\ \mathrm{m\,s^{-1}}$ on the observed precipitation-temperature scatter plots; the dense part of the observations tracks the $0.01\ \mathrm{m\,s^{-1}}$ curve, with the 0.02 m/s average cited in the abstract, and the deviations are attributed to steep local topography.

What would settle it

Compute a full column moisture budget over the Antarctic margin from high-resolution reanalysis or a regional model, retaining the horizontal advection terms $u\,\partial q/\partial x+v\,\partial q/\partial y$, and compare the diagnosed condensation profile to CloudSat's measured precipitation. If the full-budget condensation does not reproduce the observed precipitation-temperature scatter, or if direct wind measurements show vertical velocities far from 0.01 to 0.02 m/s over the slopes, then Equation 1 is not the controlling mechanism.

Watch

Extended reading notes

Core claim

The paper's central claim is that the vertical structure of Antarctic precipitation is governed by forced orographic lifting of near-saturated marine air over the ice-sheet margins, with an average vertical velocity of about $0.02\ \mathrm{m\,s^{-1}}$. To establish this, the authors regrid the CloudSat 2C-SNOW-PROFILE snowfall retrievals onto a $1^{\circ}\times2^{\circ}$ horizontal grid with 240 m vertical bins from roughly 1200 m to 10 km above ground, and compare the precipitation-temperature histograms at each level with an analytical relation for condensation by steady saturated ascent. The observed distributions sit between the curves for $w=0.01$ and $w=0.1\ \mathrm{m\,s^{-1}}$, close to the $0.01\ \mathrm{m\,s^{-1}}$ curve over the periphery and slightly above it over the plateau, and the paper interprets the spread at fixed temperature as the variety of slopes and horizontal wind strengths that set the local vertical wind. The same dataset yields the regional contrasts: high, weakly seasonal snowfall over the coasts and peninsula, low and rare snowfall on the plateau, and a strong dependence of ice-shelf precipitation on sea-ice coverage.

Load-bearing premise

The load-bearing premise is that horizontal moisture advection can be neglected, so the column condensation is simply $w\,\partial q_{\mathrm{sat}}/\partial z=-\mathrm{Pr}$; if horizontal transport of moisture is as important as vertical lifting over Antarctic slopes, the inferred vertical wind of 0.01 to 0.02 m/s is not a real physical wind.

Editorial extensions

If this is right

  • Climate-model evaluation can move from surface snowfall totals to three-dimensional precipitation-temperature distributions: a model that places its snowfall off the observed $w\approx0.01$ to $0.02\ \mathrm{m\,s^{-1}}$ envelope has a transport, thermodynamics, or microphysics bias.
  • The periphery/plateau contrast implies that model skill must be assessed separately for the two regimes, since on the plateau, where the seasonal swing is ±143%, a few large events dominate and mean-state comparisons over short periods can mislead.
  • Over the ice shelves, summer versus winter precipitation differences and their link to sea-ice coverage give a direct test of coupled sea-ice-atmosphere behavior in models.
  • The analytical relation turns the average Antarctic slope and horizontal wind into a predicted snowfall rate, so the paper's diagnostic can be applied without retuning.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Not pursued in the paper: a direct computation of the same precipitation-temperature scatter from a full-physics model that retains horizontal moisture advection would test whether the $w\approx0.02\ \mathrm{m\,s^{-1}}$ relation is a causal mechanism or a curve fit.
  • A testable extension would be to predict interannual snowfall from the product of near-surface wind speed and slope, $u\,dz/dx$, times saturation humidity; if the relation is causal, years with stronger onshore flow should show proportionally more peripheral precipitation.
  • Because ground clutter hides the lowest roughly 1200 m, the inferred vertical wind applies aloft; an observational follow-up using ground-based micro rain radars at coastal East Antarctic stations could show where the lifting curve breaks as sublimation and katabatic winds take over.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. The manuscript constructs the first multi-year, three-dimensional CloudSat snowfall climatology over Antarctica (2007–2010) on a 1° latitude × 2° longitude grid with 240 m vertical bins, using the 2C-SNOW-PROFILE product and co-located ECMWF-AUX temperatures. It documents strong contrasts between peripheral areas and the plateau, regional zonal structures, sea-ice influence over western ice shelves, and histograms/scatterplots of precipitation versus temperature at multiple heights. The paper then derives a saturated-lifting analytical relation (Eq. 1) and, by visual comparison of the curve family to the observed scatter, concludes that precipitation is largely controlled by topographic advection with an average vertical wind of 0.01–0.02 m/s. This mechanism claim is the stated central finding.

Significance. The three-dimensional climatology itself is a valuable community resource: it extends the existing 2D Palerme climatologies, provides vertical-profile diagnostics, and is accompanied by uncertainty estimates from ground-radar comparisons. If the 0.02 m/s result were rigorously established, it would be a compact and useful diagnostic for evaluating model precipitation processes over Antarctica. However, the mechanism claim is currently much weaker than the dataset description: the physical derivation omits horizontal advection without justification, and the agreement is assessed visually rather than quantitatively. The paper therefore needs either a substantial reanalysis-based budget analysis or a careful reframing of Eq. (1) as a conditional-mean diagnostic rather than a retrieved vertical velocity.

major comments (3)
  1. [Appendix B, Eqs. (B3)–(B5)] The reduction from the full steady-state moisture budget to w ∂q_sat/∂z = −Pr silently drops the horizontal advection terms u∂q/∂x + v∂q/∂y. The text justifies this as “assuming a purely vertical motion”, but the proposed mechanism is topographic lifting of air that is advected horizontally; if u = v = 0 there is no horizontal airflow to be deflected upslope, so the reduced equation is not the limit described. Along the Antarctic coastal margin, synoptic systems and cold-air outbreaks produce strong horizontal moisture gradients, and u·∇q can plausibly be comparable to w∂q_sat/∂z. Without a scale analysis or a quantitative evaluation using collocated reanalysis winds and moisture, Eq. (1) is not demonstrated to be the governing relation for the observed precipitation–temperature distributions. This is the load-bearing step for the abstract’s 0.02 m/s claim, and it needs either a defended derivation (for example, in terrain-following coordinates with an explicit slope term) or an explicit statement that Eq. (1) is a heuristic diagnostic rather than a retrieved physical vertical velocity.
  2. [Section 4.2, Figs. 10–11] There is no quantitative measure of agreement between the observed scatter and the analytical curves. The manuscript states that the distribution “follows” or “evolves just over the line with triangle markers” (w = 0.01–0.02 m/s), but no skill score, correlation, likelihood, regression, or residual statistics are reported. Because Eq. (1) is integrated using the CloudSat-observed column temperatures, the fitted w absorbs all retrieval biases, unrepresented microphysical processes, and the neglected advection and pressure terms. The circularity also matters: a multi-curve family is drawn and w is selected by eye so that the curves align with the data, and the same w is then reported as the average vertical wind. I ask the authors to add a formal fit with uncertainty (for example, maximum-likelihood estimation of w per region and height with confidence intervals), or to reposition Eq. (1) as a purely descriptive scaling relation and remove the physical 0.02 m/s wording from the abstract.
  3. [Section 4.2, Eq. (1) and the 0.2 m/s threshold] The plausibility estimate w = u dz/dx uses a representative u = 5 m/s and a zonally averaged slope; this is not an observational determination of w, and dz/dx should be evaluated along the actual air trajectory rather than on the zonal-mean cross-section. The text also introduces a 0.2 m/s exceedance threshold without stating how it was chosen or what uncertainty it carries; Fig. 12 then uses it to classify extreme events. Finally, Eq. (B8) computes ∂q_sat/∂z from the Clausius–Clapeyron relation at constant pressure while the integral in Eq. (B9) is taken over a finite depth with varying pressure and temperature; the pressure dependence of q_sat is not accounted for. Please state the additional approximations explicitly and provide a sensitivity test of Eq. (1) to the pressure term. These issues do not affect the climatological maps, but they directly affect the magnitude of the inferred w.
minor comments (6)
  1. [Appendix B heading] The heading “demonstation” should be “demonstration”.
  2. [Figure 4 caption] In the caption of Fig. 4, “Antartic plateau” should be “Antarctic plateau”.
  3. [Table A2, 2160 m row] The 2160 m row lists the temperature interval as “-17.1429 – -36.8571”, the reverse order of the other rows; correct it for readability.
  4. [Abstract and Section 3.1] The abstract and Section 3.1 use “relative seasonal variation” of ±11% and ±143%; please define this statistic explicitly (for example, half of the annual range divided by the annual mean).
  5. [Eq. (1) and Section 4.2] The lower limit of the integral in Eq. (1) is not specified, and the text states that Γ_sat is the moist adiabatic lapse rate while using a constant value of −6.5 K/km; clarify the integration bounds and note the constant-lapse-rate approximation.
  6. [Figures 10–11 captions] The white contours labelled “σ standard deviation of the distributions” are not defined; state whether σ is computed on precipitation rate, on log precipitation, or on observation counts.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: Eq. 1 is an independent analytical curve family, and the 0.01-0.02 m/s vertical wind is inferred from CloudSat/ECMWF data, not forced by construction.

full rationale

The paper's central mechanism claim is that observed precipitation-temperature distributions follow an analytical orographic-lifting relationship with vertical wind w near 0.01-0.02 m/s. This is not circular. Equation 1 is derived in Appendix B from the moisture budget (Eqs. B3-B9) under explicit assumptions: steady state, saturation, no evaporation, and purely vertical motion. The compared observations are CloudSat 2C-SNOW-PROFILE precipitation rates and ECMWF-AUX temperatures, both independent of Eq. 1. The w values are trial parameters of the analytical family, and the paper's identification of the triangle-marker (0.01 m/s) or slightly-above-triangle (about 0.02 m/s) curve is an inverse inference from the data, not a quantity defined by the data in a way that guarantees agreement. The main vulnerability is the reduction from Eq. B4 to Eq. B5, which drops u dq/dx + v dq/dy without a quantitative scale analysis; if horizontal advection is comparable to vertical advection in coastal Antarctica, the inferred w may not be a physically meaningful vertical wind. That is a modeling-assumption and correctness risk, not a circularity: the paper does not use Eq. 1 to generate the data it claims to explain. Self-citations to Palerme et al. (2014, 2019) and Lemonnier et al. (2019) concern data provenance, retrieval validation, and uncertainty estimates for an externally available CloudSat product; none is used as a uniqueness theorem, a forbidden alternative, or an ansatz that smuggles in the orographic conclusion. No step in the derivation reduces by construction to its own inputs, so the circularity score is 0.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

The central climatological claims rest on standard remote sensing assumptions and retrieval products. The mechanism claim rests on the saturated-parcel, purely vertical moisture budget and on the implicitly fitted vertical wind w. No new physical entities are introduced.

free parameters (2)
  • vertical wind speed w = ~0.01-0.02 m.s-1 (by visual match to observed precipitation-temperature distributions)
    Equation 1 is evaluated for w = 0.0001, 0.001, 0.01, 0.1, 1 m/s (Fig. 10); the paper states the observed distributions follow the 0.01 m/s curve and the abstract cites an average vertical wind of 0.02 m/s, but no formal fitting or uncertainty is provided.
  • 0.2 m.s-1 exceedance threshold = 0.2 m.s-1
    Threshold used in Fig. 12 to identify extreme precipitation records; chosen by the authors rather than derived.
assumptions (5)
  • domain assumption Air parcels advected over Antarctica are at saturation (q = q_sat) with no evaporation (Ev = 0)
    Introduced in Appendix B before Eq. B4; if violated, the condensation rate is not equal to the moisture convergence.
  • domain assumption The moisture budget can be reduced to a purely vertical advection term, dropping u*dq/dx + v*dq/dy (Eq. B3 to B5)
    This eliminates the horizontal transport that actually produces orographic precipitation; it is the load-bearing simplification of the analytical relationship.
  • standard math Steady state (dq/dt = 0)
    Used in Appendix B; appropriate for climatological means.
  • domain assumption The vertical temperature profile is moist adiabatic with Gamma_sat = -6.5 K/km
    Stated in Appendix B; Antarctic soundings are often more stable, so the lapse rate may be an approximation.
  • domain assumption CloudSat retrievals at 1200 m a.g.l. and above are representative of the precipitation profile, with ground clutter not biasing the climatological means
    The first four bins are excluded (Section 2); the authors test the effect of low-rate truncation at 1440 m but not the full clutter bias at 1200 m.

how reviews work

0 comments
Cite this review

Pith. "Pith review of CloudSat-inferred vertical structure of precipitation over the Antarctic continent." pith.science (2026). https://pith.science/paper/VXB7PRIS

@misc{pith2026190800457,
  author       = {Pith},
  title        = {Pith review of: CloudSat-inferred vertical structure of precipitation over the Antarctic continent},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/VXB7PRIS}},
  note         = {Machine review of arXiv:1908.00457}
}
read the original abstract

Current global warming is causing significant changes in snowfall in polar regions, directly impacting the mass balance of the ice caps. The only water supply in Antarctica, precipitation, is poorly estimated from surface measurements. The onboard cloud-profiling radar of the CloudSat satellite provided the first real opportunity to estimate precipitation at continental scale. Based on CloudSat observations, we propose to explore the vertical structure of precipitation in Antarctica over the 2007-2010 period. A first division of this dataset following a topographical approach (continent versus peripheral regions, with a 2250m topographical criterion) shows a high precipitation rate (275mm/yr at 1200meters above ground level) with low relative seasonal variation (+/-11%) over the peripheral areas. Over the plateau, the precipitation rate is low (34mm/yr at 1200m.a.g.l.) with a much larger relative seasonal variation (+/-143%). A second study that follows a geographical division highlights the average vertical structure of precipitation and temperature depending on the regions and their interactions with topography. In particular, over ice-shelves, we see a strong dependence of the distribution of precipitation on the sea-ice coverage. Finally, the relationship between precipitation and temperature is analyzed and compared with a simple analytical relationship. This study highlights that precipitation is largely dependent on the advection of air masses along the topographic slopes with an average vertical wind of 0.02m/s. This provides new diagnostics to evaluate climate models with a three-dimensional approach of the atmospheric structure of precipitation.

Figures

Figures reproduced from arXiv: 1908.00457 by the authors.

Figure 1
Figure 1. Mean annual snowfall rate (mm water equivalent / year – mm.yr−1 ) from the 2C￾SNOW-PROFILE product over the 2007–2010 period a) at 1200 m.a.g.l. (5th bin); b) at 2160 m.a.g.l. (8th bin); c) at 3120 m.a.g.l. (12th bin) and d) at 5040 m.a.g.l. (20th bin). Genthon et al., 2009). This figure corresponds to the 5th CloudSat vertical bin at about 1200 m.a.g.l. Over the Antarctic continent and especially over peripheral ar… view at source ↗
Figure 2
Figure 2. Digital Elevation Map of the Antarctic Ice Sheet (Liu et al., 2015) with four frames corresponding to the four studied areas. A in magenta is the East Antarctic continent; B in red is the West Antarctic, which has been subdivided into continental region (B.1) and ice-shelves (B.2); C in green is the Peninsula. Thin black solid line is the iso-altitude 2250 m and separates the coastal areas from the plateau [PITH_FU… view at source ↗
Figure 3
Figure 3. Seasonal variability of snowfall north of 82◦ during the period 2007-2010 for Cloud￾Sat in mm/yr at about 1200 m.a.g.l. over the entire continent in red, over the peripheral areas in green and over the high continental plateau in blue. Errorbars represent uncertainties as calcu￾lated by Lemonnier et al. (2019) and extrapolated to the entire continent. profile is averaged over the 2007–2010 period, then area-averaged… view at source ↗
Figures from the paper (13 more)
Figure 4
Figure 4. Figure 4: a) Averaged vertical profiles of precipitation over the 2007-2010 period of CloudSat observations in solid lines, filled areas are corresponding to the temporal σ standard deviations (1) over the entire continent in red. (2) over the plateau in blue. (3) over the perip…
Figure 5
Figure 5. Figure 5: a represents precipitation structure over East Antarctica, the most homo [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 5
Figure 5. Figure 5: First column presents the zonal averaged precipitation rate (shaded colors) and its corresponding atmospheric temperature (contours) of each region, as follows : a) for East con￾tinent (A in fig.2), c) for West continent (B.1 in fig.2), e) for West ice-shelves (B.2 in …
Figure 6
Figure 6. Figure 6: Zonal mean precipitation and its corresponding atmospheric temperature (con￾tours) of the west Antarctic ice-shelves during the averaged summer and winter. The average period are a) December-January-February and b) June-July-August over the 2007-2010 period. The zonal …
Figure 8
Figure 8. Figure 8: a summarizes the precipitation structure over the entire continent. It clearly [PITH_FULL_IMAGE:figures/full_fig_p011_8.png]
Figure 7
Figure 7. Figure 7: Averaged annual precipitation and temperature over the 2007–2010 period at 1200 m above ground level. The grid resolution is 0.1◦ in longitude by 0.1◦ in latitude. Precipita￾tion is obtained from the 2C-SNOW-PROFILE product presented in section 2 and temperature is obt…
Figure 8
Figure 8. Figure 8: a) Latitudinally average of the precipitation structure and its corresponding atmo￾spheric temperature (contours) for the entire continent. b) First CloudSat level of precipitation along the latitude (in blue) with its σ-spatial variation, and associated temperature (i…
Figure 9
Figure 9. Figure 9: Histogram plots of snowfall rates in mm.hr−1 and vertical evolutions (a) for the peripheral areas (<2250 m) and b) for the plateau (>2250 m) at different altitudes above ground level. Black dashed lines are passing through maxima of each vertical bin distribution. We o…
Figure 10
Figure 10. Figure 10: First column presents scatter plots of precipitation in mm/hr and temperature in ◦C at different altitudes over the peripheral areas. Second column presents the same results over plateau area. The dashed black lines are the assumptions of theoretical precipitation rat…
Figure 11
Figure 11. Figure 11: a) Scatter plots of precipitation in mm.hr−1 and temperature in ◦C at all alti￾tudes over the peripheral areas. a) Same result over plateau area. The dashed black lines are the assumptions of theoretical precipitation rates calculated using equation 1 for vertical win…
Figure 12
Figure 12. Figure 12: Observations on the plateau and coasts that exceed the resulting analytical rela￾tionship with a wind speed of 0.2 m.s−1 (red scattered points). The dashed black line represents the analytical relationship with a vertical speed of 0.2 m.s−1 . There are 1251 records sh…
Figure 13
Figure 13. Figure 13: High resolution (200 m) topographic map (Greene et al., 2017; Howat et al., 2019) over Terre Ad´elie, Ellsworth Land, the peninsula and Dronning Maud Land. The red points cor￾respond to the measurements greater than the 0.2 m.s−1 vertical velocity precipitation hypoth…
Figure 14
Figure 14. Figure 14: Scatter plots of precipitation in mm.hr−1 and temperature in ◦C at all altitudes over the Antarctic continent. The colorbar indicates the relative number of observations for a given precipitation rate and temperature. The dashed black lines are the assumptions of theo…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

42 extracted references · 41 canonical work pages

  1. [1]

    apacite url apacite =6pt Acknowledgments. 6pt 1sp \@dates Received \@recvdate\@empty\@rcvaccrule \@recvdate \@revisedate\@empty ; revised \@revisedate; \@accptdate\@empty \@revisedate\@empty; accepted \@accptdate \@pubdate\@empty. ; published \@pubdate. -2pt \@authaddrs @list\@empty =.15in @list 1sp @list =9pt plus 2pt minus 6pt \@sluginfo width 4pc =3000...

    2001

  2. [2]

    Global climate modeling of Saturn's atmosphere. Part II: multi-annual high-resolution dynamical simulations

    \@ifstar \@figbox \@figbox \@figbox#1#2#3 to !#1! #3 [#1][c] !#2!#3 \@tempdima#2 \@tempdima by2 \@tempdima by- \@tempdima by- \@height\@tempdima\@depth\@tempdima\@width @ to @ #3 Bib ??? ??? ??? =0 =0 = @figure=0 @table=0 #1 --#1 -24pt -2ex #1 0= #1 to 0 #1 I NDEX T ERMS: #1 #1 Citation: #1 Feb 9, 2009 Changed name and references to name from agu2001 to a...

    work page Pith review arXiv 2009

  3. [3]

    APACrefauthors \ 1988

    bromwich1988snowfall APACrefauthors Bromwich, D H. APACrefauthors \ 1988 . Snowfall in high southern latitudes Snowfall in high southern latitudes . Reviews of Geophysics 26 1 149--168

    work page 1988

  4. [4]

    \ Parish, T R

    bromwich1998meteorology APACrefauthors Bromwich, D H. \ Parish, T R. APACrefauthors \ 1998 . Meteorology of the Antarctic Meteorology of the antarctic . Meteorology of the Southern Hemisphere Meteorology of the southern hemisphere \ ( \ 175--200). Springer

    work page 1998

  5. [5]

    , Clark, P U

    church2013sea APACrefauthors Church, J A. , Clark, P U. , Cazenave, A. , Gregory, J M. , Jevrejeva, S. , Levermann, A. others APACrefauthors \ 2013 . Sea-level rise by 2100 Sea-level rise by 2100 . Science 342 6165 1445--1445

    work page 2013

  6. [6]

    , Boudevillain, B

    duranalarcon2018VPR APACrefauthors Dur\'an-Alarc\'on, C. , Boudevillain, B. , Genthon, C. , Grazioli, J. , Souverijns, N. , van Lipzig, N P M. Berne, A. APACrefauthors \ 2019 . The vertical structure of precipitation at two stations in East Antarctica derived from micro rain radars The vertical structure of precipitation at two stations in east antarctica...

    work page 2019

  7. [7]

    , Knight, C A

    dye1974mechanism APACrefauthors Dye, J E. , Knight, C A. , Toutenhoofd, V. \ Cannon, T W. APACrefauthors \ 1974 . The mechanism of precipitation formation in northeastern Colorado cumulus III. Coordinated microphysical and radar observations and summary The mechanism of precipitation formation in northeastern colorado cumulus iii. coordinated microphysica...

    work page 1974

  8. [8]

    , Frezzotti, M

    eisen2008ground APACrefauthors Eisen, O. , Frezzotti, M. , Genthon, C. , Isaksson, E. , Magand, O. , van den Broeke, M R. others APACrefauthors \ 2008 . Ground-based measurements of spatial and temporal variability of snow accumulation in East Antarctica Ground-based measurements of spatial and temporal variability of snow accumulation in east antarctica ...

    work page 2008

Show all 42 references
  1. [9]

    , Volken, E

    findeisen2015colloidal APACrefauthors Findeisen, W. , Volken, E. , Giesche, A M. \ Br \"o nnimann, S. APACrefauthors \ 2015 . Colloidal meteorological processes in the formation of precipitation Colloidal meteorological processes in the formation of precipitation . Meteorologi...

    2015

  2. [10]

    \ Abe, O

    fujita2006stable APACrefauthors Fujita, K. \ Abe, O. APACrefauthors \ 2006 . Stable isotopes in daily precipitation at Dome Fuji, East Antarctica Stable isotopes in daily precipitation at dome fuji, east antarctica . Geophysical research letters 33 18

    2006

  3. [11]

    , Krinner, G

    genthon2009antarctic APACrefauthors Genthon, C. , Krinner, G. \ Castebrunet, H. APACrefauthors \ 2009 . Antarctic precipitation and climate-change predictions: horizontal resolution and margin vs plateau issues Antarctic precipitation and climate-change predictions: horizontal...

    2009

  4. [12]

    , Tsukernik, M

    gorodetskaya2014role APACrefauthors Gorodetskaya, I V. , Tsukernik, M. , Claes, K. , Ralph, M F. , Neff, W D. \ Van Lipzig, N P. APACrefauthors \ 2014 . The role of atmospheric rivers in anomalous snow accumulation in East Antarctica The role of atmospheric rivers in anomalous...

    2014

  5. [13]

    , Genthon, C

    grazioli2017measurements APACrefauthors Grazioli, J. , Genthon, C. , Boudevillain, B. , Duran-Alarcon, C. , Del Guasta, M. , Jean-Baptiste, M. \ Berne, A. APACrefauthors \ 2017 . Measurements of precipitation in Dumont d'Urville, Ad \'e lie Land, East Antarctica Measurements o...

    2017

  6. [14]

    , Madeleine, J B

    grazioli2017katabatic APACrefauthors Grazioli, J. , Madeleine, J B. , Gall \'e e, H. , Forbes, R M. , Genthon, C. , Krinner, G. \ Berne, A. APACrefauthors \ 2017 . Katabatic winds diminish precipitation contribution to the Antarctic ice mass balance Katabatic winds diminish pr...

    2017

  7. [15]

    , Gwyther, D E

    greene2017antarctic APACrefauthors Greene, C A. , Gwyther, D E. \ Blankenship, D D. APACrefauthors \ 2017 . Antarctic mapping tools for MATLAB Antarctic mapping tools for matlab . Computers & Geosciences 104 151--157

    2017

  8. [16]

    , Porter, C

    howat2019reference APACrefauthors Howat, I M. , Porter, C. , Smith, B E. , Noh, M J. \ Morin, P. APACrefauthors \ 2019 . The Reference Elevation Model of Antarctica The reference elevation model of antarctica . The Cryosphere 13 2 665--674

    2019

  9. [17]

    \ Turner, J

    king2007antarctic APACrefauthors King, J C. \ Turner, J. APACrefauthors \ 2007 . Antarctic meteorology and climatology Antarctic meteorology and climatology . Cambridge University Press

    2007

  10. [18]

    , Tripoli, G J

    knuth2010influence APACrefauthors Knuth, S L. , Tripoli, G J. , Thom, J E. \ Weidner, G A. APACrefauthors \ 2010 . The influence of blowing snow and precipitation on snow depth change across the Ross Ice Shelf and Ross Sea regions of Antarctica The influence of blowing snow an...

    2010

  11. [19]

    , Milani, L

    kulie2016shallow APACrefauthors Kulie, M S. , Milani, L. , Wood, N B. , Tushaus, S A. , Bennartz, R. \ L’Ecuyer, T S. APACrefauthors \ 2016 . A shallow cumuliform snowfall census using spaceborne radar A shallow cumuliform snowfall census using spaceborne radar . Journal of Hy...

    2016

  12. [20]

    , Ladkin, R

    lachlan2001observations APACrefauthors Lachlan-Cope, T. , Ladkin, R. , Turner, J. \ Davison, P. APACrefauthors \ 2001 . Observations of cloud and precipitation particles on the Avery Plateau, Antarctic Peninsula Observations of cloud and precipitation particles on the avery pl...

    2001

  13. [21]

    , Baker, B A

    lawson2006microphysical APACrefauthors Lawson, R P. , Baker, B A. , Zmarzly, P. , O’Connor, D. , Mo, Q. , Gayet, J F. \ Shcherbakov, V. APACrefauthors \ 2006 . Microphysical and optical properties of atmospheric ice crystals at South Pole Station Microphysical and optical prop...

    2006

  14. [22]

    , Madeleine, J

    lemonnier2018evaluation APACrefauthors Lemonnier, F. , Madeleine, J. , Claud, C. , Genthon, C. , Dur \'a n-Alarc \'o n, C. , Palerme, C. others APACrefauthors \ 2019 . Evaluation of CloudSat snowfall rate profiles by a comparison with in-situ micro rain radars observations in ...

    2019 doi

  15. [23]

    , Fyke, J

    lenaerts2018signature APACrefauthors Lenaerts, J T. , Fyke, J. \ Medley, B. APACrefauthors \ 2018 . The signature of ozone depletion in recent Antarctic precipitation change: A study with the Community Earth System Model The signature of ozone depletion in recent antarctic pre...

    2018

  16. [24]

    , Zipser, E J

    liu2008cloud APACrefauthors Liu, C. , Zipser, E J. , Cecil, D J. , Nesbitt, S W. \ Sherwood, S. APACrefauthors \ 2008 . A cloud and precipitation feature database from nine years of TRMM observations A cloud and precipitation feature database from nine years of trmm observatio...

    2008

  17. [25]

    , Burgard, C

    maahn2014 APACrefauthors Maahn, M. , Burgard, C. , Crewell, S. , Gorodetskaya, I V. , Kneifel, S. , Lhermitte, S. van Lipzig, N P. APACrefauthors \ 2014 . How does the spaceborne radar blind zone affect derived surface snowfall statistics in polar regions? How does the spacebo...

    2014

  18. [26]

    , Kulie, M S

    milani2018cloudsat APACrefauthors Milani, L. , Kulie, M S. , Casella, D. , Dietrich, S. , L’Ecuyer, T S. , Panegrossi, G. Wood, N B. APACrefauthors \ 2018 . CloudSat snowfall estimates over Antarctica and the Southern Ocean: An assessment of independent retrieval methodologies...

    2018

  19. [27]

    \ Bromwich, D H

    nicolas2011climate APACrefauthors Nicolas, J P. \ Bromwich, D H. APACrefauthors \ 2011 . Climate of West Antarctica and influence of marine air intrusions Climate of west antarctica and influence of marine air intrusions . Journal of Climate 24 1 49--67

    2011

  20. [28]

    , Claud, C

    palerme2018groundclutter APACrefauthors Palerme, C. , Claud, C. , Wood, N. , L'Ecuyer, T. \ Genthon, C. APACrefauthors \ 2019 . How does ground clutter affect CloudSat snowfall retrievals over ice sheets? How does ground clutter affect cloudsat snowfall retrievals over ice she...

    2019

  21. [29]

    , Genthon, C

    palerme2017evaluation APACrefauthors Palerme, C. , Genthon, C. , Claud, C. , Kay, J E. , Wood, N B. \ L Ecuyer, T. APACrefauthors \ 2017 . Evaluation of current and projected Antarctic precipitation in CMIP5 models Evaluation of current and projected antarctic precipitation in...

    2017

  22. [30]

    , Kay, J

    palerme2014much APACrefauthors Palerme, C. , Kay, J. , Genthon, C. , L'Ecuyer, T. , Wood, N. \ Claud, C. APACrefauthors \ 2014 . How much snow falls on the Antarctic ice sheet? How much snow falls on the antarctic ice sheet? The Cryosphere 8 4 1577--1587

    2014

  23. [31]

    , Ligtenberg, S

    pritchard2012antarctic APACrefauthors Pritchard, H. , Ligtenberg, S. , Fricker, H. , Vaughan, D. , Van den Broeke, M. \ Padman, L. APACrefauthors \ 2012 . Antarctic ice-sheet loss driven by basal melting of ice shelves Antarctic ice-sheet loss driven by basal melting of ice sh...

    2012

  24. [32]

    , Mouginot, J

    rignot2019four APACrefauthors Rignot, E. , Mouginot, J. , Scheuchl, B. , van den Broeke, M. , van Wessem, M J. \ Morlighem, M. APACrefauthors \ 2019 . Four decades of Antarctic Ice Sheet mass balance from 1979--2017 Four decades of antarctic ice sheet mass balance from 1979--2...

    2019

  25. [33]

    APACrefauthors \ 2000

    rodgers2000inverse APACrefauthors Rodgers, C D. APACrefauthors \ 2000 . Inverse methods for atmospheric sounding: theory and practice Inverse methods for atmospheric sounding: theory and practice \ ( 2). World scientific

    2000

  26. [34]

    , Lindsay, R W

    schweiger2008relationships APACrefauthors Schweiger, A J. , Lindsay, R W. , Vavrus, S. \ Francis, J A. APACrefauthors \ 2008 . Relationships between Arctic sea ice and clouds during autumn Relationships between arctic sea ice and clouds during autumn . Journal of Climate 21 18...

    2008

  27. [35]

    , Ivins, E

    shepherd2018mass APACrefauthors Shepherd, A. , Ivins, E. , Rignot, E. , Smith, B. , Van Den Broeke, M. , Velicogna, I. others APACrefauthors \ 2018 . Mass balance of the Antarctic Ice Sheet from 1992 to 2017 Mass balance of the antarctic ice sheet from 1992 to 2017 . Nature 55...

    2018

  28. [36]

    , Ivins, E R

    shepherd2012reconciled APACrefauthors Shepherd, A. , Ivins, E R. , Geruo, A. , Barletta, V R. , Bentley, M J. , Bettadpur, S. others APACrefauthors \ 2012 . A reconciled estimate of ice-sheet mass balance A reconciled estimate of ice-sheet mass balance . Science 338 6111 1183--1189

    2012

  29. [37]

    , Gossart, A

    souverijns2018cloudsatgrid APACrefauthors Souverijns, N. , Gossart, A. , Lhermitte, S. , Gorodetskaya, I V. , Grazioli, J. , Berne, A. van Lipzig, N P M. APACrefauthors \ 2018 . Evaluation of the CloudSat surface snowfall product over Antarctica using ground-based precipitatio...

    2018

  30. [38]

    \ Ellis, T D

    stephens2008controls APACrefauthors Stephens, G L. \ Ellis, T D. APACrefauthors \ 2008 . Controls of global-mean precipitation increases in global warming GCM experiments Controls of global-mean precipitation increases in global warming gcm experiments . Journal of Climate 21 ...

    2008

  31. [39]

    , Phillips, T

    turner2019dominant APACrefauthors Turner, J. , Phillips, T. , Thamban, M. , Rahaman, W. , Marshall, G J. , Wille, J D. others APACrefauthors \ 2019 . The Dominant Role of Extreme Precipitation Events in Antarctic Snowfall Variability The dominant role of extreme precipitation ...

    2019

  32. [40]

    , Van den Broeke, M

    van2007heat APACrefauthors Van de Berg, W. , Van den Broeke, M. \ Van Meijgaard, E. APACrefauthors \ 2007 . Heat budget of the East Antarctic lower atmosphere derived from a regional atmospheric climate model Heat budget of the east antarctic lower atmosphere derived from a re...

    2007

  33. [41]

    APACrefauthors \ 2011

    wood2011estimation APACrefauthors Wood, N B. APACrefauthors \ 2011 . Estimation of snow microphysical properties with application to millimeter-wavelength radar retrievals for snowfall rate (PhD thesis) Estimation of snow microphysical properties with application to millimeter...

    2011

  34. [42]

    , L'Ecuyer, T S

    wood2014estimating APACrefauthors Wood, N B. , L'Ecuyer, T S. , Heymsfield, A J. , Stephens, G L. , Hudak, D R. \ Rodriguez, P. APACrefauthors \ 2014 . Estimating snow microphysical properties using collocated multisensor observations Estimating snow microphysical properties u...

    2014

Pith tools

Reviewed August 14, 2026 · model on record in the stance chip above.