LoRA Adaptation Strength in Aurora-WRF: Trade-offs in Regional Heavy-Rainfall Forecasting

Boyan Liu; Xiaoyuan Zhang

physics.ao-phSep 24, 2026

LoRA Adaptation Strength in Aurora-WRF: Trade-offs in Regional Heavy-Rainfall Forecasting

Authors: Boyan Liu, Xiaoyuan Zhang

Organizations: Zhongguancun Academy, Beijing, China

Abstract

We investigate how parameter-efficient adaptation of an atmospheric foundation model affects downstream regional precipitation in a controlled Aurora-WRF coupling experiment over the Beijing-Tianjin-Hebei region. A single-step, precipitation-weighted LoRA adaptation of AuroraPretrained is trained on May-September 2020-2021 and selected using 2022 validation data. Five inference-time adaptation strengths are coupled to an unchanged 9-km WRF configuration and compared with a GFS-driven control under common ERA5 initialization and auxiliary-field rules. Evaluation uses 17 initializations in 2023, hourly ERA5 precipitation, and conservative remapping to a fixed 356-cell, 0.25-degree verification grid. Heavy rainfall is defined exclusively as at least 50 mm in a continuous 24-hour window, advanced hourly. For window starts from 0 to 48 hours, unadapted Aurora attains the highest mean critical success index (CSI), 0.216, compared with 0.144 for the GFS control. An intermediate LoRA strength of 0.75 reduces the Aurora-driven 24-hour precipitation mean squared error by 30.7% and brings pooled frequency Bias from 1.510 to 1.024, but lowers CSI to 0.182. GFS retains the lowest whole-domain error. These results characterize a trade-off between rainfall detection, frequency calibration, and intensity error, showing the importance of evaluating adaptation strength against multiple downstream criteria within a common coupling framework.

Figures & tables

Field	Source and treatment
Soil temperature/moisture, skin temperature, SST, sea ice, snow	ERA5 at the start of the adjustment period; prescribed auxiliary fields persist. The land-surface model evolves its internal state; SST updating is disabled.
Surface pressure $p_{s}$	After $t_{0}$ , $\widehat{p}_{s}(t)=[p_{s}(t_{0})/p_{\rm msl}(t_{0})]\widehat{p}_{\rm msl}(t)$ .
2-m specific humidity $q_{2}$	Derived from ERA5 dew point and pressure at $t_{0}$ ; scaled subsequently by forecast lowest-level specific humidity relative to its initial value and capped at saturation.
Cloud liquid and ice	ERA5 cloud fields only at initialization; subsequent prescribed cloud boundary mixing ratios are zero.
Static fields	Common land–sea mask, orography, soil categories, and WPS geography.

Table 1: Shared auxiliary-field rules. Initialization fields are not future observations.

Driver	CSI	Bias	POD	FAR	MAE (mm)	MSE (mm 2 )
GFS	0.144	0.896	0.218	0.757	5.17	167.88
$\alpha=0$	0.216	1.510	0.405	0.732	7.16	302.20
$\alpha=0.25$	0.202	1.326	0.332	0.749	6.81	296.94
$\alpha=0.50$	0.192	1.131	0.305	0.730	6.40	233.14
$\alpha=0.75$	0.182	1.024	0.286	0.720	6.47	209.57
$\alpha=1$	0.180	1.649	0.327	0.802	7.01	274.73

Table 2: Main 17-initialization results, 24-hour window starts 0–48 h. Each CSI averages 49 pooled window scores. MAE and MSE use all verification cells.

Figure 1: Pooled main-scope performance for all six drivers. Bars deliberately show the established aggregate estimators without attaching case-level standard deviations to a different estimator. Case dispersion is reported separately in Table 3 and Figure 3 .

Figure 2: Skill and errors versus forecast lead. Solid curves retain the pooled CSI/Bias and mean MSE estimators. Shading and its dotted boundaries show

\pm 1

bootstrap SD for CSI/Bias and

\pm 1

case SD for MSE; these are not confidence bands. Negative lower bounds reflect the symmetric SD construction, not negative scores. For the first three panels, lead is the 24-hour window start : 0 denotes 0–24 h and 48 denotes 48–72 h. Hourly MSE uses interval ends 1–72 h, with no fabricated hour-zero error.

Driver	Case CSI	Case Bias	MSE 24 (mm 2 )	MSE 1 (mm 2 )
GFS	$0.037\pm 0.056$ (10)	$1.173\pm 1.343$ (9)	$167.88\pm 262.22$ (17)	$1.45\pm 2.01$ (17)
$\alpha=0$	$0.037\pm 0.082$ (12)	$2.523\pm 4.393$ (9)	$302.20\pm 541.73$ (17)	$2.30\pm 3.63$ (17)
$\alpha=0.25$	$0.025\pm 0.075$ (12)	$2.486\pm 5.496$ (9)	$296.94\pm 626.85$ (17)	$1.97\pm 4.02$ (17)
$\alpha=0.50$	$0.026\pm 0.077$ (10)	$5.786\pm 15.880$ (9)	$233.14\pm 376.13$ (17)	$1.53\pm 2.92$ (17)
$\alpha=0.75$	$0.025\pm 0.076$ (10)	$5.780\pm 15.427$ (9)	$209.57\pm 273.28$ (17)	$1.56\pm 2.43$ (17)
$\alpha=1$	$0.025\pm 0.079$ (11)	$19.949\pm 56.790$ (9)	$274.73\pm 390.98$ (17)	$2.00\pm 3.00$ (17)

Table 3: Initialization-level mean

\pm

sample SD; parentheses give valid initialization counts. CSI and Bias here are case statistics , not the headline pooled estimators. MSE 24 averages the 49 windows; MSE 1 averages hours 1–72.

Figure 3: Initialization-level distributions over the 17 starts. Boxes show quartiles and medians; whiskers extend to observations within 1.5 interquartile ranges. CSI and full-range Bias use symmetric-log axes (base 10, linear scale 1), linear from zero to 0.01 and 1, respectively, and logarithmic above these thresholds. Zeros and all extremes are retained; box statistics use untransformed values. Both Bias panels show the same nine defined cases per driver. The 0–6 detail remains linear; triangles mark values above its range. The dotted line is Bias=1. Counts denote valid cases, not independent events.

Appendix figures & tables5 assets

Supplementary material from the paper’s appendix.

Appendix

Date	Event cell-windows	Max event cells/window	Max 24 h (mm)
2023-05-07	0	0	0.23
2023-05-15	6	1	51.00
2023-05-21	0	0	2.01
2023-06-03	0	0	1.12
2023-06-14	0	0	1.36
2023-06-26	0	0	47.92

Appendix

Table 4: The 17 evaluation initializations (00 UTC, 2023). Reference statistics use the fixed 356-cell mask and 49 rolling 24-hour windows starting at 0–48 h. Event counts use the 50-mm threshold and include overlapping windows; zero denotes no threshold exceedance, not necessarily no rain.

Driver	Mean CSI	$n$	Pooled Bias	24 h MSE (mm 2 )
GFS	0.101	70	0.996	128.57
$\alpha=0$	0.145	73	1.704	240.74
$\alpha=0.25$	0.136	73	1.672	260.23
$\alpha=0.50$	0.129	73	1.498	205.56
$\alpha=0.75$	0.122	73	1.284	181.77
$\alpha=1$	0.121	73	2.201	257.70

Appendix

Table 5: Supplementary starts 0–72 h, requiring rain forecasts through 96 h.

n

counts defined pooled CSI windows out of 73. Bias retains all false alarms, including in windows without reference events.

Figure 4: 20 July 2023 initialization, accumulation from +25 to +49 h. The window is chosen from reference precipitation only. Fields are conservatively mapped to the verification grid; red contours mark 50 mm. The same discrete color scale is used for all drivers and all three map figures.

Figure 5: 30 July 2023 initialization, accumulation from +0 to +24 h, selected by the same reference-only rule. Fields use the common verification grid, color scale, and 50-mm contour convention.

Figure 6: 10 August 2023 initialization, accumulation from +30 to +54 h, selected by the same reference-only rule. All six drivers are displayed on the common verification grid and color scale.

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